Extracting the sovereigns’ CDS market hierarchy: A correlation-filtering approach

NASA Astrophysics Data System (ADS)

León, Carlos; Leiton, Karen; Pérez, Jhonatan

2014-12-01

This paper employs correlation-into-distance mapping techniques and a minimal spanning tree-based correlation-filtering methodology on 36 sovereign CDS spread time-series in order to identify the sovereigns’ informational hierarchy. The resulting hierarchy (i) concurs with sovereigns’ eigenvector centrality; (ii) confirms the importance of geographical and credit rating clustering; (iii) identifies Russia, Turkey and Brazil as regional benchmarks; (iv) reveals the idiosyncratic nature of Japan and United States; (v) confirms that a small set of common factors affects the system; (vi) suggests that lower-medium grade rated sovereigns are the most influential, but also the most prone to contagion; and (vii) suggests the existence of a “Latin American common factor”.

Social structure of a semi-free ranging group of mandrills (Mandrillus sphinx): a social network analysis.

PubMed

Bret, Céline; Sueur, Cédric; Ngoubangoye, Barthélémy; Verrier, Delphine; Deneubourg, Jean-Louis; Petit, Odile

2013-01-01

The difficulty involved in following mandrills in the wild means that very little is known about social structure in this species. Most studies initially considered mandrill groups to be an aggregation of one-male/multifemale units, with males occupying central positions in a structure similar to those observed in the majority of baboon species. However, a recent study hypothesized that mandrills form stable groups with only two or three permanent males, and that females occupy more central positions than males within these groups. We used social network analysis methods to examine how a semi-free ranging group of 19 mandrills is structured. We recorded all dyads of individuals that were in contact as a measure of association. The betweenness and the eigenvector centrality for each individual were calculated and correlated to kinship, age and dominance. Finally, we performed a resilience analysis by simulating the removal of individuals displaying the highest betweenness and eigenvector centrality values. We found that related dyads were more frequently associated than unrelated dyads. Moreover, our results showed that the cumulative distribution of individual betweenness and eigenvector centrality followed a power function, which is characteristic of scale-free networks. This property showed that some group members, mostly females, occupied a highly central position. Finally, the resilience analysis showed that the removal of the two most central females split the network into small subgroups and increased the network diameter. Critically, this study confirms that females appear to occupy more central positions than males in mandrill groups. Consequently, these females appear to be crucial for group cohesion and probably play a pivotal role in this species.

Social Structure of a Semi-Free Ranging Group of Mandrills (Mandrillus sphinx): A Social Network Analysis

PubMed Central

Bret, Céline; Sueur, Cédric; Ngoubangoye, Barthélémy; Verrier, Delphine; Deneubourg, Jean-Louis; Petit, Odile

2013-01-01

The difficulty involved in following mandrills in the wild means that very little is known about social structure in this species. Most studies initially considered mandrill groups to be an aggregation of one-male/multifemale units, with males occupying central positions in a structure similar to those observed in the majority of baboon species. However, a recent study hypothesized that mandrills form stable groups with only two or three permanent males, and that females occupy more central positions than males within these groups. We used social network analysis methods to examine how a semi-free ranging group of 19 mandrills is structured. We recorded all dyads of individuals that were in contact as a measure of association. The betweenness and the eigenvector centrality for each individual were calculated and correlated to kinship, age and dominance. Finally, we performed a resilience analysis by simulating the removal of individuals displaying the highest betweenness and eigenvector centrality values. We found that related dyads were more frequently associated than unrelated dyads. Moreover, our results showed that the cumulative distribution of individual betweenness and eigenvector centrality followed a power function, which is characteristic of scale-free networks. This property showed that some group members, mostly females, occupied a highly central position. Finally, the resilience analysis showed that the removal of the two most central females split the network into small subgroups and increased the network diameter. Critically, this study confirms that females appear to occupy more central positions than males in mandrill groups. Consequently, these females appear to be crucial for group cohesion and probably play a pivotal role in this species. PMID:24340074

Diffusion tensor eigenvector directional color imaging patterns in the evaluation of cerebral white matter tracts altered by tumor.

PubMed

Field, Aaron S; Alexander, Andrew L; Wu, Yu-Chien; Hasan, Khader M; Witwer, Brian; Badie, Behnam

2004-10-01

To categorize the varied appearances of tumor-altered white matter (WM) tracts on diffusion tensor eigenvector directional color maps. Diffusion tensor imaging (DTI) was obtained preoperatively in 13 patients with brain tumors ranging from benign to high-grade malignant, including primary and metastatic lesions, and maps of apparent diffusion coefficient (ADC), fractional anisotropy (FA), and major eigenvector direction were generated. Regions of interest (ROIs) were drawn within identifiable WM tracts affected by tumor, avoiding grossly cystic and necrotic regions, known fiber crossings, and gray matter. Patterns of WM tract alteration were categorized on the basis of qualitative analysis of directional color maps and correlation analysis of ADC and FA. Four basic patterns of WM alteration were identified: 1) normal or nearly normal FA and ADC, with abnormal tract location or tensor directions attributable to bulk mass displacement, 2) moderately decreased FA and increased ADC with normal tract locations and tensor directions, 3) moderately decreased FA and increased ADC with abnormal tensor directions, and 4) near isotropy. FA and ADC were inversely correlated for Patterns 1-3 but did not discriminate edema from infiltrating tumor. However, in the absence of mass displacement, infiltrating tumor was found to produce tensor directional changes that were not observed with vasogenic edema, suggesting the possibility of discrimination on the basis of directional statistics. Tumor alteration of WM tracts tends to produce one of four patterns on FA and directional color maps. Clinical application of these patterns must await further study. Copyright 2004 Wiley-Liss, Inc.

Centrality measures in temporal networks with time series analysis

NASA Astrophysics Data System (ADS)

Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun

2017-05-01

The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.

Analytical minimization of synchronicity errors in stochastic identification

NASA Astrophysics Data System (ADS)

Bernal, D.

2018-01-01

An approach to minimize error due to synchronicity faults in stochastic system identification is presented. The scheme is based on shifting the time domain signals so the phases of the fundamental eigenvector estimated from the spectral density are zero. A threshold on the mean of the amplitude-weighted absolute value of these phases, above which signal shifting is deemed justified, is derived and found to be proportional to the first mode damping ratio. It is shown that synchronicity faults do not map precisely to phasor multiplications in subspace identification and that the accuracy of spectral density estimated eigenvectors, for inputs with arbitrary spectral density, decrease with increasing mode number. Selection of a corrective strategy based on signal alignment, instead of eigenvector adjustment using phasors, is shown to be the product of the foregoing observations. Simulations that include noise and non-classical damping suggest that the scheme can provide sufficient accuracy to be of practical value.

Disconnection of network hubs and cognitive impairment after traumatic brain injury.

PubMed

Fagerholm, Erik D; Hellyer, Peter J; Scott, Gregory; Leech, Robert; Sharp, David J

2015-06-01

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Functional network centrality in obesity: A resting-state and task fMRI study.

PubMed

García-García, Isabel; Jurado, María Ángeles; Garolera, Maite; Marqués-Iturria, Idoia; Horstmann, Annette; Segura, Bàrbara; Pueyo, Roser; Sender-Palacios, María José; Vernet-Vernet, Maria; Villringer, Arno; Junqué, Carme; Margulies, Daniel S; Neumann, Jane

2015-09-30

Obesity is associated with structural and functional alterations in brain areas that are often functionally distinct and anatomically distant. This suggests that obesity is associated with differences in functional connectivity of regions distributed across the brain. However, studies addressing whole brain functional connectivity in obesity remain scarce. Here, we compared voxel-wise degree centrality and eigenvector centrality between participants with obesity (n=20) and normal-weight controls (n=21). We analyzed resting state and task-related fMRI data acquired from the same individuals. Relative to normal-weight controls, participants with obesity exhibited reduced degree centrality in the right middle frontal gyrus in the resting-state condition. During the task fMRI condition, obese participants exhibited less degree centrality in the left middle frontal gyrus and the lateral occipital cortex along with reduced eigenvector centrality in the lateral occipital cortex and occipital pole. Our results highlight the central role of the middle frontal gyrus in the pathophysiology of obesity, a structure involved in several brain circuits signaling attention, executive functions and motor functions. Additionally, our analysis suggests the existence of task-dependent reduced centrality in occipital areas; regions with a role in perceptual processes and that are profoundly modulated by attention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

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

Welch, Jr., Paul Michael; Welch, Cynthia F.

Here, we present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstratemore » that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.« less

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

DOE PAGES

Welch, Jr., Paul Michael; Welch, Cynthia F.

2017-04-27

Here, we present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstratemore » that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.« less

Diffusion Tensor Magnetic Resonance Imaging Strategies for Color Mapping of Human Brain Anatomy

PubMed Central

Boujraf, Saïd

2018-01-01

Background: A color mapping of fiber tract orientation using diffusion tensor imaging (DTI) can be prominent in clinical practice. The goal of this paper is to perform a comparative study of visualized diffusion anisotropy in the human brain anatomical entities using three different color-mapping techniques based on diffusion-weighted imaging (DWI) and DTI. Methods: The first technique is based on calculating a color map from DWIs measured in three perpendicular directions. The second technique is based on eigenvalues derived from the diffusion tensor. The last technique is based on three eigenvectors corresponding to sorted eigenvalues derived from the diffusion tensor. All magnetic resonance imaging measurements were achieved using a 1.5 Tesla Siemens Vision whole body imaging system. A single-shot DW echoplanar imaging sequence used a Stejskal–Tanner approach. Trapezoidal diffusion gradients are used. The slice orientation was transverse. The basic measurement yielded a set of 13 images. Each series consists of a single image without diffusion weighting, besides two DWIs for each of the next six noncollinear magnetic field gradient directions. Results: The three types of color maps were calculated consequently using the DWI obtained and the DTI. Indeed, we established an excellent similarity between the image data in the color maps and the fiber directions of known anatomical structures (e.g., corpus callosum and gray matter). Conclusions: In the meantime, rotationally invariant quantities such as the eigenvectors of the diffusion tensor reflected better, the real orientation found in the studied tissue. PMID:29928631

MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.

PubMed

Mallik, Saurav; Maulik, Ujjwal

2015-10-01

Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided. Copyright © 2015 Elsevier Inc. All rights reserved.

Visualizing Hyolaryngeal Mechanics in Swallowing Using Dynamic MRI

PubMed Central

Pearson, William G.; Zumwalt, Ann C.

2013-01-01

Introduction Coordinates of anatomical landmarks are captured using dynamic MRI to explore whether a proposed two-sling mechanism underlies hyolaryngeal elevation in pharyngeal swallowing. A principal components analysis (PCA) is applied to coordinates to determine the covariant function of the proposed mechanism. Methods Dynamic MRI (dMRI) data were acquired from eleven healthy subjects during a repeated swallows task. Coordinates mapping the proposed mechanism are collected from each dynamic (frame) of a dynamic MRI swallowing series of a randomly selected subject in order to demonstrate shape changes in a single subject. Coordinates representing minimum and maximum hyolaryngeal elevation of all 11 subjects were also mapped to demonstrate shape changes of the system among all subjects. MophoJ software was used to perform PCA and determine vectors of shape change (eigenvectors) for elements of the two-sling mechanism of hyolaryngeal elevation. Results For both single subject and group PCAs, hyolaryngeal elevation accounted for the first principal component of variation. For the single subject PCA, the first principal component accounted for 81.5% of the variance. For the between subjects PCA, the first principal component accounted for 58.5% of the variance. Eigenvectors and shape changes associated with this first principal component are reported. Discussion Eigenvectors indicate that two-muscle slings and associated skeletal elements function as components of a covariant mechanism to elevate the hyolaryngeal complex. Morphological analysis is useful to model shape changes in the two-sling mechanism of hyolaryngeal elevation. PMID:25090608

Financial fluctuations anchored to economic fundamentals: A mesoscopic network approach.

PubMed

Sharma, Kiran; Gopalakrishnan, Balagopal; Chakrabarti, Anindya S; Chakraborti, Anirban

2017-08-14

We demonstrate the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and infer the relative importance of the sectors in the nominal network through measures of centrality and clustering algorithms. Eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sectors that are relatively large in size, defined with three metrics, viz., market capitalization, revenue and number of employees, constitute the core of the return networks, whereas the periphery is mostly populated by relatively smaller sectors. Therefore, sector-level nominal return dynamics are anchored to the real size effect, which ultimately shapes the optimal portfolios for risk management. Our results are reasonably robust across 27 countries of varying degrees of prosperity and across periods of market turbulence (2008-09) as well as periods of relative calmness (2012-13 and 2015-16).

Eigenvector method for umbrella sampling enables error analysis

PubMed Central

Thiede, Erik H.; Van Koten, Brian; Weare, Jonathan; Dinner, Aaron R.

2016-01-01

Umbrella sampling efficiently yields equilibrium averages that depend on exploring rare states of a model by biasing simulations to windows of coordinate values and then combining the resulting data with physical weighting. Here, we introduce a mathematical framework that casts the step of combining the data as an eigenproblem. The advantage to this approach is that it facilitates error analysis. We discuss how the error scales with the number of windows. Then, we derive a central limit theorem for averages that are obtained from umbrella sampling. The central limit theorem suggests an estimator of the error contributions from individual windows, and we develop a simple and computationally inexpensive procedure for implementing it. We demonstrate this estimator for simulations of the alanine dipeptide and show that it emphasizes low free energy pathways between stable states in comparison to existing approaches for assessing error contributions. Our work suggests the possibility of using the estimator and, more generally, the eigenvector method for umbrella sampling to guide adaptation of the simulation parameters to accelerate convergence. PMID:27586912

The solution structures of the cucumber mosaic virus and tomato aspermy virus coat proteins explored with molecular dynamics simulations.

PubMed

Gellért, Akos; Balázs, Ervin

2010-02-26

The three-dimensional structures of two cucumovirus coat proteins (CP), namely Cucumber mosaic virus (CMV) and Tomato aspermy virus (TAV), were explored by molecular dynamics (MD) simulations. The N-terminal domain and the C-terminal tail of the CPs proved to be intrinsically unstructured protein regions in aqueous solution. The N-terminal alpha-helix had a partially unrolled conformation. The thermal factor analysis of the CP loop regions demonstrated that the CMV CP had more flexible loop regions than the TAV CP. The principal component analysis (PCA) of the MD trajectories showed that the first three eigenvectors represented the three main conformational motions in the CPs. The first motion components with the highest variance contribution described an opening movement between the hinge and the N-terminal domain of both CPs. The second eigenvector showed a closing motion, while the third eigenvector represented crosswise conformational fluctuations. These new findings, together with previous results, suggest that the hinge region of CPs plays a central role in the recognition and binding of viral RNA. Copyright 2009 Elsevier Inc. All rights reserved.

GFT centrality: A new node importance measure for complex networks

NASA Astrophysics Data System (ADS)

Singh, Rahul; Chakraborty, Abhishek; Manoj, B. S.

2017-12-01

Identifying central nodes is very crucial to design efficient communication networks or to recognize key individuals of a social network. In this paper, we introduce Graph Fourier Transform Centrality (GFT-C), a metric that incorporates local as well as global characteristics of a node, to quantify the importance of a node in a complex network. GFT-C of a reference node in a network is estimated from the GFT coefficients derived from the importance signal of the reference node. Our study reveals the superiority of GFT-C over traditional centralities such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and Google PageRank centrality, in the context of various arbitrary and real-world networks with different degree-degree correlations.

Towards a Methodology for Validation of Centrality Measures in Complex Networks

PubMed Central

2014-01-01

Background Living systems are associated with Social networks — networks made up of nodes, some of which may be more important in various aspects as compared to others. While different quantitative measures labeled as “centralities” have previously been used in the network analysis community to find out influential nodes in a network, it is debatable how valid the centrality measures actually are. In other words, the research question that remains unanswered is: how exactly do these measures perform in the real world? So, as an example, if a centrality of a particular node identifies it to be important, is the node actually important? Purpose The goal of this paper is not just to perform a traditional social network analysis but rather to evaluate different centrality measures by conducting an empirical study analyzing exactly how do network centralities correlate with data from published multidisciplinary network data sets. Method We take standard published network data sets while using a random network to establish a baseline. These data sets included the Zachary's Karate Club network, dolphin social network and a neural network of nematode Caenorhabditis elegans. Each of the data sets was analyzed in terms of different centrality measures and compared with existing knowledge from associated published articles to review the role of each centrality measure in the determination of influential nodes. Results Our empirical analysis demonstrates that in the chosen network data sets, nodes which had a high Closeness Centrality also had a high Eccentricity Centrality. Likewise high Degree Centrality also correlated closely with a high Eigenvector Centrality. Whereas Betweenness Centrality varied according to network topology and did not demonstrate any noticeable pattern. In terms of identification of key nodes, we discovered that as compared with other centrality measures, Eigenvector and Eccentricity Centralities were better able to identify important nodes. PMID:24709999

Diffusion Forecasting Model with Basis Functions from QR-Decomposition

NASA Astrophysics Data System (ADS)

Harlim, John; Yang, Haizhao

2018-06-01

The diffusion forecasting is a nonparametric approach that provably solves the Fokker-Planck PDE corresponding to Itô diffusion without knowing the underlying equation. The key idea of this method is to approximate the solution of the Fokker-Planck equation with a discrete representation of the shift (Koopman) operator on a set of basis functions generated via the diffusion maps algorithm. While the choice of these basis functions is provably optimal under appropriate conditions, computing these basis functions is quite expensive since it requires the eigendecomposition of an N× N diffusion matrix, where N denotes the data size and could be very large. For large-scale forecasting problems, only a few leading eigenvectors are computationally achievable. To overcome this computational bottleneck, a new set of basis functions constructed by orthonormalizing selected columns of the diffusion matrix and its leading eigenvectors is proposed. This computation can be carried out efficiently via the unpivoted Householder QR factorization. The efficiency and effectiveness of the proposed algorithm will be shown in both deterministically chaotic and stochastic dynamical systems; in the former case, the superiority of the proposed basis functions over purely eigenvectors is significant, while in the latter case forecasting accuracy is improved relative to using a purely small number of eigenvectors. Supporting arguments will be provided on three- and six-dimensional chaotic ODEs, a three-dimensional SDE that mimics turbulent systems, and also on the two spatial modes associated with the boreal winter Madden-Julian Oscillation obtained from applying the Nonlinear Laplacian Spectral Analysis on the measured Outgoing Longwave Radiation.

Diffusion Forecasting Model with Basis Functions from QR-Decomposition

NASA Astrophysics Data System (ADS)

Harlim, John; Yang, Haizhao

2017-12-01

The diffusion forecasting is a nonparametric approach that provably solves the Fokker-Planck PDE corresponding to Itô diffusion without knowing the underlying equation. The key idea of this method is to approximate the solution of the Fokker-Planck equation with a discrete representation of the shift (Koopman) operator on a set of basis functions generated via the diffusion maps algorithm. While the choice of these basis functions is provably optimal under appropriate conditions, computing these basis functions is quite expensive since it requires the eigendecomposition of an N× N diffusion matrix, where N denotes the data size and could be very large. For large-scale forecasting problems, only a few leading eigenvectors are computationally achievable. To overcome this computational bottleneck, a new set of basis functions constructed by orthonormalizing selected columns of the diffusion matrix and its leading eigenvectors is proposed. This computation can be carried out efficiently via the unpivoted Householder QR factorization. The efficiency and effectiveness of the proposed algorithm will be shown in both deterministically chaotic and stochastic dynamical systems; in the former case, the superiority of the proposed basis functions over purely eigenvectors is significant, while in the latter case forecasting accuracy is improved relative to using a purely small number of eigenvectors. Supporting arguments will be provided on three- and six-dimensional chaotic ODEs, a three-dimensional SDE that mimics turbulent systems, and also on the two spatial modes associated with the boreal winter Madden-Julian Oscillation obtained from applying the Nonlinear Laplacian Spectral Analysis on the measured Outgoing Longwave Radiation.

VizieR Online Data Catalog: Spatial deconvolution code (Quintero Noda+, 2015)

NASA Astrophysics Data System (ADS)

Quintero Noda, C.; Asensio Ramos, A.; Orozco Suarez, D.; Ruiz Cobo, B.

2015-05-01

This deconvolution method follows the scheme presented in Ruiz Cobo & Asensio Ramos (2013A&A...549L...4R) The Stokes parameters are projected onto a few spectral eigenvectors and the ensuing maps of coefficients are deconvolved using a standard Lucy-Richardson algorithm. This introduces a stabilization because the PCA filtering reduces the amount of noise. (1 data file).

The diversity of quasars unified by accretion and orientation.

PubMed

Shen, Yue; Ho, Luis C

2014-09-11

Quasars are rapidly accreting supermassive black holes at the centres of massive galaxies. They display a broad range of properties across all wavelengths, reflecting the diversity in the physical conditions of the regions close to the central engine. These properties, however, are not random, but form well-defined trends. The dominant trend is known as 'Eigenvector 1', in which many properties correlate with the strength of optical iron and [O III] emission. The main physical driver of Eigenvector 1 has long been suspected to be the quasar luminosity normalized by the mass of the hole (the 'Eddington ratio'), which is an important parameter of the black hole accretion process. But a definitive proof has been missing. Here we report an analysis of archival data that reveals that the Eddington ratio indeed drives Eigenvector 1. We also find that orientation plays a significant role in determining the observed kinematics of the gas in the broad-line region, implying a flattened, disk-like geometry for the fast-moving clouds close to the black hole. Our results show that most of the diversity of quasar phenomenology can be unified using two simple quantities: Eddington ratio and orientation.

Multi-parametric centrality method for graph network models

NASA Astrophysics Data System (ADS)

Ivanov, Sergei Evgenievich; Gorlushkina, Natalia Nikolaevna; Ivanova, Lubov Nikolaevna

2018-04-01

The graph model networks are investigated to determine centrality, weights and the significance of vertices. For centrality analysis appliesa typical method that includesany one of the properties of graph vertices. In graph theory, methods of analyzing centrality are used: in terms by degree, closeness, betweenness, radiality, eccentricity, page-rank, status, Katz and eigenvector. We have proposed a new method of multi-parametric centrality, which includes a number of basic properties of the network member. The mathematical model of multi-parametric centrality method is developed. Comparison of results for the presented method with the centrality methods is carried out. For evaluate the results for the multi-parametric centrality methodthe graph model with hundreds of vertices is analyzed. The comparative analysis showed the accuracy of presented method, includes simultaneously a number of basic properties of vertices.

Centralities in simplicial complexes. Applications to protein interaction networks.

PubMed

Estrada, Ernesto; Ross, Grant J

2018-02-07

Complex networks can be used to represent complex systems which originate in the real world. Here we study a transformation of these complex networks into simplicial complexes, where cliques represent the simplices of the complex. We extend the concept of node centrality to that of simplicial centrality and study several mathematical properties of degree, closeness, betweenness, eigenvector, Katz, and subgraph centrality for simplicial complexes. We study the degree distributions of these centralities at the different levels. We also compare and describe the differences between the centralities at the different levels. Using these centralities we study a method for detecting essential proteins in PPI networks of cells and explain the varying abilities of the centrality measures at the different levels in identifying these essential proteins. Copyright © 2017 Elsevier Ltd. All rights reserved.

An exploration of diffusion tensor eigenvector variability within human calf muscles.

PubMed

Rockel, Conrad; Noseworthy, Michael D

2016-01-01

To explore the effect of diffusion tensor imaging (DTI) acquisition parameters on principal and minor eigenvector stability within human lower leg skeletal muscles. Lower leg muscles were evaluated in seven healthy subjects at 3T using an 8-channel transmit/receive coil. Diffusion-encoding was performed with nine signal averages (NSA) using 6, 15, and 25 directions (NDD). Individual DTI volumes were combined into aggregate volumes of 3, 2, and 1 NSA according to number of directions. Tensor eigenvalues (λ1 , λ2 , λ3 ), eigenvectors (ε1 , ε2 , ε3 ), and DTI metrics (fractional anisotropy [FA] and mean diffusivity [MD]) were calculated for each combination of NSA and NDD. Spatial maps of signal-to-noise ratio (SNR), λ3 :λ2 ratio, and zenith angle were also calculated for region of interest (ROI) analysis of vector orientation consistency. ε1 variability was only moderately related to ε2 variability (r = 0.4045). Variation of ε1 was affected by NDD, not NSA (P < 0.0002), while variation of ε2 was affected by NSA, not NDD (P < 0.0003). In terms of tensor shape, vector variability was weakly related to FA (ε1 :r = -0.1854, ε2 : ns), but had a stronger relation to the λ3 :λ2 ratio (ε1 :r = -0.5221, ε2 :r = -0.1771). Vector variability was also weakly related to SNR (ε1 :r = -0.2873, ε2 :r = -0.3483). Zenith angle was found to be strongly associated with variability of ε1 (r = 0.8048) but only weakly with that of ε2 (r = 0.2135). The second eigenvector (ε2 ) displayed higher directional variability relative to ε1 , and was only marginally affected by experimental conditions that impacted ε1 variability. © 2015 Wiley Periodicals, Inc.

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

PubMed

Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be obtained from git.io/diffslcpy. The R implementation and code to reproduce the analysis is available via git.io/diffslc.

Diffusion tensor imaging in evaluation of human skeletal muscle injury.

PubMed

Zaraiskaya, Tatiana; Kumbhare, Dinesh; Noseworthy, Michael D

2006-08-01

To explore the capability and reliability of diffusion tensor magnetic resonance imaging (DTI) in the evaluation of human skeletal muscle injury. DTI of four patients with gastrocnemius and soleus muscles injuries was compared to eight healthy controls. Imaging was performed using a GE 3.0T short-bore scanner. A diffusion-weighted 2D spin echo echo-planar imaging (EPI) pulse sequence optimized for skeletal muscle was used. From a series of axially acquired diffusion tensor images the diffusion tensor eigenparameters (eigenvalues and eigenvectors), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) were calculated and compared for injured and healthy calf muscles. Two dimensional (2D) projection maps of the principal eigenvectors were plotted to visualize the healthy and pathologic muscle fiber architectures. Clear differences in FA and ADC were observed in injured skeletal muscle, compared to healthy controls. Mean control FA was 0.23 +/- 0.02 for medial and lateral gastrocnemius (mg and lg) muscles, and 0.20 +/- 0.02 for soleus (sol) muscles. In all patients FA values were reduced compared to controls, to as low as 0.08 +/- 0.02. The ADC in controls ranged from 1.41 to 1.31 x 10(-9) m(2)/second, while in patients this was consistently higher. The 2D projection maps revealed muscle fiber disorder in injured calves, while in healthy controls the 2D projection maps show a well organized (ordered) fiber structure. DTI is a suitable method to assess human calf muscle injury.

Eigenvectors determination of the ribosome dynamics model during mRNA translation using the Kleene Star algorithm

NASA Astrophysics Data System (ADS)

Ernawati; Carnia, E.; Supriatna, A. K.

2018-03-01

Eigenvalues and eigenvectors in max-plus algebra have the same important role as eigenvalues and eigenvectors in conventional algebra. In max-plus algebra, eigenvalues and eigenvectors are useful for knowing dynamics of the system such as in train system scheduling, scheduling production systems and scheduling learning activities in moving classes. In the translation of proteins in which the ribosome move uni-directionally along the mRNA strand to recruit the amino acids that make up the protein, eigenvalues and eigenvectors are used to calculate protein production rates and density of ribosomes on the mRNA. Based on this, it is important to examine the eigenvalues and eigenvectors in the process of protein translation. In this paper an eigenvector formula is given for a ribosome dynamics during mRNA translation by using the Kleene star algorithm in which the resulting eigenvector formula is simpler and easier to apply to the system than that introduced elsewhere. This paper also discusses the properties of the matrix {B}λ \\otimes n of model. Among the important properties, it always has the same elements in the first column for n = 1, 2,… if the eigenvalue is the time of initiation, λ = τin , and the column is the eigenvector of the model corresponding to λ.

The Weyl law for contractive maps

NASA Astrophysics Data System (ADS)

Spina, Maria E.; Rivas, Alejandro M. F.; Carlo, Gabriel

2013-11-01

We find an empirical Weyl law followed by the eigenvalues of contractive maps. An important property is that it is mainly insensitive to the dimension of the corresponding invariant classical set, the strange attractor. The usual explanation for the fractal Weyl law emergence in scattering systems (i.e., having a projective opening) is based on the classical phase space distributions evolved up to the quantum to classical correspondence (Ehrenfest) time. In the contractive case this reasoning fails to describe it. Instead, we conjecture that the support for this behavior is essentially given by the strong non-orthogonality of the eigenvectors of the contractive superoperator. We test the validity of the Weyl law and this conjecture on two paradigmatic systems, the dissipative baker and kicked top maps.

Age-dependent effects of brain stimulation on network centrality.

PubMed

Antonenko, Daria; Nierhaus, Till; Meinzer, Marcus; Prehn, Kristin; Thielscher, Axel; Ittermann, Bernd; Flöel, Agnes

2018-04-18

Functional magnetic resonance imaging (fMRI) studies have suggested that advanced age may mediate the effects of transcranial direct current stimulation (tDCS) on brain function. However, studies directly comparing neural tDCS effects between young and older adults are scarce and limited to task-related imaging paradigms. Resting-state (rs-) fMRI, that is independent of age-related differences in performance, is well suited to investigate age-associated differential neural tDCS effects. Three "online" tDCS conditions (anodal, cathodal, sham) were compared in a cross-over, within-subject design, in 30 young and 30 older adults. Active stimulation targeted the left sensorimotor network (active electrode over left sensorimotor cortex with right supraorbital reference electrode). A graph-based rs-fMRI data analysis approach (eigenvector centrality mapping) and complementary seed-based analyses characterized neural tDCS effects. An interaction between anodal tDCS and age group was observed. Specifically, centrality in bilateral paracentral and posterior regions (precuneus, superior parietal cortex) was increased in young, but decreased in older adults. Seed-based analyses revealed that these opposing patterns of tDCS-induced centrality modulation originated from differential effects of tDCS on functional coupling of the stimulated left paracentral lobule. Cathodal tDCS did not show significant effects. Our study provides first evidence for differential tDCS effects on neural network organization in young and older adults. Anodal stimulation mainly affected coupling of sensorimotor with ventromedial prefrontal areas in young and decoupling with posteromedial areas in older adults. Copyright © 2018 Elsevier Inc. All rights reserved.

PCA Tomography: how to extract information from data cubes

NASA Astrophysics Data System (ADS)

Steiner, J. E.; Menezes, R. B.; Ricci, T. V.; Oliveira, A. S.

2009-05-01

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector's orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation on behalf of the Gemini partnership: the National Science Foundation (United States), the Science and Technology Facilities Council (United Kingdom), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência e Tecnologia (Brazil) and SECYT (Argentina). E-mail: steiner@astro.iag.usp.br

Brain activity and connectivity changes in response to glucose ingestion.

PubMed

van Opstal, A M; Hafkemeijer, A; van den Berg-Huysmans, A A; Hoeksma, M; Blonk, C; Pijl, H; Rombouts, S A R B; van der Grond, J

2018-05-27

The regulatory role of the brain in directing eating behavior becomes increasingly recognized. Although many areas in the brain have been found to respond to food cues, very little data is available after actual caloric intake. The aim of this study was to determine normal whole brain functional responses to ingestion of glucose after an overnight fast. Twenty-five normal weight, adult males underwent functional MRI on two separate visits. In a single-blind randomized study setup, participants received either glucose solution (50 g/300 ml of water) or plain water. We studied changes in Blood Oxygen Level Dependent (BOLD) signal, voxel-based connectivity by Eigenvector Centrality Mapping, and functional network connectivity. Ingestion of glucose led to increased centrality in the thalamus and to decreases in BOLD signal in various brain areas. Decreases in connectivity in the sensory-motor and dorsal visual stream networks were found. Ingestion of water resulted in increased centrality across the brain, and increases in connectivity in the medial and lateral visual cortex network. Increased BOLD intensity was found in the intracalcarine and cingulate cortex. Our data show that ingestion of glucose leads to decreased activity and connectivity in brain areas and networks linked to energy seeking and satiation. In contrast, drinking plain water leads to increased connectivity probably associated with continued food seeking and unfulfilled reward. Trail registration: This study combines data of two studies registered at clinicaltrails.gov under numbers NCT03202342 and NCT03247114.

Covariance expressions for eigenvalue and eigenvector problems

NASA Astrophysics Data System (ADS)

Liounis, Andrew J.

There are a number of important scientific and engineering problems whose solutions take the form of an eigenvalue--eigenvector problem. Some notable examples include solutions to linear systems of ordinary differential equations, controllability of linear systems, finite element analysis, chemical kinetics, fitting ellipses to noisy data, and optimal estimation of attitude from unit vectors. In many of these problems, having knowledge of the eigenvalue and eigenvector Jacobians is either necessary or is nearly as important as having the solution itself. For instance, Jacobians are necessary to find the uncertainty in a computed eigenvalue or eigenvector estimate. This uncertainty, which is usually represented as a covariance matrix, has been well studied for problems similar to the eigenvalue and eigenvector problem, such as singular value decomposition. There has been substantially less research on the covariance of an optimal estimate originating from an eigenvalue-eigenvector problem. In this thesis we develop two general expressions for the Jacobians of eigenvalues and eigenvectors with respect to the elements of their parent matrix. The expressions developed make use of only the parent matrix and the eigenvalue and eigenvector pair under consideration. In addition, they are applicable to any general matrix (including complex valued matrices, eigenvalues, and eigenvectors) as long as the eigenvalues are simple. Alongside this, we develop expressions that determine the uncertainty in a vector estimate obtained from an eigenvalue-eigenvector problem given the uncertainty of the terms of the matrix. The Jacobian expressions developed are numerically validated with forward finite, differencing and the covariance expressions are validated using Monte Carlo analysis. Finally, the results from this work are used to determine covariance expressions for a variety of estimation problem examples and are also applied to the design of a dynamical system.

Active constrained clustering by examining spectral Eigenvectors

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; desJardins, Marie; Xu, Qianjun

2005-01-01

This work focuses on the active selection of pairwise constraints for spectral clustering. We develop and analyze a technique for Active Constrained Clustering by Examining Spectral eigenvectorS (ACCESS) derived from a similarity matrix.

Relationships between the Definition of the Hyperplane Width to the Fidelity of Principal Component Loading Patterns.

NASA Astrophysics Data System (ADS)

Richman, Michael B.; Gong, Xiaofeng

1999-06-01

When applying eigenanalysis, one decision analysts make is the determination of what magnitude an eigenvector coefficient (e.g., principal component (PC) loading) must achieve to be considered as physically important. Such coefficients can be displayed on maps or in a time series or tables to gain a fuller understanding of a large array of multivariate data. Previously, such a decision on what value of loading designates a useful signal (hereafter called the loading `cutoff') for each eigenvector has been purely subjective. The importance of selecting such a cutoff is apparent since those loading elements in the range of zero to the cutoff are ignored in the interpretation and naming of PCs since only the absolute values of loadings greater than the cutoff are physically analyzed. This research sets out to objectify the problem of best identifying the cutoff by application of matching between known correlation/covariance structures and their corresponding eigenpatterns, as this cutoff point (known as the hyperplane width) is varied.A Monte Carlo framework is used to resample at five sample sizes. Fourteen different hyperplane cutoff widths are tested, bootstrap resampled 50 times to obtain stable results. The key findings are that the location of an optimal hyperplane cutoff width (one which maximized the information content match between the eigenvector and the parent dispersion matrix from which it was derived) is a well-behaved unimodal function. On an individual eigenvector, this enables the unique determination of a hyperplane cutoff value to be used to separate those loadings that best reflect the relationships from those that do not. The effects of sample size on the matching accuracy are dramatic as the values for all solutions (i.e., unrotated, rotated) rose steadily from 25 through 250 observations and then weakly thereafter. The specific matching coefficients are useful to assess the penalties incurred when one analyzes eigenvector coefficients of a lower absolute value than the cutoff (termed coefficient in the hyperplane) or, alternatively, chooses not to analyze coefficients that contain useful physical signal outside of the hyperplane. Therefore, this study enables the analyst to make the best use of the information available in their PCs to shed light on complicated data structures.

Using Solar Radiation Pressure to Control L2 Orbits

NASA Technical Reports Server (NTRS)

Tene, Noam; Richon, Karen; Folta, David

1998-01-01

The main perturbations at the Sun-Earth Lagrange points L1 and L2 are from solar radiation pressure (SRP), the Moon and the planets. Traditional approaches to trajectory design for Lagrange-point orbits use maneuvers every few months to correct for these perturbations. The gravitational effects of the Moon and the planets are small and periodic. However, they cannot be neglected because small perturbations in the direction of the unstable eigenvector are enough to cause exponential growth within a few months. The main effect of a constant SRP is to shift the center of the orbit by a small distance. For spacecraft with large sun-shields like the Microwave Anisotropy Probe (MAP) and the Next Generation Space Telescope (NGST), the SRP effect is larger than all other perturbations and depends mostly on spacecraft attitude. Small variations in the spacecraft attitude are large enough to excite or control the exponential eigenvector. A closed-loop linear controller based on the SRP variations would eliminate one of the largest errors to the orbit and provide a continuous acceleration for use in controlling other disturbances. It is possible to design reference trajectories that account for the periodic lunar and planetary perturbations and still satisfy mission requirements. When such trajectories are used the acceleration required to control the unstable eigenvector is well within the capabilities of a continuous linear controller. Initial estimates show that by using attitude control it should be possible to minimize and even eliminate thruster maneuvers for station keeping.

ORA User’s Guide 2013

DTIC Science & Technology

2013-06-03

and a C++ computational backend . The most current version of ORA (3.0.8.5) software is available on the casos website: http://casos.cs.cmu.edu...optimizing a network’s design structure. ORA uses a Java interface for ease of use, and a C++ computational backend . The most current version of ORA...Eigenvector Centrality : Node most connected to other highly connected nodes. Assists in identifying those who can mobilize others Entity Class

An algorithm for the basis of the finite Fourier transform

NASA Technical Reports Server (NTRS)

Santhanam, Thalanayar S.

1995-01-01

The Finite Fourier Transformation matrix (F.F.T.) plays a central role in the formulation of quantum mechanics in a finite dimensional space studied by the author over the past couple of decades. An outstanding problem which still remains open is to find a complete basis for F.F.T. In this paper we suggest a simple algorithm to find the eigenvectors of F.T.T.

Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.

PubMed

Sato, João Ricardo; Biazoli, Claudinei Eduardo; Salum, Giovanni Abrahão; Gadelha, Ary; Crossley, Nicolas; Vieira, Gilson; Zugman, André; Picon, Felipe Almeida; Pan, Pedro Mario; Hoexter, Marcelo Queiroz; Amaro, Edson; Anés, Mauricio; Moura, Luciana Monteiro; Del'Aquilla, Marco Antonio Gomes; Mcguire, Philip; Rohde, Luis Augusto; Miguel, Euripedes Constantino; Jackowski, Andrea Parolin; Bressan, Rodrigo Affonseca

2018-03-01

One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a novel method for assessing brain networks based on the combination of a graph theory measure (eigenvector centrality) and a one-class support vector machine (OC-SVM). We applied this approach to resting-state fMRI data from 622 children and adolescents. Eigenvector centrality (EVC) of nodes from positive- and negative-task networks were extracted from each subject and used as input to an OC-SVM to label individual brain networks as typical or atypical. We hypothesised that classification of these subjects regarding the pattern of brain connectivity would predict the level of psychopathology. Subjects with atypical brain network organisation had higher levels of psychopathology (p < 0.001). There was a greater EVC in the typical group at the bilateral posterior cingulate and bilateral posterior temporal cortices; and significant decreases in EVC at left temporal pole. The combination of graph theory methods and an OC-SVM is a promising method to characterise neurodevelopment, and may be useful to understand the deviations leading to mental disorders.

An object recognition method based on fuzzy theory and BP networks

NASA Astrophysics Data System (ADS)

Wu, Chuan; Zhu, Ming; Yang, Dong

2006-01-01

It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling, shifting, rotation if eigenvectors can not be chosen appropriately. In order to solve this problem, the image is edged, the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively, correctly and quickly.

Matrix with Prescribed Eigenvectors

ERIC Educational Resources Information Center

Ahmad, Faiz

2011-01-01

It is a routine matter for undergraduates to find eigenvalues and eigenvectors of a given matrix. But the converse problem of finding a matrix with prescribed eigenvalues and eigenvectors is rarely discussed in elementary texts on linear algebra. This problem is related to the "spectral" decomposition of a matrix and has important technical…

Eigenvalue and eigenvector sensitivity and approximate analysis for repeated eigenvalue problems

NASA Technical Reports Server (NTRS)

Hou, Gene J. W.; Kenny, Sean P.

1991-01-01

A set of computationally efficient equations for eigenvalue and eigenvector sensitivity analysis are derived, and a method for eigenvalue and eigenvector approximate analysis in the presence of repeated eigenvalues is presented. The method developed for approximate analysis involves a reparamaterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations of changes in both the eigenvalues and eigenvectors associated with the repeated eigenvalue problem. Examples are given to demonstrate the application of such equations for sensitivity and approximate analysis.

Ulam method and fractal Weyl law for Perron-Frobenius operators

NASA Astrophysics Data System (ADS)

Ermann, L.; Shepelyansky, D. L.

2010-06-01

We use the Ulam method to study spectral properties of the Perron-Frobenius operators of dynamical maps in a chaotic regime. For maps with absorption we show numerically that the spectrum is characterized by the fractal Weyl law recently established for nonunitary operators describing poles of quantum chaotic scattering with the Weyl exponent ν = d-1, where d is the fractal dimension of corresponding strange set of trajectories nonescaping in future times. In contrast, for dissipative maps we numerically find the Weyl exponent ν = d/2 where d is the fractal dimension of strange attractor. The Weyl exponent can be also expressed via the relation ν = d0/2 where d0 is the fractal dimension of the invariant sets. We also discuss the properties of eigenvalues and eigenvectors of such operators characterized by the fractal Weyl law.

Partitioning sparse matrices with eigenvectors of graphs

NASA Technical Reports Server (NTRS)

Pothen, Alex; Simon, Horst D.; Liou, Kang-Pu

1990-01-01

The problem of computing a small vertex separator in a graph arises in the context of computing a good ordering for the parallel factorization of sparse, symmetric matrices. An algebraic approach for computing vertex separators is considered in this paper. It is shown that lower bounds on separator sizes can be obtained in terms of the eigenvalues of the Laplacian matrix associated with a graph. The Laplacian eigenvectors of grid graphs can be computed from Kronecker products involving the eigenvectors of path graphs, and these eigenvectors can be used to compute good separators in grid graphs. A heuristic algorithm is designed to compute a vertex separator in a general graph by first computing an edge separator in the graph from an eigenvector of the Laplacian matrix, and then using a maximum matching in a subgraph to compute the vertex separator. Results on the quality of the separators computed by the spectral algorithm are presented, and these are compared with separators obtained from other algorithms for computing separators. Finally, the time required to compute the Laplacian eigenvector is reported, and the accuracy with which the eigenvector must be computed to obtain good separators is considered. The spectral algorithm has the advantage that it can be implemented on a medium-size multiprocessor in a straightforward manner.

Social network analysis of Iranian researchers in the field of violence.

PubMed

Salamati, Payman; Soheili, Faramarz

2016-10-01

The social network analysis (SNA) is a paradigm for analyzing structural patterns in social re- lations, testing knowledge sharing process and identifying bottlenecks of information flow. The purpose of this study was to determine the status of research in the fleld of violence in Iran using SNA. Research population included all the papers with at least one Iranian affiliation published in violence fleld indexed in SCIE, PubMed and Scopus databases. The co-word maps, co-authorship network and structural holes were drawn using related software. In the next step, the active authors and some measures of our network including degree centrality (DC), closeness, eigenvector, betweeness, density, diameter, compactness and size of the main component were assessed. Likewise, the trend of the published articles was evaluated based on the number of documents and their citations from 1972 to 2014. Five hundred and seventy one records were obtained. The five main clusters and hot spots were mental health, violence, war, psychiatric disorders and suicide. The co-authorship network was complex, tangled and scale free. The top nine authors with cut point role and top ten active authors were identified. The mean (standard deviation) of normalized DC, closeness, eigenvector and betweeness were 0.449 (0.805), 0.609 (0.214), 2.373 (7.353) and 0.338 (1.122), respectively. The density, diameter and mean compactness of our co-authorship network were 0.0494, 3.955 and 0.125, respectively. The main component consisted of 216 nodes that formed 17% of total size of the network. Both the number of the documents and their citations has increased in the field of violence in the recent years. Although the number of the documents has recently increased in the field of violence, the information flow is slow and there are not many relations among the authors in the network. However, the active authors have ability to influence the flow of knowledge within the network.

Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors

NASA Astrophysics Data System (ADS)

Chen, Xiang; Li, Jingchao; Han, Hui; Ying, Yulong

2018-05-01

Because of the limitations of the traditional fractal box-counting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension eigenvector algorithm is proposed. First, the radiation source signal was preprocessed, and a Hilbert transform was performed to obtain the instantaneous amplitude of the signal. Then, the improved fractal box-counting dimension of the signal instantaneous amplitude was extracted as the first eigenvector. At the same time, the improved fractal box-counting dimension of the signal without the Hilbert transform was extracted as the second eigenvector. Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the grey relation algorithm. The experimental results show that, compared with the traditional fractal box-counting dimension algorithm and the single improved fractal box-counting dimension algorithm, the proposed dual improved fractal box-counting dimension algorithm can better extract the signal subtle distribution characteristics under different reconstruction phase space, and has a better recognition effect with good real-time performance.

A new method for computation of eigenvector derivatives with distinct and repeated eigenvalues in structural dynamic analysis

NASA Astrophysics Data System (ADS)

Li, Zhengguang; Lai, Siu-Kai; Wu, Baisheng

2018-07-01

Determining eigenvector derivatives is a challenging task due to the singularity of the coefficient matrices of the governing equations, especially for those structural dynamic systems with repeated eigenvalues. An effective strategy is proposed to construct a non-singular coefficient matrix, which can be directly used to obtain the eigenvector derivatives with distinct and repeated eigenvalues. This approach also has an advantage that only requires eigenvalues and eigenvectors of interest, without solving the particular solutions of eigenvector derivatives. The Symmetric Quasi-Minimal Residual (SQMR) method is then adopted to solve the governing equations, only the existing factored (shifted) stiffness matrix from an iterative eigensolution such as the subspace iteration method or the Lanczos algorithm is utilized. The present method can deal with both cases of simple and repeated eigenvalues in a unified manner. Three numerical examples are given to illustrate the accuracy and validity of the proposed algorithm. Highly accurate approximations to the eigenvector derivatives are obtained within a few iteration steps, making a significant reduction of the computational effort. This method can be incorporated into a coupled eigensolver/derivative software module. In particular, it is applicable for finite element models with large sparse matrices.

Identifying the starting point of a spreading process in complex networks.

PubMed

Comin, Cesar Henrique; Costa, Luciano da Fontoura

2011-11-01

When dealing with the dissemination of epidemics, one important question that can be asked is the location where the contamination began. In this paper, we analyze three spreading schemes and propose and validate an effective methodology for the identification of the source nodes. The method is based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness, and eigenvector centrality. We show that the source node tends to have the highest measurement values. The potential of the methodology is illustrated with respect to three theoretical complex network models as well as a real-world network, the email network of the University Rovira i Virgili.

Those Do What? Connecting Eigenvectors and Eigenvalues to the Rest of Linear Algebra: Using Visual Enhancements to Help Students Connect Eigenvectors to the Rest of Linear Algebra

ERIC Educational Resources Information Center

Nyman, Melvin A.; Lapp, Douglas A.; St. John, Dennis; Berry, John S.

2010-01-01

This paper discusses student difficulties in grasping concepts from Linear Algebra--in particular, the connection of eigenvalues and eigenvectors to other important topics in linear algebra. Based on our prior observations from student interviews, we propose technology-enhanced instructional approaches that might positively impact student…

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows.

PubMed

Savegnago, R P; Rosa, G J M; Valente, B D; Herrera, L G G; Carneiro, R L R; Sesana, R C; El Faro, L; Munari, D P

2013-01-01

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1984-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1985-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The fulll state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system remain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Elastic Model Transitions: A Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

NASA Technical Reports Server (NTRS)

Hannan, Mike R.; Jurenko, Robert J.; Bush, Jason; Ottander, John

2014-01-01

A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes a hybrid approach for determining physical displacements by augmenting the original quadratically constrained least squares (LSQI) algorithm with Direct Shape Mapping (DSM) and modifying the energy constraints. The approach presented is applicable to simulation of the elastic behavior of launch vehicles and other structures that utilize discrete LTI finite element model (FEM) derived mode sets (eigenvalues and eigenvectors) that are propagated throughout time. The time invariant nature of the elastic data presents a problem of how to properly transition elastic states from the prior to the new model while preserving motion across the transition and ensuring there is no truncation or excitation of the system. A previous approach utilizes a LSQI algorithm with an energy constraint to effect smooth transitions between eigenvector sets with no requirement that the models be of similar dimension or have any correlation. This approach assumes energy is conserved across the transition, which results in significant non-physical transients due to changing quasi-steady state energy between mode sets, a phenomenon seen when utilizing a truncated mode set. The computational burden of simulating a full mode set is significant so a subset of modes is often selected to reduce run time. As a result of this truncation, energy between mode sets may not be constant and solutions across transitions could produce non-physical transients. In an effort to abate these transients an improved methodology was developed based on the aforementioned approach, but this new approach can handle significant changes in energy across mode set transitions. It is proposed that physical velocities due to elastic behavior be solved for using the LSQI algorithm, but solve for displacements using a two-step process that independently addresses the quasi-steady-state and non-steady-state contributions to the elastic displacement. For structures subject to large external forces, such as thrust or atmospheric drag, it is imperative to capture these forces when solving for elastic displacement. To simplify the mathematical formulation, assumptions are made regarding mass matrix normalization, constant external forcing, and constant viscous damping. These simplifications allow for direct solutions to the quasi-steady-state displacements through a process titled Direct Shape Mapping. DSM solves for the displacements using the eigenvalues of the elastic modes and the external forcing and returns a set of elastic displacements dictated by the eigenvectors of the post-transition mode set. For the non-steady-state contributions to displacement we formulate a LSQI problem that is constrained by energy of the non-steady state terms. The contributions from the quasi-steady-state and non-steady state solutions are then combined to obtain the physical displacements associated with the new set of eigenvectors. Results for the LSQI-DSM approach show significant reduction/complete removal of transients across mode set transitions while maintaining elastic motion from the prior state. For time propagation applications employing discrete elastic models that need to be transitioned in time and where running with full a full mode set is not feasible, the method developed offers a practical solution to simulating vehicle elasticity.

Graph edit distance from spectral seriation.

PubMed

Robles-Kelly, Antonio; Hancock, Edwin R

2005-03-01

This paper is concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that they lack some of the formality and rigor of the computation of string edit distance. Hence, our aim is to convert graphs to string sequences so that string matching techniques can be used. To do this, we use a graph spectral seriation method to convert the adjacency matrix into a string or sequence order. We show how the serial ordering can be established using the leading eigenvector of the graph adjacency matrix. We pose the problem of graph-matching as a maximum a posteriori probability (MAP) alignment of the seriation sequences for pairs of graphs. This treatment leads to an expression in which the edit cost is the negative logarithm of the a posteriori sequence alignment probability. We compute the edit distance by finding the sequence of string edit operations which minimizes the cost of the path traversing the edit lattice. The edit costs are determined by the components of the leading eigenvectors of the adjacency matrix and by the edge densities of the graphs being matched. We demonstrate the utility of the edit distance on a number of graph clustering problems.

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

Dhou, S; Cai, W; Hurwitz, M

Purpose: The goal of this study is to quantify the interfraction reproducibility of patient-specific motion models derived from 4DCBCT acquired on the day of treatment of lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived from patient 4DCBCT images acquired daily over 3–5 fractions of treatment by 1) applying deformable image registration between each 4DCBCT image and a reference phase from that day, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs to derive a motion model. The motion model from the first day of treatment ismore » compared to motion models from each successive day of treatment to quantify variability in motion models generated from different days. Four SBRT patient datasets have been acquired thus far in this IRB approved study. Results: Fraction-specific motion models for each fraction and patient were derived and PCA eigenvectors and their associated eigenvalues are compared for each fraction. For the first patient dataset, the average root mean square error between the first two eigenvectors associated with the highest two eigenvalues, in four fractions was 0.1, while it was 0.25 between the last three PCA eigenvectors associated with the lowest three eigenvalues. It was found that the eigenvectors and eigenvalues of PCA motion models for each treatment fraction have variations and the first few eigenvectors are shown to be more stable across treatment fractions than others. Conclusion: Analysis of this dataset showed that the first two eigenvectors of the PCA patient-specific motion models derived from 4DCBCT were stable over the course of several treatment fractions. The third, fourth, and fifth eigenvectors had larger variations.« less

Exact Solution of the Markov Propagator for the Voter Model on the Complete Graph

DTIC Science & Technology

2014-07-01

distribution of the random walk. This process can also be applied to other models, incomplete graphs, or to multiple dimensions. An advantage of this...since any multiple of an eigenvector remains an eigenvector. Without any loss, let bk = 1. Now we can ascertain the explicit solution for bj when k < j...this bound is valid for all initial probability distributions. However, without detailed information about the eigenvectors, we cannot extract more

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

PubMed

Bansal, Ravi; Hao, Xuejun; Peterson, Bradley S

2015-05-01

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology using DTI data from a different set of 20 healthy adults (10 males, mean age 29.7 ± 7.7 years). The PCA identified portions of structures that covaried across the brain, the eigenvalues measuring the magnitude of the covariation in morphology along the respective eigenvectors. Our results showed that the eigenvectors, and the DTI fibers tracked from their associated brain regions, corresponded with known neural pathways in the brain. In addition, the eigenvectors that captured morphological covariation across regions, and the principal components along those eigenvectors, identified neural pathways with aberrant morphological features associated with TS. These findings suggest that covariations in brain morphology can identify aberrant neural pathways in specific neuropsychiatric disorders. Copyright © 2015. Published by Elsevier Inc.

A tale of two Bethe ansätze

NASA Astrophysics Data System (ADS)

Lima-Santos, Antonio; Nepomechie, Rafael I.; Pimenta, Rodrigo A.

2018-04-01

We revisit the construction of the eigenvectors of the single and double-row transfer matrices associated with the Zamolodchikov–Fateev model, within the algebraic Bethe ansatz method. The left and right eigenvectors are constructed using two different methods: the fusion technique and Tarasov’s construction. A simple explicit relation between the eigenvectors from the two Bethe ansätze is obtained. As a consequence, we obtain the Slavnov formula for the scalar product between on-shell and off-shell Tarasov–Bethe vectors.

SU-C-BRA-07: Variability of Patient-Specific Motion Models Derived Using Different Deformable Image Registration Algorithms for Lung Cancer Stereotactic Body Radiotherapy (SBRT) Patients

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

Dhou, S; Williams, C; Ionascu, D

2016-06-15

Purpose: To study the variability of patient-specific motion models derived from 4-dimensional CT (4DCT) images using different deformable image registration (DIR) algorithms for lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived by 1) applying DIR between each 4DCT image and a reference image, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs, resulting in a motion model (a set of eigenvectors capturing the variations in the DVFs). Three DIR algorithms were used: 1) Demons, 2) Horn-Schunck, and 3) iterative optical flow. The motion models derived weremore » compared using patient 4DCT scans. Results: Motion models were derived and the variations were evaluated according to three criteria: 1) the average root mean square (RMS) difference which measures the absolute difference between the components of the eigenvectors, 2) the dot product between the eigenvectors which measures the angular difference between the eigenvectors in space, and 3) the Euclidean Model Norm (EMN), which is calculated by summing the dot products of an eigenvector with the first three eigenvectors from the reference motion model in quadrature. EMN measures how well an eigenvector can be reconstructed using another motion model derived using a different DIR algorithm. Results showed that comparing to a reference motion model (derived using the Demons algorithm), the eigenvectors of the motion model derived using the iterative optical flow algorithm has smaller RMS, larger dot product, and larger EMN values than those of the motion model derived using Horn-Schunck algorithm. Conclusion: The study showed that motion models vary depending on which DIR algorithms were used to derive them. The choice of a DIR algorithm may affect the accuracy of the resulting model, and it is important to assess the suitability of the algorithm chosen for a particular application. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc, Palo Alto, CA.« less

A comparison of two central difference schemes for solving the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Maksymiuk, C. M.; Swanson, R. C.; Pulliam, T. H.

1990-01-01

Five viscous transonic airfoil cases were computed by two significantly different computational fluid dynamics codes: An explicit finite-volume algorithm with multigrid, and an implicit finite-difference approximate-factorization method with Eigenvector diagonalization. Both methods are described in detail, and their performance on the test cases is compared. The codes utilized the same grids, turbulence model, and computer to provide the truest test of the algorithms. The two approaches produce very similar results, which, for attached flows, also agree well with experimental results; however, the explicit code is considerably faster.

Analysis of complex network performance and heuristic node removal strategies

NASA Astrophysics Data System (ADS)

Jahanpour, Ehsan; Chen, Xin

2013-12-01

Removing important nodes from complex networks is a great challenge in fighting against criminal organizations and preventing disease outbreaks. Six network performance metrics, including four new metrics, are applied to quantify networks' diffusion speed, diffusion scale, homogeneity, and diameter. In order to efficiently identify nodes whose removal maximally destroys a network, i.e., minimizes network performance, ten structured heuristic node removal strategies are designed using different node centrality metrics including degree, betweenness, reciprocal closeness, complement-derived closeness, and eigenvector centrality. These strategies are applied to remove nodes from the September 11, 2001 hijackers' network, and their performance are compared to that of a random strategy, which removes randomly selected nodes, and the locally optimal solution (LOS), which removes nodes to minimize network performance at each step. The computational complexity of the 11 strategies and LOS is also analyzed. Results show that the node removal strategies using degree and betweenness centralities are more efficient than other strategies.

Fixed Eigenvector Analysis of Thermographic NDE Data

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Winfree, William P.

2011-01-01

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. This paper will discuss an alternative method of analysis that has been developed where a predetermined set of eigenvectors is used to process the thermal data from both reinforced carbon-carbon (RCC) and graphiteepoxy honeycomb materials. These eigenvectors can be generated either from an analytic model of the thermal response of the material system under examination, or from a large set of experimental data. This paper provides the details of the analytic model, an overview of the PCA process, as well as a quantitative signal-to-noise comparison of the results of performing both conventional PCA and fixed eigenvector analysis on thermographic data from two specimens, one Reinforced Carbon-Carbon with flat bottom holes and the second a sandwich construction with graphite-epoxy face sheets and aluminum honeycomb core.

Age-related functional brain changes in young children.

PubMed

Long, Xiangyu; Benischek, Alina; Dewey, Deborah; Lebel, Catherine

2017-07-15

Brain function and structure change significantly during the toddler and preschool years. However, most studies focus on older or younger children, so the specific nature of these changes is unclear. In the present study, we analyzed 77 functional magnetic resonance imaging datasets from 44 children aged 2-6 years. We extracted measures of both local (amplitude of low frequency fluctuation and regional homogeneity) and global (eigenvector centrality mapping) activity and connectivity, and examined their relationships with age using robust linear correlation analysis and strict control for head motion. Brain areas within the default mode network and the frontoparietal network, such as the middle frontal gyrus, the inferior parietal lobule and the posterior cingulate cortex, showed increases in local and global functional features with age. Several brain areas such as the superior parietal lobule and superior temporal gyrus presented opposite development trajectories of local and global functional features, suggesting a shifting connectivity framework in early childhood. This development of functional connectivity in early childhood likely underlies major advances in cognitive abilities, including language and development of theory of mind. These findings provide important insight into the development patterns of brain function during the preschool years, and lay the foundation for future studies of altered brain development in young children with brain disorders or injury. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatial orientation of the vestibular system

NASA Technical Reports Server (NTRS)

Raphan, T.; Dai, M.; Cohen, B.

1992-01-01

1. A simplified three-dimensional state space model of visual vestibular interaction was formulated. Matrix and dynamical system operators representing coupling from the semicircular canals and the visual system to the velocity storage integrator were incorporated into the model. 2. It was postulated that the system matrix for a tilted position was a composition of two linear transformations of the system matrix for the upright position. One transformation modifies the eigenvalues of the system matrix while another rotates the pitch and roll eigenvectors with the head, while maintaining the yaw axis eigenvector approximately spatially invariant. Using this representation, the response characteristics of the pitch, roll, and yaw eye velocity were obtained in terms of the eigenvalues and associated eigenvectors. 3. Using OKAN data obtained from monkeys and comparing to the model predictions, the eigenvalues and eigenvectors of the system matrix were identified as a function of tilt to the side or of tilt to the prone positions, using a modification of the Marquardt algorithm. The yaw eigenvector for right-side-down tilt and for downward pitch cross-coupling was approximately 30 degrees from the spatial vertical. For the prone position, the eigenvector was computed to be approximately 20 degrees relative to the spatial vertical. For both side-down and prone positions, oblique OKN induced along eigenvector directions generated OKAN which decayed to zero along a straight line with approximately a single time constant. This was verified by a spectral analysis of the residual sequence about the straight line fit to the decaying data. The residual sequence was associated with a narrow autocorrelation function and a wide power spectrum. 4. Parameters found using the Marquardt algorithm were incorporated into the model. Diagonal matrices in a head coordinate frame were introduced to represent the direct pathway and the coupling of the visual system to the integrator. Model simulations predicted the behavior of yaw and pitch OKN and OKAN when the animal was upright, as well as the cross-coupling in the tilted position. The trajectories in velocity space were also accurately simulated. 5. There were similarities between the monkey eigenvectors and human perception of the spatial vertical. For side-down tilts and downward eye velocity cross-coupling, there was only an Aubert (A) effect. For upward eye velocity cross-coupling there were both Muller (E) and Aubert (A) effects. The mean of the eigenvectors for upward and downward eye velocities overlay human 1 x g perceptual data.(ABSTRACT TRUNCATED AT 400 WORDS).

An ensemble framework for identifying essential proteins.

PubMed

Zhang, Xue; Xiao, Wangxin; Acencio, Marcio Luis; Lemke, Ney; Wang, Xujing

2016-08-25

Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy, and the number of common predicted essential proteins by different methods is very small. In this paper, an ensemble framework is proposed which integrates gene expression data and protein-protein interaction networks (PINs). It aims to improve the prediction accuracy of basic centrality measures. The idea behind this ensemble framework is that different protein-protein interactions (PPIs) may show different contributions to protein essentiality. Five standard centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and subgraph centrality) are integrated into the ensemble framework respectively. We evaluated the performance of the proposed ensemble framework using yeast PINs and gene expression data. The results show that it can considerably improve the prediction accuracy of the five centrality measures individually. It can also remarkably increase the number of common predicted essential proteins among those predicted by each centrality measure individually and enable each centrality measure to find more low-degree essential proteins. This paper demonstrates that it is valuable to differentiate the contributions of different PPIs for identifying essential proteins based on network topological characteristics. The proposed ensemble framework is a successful paradigm to this end.

NASA Astrophysics Data System (ADS)

2018-05-01

Eigenvalues and eigenvectors, together, constitute the eigenstructure of the system. The design of vibrating systems aimed at satisfying specifications on eigenvalues and eigenvectors, which is commonly known as eigenstructure assignment, has drawn increasing interest over the recent years. The most natural mathematical framework for such problems is constituted by the inverse eigenproblems, which consist in the determination of the system model that features a desired set of eigenvalues and eigenvectors. Although such a problem is intrinsically challenging, several solutions have been proposed in the literature. The approaches to eigenstructure assignment can be basically divided into passive control and active control.

The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics.

PubMed

Shen, Dan; Shen, Haipeng; Zhu, Hongtu; Marron, J S

2016-10-01

The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal an asymptotic conical structure in critical sample eigendirections under the spike models with distinguishable (or indistinguishable) eigenvalues, when the sample size and/or the number of variables (or dimension) tend to infinity. The consistency of the sample eigenvectors relative to their population counterparts is determined by the ratio between the dimension and the product of the sample size with the spike size. When this ratio converges to a nonzero constant, the sample eigenvector converges to a cone, with a certain angle to its corresponding population eigenvector. In the High Dimension, Low Sample Size case, the angle between the sample eigenvector and its population counterpart converges to a limiting distribution. Several generalizations of the multi-spike covariance models are also explored, and additional theoretical results are presented.

Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ochilov, S.; Alam, M. S.; Bal, A.

2006-05-01

Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.

Gain weighted eigenspace assignment

NASA Technical Reports Server (NTRS)

Davidson, John B.; Andrisani, Dominick, II

1994-01-01

This report presents the development of the gain weighted eigenspace assignment methodology. This provides a designer with a systematic methodology for trading off eigenvector placement versus gain magnitudes, while still maintaining desired closed-loop eigenvalue locations. This is accomplished by forming a cost function composed of a scalar measure of error between desired and achievable eigenvectors and a scalar measure of gain magnitude, determining analytical expressions for the gradients, and solving for the optimal solution by numerical iteration. For this development the scalar measure of gain magnitude is chosen to be a weighted sum of the squares of all the individual elements of the feedback gain matrix. An example is presented to demonstrate the method. In this example, solutions yielding achievable eigenvectors close to the desired eigenvectors are obtained with significant reductions in gain magnitude compared to a solution obtained using a previously developed eigenspace (eigenstructure) assignment method.

Eigenvectors of optimal color spectra.

PubMed

Flinkman, Mika; Laamanen, Hannu; Tuomela, Jukka; Vahimaa, Pasi; Hauta-Kasari, Markku

2013-09-01

Principal component analysis (PCA) and weighted PCA were applied to spectra of optimal colors belonging to the outer surface of the object-color solid or to so-called MacAdam limits. The correlation matrix formed from this data is a circulant matrix whose biggest eigenvalue is simple and the corresponding eigenvector is constant. All other eigenvalues are double, and the eigenvectors can be expressed with trigonometric functions. Found trigonometric functions can be used as a general basis to reconstruct all possible smooth reflectance spectra. When the spectral data are weighted with an appropriate weight function, the essential part of the color information is compressed to the first three components and the shapes of the first three eigenvectors correspond to one achromatic response function and to two chromatic response functions, the latter corresponding approximately to Munsell opponent-hue directions 9YR-9B and 2BG-2R.

Balanced Centrality of Networks.

PubMed

Debono, Mark; Lauri, Josef; Sciriha, Irene

2014-01-01

There is an age-old question in all branches of network analysis. What makes an actor in a network important, courted, or sought? Both Crossley and Bonacich contend that rather than its intrinsic wealth or value, an actor's status lies in the structures of its interactions with other actors. Since pairwise relation data in a network can be stored in a two-dimensional array or matrix, graph theory and linear algebra lend themselves as great tools to gauge the centrality (interpreted as importance, power, or popularity, depending on the purpose of the network) of each actor. We express known and new centralities in terms of only two matrices associated with the network. We show that derivations of these expressions can be handled exclusively through the main eigenvectors (not orthogonal to the all-one vector) associated with the adjacency matrix. We also propose a centrality vector (SWIPD) which is a linear combination of the square, walk, power, and degree centrality vectors with weightings of the various centralities depending on the purpose of the network. By comparing actors' scores for various weightings, a clear understanding of which actors are most central is obtained. Moreover, for threshold networks, the (SWIPD) measure turns out to be independent of the weightings.

Competitive seeds-selection in complex networks

NASA Astrophysics Data System (ADS)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2017-02-01

This paper investigates a competitive diffusion model where two competitors simultaneously select a set of nodes (seeds) in the network to influence. We focus on the problem of how to select these seeds such that, when the diffusion process terminates, a competitor can obtain more supports than its opponent. Instead of studying this problem in the game-theoretic framework as in the existing work, in this paper we design several heuristic seed-selection strategies inspired by commonly used centrality measures-Betweenness Centrality (BC), Closeness Centrality (CC), Degree Centrality (DC), Eigenvector Centrality (EC), and K-shell Centrality (KS). We mainly compare three centrality-based strategies, which have better performances in competing with the random selection strategy, through simulations on both real and artificial networks. Even though network structure varies across different networks, we find certain common trend appearing in all of these networks. Roughly speaking, BC-based strategy and DC-based strategy are better than CC-based strategy. Moreover, if a competitor adopts CC-based strategy, then BC-based strategy is a better strategy than DC-based strategy for his opponent, and the superiority of BC-based strategy decreases as the heterogeneity of the network decreases.

White matter tractography using diffusion tensor deflection.

PubMed

Lazar, Mariana; Weinstein, David M; Tsuruda, Jay S; Hasan, Khader M; Arfanakis, Konstantinos; Meyerand, M Elizabeth; Badie, Benham; Rowley, Howard A; Haughton, Victor; Field, Aaron; Alexander, Andrew L

2003-04-01

Diffusion tensor MRI provides unique directional diffusion information that can be used to estimate the patterns of white matter connectivity in the human brain. In this study, the behavior of an algorithm for white matter tractography is examined. The algorithm, called TEND, uses the entire diffusion tensor to deflect the estimated fiber trajectory. Simulations and imaging experiments on in vivo human brains were performed to investigate the behavior of the tractography algorithm. The simulations show that the deflection term is less sensitive than the major eigenvector to image noise. In the human brain imaging experiments, estimated tracts were generated in corpus callosum, corticospinal tract, internal capsule, corona radiata, superior longitudinal fasciculus, inferior longitudinal fasciculus, fronto-occipital fasciculus, and uncinate fasciculus. This approach is promising for mapping the organizational patterns of white matter in the human brain as well as mapping the relationship between major fiber trajectories and the location and extent of brain lesions. Copyright 2003 Wiley-Liss, Inc.

Computing interior eigenvalues of nonsymmetric matrices: application to three-dimensional metamaterial composites.

PubMed

Terao, Takamichi

2010-08-01

We propose a numerical method to calculate interior eigenvalues and corresponding eigenvectors for nonsymmetric matrices. Based on the subspace projection technique onto expanded Ritz subspace, it becomes possible to obtain eigenvalues and eigenvectors with sufficiently high precision. This method overcomes the difficulties of the traditional nonsymmetric Lanczos algorithm, and improves the accuracy of the obtained interior eigenvalues and eigenvectors. Using this algorithm, we investigate three-dimensional metamaterial composites consisting of positive and negative refractive index materials, and it is demonstrated that the finite-difference frequency-domain algorithm is applicable to analyze these metamaterial composites.

Parallel solution of the symmetric tridiagonal eigenproblem. Research report

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

Jessup, E.R.

1989-10-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed-memory Multiple Instruction, Multiple Data multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speed up, and accuracy. Experiments on an IPSC hypercube multiprocessor reveal that Cuppen's method ismore » the most accurate approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effect of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptions of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

Parallel solution of the symmetric tridiagonal eigenproblem

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

Jessup, E.R.

1989-01-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed memory MIMD multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues, and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speedup, and accuracy. Experiments on an iPSC hyper-cube multiprocessor reveal that Cuppen's method is the most accuratemore » approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effects of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptations of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

DUALITY IN MULTIVARIATE RECEPTOR MODEL. (R831078)

EPA Science Inventory

Multivariate receptor models are used for source apportionment of multiple observations of compositional data of air pollutants that obey mass conservation. Singular value decomposition of the data leads to two sets of eigenvectors. One set of eigenvectors spans a space in whi...

A robust multilevel simultaneous eigenvalue solver

NASA Technical Reports Server (NTRS)

Costiner, Sorin; Taasan, Shlomo

1993-01-01

Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.

Thermal Inspection of a Composite Fuselage Section Using a Fixed Eigenvector Principal Component Analysis Method

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Bolduc, Sean; Harman, Rebecca

2017-01-01

A composite fuselage aircraft forward section was inspected with flash thermography. The fuselage section is 24 feet long and approximately 8 feet in diameter. The structure is primarily configured with a composite sandwich structure of carbon fiber face sheets with a Nomex(Trademark) honeycomb core. The outer surface area was inspected. The thermal data consisted of 477 data sets totaling in size of over 227 Gigabytes. Principal component analysis (PCA) was used to process the data sets for substructure and defect detection. A fixed eigenvector approach using a global covariance matrix was used and compared to a varying eigenvector approach. The fixed eigenvector approach was demonstrated to be a practical analysis method for the detection and interpretation of various defects such as paint thickness variation, possible water intrusion damage, and delamination damage. In addition, inspection considerations are discussed including coordinate system layout, manipulation of the fuselage section, and the manual scanning technique used for full coverage.

Lateral-Directional Eigenvector Flying Qualities Guidelines for High Performance Aircraft

NASA Technical Reports Server (NTRS)

Davidson, John B.; Andrisani, Dominick, II

1996-01-01

This report presents the development of lateral-directional flying qualities guidelines with application to eigenspace (eigenstructure) assignment methods. These guidelines will assist designers in choosing eigenvectors to achieve desired closed-loop flying qualities or performing trade-offs between flying qualities and other important design requirements, such as achieving realizable gain magnitudes or desired system robustness. This has been accomplished by developing relationships between the system's eigenvectors and the roll rate and sideslip transfer functions. Using these relationships, along with constraints imposed by system dynamics, key eigenvector elements are identified and guidelines for choosing values of these elements to yield desirable flying qualities have been developed. Two guidelines are developed - one for low roll-to-sideslip ratio and one for moderate-to-high roll-to-sideslip ratio. These flying qualities guidelines are based upon the Military Standard lateral-directional coupling criteria for high performance aircraft - the roll rate oscillation criteria and the sideslip excursion criteria. Example guidelines are generated for a moderate-to-large, an intermediate, and low value of roll-to-sideslip ratio.

Statistical properties of color-signal spaces.

PubMed

Lenz, Reiner; Bui, Thanh Hai

2005-05-01

In applications of principal component analysis (PCA) it has often been observed that the eigenvector with the largest eigenvalue has only nonnegative entries when the vectors of the underlying stochastic process have only nonnegative values. This has been used to show that the coordinate vectors in PCA are all located in a cone. We prove that the nonnegativity of the first eigenvector follows from the Perron-Frobenius (and Krein-Rutman theory). Experiments show also that for stochastic processes with nonnegative signals the mean vector is often very similar to the first eigenvector. This is not true in general, but we first give a heuristical explanation why we can expect such a similarity. We then derive a connection between the dominance of the first eigenvalue and the similarity between the mean and the first eigenvector and show how to check the relative size of the first eigenvalue without actually computing it. In the last part of the paper we discuss the implication of theoretical results for multispectral color processing.

Statistical properties of color-signal spaces

NASA Astrophysics Data System (ADS)

Lenz, Reiner; Hai Bui, Thanh

2005-05-01

In applications of principal component analysis (PCA) it has often been observed that the eigenvector with the largest eigenvalue has only nonnegative entries when the vectors of the underlying stochastic process have only nonnegative values. This has been used to show that the coordinate vectors in PCA are all located in a cone. We prove that the nonnegativity of the first eigenvector follows from the Perron-Frobenius (and Krein-Rutman theory). Experiments show also that for stochastic processes with nonnegative signals the mean vector is often very similar to the first eigenvector. This is not true in general, but we first give a heuristical explanation why we can expect such a similarity. We then derive a connection between the dominance of the first eigenvalue and the similarity between the mean and the first eigenvector and show how to check the relative size of the first eigenvalue without actually computing it. In the last part of the paper we discuss the implication of theoretical results for multispectral color processing.

An O(N squared) method for computing the eigensystem of N by N symmetric tridiagonal matrices by the divide and conquer approach

NASA Technical Reports Server (NTRS)

Gill, Doron; Tadmor, Eitan

1988-01-01

An efficient method is proposed to solve the eigenproblem of N by N Symmetric Tridiagonal (ST) matrices. Unlike the standard eigensolvers which necessitate O(N cubed) operations to compute the eigenvectors of such ST matrices, the proposed method computes both the eigenvalues and eigenvectors with only O(N squared) operations. The method is based on serial implementation of the recently introduced Divide and Conquer (DC) algorithm. It exploits the fact that by O(N squared) of DC operations, one can compute the eigenvalues of N by N ST matrix and a finite number of pairs of successive rows of its eigenvector matrix. The rest of the eigenvectors--all of them or one at a time--are computed by linear three-term recurrence relations. Numerical examples are presented which demonstrate the superiority of the proposed method by saving an order of magnitude in execution time at the expense of sacrificing a few orders of accuracy.

Investigation, development and application of optimal output feedback theory. Vol. 4: Measures of eigenvalue/eigenvector sensitivity to system parameters and unmodeled dynamics

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1987-01-01

Some measures of eigenvalue and eigenvector sensitivity applicable to both continuous and discrete linear systems are developed and investigated. An infinite series representation is developed for the eigenvalues and eigenvectors of a system. The coefficients of the series are coupled, but can be obtained recursively using a nonlinear coupled vector difference equation. A new sensitivity measure is developed by considering the effects of unmodeled dynamics. It is shown that the sensitivity is high when any unmodeled eigenvalue is near a modeled eigenvalue. Using a simple example where the sensor dynamics have been neglected, it is shown that high feedback gains produce high eigenvalue/eigenvector sensitivity. The smallest singular value of the return difference is shown not to reflect eigenvalue sensitivity since it increases with the feedback gains. Using an upper bound obtained from the infinite series, a procedure to evaluate whether the sensitivity to parameter variations is within given acceptable bounds is developed and demonstrated by an example.

Optimal Landsat transforms for forest applications

NASA Technical Reports Server (NTRS)

Logan, T. L.; Strahler, A. H.

1983-01-01

Eleven transformations of data from four Landsat MSS channels were investigated to find if any of the transforms accentuated the separability of natural vegetation classes in regions of varying topographical relief. Attention was given to the divergence analysis and classification accuracy of information content of the eleven transforms and four channels. A useful scaling function was observed with the second eigenvector being the denominator in the divergence values obtained. The second eigenvector was found to reduce the effects of shadowing and differential illumination of vegetation signatures, thereby enhancing the divergence values. The highest accuracies in crop identification were provided by the averages of channels 4, 6, and 7 divided by the second eigenvector.

The right friends in the right places: Understanding network structure as a predictor of voluntary turnover.

PubMed

Ballinger, Gary A; Cross, Rob; Holtom, Brooks C

2016-04-01

Research examining the relationship between social networks and employee retention has focused almost exclusively on the number of direct links and generally found that having more ties decreases the likelihood of turnover. The present research moves beyond simple measures of network centrality to investigate the relationship between 2 additional, and theoretically distinct, facets of social capital and voluntary turnover. In 2 organizations, we found consistent evidence of a negative relationship between reputation, as measured by relationships with highly sought-out others (incoming eigenvector centrality) and voluntary turnover. Further, we found that the negative relationship between brokerage (structural holes) and turnover is significant, but only for higher-level employees. The theoretical and practical implications of expanding the suite of social capital measures to understand voluntary turnover are discussed. (c) 2016 APA, all rights reserved).

An accelerated subspace iteration for eigenvector derivatives

NASA Technical Reports Server (NTRS)

Ting, Tienko

1991-01-01

An accelerated subspace iteration method for calculating eigenvector derivatives has been developed. Factors affecting the effectiveness and the reliability of the subspace iteration are identified, and effective strategies concerning these factors are presented. The method has been implemented, and the results of a demonstration problem are presented.

Local or global? How to choose the training set for principal component compression of hyperspectral satellite measurements: a hybrid approach

NASA Astrophysics Data System (ADS)

Hultberg, Tim; August, Thomas; Lenti, Flavia

2017-09-01

Principal Component (PC) compression is the method of choice to achieve band-width reduction for dissemination of hyper spectral (HS) satellite measurements and will become increasingly important with the advent of future HS missions (such as IASI-NG and MTG-IRS) with ever higher data-rates. It is a linear transformation defined by a truncated set of the leading eigenvectors of the covariance of the measurements as well as the mean of the measurements. We discuss the strategy for generation of the eigenvectors, based on the operational experience made with IASI. To compute the covariance and mean, a so-called training set of measurements is needed, which ideally should include all relevant spectral features. For the dissemination of IASI PC scores a global static training set consisting of a large sample of measured spectra covering all seasons and all regions is used. This training set was updated once after the start of the dissemination of IASI PC scores in April 2010 by adding spectra from the 2010 Russian wildfires, in which spectral features not captured by the previous training set were identified. An alternative approach, which has sometimes been proposed, is to compute the eigenvectors on the fly from a local training set, for example consisting of all measurements in the current processing granule. It might naively be thought that this local approach would improve the compression rate by reducing the number of PC scores needed to represent the measurements within each granule. This false belief is apparently confirmed, if the reconstruction scores (root mean square of the reconstruction residuals) is used as the sole criteria for choosing the number of PC scores to retain, which would overlook the fact that the decrease in reconstruction score (for the same number of PCs) is achieved only by the retention of an increased amount of random noise. We demonstrate that the local eigenvectors retain a higher amount of noise and a lower amount of atmospheric signal than global eigenvectors. Local eigenvectors do not increase the compression rate, but increase the amount of atmospheric loss and should be avoided. Only extremely rare situations, resulting in spectra with features which have not been observed previously, can lead to problems for the global approach. To cope with such situations we investigate a hybrid approach, which first apply the global eigenvectors and then apply local compression to the residuals in order to identify and disseminate in addition any directions in the local signal, which are orthogonal to the subspace spanned by the global eigenvectors.

Stochastic Evolution of Augmented Born-Infeld Equations

NASA Astrophysics Data System (ADS)

Holm, Darryl D.

2018-06-01

This paper compares the results of applying a recently developed method of stochastic uncertainty quantification designed for fluid dynamics to the Born-Infeld model of nonlinear electromagnetism. The similarities in the results are striking. Namely, the introduction of Stratonovich cylindrical noise into each of their Hamiltonian formulations introduces stochastic Lie transport into their dynamics in the same form for both theories. Moreover, the resulting stochastic partial differential equations retain their unperturbed form, except for an additional term representing induced Lie transport by the set of divergence-free vector fields associated with the spatial correlations of the cylindrical noise. The explanation for this remarkable similarity lies in the method of construction of the Hamiltonian for the Stratonovich stochastic contribution to the motion in both cases, which is done via pairing spatial correlation eigenvectors for cylindrical noise with the momentum map for the deterministic motion. This momentum map is responsible for the well-known analogy between hydrodynamics and electromagnetism. The momentum map for the Maxwell and Born-Infeld theories of electromagnetism treated here is the 1-form density known as the Poynting vector. Two appendices treat the Hamiltonian structures underlying these results.

Low-dimensional Representation of Error Covariance

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; Cohn, Stephen E.; Todling, Ricardo; Marchesin, Dan

2000-01-01

Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause the steady-state analysis error covariance to admit a low-dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix, a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady-state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time-dependent systems. If much of the steady-state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady-state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting nonmodal transient growth. Failure to observe growing modes leads to increased steady-state analysis error variances. Leading eigenvectors of the steady-state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest-order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady-state analysis error covariance matrix.

The genealogical decomposition of a matrix population model with applications to the aggregation of stages.

PubMed

Bienvenu, François; Akçay, Erol; Legendre, Stéphane; McCandlish, David M

2017-06-01

Matrix projection models are a central tool in many areas of population biology. In most applications, one starts from the projection matrix to quantify the asymptotic growth rate of the population (the dominant eigenvalue), the stable stage distribution, and the reproductive values (the dominant right and left eigenvectors, respectively). Any primitive projection matrix also has an associated ergodic Markov chain that contains information about the genealogy of the population. In this paper, we show that these facts can be used to specify any matrix population model as a triple consisting of the ergodic Markov matrix, the dominant eigenvalue and one of the corresponding eigenvectors. This decomposition of the projection matrix separates properties associated with lineages from those associated with individuals. It also clarifies the relationships between many quantities commonly used to describe such models, including the relationship between eigenvalue sensitivities and elasticities. We illustrate the utility of such a decomposition by introducing a new method for aggregating classes in a matrix population model to produce a simpler model with a smaller number of classes. Unlike the standard method, our method has the advantage of preserving reproductive values and elasticities. It also has conceptually satisfying properties such as commuting with changes of units. Copyright © 2017 Elsevier Inc. All rights reserved.

Multiplex network analysis of employee performance and employee social relationships

NASA Astrophysics Data System (ADS)

Cai, Meng; Wang, Wei; Cui, Ying; Stanley, H. Eugene

2018-01-01

In human resource management, employee performance is strongly affected by both formal and informal employee networks. Most previous research on employee performance has focused on monolayer networks that can represent only single categories of employee social relationships. We study employee performance by taking into account the entire multiplex structure of underlying employee social networks. We collect three datasets consisting of five different employee relationship categories in three firms, and predict employee performance using degree centrality and eigenvector centrality in a superimposed multiplex network (SMN) and an unfolded multiplex network (UMN). We use a quadratic assignment procedure (QAP) analysis and a regression analysis to demonstrate that the different categories of relationship are mutually embedded and that the strength of their impact on employee performance differs. We also use weighted/unweighted SMN/UMN to measure the predictive accuracy of this approach and find that employees with high centrality in a weighted UMN are more likely to perform well. Our results shed new light on how social structures affect employee performance.

Motivating the Concept of Eigenvectors via Cryptography

ERIC Educational Resources Information Center

Siap, Irfan

2008-01-01

New methods of teaching linear algebra in the undergraduate curriculum have attracted much interest lately. Most of this work is focused on evaluating and discussing the integration of special computer software into the Linear Algebra curriculum. In this article, I discuss my approach on introducing the concept of eigenvectors and eigenvalues,…

Signature extraction of ocean pollutants by eigenvector transformation of remote spectra

NASA Technical Reports Server (NTRS)

Grew, G. W.

1978-01-01

Spectral signatures of suspended matter in the ocean are being extracted through characteristic vector analysis of remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor). Spectral signatures appear to be obtainable through analyses of 'linear' clusters that appear on scatter diagrams associated with eigenvectors. Signatures associated with acid waste, sewage sludge, oil, and algae are presented. The application of vector analysis to two acid waste dumps overflown two years apart is examined in some detail. The relationships between eigenvectors and spectral signatures for these examples are analyzed. These cases demonstrate the value of characteristic vector analysis in remotely identifying pollutants in the ocean and in determining the consistency of their spectral signatures.

Lines of Eigenvectors and Solutions to Systems of Linear Differential Equations

ERIC Educational Resources Information Center

Rasmussen, Chris; Keynes, Michael

2003-01-01

The purpose of this paper is to describe an instructional sequence where students invent a method for locating lines of eigenvectors and corresponding solutions to systems of two first order linear ordinary differential equations with constant coefficients. The significance of this paper is two-fold. First, it represents an innovative alternative…

Twisting singular solutions of Betheʼs equations

NASA Astrophysics Data System (ADS)

Nepomechie, Rafael I.; Wang, Chunguang

2014-12-01

The Bethe equations for the periodic XXX and XXZ spin chains admit singular solutions, for which the corresponding eigenvalues and eigenvectors are ill-defined. We use a twist regularization to derive conditions for such singular solutions to be physical, in which case they correspond to genuine eigenvalues and eigenvectors of the Hamiltonian.

A Teaching Proposal for the Study of Eigenvectors and Eigenvalues

ERIC Educational Resources Information Center

Meneu, María José Beltrán; Murillo Arcila, Marina; Jordá Mora, Enrique

2017-01-01

In this work, we present a teaching proposal which emphasizes on visualization and physical applications in the study of eigenvectors and eigenvalues. These concepts are introduced using the notion of the moment of inertia of a rigid body and the GeoGebra software. The proposal was motivated after observing students' difficulties when treating…

Emphasizing Visualization and Physical Applications in the Study of Eigenvectors and Eigenvalues

ERIC Educational Resources Information Center

BeltrÁn-Meneu, María José; Murillo-Arcila, Marina; Albarracín, Lluís

2017-01-01

This article presents a teaching proposal that emphasizes on visualization and physical applications in the study of eigenvectors and eigenvalues. More concretely, these concepts were introduced using the notion of the moment of inertia of a rigid body and the GeoGebra software. The proposal was designed after observing architecture students…

Using Dynamic Geometry Software to Explore Eigenvectors: The Emergence of Dynamic-Synthetic-Geometric Thinking

ERIC Educational Resources Information Center

Gol Tabaghi, Shiva; Sinclair, Nathalie

2013-01-01

This article analyses students' thinking as they interacted with a dynamic geometric sketch designed to explore eigenvectors and eigenvalues. We draw on the theory of instrumental genesis and, in particular, attend to the different dragging modalities used by the students throughout their explorations. Given the kinaesthetic and dynamic…

RELATIVISTIC MAGNETOHYDRODYNAMICS: RENORMALIZED EIGENVECTORS AND FULL WAVE DECOMPOSITION RIEMANN SOLVER

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

Anton, Luis; MartI, Jose M; Ibanez, Jose M

2010-05-01

We obtain renormalized sets of right and left eigenvectors of the flux vector Jacobians of the relativistic MHD equations, which are regular and span a complete basis in any physical state including degenerate ones. The renormalization procedure relies on the characterization of the degeneracy types in terms of the normal and tangential components of the magnetic field to the wave front in the fluid rest frame. Proper expressions of the renormalized eigenvectors in conserved variables are obtained through the corresponding matrix transformations. Our work completes previous analysis that present different sets of right eigenvectors for non-degenerate and degenerate states, andmore » can be seen as a relativistic generalization of earlier work performed in classical MHD. Based on the full wave decomposition (FWD) provided by the renormalized set of eigenvectors in conserved variables, we have also developed a linearized (Roe-type) Riemann solver. Extensive testing against one- and two-dimensional standard numerical problems allows us to conclude that our solver is very robust. When compared with a family of simpler solvers that avoid the knowledge of the full characteristic structure of the equations in the computation of the numerical fluxes, our solver turns out to be less diffusive than HLL and HLLC, and comparable in accuracy to the HLLD solver. The amount of operations needed by the FWD solver makes it less efficient computationally than those of the HLL family in one-dimensional problems. However, its relative efficiency increases in multidimensional simulations.« less

Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques

NASA Astrophysics Data System (ADS)

Jha, Madan K.; Chowdary, V. M.; Chowdhury, Alivia

2010-11-01

An approach is presented for the evaluation of groundwater potential using remote sensing, geographic information system, geoelectrical, and multi-criteria decision analysis techniques. The approach divides the available hydrologic and hydrogeologic data into two groups, exogenous (hydrologic) and endogenous (subsurface). A case study in Salboni Block, West Bengal (India), uses six thematic layers of exogenous parameters and four thematic layers of endogenous parameters. These thematic layers and their features were assigned suitable weights which were normalized by analytic hierarchy process and eigenvector techniques. The layers were then integrated using ArcGIS software to generate two groundwater potential maps. The hydrologic parameters-based groundwater potential zone map indicated that the `good' groundwater potential zone covers 27.14% of the area, the `moderate' zone 45.33%, and the `poor' zone 27.53%. A comparison of this map with the groundwater potential map based on subsurface parameters revealed that the hydrologic parameters-based map accurately delineates groundwater potential zones in about 59% of the area, and hence it is dependable to a certain extent. More than 80% of the study area has moderate-to-poor groundwater potential, which necessitates efficient groundwater management for long-term water security. Overall, the integrated technique is useful for the assessment of groundwater resources at a basin or sub-basin scale.

A stochastic model for correlated protein motions

NASA Astrophysics Data System (ADS)

Karain, Wael I.; Qaraeen, Nael I.; Ajarmah, Basem

2006-06-01

A one-dimensional Langevin-type stochastic difference equation is used to find the deterministic and Gaussian contributions of time series representing the projections of a Bovine Pancreatic Trypsin Inhibitor (BPTI) protein molecular dynamics simulation along different eigenvector directions determined using principal component analysis. The deterministic part shows a distinct nonlinear behavior only for eigenvectors contributing significantly to the collective protein motion.

Comparison of eigenvectors for coupled seismo-electromagnetic layered-Earth modelling

NASA Astrophysics Data System (ADS)

Grobbe, N.; Slob, E. C.; Thorbecke, J. W.

2016-07-01

We study the accuracy and numerical stability of three eigenvector sets for modelling the coupled poroelastic and electromagnetic layered-Earth response. We use a known eigenvector set, its flux-normalized version and a newly derived flux-normalized set. The new set is chosen such that the system is properly uncoupled when the coupling between the poroelastic and electromagnetic fields vanishes. We carry out two different numerical stability tests: the first test focuses on the internal system, eigenvector and eigenvalue consistency; the second test investigates the stability and preciseness of the flux-normalized systems by looking at identity relations. We find that the known set shows the largest deviation for both tests, whereas the new set performs best. In two additional numerical modelling experiments, these numerical inaccuracies are shown to generate numerical noise levels comparable to small signals, such as signals coming from the important interface conversion responses, especially when the coupling coefficient is small. When coupling vanishes completely, the known set does not produce proper results. The new set produces numerically stable and accurate results in all situations. We therefore strongly recommend to use this newly derived set for future layered-Earth seismo-electromagnetic modelling experiments.

Eigenvectors phase correction in inverse modal problem

NASA Astrophysics Data System (ADS)

Qiao, Guandong; Rahmatalla, Salam

2017-12-01

The solution of the inverse modal problem for the spatial parameters of mechanical and structural systems is heavily dependent on the quality of the modal parameters obtained from the experiments. While experimental and environmental noises will always exist during modal testing, the resulting modal parameters are expected to be corrupted with different levels of noise. A novel methodology is presented in this work to mitigate the errors in the eigenvectors when solving the inverse modal problem for the spatial parameters. The phases of the eigenvector component were utilized as design variables within an optimization problem that minimizes the difference between the calculated and experimental transfer functions. The equation of motion in terms of the modal and spatial parameters was used as a constraint in the optimization problem. Constraints that reserve the positive and semi-positive definiteness and the inter-connectivity of the spatial matrices were implemented using semi-definite programming. Numerical examples utilizing noisy eigenvectors with augmented Gaussian white noise of 1%, 5%, and 10% were used to demonstrate the efficacy of the proposed method. The results showed that the proposed method is superior when compared with a known method in the literature.

Approximate analysis for repeated eigenvalue problems with applications to controls-structure integrated design

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Hou, Gene J. W.

1994-01-01

A method for eigenvalue and eigenvector approximate analysis for the case of repeated eigenvalues with distinct first derivatives is presented. The approximate analysis method developed involves a reparameterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations to changes in the eigenvalues and the eigenvectors associated with the repeated eigenvalue problem. This work also presents a numerical technique that facilitates the definition of an eigenvector derivative for the case of repeated eigenvalues with repeated eigenvalue derivatives (of all orders). Examples are given which demonstrate the application of such equations for sensitivity and approximate analysis. Emphasis is placed on the application of sensitivity analysis to large-scale structural and controls-structures optimization problems.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach

NASA Astrophysics Data System (ADS)

Tarai, Madhumita; Kumar, Keshav; Divya, O.; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-01

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix.

A Spectral Algorithm for Envelope Reduction of Sparse Matrices

NASA Technical Reports Server (NTRS)

Barnard, Stephen T.; Pothen, Alex; Simon, Horst D.

1993-01-01

The problem of reordering a sparse symmetric matrix to reduce its envelope size is considered. A new spectral algorithm for computing an envelope-reducing reordering is obtained by associating a Laplacian matrix with the given matrix and then sorting the components of a specified eigenvector of the Laplacian. This Laplacian eigenvector solves a continuous relaxation of a discrete problem related to envelope minimization called the minimum 2-sum problem. The permutation vector computed by the spectral algorithm is a closest permutation vector to the specified Laplacian eigenvector. Numerical results show that the new reordering algorithm usually computes smaller envelope sizes than those obtained from the current standard algorithms such as Gibbs-Poole-Stockmeyer (GPS) or SPARSPAK reverse Cuthill-McKee (RCM), in some cases reducing the envelope by more than a factor of two.

Identification of Large Space Structures on Orbit

DTIC Science & Technology

1986-09-01

requires only the eigenvector corresponding to the eigenvector 93 .:. ,S --- k’.’ L derivative being calculated. However, a set of linear algebraic ...Journal of Guidance, Control and Dynamics. 204. Noble, B. and J. W. Daniel, Applied Linear Algebra , Prentice-Hall, Inc., 1977. 205. Nurre, G. S., R. S...4.2.1. Linear Relationships . . . . . . . . . . 114 4.2.2. Nonlinear Relationships . . . . . . . . . 120 4.3. Series Expansion Methods

Generalized reproduction numbers and the prediction of patterns in waterborne disease

PubMed Central

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-01-01

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix , explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number (the dominant eigenvalue of ) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of . Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections. PMID:23150538

Spatial Mapping of Translational Diffusion Coefficients Using Diffusion Tensor Imaging: A Mathematical Description

PubMed Central

SHETTY, ANIL N.; CHIANG, SHARON; MALETIC-SAVATIC, MIRJANA; KASPRIAN, GREGOR; VANNUCCI, MARINA; LEE, WESLEY

2016-01-01

In this article, we discuss the theoretical background for diffusion weighted imaging and diffusion tensor imaging. Molecular diffusion is a random process involving thermal Brownian motion. In biological tissues, the underlying microstructures restrict the diffusion of water molecules, making diffusion directionally dependent. Water diffusion in tissue is mathematically characterized by the diffusion tensor, the elements of which contain information about the magnitude and direction of diffusion and is a function of the coordinate system. Thus, it is possible to generate contrast in tissue based primarily on diffusion effects. Expressing diffusion in terms of the measured diffusion coefficient (eigenvalue) in any one direction can lead to errors. Nowhere is this more evident than in white matter, due to the preferential orientation of myelin fibers. The directional dependency is removed by diagonalization of the diffusion tensor, which then yields a set of three eigenvalues and eigenvectors, representing the magnitude and direction of the three orthogonal axes of the diffusion ellipsoid, respectively. For example, the eigenvalue corresponding to the eigenvector along the long axis of the fiber corresponds qualitatively to diffusion with least restriction. Determination of the principal values of the diffusion tensor and various anisotropic indices provides structural information. We review the use of diffusion measurements using the modified Stejskal–Tanner diffusion equation. The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor. We further describe diffusion tensor properties in visualizing fiber tract organization of the human brain. PMID:27441031

Random matrix approach to cross correlations in financial data

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki; Gopikrishnan, Parameswaran; Rosenow, Bernd; Amaral, Luís A.; Guhr, Thomas; Stanley, H. Eugene

2002-06-01

We analyze cross correlations between price fluctuations of different stocks using methods of random matrix theory (RMT). Using two large databases, we calculate cross-correlation matrices C of returns constructed from (i) 30-min returns of 1000 US stocks for the 2-yr period 1994-1995, (ii) 30-min returns of 881 US stocks for the 2-yr period 1996-1997, and (iii) 1-day returns of 422 US stocks for the 35-yr period 1962-1996. We test the statistics of the eigenvalues λi of C against a ``null hypothesis'' - a random correlation matrix constructed from mutually uncorrelated time series. We find that a majority of the eigenvalues of C fall within the RMT bounds [λ-,λ+] for the eigenvalues of random correlation matrices. We test the eigenvalues of C within the RMT bound for universal properties of random matrices and find good agreement with the results for the Gaussian orthogonal ensemble of random matrices-implying a large degree of randomness in the measured cross-correlation coefficients. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the eigenvalues outside the RMT bound display systematic deviations from the RMT prediction. In addition, we find that these ``deviating eigenvectors'' are stable in time. We analyze the components of the deviating eigenvectors and find that the largest eigenvalue corresponds to an influence common to all stocks. Our analysis of the remaining deviating eigenvectors shows distinct groups, whose identities correspond to conventionally identified business sectors. Finally, we discuss applications to the construction of portfolios of stocks that have a stable ratio of risk to return.

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach.

PubMed

Tarai, Madhumita; Kumar, Keshav; Divya, O; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-05

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix. Copyright © 2017 Elsevier B.V. All rights reserved.

PLUS highway network analysis: Case of in-coming traffic burden in 2013

NASA Astrophysics Data System (ADS)

Asrah, Norhaidah Mohd; Djauhari, Maman Abdurachman; Mohamad, Ismail

2017-05-01

PLUS highway is the largest concessionary in Malaysia. The study on PLUS highway development, in order to overcome the demand for efficient road transportation, is crucial. If the highways have better interconnected network, it will help the economic activities such as trade to increase. If economic activities are increasing, the benefit will come to the people and state. In its turn, it will help the leaders to plan and conduct national development program. In this paper, network analysis approach will be used to study the in-coming traffic burden during the year of 2013. The highway network linking all the toll plazas is a dynamic network. The objective of this study is to learn and understand about highway network in terms of the in-coming traffic burden entering to each toll plazas along PLUS highway. For this purpose, the filtered network topology based on the forest of all possible minimum spanning trees is used. The in-coming traffic burden of a city is represented by the number of cars passing through the corresponding toll plaza. To interpret the filtered network, centrality measures such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality are used. An overall centrality will be proposed if those four measures are assumed to have the same role. Based on the results, some suggestions and recommendations for PLUS highway network development will be delivered to PLUS highway management.

Numerical Aspects of Eigenvalue and Eigenfunction Computations for Chaotic Quantum Systems

NASA Astrophysics Data System (ADS)

Bäcker, A.

Summary: We give an introduction to some of the numerical aspects in quantum chaos. The classical dynamics of two-dimensional area-preserving maps on the torus is illustrated using the standard map and a perturbed cat map. The quantization of area-preserving maps given by their generating function is discussed and for the computation of the eigenvalues a computer program in Python is presented. We illustrate the eigenvalue distribution for two types of perturbed cat maps, one leading to COE and the other to CUE statistics. For the eigenfunctions of quantum maps we study the distribution of the eigenvectors and compare them with the corresponding random matrix distributions. The Husimi representation allows for a direct comparison of the localization of the eigenstates in phase space with the corresponding classical structures. Examples for a perturbed cat map and the standard map with different parameters are shown. Billiard systems and the corresponding quantum billiards are another important class of systems (which are also relevant to applications, for example in mesoscopic physics). We provide a detailed exposition of the boundary integral method, which is one important method to determine the eigenvalues and eigenfunctions of the Helmholtz equation. We discuss several methods to determine the eigenvalues from the Fredholm equation and illustrate them for the stadium billiard. The occurrence of spurious solutions is discussed in detail and illustrated for the circular billiard, the stadium billiard, and the annular sector billiard. We emphasize the role of the normal derivative function to compute the normalization of eigenfunctions, momentum representations or autocorrelation functions in a very efficient and direct way. Some examples for these quantities are given and discussed.

A Family of Algorithms for Computing Consensus about Node State from Network Data

PubMed Central

Brush, Eleanor R.; Krakauer, David C.; Flack, Jessica C.

2013-01-01

Biological and social networks are composed of heterogeneous nodes that contribute differentially to network structure and function. A number of algorithms have been developed to measure this variation. These algorithms have proven useful for applications that require assigning scores to individual nodes–from ranking websites to determining critical species in ecosystems–yet the mechanistic basis for why they produce good rankings remains poorly understood. We show that a unifying property of these algorithms is that they quantify consensus in the network about a node's state or capacity to perform a function. The algorithms capture consensus by either taking into account the number of a target node's direct connections, and, when the edges are weighted, the uniformity of its weighted in-degree distribution (breadth), or by measuring net flow into a target node (depth). Using data from communication, social, and biological networks we find that that how an algorithm measures consensus–through breadth or depth– impacts its ability to correctly score nodes. We also observe variation in sensitivity to source biases in interaction/adjacency matrices: errors arising from systematic error at the node level or direct manipulation of network connectivity by nodes. Our results indicate that the breadth algorithms, which are derived from information theory, correctly score nodes (assessed using independent data) and are robust to errors. However, in cases where nodes “form opinions” about other nodes using indirect information, like reputation, depth algorithms, like Eigenvector Centrality, are required. One caveat is that Eigenvector Centrality is not robust to error unless the network is transitive or assortative. In these cases the network structure allows the depth algorithms to effectively capture breadth as well as depth. Finally, we discuss the algorithms' cognitive and computational demands. This is an important consideration in systems in which individuals use the collective opinions of others to make decisions. PMID:23874167

A uniform object-oriented solution to the eigenvalue problem for real symmetric and Hermitian matrices

NASA Astrophysics Data System (ADS)

Castro, María Eugenia; Díaz, Javier; Muñoz-Caro, Camelia; Niño, Alfonso

2011-09-01

We present a system of classes, SHMatrix, to deal in a unified way with the computation of eigenvalues and eigenvectors in real symmetric and Hermitian matrices. Thus, two descendant classes, one for the real symmetric and other for the Hermitian cases, override the abstract methods defined in a base class. The use of the inheritance relationship and polymorphism allows handling objects of any descendant class using a single reference of the base class. The system of classes is intended to be the core element of more sophisticated methods to deal with large eigenvalue problems, as those arising in the variational treatment of realistic quantum mechanical problems. The present system of classes allows computing a subset of all the possible eigenvalues and, optionally, the corresponding eigenvectors. Comparison with well established solutions for analogous eigenvalue problems, as those included in LAPACK, shows that the present solution is competitive against them. Program summaryProgram title: SHMatrix Catalogue identifier: AEHZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2616 No. of bytes in distributed program, including test data, etc.: 127 312 Distribution format: tar.gz Programming language: Standard ANSI C++. Computer: PCs and workstations. Operating system: Linux, Windows. Classification: 4.8. Nature of problem: The treatment of problems involving eigensystems is a central topic in the quantum mechanical field. Here, the use of the variational approach leads to the computation of eigenvalues and eigenvectors of real symmetric and Hermitian Hamiltonian matrices. Realistic models with several degrees of freedom leads to large (sometimes very large) matrices. Different techniques, such as divide and conquer, can be used to factorize the matrices in order to apply a parallel computing approach. However, it is still interesting to have a core procedure able to tackle the computation of eigenvalues and eigenvectors once the matrix has been factorized to pieces of enough small size. Several available software packages, such as LAPACK, tackled this problem under the traditional imperative programming paradigm. In order to ease the modelling of complex quantum mechanical models it could be interesting to apply an object-oriented approach to the treatment of the eigenproblem. This approach offers the advantage of a single, uniform treatment for the real symmetric and Hermitian cases. Solution method: To reach the above goals, we have developed a system of classes: SHMatrix. SHMatrix is composed by an abstract base class and two descendant classes, one for real symmetric matrices and the other for the Hermitian case. The object-oriented characteristics of inheritance and polymorphism allows handling both cases using a single reference of the base class. The basic computing strategy applied in SHMatrix allows computing subsets of eigenvalues and (optionally) eigenvectors. The tests performed show that SHMatrix is competitive, and more efficient for large matrices, than the equivalent routines of the LAPACK package. Running time: The examples included in the distribution take only a couple of seconds to run.

Common Eigenvectors of N Particles' Compatible Observables and its Squeezing Operator

NASA Astrophysics Data System (ADS)

Xu, Shi-Min; Xu, Xing-Lei; Li, Hong-Qi

We construct 2N operators for a N-particle system, namely one center-of-mass coordinate operator, N-1 relative coordinate operators, one total momentum operator and N-1 mass-weighted relative momentum operators, and give common eigenvectors of N compatible observables \\{∑ Ni=1hat {p}i,hat {x}1-hat {x}2,hat {x}2-hat {x}3,hat {x}3-hat {x}4,...; ,hat {x}N-1-hat {x}N\\}, which are composed of N particles' coordinate hat {x}i and momentum hat {p}i. By compatible, we mean such observables can be simultaneously determined. Using the technique of integration within an ordered product of operators (IWOP), we prove that the common eigenvectors are complete and orthonormal, and hereby qualified for making up a representation. This new representation can be applied to solving some dynamic problems in quantum mechanics.

The generalized DMPK equation revisited: towards a systematic derivation

NASA Astrophysics Data System (ADS)

Douglas, Andrew; Markoš, Peter; Muttalib, K. A.

2014-03-01

The generalized Dorokov-Mello-Pereyra-Kumar (DMPK) equation has recently been used to obtain a family of very broad and highly asymmetric conductance distributions for three-dimensional disordered conductors. However, there are two major criticisms of the derivation of the generalized DMPK equation: (1) certain eigenvector correlations were neglected based on qualitative arguments that cannot be valid for all strengths of disorder, and (2) the repulsion between two closely spaced eigenvalues were not rigorously governed by symmetry considerations. In this work we show that it is possible to address both criticisms by including the eigenvalue and eigenvector correlations in a systematic and controlled way. It turns out that the added correlations determine the evolution of the Jacobian, without affecting the evaluation of the conductance distributions. They also guarantee the symmetry requirements. In addition, we obtain an exact relationship between the eigenvectors and the Lyapunov exponents leading to a sum rule for the latter at all disorder strengths.

Development of adaptive observation strategy using retrospective optimal interpolation

NASA Astrophysics Data System (ADS)

Noh, N.; Kim, S.; Song, H.; Lim, G.

2011-12-01

Retrospective optimal interpolation (ROI) is a method that is used to minimize cost functions with multiple minima without using adjoint models. Song and Lim (2011) perform the experiments to reduce the computational costs for implementing ROI by transforming the control variables into eigenvectors of background error covariance. We adapt the ROI algorithm to compute sensitivity estimates of severe weather events over the Korean peninsula. The eigenvectors of the ROI algorithm is modified every time the observations are assimilated. This implies that the modified eigenvectors shows the error distribution of control variables which are updated by assimilating observations. So, We can estimate the effects of the specific observations. In order to verify the adaptive observation strategy, High-impact weather over the Korean peninsula is simulated and interpreted using WRF modeling system and sensitive regions for each high-impact weather is calculated. The effects of assimilation for each observation type is discussed.

Analyzing Small Signal Stability of Power System based on Online Data by Use of SMES

NASA Astrophysics Data System (ADS)

Ishikawa, Hiroyuki; Shirai, Yasuyuki; Nitta, Tanzo; Shibata, Katsuhiko

The purpose of this study is to estimate eigen-values and eigen-vectors of a power system from on-line data to evaluate the power system stability. Power system responses due to the small power modulation of known pattern from SMES (Superconducting Magnetic Energy Storage) were analyzed, and the transfer functions between the power modulation and power oscillations of generators were obtained. Eigen-values and eigen-vectors were estimated from the transfer functions. Experiments were carried out by use of a model SMES and Advanced Power System Analyzer (APSA), which is an analogue type power system simulator of Kansai Electric Power Company Inc., Japan. Changes in system condition were observed by the estimated eigen-values and eigen-vectors. Result agreed well with the resent report and digital simulation. This method gives a new application for SMES, which will be installed for improving electric power quality.

The place of the Local Group in the cosmic web

NASA Astrophysics Data System (ADS)

Forero-Romero, Jaime E.; González, Roberto

2016-10-01

We use the Bolshoi Simulation to find the most probable location of the Local Group (LG) in the cosmic web. Our LG simulacra are pairs of halos with isolation and kinematic properties consistent with observations. The cosmic web is defined using a tidal tensor approach. We find that the LG's preferred location is regions with a dark matter overdensity close to the cosmic average. This makes filaments and sheets the preferred environment. We also find a strong alignment between the LG and the cosmic web. The orbital angular momentum is preferentially perpendicular to the smallest tidal eigenvector, while the vector connecting the two halos is strongly aligned along the the smallest tidal eigenvector and perpendicular to the largest tidal eigenvector; the pair lies and moves along filaments and sheets. We do not find any evidence for an alignment between the spin of each halo in the pair and the cosmic web.

Characterization of architectural distortion on mammograms using a linear energy detector

NASA Astrophysics Data System (ADS)

Alvarez, Jorge; Narváez, Fabián.; Poveda, César; Romero, Eduardo

2013-11-01

Architectural distortion is a breast cancer sign, characterized by spiculated patterns that define the disease malignancy level. In this paper, the radial spiculae of a typical architectural distortion were characterized by a new strategy. Firstly, previously selected Regions of Interest are divided into a set of parallel and disjoint bands (4 pixels the ROI length), from which intensity integrals (coefficients) are calculated. This partition is rotated every two degrees, searching in the phase plane the characteristic radial spiculation. Then, these coefficients are used to construct a fully connected graph whose edges correspond to the integral values or coefficients and the nodes to x and y image positions. A centrality measure like the first eigenvector is used to extract a set of discriminant coefficients that represent the locations with higher linear energy. Finally, the approach is trained using a set of 24 Regions of Interest obtained from the MIAS database, namely, 12 Architectural Distortions and 12 controls. The first eigenvector is then used as input to a conventional Support Vector Machine classifier whose optimal parameters were obtained by a leave-one-out cross validation. The whole method was assessed in a set of 12 RoIs with different distribution of breast tissues (normal and abnormal), and the classification results were compared against a ground truth, already provided by the data base, showing a precision rate of 0.583%, a sensitivity rate of 0.833% and a specificity rate of 0.333%.

Cosmography and Data Visualization

NASA Astrophysics Data System (ADS)

Pomarède, Daniel; Courtois, Hélène M.; Hoffman, Yehuda; Tully, R. Brent

2017-05-01

Cosmography, the study and making of maps of the universe or cosmos, is a field where visual representation benefits from modern three-dimensional visualization techniques and media. At the extragalactic distance scales, visualization is contributing to our understanding of the complex structure of the local universe in terms of spatial distribution and flows of galaxies and dark matter. In this paper, we report advances in the field of extragalactic cosmography obtained using the SDvision visualization software in the context of the Cosmicflows Project. Here, multiple visualization techniques are applied to a variety of data products: catalogs of galaxy positions and galaxy peculiar velocities, reconstructed velocity field, density field, gravitational potential field, velocity shear tensor viewed in terms of its eigenvalues and eigenvectors, envelope surfaces enclosing basins of attraction. These visualizations, implemented as high-resolution images, videos, and interactive viewers, have contributed to a number of studies: the cosmography of the local part of the universe, the nature of the Great Attractor, the discovery of the boundaries of our home supercluster of galaxies Laniakea, the mapping of the cosmic web, and the study of attractors and repellers.

Epidemic extinction paths in complex networks

NASA Astrophysics Data System (ADS)

Hindes, Jason; Schwartz, Ira B.

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

Epidemic extinction paths in complex networks.

PubMed

Hindes, Jason; Schwartz, Ira B

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

Quantum damped oscillator I: Dissipation and resonances

NASA Astrophysics Data System (ADS)

Chruściński, Dariusz; Jurkowski, Jacek

2006-04-01

Quantization of a damped harmonic oscillator leads to so called Bateman’s dual system. The corresponding Bateman’s Hamiltonian, being a self-adjoint operator, displays the discrete family of complex eigenvalues. We show that they correspond to the poles of energy eigenvectors and the corresponding resolvent operator when continued to the complex energy plane. Therefore, the corresponding generalized eigenvectors may be interpreted as resonant states which are responsible for the irreversible quantum dynamics of a damped harmonic oscillator.

Group identification in Indonesian stock market

NASA Astrophysics Data System (ADS)

Nurriyadi Suparno, Ervano; Jo, Sung Kyun; Lim, Kyuseong; Purqon, Acep; Kim, Soo Yong

2016-08-01

The characteristic of Indonesian stock market is interesting especially because it represents developing countries. We investigate the dynamics and structures by using Random Matrix Theory (RMT). Here, we analyze the cross-correlation of the fluctuations of the daily closing price of stocks from the Indonesian Stock Exchange (IDX) between January 1, 2007, and October 28, 2014. The eigenvalue distribution of the correlation matrix consists of noise which is filtered out using the random matrix as a control. The bulk of the eigenvalue distribution conforms to the random matrix, allowing the separation of random noise from original data which is the deviating eigenvalues. From the deviating eigenvalues and the corresponding eigenvectors, we identify the intrinsic normal modes of the system and interpret their meaning based on qualitative and quantitative approach. The results show that the largest eigenvector represents the market-wide effect which has a predominantly common influence toward all stocks. The other eigenvectors represent highly correlated groups within the system. Furthermore, identification of the largest components of the eigenvectors shows the sector or background of the correlated groups. Interestingly, the result shows that there are mainly two clusters within IDX, natural and non-natural resource companies. We then decompose the correlation matrix to investigate the contribution of the correlated groups to the total correlation, and we find that IDX is still driven mainly by the market-wide effect.

Random matrix theory and cross-correlations in global financial indices and local stock market indices

NASA Astrophysics Data System (ADS)

Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

2013-02-01

We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest eigenvectors of the cross-correlation matrix before, during, and after the global financial the crisis in the year 2008. We find that the majority of its eigenvalues fall within the RMT bounds [ λ -, λ +], where λ - and λ + are the lower and the upper bounds of the eigenvalues of random correlation matrices. The components of the eigenvectors for the largest positive eigenvalues indicate the identical financial market mode dominating the global and local indices. On the other hand, the components of the eigenvector corresponding to the second largest eigenvalue are positive and negative values alternatively. The components before the crisis change sign during the crisis, and those during the crisis change sign after the crisis. The largest inverse participation ratio (IPR) corresponding to the smallest eigenvector is higher after the crisis than during any other periods in the global and local indices. During the global financial the crisis, the correlations among the global indices and among the local stock indices are perturbed significantly. However, the correlations between indices quickly recover the trends before the crisis.

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

Kim, Sang Beom; Dsilva, Carmeline J.; Debenedetti, Pablo G., E-mail: pdebene@princeton.edu

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories inmore » a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.« less

BRIDGE OVER TROUBLED WATERS? THE MOST "CENTRAL" MEMBERS OF PSYCHOLOGY AND PHILOSOPHY ASSOCIATIONS CA. 1900.

PubMed

Green, Christopher D; Heidari, Crystal; Chiacchia, Daniel; Martin, Shane M

2016-07-01

There are many different ways to assess the significance of historical figures. Often we look at the influence of their writings, or at the important offices they held with disciplinary institutions such as universities, journals, and scholarly societies. In this study, however, we took a novel approach: we took the complete memberships, ca. 1900, of four organizations-the American Psychological Association, the Western Philosophical Association, the American Philosophical Association, and the Southern Society for Philosophy and Psychology-and visualized them as a network. We then identified individuals who "bridged" between two or more of these groups and considered what might be termed their "centrality" to the psychological-philosophical community of their time. First, we examined these figures qualitatively, briefly describing their lives and careers. Then we approached the problem mathematically, considering several alternative technical realizations of "centrality" and then explaining our reasons for choosing eigenvector centrality as the best for our purposes. We found a great deal of overlap among the results of the qualitative and quantitative approaches, but also some telling differences. J. Mark Baldwin, Edward Buchner, Christine Ladd Franklin, and Frank Thilly consistently emerged as highly central figures. Some more marginal figures such as Max Meyer, and Frederick J. E. Woodbridge, Edward A. Pace, Edward H. Griffin played interesting roles as well. © 2016 Wiley Periodicals, Inc.

Structural covariance network centrality in maltreated youth with posttraumatic stress disorder

PubMed Central

Sun, Delin; Peverill, Matthew R.; Swanson, Chelsea S.; McLaughlin, Katie A.; Morey, Rajendra A.

2018-01-01

Childhood maltreatment is associated with posttraumatic stress disorder (PTSD) and elevated rates of adolescent and adult psychopathology including major depression, bipolar disorder, substance use disorders, and other medical comorbidities. Gray matter volume changes have been found in maltreated youth with (versus without) PTSD. However, little is known about the alterations of brain structural covariance network topology derived from cortical thickness in maltreated youth with PTSD. High-resolution T1-weighted magnetic resonance imaging scans were from demographically matched maltreated youth with PTSD (N = 24), without PTSD (N =64), and non-maltreated healthy controls (n = 67). Cortical thickness data from 148 cortical regions was entered into interregional partial correlation analyses across participants. The supra-threshold correlations constituted connections in a structural brain network derived from four types of centrality measures (degree, betweenness, closeness, and eigenvector) estimated network topology and the importance of nodes. Between-group differences were determined by permutation testing. Maltreated youth with PTSD exhibited larger centrality in left anterior cingulate cortex than the other two groups, suggesting cortical network topology specific to maltreated youth with PTSD. Moreover, maltreated youth with versus without PTSD showed smaller centrality in right orbitofrontal cortex, suggesting that this may represent a vulnerability factor to PTSD following maltreatment. Longitudinal follow-up of the present results will help characterize the role that altered centrality plays in vulnerability and resilience to PTSD following childhood maltreatment. PMID:29294430

Finite-temperature stress calculations in atomic models using moments of position.

PubMed

Parthasarathy, Ranganathan; Misra, Anil; Ouyang, Lizhi

2018-07-04

Continuum modeling of finite temperature mechanical behavior of atomic systems requires refined description of atomic motions. In this paper, we identify additional kinematical quantities that are relevant for a more accurate continuum description as the system is subjected to step-wise loading. The presented formalism avoids the necessity for atomic trajectory mapping with deformation, provides the definitions of the kinematic variables and their conjugates in real space, and simplifies local work conjugacy. The total work done on an atom under deformation is decomposed into the work corresponding to changing its equilibrium position and work corresponding to changing its second moment about equilibrium position. Correspondingly, we define two kinematic variables: a deformation gradient tensor and a vibration tensor, and derive their stress conjugates, termed here as static and vibration stresses, respectively. The proposed approach is validated using MD simulation in NVT ensembles for fcc aluminum subjected to uniaxial extension. The observed evolution of second moments in the MD simulation with macroscopic deformation is not directly related to the transformation of atomic trajectories through the deformation gradient using generator functions. However, it is noteworthy that deformation leads to a change in the second moment of the trajectories. Correspondingly, the vibration part of the Piola stress becomes particularly significant at high temperature and high tensile strain as the crystal approaches the softening limit. In contrast to the eigenvectors of the deformation gradient, the eigenvectors of the vibration tensor show strong spatial heterogeneity in the vicinity of softening. More importantly, the elliptic distribution of local atomic density transitions to a dumbbell shape, before significant non-affinity in equilibrium positions has occurred.

Finite-temperature stress calculations in atomic models using moments of position

NASA Astrophysics Data System (ADS)

Parthasarathy, Ranganathan; Misra, Anil; Ouyang, Lizhi

2018-07-01

Continuum modeling of finite temperature mechanical behavior of atomic systems requires refined description of atomic motions. In this paper, we identify additional kinematical quantities that are relevant for a more accurate continuum description as the system is subjected to step-wise loading. The presented formalism avoids the necessity for atomic trajectory mapping with deformation, provides the definitions of the kinematic variables and their conjugates in real space, and simplifies local work conjugacy. The total work done on an atom under deformation is decomposed into the work corresponding to changing its equilibrium position and work corresponding to changing its second moment about equilibrium position. Correspondingly, we define two kinematic variables: a deformation gradient tensor and a vibration tensor, and derive their stress conjugates, termed here as static and vibration stresses, respectively. The proposed approach is validated using MD simulation in NVT ensembles for fcc aluminum subjected to uniaxial extension. The observed evolution of second moments in the MD simulation with macroscopic deformation is not directly related to the transformation of atomic trajectories through the deformation gradient using generator functions. However, it is noteworthy that deformation leads to a change in the second moment of the trajectories. Correspondingly, the vibration part of the Piola stress becomes particularly significant at high temperature and high tensile strain as the crystal approaches the softening limit. In contrast to the eigenvectors of the deformation gradient, the eigenvectors of the vibration tensor show strong spatial heterogeneity in the vicinity of softening. More importantly, the elliptic distribution of local atomic density transitions to a dumbbell shape, before significant non-affinity in equilibrium positions has occurred.

Cucheb: A GPU implementation of the filtered Lanczos procedure

NASA Astrophysics Data System (ADS)

Aurentz, Jared L.; Kalantzis, Vassilis; Saad, Yousef

2017-11-01

This paper describes the software package Cucheb, a GPU implementation of the filtered Lanczos procedure for the solution of large sparse symmetric eigenvalue problems. The filtered Lanczos procedure uses a carefully chosen polynomial spectral transformation to accelerate convergence of the Lanczos method when computing eigenvalues within a desired interval. This method has proven particularly effective for eigenvalue problems that arise in electronic structure calculations and density functional theory. We compare our implementation against an equivalent CPU implementation and show that using the GPU can reduce the computation time by more than a factor of 10. Program Summary Program title: Cucheb Program Files doi:http://dx.doi.org/10.17632/rjr9tzchmh.1 Licensing provisions: MIT Programming language: CUDA C/C++ Nature of problem: Electronic structure calculations require the computation of all eigenvalue-eigenvector pairs of a symmetric matrix that lie inside a user-defined real interval. Solution method: To compute all the eigenvalues within a given interval a polynomial spectral transformation is constructed that maps the desired eigenvalues of the original matrix to the exterior of the spectrum of the transformed matrix. The Lanczos method is then used to compute the desired eigenvectors of the transformed matrix, which are then used to recover the desired eigenvalues of the original matrix. The bulk of the operations are executed in parallel using a graphics processing unit (GPU). Runtime: Variable, depending on the number of eigenvalues sought and the size and sparsity of the matrix. Additional comments: Cucheb is compatible with CUDA Toolkit v7.0 or greater.

Generalized reproduction numbers and the prediction of patterns in waterborne disease.

PubMed

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-11-27

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0, explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Network-Centric Interventions to Contain the Syphilis Epidemic in San Francisco.

PubMed

Juher, David; Saldaña, Joan; Kohn, Robert; Bernstein, Kyle; Scoglio, Caterina

2017-07-25

The number of reported early syphilis cases in San Francisco has increased steadily since 2005. It is not yet clear what factors are responsible for such an increase. A recent analysis of the sexual contact network of men who have sex with men with syphilis in San Francisco has discovered a large connected component, members of which have a significantly higher chance of syphilis and HIV compared to non-member individuals. This study investigates whether it is possible to exploit the existence of the largest connected component to design new notification strategies that can potentially contribute to reducing the number of cases. We develop a model capable of incorporating multiple types of notification strategies and compare the corresponding incidence of syphilis. Through extensive simulations, we show that notifying the community of the infection state of few central nodes appears to be the most effective approach, balancing the cost of notification and the reduction of syphilis incidence. Additionally, among the different measures of centrality, the eigenvector centrality reveals to be the best to reduce the incidence in the long term as long as the number of missing links (non-disclosed contacts) is not very large.

Non-isospectral Hamiltonians, intertwining operators and hidden hermiticity

NASA Astrophysics Data System (ADS)

Bagarello, F.

2011-12-01

We have recently proposed a strategy to produce, starting from a given Hamiltonian h and a certain operator x for which [h,xx]=0 and xx is invertible, a second Hamiltonian h with the same eigenvalues as h and whose eigenvectors are related to those of h by x. Here we extend this procedure to build up a second Hamiltonian, whose eigenvalues are different from those of h, and whose eigenvectors are still related as before. This new procedure is also extended to crypto-hermitian Hamiltonians.

Elastic Model Transitions Using Quadratic Inequality Constrained Least Squares

NASA Technical Reports Server (NTRS)

Orr, Jeb S.

2012-01-01

A technique is presented for initializing multiple discrete finite element model (FEM) mode sets for certain types of flight dynamics formulations that rely on superposition of orthogonal modes for modeling the elastic response. Such approaches are commonly used for modeling launch vehicle dynamics, and challenges arise due to the rapidly time-varying nature of the rigid-body and elastic characteristics. By way of an energy argument, a quadratic inequality constrained least squares (LSQI) algorithm is employed to e ect a smooth transition from one set of FEM eigenvectors to another with no requirement that the models be of similar dimension or that the eigenvectors be correlated in any particular way. The physically unrealistic and controversial method of eigenvector interpolation is completely avoided, and the discrete solution approximates that of the continuously varying system. The real-time computational burden is shown to be negligible due to convenient features of the solution method. Simulation results are presented, and applications to staging and other discontinuous mass changes are discussed

Characterizing Aeroelastic Systems Using Eigenanalysis, Explicitly Retaining The Aerodynamic Degrees of Freedom

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Dowell, Earl H.

2001-01-01

Discrete time aeroelastic models with explicitly retained aerodynamic modes have been generated employing a time marching vortex lattice aerodynamic model. This paper presents analytical results from eigenanalysis of these models. The potential of these models to calculate the behavior of modes that represent damped system motion (noncritical modes) in addition to the simple harmonic modes is explored. A typical section with only structural freedom in pitch is examined. The eigenvalues are examined and compared to experimental data. Issues regarding the convergence of the solution with regard to refining the aerodynamic discretization are investigated. Eigenvector behavior is examined; the eigenvector associated with a particular eigenvalue can be viewed as the set of modal participation factors for that particular mode. For the present formulation of the equations of motion, the vorticity for each aerodynamic element appears explicitly as an element of each eigenvector in addition to the structural dynamic generalized coordinates. Thus, modal participation of the aerodynamic degrees of freedom can be assessed in M addition to participation of structural degrees of freedom.

Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains.

PubMed

Allefeld, Carsten; Bialonski, Stephan

2007-12-01

Synchronization cluster analysis is an approach to the detection of underlying structures in data sets of multivariate time series, starting from a matrix R of bivariate synchronization indices. A previous method utilized the eigenvectors of R for cluster identification, analogous to several recent attempts at group identification using eigenvectors of the correlation matrix. All of these approaches assumed a one-to-one correspondence of dominant eigenvectors and clusters, which has however been shown to be wrong in important cases. We clarify the usefulness of eigenvalue decomposition for synchronization cluster analysis by translating the problem into the language of stochastic processes, and derive an enhanced clustering method harnessing recent insights from the coarse-graining of finite-state Markov processes. We illustrate the operation of our method using a simulated system of coupled Lorenz oscillators, and we demonstrate its superior performance over the previous approach. Finally we investigate the question of robustness of the algorithm against small sample size, which is important with regard to field applications.

Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

PubMed

Abdelnour, Farras; Dayan, Michael; Devinsky, Orrin; Thesen, Thomas; Raj, Ashish

2018-05-15

How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses. Copyright © 2018. Published by Elsevier Inc.

A study of the eigenvectors of low frequency vibrational modes in crystalline cytidine via high pressure Raman spectroscopy

NASA Astrophysics Data System (ADS)

Lee, Scott A.

2014-03-01

High-pressure Raman spectroscopy has been used to study the eigenvectors and eigenvalues of the low-frequency vibrational modes of crystalline cytidine at 295 K by evaluating the logarithmic derivative of the vibrational frequency with respect to pressure: 1/ω dω/dP. Crystalline samples of molecular materials such as cytidine have vibrational modes that are localized within a molecular unit (``internal'' modes) as well as modes in which the molecular units vibrate against each other (``external'' modes). The value of the logarithmic derivative is a diagnostic probe of the nature of the eigenvector of the vibrational modes, making high pressure experiments a very useful probe for such studies. Internal stretching modes have low logarithmic derivatives while external as well as internal torsional and bending modes have higher logarithmic derivatives. All of the Raman modes below 200 cm-1 in cytidine are found to have high logarithmic derivatives, consistent with being either external modes or internal torsional or bending modes.

An autonomous dynamical system captures all LCSs in three-dimensional unsteady flows.

PubMed

Oettinger, David; Haller, George

2016-10-01

Lagrangian coherent structures (LCSs) are material surfaces that shape the finite-time tracer patterns in flows with arbitrary time dependence. Depending on their deformation properties, elliptic and hyperbolic LCSs have been identified from different variational principles, solving different equations. Here we observe that, in three dimensions, initial positions of all variational LCSs are invariant manifolds of the same autonomous dynamical system, generated by the intermediate eigenvector field, ξ 2 (x 0 ), of the Cauchy-Green strain tensor. This ξ 2 -system allows for the detection of LCSs in any unsteady flow by classical methods, such as Poincaré maps, developed for autonomous dynamical systems. As examples, we consider both steady and time-aperiodic flows, and use their dual ξ 2 -system to uncover both hyperbolic and elliptic LCSs from a single computation.

Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments.

PubMed

Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J

2017-01-01

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D , observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄ . When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model.

The phylogeny of quasars and the ontogeny of their central black holes

NASA Astrophysics Data System (ADS)

Fraix-Burnet, Didier; Marziani, Paola; D'Onofrio, Mauro; Dultzin, Deborah

2017-02-01

The connection between multifrequency quasar observational and physical parameters related to accretion processes is still open to debate. In the last 20 year, Eigenvector 1-based approaches developed since the early papers by Boroson and Green (1992) and Sulentic et al. (2000b) have been proved to be a remarkably powerful tool to investigate this issue, and have led to the definition of a quasar "main sequence". In this paper we perform a cladistic analysis on two samples of 215 and 85 low-z quasars (z ~ 0.7) which were studied in several previous works and which offer a satisfactory coverage of the Eigenvector 1-derived main sequence. The data encompass accurate measurements of observational parameters which represents key aspects associated with the structural diversity of quasars. Cladistics is able to group sources radiating at higher Eddington ratios, as well as to separate radio-quiet (RQ) and radio-loud (RL) quasars. The analysis suggests a black hole mass threshold for powerful radio emission and also properly distinguishes core-dominated and lobe-dominated quasars, in accordance with the basic tenet of RL unification schemes. Considering that black hole mass provides a sort of "arrow of time" of nuclear activity, a phylogenetic interpretation becomes possible if cladistic trees are rooted on black hole mass: the ontogeny of black holes is represented by their monotonic increase in mass. More massive radio-quiet Population B sources at low-z become a more evolved counterpart of Population A i.e., wind dominated sources to which the "local" Narrow-Line Seyfert 1s belong.

Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments*

PubMed Central

Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J.

2017-01-01

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D, observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄. When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model. PMID:28989561

Alternative definition of excitation amplitudes in multi-reference state-specific coupled cluster

NASA Astrophysics Data System (ADS)

Garniron, Yann; Giner, Emmanuel; Malrieu, Jean-Paul; Scemama, Anthony

2017-04-01

A central difficulty of state-specific Multi-Reference Coupled Cluster (MR-CC) in the multi-exponential Jeziorski-Monkhorst formalism concerns the definition of the amplitudes of the single and double excitation operators appearing in the exponential wave operators. If the reference space is a complete active space (CAS), the number of these amplitudes is larger than the number of singly and doubly excited determinants on which one may project the eigenequation, and one must impose additional conditions. The present work first defines a state-specific reference-independent operator T˜ ^ m which acting on the CAS component of the wave function |Ψ0m⟩ maximizes the overlap between (1 +T˜ ^ m ) |Ψ0m⟩ and the eigenvector of the CAS-SD (Singles and Doubles) Configuration Interaction (CI) matrix |ΨCAS-SDm⟩ . This operator may be used to generate approximate coefficients of the triples and quadruples, and a dressing of the CAS-SD CI matrix, according to the intermediate Hamiltonian formalism. The process may be iterated to convergence. As a refinement towards a strict coupled cluster formalism, one may exploit reference-independent amplitudes provided by (1 +T˜ ^ m ) |Ψ0m⟩ to define a reference-dependent operator T^ m by fitting the eigenvector of the (dressed) CAS-SD CI matrix. The two variants, which are internally uncontracted, give rather similar results. The new MR-CC version has been tested on the ground state potential energy curves of 6 molecules (up to triple-bond breaking) and two excited states. The non-parallelism error with respect to the full-CI curves is of the order of 1 mEh.

Research on the application of a decoupling algorithm for structure analysis

NASA Technical Reports Server (NTRS)

Denman, E. D.

1980-01-01

The mathematical theory for decoupling mth-order matrix differential equations is presented. It is shown that the decoupling precedure can be developed from the algebraic theory of matrix polynomials. The role of eigenprojectors and latent projectors in the decoupling process is discussed and the mathematical relationships between eigenvalues, eigenvectors, latent roots, and latent vectors are developed. It is shown that the eigenvectors of the companion form of a matrix contains the latent vectors as a subset. The spectral decomposition of a matrix and the application to differential equations is given.

Spatial and physical frames of reference in positioning a limb.

PubMed

Garrett, S R; Pagano, C; Austin, G; Turvey, M T

1998-10-01

Splints attached to the right forearm were used to rotate the forearm's physical reference frame, as defined by the eigenvectors of its inertia tensor, relative to its spatial reference frame. In two experiments, when subjects were required to orient the forearm parallel to, or at 45 degrees to, the environmental horizontal, they produced limb orientations that were systematically deflected from the forearm's longitudinal spatial axis in the direction of the forearm's physical axes. The position sense seems to be based on inertial eigenvectors rather than on joint angles or gravitational torques.

Structural covariance network centrality in maltreated youth with posttraumatic stress disorder.

PubMed

Sun, Delin; Peverill, Matthew R; Swanson, Chelsea S; McLaughlin, Katie A; Morey, Rajendra A

2018-03-01

Childhood maltreatment is associated with posttraumatic stress disorder (PTSD) and elevated rates of adolescent and adult psychopathology including major depression, bipolar disorder, substance use disorders, and other medical comorbidities. Gray matter volume changes have been found in maltreated youth with (versus without) PTSD. However, little is known about the alterations of brain structural covariance network topology derived from cortical thickness in maltreated youth with PTSD. High-resolution T1-weighted magnetic resonance imaging scans were from demographically matched maltreated youth with PTSD (N = 24), without PTSD (N = 64), and non-maltreated healthy controls (n = 67). Cortical thickness data from 148 cortical regions was entered into interregional partial correlation analyses across participants. The supra-threshold correlations constituted connections in a structural brain network derived from four types of centrality measures (degree, betweenness, closeness, and eigenvector) estimated network topology and the importance of nodes. Between-group differences were determined by permutation testing. Maltreated youth with PTSD exhibited larger centrality in left anterior cingulate cortex than the other two groups, suggesting cortical network topology specific to maltreated youth with PTSD. Moreover, maltreated youth with versus without PTSD showed smaller centrality in right orbitofrontal cortex, suggesting that this may represent a vulnerability factor to PTSD following maltreatment. Longitudinal follow-up of the present results will help characterize the role that altered centrality plays in vulnerability and resilience to PTSD following childhood maltreatment. Copyright © 2017. Published by Elsevier Ltd.

COMPUTATIONAL ANALYSIS OF SWALLOWING MECHANICS UNDERLYING IMPAIRED EPIGLOTTIC INVERSION

PubMed Central

Pearson, William G.; Taylor, Brandon K; Blair, Julie; Martin-Harris, Bonnie

2015-01-01

Objective Determine swallowing mechanics associated with the first and second epiglottic movements, that is, movement to horizontal and full inversion respectively, in order to provide a clinical interpretation of impaired epiglottic function. Study Design Retrospective cohort study. Methods A heterogeneous cohort of patients with swallowing difficulties was identified (n=92). Two speech-language pathologists reviewed 5ml thin and 5ml pudding videofluoroscopic swallow studies per subject, and assigned epiglottic component scores of 0=complete inversion, 1=partial inversion, and 2=no inversion forming three groups of videos for comparison. Coordinates mapping minimum and maximum excursion of the hyoid, pharynx, larynx, and tongue base during pharyngeal swallowing were recorded using ImageJ software. A canonical variate analysis with post-hoc discriminant function analysis of coordinates was performed using MorphoJ software to evaluate mechanical differences between groups. Eigenvectors characterizing swallowing mechanics underlying impaired epiglottic movements were visualized. Results Nineteen of 184 video-swallows were rejected for poor quality (n=165). A Goodman-Kruskal index of predictive association showed no correlation between epiglottic component scores and etiologies of dysphagia (λ=.04). A two-way analysis of variance by epiglottic component scores showed no significant interaction effects between sex and age (f=1.4, p=.25). Discriminant function analysis demonstrated statistically significant mechanical differences between epiglottic component scores: 1&2, representing the first epiglottic movement (Mahalanobis distance=1.13, p=.0007); and, 0&1, representing the second epiglottic movement (Mahalanobis distance=0.83, p=.003). Eigenvectors indicate that laryngeal elevation and tongue base retraction underlie both epiglottic movements. Conclusion Results suggest that reduced tongue base retraction and laryngeal elevation underlie impaired first and second epiglottic movements. The styloglossus, hyoglossus and long pharyngeal muscles are implicated as targets for rehabilitation in dysphagic patients with impaired epiglottic inversion. PMID:27426940

Palaeohistological Evidence for Ancestral High Metabolic Rate in Archosaurs.

PubMed

Legendre, Lucas J; Guénard, Guillaume; Botha-Brink, Jennifer; Cubo, Jorge

2016-11-01

Metabolic heat production in archosaurs has played an important role in their evolutionary radiation during the Mesozoic, and their ancestral metabolic condition has long been a matter of debate in systematics and palaeontology. The study of fossil bone histology provides crucial information on bone growth rate, which has been used to indirectly investigate the evolution of thermometabolism in archosaurs. However, no quantitative estimation of metabolic rate has ever been performed on fossils using bone histological features. Moreover, to date, no inference model has included phylogenetic information in the form of predictive variables. Here we performed statistical predictive modeling using the new method of phylogenetic eigenvector maps on a set of bone histological features for a sample of extant and extinct vertebrates, to estimate metabolic rates of fossil archosauromorphs. This modeling procedure serves as a case study for eigenvector-based predictive modeling in a phylogenetic context, as well as an investigation of the poorly known evolutionary patterns of metabolic rate in archosaurs. Our results show that Mesozoic theropod dinosaurs exhibit metabolic rates very close to those found in modern birds, that archosaurs share a higher ancestral metabolic rate than that of extant ectotherms, and that this derived high metabolic rate was acquired at a much more inclusive level of the phylogenetic tree, among non-archosaurian archosauromorphs. These results also highlight the difficulties of assigning a given heat production strategy (i.e., endothermy, ectothermy) to an estimated metabolic rate value, and confirm findings of previous studies that the definition of the endotherm/ectotherm dichotomy may be ambiguous. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Electrical impedance tomography in anisotropic media with known eigenvectors

NASA Astrophysics Data System (ADS)

Abascal, Juan-Felipe P. J.; Lionheart, William R. B.; Arridge, Simon R.; Schweiger, Martin; Atkinson, David; Holder, David S.

2011-06-01

Electrical impedance tomography is an imaging method, with which volumetric images of conductivity are produced by injecting electrical current and measuring boundary voltages. It has the potential to become a portable non-invasive medical imaging technique. Until now, most implementations have neglected anisotropy even though human tissues like bone, muscle and brain white matter are markedly anisotropic. The recovery of an anisotropic conductivity tensor is uniquely determined by boundary measurements only up to a diffeomorphism that fixes the boundary. Nevertheless, uniqueness can be restored by providing information about the diffeomorphism. There are uniqueness results for two constraints: one eigenvalue and a multiple scalar of a general tensor. A useable constraint for medical applications is when the eigenvectors of the underlying tissue are known, which can be approximated from MRI or estimated from DT-MRI, although the eigenvalues are unknown. However there is no known theoretical result guaranteeing uniqueness for this constraint. In fact, only a few previous inversion studies have attempted to recover one or more eigenvalues assuming certain symmetries while ignoring nonuniqueness. In this work, the aim was to undertake a numerical study of the feasibility of the recovery of a piecewise linear finite element conductivity tensor in anisotropic media with known eigenvectors from the complete boundary data. The work suggests that uniqueness holds for this constraint, in addition to proposing a methodology for the incorporation of this prior for general conductivity tensors. This was carried out by performing an analysis of the Jacobian rank and by reconstructing four conductivity distributions: two diagonal tensors whose eigenvalues were linear and sinusoidal functions, and two general tensors whose eigenvectors resembled physiological tissue, one with eigenvectors spherically orientated like a spherical layered structure, and a sample of DT-MRI data of brain white matter. The Jacobian with respect to three eigenvalues was full-rank and it was possible to recover three eigenvalues for the four simulated distributions. This encourages further theoretical study of the uniqueness for this constraint and supports the use of this as a relevant usable method for medical applications.

Using Perturbation Theory to Compute the Morphological Similarity of Diffusion Tensors

PubMed Central

Bansal, Ravi; Staib, Lawrence H.; Xu, Dongrong; Laine, Andrew F.; Royal, Jason; Peterson, Bradley S.

2008-01-01

Computing the morphological similarity of Diffusion Tensors (DTs) at neighboring voxels within a DT image, or at corresponding locations across different DT images, is a fundamental and ubiquitous operation in the post-processing of DT images. The morphological similarity of DTs typically has been computed using either the Principal Directions (PDs) of DTs (i.e., the direction along which water molecules diffuse preferentially) or their tensor elements. Although comparing PDs allows the similarity of one morphological feature of DTs to be visualized directly in eigenspace, this method takes into account only a single eigenvector, and it is therefore sensitive to the presence of noise in the images that can introduce error into the estimation of that vector. Although comparing tensor elements, rather than PDs, is comparatively more robust to the effects of noise, the individual elements of a given tensor do not directly reflect the diffusion properties of water molecules. We propose a measure for computing the morphological similarity of DTs that uses both their eigenvalues and eigenvectors, and that also accounts for the noise levels present in DT images. Our measure presupposes that DTs in a homogeneous region within or across DT images are random perturbations of one another in the presence of noise. The similarity values that are computed using our method are smooth (in the sense that small changes in eigenvalues and eigenvectors cause only small changes in similarity), and they are symmetric when differences in eigenvalues and eigenvectors are also symmetric. In addition, our method does not presuppose that the corresponding eigenvectors across two DTs have been identified accurately, an assumption that is problematic in the presence of noise. Because we compute the similarity between DTs using their eigenspace components, our similarity measure relates directly to both the magnitude and the direction of the diffusion of water molecules. The favorable performance characteristics of our measure offer the prospect of substantially improving additional post-processing operations that are commonly performed on DTI datasets, such as image segmentation, fiber tracking, noise filtering, and spatial normalization. PMID:18450533

What affects the predictability of evolutionary constraints using a G-matrix? The relative effects of modular pleiotropy and mutational correlation.

PubMed

Chebib, Jobran; Guillaume, Frédéric

2017-10-01

Phenotypic traits do not always respond to selection independently from each other and often show correlated responses to selection. The structure of a genotype-phenotype map (GP map) determines trait covariation, which involves variation in the degree and strength of the pleiotropic effects of the underlying genes. It is still unclear, and debated, how much of that structure can be deduced from variational properties of quantitative traits that are inferred from their genetic (co) variance matrix (G-matrix). Here we aim to clarify how the extent of pleiotropy and the correlation among the pleiotropic effects of mutations differentially affect the structure of a G-matrix and our ability to detect genetic constraints from its eigen decomposition. We show that the eigenvectors of a G-matrix can be predictive of evolutionary constraints when they map to underlying pleiotropic modules with correlated mutational effects. Without mutational correlation, evolutionary constraints caused by the fitness costs associated with increased pleiotropy are harder to infer from evolutionary metrics based on a G-matrix's geometric properties because uncorrelated pleiotropic effects do not affect traits' genetic correlations. Correlational selection induces much weaker modular partitioning of traits' genetic correlations in absence then in presence of underlying modular pleiotropy. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Voxel-Wise Comparisons of the Morphology of Diffusion Tensors Across Groups of Experimental Subjects

PubMed Central

Bansal, Ravi; Staib, Lawrence H.; Plessen, Kerstin J.; Xu, Dongrong; Royal, Jason; Peterson, Bradley S.

2007-01-01

Water molecules in the brain diffuse preferentially along the fiber tracts within white matter, which form the anatomical connections across spatially distant brain regions. A diffusion tensor (DT) is a probabilistic ellipsoid composed of 3 orthogonal vectors, each having a direction and an associated scalar magnitude, that represent the probability of water molecules diffusing in each of those directions. The 3D morphologies of DTs can be compared across groups of subjects to reveal disruptions in structural organization and neuroanatomical connectivity of the brains of persons with various neuropsychiatric illnesses. Comparisons of tensor morphology across groups have typically been performed on scalar measures of diffusivity, such as Fractional Anisotropy (FA), rather than directly on the complex 3D morphologies of DTs. Scalar measures, however, are related in nonlinear ways to the eigenvalues and eigenvectors that create the 3D morphologies of DTs. We present a mathematical framework that permits the direct comparison across groups of mean eigenvalues and eigenvectors of individual DTs. We show that group-mean eigenvalues and eigenvectors are multivariate Gaussian distributed, and we use the Delta method to compute their approximate covariance matrices. Our results show that the theoretically computed Mean Tensor (MT) eigenvectors and eigenvalues match well with their respective true values. Furthermore, a comparison of synthetically generated groups of DTs highlights the limitations of using FA to detect group differences. Finally, analyses of in vivo DT data using our method reveal significant between-group differences in diffusivity along fiber tracts within white matter, whereas analyses based on FA values failed to detect some of these differences. PMID:18006284

Network-Based Detection and Classification of Seismovolcanic Tremors: Example From the Klyuchevskoy Volcanic Group in Kamchatka

NASA Astrophysics Data System (ADS)

Soubestre, Jean; Shapiro, Nikolai M.; Seydoux, Léonard; de Rosny, Julien; Droznin, Dmitry V.; Droznina, Svetlana Ya.; Senyukov, Sergey L.; Gordeev, Evgeniy I.

2018-01-01

We develop a network-based method for detecting and classifying seismovolcanic tremors. The proposed approach exploits the coherence of tremor signals across the network that is estimated from the array covariance matrix. The method is applied to four and a half years of continuous seismic data recorded by 19 permanent seismic stations in the vicinity of the Klyuchevskoy volcanic group in Kamchatka (Russia), where five volcanoes were erupting during the considered time period. We compute and analyze daily covariance matrices together with their eigenvalues and eigenvectors. As a first step, most coherent signals corresponding to dominating tremor sources are detected based on the width of the covariance matrix eigenvalues distribution. Thus, volcanic tremors of the two volcanoes known as most active during the considered period, Klyuchevskoy and Tolbachik, are efficiently detected. As a next step, we consider the daily array covariance matrix's first eigenvector. Our main hypothesis is that these eigenvectors represent the principal components of the daily seismic wavefield and, for days with tremor activity, characterize dominant tremor sources. Those daily first eigenvectors, which can be used as network-based fingerprints of tremor sources, are then grouped into clusters using correlation coefficient as a measure of the vector similarity. As a result, we identify seven clusters associated with different periods of activity of four volcanoes: Tolbachik, Klyuchevskoy, Shiveluch, and Kizimen. The developed method does not require a priori knowledge and is fully automatic; and the database of the network-based tremor fingerprints can be continuously enriched with newly available data.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

We present two efficient iterative algorithms for solving the linear response eigen- value problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into a product eigenvalue problem that is self-adjoint with respect to a K-inner product. This product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-innermore » product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. However, the other component of the eigenvector can be easily recovered in a postprocessing procedure. Therefore, the algorithms we present here are more efficient than existing algorithms that try to approximate both components of the eigenvectors simultaneously. The efficiency of the new algorithms is demonstrated by numerical examples.« less

Eigenvector dynamics: General theory and some applications

NASA Astrophysics Data System (ADS)

Allez, Romain; Bouchaud, Jean-Philippe

2012-10-01

We propose a general framework to study the stability of the subspace spanned by P consecutive eigenvectors of a generic symmetric matrix H0 when a small perturbation is added. This problem is relevant in various contexts, including quantum dissipation (H0 is then the Hamiltonian) and financial risk control (in which case H0 is the assets' return covariance matrix). We argue that the problem can be formulated in terms of the singular values of an overlap matrix, which allows one to define an overlap distance. We specialize our results for the case of a Gaussian orthogonal H0, for which the full spectrum of singular values can be explicitly computed. We also consider the case when H0 is a covariance matrix and illustrate the usefulness of our results using financial data. The special case where the top eigenvalue is much larger than all the other ones can be investigated in full detail. In particular, the dynamics of the angle made by the top eigenvector and its true direction defines an interesting class of random processes.

Monte Carlo simulation of errors in the anisotropy of magnetic susceptibility - A second-rank symmetric tensor. [for grains in sedimentary and volcanic rocks

NASA Technical Reports Server (NTRS)

Lienert, Barry R.

1991-01-01

Monte Carlo perturbations of synthetic tensors to evaluate the Hext/Jelinek elliptical confidence regions for anisotropy of magnetic susceptibility (AMS) eigenvectors are used. When the perturbations are 33 percent of the minimum anisotropy, both the shapes and probability densities of the resulting eigenvector distributions agree with the elliptical distributions predicted by the Hext/Jelinek equations. When the perturbation size is increased to 100 percent of the minimum eigenvalue difference, the major axis of the 95 percent confidence ellipse underestimates the observed eigenvector dispersion by about 10 deg. The observed distributions of the principal susceptibilities (eigenvalues) are close to being normal, with standard errors that agree well with the calculated Hext/Jelinek errors. The Hext/Jelinek ellipses are also able to describe the AMS dispersions due to instrumental noise and provide reasonable limits for the AMS dispersions observed in two Hawaiian basaltic dikes. It is concluded that the Hext/Jelinek method provides a satisfactory description of the errors in AMS data and should be a standard part of any AMS data analysis.

The spectra of reducible matrices over complete commutative idempotent semifields and their spectral lattices

NASA Astrophysics Data System (ADS)

José Valverde-Albacete, Francisco; Peláez-Moreno, Carmen

2016-02-01

Previous work has shown a relation between L-valued extensions of Formal Concept Analysis and the spectra of some matrices related to L-valued contexts. To clarify this relation, we investigated elsewhere the nature of the spectra of irreducible matrices over idempotent semifields in the framework of dioids, naturally ordered semirings, that encompass several of those extensions. This initial work already showed many differences with respect to their counterparts over incomplete idempotent semifields, in what concerns the definition of the spectrum and the eigenvectors. Considering special sets of eigenvectors also brought out complete lattices in the picture and we argue that such structure may be more important than standard eigenspace structure for matrices over completed idempotent semifields. In this paper, we complete that investigation in the sense that we consider the spectra of reducible matrices over completed idempotent semifields and dioids, giving, as a result, a constructive solution to the all-eigenvectors problem in this setting. This solution shows that the relation of complete lattices to eigenspaces is even tighter than suspected.

Social networks predict selective observation and information spread in ravens

PubMed Central

Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

2016-01-01

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

Iterative Neighbour-Information Gathering for Ranking Nodes in Complex Networks

NASA Astrophysics Data System (ADS)

Xu, Shuang; Wang, Pei; Lü, Jinhu

2017-01-01

Designing node influence ranking algorithms can provide insights into network dynamics, functions and structures. Increasingly evidences reveal that node’s spreading ability largely depends on its neighbours. We introduce an iterative neighbourinformation gathering (Ing) process with three parameters, including a transformation matrix, a priori information and an iteration time. The Ing process iteratively combines priori information from neighbours via the transformation matrix, and iteratively assigns an Ing score to each node to evaluate its influence. The algorithm appropriates for any types of networks, and includes some traditional centralities as special cases, such as degree, semi-local, LeaderRank. The Ing process converges in strongly connected networks with speed relying on the first two largest eigenvalues of the transformation matrix. Interestingly, the eigenvector centrality corresponds to a limit case of the algorithm. By comparing with eight renowned centralities, simulations of susceptible-infected-removed (SIR) model on real-world networks reveal that the Ing can offer more exact rankings, even without a priori information. We also observe that an optimal iteration time is always in existence to realize best characterizing of node influence. The proposed algorithms bridge the gaps among some existing measures, and may have potential applications in infectious disease control, designing of optimal information spreading strategies.

Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses.

PubMed

Griffith, Daniel A; Peres-Neto, Pedro R

2006-10-01

Recently, analytical approaches based on the eigenfunctions of spatial configuration matrices have been proposed in order to consider explicitly spatial predictors. The present study demonstrates the usefulness of eigenfunctions in spatial modeling applied to ecological problems and shows equivalencies of and differences between the two current implementations of this methodology. The two approaches in this category are the distance-based (DB) eigenvector maps proposed by P. Legendre and his colleagues, and spatial filtering based upon geographic connectivity matrices (i.e., topology-based; CB) developed by D. A. Griffith and his colleagues. In both cases, the goal is to create spatial predictors that can be easily incorporated into conventional regression models. One important advantage of these two approaches over any other spatial approach is that they provide a flexible tool that allows the full range of general and generalized linear modeling theory to be applied to ecological and geographical problems in the presence of nonzero spatial autocorrelation.

A Riemann solver for RANS

NASA Astrophysics Data System (ADS)

Chuvakhov, P. V.

2014-01-01

An exact expression for a system of both eigenvalues and right/left eigenvectors of a Jacobian matrix for a convective two-equation differential closure RANS operator split along a curvilinear coordinate is derived. It is shown by examples of numerical modeling of supersonic flows over a flat plate and a compression corner with separation that application of the exact system of eigenvalues and eigenvectors to the Roe approach for approximate solution of the Riemann problem gives rise to an increase in the convergence rate, better stability and higher accuracy of a steady-state solution in comparison with those in the case of an approximate system.

Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI

NASA Astrophysics Data System (ADS)

Hwuang, Eileen; Rusu, Mirabela; Karthigeyan, Sudha; Agner, Shannon C.; Sparks, Rachel; Shih, Natalie; Tomaszewski, John E.; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

2014-03-01

Multi-modal image registration is needed to align medical images collected from different protocols or imaging sources, thereby allowing the mapping of complementary information between images. One challenge of multimodal image registration is that typical similarity measures rely on statistical correlations between image intensities to determine anatomical alignment. The use of alternate image representations could allow for mapping of intensities into a space or representation such that the multimodal images appear more similar, thus facilitating their co-registration. In this work, we present a spectral embedding based registration (SERg) method that uses non-linearly embedded representations obtained from independent components of statistical texture maps of the original images to facilitate multimodal image registration. Our methodology comprises the following main steps: 1) image-derived textural representation of the original images, 2) dimensionality reduction using independent component analysis (ICA), 3) spectral embedding to generate the alternate representations, and 4) image registration. The rationale behind our approach is that SERg yields embedded representations that can allow for very different looking images to appear more similar, thereby facilitating improved co-registration. Statistical texture features are derived from the image intensities and then reduced to a smaller set by using independent component analysis to remove redundant information. Spectral embedding generates a new representation by eigendecomposition from which only the most important eigenvectors are selected. This helps to accentuate areas of salience based on modality-invariant structural information and therefore better identifies corresponding regions in both the template and target images. The spirit behind SERg is that image registration driven by these areas of salience and correspondence should improve alignment accuracy. In this work, SERg is implemented using Demons to allow the algorithm to more effectively register multimodal images. SERg is also tested within the free-form deformation framework driven by mutual information. Nine pairs of synthetic T1-weighted to T2-weighted brain MRI were registered under the following conditions: five levels of noise (0%, 1%, 3%, 5%, and 7%) and two levels of bias field (20% and 40%) each with and without noise. We demonstrate that across all of these conditions, SERg yields a mean squared error that is 81.51% lower than that of Demons driven by MRI intensity alone. We also spatially align twenty-six ex vivo histology sections and in vivo prostate MRI in order to map the spatial extent of prostate cancer onto corresponding radiologic imaging. SERg performs better than intensity registration by decreasing the root mean squared distance of annotated landmarks in the prostate gland via both Demons algorithm and mutual information-driven free-form deformation. In both synthetic and clinical experiments, the observed improvement in alignment of the template and target images suggest the utility of parametric eigenvector representations and hence SERg for multimodal image registration.

Early social networks predict survival in wild bottlenose dolphins.

PubMed

Stanton, Margaret A; Mann, Janet

2012-01-01

A fundamental question concerning group-living species is what factors influence the evolution of sociality. Although several studies link adult social bonds to fitness, social patterns and relationships are often formed early in life and are also likely to have fitness consequences, particularly in species with lengthy developmental periods, extensive social learning, and early social bond-formation. In a longitudinal study of bottlenose dolphins (Tursiops sp.), calf social network structure, specifically the metric eigenvector centrality, predicted juvenile survival in males. Additionally, male calves that died post-weaning had stronger ties to juvenile males than surviving male calves, suggesting that juvenile males impose fitness costs on their younger counterparts. Our study indicates that selection is acting on social traits early in life and highlights the need to examine the costs and benefits of social bonds during formative life history stages.

Publications - RI 2013-2 | Alaska Division of Geological & Geophysical

Science.gov Websites

content DGGS RI 2013-2 Publication Details Title: Surficial-geologic map of the Livengood area, central Burns, P.A.C., 2013, Surficial-geologic map of the Livengood area, central Alaska: Alaska Division of Sheet 1 Surficial-geologic map of the Livengood area, central Alaska, scale 1:50,000 (30.0 M) Digital

4D Cone-beam CT reconstruction using a motion model based on principal component analysis

PubMed Central

Staub, David; Docef, Alen; Brock, Robert S.; Vaman, Constantin; Murphy, Martin J.

2011-01-01

Purpose: To provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm. Methods: The algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT. The motion model uses a basis of eigenvectors that are generated via principal component analysis (PCA) of a training set of displacement vector fields (DVFs) that approximate patient motion. The eigenvectors are weighted by a parameterized function of the patient breathing trace recorded during 4DCBCT. The algorithm is demonstrated and tested via numerical simulation. Results: The algorithm is shown to produce accurate reconstruction results for the most complicated simulated motion, in which voxels move with a pseudo-periodic pattern and relative phase shifts exist between voxels. The tests show that principal component eigenvectors trained on DVFs from a novel 2D/3D registration method give substantially better results than eigenvectors trained on DVFs obtained by conventionally registering 4DCBCT phases reconstructed via filtered backprojection. Conclusions: Proof of concept testing has validated the 4DCBCT reconstruction approach for the types of simulated data considered. In addition, the authors found the 2D/3D registration approach to be our best choice for generating the DVF training set, and the Nelder-Mead simplex algorithm the most robust optimization routine. PMID:22149852

The Topology of Symmetric Tensor Fields

NASA Technical Reports Server (NTRS)

Levin, Yingmei; Batra, Rajesh; Hesselink, Lambertus; Levy, Yuval

1997-01-01

Combinatorial topology, also known as "rubber sheet geometry", has extensive applications in geometry and analysis, many of which result from connections with the theory of differential equations. A link between topology and differential equations is vector fields. Recent developments in scientific visualization have shown that vector fields also play an important role in the analysis of second-order tensor fields. A second-order tensor field can be transformed into its eigensystem, namely, eigenvalues and their associated eigenvectors without loss of information content. Eigenvectors behave in a similar fashion to ordinary vectors with even simpler topological structures due to their sign indeterminacy. Incorporating information about eigenvectors and eigenvalues in a display technique known as hyperstreamlines reveals the structure of a tensor field. The simplify and often complex tensor field and to capture its important features, the tensor is decomposed into an isotopic tensor and a deviator. A tensor field and its deviator share the same set of eigenvectors, and therefore they have a similar topological structure. A a deviator determines the properties of a tensor field, while the isotopic part provides a uniform bias. Degenerate points are basic constituents of tensor fields. In 2-D tensor fields, there are only two types of degenerate points; while in 3-D, the degenerate points can be characterized in a Q'-R' plane. Compressible and incompressible flows share similar topological feature due to the similarity of their deviators. In the case of the deformation tensor, the singularities of its deviator represent the area of vortex core in the field. In turbulent flows, the similarities and differences of the topology of the deformation and the Reynolds stress tensors reveal that the basic addie-viscosity assuptions have their validity in turbulence modeling under certain conditions.

Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

NASA Astrophysics Data System (ADS)

Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

2017-03-01

Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological function.

Identification and classification of transient pulses observed in magnetometer array data by time-domain principal component analysis filtering

NASA Astrophysics Data System (ADS)

Kappler, Karl N.; Schneider, Daniel D.; MacLean, Laura S.; Bleier, Thomas E.

2017-08-01

A method for identification of pulsations in time series of magnetic field data which are simultaneously present in multiple channels of data at one or more sensor locations is described. Candidate pulsations of interest are first identified in geomagnetic time series by inspection. Time series of these "training events" are represented in matrix form and transpose-multiplied to generate time-domain covariance matrices. The ranked eigenvectors of this matrix are stored as a feature of the pulsation. In the second stage of the algorithm, a sliding window (approximately the width of the training event) is moved across the vector-valued time-series comprising the channels on which the training event was observed. At each window position, the data covariance matrix and associated eigenvectors are calculated. We compare the orientation of the dominant eigenvectors of the training data to those from the windowed data and flag windows where the dominant eigenvectors directions are similar. This was successful in automatically identifying pulses which share polarization and appear to be from the same source process. We apply the method to a case study of continuously sampled (50 Hz) data from six observatories, each equipped with three-component induction coil magnetometers. We examine a 90-day interval of data associated with a cluster of four observatories located within 50 km of Napa, California, together with two remote reference stations-one 100 km to the north of the cluster and the other 350 km south. When the training data contains signals present in the remote reference observatories, we are reliably able to identify and extract global geomagnetic signals such as solar-generated noise. When training data contains pulsations only observed in the cluster of local observatories, we identify several types of non-plane wave signals having similar polarization.

Targeting functional motifs of a protein family

NASA Astrophysics Data System (ADS)

Bhadola, Pradeep; Deo, Nivedita

2016-10-01

The structural organization of a protein family is investigated by devising a method based on the random matrix theory (RMT), which uses the physiochemical properties of the amino acid with multiple sequence alignment. A graphical method to represent protein sequences using physiochemical properties is devised that gives a fast, easy, and informative way of comparing the evolutionary distances between protein sequences. A correlation matrix associated with each property is calculated, where the noise reduction and information filtering is done using RMT involving an ensemble of Wishart matrices. The analysis of the eigenvalue statistics of the correlation matrix for the β -lactamase family shows the universal features as observed in the Gaussian orthogonal ensemble (GOE). The property-based approach captures the short- as well as the long-range correlation (approximately following GOE) between the eigenvalues, whereas the previous approach (treating amino acids as characters) gives the usual short-range correlations, while the long-range correlations are the same as that of an uncorrelated series. The distribution of the eigenvector components for the eigenvalues outside the bulk (RMT bound) deviates significantly from RMT observations and contains important information about the system. The information content of each eigenvector of the correlation matrix is quantified by introducing an entropic estimate, which shows that for the β -lactamase family the smallest eigenvectors (low eigenmodes) are highly localized as well as informative. These small eigenvectors when processed gives clusters involving positions that have well-defined biological and structural importance matching with experiments. The approach is crucial for the recognition of structural motifs as shown in β -lactamase (and other families) and selectively identifies the important positions for targets to deactivate (activate) the enzymatic actions.

Gravimetric maps of the Central African Republic

NASA Technical Reports Server (NTRS)

Albouy, J.; Godivier, R. (Principal Investigator)

1982-01-01

Gravimetric maps of the Central African Republic are described including a map of Bouguer anomalies at 1/1,000,000 in two sections (eastern sheet, western sheet) and a map, in color, of Bouguer anomalies at 1/2,000,000. Instrumentation, data acquisition, calibration, and data correction procedures are discussed.

Magnetic anomaly map of the central Cayman Trough, northwestern Caribbean Sea

USGS Publications Warehouse

Dillon, William P.; Edgar, N. Terence; Parson, Lindsay M.; Scanlon, Kathryn M.; Driscoll, George R.; Jacobs, Colin L.

1993-01-01

This is the first large-scale published map of magnetic anomalies in the central Cayman Trough area. Two previously published very small scale maps based on much less data are a regional map (Gough and Heirtzler, 1969) and a map compiled from several tracklines running parallel to the axis of the Cayman Trough (MacDonald and Holcombe, 1978).

Resting-state functional magnetic resonance imaging of the subthalamic microlesion and stimulation effects in Parkinson's disease: Indications of a principal role of the brainstem

PubMed Central

Holiga, Štefan; Mueller, Karsten; Möller, Harald E.; Urgošík, Dušan; Růžička, Evžen; Schroeter, Matthias L.; Jech, Robert

2015-01-01

During implantation of deep-brain stimulation (DBS) electrodes in the target structure, neurosurgeons and neurologists commonly observe a “microlesion effect” (MLE), which occurs well before initiating subthalamic DBS. This phenomenon typically leads to a transitory improvement of motor symptoms of patients suffering from Parkinson's disease (PD). Mechanisms behind MLE remain poorly understood. In this work, we exploited the notion of ranking to assess spontaneous brain activity in PD patients examined by resting-state functional magnetic resonance imaging in response to penetration of DBS electrodes in the subthalamic nucleus. In particular, we employed a hypothesis-free method, eigenvector centrality (EC), to reveal motor-communication-hubs of the highest rank and their reorganization following the surgery; providing a unique opportunity to evaluate the direct impact of disrupting the PD motor circuitry in vivo without prior assumptions. Penetration of electrodes was associated with increased EC of functional connectivity in the brainstem. Changes in connectivity were quantitatively related to motor improvement, which further emphasizes the clinical importance of the functional integrity of the brainstem. Surprisingly, MLE and DBS were associated with anatomically different EC maps despite their similar clinical benefit on motor functions. The DBS solely caused an increase in connectivity of the left premotor region suggesting separate pathophysiological mechanisms of both interventions. While the DBS acts at the cortical level suggesting compensatory activation of less affected motor regions, the MLE affects more fundamental circuitry as the dysfunctional brainstem predominates in the beginning of PD. These findings invigorate the overlooked brainstem perspective in the understanding of PD and support the current trend towards its early diagnosis. PMID:26509113

Serum BDNF correlates with connectivity in the (pre)motor hub in the aging human brain--a resting-state fMRI pilot study.

PubMed

Mueller, Karsten; Arelin, Katrin; Möller, Harald E; Sacher, Julia; Kratzsch, Jürgen; Luck, Tobias; Riedel-Heller, Steffi; Villringer, Arno; Schroeter, Matthias L

2016-02-01

Brain-derived neurotrophic factor (BDNF) has been discussed to be involved in plasticity processes in the human brain, in particular during aging. Recently, aging and its (neurodegenerative) diseases have increasingly been conceptualized as disconnection syndromes. Here, connectivity changes in neural networks (the connectome) are suggested to be the most relevant and characteristic features for such processes or diseases. To further elucidate the impact of aging on neural networks, we investigated the interaction between plasticity processes, brain connectivity, and healthy aging by measuring levels of serum BDNF and resting-state fMRI data in 25 young (mean age 24.8 ± 2.7 (SD) years) and 23 old healthy participants (mean age, 68.6 ± 4.1 years). To identify neural hubs most essentially related to serum BDNF, we applied graph theory approaches, namely the new data-driven and parameter-free approach eigenvector centrality (EC) mapping. The analysis revealed a positive correlation between serum BDNF and EC in the premotor and motor cortex in older participants in contrast to young volunteers, where we did not detect any association. This positive relationship between serum BDNF and EC appears to be specific for older adults. Our results might indicate that the amount of physical activity and learning capacities, leading to higher BDNF levels, increases brain connectivity in (pre)motor areas in healthy aging in agreement with rodent animal studies. Pilot results have to be replicated in a larger sample including behavioral data to disentangle the cause for the relationship between BDNF levels and connectivity. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatial arrangement overrules environmental factors to structure native and non-native assemblages of synanthropic harvestmen.

PubMed

Muster, Christoph; Meyer, Marc; Sattler, Thomas

2014-01-01

Understanding how space affects the occurrence of native and non-native species is essential for inferring processes that shape communities. However, studies considering spatial and environmental variables for the entire community - as well as for the native and non-native assemblages in a single study - are scarce for animals. Harvestmen communities in central Europe have undergone drastic turnovers during the past decades, with several newly immigrated species, and thus provide a unique system to study such questions. We studied the wall-dwelling harvestmen communities from 52 human settlements in Luxembourg and found the assemblages to be largely dominated by non-native species (64% of specimens). Community structure was analysed using Moran's eigenvector maps as spatial variables, and landcover variables at different radii (500 m, 1000 m, 2000 m) in combination with climatic parameters as environmental variables. A surprisingly high portion of pure spatial variation (15.7% of total variance) exceeded the environmental (10.6%) and shared (4%) components of variation, but we found only minor differences between native and non-native assemblages. This could result from the ecological flexibility of both, native and non-native harvestmen that are not restricted to urban habitats but also inhabit surrounding semi-natural landscapes. Nevertheless, urban landcover variables explained more variation in the non-native community, whereas coverage of semi-natural habitats (forests, rivers) at broader radii better explained the native assemblage. This indicates that some urban characteristics apparently facilitate the establishment of non-native species. We found no evidence for competitive replacement of native by invasive species, but a community with novel combination of native and non-native species.

Spatial Arrangement Overrules Environmental Factors to Structure Native and Non-Native Assemblages of Synanthropic Harvestmen

PubMed Central

Muster, Christoph; Meyer, Marc; Sattler, Thomas

2014-01-01

Understanding how space affects the occurrence of native and non-native species is essential for inferring processes that shape communities. However, studies considering spatial and environmental variables for the entire community – as well as for the native and non-native assemblages in a single study – are scarce for animals. Harvestmen communities in central Europe have undergone drastic turnovers during the past decades, with several newly immigrated species, and thus provide a unique system to study such questions. We studied the wall-dwelling harvestmen communities from 52 human settlements in Luxembourg and found the assemblages to be largely dominated by non-native species (64% of specimens). Community structure was analysed using Moran's eigenvector maps as spatial variables, and landcover variables at different radii (500 m, 1000 m, 2000 m) in combination with climatic parameters as environmental variables. A surprisingly high portion of pure spatial variation (15.7% of total variance) exceeded the environmental (10.6%) and shared (4%) components of variation, but we found only minor differences between native and non-native assemblages. This could result from the ecological flexibility of both, native and non-native harvestmen that are not restricted to urban habitats but also inhabit surrounding semi-natural landscapes. Nevertheless, urban landcover variables explained more variation in the non-native community, whereas coverage of semi-natural habitats (forests, rivers) at broader radii better explained the native assemblage. This indicates that some urban characteristics apparently facilitate the establishment of non-native species. We found no evidence for competitive replacement of native by invasive species, but a community with novel combination of native and non-native species. PMID:24595309

Resting-state functional magnetic resonance imaging of the subthalamic microlesion and stimulation effects in Parkinson's disease: Indications of a principal role of the brainstem.

PubMed

Holiga, Štefan; Mueller, Karsten; Möller, Harald E; Urgošík, Dušan; Růžička, Evžen; Schroeter, Matthias L; Jech, Robert

2015-01-01

During implantation of deep-brain stimulation (DBS) electrodes in the target structure, neurosurgeons and neurologists commonly observe a "microlesion effect" (MLE), which occurs well before initiating subthalamic DBS. This phenomenon typically leads to a transitory improvement of motor symptoms of patients suffering from Parkinson's disease (PD). Mechanisms behind MLE remain poorly understood. In this work, we exploited the notion of ranking to assess spontaneous brain activity in PD patients examined by resting-state functional magnetic resonance imaging in response to penetration of DBS electrodes in the subthalamic nucleus. In particular, we employed a hypothesis-free method, eigenvector centrality (EC), to reveal motor-communication-hubs of the highest rank and their reorganization following the surgery; providing a unique opportunity to evaluate the direct impact of disrupting the PD motor circuitry in vivo without prior assumptions. Penetration of electrodes was associated with increased EC of functional connectivity in the brainstem. Changes in connectivity were quantitatively related to motor improvement, which further emphasizes the clinical importance of the functional integrity of the brainstem. Surprisingly, MLE and DBS were associated with anatomically different EC maps despite their similar clinical benefit on motor functions. The DBS solely caused an increase in connectivity of the left premotor region suggesting separate pathophysiological mechanisms of both interventions. While the DBS acts at the cortical level suggesting compensatory activation of less affected motor regions, the MLE affects more fundamental circuitry as the dysfunctional brainstem predominates in the beginning of PD. These findings invigorate the overlooked brainstem perspective in the understanding of PD and support the current trend towards its early diagnosis.

A Perron-Frobenius theory for block matrices associated to a multiplex network

NASA Astrophysics Data System (ADS)

Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

2015-03-01

The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers.

A Main Sequence For Quasars

NASA Astrophysics Data System (ADS)

Marziani, Paola; Sulentic, J. W.; Dultzin, D.; Negrete, A.; del Olmo, A.; Martínez-Carballo, M. A.; Stirpe, G. M.; D'Onofrio, M.; Perea, J.

2016-10-01

The 4D eigenvector 1 parameter space defined by Sulentic et al. may be seen as a surrogate H-R diagram for quasars. As in the stellar H-R diagram, a source sequence can be easily identified. In the case of quasars, the main sequence appears to be mainly driven by Eddington ratio. A transition Eddington ratio may in part explain the striking observational differences between quasars at opposite ends of the main sequence. The eigenvector-1 approach opens the door towards properly contextualized models of quasar physics, geometry and kinematics. We review some of the progress that has been made over the past 15 years, and point out still unsolved issues.

Robust Assignment Of Eigensystems For Flexible Structures

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Lim, Kyong B.; Junkins, John L.

1992-01-01

Improved method for placement of eigenvalues and eigenvectors of closed-loop control system by use of either state or output feedback. Applied to reduced-order finite-element mathematical model of NASA's MAST truss beam structure. Model represents deployer/retractor assembly, inertial properties of Space Shuttle, and rigid platforms for allocation of sensors and actuators. Algorithm formulated in real arithmetic for efficient implementation. Choice of open-loop eigenvector matrix and its closest unitary matrix believed suitable for generating well-conditioned eigensystem with small control gains. Implication of this approach is that element of iterative search for "optimal" unitary matrix appears unnecessary in practice for many test problems.

Characteristic vector analysis as a technique for signature extraction of remote ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1977-01-01

Characteristic vector analysis is being used to extract spectral signatures of suspended matter in the ocean from remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor), a multispectral scanner. Spectral signatures appear to be obtainable either directly from characteristic vectors or through a transformation of these eigenvectors. Quantification of the suspended matter associated with each resulting signature seems feasible using associated coefficients generated by the technique. This paper presents eigenvectors associated with algae, 'sediment', acid waste, sewage sludge, and oil. The results suggest an efficient method of transmitting from satellites multispectral data of pollution in our oceans.

Principal Components Analysis of Triaxial Vibration Data From Helicopter Transmissions

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Huff, Edward M.

2001-01-01

Research on the nature of the vibration data collected from helicopter transmissions during flight experiments has led to several crucial observations believed to be responsible for the high rates of false alarms and missed detections in aircraft vibration monitoring systems. This work focuses on one such finding, namely, the need to consider additional sources of information about system vibrations. In this light, helicopter transmission vibration data, collected using triaxial accelerometers, were explored in three different directions, analyzed for content, and then combined using Principal Components Analysis (PCA) to analyze changes in directionality. In this paper, the PCA transformation is applied to 176 test conditions/data sets collected from an OH58C helicopter to derive the overall experiment-wide covariance matrix and its principal eigenvectors. The experiment-wide eigenvectors. are then projected onto the individual test conditions to evaluate changes and similarities in their directionality based on the various experimental factors. The paper will present the foundations of the proposed approach, addressing the question of whether experiment-wide eigenvectors accurately model the vibration modes in individual test conditions. The results will further determine the value of using directionality and triaxial accelerometers for vibration monitoring and anomaly detection.

Method of locating related items in a geometric space for data mining

DOEpatents

Hendrickson, B.A.

1999-07-27

A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, a storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity. 12 figs.

Correlation and volatility in an Indian stock market: A random matrix approach

NASA Astrophysics Data System (ADS)

Kulkarni, Varsha; Deo, Nivedita

2007-11-01

We examine the volatility of an Indian stock market in terms of correlation of stocks and quantify the volatility using the random matrix approach. First we discuss trends observed in the pattern of stock prices in the Bombay Stock Exchange for the three-year period 2000 2002. Random matrix analysis is then applied to study the relationship between the coupling of stocks and volatility. The study uses daily returns of 70 stocks for successive time windows of length 85 days for the year 2001. We compare the properties of matrix C of correlations between price fluctuations in time regimes characterized by different volatilities. Our analyses reveal that (i) the largest (deviating) eigenvalue of C correlates highly with the volatility of the index, (ii) there is a shift in the distribution of the components of the eigenvector corresponding to the largest eigenvalue across regimes of different volatilities, (iii) the inverse participation ratio for this eigenvector anti-correlates significantly with the market fluctuations and finally, (iv) this eigenvector of C can be used to set up a Correlation Index, CI whose temporal evolution is significantly correlated with the volatility of the overall market index.

Method of locating related items in a geometric space for data mining

DOEpatents

Hendrickson, Bruce A.

1999-01-01

A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, a storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity.

Exploration of the forbidden regions of the Ramachandran plot (ϕ-ψ) with QTAIM.

PubMed

Momen, Roya; Azizi, Alireza; Wang, Lingling; Ping, Yang; Xu, Tianlv; Kirk, Steven R; Li, Wenxuan; Manzhos, Sergei; Jenkins, Samantha

2017-10-04

A new QTAIM interpretation of the Ramachandran plot is formulated from the most and least facile eigenvectors of the second-derivative matrix of the electron density with a set of 29 magainin-2 peptide conformers. The presence of QTAIM eigenvectors associated with the most and least preferred directions of electronic charge density explained the role of hydrogen bonding, HH contacts and the glycine amino acid monomer in peptide folding. The highest degree of occupation of the QTAIM interpreted Ramachandran plot was found for the glycine amino acid monomer compared with the remaining backbone peptide bonds. The mobility of the QTAIM eigenvectors of the glycine amino acid monomer was higher than for the other amino acids and was comparable to that of the hydrogen bonding, explaining the flexibility of the magainin-2 backbone. We experimented with a variety of hybrid QTAIM-Ramachandran plots to highlight and explain why the glycine amino acid monomer largely occupies the 'forbidden' region on the Ramachandran plot. In addition, the new hybrid QTAIM-Ramachandran plots contained recognizable regions that can be associated with concepts familiar from the conventional Ramachandran plot whilst retaining the character of the QTAIM most and least preferred regions.

Eigenpairs of Toeplitz and Disordered Toeplitz Matrices with a Fisher-Hartwig Symbol

NASA Astrophysics Data System (ADS)

Movassagh, Ramis; Kadanoff, Leo P.

2017-05-01

Toeplitz matrices have entries that are constant along diagonals. They model directed transport, are at the heart of correlation function calculations of the two-dimensional Ising model, and have applications in quantum information science. We derive their eigenvalues and eigenvectors when the symbol is singular Fisher-Hartwig. We then add diagonal disorder and study the resulting eigenpairs. We find that there is a "bulk" behavior that is well captured by second order perturbation theory of non-Hermitian matrices. The non-perturbative behavior is classified into two classes: Runaways type I leave the complex-valued spectrum and become completely real because of eigenvalue attraction. Runaways type II leave the bulk and move very rapidly in response to perturbations. These have high condition numbers and can be predicted. Localization of the eigenvectors are then quantified using entropies and inverse participation ratios. Eigenvectors corresponding to Runaways type II are most localized (i.e., super-exponential), whereas Runaways type I are less localized than the unperturbed counterparts and have most of their probability mass in the interior with algebraic decays. The results are corroborated by applying free probability theory and various other supporting numerical studies.

Variable importance in nonlinear kernels (VINK): classification of digitized histopathology.

PubMed

Ginsburg, Shoshana; Ali, Sahirzeeshan; Lee, George; Basavanhally, Ajay; Madabhushi, Anant

2013-01-01

Quantitative histomorphometry is the process of modeling appearance of disease morphology on digitized histopathology images via image-based features (e.g., texture, graphs). Due to the curse of dimensionality, building classifiers with large numbers of features requires feature selection (which may require a large training set) or dimensionality reduction (DR). DR methods map the original high-dimensional features in terms of eigenvectors and eigenvalues, which limits the potential for feature transparency or interpretability. Although methods exist for variable selection and ranking on embeddings obtained via linear DR schemes (e.g., principal components analysis (PCA)), similar methods do not yet exist for nonlinear DR (NLDR) methods. In this work we present a simple yet elegant method for approximating the mapping between the data in the original feature space and the transformed data in the kernel PCA (KPCA) embedding space; this mapping provides the basis for quantification of variable importance in nonlinear kernels (VINK). We show how VINK can be implemented in conjunction with the popular Isomap and Laplacian eigenmap algorithms. VINK is evaluated in the contexts of three different problems in digital pathology: (1) predicting five year PSA failure following radical prostatectomy, (2) predicting Oncotype DX recurrence risk scores for ER+ breast cancers, and (3) distinguishing good and poor outcome p16+ oropharyngeal tumors. We demonstrate that subsets of features identified by VINK provide similar or better classification or regression performance compared to the original high dimensional feature sets.

Implementation of the analytical hierarchy process with VBA in ArcGIS

NASA Astrophysics Data System (ADS)

Marinoni, Oswald

2004-07-01

Decisions on landuse have become progressively more difficult in the last decades. The main reasons for this development lie in the increasing population combined with an increasing demand for new land and resources and in the growing consciousness for sustainable land and resource use. The steady reduction of valuable land leads to an increase of conflicts in land use decision-making processes since more interests are being affected and therefore more stakeholders with different land use interests and different valuation criteria are being involved in the decision-making process. In the course of such a decision process all identified criteria are weighted according to their relative importance. But assigning weights to the relevant criteria quickly becomes a difficult task when a greater number of criteria are being considered, especially with regard to land use decisions where decision makers expect some kind of mapped result it is therefore useful to use procedures that not only help to derive criteria weights but also accelerate the visualisation and mapping of land use assessment results. Both aspects can easily be facilitated in a GIS. This paper focuses the development of an ArcGIS VBA macro which enables the user to derive criteria weights with the analytical hierarchy process and which allows a mapping of the land use assessment results by a weighted summation of GIS raster data sets. A dynamic link library for the calculation of the eigenvalues and eigenvectors of a square matrix is provided.

Try This: Collaborative Mind Mapping

ERIC Educational Resources Information Center

Mendelson, Melissa

2016-01-01

In this "Try This" article, students learn about collaborative mind mapping. A mind map is a type of graphic organizer that allows for short ideas to be written and linked to related ideas on a "map." A central idea is placed in the middle of the paper with related ideas connected to the central idea as well as to other ideas.…

Publications - RI 97-15C | Alaska Division of Geological & Geophysical

Science.gov Websites

content DGGS RI 97-15C Publication Details Title: Surficial geologic map of the Tanana B-1 Quadrangle geologic map of the Tanana B-1 Quadrangle, central Alaska: Alaska Division of Geological & Geophysical Maps & Other Oversized Sheets Sheet 1 Surficial geologic map of the Tanana B-1 Quadrangle, Central

Map showing seismicity and sandblows in the vicinity of New Madrid, Missouri

USGS Publications Warehouse

Rhea, B. Susan; Tarr, Arthur C.; Wheeler, Russell L.

1994-01-01

This is one of a series of five seismotectic maps of the seismically active New Madrid, Missouri, area (table 1; Wheeler and others, 1992). The map area centers near the sites of three great earthquakes that struck during the winter of 1811-12 (Fuller, 1912; Nuttli, 1973). These earthquakes and continuing subsequent seismicity rank the New Madrid area with Cherlevoix, Quebec, as the two most seismically active areas in North America east of the Rocky Mountains. The threat posed by New Madrid seismicity to the central United States makes the area the focus of many investigations (for examples, Heyl and McKeown, 1978; McKeown and Pakiser, 1982; Algemissen and Hopper, 1984; Hamilton and Johnston, 1990; Applied Technology Council, 1991; Johnston and others, 1992). The map area includes the most intense seismic activity in the New Madrid region. A seismotectic map shows some of the geologic and geophysical information needed to assess seismic hazard (Hadley and Devine, 1974; Pavoni, 1985). A previous seismotectonic map of the central Mississippi River valley (Heyl and McKeown, 1978) has had wide use for planning field surveys, as a base map for plotting data collected during single investigations, and for compiling a range of information. Since 1978 numcrous researchers have greatly advanced our knowledge of the geology and geophysics of the central Mississippi Valley. The New Madrid seismotectonic map folio updates approximately the south-central sixth of the central Mississippi Valley seismotectonic map of Heyl and McKeown (1978).

How Structure Shapes Dynamics: Knowledge Development in Wikipedia - A Network Multilevel Modeling Approach

PubMed Central

Halatchliyski, Iassen; Cress, Ulrike

2014-01-01

Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base. PMID:25365319

On the Topologic Properties of River Networks

NASA Astrophysics Data System (ADS)

Sarker, S.; Singh, A.

2017-12-01

River network is an important landscape feature and has been studied extensively from a range of geomorphological and hydrological perspective. However, quantifying topologic dynamics and reorganization of river networks is becoming more and more challenging under changing natural and anthropogenic forcings. Here, we use a graph-theoretical approach to study topologic properties of natural and simulated river networks for a range of climatic and tectonic conditions. Among other metrics, we use betweeness and eigenvector centrality distributions computed using adjacency matrix of river networks and show their dependence on energy exponent γ that characterizes mechanism of erosional processes on a landscape. We further compare these topologic characteristics of landscape to geomorphic features such as slope-area curve and drainage density. Furthermore, we identify locations of critical nodes and links on a network as a function of energy exponent γ to understand network robustness and vulnerability under external attacks.

Neuroendocrine and immune network re-modeling in chronic fatigue syndrome: an exploratory analysis.

PubMed

Fuite, Jim; Vernon, Suzanne D; Broderick, Gordon

2008-12-01

This work investigates the significance of changes in association patterns linking indicators of neuroendocrine and immune activity in patients with chronic fatigue syndrome (CFS). Gene sets preferentially expressed in specific immune cell isolates were integrated with neuroendocrine data from a large population-based study. Co-expression patterns linking immune cell activity with hypothalamic-pituitary-adrenal (HPA), thyroidal (HPT) and gonadal (HPG) axis status were computed using mutual information criteria. Networks in control and CFS subjects were compared globally in terms of a weighted graph edit distance. Local re-modeling of node connectivity was quantified by node degree and eigenvector centrality measures. Results indicate statistically significant differences between CFS and control networks determined mainly by re-modeling around pituitary and thyroid nodes as well as an emergent immune sub-network. Findings align with known mechanisms of chronic inflammation and support possible immune-mediated loss of thyroid function in CFS exacerbated by blunted HPA axis responsiveness.

A new mutually reinforcing network node and link ranking algorithm

PubMed Central

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

2015-01-01

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity. PMID:26492958

Analysis of Soccer Players’ Positional Variability During the 2012 UEFA European Championship: A Case Study

PubMed Central

Moura, Felipe Arruda; Santana, Juliana Exel; Vieira, Nathália Arnosti; Santiago, Paulo Roberto Pereira; Cunha, Sergio Augusto

2015-01-01

The purpose of this study was to analyse players’ positional variability during the 2012 UEFA European Championship by applying principal component analysis (PCA) to data gathered from heat maps posted on the UEFA website. We analysed the teams that reached the finals and semi-finals of the competition. The players’ 2D coordinates from each match were obtained by applying an image-processing algorithm to the heat maps. With all the players’ 2D coordinates for each match, we applied PCA to identify the directions of greatest variability. Then, two orthogonal segments were centred on each player’s mean position for all matches. The segments’ directions were driven by the eigenvectors of the PCA, and the length of each segment was defined as one standard deviation around the mean. Finally, an ellipse was circumscribed around both segments. To represent player variability, segment lengths and elliptical areas were analysed. The results demonstrate that Portugal exhibited the lowest variability, followed by Germany, Spain and Italy. Additionally, a graphical representation of every player’s ellipse provided insight into the teams’ organisational features throughout the competition. The presented study provides important information regarding soccer teams’ tactical strategy in high-level championships that allows coaches to better control team organisation on the pitch. PMID:26557206

Publications - RI 97-15A | Alaska Division of Geological & Geophysical

Science.gov Websites

content DGGS RI 97-15A Publication Details Title: Geologic map of the Tanana B-1 Quadrangle, central ., and Weber, F.R., 1997, Geologic map of the Tanana B-1 Quadrangle, central Alaska: Alaska Division of ; Other Oversized Sheets Maps & Other Oversized Sheets Sheet 1 Geologic map of the Tanana B-1

Geologic map of Ophir and central Candor Chasmata (MTM -05072) of Mars

USGS Publications Warehouse

Lucchitta, Baerbel K.

1999-01-01

The geologic map of Ophir and central Candor Chasmata is one of a series of 1:500,000 scale maps prepared for areas on Mars that are of particular scientific interest and may serve as potential future landing sites. This map is also part of a set that includes east Candor Chasma, west Candor Chasma, and Melas Chasma. The geologic interpretations are based dominantly on medium- and high-resolution Viking images, many of them stereoscopic, and supplemented by lower resolution apoapsis and other color images. A strip of very high resolution stereoscopic images (~20 m/pixel) crosses the central part of the quadrangle from northwest to southeast and served to clarify detailed relations not obvious on other images. A topographic map with contour intervals of 200 m was also used, as were multidirectional oblique images derived from merged image mosaics and topography (see fig. 1) (Bertolini and McEwen, 1990). Geologic relations and interpretations are based on the entire central Valles Marineris map set. The map area is included in the Valles Marineris map of Witbeck and others (1991), but units were defined independently. Age assignments, however, were integrated with those by Witbeck and others and Scott and Tanaka (1986).

Who Are the Most Influential Emergency Physicians on Twitter?

PubMed Central

Riddell, Jeff; Brown, Alisha; Kovic, Ivor; Jauregui, Joshua

2017-01-01

Introduction Twitter has recently gained popularity in emergency medicine (EM). Opinion leaders on Twitter have significant influence on the conversation and content, yet little is known about these opinion leaders. We aimed to describe a methodology to identify the most influential emergency physicians (EP) on Twitter and present a current list. Methods We analyzed 2,234 English-language EPs on Twitter from a previously published list of Twitter accounts generated by a snowball sampling technique. Using NodeXL software, we performed a network analysis of these EPs and ranked them on three measures of influence: in-degree centrality, eigenvector centrality, and betweenness centrality. We analyzed the top 100 users in each of these three measures of influence and compiled a list of users found in the top 100 in all three measures. Results Of the 300 total users identified by one of the measures of influence, there were 142 unique users. Of the 142 unique users, 61 users were in the top 100 on all three measures of influence. We identify these 61 users as the most influential EM Twitter users. Conclusion We both describe a method for identifying the most influential users and provide a list of the 61 most influential EPs on Twitter as of January 1, 2016. This application of network science to the EM Twitter community can guide future research to better understand the networked global community of EM. PMID:28210365

Who Are the Most Influential Emergency Physicians on Twitter?

PubMed

Riddell, Jeff; Brown, Alisha; Kovic, Ivor; Jauregui, Joshua

2017-02-01

Twitter has recently gained popularity in emergency medicine (EM). Opinion leaders on Twitter have significant influence on the conversation and content, yet little is known about these opinion leaders. We aimed to describe a methodology to identify the most influential emergency physicians (EP) on Twitter and present a current list. We analyzed 2,234 English-language EPs on Twitter from a previously published list of Twitter accounts generated by a snowball sampling technique. Using NodeXL software, we performed a network analysis of these EPs and ranked them on three measures of influence: in-degree centrality, eigenvector centrality, and betweenness centrality. We analyzed the top 100 users in each of these three measures of influence and compiled a list of users found in the top 100 in all three measures. Of the 300 total users identified by one of the measures of influence, there were 142 unique users. Of the 142 unique users, 61 users were in the top 100 on all three measures of influence. We identify these 61 users as the most influential EM Twitter users. We both describe a method for identifying the most influential users and provide a list of the 61 most influential EPs on Twitter as of January 1, 2016. This application of network science to the EM Twitter community can guide future research to better understand the networked global community of EM.

Geologic map of the Alamosa 30’ × 60’ quadrangle, south-central Colorado

USGS Publications Warehouse

Thompson, Ren A.; Shroba, Ralph R.; Michael N. Machette,; Fridrich, Christopher J.; Brandt, Theodore R.; Cosca, Michael A.

2015-10-15

The Alamosa 30'× 60' quadrangle is located in the central San Luis Basin of southern Colorado and is bisected by the Rio Grande. The Rio Grande has headwaters in the San Juan Mountains of Colorado and ultimately discharges into the Gulf of Mexico 3,000 kilometers (km) downstream. Alluvial floodplains and associated deposits of the Rio Grande and east-draining tributaries, La Jara Creek and Conejos River, occupy the north-central and northwestern part of the map area. Alluvial deposits of west-draining Rio Grande tributaries, Culebra and Costilla Creeks, bound the Costilla Plain in the south-central part of the map area. The San Luis Hills, a northeast-trending series of flat-topped mesas and hills, dominate the landscape in the central and southwestern part of the map and preserve fault-bound Neogene basin surfaces and deposits. The Precambrian-cored Sangre de Cristo Mountains rise to an elevation of nearly 4,300 meters (m), almost 2,000 m above the valley floor, in the eastern part of the map area. In total, the map area contains deposits that record surficial, tectonic, sedimentary, volcanic, magmatic, and metamorphic processes over the past 1.7 billion years.

An improved V-Lambda solution of the matrix Riccati equation

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Markley, F. Landis

1988-01-01

The authors present an improved algorithm for computing the V-Lambda solution of the matrix Riccati equation. The improvement is in the reduction of the computational load, results from the orthogonality of the eigenvector matrix that has to be solved for. The orthogonality constraint reduces the number of independent parameters which define the matrix from n-squared to n (n - 1)/2. The authors show how to specify the parameters, how to solve for them and how to form from them the needed eigenvector matrix. In the search for suitable parameters, the analogy between the present problem and the problem of attitude determination is exploited, resulting in the choice of Rodrigues parameters.

On Theoretical Limits of Dynamic Model Updating Using a Sensitivity-Based Approach

NASA Astrophysics Data System (ADS)

GOLA, M. M.; SOMÀ, A.; BOTTO, D.

2001-07-01

The present work deals with the determination of the newly discovered conditions necessary for model updating with the eigensensitivity approach. The treatment concerns the maximum number of identifiable parameters regarding the structure of the eigenvectors derivatives. A mathematical demonstration is based on the evaluation of the rank of the least-squares matrix and produces the algebraic limiting conditions. Numerical application to a lumped parameter structure is employed to validate the mathematical limits taking into account different subsets of mode shapes. The demonstration is extended to the calculation of the eigenvector derivatives with both the Fox and Kapoor, and Nelson methods. III conditioning of the least-squares sensitivity matrix is revealed through the covariance jump.

A Spectral Analysis of Discrete-Time Quantum Walks Related to the Birth and Death Chains

NASA Astrophysics Data System (ADS)

Ho, Choon-Lin; Ide, Yusuke; Konno, Norio; Segawa, Etsuo; Takumi, Kentaro

2018-04-01

In this paper, we consider a spectral analysis of discrete time quantum walks on the path. For isospectral coin cases, we show that the time averaged distribution and stationary distributions of the quantum walks are described by the pair of eigenvalues of the coins as well as the eigenvalues and eigenvectors of the corresponding random walks which are usually referred as the birth and death chains. As an example of the results, we derive the time averaged distribution of so-called Szegedy's walk which is related to the Ehrenfest model. It is represented by Krawtchouk polynomials which is the eigenvectors of the model and includes the arcsine law.

Spin-orbit splitted excited states using explicitly-correlated equation-of-motion coupled-cluster singles and doubles eigenvectors

NASA Astrophysics Data System (ADS)

Bokhan, Denis; Trubnikov, Dmitrii N.; Perera, Ajith; Bartlett, Rodney J.

2018-04-01

An explicitly-correlated method of calculation of excited states with spin-orbit couplings, has been formulated and implemented. Developed approach utilizes left and right eigenvectors of equation-of-motion coupled-cluster model, which is based on the linearly approximated explicitly correlated coupled-cluster singles and doubles [CCSD(F12)] method. The spin-orbit interactions are introduced by using the spin-orbit mean field (SOMF) approximation of the Breit-Pauli Hamiltonian. Numerical tests for several atoms and molecules show good agreement between explicitly-correlated results and the corresponding values, calculated in complete basis set limit (CBS); the highly-accurate excitation energies can be obtained already at triple- ζ level.

Non-linear eigensolver-based alternative to traditional SCF methods

NASA Astrophysics Data System (ADS)

Gavin, B.; Polizzi, E.

2013-05-01

The self-consistent procedure in electronic structure calculations is revisited using a highly efficient and robust algorithm for solving the non-linear eigenvector problem, i.e., H({ψ})ψ = Eψ. This new scheme is derived from a generalization of the FEAST eigenvalue algorithm to account for the non-linearity of the Hamiltonian with the occupied eigenvectors. Using a series of numerical examples and the density functional theory-Kohn/Sham model, it will be shown that our approach can outperform the traditional SCF mixing-scheme techniques by providing a higher converge rate, convergence to the correct solution regardless of the choice of the initial guess, and a significant reduction of the eigenvalue solve time in simulations.

Presentations - Loveland, A.M. and others, 2009 | Alaska Division of

Science.gov Websites

Details Title: Geologic map of the South-central Sagavanirktok Quadrangle, North Slope, Alaska (poster , Geologic map of the South-central Sagavanirktok Quadrangle, North Slope, Alaska (poster): Alaska Geological quadrangle, North Slope, Alaska (14.0 M) Keywords Energy Resources Posters and Presentations; Geologic Map

Analysis of Preferred Directions in Phase Space for Tidal Measurements at Europa

NASA Astrophysics Data System (ADS)

Boone, D.; Scheeres, D. J.

2012-12-01

The NASA Jupiter Europa Orbiter mission requires a circular, near-polar orbit to measure Europa's Love numbers, geophysical coefficients which give insight into whether a liquid ocean exists. This type of orbit about planetary satellites is known to be unstable. The effects of Jupiter's tidal gravity are seen in changes in Europa's gravity field and surface deformation, which are sensed through doppler tracking over time and altimetry measurements respectively. These two measurement types separately determine the h and k Love numbers, a combination of which bounds how thick the ice shell of Europa is and whether liquid water is present. This work shows how the properties of an unstable periodic orbit about Europa generate preferred measurement directions in position and velocity phase space for the orbit determination process. We generate an error covariance over seven days for the orbiter state and science parameters using a periodic orbit and then disperse the orbit initial conditions in a Monte Carlo simulation according to this covariance. The dispersed orbits are shown to have a bias toward longer lifetimes and we discuss this as an effect of the stable and unstable manifolds of the periodic orbit. Using an epoch formulation of a square-root information filter, measurements aligned with the unstable manifold mapped back in time add more information to the orbit determination process than measurements aligned with the stable manifold. This corresponds to a contraction in the uncertainty of the estimate of the desired parameters, including the Love numbers. We demonstrate this mapping mathematically using a representation of the State Transition Matrix involving its eigenvectors and eigenvalues. Then using the properties of left and right eigenvectors, we show how measurements in the orbit determination process are mapped in time leading to a concentration of information at epoch. We present examples of measurements taken on different time schedules to show the effect of preferred phase space directions in the estimation process. Manifold coordinate decomposition is applied to the orbit initial conditions as well as measurement partials in the filter to show the alignment of each with the stable and unstable manifolds of the periodic orbit. The connection between orbit lifetime and regions of increased information density in phase space is made using the properties of these manifolds. Low altitude, near-polar periodic orbits with these characteristics are discussed along with the estimation results for the Love numbers, orbiter state, and orbit lifetime. Different measurement schedules and the resulting estimation performance are presented along with an analysis of information content for single measurements with respect to manifold alignment. These results allow more sensitive estimation of the tidal Love numbers and may allow measurements to be taken less frequently or compensate for corrupted data arcs. Other measurement types will be mapped in the same way using the State Transition matrix and have increased information density at epoch if aligned with the unstable manifold. In the same way, these results are applicable to planetary satellite orbiters about Enceladus or Dione since they share the governing equations of motion and properties of unstable periodic orbits.

REQUEST: A Recursive QUEST Algorithm for Sequential Attitude Determination

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.

1996-01-01

In order to find the attitude of a spacecraft with respect to a reference coordinate system, vector measurements are taken. The vectors are pairs of measurements of the same generalized vector, taken in the spacecraft body coordinates, as well as in the reference coordinate system. We are interested in finding the best estimate of the transformation between these coordinate system.s The algorithm called QUEST yields that estimate where attitude is expressed by a quarternion. Quest is an efficient algorithm which provides a least squares fit of the quaternion of rotation to the vector measurements. Quest however, is a single time point (single frame) batch algorithm, thus measurements that were taken at previous time points are discarded. The algorithm presented in this work provides a recursive routine which considers all past measurements. The algorithm is based on on the fact that the, so called, K matrix, one of whose eigenvectors is the sought quaternion, is linerly related to the measured pairs, and on the ability to propagate K. The extraction of the appropriate eigenvector is done according to the classical QUEST algorithm. This stage, however, can be eliminated, and the computation simplified, if a standard eigenvalue-eigenvector solver algorithm is used. The development of the recursive algorithm is presented and illustrated via a numerical example.

An improved algorithm for balanced POD through an analytic treatment of impulse response tails

NASA Astrophysics Data System (ADS)

Tu, Jonathan H.; Rowley, Clarence W.

2012-06-01

We present a modification of the balanced proper orthogonal decomposition (balanced POD) algorithm for systems with simple impulse response tails. In this new method, we use dynamic mode decomposition (DMD) to estimate the slowly decaying eigenvectors that dominate the long-time behavior of the direct and adjoint impulse responses. This is done using a new, low-memory variant of the DMD algorithm, appropriate for large datasets. We then formulate analytic expressions for the contribution of these eigenvectors to the controllability and observability Gramians. These contributions can be accounted for in the balanced POD algorithm by simply appending the impulse response snapshot matrices (direct and adjoint, respectively) with particular linear combinations of the slow eigenvectors. Aside from these additions to the snapshot matrices, the algorithm remains unchanged. By treating the tails analytically, we eliminate the need to run long impulse response simulations, lowering storage requirements and speeding up ensuing computations. To demonstrate its effectiveness, we apply this method to two examples: the linearized, complex Ginzburg-Landau equation, and the two-dimensional fluid flow past a cylinder. As expected, reduced-order models computed using an analytic tail match or exceed the accuracy of those computed using the standard balanced POD procedure, at a fraction of the cost.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

NASA Astrophysics Data System (ADS)

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; Govind, Niranjan; Yang, Chao

2017-12-01

We present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.

Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

Exact solution of corner-modified banded block-Toeplitz eigensystems

NASA Astrophysics Data System (ADS)

Cobanera, Emilio; Alase, Abhijeet; Ortiz, Gerardo; Viola, Lorenza

2017-05-01

Motivated by the challenge of seeking a rigorous foundation for the bulk-boundary correspondence for free fermions, we introduce an algorithm for determining exactly the spectrum and a generalized-eigenvector basis of a class of banded block quasi-Toeplitz matrices that we call corner-modified. Corner modifications of otherwise arbitrary banded block-Toeplitz matrices capture the effect of boundary conditions and the associated breakdown of translational invariance. Our algorithm leverages the interplay between a non-standard, projector-based method of kernel determination (physically, a bulk-boundary separation) and families of linear representations of the algebra of matrix Laurent polynomials. Thanks to the fact that these representations act on infinite-dimensional carrier spaces in which translation symmetry is restored, it becomes possible to determine the eigensystem of an auxiliary projected block-Laurent matrix. This results in an analytic eigenvector Ansatz, independent of the system size, which we prove is guaranteed to contain the full solution of the original finite-dimensional problem. The actual solution is then obtained by imposing compatibility with a boundary matrix, whose shape is also independent of system size. As an application, we show analytically that eigenvectors of short-ranged fermionic tight-binding models may display power-law corrections to exponential behavior, and demonstrate the phenomenon for the paradigmatic Majorana chain of Kitaev.

The cosmic web and the orientation of angular momenta

NASA Astrophysics Data System (ADS)

Libeskind, Noam I.; Hoffman, Yehuda; Knebe, Alexander; Steinmetz, Matthias; Gottlöber, Stefan; Metuki, Ofer; Yepes, Gustavo

2012-03-01

We use a 64 h-1 Mpc dark-matter-only cosmological simulation to examine the large-scale orientation of haloes and substructures with respect to the cosmic web. A web classification scheme based on the velocity shear tensor is used to assign to each halo in the simulation a web type: knot, filament, sheet or void. Using ˜106 haloes that span ˜3 orders of magnitude in mass, the orientation of the halo's spin and the orbital angular momentum of subhaloes with respect to the eigenvectors of the shear tensor is examined. We find that the orbital angular momentum of subhaloes tends to align with the intermediate eigenvector of the velocity shear tensor for all haloes in knots, filaments and sheets. This result indicates that the kinematics of substructures located deep within the virialized regions of a halo is determined by its infall which in turn is determined by the large-scale velocity shear, a surprising result given the virialized nature of haloes. The non-random nature of subhalo accretion is thus imprinted on the angular momentum measured at z= 0. We also find that the haloes' spin axis is aligned with the third eigenvector of the velocity shear tensor in filaments and sheets: the halo spin axis points along filaments and lies in the plane of cosmic sheets.

Topographical map series in the Map Room of Institute and Museum of Military History in Budapest, Hungary between 1919-1945: Smaller scale series (1:100,000, 1:200,000, 1:300,000, 1:500,000, 1:750,000) of the territory of Central Europe

NASA Astrophysics Data System (ADS)

Jankó, A.; Bánfi, R.

2009-04-01

The Royal Hungarian State Mapping Institute kept the smaller scales series of the third military survey of the Austro-Hungarian Monarchy, too, so the scales 1:200,000 and 1:750,000 maps. The results of the supervisions of larger scales were transferred onto these scales, 1:200,000 and 1:750,000 maps, for the territory of Central Europe. In 1943 a scale 1:500,000 aerial map was accomplished, too, for the territory of Pannonian basin. There are many other important series in the Map Room between 1919 and 1945, including the WWII German edition 1:300,000 scale map series of Central Europe and Russia to the Ural Mts.; and a series of scale 1:100,000 for the territory of Poland and Russia between 1939-1940.

Efficient estimation of three-dimensional covariance and its application in the analysis of heterogeneous samples in cryo-electron microscopy

PubMed Central

Liao, Hstau Y.; Hashem, Yaser; Frank, Joachim

2015-01-01

Summary Single-particle cryogenic electron microscopy (cryo-EM) is a powerful tool for the study of macromolecular structures at high resolution. Classification allows multiple structural states to be extracted and reconstructed from the same sample. One classification approach is via the covariance matrix, which captures the correlation between every pair of voxels. Earlier approaches employ computing-intensive resampling and estimate only the eigenvectors of the matrix, which are then used in a separate fast classification step. We propose an iterative scheme to explicitly estimate the covariance matrix in its entirety. In our approach, the flexibility in choosing the solution domain allows us to examine a part of the molecule in greater detail. 3D covariance maps obtained in this way from experimental data (cryo-EM images of the eukaryotic pre-initiation complex) prove to be in excellent agreement with conclusions derived by using traditional approaches, revealing in addition the interdependencies of ligand bindings and structural changes. PMID:25982529

Efficient estimation of three-dimensional covariance and its application in the analysis of heterogeneous samples in cryo-electron microscopy.

PubMed

Liao, Hstau Y; Hashem, Yaser; Frank, Joachim

2015-06-02

Single-particle cryogenic electron microscopy (cryo-EM) is a powerful tool for the study of macromolecular structures at high resolution. Classification allows multiple structural states to be extracted and reconstructed from the same sample. One classification approach is via the covariance matrix, which captures the correlation between every pair of voxels. Earlier approaches employ computing-intensive resampling and estimate only the eigenvectors of the matrix, which are then used in a separate fast classification step. We propose an iterative scheme to explicitly estimate the covariance matrix in its entirety. In our approach, the flexibility in choosing the solution domain allows us to examine a part of the molecule in greater detail. Three-dimensional covariance maps obtained in this way from experimental data (cryo-EM images of the eukaryotic pre-initiation complex) prove to be in excellent agreement with conclusions derived by using traditional approaches, revealing in addition the interdependencies of ligand bindings and structural changes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A SPECTRAL GRAPH APPROACH TO DISCOVERING GENETIC ANCESTRY1

PubMed Central

Lee, Ann B.; Luca, Diana; Roeder, Kathryn

2010-01-01

Mapping human genetic variation is fundamentally interesting in fields such as anthropology and forensic inference. At the same time, patterns of genetic diversity confound efforts to determine the genetic basis of complex disease. Due to technological advances, it is now possible to measure hundreds of thousands of genetic variants per individual across the genome. Principal component analysis (PCA) is routinely used to summarize the genetic similarity between subjects. The eigenvectors are interpreted as dimensions of ancestry. We build on this idea using a spectral graph approach. In the process we draw on connections between multidimensional scaling and spectral kernel methods. Our approach, based on a spectral embedding derived from the normalized Laplacian of a graph, can produce more meaningful delineation of ancestry than by using PCA. The method is stable to outliers and can more easily incorporate different similarity measures of genetic data than PCA. We illustrate a new algorithm for genetic clustering and association analysis on a large, genetically heterogeneous sample. PMID:20689656

Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxies

NASA Astrophysics Data System (ADS)

Lawlor, David; Budavári, Tamás; Mahoney, Michael W.

2016-12-01

We present a novel approach to studying the diversity of galaxies. It is based on a novel spectral graph technique, that of locally-biased semi-supervised eigenvectors. Our method introduces new coordinates that summarize an entire spectrum, similar to but going well beyond the widely used Principal Component Analysis (PCA). Unlike PCA, however, this technique does not assume that the Euclidean distance between galaxy spectra is a good global measure of similarity. Instead, we relax that condition to only the most similar spectra, and we show that doing so yields more reliable results for many astronomical questions of interest. The global variant of our approach can identify very finely numerous astronomical phenomena of interest. The locally-biased variants of our basic approach enable us to explore subtle trends around a set of chosen objects. The power of the method is demonstrated in the Sloan Digital Sky Survey Main Galaxy Sample, by illustrating that the derived spectral coordinates carry an unprecedented amount of information.

Total Electron Content forecast model over Australia

NASA Astrophysics Data System (ADS)

Bouya, Zahra; Terkildsen, Michael; Francis, Matthew

Ionospheric perturbations can cause serious propagation errors in modern radio systems such as Global Navigation Satellite Systems (GNSS). Forecasting ionospheric parameters is helpful to estimate potential degradation of the performance of these systems. Our purpose is to establish an Australian Regional Total Electron Content (TEC) forecast model at IPS. In this work we present an approach based on the combined use of the Principal Component Analysis (PCA) and Artificial Neural Network (ANN) to predict future TEC values. PCA is used to reduce the dimensionality of the original TEC data by mapping it into its eigen-space. In this process the top- 5 eigenvectors are chosen to reflect the directions of the maximum variability. An ANN approach was then used for the multicomponent prediction. We outline the design of the ANN model with its parameters. A number of activation functions along with different spectral ranges and different numbers of Principal Components (PCs) were tested to find the PCA-ANN models reaching the best results. Keywords: GNSS, Space Weather, Regional, Forecast, PCA, ANN.

Coupling coefficients for tensor product representations of quantum SU(2)

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

Groenevelt, Wolter, E-mail: w.g.m.groenevelt@tudelft.nl

2014-10-15

We study tensor products of infinite dimensional irreducible {sup *}-representations (not corepresentations) of the SU(2) quantum group. We obtain (generalized) eigenvectors of certain self-adjoint elements using spectral analysis of Jacobi operators associated to well-known q-hypergeometric orthogonal polynomials. We also compute coupling coefficients between different eigenvectors corresponding to the same eigenvalue. Since the continuous spectrum has multiplicity two, the corresponding coupling coefficients can be considered as 2 × 2-matrix-valued orthogonal functions. We compute explicitly the matrix elements of these functions. The coupling coefficients can be considered as q-analogs of Bessel functions. As a results we obtain several q-integral identities involving q-hypergeometricmore » orthogonal polynomials and q-Bessel-type functions.« less

Staggered fermions, zero modes, and flavor-singlet mesons

DOE PAGES

Donald, Gordon C; Davies, Christine T.H.; Follana, Eduardo; ...

2011-09-12

We examine the taste structure of eigenvectors of the staggered-fermion Dirac operator. We derive a set of conditions on the eigenvectors of modes with small eigenvalues (near-zero modes), such that staggered fermions reproduce the 't Hooft vertex in the continuum limit. We also show that, assuming these conditions, the correlators of flavor-singlet mesons are free of contributions singular in 1/m, where m is the quark mass. This conclusion holds also when a single flavor of sea quark is represented by the fourth root of the staggered-fermion determinant. We then test numerically, using the HISQ action, whether these conditions hold onmore » realistic lattice gauge fields. We find that the needed structure does indeed emerge.« less

Asymptotics of eigenvalues and eigenvectors of Toeplitz matrices

NASA Astrophysics Data System (ADS)

Böttcher, A.; Bogoya, J. M.; Grudsky, S. M.; Maximenko, E. A.

2017-11-01

Analysis of the asymptotic behaviour of the spectral characteristics of Toeplitz matrices as the dimension of the matrix tends to infinity has a history of over 100 years. For instance, quite a number of versions of Szegő's theorem on the asymptotic behaviour of eigenvalues and of the so-called strong Szegő theorem on the asymptotic behaviour of the determinants of Toeplitz matrices are known. Starting in the 1950s, the asymptotics of the maximum and minimum eigenvalues were actively investigated. However, investigation of the individual asymptotics of all the eigenvalues and eigenvectors of Toeplitz matrices started only quite recently: the first papers on this subject were published in 2009-2010. A survey of this new field is presented here. Bibliography: 55 titles.

Inflationary dynamics for matrix eigenvalue problems

PubMed Central

Heller, Eric J.; Kaplan, Lev; Pollmann, Frank

2008-01-01

Many fields of science and engineering require finding eigenvalues and eigenvectors of large matrices. The solutions can represent oscillatory modes of a bridge, a violin, the disposition of electrons around an atom or molecule, the acoustic modes of a concert hall, or hundreds of other physical quantities. Often only the few eigenpairs with the lowest or highest frequency (extremal solutions) are needed. Methods that have been developed over the past 60 years to solve such problems include the Lanczos algorithm, Jacobi–Davidson techniques, and the conjugate gradient method. Here, we present a way to solve the extremal eigenvalue/eigenvector problem, turning it into a nonlinear classical mechanical system with a modified Lagrangian constraint. The constraint induces exponential inflationary growth of the desired extremal solutions. PMID:18511564

Inertial constraints on limb proprioception are independent of visual calibration.

PubMed

Riley, M A; Turvey, M T

2001-04-01

When the coincidence of a limb's spatial axes and inertial eigenvectors is broken, haptic proprioception of the limb's position conforms to the eigenvectors. Additionally, when prisms break the coincidence between an arm's visual and actual positions, haptic proprioception is shifted toward the visual-spatial direction. In 3 experiments, variation of the arm's mass distribution was combined with prism adaptation to investigate the hypothesis that the proprioceptive effects of inertial and visual manipulations are additive. This hypothesis was supported across manipulations of plane of motion, body posture, proprioceptive target, and proprioceptive experience during prism adaptation. Haptic proprioception seems to depend on local, physical reference frames that are relative to the physical reference frames for the body's environmental position and orientation.

Discrimination of fluoride and phosphate contamination in central Florida for analyses of environmental effects

NASA Technical Reports Server (NTRS)

Coker, A. E.; Marshall, R.; Thomson, F.

1972-01-01

A study was made of the spatial registration of fluoride and phosphate pollution parameters in central Florida by utilizing remote sensing techniques. Multispectral remote sensing data were collected over the area and processed to produce multispectral recognition maps. These processed data were used to map land areas and waters containing concentrations of fluoride and phosphate. Maps showing distribution of affected and unaffected vegetation were produced. In addition, the multispectral data were processed by single band radiometric slicing to produce radiometric maps used to delineate areas of high ultraviolet radiance, which indicates high fluoride concentrations. The multispectral parameter maps and radiometric maps in combination showed distinctive patterns, which are correlated with areas known to be affected by fluoride and phosphate contamination. These remote sensing techniques have the potential for regional use to assess the environmental impact of fluoride and phosphate wastes in central Florida.

Relations of Central Hemodynamics and Aortic Stiffness with Left Ventricular Structure and Function: The Framingham Heart Study.

PubMed

Kaess, Bernhard M; Rong, Jian; Larson, Martin G; Hamburg, Naomi M; Vita, Joseph A; Cheng, Susan; Aragam, Jayashree; Levy, Daniel; Benjamin, Emelia J; Vasan, Ramachandran S; Mitchell, Gary F

2016-03-25

The differing relations of steady and pulsatile components of central hemodynamics and aortic stiffness with cardiac dimensions and function have not been fully elucidated. Central hemodynamics and carotid-femoral pulse wave velocity (CFPWV, a measure of aortic stiffness) were measured by arterial tonometry in 5799 participants of the Framingham Heart Study (mean age 51 years, 54% women) and related to echocardiographic left ventricular (LV) dimensions and systolic and diastolic function using multivariable-adjusted partial Pearson correlations. Mean arterial pressure (MAP, steady component of central blood pressure) was associated positively with LV wall thickness (r=0.168; P<0.0001) but showed only a weak direct association with LV diastolic dimension (r=0.035, P=0.006). Central pulse pressure (pulsatile component of central blood pressure) showed a direct correlation with both LV diastolic dimension and LV wall thickness (r=0.08 and 0.044, both P<0.0001 in multivariable models that included MAP). CFPWV was not associated with LV structure (all P≥0.27) in MAP-adjusted models). Both MAP and CFPWV were associated inversely with LV diastolic function (E'; r=-0.140 and -0.153, respectively; both P<0.0001), and these associations persisted after additional adjustment for LV mass and central pulse pressure (r=-0.142 and -0.108, both P<0.0001). MAP and CFPWV were not associated with LV fractional shortening (P≥0.10), whereas central pulse pressure was positively related (r=0.064, P<0.0001). Pulsatile and steady components of central pressure are conjointly yet variably related to LV structure. CFPWV is related to LV diastolic function but not to systolic function. Additional studies are warranted to confirm these observations. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

7. ENGINE TEST CELL BUILDING INTERIOR. WALL MAP IN CENTRAL ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. ENGINE TEST CELL BUILDING INTERIOR. WALL MAP IN CENTRAL BASEMENT OFFICE AREA. LOOKING SOUTHWEST. - Fairchild Air Force Base, Engine Test Cell Building, Near intersection of Arnold Street & George Avenue, Spokane, Spokane County, WA

Publications - RI 97-15B | Alaska Division of Geological & Geophysical

Science.gov Websites

content DGGS RI 97-15B Publication Details Title: Interpretive geologic bedrock map of the Tanana B-1 ., 1997, Interpretive geologic bedrock map of the Tanana B-1 Quadrangle, central Alaska: Alaska Division bedrock map of the Tanana B-1 Quadrangle, Central Alaska, scale 1:63,360 (8.3 M) Digital Geospatial Data

Geologic Map of the Cedargrove Quadrangle, Dent and Shannon Counties, Missouri

USGS Publications Warehouse

Weary, David J.

2008-01-01

The Cedargrove 7.5-minute quadrangle is located in south-central Missouri within the Salem Plateau region of the Ozark Plateaus physiographic province. Most of the land in the quadrangle is privately owned and used primarily for grazing cattle and horses and growing timber. The map area has topographic relief of about 565 feet (ft), with elevations ranging from about 760 ft at Akers Ferry on the central-southern edge of the map to about 1,325 ft near the town of Jadwin in the north-central part of the map area. The most prominent physiographic features in the quadrangle are the valleys of the Current River and Big Creek in the southwestern part of the map area, and the valley of Gladden Creek, which transects the eastern part of the quadrangle from north to south.

Detecting, anticipating, and predicting critical transitions in spatially extended systems.

PubMed

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

Within this paper, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. Additionally, the solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

In this article, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Possibility of modifying the growth trajectory in Raeini Cashmere goat.

PubMed

Ghiasi, Heydar; Mokhtari, M S

2018-03-27

The objective of this study was to investigate the possibility of modifying the growth trajectory in Raeini Cashmere goat breed. In total, 13,193 records on live body weight collected from 4788 Raeini Cashmere goats were used. According to Akanke's information criterion (AIC), the sing-trait random regression model included fourth-order Legendre polynomial for direct and maternal genetic effect; maternal and individual permanent environmental effect was the best model for estimating (co)variance components. The matrices of eigenvectors for (co)variances between random regression coefficients of direct additive genetic were used to calculate eigenfunctions, and different eigenvector indices were also constructed. The obtained results showed that the first eigenvalue explained 79.90% of total genetic variance. Therefore, changing the body weights applying the first eigenfunction will be obtained rapidly. Selection based on the first eigenvector will cause favorable positive genetic gains for all body weight considered from birth to 12 months of age. For modifying the growth trajectory in Raeini Cashmere goat, the selection should be based on the second eigenfunction. The second eigenvalue accounted for 14.41% of total genetic variance for body weights that is low in comparison with genetic variance explained by the first eigenvalue. The complex patterns of genetic change in growth trajectory observed under the third and fourth eigenfunction and low amount of genetic variance explained by the third and fourth eigenvalues.

Three-dimensional geometry of coronal loops inferred by the Principal Component Analysis

NASA Astrophysics Data System (ADS)

Nisticò, Giuseppe; Nakariakov, Valery

We propose a new method for the determination of the three dimensional (3D) shape of coronal loops from stereoscopy. The common approach requires to find a 1D geometric curve, as circumference or ellipse, that best-fits the 3D tie-points which sample the loop shape in a given coordinate system. This can be easily achieved by the Principal Component (PC) analysis. It mainly consists in calculating the eigenvalues and eigenvectors of the covariance matrix of the 3D tie-points: the eigenvalues give a measure of the variability of the distribution of the tie-points, and the corresponding eigenvectors define a new cartesian reference frame directly related to the loop. The eigenvector associated with the smallest eigenvalues defines the normal to the loop plane, while the other two determine the directions of the loop axes: the major axis is related to the largest eigenvalue, and the minor axis with the second one. The magnitude of the axes is directly proportional to the square roots of these eigenvalues. The technique is fast and easily implemented in some examples, returning best-fitting estimations of the loop parameters and 3D reconstruction with a reasonable small number of tie-points. The method is suitable for serial reconstruction of coronal loops in active regions, providing a useful tool for comparison between observations and theoretical magnetic field extrapolations from potential or force-free fields.

On Statistics of Bi-Orthogonal Eigenvectors in Real and Complex Ginibre Ensembles: Combining Partial Schur Decomposition with Supersymmetry

NASA Astrophysics Data System (ADS)

Fyodorov, Yan V.

2018-06-01

We suggest a method of studying the joint probability density (JPD) of an eigenvalue and the associated `non-orthogonality overlap factor' (also known as the `eigenvalue condition number') of the left and right eigenvectors for non-selfadjoint Gaussian random matrices of size {N× N} . First we derive the general finite N expression for the JPD of a real eigenvalue {λ} and the associated non-orthogonality factor in the real Ginibre ensemble, and then analyze its `bulk' and `edge' scaling limits. The ensuing distribution is maximally heavy-tailed, so that all integer moments beyond normalization are divergent. A similar calculation for a complex eigenvalue z and the associated non-orthogonality factor in the complex Ginibre ensemble is presented as well and yields a distribution with the finite first moment. Its `bulk' scaling limit yields a distribution whose first moment reproduces the well-known result of Chalker and Mehlig (Phys Rev Lett 81(16):3367-3370, 1998), and we provide the `edge' scaling distribution for this case as well. Our method involves evaluating the ensemble average of products and ratios of integer and half-integer powers of characteristic polynomials for Ginibre matrices, which we perform in the framework of a supersymmetry approach. Our paper complements recent studies by Bourgade and Dubach (The distribution of overlaps between eigenvectors of Ginibre matrices, 2018. arXiv:1801.01219).

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

DOE PAGES

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; ...

2017-12-01

In this article, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Evolution of the shock front and turbulence structures in the shock/turbulence interaction

NASA Technical Reports Server (NTRS)

Kevlahan, N.; Mahesh, K.; Lee, S.

1992-01-01

The interaction of a weak shock front with isotropic turbulence has been investigated using Direct Numerical Simulation (DNS). Two problems were considered: the ability of the field equation (the equation for a propagating surface) to model the shock; and a quantitative study of the evolution of turbulence structure using the database generated by Lee et al. Field equation model predictions for front shape have been compared with DNS results; good agreement is found for shock wave interaction with 2D turbulence and for a single steady vorticity wave. In the interaction of 3D isotropic turbulence with a normal shock, strong alignment of vorticity with the intermediate eigenvector of the rate of strain tensor (S(sup *)(sub ij) = S(sub ij) - (1/3)(delta(sub ij))(S(sub kk))) is seen to develop upstream of the shock and to be further amplified on passage through the shock. Vorticity tends to align at 90 deg to the largest eigenvector, but there is no preferred alignment with the smallest eigenvector. Upstream of the shock, the alignments continue to develop even after the velocity derivative skewness saturates. There is a significant tendency, which increases with time throughout the computational domain, for velocity to align with vorticity. The alignment between velocity and vorticity is strongest in eddy regions and weakest in convergence regions.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

DOE PAGES

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue; ...

2017-08-24

Within this paper, we present two efficient iterative algorithms for solving the linear response eigenvalue problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into an eigenvalue problem that involves the product of two matrices M and K. We show that, because MK is self-adjoint with respect to the inner product induced by the matrix K, this product eigenvalue problem can be solved efficiently by amore » modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-inner product. Additionally, the solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. We show that the other component of the eigenvector can be easily recovered in an inexpensive postprocessing procedure. As a result, the algorithms we present here become more efficient than existing methods that try to approximate both components of the eigenvectors simultaneously. In particular, our numerical experiments demonstrate that the new algorithms presented here consistently outperform the existing state-of-the-art Davidson type solvers by a factor of two in both solution time and storage.« less

Method for distinguishing multiple targets using time-reversal acoustics

DOEpatents

Berryman, James G.

2004-06-29

A method for distinguishing multiple targets using time-reversal acoustics. Time-reversal acoustics uses an iterative process to determine the optimum signal for locating a strongly reflecting target in a cluttered environment. An acoustic array sends a signal into a medium, and then receives the returned/reflected signal. This returned/reflected signal is then time-reversed and sent back into the medium again, and again, until the signal being sent and received is no longer changing. At that point, the array has isolated the largest eigenvalue/eigenvector combination and has effectively determined the location of a single target in the medium (the one that is most strongly reflecting). After the largest eigenvalue/eigenvector combination has been determined, to determine the location of other targets, instead of sending back the same signals, the method sends back these time reversed signals, but half of them will also be reversed in sign. There are various possibilities for choosing which half to do sign reversal. The most obvious choice is to reverse every other one in a linear array, or as in a checkerboard pattern in 2D. Then, a new send/receive, send-time reversed/receive iteration can proceed. Often, the first iteration in this sequence will be close to the desired signal from a second target. In some cases, orthogonalization procedures must be implemented to assure the returned signals are in fact orthogonal to the first eigenvector found.

A study of the eigenvectors of the vibrational modes in crystalline cytidine via high-pressure Raman spectroscopy.

PubMed

Lee, Scott A; Pinnick, David A; Anderson, A

2015-01-01

Raman spectroscopy has been used to study the eigenvectors and eigenvalues of the vibrational modes of crystalline cytidine at 295 K and high pressures by evaluating the logarithmic derivative of the vibrational frequency ω with respect to pressure P: [Formula: see text]. Crystalline samples of molecular materials have strong intramolecular bonds and weak intermolecular bonds. This hierarchy of bonding strengths causes the vibrational optical modes localized within a molecular unit ("internal" modes) to be relatively high in frequency while the modes in which the molecular units vibrate against each other ("external" modes) have relatively low frequencies. The value of the logarithmic derivative is a useful diagnostic probe of the nature of the eigenvector of the vibrational modes because stretching modes (which are predominantly internal to the molecule) have low logarithmic derivatives while external modes have higher logarithmic derivatives. In crystalline cytidine, the modes at 85.8, 101.4, and 110.6 cm(-1) are external in which the molecules of the unit cell vibrate against each other in either translational or librational motions (or some linear combination thereof). All of the modes above 320 cm(-1) are predominantly internal stretching modes. The remaining modes below 320 cm(-1) include external modes and internal modes, mostly involving either torsional or bending motions of groups of atoms within a molecule.

Identifying the structure of group correlation in the Korean financial market

NASA Astrophysics Data System (ADS)

Ahn, Sanghyun; Choi, Jaewon; Lim, Gyuchang; Cha, Kil Young; Kim, Sooyong; Kim, Kyungsik

2011-06-01

We investigate the structure of the cross-correlation in the Korean stock market. We analyze daily cross-correlations between price fluctuations of 586 different Korean stock entities for the 6-year time period from 2003 to 2008. The main purpose is to investigate the structure of group correlation and its stability by undressing the market-wide effect using the Markowitz multi-factor model and the network-based approach. We find the explicit list of significant firms in the few largest eigenvectors from the undressed correlation matrix. We also observe that each contributor is involved in the same business sectors. The structure of group correlation can not remain constant during each 1-year time period with different starting points, whereas only two largest eigenvectors are stable for 6 years 8-9 eigenvectors remain stable for half-year. The structure of group correlation in the Korean financial market is disturbed during a sufficiently short time period even though the group correlation exists as an ensemble for the 6-year time period in the evolution of the system. We verify the structure of group correlation by applying a network-based approach. In addition, we examine relations between market capitalization and businesses. The Korean stock market shows a different behavior compared to mature markets, implying that the KOSPI is a target for short-positioned investors.

Detecting, anticipating, and predicting critical transitions in spatially extended systems

NASA Astrophysics Data System (ADS)

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

The Crash Intensity Evaluation Using General Centrality Criterions and a Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Ghadiriyan Arani, M.; Pahlavani, P.; Effati, M.; Noori Alamooti, F.

2017-09-01

Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics

NASA Astrophysics Data System (ADS)

Chen, Lei; Kou, Yingxin; Li, Zhanwu; Xu, An; Wu, Cheng

2018-01-01

We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core-periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes.

Tracking the Resolution of Student Misconceptions about the Central Dogma of Molecular Biology†

PubMed Central

Briggs, Amy G.; Morgan, Stephanie K.; Sanderson, Seth K.; Schulting, Molly C.; Wieseman, Laramie J.

2016-01-01

The goal of our study was to track changes in student understanding of the central dogma of molecular biology before and after taking a genetics course. Concept maps require the ability to synthesize new information into existing knowledge frameworks, and so the hypothesis guiding this study was that student performance on concept maps reveals specific central dogma misconceptions gained, lost, and retained by students. Students in a genetics course completed pre- and posttest concept mapping tasks using terms related to the central dogma. Student maps increased in complexity and validity, indicating learning gains in both content and complexity of understanding. Changes in each of the 351 possible connections in the mapping task were tracked for each student. Our students did not retain much about the central dogma from their introductory biology courses, but they did move to more advanced levels of understanding by the end of the genetics course. The information they retained from their introductory courses focused on structural components (e.g., protein is made of amino acids) and not on overall mechanistic components (e.g., DNA comes before RNA, the ribosome makes protein). Students made the greatest gains in connections related to transcription, and they resolved the most prior misconceptions about translation. These concept-mapping tasks revealed that students are able to correct prior misconceptions about the central dogma during an intermediate-level genetics course. From these results, educators can design new classroom interventions to target those aspects of this foundational principle with which students have the most trouble. PMID:28101260

Tracking the Resolution of Student Misconceptions about the Central Dogma of Molecular Biology.

PubMed

Briggs, Amy G; Morgan, Stephanie K; Sanderson, Seth K; Schulting, Molly C; Wieseman, Laramie J

2016-12-01

The goal of our study was to track changes in student understanding of the central dogma of molecular biology before and after taking a genetics course. Concept maps require the ability to synthesize new information into existing knowledge frameworks, and so the hypothesis guiding this study was that student performance on concept maps reveals specific central dogma misconceptions gained, lost, and retained by students. Students in a genetics course completed pre- and posttest concept mapping tasks using terms related to the central dogma. Student maps increased in complexity and validity, indicating learning gains in both content and complexity of understanding. Changes in each of the 351 possible connections in the mapping task were tracked for each student. Our students did not retain much about the central dogma from their introductory biology courses, but they did move to more advanced levels of understanding by the end of the genetics course. The information they retained from their introductory courses focused on structural components (e.g., protein is made of amino acids) and not on overall mechanistic components (e.g., DNA comes before RNA, the ribosome makes protein). Students made the greatest gains in connections related to transcription, and they resolved the most prior misconceptions about translation. These concept-mapping tasks revealed that students are able to correct prior misconceptions about the central dogma during an intermediate-level genetics course. From these results, educators can design new classroom interventions to target those aspects of this foundational principle with which students have the most trouble.

Susceptibility Tensor Imaging (STI) of the Brain

PubMed Central

Li, Wei; Liu, Chunlei; Duong, Timothy Q.; van Zijl, Peter C.M.; Li, Xu

2016-01-01

Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping (QSM) to remove such dependence. Similar to diffusion tensor imaging (DTI), STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of susceptibility anisotropy in brain white matter is myelin. Another unique feature of susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. PMID:27120169

Earthquakes of the Central United States, 1795-2002

USGS Publications Warehouse

Wheeler, Russell L.

2003-01-01

This report describes construction of a list of Central U.S. earthquakes to be shown on a large-format map that is targeted for a non-technical audience. The map shows the locations and sizes of historical earthquakes of magnitude 3.0 or larger over the most seismically active part of the central U.S., including the New Madrid seismic zone. The map shows more than one-half million square kilometers and parts or all of ten States. No existing earthquake catalog had provided current, uniform coverage down to magnitude 3.0, so one had to be made. Consultation with State geological surveys insured compatibility with earthquake lists maintained by them, thereby allowing the surveys and the map to present consistent information to the public.

Squared eigenvalue condition numbers and eigenvector correlations from the single ring theorem

NASA Astrophysics Data System (ADS)

Belinschi, Serban; Nowak, Maciej A.; Speicher, Roland; Tarnowski, Wojciech

2017-03-01

We extend the so-called ‘single ring theorem’ (Feinberg and Zee 1997 Nucl. Phys. B 504 579), also known as the Haagerup-Larsen theorem (Haagerup and Larsen 2000 J. Funct. Anal. 176 331). We do this by showing that in the limit when the size of the matrix goes to infinity a particular correlator between left and right eigenvectors of the relevant non-hermitian matrix X, being the spectral density weighted by the squared eigenvalue condition number, is given by a simple formula involving only the radial spectral cumulative distribution function of X. We show that this object allows the calculation of the conditional expectation of the squared eigenvalue condition number. We give examples and provide a cross-check of the analytic prediction by the large scale numerics.

Anderson Localization in Quark-Gluon Plasma

NASA Astrophysics Data System (ADS)

Kovács, Tamás G.; Pittler, Ferenc

2010-11-01

At low temperature the low end of the QCD Dirac spectrum is well described by chiral random matrix theory. In contrast, at high temperature there is no similar statistical description of the spectrum. We show that at high temperature the lowest part of the spectrum consists of a band of statistically uncorrelated eigenvalues obeying essentially Poisson statistics and the corresponding eigenvectors are extremely localized. Going up in the spectrum the spectral density rapidly increases and the eigenvectors become more and more delocalized. At the same time the spectral statistics gradually crosses over to the bulk statistics expected from the corresponding random matrix ensemble. This phenomenon is reminiscent of Anderson localization in disordered conductors. Our findings are based on staggered Dirac spectra in quenched lattice simulations with the SU(2) gauge group.

Existence and analyticity of eigenvalues of a two-channel molecular resonance model

NASA Astrophysics Data System (ADS)

Lakaev, S. N.; Latipov, Sh. M.

2011-12-01

We consider a family of operators Hγμ(k), k ∈ mathbb{T}^d := (-π,π]d, associated with the Hamiltonian of a system consisting of at most two particles on a d-dimensional lattice ℤd, interacting via both a pair contact potential (μ > 0) and creation and annihilation operators (γ > 0). We prove the existence of a unique eigenvalue of Hγμ(k), k ∈ mathbb{T}^d , or its absence depending on both the interaction parameters γ,μ ≥ 0 and the system quasimomentum k ∈ mathbb{T}^d . We show that the corresponding eigenvector is analytic. We establish that the eigenvalue and eigenvector are analytic functions of the quasimomentum k ∈ mathbb{T}^d in the existence domain G ⊂ mathbb{T}^d.

Automated Analysis, Classification, and Display of Waveforms

NASA Technical Reports Server (NTRS)

Kwan, Chiman; Xu, Roger; Mayhew, David; Zhang, Frank; Zide, Alan; Bonggren, Jeff

2004-01-01

A computer program partly automates the analysis, classification, and display of waveforms represented by digital samples. In the original application for which the program was developed, the raw waveform data to be analyzed by the program are acquired from space-shuttle auxiliary power units (APUs) at a sampling rate of 100 Hz. The program could also be modified for application to other waveforms -- for example, electrocardiograms. The program begins by performing principal-component analysis (PCA) of 50 normal-mode APU waveforms. Each waveform is segmented. A covariance matrix is formed by use of the segmented waveforms. Three eigenvectors corresponding to three principal components are calculated. To generate features, each waveform is then projected onto the eigenvectors. These features are displayed on a three-dimensional diagram, facilitating the visualization of the trend of APU operations.

An Exactly Solvable Spin Chain Related to Hahn Polynomials

NASA Astrophysics Data System (ADS)

Stoilova, Neli I.; van der Jeugt, Joris

2011-03-01

We study a linear spin chain which was originally introduced by Shi et al. [Phys. Rev. A 71 (2005), 032309, 5 pages], for which the coupling strength contains a parameter α and depends on the parity of the chain site. Extending the model by a second parameter β, it is shown that the single fermion eigenstates of the Hamiltonian can be computed in explicit form. The components of these eigenvectors turn out to be Hahn polynomials with parameters (α,β) and (α+1,β-1). The construction of the eigenvectors relies on two new difference equations for Hahn polynomials. The explicit knowledge of the eigenstates leads to a closed form expression for the correlation function of the spin chain. We also discuss some aspects of a q-extension of this model.

Complex correlation approach for high frequency financial data

NASA Astrophysics Data System (ADS)

Wilinski, Mateusz; Ikeda, Yuichi; Aoyama, Hideaki

2018-02-01

We propose a novel approach that allows the calculation of a Hilbert transform based complex correlation for unevenly spaced data. This method is especially suitable for high frequency trading data, which are of a particular interest in finance. Its most important feature is the ability to take into account lead-lag relations on different scales, without knowing them in advance. We also present results obtained with this approach while working on Tokyo Stock Exchange intraday quotations. We show that individual sectors and subsectors tend to form important market components which may follow each other with small but significant delays. These components may be recognized by analysing eigenvectors of complex correlation matrix for Nikkei 225 stocks. Interestingly, sectorial components are also found in eigenvectors corresponding to the bulk eigenvalues, traditionally treated as noise.

Geologic Map of the Pueblo of Isleta Tribal Lands and Vicinity, Bernalillo, Torrance, and Valencia Counties, Central New Mexico

USGS Publications Warehouse

Maldonado, Florian; Slate, Janet L.; Love, Dave W.; Connell, Sean D.; Cole, James C.; Karlstrom, Karl E.

2007-01-01

This 1:50,000-scale map compiles geologic mapping of the Pueblo of Isleta tribal lands and vicinity in the central part of the Albuquerque Basin in central New Mexico. The map synthesizes new geologic mapping and summarizes the stratigraphy, structure, and geomorphology of an area of approximately 2,000 km2 that spans the late Paleogene-Neogene Rio Grande rift south of Albuquerque, N. Mex. The map is part of studies conducted between 1996 and 2001 under the U.S. Geological Survey (USGS) Middle Rio Grande Basin Study by geologists from the USGS, the New Mexico Bureau of Geology and Mineral Resources (NMBGMR), and the University of New Mexico (UNM). This work was conducted in order to investigate the geologic factors that influence ground-water resources of the Middle Rio Grande Basin, and to provide new insights into the complex geologic history of the Rio Grande rift in this region.

RANDOM MATRIX DIAGONALIZATION--A COMPUTER PROGRAM

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

Fuchel, K.; Greibach, R.J.; Porter, C.E.

A computer prograra is described which generates random matrices, diagonalizes them and sorts appropriately the resulting eigenvalues and eigenvector components. FAP and FORTRAN listings for the IBM 7090 computer are included. (auth)

Childhood Physical and Sexual Abuse and Social Network Patterns on Social Media: Associations With Alcohol Use and Problems Among Young Adult Women

PubMed Central

Oshri, Assaf; Himelboim, Itai; Kwon, Josephine A.; Sutton, Tara E.; Mackillop, James

2015-01-01

Objective: The aim of the present study was to examine the links between severities of child abuse (physical vs. sexual), and alcohol use versus problems via social media (Facebook) peer connection structures. Method: A total of 318 undergraduate female students at a public university in the United States reported severity of child abuse experiences and current alcohol use and problems. Social network data were obtained directly from the individuals’ Facebook network. Results: Severity of childhood physical abuse was positively linked to alcohol use and problems via eigenvector centrality, whereas severity of childhood sexual abuse was negatively linked to alcohol use and problems via clustering coefficient. Conclusions: Childhood physical and sexual abuse were linked positively and negatively, respectively, to online social network patterns associated with alcohol use and problems. The study suggests the potential utility of these online network patterns as risk indices and ultimately using social media as a platform for targeted preventive interventions. PMID:26562592

Discontinuous Galerkin Methods for NonLinear Differential Systems

NASA Technical Reports Server (NTRS)

Barth, Timothy; Mansour, Nagi (Technical Monitor)

2001-01-01

This talk considers simplified finite element discretization techniques for first-order systems of conservation laws equipped with a convex (entropy) extension. Using newly developed techniques in entropy symmetrization theory, simplified forms of the discontinuous Galerkin (DG) finite element method have been developed and analyzed. The use of symmetrization variables yields numerical schemes which inherit global entropy stability properties of the PDE (partial differential equation) system. Central to the development of the simplified DG methods is the Eigenvalue Scaling Theorem which characterizes right symmetrizers of an arbitrary first-order hyperbolic system in terms of scaled eigenvectors of the corresponding flux Jacobian matrices. A constructive proof is provided for the Eigenvalue Scaling Theorem with detailed consideration given to the Euler equations of gas dynamics and extended conservation law systems derivable as moments of the Boltzmann equation. Using results from kinetic Boltzmann moment closure theory, we then derive and prove energy stability for several approximate DG fluxes which have practical and theoretical merit.

Childhood Physical and Sexual Abuse and Social Network Patterns on Social Media: Associations With Alcohol Use and Problems Among Young Adult Women.

PubMed

Oshri, Assaf; Himelboim, Itai; Kwon, Josephine A; Sutton, Tara E; Mackillop, James

2015-11-01

The aim of the present study was to examine the links between severities of child abuse (physical vs. sexual), and alcohol use versus problems via social media (Facebook) peer connection structures. A total of 318 undergraduate female students at a public university in the United States reported severity of child abuse experiences and current alcohol use and problems. Social network data were obtained directly from the individuals' Facebook network. Severity of childhood physical abuse was positively linked to alcohol use and problems via eigenvector centrality, whereas severity of childhood sexual abuse was negatively linked to alcohol use and problems via clustering coefficient. Childhood physical and sexual abuse were linked positively and negatively, respectively, to online social network patterns associated with alcohol use and problems. The study suggests the potential utility of these online network patterns as risk indices and ultimately using social media as a platform for targeted preventive interventions.

Shock and Rarefaction Waves in a Heterogeneous Mantle

NASA Astrophysics Data System (ADS)

Jordan, J.; Hesse, M. A.

2012-12-01

We explore the effect of heterogeneities on partial melting and melt migration during active upwelling in the Earth's mantle. We have constructed simple, explicit nonlinear models in one dimension to examine heterogeneity and its dynamic affects on porosity, temperature and the magnesium number in a partially molten, porous medium comprised of olivine. The composition of the melt and solid are defined by a closed, binary phase diagram for a simplified, two-component olivine system. The two-component solid solution is represented by a phase loop where concentrations 0 and 1 to correspond to fayalite and forsterite, respectively. For analysis, we examine an advective system with a Riemann initial condition. Chromatographic tools and theory have primarily been used to track large, rare earth elements as tracers. In our case, we employ these theoretical tools to highlight the importance of the magnesium number, enthalpy and overall heterogeneity in the dynamics of melt migration. We calculate the eigenvectors and eigenvalues in the concentration-enthalpy space in order to glean the characteristics of the waves emerging the Riemann step. Analysis on Riemann problems of this nature shows us that the composition-enthalpy waves can be represented by self-similar solutions. The eigenvalues of the composition-enthalpy system represent the characteristic wave propagation speeds of the compositions and enthalpy through the domain. Furthermore, the corresponding eigenvectors are the directions of variation, or ``pathways," in concentration-enthalpy space that the characteristic waves follow. In the two-component system, the Riemann problem yields two waves connected by an intermediate concentration-enthalpy state determined by the intersections of the integral curves of the eigenvectors emanating from both the initial and boundary states. The first wave, ``slow path," and second wave, ``fast path," follow the aformentioned pathways set by the eigenvectors. The slow path wave has a zero eigenvalue, corresponding to a wave speed of zero, which preserves a residual imprint of the initial condition. Freezing fronts textemdash those that result in a negative change in porositytextemdash feature fast path waves that travel as shocks, whereas the fast path waves of melting fronts travel as spreading, rarefaction waves.

Principal Component Analysis of Thermographic Data

NASA Technical Reports Server (NTRS)

Winfree, William P.; Cramer, K. Elliott; Zalameda, Joseph N.; Howell, Patricia A.; Burke, Eric R.

2015-01-01

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.

Eigenspace techniques for active flutter suppression

NASA Technical Reports Server (NTRS)

Garrard, William L.; Liebst, Bradley S.; Farm, Jerome A.

1987-01-01

The use of eigenspace techniques for the design of an active flutter suppression system for a hypothetical research drone is discussed. One leading edge and two trailing edge aerodynamic control surfaces and four sensors (accelerometers) are available for each wing. Full state control laws are designed by selecting feedback gains which place closed loop eigenvalues and shape closed loop eigenvectors so as to stabilize wing flutter and reduce gust loads at the wing root while yielding accepatable robustness and satisfying constrains on rms control surface activity. These controllers are realized by state estimators designed using an eigenvalue placement/eigenvector shaping technique which results in recovery of the full state loop transfer characteristics. The resulting feedback compensators are shown to perform almost as well as the full state designs. They also exhibit acceptable performance in situations in which the failure of an actuator is simulated.

Viewing Angle Classification of Cryo-Electron Microscopy Images Using Eigenvectors

PubMed Central

Singer, A.; Zhao, Z.; Shkolnisky, Y.; Hadani, R.

2012-01-01

The cryo-electron microscopy (cryo-EM) reconstruction problem is to find the three-dimensional structure of a macromolecule given noisy versions of its two-dimensional projection images at unknown random directions. We introduce a new algorithm for identifying noisy cryo-EM images of nearby viewing angles. This identification is an important first step in three-dimensional structure determination of macromolecules from cryo-EM, because once identified, these images can be rotationally aligned and averaged to produce “class averages” of better quality. The main advantage of our algorithm is its extreme robustness to noise. The algorithm is also very efficient in terms of running time and memory requirements, because it is based on the computation of the top few eigenvectors of a specially designed sparse Hermitian matrix. These advantages are demonstrated in numerous numerical experiments. PMID:22506089

Eigenmode computation of cavities with perturbed geometry using matrix perturbation methods applied on generalized eigenvalue problems

NASA Astrophysics Data System (ADS)

Gorgizadeh, Shahnam; Flisgen, Thomas; van Rienen, Ursula

2018-07-01

Generalized eigenvalue problems are standard problems in computational sciences. They may arise in electromagnetic fields from the discretization of the Helmholtz equation by for example the finite element method (FEM). Geometrical perturbations of the structure under concern lead to a new generalized eigenvalue problems with different system matrices. Geometrical perturbations may arise by manufacturing tolerances, harsh operating conditions or during shape optimization. Directly solving the eigenvalue problem for each perturbation is computationally costly. The perturbed eigenpairs can be approximated using eigenpair derivatives. Two common approaches for the calculation of eigenpair derivatives, namely modal superposition method and direct algebraic methods, are discussed in this paper. Based on the direct algebraic methods an iterative algorithm is developed for efficiently calculating the eigenvalues and eigenvectors of the perturbed geometry from the eigenvalues and eigenvectors of the unperturbed geometry.

Preliminary demonstration of a robust controller design method

NASA Technical Reports Server (NTRS)

Anderson, L. R.

1980-01-01

Alternative computational procedures for obtaining a feedback control law which yields a control signal based on measurable quantitites are evaluated. The three methods evaluated are: (1) the standard linear quadratic regulator design model; (2) minimization of the norm of the feedback matrix, k via nonlinear programming subject to the constraint that the closed loop eigenvalues be in a specified domain in the complex plane; and (3) maximize the angles between the closed loop eigenvectors in combination with minimizing the norm of K also via the constrained nonlinear programming. The third or robust design method was chosen to yield a closed loop system whose eigenvalues are insensitive to small changes in the A and B matrices. The relationship between orthogonality of closed loop eigenvectors and the sensitivity of closed loop eigenvalues is described. Computer programs are described.

Matrix superpotentials

NASA Astrophysics Data System (ADS)

Nikitin, Anatoly G.; Karadzhov, Yuri

2011-07-01

We present a collection of matrix-valued shape invariant potentials which give rise to new exactly solvable problems of SUSY quantum mechanics. It includes all irreducible matrix superpotentials of the generic form W=kQ+\\frac{1}{k} R+P, where k is a variable parameter, Q is the unit matrix multiplied by a real-valued function of independent variable x, and P and R are the Hermitian matrices depending on x. In particular, we recover the Pron'ko-Stroganov 'matrix Coulomb potential' and all known scalar shape invariant potentials of SUSY quantum mechanics. In addition, five new shape invariant potentials are presented. Three of them admit a dual shape invariance, i.e. the related Hamiltonians can be factorized using two non-equivalent superpotentials. We find discrete spectrum and eigenvectors for the corresponding Schrödinger equations and prove that these eigenvectors are normalizable.

Intelligent diagnosis of short hydraulic signal based on improved EEMD and SVM with few low-dimensional training samples

NASA Astrophysics Data System (ADS)

Zhang, Meijun; Tang, Jian; Zhang, Xiaoming; Zhang, Jiaojiao

2016-03-01

The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors, however the characteristics of the signal need to be extracted accurately. Although the existing EMD(empirical mode decomposition) and EEMD(ensemble empirical mode decomposition) are suitable for processing non-stationary and non-linear signals, but when a short signal, such as a hydraulic impact signal, is concerned, their decomposition accuracy become very poor. An improve EEMD is proposed specifically for short hydraulic impact signals. The improvements of this new EEMD are mainly reflected in four aspects, including self-adaptive de-noising based on EEMD, signal extension based on SVM(support vector machine), extreme center fitting based on cubic spline interpolation, and pseudo component exclusion based on cross-correlation analysis. After the energy eigenvector is extracted from the result of the improved EEMD, the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied. At last, the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods, and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high. The improved EEMD is very propitious for the decomposition of short signal, such as hydraulic impact signal, and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.

Scale dependence of the alignment between strain rate and rotation in turbulent shear flow

NASA Astrophysics Data System (ADS)

Fiscaletti, D.; Elsinga, G. E.; Attili, A.; Bisetti, F.; Buxton, O. R. H.

2016-10-01

The scale dependence of the statistical alignment tendencies of the eigenvectors of the strain-rate tensor ei, with the vorticity vector ω , is examined in the self-preserving region of a planar turbulent mixing layer. Data from a direct numerical simulation are filtered at various length scales and the probability density functions of the magnitude of the alignment cosines between the two unit vectors | ei.ω ̂| are examined. It is observed that the alignment tendencies are insensitive to the concurrent large-scale velocity fluctuations, but are quantitatively affected by the nature of the concurrent large-scale velocity-gradient fluctuations. It is confirmed that the small-scale (local) vorticity vector is preferentially aligned in parallel with the large-scale (background) extensive strain-rate eigenvector e1, in contrast to the global tendency for ω to be aligned in parallel with the intermediate strain-rate eigenvector [Hamlington et al., Phys. Fluids 20, 111703 (2008), 10.1063/1.3021055]. When only data from regions of the flow that exhibit strong swirling are included, the so-called high-enstrophy worms, the alignment tendencies are exaggerated with respect to the global picture. These findings support the notion that the production of enstrophy, responsible for a net cascade of turbulent kinetic energy from large scales to small scales, is driven by vorticity stretching due to the preferential parallel alignment between ω and nonlocal e1 and that the strongly swirling worms are kinematically significant to this process.

Linear algebra of the permutation invariant Crow-Kimura model of prebiotic evolution.

PubMed

Bratus, Alexander S; Novozhilov, Artem S; Semenov, Yuri S

2014-10-01

A particular case of the famous quasispecies model - the Crow-Kimura model with a permutation invariant fitness landscape - is investigated. Using the fact that the mutation matrix in the case of a permutation invariant fitness landscape has a special tridiagonal form, a change of the basis is suggested such that in the new coordinates a number of analytical results can be obtained. In particular, using the eigenvectors of the mutation matrix as the new basis, we show that the quasispecies distribution approaches a binomial one and give simple estimates for the speed of convergence. Another consequence of the suggested approach is a parametric solution to the system of equations determining the quasispecies. Using this parametric solution we show that our approach leads to exact asymptotic results in some cases, which are not covered by the existing methods. In particular, we are able to present not only the limit behavior of the leading eigenvalue (mean population fitness), but also the exact formulas for the limit quasispecies eigenvector for special cases. For instance, this eigenvector has a geometric distribution in the case of the classical single peaked fitness landscape. On the biological side, we propose a mathematical definition, based on the closeness of the quasispecies to the binomial distribution, which can be used as an operational definition of the notorious error threshold. Using this definition, we suggest two approximate formulas to estimate the critical mutation rate after which the quasispecies delocalization occurs. Copyright © 2014 Elsevier Inc. All rights reserved.

SOIL RADON POTENTIAL MAPPLING OF TWELVE COUNTIES IN NORTH-CENTRAL FLORIDA

EPA Science Inventory

The report describes the approach, methods, and detailed data used to prepare soil radon potential maps of 12 counties in North-Central Florida. he maps were developed under the Florida Radon Research Program to provide a scientific basis for implementing radon-protective buildin...

Comparing an Atomic Model or Structure to a Corresponding Cryo-electron Microscopy Image at the Central Axis of a Helix.

PubMed

Zeil, Stephanie; Kovacs, Julio; Wriggers, Willy; He, Jing

2017-01-01

Three-dimensional density maps of biological specimens from cryo-electron microscopy (cryo-EM) can be interpreted in the form of atomic models that are modeled into the density, or they can be compared to known atomic structures. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. This method was applied to 79 helices in simulated density maps and six case studies using cryo-EM maps at 6.4-7.7 Å resolution. The arc-length association method is then compared to three existing measures that evaluate the separation of two helical axes: a two-way distance between point sets, the length difference between two axes, and the individual amino acid detection accuracy. The results show that our proposed method sensitively distinguishes lateral and longitudinal discrepancies between the two axes, which makes the method particularly suitable for the systematic investigation of cryo-EM map-model pairs.

Publications - PDF 95-33B | Alaska Division of Geological & Geophysical

Science.gov Websites

D-1, C-1, and part of the B-1 quadrangles, east-central Alaska Authors: Clough, J.G., Mull, C.G , Interpretive bedrock geologic map of the Charley River D-1, C-1, and part of the B-1 quadrangles, east-central 1:63,360. http://doi.org/10.14509/1713 Publication Products Maps & Other Oversized Sheets Maps

Map showing geologic terranes of the Hailey 1 degree x 2 degrees quadrangle and the western part of the Idaho Falls 1 degree x 2 degrees quadrangle, south-central Idaho

USGS Publications Warehouse

Worl, R.G.; Johnson, K.M.

1995-01-01

The paper version of Map Showing Geologic Terranes of the Hailey 1x2 Quadrangle and the western part of the Idaho Falls 1x2 Quadrangle, south-central Idaho was compiled by Ron Worl and Kate Johnson in 1995. The plate was compiled on a 1:250,000 scale topographic base map. TechniGraphic System, Inc. of Fort Collins Colorado digitized this map under contract for N.Shock. G.Green edited and prepared the digital version for publication as a geographic information system database. The digital geologic map database can be queried in many ways to produce a variety of geologic maps.

DIGITAL GEOLOGIC MAP OF SHERMAN QUADRANGLE, NORTH CENTRAL TEXAS (CD-ROM)

EPA Science Inventory

This compact disc contains digital data sets of the surficial geology and geologic faults for the 1:250,000-scale Sherman quadrangle, North Central Texas, and can be used to make geologic maps, and determine approximate areas and locations of various geologic units. The source d...

Central Limit Theorems for the Shrinking Target Problem

NASA Astrophysics Data System (ADS)

Haydn, Nicolai; Nicol, Matthew; Vaienti, Sandro; Zhang, Licheng

2013-12-01

Suppose B i := B( p, r i ) are nested balls of radius r i about a point p in a dynamical system ( T, X, μ). The question of whether T i x∈ B i infinitely often (i.o.) for μ a.e. x is often called the shrinking target problem. In many dynamical settings it has been shown that if diverges then there is a quantitative rate of entry and for μ a.e. x∈ X. This is a self-norming type of strong law of large numbers. We establish self-norming central limit theorems (CLT) of the form (in distribution) for a variety of hyperbolic and non-uniformly hyperbolic dynamical systems, the normalization constants are . Dynamical systems to which our results apply include smooth expanding maps of the interval, Rychlik type maps, Gibbs-Markov maps, rational maps and, in higher dimensions, piecewise expanding maps. For such central limit theorems the main difficulty is to prove that the non-stationary variance has a limit in probability.

LANDSAT (ERTS) used as a basis for geological volcanological mapping in the central Andes

NASA Technical Reports Server (NTRS)

Kussmaul, S.; Brockman, C. E.

1977-01-01

LANDSAT images of the central Andes (N-Chile, W-Bolivia) were effectively used for volcanological mapping of an area about 160,000 km. The map shown exhibits more and better details than the older small scale geological maps of that area. Even on a scale of 1:1,000,000 details greater than 200 m in size are recognizable. The interpretation of LANDSAT images makes it possible to establish relative age sequences of strato-volcanoes. Finally, the images will also be helpful in prospecting for mineral deposits and geothermal sources.

Comparison of an Atomic Model and Its Cryo-EM Image at the Central Axis of a Helix

PubMed Central

He, Jing; Zeil, Stephanie; Hallak, Hussam; McKaig, Kele; Kovacs, Julio; Wriggers, Willy

2016-01-01

Cryo-electron microscopy (cryo-EM) is an important biophysical technique that produces three-dimensional (3D) density maps at different resolutions. Because more and more models are being produced from cryo-EM density maps, validation of the models is becoming important. We propose a method for measuring local agreement between a model and the density map using the central axis of the helix. This method was tested using 19 helices from cryo-EM density maps between 5.5 Å and 7.2 Å resolution and 94 helices from simulated density maps. This method distinguished most of the well-fitting helices, although challenges exist for shorter helices. PMID:27280059

Ideal flow theory for the double - shearing model as a basis for metal forming design

NASA Astrophysics Data System (ADS)

Alexandrov, S.; Trung, N. T.

2018-02-01

In the case of Tresca’ solids (i.e. solids obeying the Tresca yield criterion and its associated flow rule) ideal flows have been defined elsewhere as solenoidal smooth deformations in which an eigenvector field associated everywhere with the greatest principal stress (and strain rate) is fixed in the material. Under such conditions all material elements undergo paths of minimum plastic work, a condition which is often advantageous for metal forming processes. Therefore, the ideal flow theory is used as the basis of a procedure for the preliminary design of such processes. The present paper extends the theory of stationary planar ideal flow to pressure dependent materials obeying the double shearing model and the double slip and rotation model. It is shown that the original problem of plasticity reduces to a purely geometric problem. The corresponding system of equations is hyperbolic. The characteristic relations are integrated in elementary functions. In regions where one family of characteristics is straight, mapping between the principal lines and Cartesian coordinates is determined by linear ordinary differential equations. An illustrative example is provided.

Multiway spectral community detection in networks

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Newman, M. E. J.

2015-11-01

One of the most widely used methods for community detection in networks is the maximization of the quality function known as modularity. Of the many maximization techniques that have been used in this context, some of the most conceptually attractive are the spectral methods, which are based on the eigenvectors of the modularity matrix. Spectral algorithms have, however, been limited, by and large, to the division of networks into only two or three communities, with divisions into more than three being achieved by repeated two-way division. Here we present a spectral algorithm that can directly divide a network into any number of communities. The algorithm makes use of a mapping from modularity maximization to a vector partitioning problem, combined with a fast heuristic for vector partitioning. We compare the performance of this spectral algorithm with previous approaches and find it to give superior results, particularly in cases where community sizes are unbalanced. We also give demonstrative applications of the algorithm to two real-world networks and find that it produces results in good agreement with expectations for the networks studied.

Watershed-based segmentation of the corpus callosum in diffusion MRI

NASA Astrophysics Data System (ADS)

Freitas, Pedro; Rittner, Leticia; Appenzeller, Simone; Lapa, Aline; Lotufo, Roberto

2012-02-01

The corpus callosum (CC) is one of the most important white matter structures of the brain, interconnecting the two cerebral hemispheres, and is related to several neurodegenerative diseases. Since segmentation is usually the first step for studies in this structure, and manual volumetric segmentation is a very time-consuming task, it is important to have a robust automatic method for CC segmentation. We propose here an approach for fully automatic 3D segmentation of the CC in the magnetic resonance diffusion tensor images. The method uses the watershed transform and is performed on the fractional anisotropy (FA) map weighted by the projection of the principal eigenvector in the left-right direction. The section of the CC in the midsagittal slice is used as seed for the volumetric segmentation. Experiments with real diffusion MRI data showed that the proposed method is able to quickly segment the CC without any user intervention, with great results when compared to manual segmentation. Since it is simple, fast and does not require parameter settings, the proposed method is well suited for clinical applications.

Multi-scale interactions between local hydrography, seabed topography, and community assembly on cold-water coral reefs

NASA Astrophysics Data System (ADS)

Henry, L.-A.; Moreno Navas, J.; Roberts, J. M.

2013-04-01

We investigated how interactions between hydrography, topography and species ecology influence the assembly of species and functional traits across multiple spatial scales of a cold-water coral reef seascape. In a novel approach for these ecosystems, we used a spatially resolved complex three-dimensional flow model of hydrography to help explain assembly patterns. Forward-selection of distance-based Moran's eigenvector mapping (dbMEM) variables identified two submodels of spatial scales at which communities change: broad-scale (across reef) and fine-scale (within reef). Variance partitioning identified bathymetric and hydrographic gradients important in creating broad-scale assembly of species and traits. In contrast, fine-scale assembly was related more to processes that created spatially autocorrelated patches of fauna, such as philopatric recruitment in sessile fauna, and social interactions and food supply in scavenging detritivores and mobile predators. Our study shows how habitat modification of reef connectivity and hydrography by bottom fishing and renewable energy installations could alter the structure and function of an entire cold-water coral reef seascape.

Modeling infection transmission in primate networks to predict centrality-based risk.

PubMed

Romano, Valéria; Duboscq, Julie; Sarabian, Cécile; Thomas, Elodie; Sueur, Cédric; MacIntosh, Andrew J J

2016-07-01

Social structure can theoretically regulate disease risk by mediating exposure to pathogens via social proximity and contact. Investigating the role of central individuals within a network may help predict infectious agent transmission as well as implement disease control strategies, but little is known about such dynamics in real primate networks. We combined social network analysis and a modeling approach to better understand transmission of a theoretical infectious agent in wild Japanese macaques, highly social animals which form extended but highly differentiated social networks. We collected focal data from adult females living on the islands of Koshima and Yakushima, Japan. Individual identities as well as grooming networks were included in a Markov graph-based simulation. In this model, the probability that an individual will transmit an infectious agent depends on the strength of its relationships with other group members. Similarly, its probability of being infected depends on its relationships with already infected group members. We correlated: (i) the percentage of subjects infected during a latency-constrained epidemic; (ii) the mean latency to complete transmission; (iii) the probability that an individual is infected first among all group members; and (iv) each individual's mean rank in the chain of transmission with different individual network centralities (eigenvector, strength, betweenness). Our results support the hypothesis that more central individuals transmit infections in a shorter amount of time and to more subjects but also become infected more quickly than less central individuals. However, we also observed that the spread of infectious agents on the Yakushima network did not always differ from expectations of spread on random networks. Generalizations about the importance of observed social networks in pathogen flow should thus be made with caution, since individual characteristics in some real world networks appear less relevant than they are in others in predicting disease spread. Am. J. Primatol. 78:767-779, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Networking Matters: A Social Network Analysis of the Association of Program Directors of Internal Medicine.

PubMed

Warm, Eric; Arora, Vineet M; Chaudhry, Saima; Halvorsen, Andrew; Schauer, Daniel; Thomas, Kris; McDonald, Furman S

2018-03-22

Networking has positive effects on career development; however, personal characteristics of group members such as gender or diversity may foster or hinder member connectedness. Social network analysis explores interrelationships between people in groups by measuring the strength of connection between all possible pairs in a given network. Social network analysis has rarely been used to examine network connections among members in an academic medical society. This study seeks to ascertain the strength of connection between program directors in the Association of Program Directors in Internal Medicine (APDIM) and its Education Innovations Project subgroup and to examine possible associations between connectedness and characteristics of program directors and programs. We hypothesize that connectedness will be measurable within a large academic medical society and will vary significantly for program directors with certain measurable characteristics (e.g., age, gender, rank, location, burnout levels, desire to resign). APDIM program directors described levels of connectedness to one another on the 2012 APDIM survey. Using social network analysis, we ascertained program director connectedness by measuring out-degree centrality, in-degree centrality, and eigenvector centrality, all common measures of connectedness. Higher centrality was associated with completion of the APDIM survey, being in a university-based program, Educational Innovations Project participation, and higher academic rank. Centrality did not vary by gender; international medical graduate status; previous chief resident status; program region; or levels of reported program director burnout, callousness, or desire to resign. In this social network analysis of program directors within a large academic medical society, we found that connectedness was related to higher academic rank and certain program characteristics but not to other program director characteristics like gender or international medical graduate status. Further research is needed to optimize our understanding of connection in organizations such as these and to determine which strategies promote valuable connections.

Seismic hazard maps of Mexico, the Caribbean, and Central and South America

USGS Publications Warehouse

Tanner, J.G.; Shedlock, K.M.

2004-01-01

The growth of megacities in seismically active regions around the world often includes the construction of seismically unsafe buildings and infrastructures due to an insufficient knowledge of existing seismic hazard and/or economic constraints. Minimization of the loss of life, property damage, and social and economic disruption due to earthquakes depends on reliable estimates of seismic hazard. We have produced a suite of seismic hazard estimates for Mexico, the Caribbean, and Central and South America. One of the preliminary maps in this suite served as the basis for the Caribbean and Central and South America portion of the Global Seismic Hazard Map (GSHM) published in 1999, which depicted peak ground acceleration (pga) with a 10% chance of exceedance in 50 years for rock sites. Herein we present maps depicting pga and 0.2 and 1.0 s spectral accelerations (SA) with 50%, 10%, and 2% chances of exceedance in 50 years for rock sites. The seismicity catalog used in the generation of these maps adds 3 more years of data to those used to calculate the GSH Map. Different attenuation functions (consistent with those used to calculate the U.S. and Canadian maps) were used as well. These nine maps are designed to assist in global risk mitigation by providing a general seismic hazard framework and serving as a resource for any national or regional agency to help focus further detailed studies required for regional/local needs. The largest seismic hazard values in Mexico, the Caribbean, and Central and South America generally occur in areas that have been, or are likely to be, the sites of the largest plate boundary earthquakes. High hazard values occur in areas where shallow-to-intermediate seismicity occurs frequently. ?? 2004 Elsevier B.V. All rights reserved.

A Mixed Prioritization Operators Strategy Using A Single Measurement Criterion For AHP Application Development

NASA Astrophysics Data System (ADS)

Yuen, Kevin Kam Fung

2009-10-01

The most appropriate prioritization method is still one of the unsettled issues of the Analytic Hierarchy Process, although many studies have been made and applied. Interestingly, many AHP applications apply only Saaty's Eigenvector method as many studies have found that this method may produce rank reversals and have proposed various prioritization methods as alternatives. Some methods have been proved to be better than the Eigenvector method. However, these methods seem not to attract the attention of researchers. In this paper, eight important prioritization methods are reviewed. A Mixed Prioritization Operators Strategy (MPOS) is developed to select a vector which is prioritized by the most appropriate prioritization operator. To verify this new method, a case study of high school selection is revised using the proposed method. The contribution is that MPOS is useful for solving prioritization problems in the AHP.

Feedback equilibrium control during human standing

PubMed Central

Alexandrov, Alexei V.; AA, Frolov; FB, Horak; P, Carlson-Kuhta; S, Park

2006-01-01

Equilibrium maintenance during standing in humans was investigated with a 3-joint (ankle, knee and hip) sagittal model of body movement. The experimental paradigm consisted of sudden perturbations of humans in quiet stance by backward displacements of the support platform. Data analysis was performed using eigenvectors of motion equation. The results supported three conclusions. First, independent feedback control of movements along eigenvectors (eigenmovements) can adequately describe human postural responses to stance perturbations. This conclusion is consistent with previous observations (Alexandrov et al., 2001b) that these same eigenmovements are also independently controlled in a feed-forward manner during voluntary upper-trunk bending. Second, independent feedback control of each eigenmovement is sufficient to provide its stability. Third, the feedback loop in each eigenmovement can be modeled as a linear visco-elastic spring with delay. Visco-elastic parameters and time-delay values result from the combined contribution of passive visco-elastic mechanisms and sensory systems of different modalities. PMID:16228222

Transfer matrix method for dynamics modeling and independent modal space vibration control design of linear hybrid multibody system

NASA Astrophysics Data System (ADS)

Rong, Bao; Rui, Xiaoting; Lu, Kun; Tao, Ling; Wang, Guoping; Ni, Xiaojun

2018-05-01

In this paper, an efficient method of dynamics modeling and vibration control design of a linear hybrid multibody system (MS) is studied based on the transfer matrix method. The natural vibration characteristics of a linear hybrid MS are solved by using low-order transfer equations. Then, by constructing the brand-new body dynamics equation, augmented operator and augmented eigenvector, the orthogonality of augmented eigenvector of a linear hybrid MS is satisfied, and its state space model expressed in each independent model space is obtained easily. According to this dynamics model, a robust independent modal space-fuzzy controller is designed for vibration control of a general MS, and the genetic optimization of some critical control parameters of fuzzy tuners is also presented. Two illustrative examples are performed, which results show that this method is computationally efficient and with perfect control performance.

Sensor Network Localization by Eigenvector Synchronization Over the Euclidean Group

PubMed Central

CUCURINGU, MIHAI; LIPMAN, YARON; SINGER, AMIT

2013-01-01

We present a new approach to localization of sensors from noisy measurements of a subset of their Euclidean distances. Our algorithm starts by finding, embedding, and aligning uniquely realizable subsets of neighboring sensors called patches. In the noise-free case, each patch agrees with its global positioning up to an unknown rigid motion of translation, rotation, and possibly reflection. The reflections and rotations are estimated using the recently developed eigenvector synchronization algorithm, while the translations are estimated by solving an overdetermined linear system. The algorithm is scalable as the number of nodes increases and can be implemented in a distributed fashion. Extensive numerical experiments show that it compares favorably to other existing algorithms in terms of robustness to noise, sparse connectivity, and running time. While our approach is applicable to higher dimensions, in the current article, we focus on the two-dimensional case. PMID:23946700

Asymptotics of empirical eigenstructure for high dimensional spiked covariance.

PubMed

Wang, Weichen; Fan, Jianqing

2017-06-01

We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.

Asymptotics of empirical eigenstructure for high dimensional spiked covariance

PubMed Central

Wang, Weichen

2017-01-01

We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies. PMID:28835726

Face recognition with the Karhunen-Loeve transform

NASA Astrophysics Data System (ADS)

Suarez, Pedro F.

1991-12-01

The major goal of this research was to investigate machine recognition of faces. The approach taken to achieve this goal was to investigate the use of Karhunen-Loe've Transform (KLT) by implementing flexible and practical code. The KLT utilizes the eigenvectors of the covariance matrix as a basis set. Faces were projected onto the eigenvectors, called eigenfaces, and the resulting projection coefficients were used as features. Face recognition accuracies for the KLT coefficients were superior to Fourier based techniques. Additionally, this thesis demonstrated the image compression and reconstruction capabilities of the KLT. This theses also developed the use of the KLT as a facial feature detector. The ability to differentiate between facial features provides a computer communications interface for non-vocal people with cerebral palsy. Lastly, this thesis developed a KLT based axis system for laser scanner data of human heads. The scanner data axis system provides the anthropometric community a more precise method of fitting custom helmets.

Experimental quantum compressed sensing for a seven-qubit system

PubMed Central

Riofrío, C. A.; Gross, D.; Flammia, S. T.; Monz, T.; Nigg, D.; Blatt, R.; Eisert, J.

2017-01-01

Well-controlled quantum devices with their increasing system size face a new roadblock hindering further development of quantum technologies. The effort of quantum tomography—the reconstruction of states and processes of a quantum device—scales unfavourably: state-of-the-art systems can no longer be characterized. Quantum compressed sensing mitigates this problem by reconstructing states from incomplete data. Here we present an experimental implementation of compressed tomography of a seven-qubit system—a topological colour code prepared in a trapped ion architecture. We are in the highly incomplete—127 Pauli basis measurement settings—and highly noisy—100 repetitions each—regime. Originally, compressed sensing was advocated for states with few non-zero eigenvalues. We argue that low-rank estimates are appropriate in general since statistical noise enables reliable reconstruction of only the leading eigenvectors. The remaining eigenvectors behave consistently with a random-matrix model that carries no information about the true state. PMID:28513587

The Spectrum of Scalar Indices of Agyrotropy

NASA Astrophysics Data System (ADS)

Scudder, J. D.; Daughton, W. S.

2017-12-01

Quantitative scalar measures of departures from gyrotropy will be contrasted using 3D-PIC guide field simulations of a reconnection layer. Of interest are the sensitivity of 4 different proposed methods for inventorying the occurrence of needed signatures of demagnetization for identification of reconnection sites. Visual maps will be presented using the originally formulated diagnostic A0e for agyrotropy and three relatively recent attempts to generalize it. These visuals highlight the essentially common information contained in these approaches. The ``flavor'' distinctions between these techniques will be organized in terms of the types of deformations of the eVDF required for their distinctions to be present/significant. The first class of disturbances are those that explicitly cause the eVDF to depend on gyro phase in addition to pitch angle, while the second class requires a strong coordinated deformation of the eVDF in both polar angles. In the first class the magnetic field remains as an eigenvector of the deformed pressure tensor as in the originally proposed diagnostic A0e; in the second class NO eigenvector is aligned with the magnetic field and accompanies a more violent disruption of magnetization than the first class. The 3D VPIC guide simulation will be used as a data base to show the relative frequency of occurrence of these two types of disruptions in regions with non-zero agyrotropy. As far as identifying whether a region has demagnetization or not all techniques are virtually interchangeable and are shown to be statistically strongly correlated using billions of estimates. Accordingly, extensive early surveys using A0e to survey PIC reconnection geometries for signatures of demagnetization are not supplanted by the existence of alternate recipes for quantifying the geometry of the pressure tensor that get slightly larger values in relatively esoteric circumstances. Of the two types of deformation of the eVDF required to produce different ``flavors'' of agyrotropy, the gyro phase only modulations resolved completely by A0e are statistically the more common instances of demagnetization in 3D-PIC simulations.

Error Modeling of Multi-baseline Optical Truss. Part II; Application to SIM Metrology Truss Field Dependent Error

NASA Technical Reports Server (NTRS)

Zhang, Liwei Dennis; Milman, Mark; Korechoff, Robert

2004-01-01

The current design of the Space Interferometry Mission (SIM) employs a 19 laser-metrology-beam system (also called L19 external metrology truss) to monitor changes of distances between the fiducials of the flight system's multiple baselines. The function of the external metrology truss is to aid in the determination of the time-variations of the interferometer baseline. The largest contributor to truss error occurs in SIM wide-angle observations when the articulation of the siderostat mirrors (in order to gather starlight from different sky coordinates) brings to light systematic errors due to offsets at levels of instrument components (which include comer cube retro-reflectors, etc.). This error is labeled external metrology wide-angle field-dependent error. Physics-based model of field-dependent error at single metrology gauge level is developed and linearly propagated to errors in interferometer delay. In this manner delay error sensitivity to various error parameters or their combination can be studied using eigenvalue/eigenvector analysis. Also validation of physics-based field-dependent model on SIM testbed lends support to the present approach. As a first example, dihedral error model is developed for the comer cubes (CC) attached to the siderostat mirrors. Then the delay errors due to this effect can be characterized using the eigenvectors of composite CC dihedral error. The essence of the linear error model is contained in an error-mapping matrix. A corresponding Zernike component matrix approach is developed in parallel, first for convenience of describing the RMS of errors across the field-of-regard (FOR), and second for convenience of combining with additional models. Average and worst case residual errors are computed when various orders of field-dependent terms are removed from the delay error. Results of the residual errors are important in arriving at external metrology system component requirements. Double CCs with ideally co-incident vertices reside with the siderostat. The non-common vertex error (NCVE) is treated as a second example. Finally combination of models, and various other errors are discussed.

SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo

2017-06-01

Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate that the proposed method is able to recognize street furniture in a practical scenario. Remaining difficult cases are touching objects, like a lamp pole close to a tree.

A model-based reconstruction for undersampled radial spin echo DTI with variational penalties on the diffusion tensor

PubMed Central

Knoll, Florian; Raya, José G; Halloran, Rafael O; Baete, Steven; Sigmund, Eric; Bammer, Roland; Block, Tobias; Otazo, Ricardo; Sodickson, Daniel K

2015-01-01

Radial spin echo diffusion imaging allows motion-robust imaging of tissues with very low T2 values like articular cartilage with high spatial resolution and signal-to-noise ratio (SNR). However, in vivo measurements are challenging due to the significantly slower data acquisition speed of spin-echo sequences and the less efficient k-space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled DTI. A model-based reconstruction implicitly exploits redundancies in the diffusion weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a Total Variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (3 and 2 volunteers, respectively). Evaluation of the new approach was conducted by comparing the results to reconstructions performed with gridding, combined parallel imaging and compressed sensing, and a recently proposed model-based approach. The experiments demonstrated improvement in terms of reduction of noise and streaking artifacts in the quantitative parameter maps as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin echo diffusion tensor imaging without degrading parameter quantification and/or SNR. PMID:25594167

Cartographic modeling of heterogeneous landscape for footprint analysis of Eddy Covariance Measurements (Central Forest and Central Chernozem reserves, Russia)

NASA Astrophysics Data System (ADS)

Kozlov, Daniil

2014-05-01

The topographical, soil and vegetation maps of FLUXNET study areas are widely used for interpretation of eddy covariance measurements, for calibration of biogeochemical models and for making regional assessments of carbon balance. The poster presents methodological problems and results of ecosystem mapping using GIS, remote sensing, statistical and field methods on the example of two RusFluxNet sites in the Central Forest (33° E, 56°30'N) and Central Chernozem (36°10' E, 51°36'N) reserves. In the Central Forest reserve tacheometric measurements were used for topographical and peat surveys of bogged sphagnum spruce forest of 20-hectare area. Its common borders and its areas affected by windfall were determined. The supplies and spatial distribution of organic matter were obtained. The datasets of groundwater monitoring measurements on ten wells were compared with each other and the analysis of spatial and temporal groundwater variability was performed. The map of typical ecosystems of the reserve and its surroundings was created on the basis of analysis of multi-temporal Landsat images. In the Central Chernozem reserve the GNSS topographical survey was used for flux tower footprint mapping (22 ha). The features of microrelief predetermine development of different soils within the footprint. Close relationship between soil (73 drilling site) and terrain attributes (DEM with 2.5 m) allowed to build maps of soils and soil properties: carbon content, bulk density, upper boundary of secondary carbonates. Position for chamber-based soil respiration measurements was defined on the basis of these maps. The detailed geodetic and soil surveys of virgin lands and plowland were performed in order to estimate the effect of agrogenic processes such as dehumification, compaction and erosion on soils during the whole period of agricultural use of Central Chernozem reserve area and around. The choice of analogous soils was based on the similarity of their position within the landscape as judged from the terrain attributes of the DEM. The dynamics of soil cover during the last 50 years was estimated on the basis of repetitive detailed surveys of the five key plots conducted in 1963, 1984 and 2013. All results of this study and map analysis conclusions are presented in the poster.

Organisational adaptation in an activist network: social networks, leadership, and change in al-Muhajiroun.

PubMed

Kenney, Michael; Horgan, John; Horne, Cale; Vining, Peter; Carley, Kathleen M; Bigrigg, Michael W; Bloom, Mia; Braddock, Kurt

2013-09-01

Social networks are said to facilitate learning and adaptation by providing the connections through which network nodes (or agents) share information and experience. Yet, our understanding of how this process unfolds in real-world networks remains underdeveloped. This paper explores this gap through a case study of al-Muhajiroun, an activist network that continues to call for the establishment of an Islamic state in Britain despite being formally outlawed by British authorities. Drawing on organisation theory and social network analysis, we formulate three hypotheses regarding the learning capacity and social network properties of al-Muhajiroun (AM) and its successor groups. We then test these hypotheses using mixed methods. Our methods combine quantitative analysis of three agent-based networks in AM measured for structural properties that facilitate learning, including connectedness, betweenness centrality and eigenvector centrality, with qualitative analysis of interviews with AM activists focusing organisational adaptation and learning. The results of these analyses confirm that al-Muhajiroun activists respond to government pressure by changing their operations, including creating new platforms under different names and adjusting leadership roles among movement veterans to accommodate their spiritual leader's unwelcome exodus to Lebanon. Simple as they are effective, these adaptations have allowed al-Muhajiroun and its successor groups to continue their activism in an increasingly hostile environment. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

The Tisza maps of Samuel Lanyi and their geodetic basis

NASA Astrophysics Data System (ADS)

Meszaros, J.

2009-04-01

The map of Lányi is the last map which represents the reach of Tisza in the former Heves and Külső-Szolnok counties in central Hungary, before the river control measures. The map was made by surveying with the leading of Sámuel Lányi, qualified engineer, between 1834 and 1843. This map was the base of the river control guided by Pál Vásárhelyi, which shows the importance of it. The map was drawn on 73*58 cm sheets of paper. Its scale is 1 Wiener inch (2.63 cm) to 400 Wiener fathoms (1,89648384 m) that is in metric system 1: 28800. Its geodetic base is the triangulation of Tisza and Maros rivers surveyed between 1834 and 1836. The coordinates was described in Cassini projection. The central point of the coordinate system was the old observatory of the Gellérthegy in Buda (now Budapest). This map is useable to ethnographical, urban-geographical, hydrological and agriculture-historical researches. It containes many missing rills and canals which had formed the surface of Great Hungarian Plain in the 19. century. The small altitude variations of the central part of the Great Hungarian Plain are displayed with surprising accuracy in extents.

Sustained attention is favored by progesterone during early luteal phase and visuo-spatial memory by estrogens during ovulatory phase in young women.

PubMed

Solís-Ortiz, S; Corsi-Cabrera, M

2008-08-01

Studies examining the influence of the menstrual cycle on cognitive function have been highly contradictory. The maintenance of attention is key to successful information processing, however how it co-vary with other cognitive functions and mood in function of phases of the menstrual cycle is not well know. Therefore, neuropsychological performance of nine healthy women with regular menstrual cycles was assessed during ovulation (OVU), early luteal (EL), late luteal (LL) and menstrual (MEN) phases. Neuropsychological test scores of sustained attention, executive functions, manual coordination, visuo-spatial memory, verbal fluency, spatial ability, anxiety and depression were obtained and submitted to a principal components analysis (PCA). Five eigenvectors that accounted the 68.31% of the total variance were identified. Performance of the sustained attention was grouped in an independent eigenvector (component 1), and the scores on verbal fluency and visuo-spatial memory were grouped together in an eigenvector (component 5), which explained 17.69% and 12.03% of the total variance, respectively. The component 1 (p<0.034) and the component 5 (p<0.003) showed significant variations during the menstrual cycle. Sustained attention showed an increase in the EL phase, when the progesterone is high. Visuo-spatial memory was increased, while that verbal fluency was decreased during the OVU phase, when the estrogens levels are high. These results indicate that sustained attention is favored by early luteal phase progesterone and do not covaried with any other neuropsychological variables studied. The influence of the estrogens on visuo-spatial memory was corroborated, and covaried inversely with verbal fluency.

Comparison of eigensolvers for symmetric band matrices.

PubMed

Moldaschl, Michael; Gansterer, Wilfried N

2014-09-15

We compare different algorithms for computing eigenvalues and eigenvectors of a symmetric band matrix across a wide range of synthetic test problems. Of particular interest is a comparison of state-of-the-art tridiagonalization-based methods as implemented in Lapack or Plasma on the one hand, and the block divide-and-conquer (BD&C) algorithm as well as the block twisted factorization (BTF) method on the other hand. The BD&C algorithm does not require tridiagonalization of the original band matrix at all, and the current version of the BTF method tridiagonalizes the original band matrix only for computing the eigenvalues. Avoiding the tridiagonalization process sidesteps the cost of backtransformation of the eigenvectors. Beyond that, we discovered another disadvantage of the backtransformation process for band matrices: In several scenarios, a lot of gradual underflow is observed in the (optional) accumulation of the transformation matrix and in the (obligatory) backtransformation step. According to the IEEE 754 standard for floating-point arithmetic, this implies many operations with subnormal (denormalized) numbers, which causes severe slowdowns compared to the other algorithms without backtransformation of the eigenvectors. We illustrate that in these cases the performance of existing methods from Lapack and Plasma reaches a competitive level only if subnormal numbers are disabled (and thus the IEEE standard is violated). Overall, our performance studies illustrate that if the problem size is large enough relative to the bandwidth, BD&C tends to achieve the highest performance of all methods if the spectrum to be computed is clustered. For test problems with well separated eigenvalues, the BTF method tends to become the fastest algorithm with growing problem size.

SU-E-I-58: Objective Models of Breast Shape Undergoing Mammography and Tomosynthesis Using Principal Component Analysis.

PubMed

Feng, Ssj; Sechopoulos, I

2012-06-01

To develop an objective model of the shape of the compressed breast undergoing mammographic or tomosynthesis acquisition. Automated thresholding and edge detection was performed on 984 anonymized digital mammograms (492 craniocaudal (CC) view mammograms and 492 medial lateral oblique (MLO) view mammograms), to extract the edge of each breast. Principal Component Analysis (PCA) was performed on these edge vectors to identify a limited set of parameters and eigenvectors that. These parameters and eigenvectors comprise a model that can be used to describe the breast shapes present in acquired mammograms and to generate realistic models of breasts undergoing acquisition. Sample breast shapes were then generated from this model and evaluated. The mammograms in the database were previously acquired for a separate study and authorized for use in further research. The PCA successfully identified two principal components and their corresponding eigenvectors, forming the basis for the breast shape model. The simulated breast shapes generated from the model are reasonable approximations of clinically acquired mammograms. Using PCA, we have obtained models of the compressed breast undergoing mammographic or tomosynthesis acquisition based on objective analysis of a large image database. Up to now, the breast in the CC view has been approximated as a semi-circular tube, while there has been no objectively-obtained model for the MLO view breast shape. Such models can be used for various breast imaging research applications, such as x-ray scatter estimation and correction, dosimetry estimates, and computer-aided detection and diagnosis. © 2012 American Association of Physicists in Medicine.

Detection of multiple damages employing best achievable eigenvectors under Bayesian inference

NASA Astrophysics Data System (ADS)

Prajapat, Kanta; Ray-Chaudhuri, Samit

2018-05-01

A novel approach is presented in this work to localize simultaneously multiple damaged elements in a structure along with the estimation of damage severity for each of the damaged elements. For detection of damaged elements, a best achievable eigenvector based formulation has been derived. To deal with noisy data, Bayesian inference is employed in the formulation wherein the likelihood of the Bayesian algorithm is formed on the basis of errors between the best achievable eigenvectors and the measured modes. In this approach, the most probable damage locations are evaluated under Bayesian inference by generating combinations of various possible damaged elements. Once damage locations are identified, damage severities are estimated using a Bayesian inference Markov chain Monte Carlo simulation. The efficiency of the proposed approach has been demonstrated by carrying out a numerical study involving a 12-story shear building. It has been found from this study that damage scenarios involving as low as 10% loss of stiffness in multiple elements are accurately determined (localized and severities quantified) even when 2% noise contaminated modal data are utilized. Further, this study introduces a term parameter impact (evaluated based on sensitivity of modal parameters towards structural parameters) to decide the suitability of selecting a particular mode, if some idea about the damaged elements are available. It has been demonstrated here that the accuracy and efficiency of the Bayesian quantification algorithm increases if damage localization is carried out a-priori. An experimental study involving a laboratory scale shear building and different stiffness modification scenarios shows that the proposed approach is efficient enough to localize the stories with stiffness modification.

Geologic map of outcrop areas of sedimentary units in the eastern part of the Hailey 1 degree x 2 degrees quadrangle and part of the southern part of the Challis 1 degree x 2 degrees quadrangle, south-central Idaho

USGS Publications Warehouse

Link, P.K.; Mahoney, J.B.; Bruner, D.J.; Batatian, L.D.; Wilson, Eric; Williams, F.J.C.

1995-01-01

The paper version of the Geologic map of outcrop areas of sedimentary units in the eastern part of the Hailey 1x2 Quadrangle and part of the southern part of the Challis 1x2 Quadrangle, south-central Idaho was compiled by Paul Link and others in 1995. The plate was compiled on a 1:100,000 scale topographic base map. TechniGraphic System, Inc. of Fort Collins Colorado digitized this map under contract for N.Shock. G.Green edited and prepared the digital version for publication as a GIS database. The digital geologic map database can be queried in many ways to produce a variety of geologic maps.

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America.

PubMed

Carroll, Carlos; McRae, Brad H; Brookes, Allen

2012-02-01

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity. ©2011 Society for Conservation Biology.

Graph Partitioning by Eigenvectors,

DTIC Science & Technology

1987-01-01

the extremal nature of eigenvalues of symmetric matrices, the interlacing theorem, monotonicity of spectral radius of nonnegative matrices, Perron ... Frobenius theory, etc. (See Varga (1962) and Lancaster and Tismenetsky (1985).) Most of the results of this paper depend on the following lemma. ABSTRACT

A fast image matching algorithm based on key points

NASA Astrophysics Data System (ADS)

Wang, Huilin; Wang, Ying; An, Ru; Yan, Peng

2014-05-01

Image matching is a very important technique in image processing. It has been widely used for object recognition and tracking, image retrieval, three-dimensional vision, change detection, aircraft position estimation, and multi-image registration. Based on the requirements of matching algorithm for craft navigation, such as speed, accuracy and adaptability, a fast key point image matching method is investigated and developed. The main research tasks includes: (1) Developing an improved celerity key point detection approach using self-adapting threshold of Features from Accelerated Segment Test (FAST). A method of calculating self-adapting threshold was introduced for images with different contrast. Hessian matrix was adopted to eliminate insecure edge points in order to obtain key points with higher stability. This approach in detecting key points has characteristics of small amount of computation, high positioning accuracy and strong anti-noise ability; (2) PCA-SIFT is utilized to describe key point. 128 dimensional vector are formed based on the SIFT method for the key points extracted. A low dimensional feature space was established by eigenvectors of all the key points, and each eigenvector was projected onto the feature space to form a low dimensional eigenvector. These key points were re-described by dimension-reduced eigenvectors. After reducing the dimension by the PCA, the descriptor was reduced to 20 dimensions from the original 128. This method can reduce dimensions of searching approximately near neighbors thereby increasing overall speed; (3) Distance ratio between the nearest neighbour and second nearest neighbour searching is regarded as the measurement criterion for initial matching points from which the original point pairs matched are obtained. Based on the analysis of the common methods (e.g. RANSAC (random sample consensus) and Hough transform cluster) used for elimination false matching point pairs, a heuristic local geometric restriction strategy is adopted to discard false matched point pairs further; and (4) Affine transformation model is introduced to correct coordinate difference between real-time image and reference image. This resulted in the matching of the two images. SPOT5 Remote sensing images captured at different date and airborne images captured with different flight attitude were used to test the performance of the method from matching accuracy, operation time and ability to overcome rotation. Results show the effectiveness of the approach.

Baroclinic wave configurations evolution at European scale in the period 1948-2013

NASA Astrophysics Data System (ADS)

Carbunaru, Daniel; Burcea, Sorin; Carbunaru, Felicia

2016-04-01

The main aim of the study was to investigate the dynamic characteristics of synoptic configurations at European scale and especially in south-eastern part of Europe for the period 1948-2013. Using the empirical orthogonal functions analysis, simultaneously applied to daily average geopotential field at different pressure levels (200 hPa, 300 hPa, 500 hPa and 850 hPa) during warm (April-September) and cold (October-March) seasons, on a synoptic spatial domain centered on Europe (-27.5o lon V to 45o lon E and 32.5o lat N to 72.5o lat N), the main mode of oscillation characteristic to vertical shift of mean baroclinic waves was obtained. The analysis independently applied on 66 years showed that the first eigenvectors in warms periods describe about 60% of the data and in cold season 40% of the data for each year. In comparison secondary eigenvectors describe up to 20% and 10% of the data. Thus, the analysis was focused on the complex evolution of the first eigenvector in 66 years, during the summer period. On average, this eigenvector describes a small vertical phase shift in the west part of the domain and a large one in the eastern part. Because the spatial extent of the considered synoptic domain incorporates in the west part AMO (Atlantic Multidecadal Oscillation) and NAO (North Atlantic Oscillation) oscillations, and in the north part being sensitive to AO (Arctic Oscillation) oscillation, these three oscillations were considered as modulating dynamic factors at hemispherical scale. The preliminary results show that in the summer seasons AMO and NAO oscillations modulated vertical phase shift of baroclinic wave in the west of the area (Northwestern Europe), and the relationship between AO and NAO oscillations modulated vertical phase shift in the southeast area (Southeast Europe). Second, it was shown the way in which this vertical phase shift modulates the overall behavior of cyclonic activity, particularly in Southeastern Europe. This work has been developed within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian Executive Agency for Higher Education Research, Development and Innovation Funding (UEFISCDI).

Digital geologic map and Landsat image map of parts of Loralai, Sibi, Quetta, and Khuzar Divisions, Balochistan Province, west-central Pakistan

USGS Publications Warehouse

Maldonado, Florian; Menga, Jan Mohammad; Khan, Shabid Hasan; Thomas, Jean-Claude

2011-01-01

This generalized digital geologic map of west-central Pakistan is a product of the Balochistan Coal-Basin Synthesis Study, which was part of a cooperative program of the Geological Survey of Pakistan and the United States Geological Survey. The original nondigital map was published by Maldonado and others (1998). Funding was provided by the Government of Pakistan and the United States Agency for International Development. The sources of geologic map data are primarily 1:253,440-scale geologic maps obtained from Hunting Survey Corporation (1961) and the geologic map of the Muslim Bagh Ophiolite Complex and Bagh Complex area. The geology was modified based on reconnaissance field work and photo interpretation of 1:250,000-scale Landsat Thematic Mapper photo image. The descriptions and thicknesses of map units were based on published and unpublished reports and converted to U.S. Geological Survey format. In the nomenclature of the Geological Survey of Pakistan, there is both an Urak Group and an Urak Formation.

Skylab photography applied to geologic mapping in northwestern Central America

NASA Technical Reports Server (NTRS)

Rose, W. I., Jr.; Johnson, D. J.; Hahn, G. A.; Johns, G. W.

1975-01-01

Two photolineation maps of southwestern Guatemala and Chiapas were made from S190 photographs along a ground track from Acajutla, El Salvador to San Cristobal de las Casas, Mexico. The maps document a structural complexity spanning the presumed triple junction of the Cocos, Americas, and Caribbean plates. The Polochic fault zone, supposedly the Americas-Caribbean plate boundary, is a sharply delineated feature across western Guatemala. Westward of the Mexican border it splays into a large number of faults with NW to SW trends. The structural pattern is quite different to the north (Americas plate) and to the south (Caribbean plate) of the Polochic fault, though both areas are dominated by NW-trending lineations. Within the Central American volcanic chain, the lineation patterns support the segmented model of the Benioff Zone, by showing a concentration of transverse lineations in the predicted locations, most notably NE-trending elements near Quezaltenango, Guatemala. The structural pattern obtained from the maps are compared to patterns described on recently published maps of more southerly parts of Central America, to begin a synthesis of the structure of the convergent plate boundary.

Mapping ecosystem services for land use planning, the case of Central Kalimantan.

PubMed

Sumarga, Elham; Hein, Lars

2014-07-01

Indonesia is subject to rapid land use change. One of the main causes for the conversion of land is the rapid expansion of the oil palm sector. Land use change involves a progressive loss of forest cover, with major impacts on biodiversity and global CO2 emissions. Ecosystem services have been proposed as a concept that would facilitate the identification of sustainable land management options, however, the scale of land conversion and its spatial diversity pose particular challenges in Indonesia. The objective of this paper is to analyze how ecosystem services can be mapped at the provincial scale, focusing on Central Kalimantan, and to examine how ecosystem services maps can be used for a land use planning. Central Kalimantan is subject to rapid deforestation including the loss of peatland forests and the provincial still lacks a comprehensive land use plan. We examine how seven key ecosystem services can be mapped and modeled at the provincial scale, using a variety of models, and how large scale ecosystem services maps can support the identification of options for sustainable expansion of palm oil production.

An Algebraic Approach to the Eigenstates of the Calogero Model

NASA Astrophysics Data System (ADS)

Ujino, Hideaki

2002-11-01

An algebraic treatment of the eigenstates of the (AN-1-) Calogero model is presented, which provides an algebraic construction of the nonsymmetric orthogonal eigenvectors, symmetrization, antisymmetrization and calculation of square norms in a unified way.

A Simple Parameterization of 3 x 3 Magic Squares

ERIC Educational Resources Information Center

Trenkler, Gotz; Schmidt, Karsten; Trenkler, Dietrich

2012-01-01

In this article a new parameterization of magic squares of order three is presented. This parameterization permits an easy computation of their inverses, eigenvalues, eigenvectors and adjoints. Some attention is paid to the Luoshu, one of the oldest magic squares.

Analysis of Hypersonic Vehicle Wakes

DTIC Science & Technology

2015-09-17

factor used with viscous Jacobian matrix of left eigenvectors for A R specific gas constant Re Reynolds number Recell cell Reynolds number......focus was shifted to characterizing other wake phenomena. The aerothermal phenomena of interest in the wake include: gas properties, chemical species

Geologic Map of Central (Interior) Alaska

USGS Publications Warehouse

Wilson, Frederic H.; Dover, James H.; Bradley, Dwight C.; Weber, Florence R.; Bundtzen, Thomas K.; Haeussler, Peter J.

1998-01-01

Introduction: This map and associated digital databases are the result of a compilation and reinterpretation of published and unpublished 1:250,000- and limited 1:125,000- and 1:63,360-scale mapping. The map area covers approximately 416,000 sq km (134,000 sq mi) and encompasses 25 1:250,000-scale quadrangles in central Alaska. The compilation was done as part of the U.S. Geological Survey National Surveys and Analysis project, whose goal is nationwide assemble geologic, geochemical, geophysical, and other data. This map is an early product of an effort that will eventually encompass all of Alaska, and is the result of an agreement with the Alaska Department of Natural Resources, Division of Oil And Gas, to provide data on interior basins in Alaska. A paper version of the three map sheets has been published as USGS Open-File Report 98-133. Two geophysical maps that cover the identical area have been published earlier: 'Bouguer gravity map of Interior Alaska' (Meyer and others, 1996); and 'Merged aeromagnetic map of Interior Alaska' (Meyer and Saltus, 1995). These two publications are supplied in the 'geophys' directory of this report.

Fusiform-Rust-Hazard Maps for Loblolly and Slash Pines

Treesearch

Robert L. Anderson; Thomas C. McCartney; Noel D. Cost; Hugh Devine; Martin Botkin

1988-01-01

Rust-hazard saps made from Forest Inventory and Analysis plot data show that fusiform rust on slash pine is most common in north-central Florida, in southeastern Georgia, and in areas north of slash pine's natural range. On loblolly pine, the disease is most common in central and southeastern Georgia and in portions of South Carolina. These maps show the general...

Comparing an Atomic Model or Structure to a Corresponding Cryo-electron Microscopy Image at the Central Axis of a Helix

PubMed Central

Zeil, Stephanie; Kovacs, Julio; Wriggers, Willy

2017-01-01

Abstract Three-dimensional density maps of biological specimens from cryo-electron microscopy (cryo-EM) can be interpreted in the form of atomic models that are modeled into the density, or they can be compared to known atomic structures. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. This method was applied to 79 helices in simulated density maps and six case studies using cryo-EM maps at 6.4–7.7 Å resolution. The arc-length association method is then compared to three existing measures that evaluate the separation of two helical axes: a two-way distance between point sets, the length difference between two axes, and the individual amino acid detection accuracy. The results show that our proposed method sensitively distinguishes lateral and longitudinal discrepancies between the two axes, which makes the method particularly suitable for the systematic investigation of cryo-EM map–model pairs. PMID:27936925

Creating Geologically Based Radon Potential Maps for Kentucky

NASA Astrophysics Data System (ADS)

Overfield, B.; Hahn, E.; Wiggins, A.; Andrews, W. M., Jr.

2017-12-01

Radon potential in the United States, Kentucky in particular, has historically been communicated using a single hazard level for each county; however, physical phenomena are not controlled by administrative boundaries, so single-value county maps do not reflect the significant variations in radon potential in each county. A more accurate approach uses bedrock geology as a predictive tool. A team of nurses, health educators, statisticians, and geologists partnered to create 120 county maps showing spatial variations in radon potential by intersecting residential radon test kit results (N = 60,000) with a statewide 1:24,000-scale bedrock geology coverage to determine statistically valid radon-potential estimates for each geologic unit. Maps using geology as a predictive tool for radon potential are inherently more detailed than single-value county maps. This mapping project revealed that areas in central and south-central Kentucky with the highest radon potential are underlain by shales and karstic limestones.

Preliminary Geologic Map of the Southern Funeral Mountains and Adjacent Ground-Water Discharge Sites, Inyo County, California, and Nye County, Nevada

USGS Publications Warehouse

Fridrich, Christopher J.; Thompson, Ren A.; Slate, Janet L.; Berry, M.E.; Machette, Michael N.

2008-01-01

This map covers the southern part of the Funeral Mountains, and adjacent parts of four structural basins - Furnace Creek, Amargosa Valley, Opera House, and central Death Valley. It extends over three full 7.5-minute quadrangles, and parts of eleven others - a total area of about 950 square kilometers. The boundaries of this map were drawn to include all of the known proximal hydrogeologic features that may affect the flow of ground water that discharges from the springs of the Furnace Creek wash area, in the west-central part of the map. These springs provide the major potable water supply for Death Valley National Park.

Maps & minds : mapping through the ages

USGS Publications Warehouse

,

1984-01-01

Throughout time, maps have expressed our understanding of our world. Human affairs have been influenced strongly by the quality of maps available to us at the major turning points in our history. "Maps & Minds" traces the ebb and flow of a few central ideas in the mainstream of mapping. Our expanding knowledge of our cosmic neighborhood stems largely from a small number of simple but grand ideas, vigorously pursued.

Topographic Map of the Ophir and Central Candor Chasmata Region of Mars MTM 500k -05/287E OMKT

USGS Publications Warehouse

,

2004-01-01

This map, compiled photogrammetrically from Viking Orbiter stereo image pairs, is part of a series of topographic maps of areas of special scientific interest on Mars. The figure of Mars used for the computation of the map projection is an oblate spheroid (flattening of 1/176.875) with an equatorial radius of 3396.0 km and a polar radius of 3376.8 km. The datum (the 0-km contour line) for elevations is defined as the equipotential surface (gravitational plus rotational) whose average value at the equator is equal to the mean radius as determined by Mars Orbiter Laser Altimeter. The projection is part of a Mars Transverse Mercator (MTM) system with 20? wide zones. For the area covered by this map sheet the central meridian is at 290? E. (70? W.). The scale factor at the central meridian of the zone containing this quadrangle is 0.9960 relative to a nominal scale of 1:500,000. Longitude increases to the east and latitude is planetocentric as allowed by IAU/IAG standards and in accordance with current NASA and USGS standards. A secondary grid (printed in red) has been added to the map as a reference to the west longitude/planetographic latitude system that is also allowed by IAU/IAG standards and has been used for previous Mars maps.

New screening methods for donor eye-bank eyes.

PubMed

Terry, M A; Ousley, P J

1999-07-01

Current methods of screening donor eyes for corneal transplantation are not always effective in excluding corneas with abnormal topography. We used the Orbscan to determine whether corneal-thickness maps could be used as a technique for donor tissue screening. Forty eye-bank eyes were measured with the Orbscan, and a corneal-thickness map was generated. Average central pachymetry measurements from each map were compared with the thinnest midperipheral thickness reading. Two eyes from a donor who had photorefractive keratectomy (PRK) and two eyes from a donor with keratoconus were then compared with the normal donor eye results. The average difference between the thinnest midperipheral pachymetry and the central pachymetry in the control group was 0.040 +/- 0.026 mm. The eyes from the donor with PRK showed larger disparities between the central and midperipheral thicknesses because of the thinned central cornea, with differences of 0.154 mm in the right eye and 0.106 mm in the left eye. The eyes from the donor with keratoconus had midperipheral corneas that were thinner than the center, indicating eccentric, ectatic cones. The differences in thickness between the center and midperiphery in the eyes from the donor with PRK and the donor with keratoconus differed from the control group by >2 SD. Diseases or surgery that affect the relationship between the central and midperipheral corneal thickness may be screened through Orbscan pachymetry mapping with comparison with a normal range.

Optimizing interconnections to maximize the spectral radius of interdependent networks

NASA Astrophysics Data System (ADS)

Chen, Huashan; Zhao, Xiuyan; Liu, Feng; Xu, Shouhuai; Lu, Wenlian

2017-03-01

The spectral radius (i.e., the largest eigenvalue) of the adjacency matrices of complex networks is an important quantity that governs the behavior of many dynamic processes on the networks, such as synchronization and epidemics. Studies in the literature focused on bounding this quantity. In this paper, we investigate how to maximize the spectral radius of interdependent networks by optimally linking k internetwork connections (or interconnections for short). We derive formulas for the estimation of the spectral radius of interdependent networks and employ these results to develop a suite of algorithms that are applicable to different parameter regimes. In particular, a simple algorithm is to link the k nodes with the largest k eigenvector centralities in one network to the node in the other network with a certain property related to both networks. We demonstrate the applicability of our algorithms via extensive simulations. We discuss the physical implications of the results, including how the optimal interconnections can more effectively decrease the threshold of epidemic spreading in the susceptible-infected-susceptible model and the threshold of synchronization of coupled Kuramoto oscillators.

Rapid identifying high-influence nodes in complex networks

NASA Astrophysics Data System (ADS)

Song, Bo; Jiang, Guo-Ping; Song, Yu-Rong; Xia, Ling-Ling

2015-10-01

A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying method (RIM) to find the fraction of high-influential nodes. Instead of ranking all nodes, our method only aims at ranking a small number of nodes in network. We set the high-influential nodes as initial spreaders, and evaluate the performance of RIM by the susceptible-infected-recovered (SIR) model. The simulations show that in different networks, RIM performs well on rapid identifying high-influential nodes, which is verified by typical ranking methods, such as degree, closeness, betweenness, and eigenvector centrality methods. Project supported by the National Natural Science Foundation of China (Grant Nos. 61374180 and 61373136), the Ministry of Education Research in the Humanities and Social Sciences Planning Fund Project, China (Grant No. 12YJAZH120), and the Six Projects Sponsoring Talent Summits of Jiangsu Province, China (Grant No. RLD201212).

Analysis of cross-correlations between financial markets after the 2008 crisis

NASA Astrophysics Data System (ADS)

Sensoy, A.; Yuksel, S.; Erturk, M.

2013-10-01

We analyze the cross-correlation matrix C of the index returns of the main financial markets after the 2008 crisis using methods of random matrix theory. We test the eigenvalues of C for universal properties of random matrices and find that the majority of the cross-correlation coefficients arise from randomness. We show that the eigenvector of the largest deviating eigenvalue of C represents a global market itself. We reveal that high volatility of financial markets is observed at the same times with high correlations between them which lowers the risk diversification potential even if one constructs a widely internationally diversified portfolio of stocks. We identify and compare the connection and cluster structure of markets before and after the crisis using minimal spanning and ultrametric hierarchical trees. We find that after the crisis, the co-movement degree of the markets increases. We also highlight the key financial markets of pre and post crisis using main centrality measures and analyze the changes. We repeat the study using rank correlation and compare the differences. Further implications are discussed.

Afferent vagal stimulation, vasopressin, and nitroprusside alter cerebrospinal fluid kinin.

PubMed

Thomas, G R; Thibodeaux, H; Margolius, H S; Webb, J G; Privitera, P J

1987-07-01

The effects of afferent vagal stimulation, cerebroventricular vasopressin, and intravenous nitroprusside on cerebrospinal fluid (CSF) kinin levels, mean arterial pressure (MAP), and heart rate (HR) were determined in anesthetized dogs in which a ventriculocisternal perfusion system (VP) was established. Following bilateral vagotomy, stimulation of the central ends of both vagi for 60 min significantly increased MAP and CSF perfusate levels of kinin and norepinephrine (NE). MAP was increased a maximum of 32 +/- 4 mmHg, and the rates of kinin and NE appearance into the CSF perfusate increased from 4.2 +/- 1.4 to 22.1 +/- 6.9 and from 28 +/- 5 to 256 +/- 39 pg/min, respectively. A significant correlation was found between CSF kinin and NE levels in these experiments. In other experiments the addition of arginine vasopressin to the VP system caused a significant increase in CSF perfusate kinin without affecting MAP or HR. Intravenous infusion of nitroprusside lowered MAP without affecting kinin levels in the CSF. However, on cessation of nitroprusside infusion, CSF kinin increased significantly in association with the return in MAP to predrug level. Collectively the data are consistent with the hypothesis that central nervous system kinins have some role in cardiovascular regulation, and furthermore that this role may involve an interaction between brain kinin and central noradrenergic neuronal pathways.

Database for the geologic map of the Bend 30- x 60-minute quadrangle, central Oregon

USGS Publications Warehouse

Koch, Richard D.; Ramsey, David W.; Sherrod, David R.; Taylor, Edward M.; Ferns, Mark L.; Scott, William E.; Conrey, Richard M.; Smith, Gary A.

2010-01-01

The Bend 30- x 60-minute quadrangle has been the locus of volcanism, faulting, and sedimentation for the past 35 million years. It encompasses parts of the Cascade Range and Blue Mountain geomorphic provinces, stretching from snowclad Quaternary stratovolcanoes on the west to bare rocky hills and sparsely forested juniper plains on the east. The Deschutes River and its large tributaries, the Metolius and Crooked Rivers, drain the area. Topographic relief ranges from 3,157 m (10,358 ft) at the top of South Sister to 590 m (1,940 ft) at the floor of the Deschutes and Crooked Rivers where they exit the area at the north-central edge of the map area. The map encompasses a part of rapidly growing Deschutes County. The city of Bend, which has over 70,000 people living in its urban growth boundary, lies at the south-central edge of the map. Redmond, Sisters, and a few smaller villages lie scattered along the major transportation routes of U.S. Highways 97 and 20. This geologic map depicts the geologic setting as a basis for structural and stratigraphic analysis of the Deschutes basin, a major hydrologic discharge area on the east flank of the Cascade Range. The map also provides a framework for studying potentially active faults of the Sisters fault zone, which trends northwest across the map area from Bend to beyond Sisters. This digital release contains all of the information used to produce the geologic map published as U.S. Geological Survey Geologic Investigations Series I-2683 (Sherrod and others, 2004). The main component of this digital release is a geologic map database prepared using ArcInfo GIS. This release also contains files to view or print the geologic map and accompanying descriptive pamphlet from I-2683.

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

Plachenov, A B; Kudashov, V N; Radin, A M

Explicit formulas are obtained for a resonator with the fundamental mode in the form of a Gaussian beam with complex astigmatism. The formulas describe the parameters of the beam directly in terms of the ray matrix without using the procedure of finding its eigenvectors. An example is considered. (resonators. modes)

CIDR

Science.gov Websites

calculate eigenvectors to adjust for population stratification in association analyses. SNP filters are developed including missing data filters, duplicate and Mendelian errors, minor allele frequency and Hardy genotype and phenotype datasets and apply the filters correctly by repeating the pre-compute results. A QC

Importance of Calibration Method in Central Blood Pressure for Cardiac Structural Abnormalities.

PubMed

Negishi, Kazuaki; Yang, Hong; Wang, Ying; Nolan, Mark T; Negishi, Tomoko; Pathan, Faraz; Marwick, Thomas H; Sharman, James E

2016-09-01

Central blood pressure (CBP) independently predicts cardiovascular risk, but calibration methods may affect accuracy of central systolic blood pressure (CSBP). Standard central systolic blood pressure (Stan-CSBP) from peripheral waveforms is usually derived with calibration using brachial SBP and diastolic BP (DBP). However, calibration using oscillometric mean arterial pressure (MAP) and DBP (MAP-CSBP) is purported to provide more accurate representation of true invasive CSBP. This study sought to determine which derived CSBP could more accurately discriminate cardiac structural abnormalities. A total of 349 community-based patients with risk factors (71±5years, 161 males) had CSBP measured by brachial oscillometry (Mobil-O-Graph, IEM GmbH, Stolberg, Germany) using 2 calibration methods: MAP-CSBP and Stan-CSBP. Left ventricular hypertrophy (LVH) and left atrial dilatation (LAD) were measured based on standard guidelines. MAP-CSBP was higher than Stan-CSBP (149±20 vs. 128±15mm Hg, P < 0.0001). Although they were modestly correlated (rho = 0.74, P < 0.001), the Bland-Altman plot demonstrated a large bias (21mm Hg) and limits of agreement (24mm Hg). In receiver operating characteristic (ROC) curve analyses, MAP-CSBP significantly better discriminated LVH compared with Stan-CSBP (area under the curve (AUC) 0.66 vs. 0.59, P = 0.0063) and brachial SBP (0.62, P = 0.027). Continuous net reclassification improvement (NRI) (P < 0.001) and integrated discrimination improvement (IDI) (P < 0.001) corroborated superior discrimination of LVH by MAP-CSBP. Similarly, MAP-CSBP better distinguished LAD than Stan-CSBP (AUC 0.63 vs. 0.56, P = 0.005) and conventional brachial SBP (0.58, P = 0.006), whereas Stan-CSBP provided no better discrimination than conventional brachial BP (P = 0.09). CSBP is calibration dependent and when oscillometric MAP and DBP are used, the derived CSBP is a better discriminator for cardiac structural abnormalities. © American Journal of Hypertension, Ltd 2016. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Publications - RI 2014-4 | Alaska Division of Geological & Geophysical

Science.gov Websites

Surveys Skip to content State of Alaska myAlaska My Government Resident Business in Alaska content DGGS RI 2014-4 RI 2014-4 thumbnail Publication Details Title: Geologic map of the south-central ., Wartes, M.A., Loveland, A.M., and Hubbard, T.D., 2014, Geologic map of the south-central Sagavanirktok

Potentiometric surface in the Central Oklahoma (Garber-Wellington) aquifer, Oklahoma, 2009

USGS Publications Warehouse

Mashburn, Shana L.; Magers, Jessica

2011-01-01

A study of the hydrogeology of the Central Oklahoma aquifer was started in 2008 to provide the Oklahoma Water Resources Board (OWRB) hydrogeologic data and a groundwater flow model that can be used as a tool to help manage the aquifer. The 1973 Oklahoma water law requires the OWRB to do hydrologic investigations of Oklahoma's aquifers (termed 'groundwater basins') and to determine amounts of water that may be withdrawn by permitted water users. 'Maximum annual yield' is a term used by OWRB to describe the total amount of water that can be withdrawn from a specific aquifer in any year while allowing a minimum 20-year life of the basin (Oklahoma Water Resources Board, 2010). Currently (2010), the maximum annual yield has not been determined for the Central Oklahoma aquifer. Until the maximum annual yield determination is made, water users are issued a temporary permit by the OWRB for 2 acre-feet/acre per year. The objective of the study, in cooperation with the Oklahoma Water Resources Board, was to study the hydrogeology of the Central Oklahoma aquifer to provide information that will enable the OWRB to determine the maximum annual yield of the aquifer based on different proposed management plans. Groundwater flow models are typically used by the OWRB as a tool to help determine the maximum annual yield. This report presents the potentiometric surface of the Central Oklahoma aquifer based on water-level data collected in 2009 as part of the current (2010) hydrologic study. The U.S. Geological Survey (USGS) Hydrologic Investigations Atlas HA-724 by Christenson and others (1992) presents the 1986-87 potentiometric-surface map. This 1986-87 potentiometric-surface map was made as part of the USGS National Water-Quality Assessment pilot project for the Central Oklahoma aquifer that examined the geochemical and hydrogeological processes operating in the aquifer. An attempt was made to obtain water-level measurements for the 2009 potentiometric-surface map from the wells used for the 1986-87 potentiometric-surface map. Well symbols with circles on the 2009 potentiometric-surface map (fig. 1) indicate wells that were used for the 1986-87 potentiometric-surface map.

Drivers of Macrofungi Community Structure Differ between Soil and Rotten-Wood Substrates in a Temperate Mountain Forest in China

PubMed Central

Chen, Yun; Svenning, Jens-Christian; Wang, Xueying; Cao, Ruofan; Yuan, Zhiliang; Ye, Yongzhong

2018-01-01

The effects of environmental and dispersal processes on macrofungi community assembly remain unclear. Further, it is not well understood if community assembly differs for different functional guilds of macrofungi, e.g., soil and rotten-wood macrofungi. In this study, using 2433 macrofungi sporocarps belonging to 217 species located within a forest dynamics plot in temperate mountain forest (China), we examined the explanatory power of topography, spatial eigenvectors (representing unknown spatial processes, e.g., dispersal), plant community, and light availability for local spatial variation in the macrofungi community through variance partitioning and partial least squares path modeling. We found spatial eigenvectors and light as the most important factors for explaining species richness and composition of macrofungi. Light was negatively correlated with species richness of macrofungi. Furthermore, species richness and composition of soil macrofungi were best explained by light, and species richness and composition of rotten-wood macrofungi were best explained by spatial eigenvectors. Woody plant community structure was not an important factor for species richness and composition of macrofungi. Our findings suggest that spatial processes, perhaps dispersal limitation, and light availability were the most important factors affecting macrofungi community in temperate deciduous broad-leaved forest. Major differences in influencing factors between soil and rotten-wood macrofungi were observed, with light as the major driver for soil macrofungi and unknown spatial processes as the major driver for rotten-wood macrofungi. These findings shed new light to the processes shaping community assembly in macrofungi in temperate deciduous broad-leaved forest and point to the potential importance of both intrinsic dynamics, such as dispersal, and external forcing, such as forest dynamics, via its effect on light availability. PMID:29410660

Protein structure recognition: From eigenvector analysis to structural threading method

NASA Astrophysics Data System (ADS)

Cao, Haibo

In this work, we try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. We found a strong correlation between amino acid sequence and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, we give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part include discussions of interactions among amino acids residues, lattice HP model, and the designablity principle. In the second part, we try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in our eigenvector study of protein contact matrix. We believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, we discuss a threading method based on the correlation between amino acid sequence and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, we list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.

Simultaneous multigrid techniques for nonlinear eigenvalue problems: Solutions of the nonlinear Schrödinger-Poisson eigenvalue problem in two and three dimensions

NASA Astrophysics Data System (ADS)

Costiner, Sorin; Ta'asan, Shlomo

1995-07-01

Algorithms for nonlinear eigenvalue problems (EP's) often require solving self-consistently a large number of EP's. Convergence difficulties may occur if the solution is not sought in an appropriate region, if global constraints have to be satisfied, or if close or equal eigenvalues are present. Multigrid (MG) algorithms for nonlinear problems and for EP's obtained from discretizations of partial differential EP have often been shown to be more efficient than single level algorithms. This paper presents MG techniques and a MG algorithm for nonlinear Schrödinger Poisson EP's. The algorithm overcomes the above mentioned difficulties combining the following techniques: a MG simultaneous treatment of the eigenvectors and nonlinearity, and with the global constrains; MG stable subspace continuation techniques for the treatment of nonlinearity; and a MG projection coupled with backrotations for separation of solutions. These techniques keep the solutions in an appropriate region, where the algorithm converges fast, and reduce the large number of self-consistent iterations to only a few or one MG simultaneous iteration. The MG projection makes it possible to efficiently overcome difficulties related to clusters of close and equal eigenvalues. Computational examples for the nonlinear Schrödinger-Poisson EP in two and three dimensions, presenting special computational difficulties that are due to the nonlinearity and to the equal and closely clustered eigenvalues are demonstrated. For these cases, the algorithm requires O(qN) operations for the calculation of q eigenvectors of size N and for the corresponding eigenvalues. One MG simultaneous cycle per fine level was performed. The total computational cost is equivalent to only a few Gauss-Seidel relaxations per eigenvector. An asymptotic convergence rate of 0.15 per MG cycle is attained.

Electrostatic point charge fitting as an inverse problem: Revealing the underlying ill-conditioning

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

Ivanov, Maxim V.; Talipov, Marat R.; Timerghazin, Qadir K., E-mail: qadir.timerghazin@marquette.edu

2015-10-07

Atom-centered point charge (PC) model of the molecular electrostatics—a major workhorse of the atomistic biomolecular simulations—is usually parameterized by least-squares (LS) fitting of the point charge values to a reference electrostatic potential, a procedure that suffers from numerical instabilities due to the ill-conditioned nature of the LS problem. To reveal the origins of this ill-conditioning, we start with a general treatment of the point charge fitting problem as an inverse problem and construct an analytical model with the point charges spherically arranged according to Lebedev quadrature which is naturally suited for the inverse electrostatic problem. This analytical model is contrastedmore » to the atom-centered point-charge model that can be viewed as an irregular quadrature poorly suited for the problem. This analysis shows that the numerical problems of the point charge fitting are due to the decay of the curvatures corresponding to the eigenvectors of LS sum Hessian matrix. In part, this ill-conditioning is intrinsic to the problem and is related to decreasing electrostatic contribution of the higher multipole moments, that are, in the case of Lebedev grid model, directly associated with the Hessian eigenvectors. For the atom-centered model, this association breaks down beyond the first few eigenvectors related to the high-curvature monopole and dipole terms; this leads to even wider spread-out of the Hessian curvature values. Using these insights, it is possible to alleviate the ill-conditioning of the LS point-charge fitting without introducing external restraints and/or constraints. Also, as the analytical Lebedev grid PC model proposed here can reproduce multipole moments up to a given rank, it may provide a promising alternative to including explicit multipole terms in a force field.« less

Distribution of electromagnetic field and group velocities in two-dimensional periodic systems with dissipative metallic components

NASA Astrophysics Data System (ADS)

Kuzmiak, Vladimir; Maradudin, Alexei A.

1998-09-01

We study the distribution of the electromagnetic field of the eigenmodes and corresponding group velocities associated with the photonic band structures of two-dimensional periodic systems consisting of an array of infinitely long parallel metallic rods whose intersections with a perpendicular plane form a simple square lattice. We consider both nondissipative and lossy metallic components characterized by a complex frequency-dependent dielectric function. Our analysis is based on the calculation of the complex photonic band structure obtained by using a modified plane-wave method that transforms the problem of solving Maxwell's equations into the problem of diagonalizing an equivalent non-Hermitian matrix. In order to investigate the nature and the symmetry properties of the eigenvectors, which significantly affect the optical properties of the photonic lattices, we evaluate the associated field distribution at the high symmetry points and along high symmetry directions in the two-dimensional first Brillouin zone of the periodic system. By considering both lossless and lossy metallic rods we study the effect of damping on the spatial distribution of the eigenvectors. Then we use the Hellmann-Feynman theorem and the eigenvectors and eigenfrequencies obtained from a photonic band-structure calculation based on a standard plane-wave approach applied to the nondissipative system to calculate the components of the group velocities associated with individual bands as functions of the wave vector in the first Brillouin zone. From the group velocity of each eigenmode the flow of energy is examined. The results obtained indicate a strong directional dependence of the group velocity, and confirm the experimental observation that a photonic crystal is a potentially efficient tool in controlling photon propagation.

Level repulsion and band sorting in phononic crystals

NASA Astrophysics Data System (ADS)

Lu, Yan; Srivastava, Ankit

2018-02-01

In this paper we consider the problem of avoided crossings (level repulsion) in phononic crystals and suggest a computationally efficient strategy to distinguish them from normal cross points. This process is essential for the correct sorting of the phononic bands and, subsequently, for the accurate determination of mode continuation, group velocities, and emergent properties which depend on them such as thermal conductivity. Through explicit phononic calculations using generalized Rayleigh quotient, we identify exact locations of exceptional points in the complex wavenumber domain which results in level repulsion in the real domain. We show that in the vicinity of the exceptional point the relevant phononic eigenvalue surfaces resemble the surfaces of a 2 by 2 parameter-dependent matrix. Along a closed loop encircling the exceptional point we show that the phononic eigenvalues are exchanged, just as they are for the 2 by 2 matrix case. However, the behavior of the associated eigenvectors is shown to be more complex in the phononic case. Along a closed loop around an exceptional point, we show that the eigenvectors can flip signs multiple times unlike a 2 by 2 matrix where the flip of sign occurs only once. Finally, we exploit these eigenvector sign flips around exceptional points to propose a simple and efficient method of distinguishing them from normal crosses and of correctly sorting the band-structure. Our proposed method is roughly an order-of-magnitude faster than the zoom-in method and correctly identifies > 96% of the cases considered. Both its speed and accuracy can be further improved and we suggest some ways of achieving this. Our method is general and, as such, would be directly applicable to other eigenvalue problems where the eigenspectrum needs to be correctly sorted.

Planning applications in East Central Florida

NASA Technical Reports Server (NTRS)

Hannah, J. W. (Principal Investigator); Thomas, G. L.; Esparza, F.; Millard, J. J.

1974-01-01

The author has identified the following significant results. This is a study of applications of ERTS data to planning problems, especially as applicable to East Central Florida. The primary method has been computer analysis of digital data, with visual analysis of images serving to supplement the digital analysis. The principal method of analysis was supervised maximum likelihood classification, supplemented by density slicing and mapping of ratios of band intensities. Land-use maps have been prepared for several urban and non-urban sectors. Thematic maps have been found to be a useful form of the land-use maps. Change-monitoring has been found to be an appropriate and useful application. Mapping of marsh regions has been found effective and useful in this region. Local planners have participated in selecting training samples and in the checking and interpretation of results.

The first large geological map of Central and Eastern Europe (1815)

NASA Astrophysics Data System (ADS)

Grigelis, Algimantas; Wójcik, Zbigniew; Narębski, Wojciech; Gelumbauskaitė, Leonora Živilė; Kozák, Jan; Czarniecki, Stanisław

2008-01-01

The first large geological map of Central and Eastern Europe was compiled by Stanisław Staszic in the early 19th century. The map is based on the geological survey that Staszic performed in different parts of Poland and adjacent areas. In 1814, Staszic presented his ideas on the geology and mineral sources of Poland and Lithuania. In 1815, he completed the book-length descriptive analysis O ziemorodztwie Karpatów i innych gór i równin Polski przez Stanisława Staszica, which was published in Warsaw and complemented by a large geological map of Central and Eastern Europe. His later studies were compiled in a historico-philosophical treatise titled Ród ludzki (1819-1820). The complete edition of Staszic's works, Dzieła, which also included these publications, appeared over 1816-1820. The geological field survey that he performed over several years, and his study of social-economic problems enabled Staszic to draw in great detail a geological map of the Carpathians, the Central Polish Highlands, Volhynia (modern Ukraine) and the Eastern Alps, as well as the areas of the Polish-Lithuanian Lowlands, the southern coast of the Baltic Sea, Polesye (modern Belarus), Moldova, Transylvania, and Hungary. Staszic was interested in the exploration of mineral deposits, particularly in Poland, which had rock salt, copper and iron ores, and coal. In his monograph and map, he adopted a stratigraphic subdivision based on types of rock contents and organic fossils, which was a slightly modified version of Werner's classification system. The lithological legend sets five classes and 135 different types of rock, and 15 types of ore deposits, using the French names for these. In general, Staszic was an advocate of Werner's paradigm; however, he did not follow exactly the ideas of the German geologist. Staszic's fundamental work recapitulates his views on geological history of Central and Eastern Europe, and brings to an end the Enlightment period in the geology of that part of Europe.

Landscape features, standards, and semantics in U.S. national topographic mapping databases

USGS Publications Warehouse

Varanka, Dalia

2009-01-01

The objective of this paper is to examine the contrast between local, field-surveyed topographical representation and feature representation in digital, centralized databases and to clarify their ontological implications. The semantics of these two approaches are contrasted by examining the categorization of features by subject domains inherent to national topographic mapping. When comparing five USGS topographic mapping domain and feature lists, results indicate that multiple semantic meanings and ontology rules were applied to the initial digital database, but were lost as databases became more centralized at national scales, and common semantics were replaced by technological terms.

Color-coded topography and shaded relief map of the lunar near side and far side hemispheres

USGS Publications Warehouse

,

2003-01-01

This publication is a set of three sheets of topographic maps that presents color-coded topographic data digitally merged with shaded relief data. Adopted figure: The figure for the Moon, used for the computation of the map projection, is a sphere with a radius of 1737.4 km. Because the Moon has no surface water, and hence no sea level, the datum (the 0 km contour) for elevations is defined as the radius of 1737.4 km. Coordinates are based on the mean Earth/polar axis (M.E.) coordinates system, the z axis is the axis of the Moon's rotation, and the x axis is the mean Earth direction. The center of mass is the origin of the coordinate system. The equator lies in the x-y plane and the prime meridian lies in the x-z plane with east longitude values being positive. Projection: The projection is Lambert Azimuthal Equal Area Projection. The scale factor at the central latitude and central longitude point is 1:10,000,000. For the near side hemisphere the central latitude and central longitude point is at 0° and 0°. For the far side hemisphere the central latitude and central longitude point is at 0° and 180°.

A Brief Historical Introduction to Determinants with Applications

ERIC Educational Resources Information Center

Debnath, L.

2013-01-01

This article deals with a short historical introduction to determinants with applications to the theory of equations, geometry, multiple integrals, differential equations and linear algebra. Included are some properties of determinants with proofs, eigenvalues, eigenvectors and characteristic equations with examples of applications to simple…

Drawing Space: Mathematicians' Kinetic Conceptions of Eigenvectors

ERIC Educational Resources Information Center

Sinclair, Nathalie; Gol Tabaghi, Shiva

2010-01-01

This paper explores how mathematicians build meaning through communicative activity involving talk, gesture and diagram. In the course of describing mathematical concepts, mathematicians use these semiotic resources in ways that blur the distinction between the mathematical and physical world. We shall argue that mathematical meaning of…

Information content of IRIS spectra. [from Nimbus 4 satellite

NASA Technical Reports Server (NTRS)

Price, J. C.

1974-01-01

Spectra from the satellite instrument IRIS (infra red interferometer spectrometer) were examined to find the number of independent variables needed to describe these broadband high spectral resolution data. The radiated power in the atmospheric window from 771 to 981/cm was the first parameter chosen for fitting observed spectra. At succeeding levels of analysis the residual variability (observed spectrum - best fit spectrum) in an ensemble of observations was partioned into spectral eigenvectors. The eigenvector describing the largest fraction of this variability was examined for a strong spectral signature; the power in the corresponding spectral band was then used as the next fitting parameter. The measured power in nine spectral intervals, when inserted in the spectral fitting functions, was adequate to describe most spectra to within the noise level of IRIS. Considerations of relative signal strength and scales of atmospheric variability suggest a combination sounder (multichannel-broad field of view) scanner (window channel-small field of view) as an efficient observing instrument.

Substructure Versus Property-Level Dispersed Modes Calculation

NASA Technical Reports Server (NTRS)

Stewart, Eric C.; Peck, Jeff A.; Bush, T. Jason; Fulcher, Clay W.

2016-01-01

This paper calculates the effect of perturbed finite element mass and stiffness values on the eigenvectors and eigenvalues of the finite element model. The structure is perturbed in two ways: at the "subelement" level and at the material property level. In the subelement eigenvalue uncertainty analysis the mass and stiffness of each subelement is perturbed by a factor before being assembled into the global matrices. In the property-level eigenvalue uncertainty analysis all material density and stiffness parameters of the structure are perturbed modified prior to the eigenvalue analysis. The eigenvalue and eigenvector dispersions of each analysis (subelement and property-level) are also calculated using an analytical sensitivity approximation. Two structural models are used to compare these methods: a cantilevered beam model, and a model of the Space Launch System. For each structural model it is shown how well the analytical sensitivity modes approximate the exact modes when the uncertainties are applied at the subelement level and at the property level.

Predicting the impact of urban flooding using open data.

PubMed

Tkachenko, Nataliya; Procter, Rob; Jarvis, Stephen

2016-05-01

This paper aims to explore whether there is a relationship between search patterns for flood risk information on the Web and how badly localities have been affected by flood events. We hypothesize that localities where people stay more actively informed about potential flooding experience less negative impact than localities where people make less effort to be informed. Being informed, of course, does not hold the waters back; however, it may stimulate (or serve as an indicator of) such resilient behaviours as timely use of sandbags, relocation of possessions from basements to upper floors and/or temporary evacuation from flooded homes to alternative accommodation. We make use of open data to test this relationship empirically. Our results demonstrate that although aggregated Web search reflects average rainfall patterns, its eigenvectors predominantly consist of locations with similar flood impacts during 2014-2015. These results are also consistent with statistically significant correlations of Web search eigenvectors with flood warning and incident reporting datasets.

The Evolution of Ih C_60 Vibrational Modes in Planar Polymerized C_60.

NASA Astrophysics Data System (ADS)

Adams, G. B.; Page, J. B.

2001-03-01

We have used first-principles local-orbital-based molecular dynamics(O.F. Sankey and D.J. Niklewski, Phys. Rev. B40), 3979 (1989). to simulate a wide variety of planar polymers of C_60, including the orthorhombic (O), tetrahedral (T), and rhombohedral (R) polymers which have been reported experimentally. It has been customary to assume that the vibrational modes of the polymers are moderately perturbed Ih C_60 vibrational modes.(See, for example V.A. Davydov et al.), Phys. Rev. B61, 11936 (2000) or V.C. Long et al., Phys. Rev. B 61, 13191 (2000). To test this assumption, we have expanded the polymer vibrational eigenvectors in the eigenvectors of Ih C_60, thus determining quantitatively the percentage contribution of each Ih C_60 mode to each polymer vibrational mode. We find that for many polymer modes the assumption is not justified. We report our results for selected Raman- and IR-active vibrational modes of the observed polymers.

Universal single level implicit algorithm for gasdynamics

NASA Technical Reports Server (NTRS)

Lombard, C. K.; Venkatapthy, E.

1984-01-01

A single level effectively explicit implicit algorithm for gasdynamics is presented. The method meets all the requirements for unconditionally stable global iteration over flows with mixed supersonic and supersonic zones including blunt body flow and boundary layer flows with strong interaction and streamwise separation. For hyperbolic (supersonic flow) regions the method is automatically equivalent to contemporary space marching methods. For elliptic (subsonic flow) regions, rapid convergence is facilitated by alternating direction solution sweeps which bring both sets of eigenvectors and the influence of both boundaries of a coordinate line equally into play. Point by point updating of the data with local iteration on the solution procedure at each spatial step as the sweeps progress not only renders the method single level in storage but, also, improves nonlinear accuracy to accelerate convergence by an order of magnitude over related two level linearized implicit methods. The method derives robust stability from the combination of an eigenvector split upwind difference method (CSCM) with diagonally dominant ADI(DDADI) approximate factorization and computed characteristic boundary approximations.

Spectral analysis of Chinese language: Co-occurrence networks from four literary genres

NASA Astrophysics Data System (ADS)

Liang, Wei; Chen, Guanrong

2016-05-01

The eigenvalues and eigenvectors of the adjacency matrix of a network contain essential information about its topology. For each of the Chinese language co-occurrence networks constructed from four literary genres, i.e., essay, popular science article, news report, and novel, it is found that the largest eigenvalue depends on the network size N, the number of edges, the average shortest path length, and the clustering coefficient. Moreover, it is found that their node-degree distributions all follow a power-law. The number of different eigenvalues, Nλ, is found numerically to increase in the manner of Nλ ∝ log N for novel and Nλ ∝ N for the other three literary genres. An ;M; shape or a triangle-like distribution appears in their spectral densities. The eigenvector corresponding to the largest eigenvalue is mostly localized to a node with the largest degree. For the above observed phenomena, mathematical analysis is provided with interpretation from a linguistic perspective.

Systemic risk and spatiotemporal dynamics of the US housing market.

PubMed

Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene

2014-01-13

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles.

Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data

PubMed Central

Hu, Jianhua; Wang, Peng; Qu, Annie

2014-01-01

Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433

Information content in Iris spectra. [Infrared Interferometer Spectrometer of Nimbus 4 satellite

NASA Technical Reports Server (NTRS)

Price, J. C.

1975-01-01

Spectra from the satellite instrument Iris (infrared interferometer spectrometer) were examined to find the number of independent variables needed to describe the broad-band high-resolution spectral data. The radiated power in the atmospheric window from 771 to 981 per cm was the first parameter chosen for fitting observed spectra. At succeeding levels of analysis, the residual variability (observed spectrum minus best-fit spectrum) in an ensemble of observations was partitioned into spectral eigenvectors. The eigenvector describing the largest fraction of this variability was examined for a strong spectral signature; the power in the corresponding spectral band was then used as the next fitting parameter. The measured power in nine spectral intervals, when it was inserted in the spectral-fitting functions, was adequate to describe most spectra to within the noise level of Iris. Considerations of relative signal strength and scales of atmospheric variability suggest a combination sounder (multichannel, broad field of view) scanner (window channel, small field of view) as an efficient observing instrument.

Power law tails in phylogenetic systems.

PubMed

Qin, Chongli; Colwell, Lucy J

2018-01-23

Covariance analysis of protein sequence alignments uses coevolving pairs of sequence positions to predict features of protein structure and function. However, current methods ignore the phylogenetic relationships between sequences, potentially corrupting the identification of covarying positions. Here, we use random matrix theory to demonstrate the existence of a power law tail that distinguishes the spectrum of covariance caused by phylogeny from that caused by structural interactions. The power law is essentially independent of the phylogenetic tree topology, depending on just two parameters-the sequence length and the average branch length. We demonstrate that these power law tails are ubiquitous in the large protein sequence alignments used to predict contacts in 3D structure, as predicted by our theory. This suggests that to decouple phylogenetic effects from the interactions between sequence distal sites that control biological function, it is necessary to remove or down-weight the eigenvectors of the covariance matrix with largest eigenvalues. We confirm that truncating these eigenvectors improves contact prediction.

Central Pacific Hurricane Center - Honolulu, Hawai`i

Science.gov Websites

Department of Commerce Central Pacific Hurricane Center National Oceanic and Atmospheric Administration Blank Tracking Maps ▾ Educational Resources Be Prepared! NWS Hurricane Prep Week Preparedness Weather Central Pacific Hurricane Center Honolulu HI 800 PM HST Thu Nov 30 2017 For the central North Pacific

Photogeologic mapping in central southwest Bahia, using LANDSAT-1 multispectral images. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Ohara, T.

1981-01-01

The interpretation of LANDSAT multispectral imagery for geologic mapping of central southwest Bahia, Brazil is described. Surface features such as drainage, topography, vegetation and land use are identified. The area is composed of low grade Precambrian rocks covered by Mezozoic and Cenozoic sediments. The principal mineral prospects of economic value are fluorite and calcareous rocks. Gold, calcite, rock crystal, copper, potassium nitrate and alumina were also identified.

Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.

Floquet states of a kicked particle in a singular potential: Exponential and power-law profiles

NASA Astrophysics Data System (ADS)

Paul, Sanku; Santhanam, M. S.

2018-03-01

It is well known that, in the chaotic regime, all the Floquet states of kicked rotor system display an exponential profile resulting from dynamical localization. If the kicked rotor is placed in an additional stationary infinite potential well, its Floquet states display power-law profile. It has also been suggested in general that the Floquet states of periodically kicked systems with singularities in the potential would have power-law profile. In this work, we study the Floquet states of a kicked particle in finite potential barrier. By varying the height of finite potential barrier, the nature of transition in the Floquet state from exponential to power-law decay profile is studied. We map this system to a tight-binding model and show that the nature of decay profile depends on energy band spanned by the Floquet states (in unperturbed basis) relative to the potential height. This property can also be inferred from the statistics of Floquet eigenvalues and eigenvectors. This leads to an unusual scenario in which the level spacing distribution, as a window in to the spectral correlations, is not a unique characteristic for the entire system.

Variable-free exploration of stochastic models: a gene regulatory network example.

PubMed

Erban, Radek; Frewen, Thomas A; Wang, Xiao; Elston, Timothy C; Coifman, Ronald; Nadler, Boaz; Kevrekidis, Ioannis G

2007-04-21

Finding coarse-grained, low-dimensional descriptions is an important task in the analysis of complex, stochastic models of gene regulatory networks. This task involves (a) identifying observables that best describe the state of these complex systems and (b) characterizing the dynamics of the observables. In a previous paper [R. Erban et al., J. Chem. Phys. 124, 084106 (2006)] the authors assumed that good observables were known a priori, and presented an equation-free approach to approximate coarse-grained quantities (i.e., effective drift and diffusion coefficients) that characterize the long-time behavior of the observables. Here we use diffusion maps [R. Coifman et al., Proc. Natl. Acad. Sci. U.S.A. 102, 7426 (2005)] to extract appropriate observables ("reduction coordinates") in an automated fashion; these involve the leading eigenvectors of a weighted Laplacian on a graph constructed from network simulation data. We present lifting and restriction procedures for translating between physical variables and these data-based observables. These procedures allow us to perform equation-free, coarse-grained computations characterizing the long-term dynamics through the design and processing of short bursts of stochastic simulation initialized at appropriate values of the data-based observables.

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

PubMed Central

Perez-Saez, Javier; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Sokolow, Susanne H.; De Leo, Giulio A.; Mande, Theophile; Ceperley, Natalie; Froehlich, Jean-Marc; Sou, Mariam; Karambiri, Harouna; Yacouba, Hamma; Maiga, Amadou; Gatto, Marino; Rinaldo, Andrea

2015-01-01

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite’s intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management. PMID:26513655

Reconstructing time series water volumes of drying lakes in Central Asia with ZY-3 stereo remote sensing data

NASA Astrophysics Data System (ADS)

Li, J.; Warner, T.; Bao, A.

2017-12-01

Central Asia is one of the world most vulnerable areas responding to global change. Lakes in arid regions of Central Asia remain sensitive to climatic change and fluctuate with temperature and precipitation variations. Study showed that some central asian inland lakes in showed a trend of area shrinkage or extinct in the last decades. Quantitative analysis of lake volume changes in spatio-temporal processes will improve our understanding water resource utilization in arid regions and their responses to regional climate change. However, due to the lack of lake bathmetry or observation data, the volumes of these lakes remain unknown. In this paper, three lakes, such as Chaiwopu lake, Alik Lake and Selectyteniz Lake in Central Asia are used to reconstruct lake volume changes. Firstly, stereo mapping technologies derived from ZY-3 high resolution data are used to map the high-precision 3-D lake bathmetry, so as to create "Area-Level-Volume" based on contours of lake bathmetry. Secondly, time series lake areas in the last 50 years are mapped with multi-source and multi-temporal remote sensing images. Based on lake storage curves and time series lake areas, lake volumes in the last 5 decades can be reconstructed, and the spatio-temporal characteristics of lake volume changes and their mechanisms are also analyzed. The results showed that the high-precision lake hydrological elements are reconstructed on arid drying lakes through the application of stereo mapping technology in remote sensing.

Effects of Multidimensional Concept Maps on Fourth Graders' Learning in Web-Based Computer Course

ERIC Educational Resources Information Center

Huang, Hwa-Shan; Chiou, Chei-Chang; Chiang, Heien-Kun; Lai, Sung-Hsi; Huang, Chiun-Yen; Chou, Yin-Yu

2012-01-01

This study explores the effect of multidimensional concept mapping instruction on students' learning performance in a web-based computer course. The subjects consisted of 103 fourth graders from an elementary school in central Taiwan. They were divided into three groups: multidimensional concept map (MCM) instruction group, Novak concept map (NCM)…

Hydrothermal alteration maps of the central and southern Basin and Range province of the United States compiled from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data

USGS Publications Warehouse

Mars, John L.

2013-01-01

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and Interactive Data Language (IDL) logical operator algorithms were used to map hydrothermally altered rocks in the central and southern parts of the Basin and Range province of the United States. The hydrothermally altered rocks mapped in this study include (1) hydrothermal silica-rich rocks (hydrous quartz, chalcedony, opal, and amorphous silica), (2) propylitic rocks (calcite-dolomite and epidote-chlorite mapped as separate mineral groups), (3) argillic rocks (alunite-pyrophyllite-kaolinite), and (4) phyllic rocks (sericite-muscovite). A series of hydrothermal alteration maps, which identify the potential locations of hydrothermal silica-rich, propylitic, argillic, and phyllic rocks on Landsat Thematic Mapper (TM) band 7 orthorectified images, and geographic information systems shape files of hydrothermal alteration units are provided in this study.

The Modern Origin of Matrices and Their Applications

ERIC Educational Resources Information Center

Debnath, L.

2014-01-01

This paper deals with the modern development of matrices, linear transformations, quadratic forms and their applications to geometry and mechanics, eigenvalues, eigenvectors and characteristic equations with applications. Included are the representations of real and complex numbers, and quaternions by matrices, and isomorphism in order to show…

Introduction to the Application of the Dynalist Computer Program to the Analysis of Rail Systems Dynamics

DOT National Transportation Integrated Search

1974-08-01

DYNALIST, a computer program that extracts complex eigenvalues and eigenvectors for dynamic systems described in terms of matrix equations of motion, has been acquired and made operational at TSC. In this report, simple dynamic systems are used to de...

Biological Applications in the Mathematics Curriculum

ERIC Educational Resources Information Center

Marland, Eric; Palmer, Katrina M.; Salinas, Rene A.

2008-01-01

In this article we provide two detailed examples of how we incorporate biological examples into two mathematics courses: Linear Algebra and Ordinary Differential Equations. We use Leslie matrix models to demonstrate the biological properties of eigenvalues and eigenvectors. For Ordinary Differential Equations, we show how using a logistic growth…

Eigensystem analysis of classical relaxation techniques with applications to multigrid analysis

NASA Technical Reports Server (NTRS)

Lomax, Harvard; Maksymiuk, Catherine

1987-01-01

Classical relaxation techniques are related to numerical methods for solution of ordinary differential equations. Eigensystems for Point-Jacobi, Gauss-Seidel, and SOR methods are presented. Solution techniques such as eigenvector annihilation, eigensystem mixing, and multigrid methods are examined with regard to the eigenstructure.

Semiclassical geometry of integrable systems

NASA Astrophysics Data System (ADS)

Reshetikhin, Nicolai

2018-04-01

The main result of this paper is a formula for the scalar product of semiclassical eigenvectors of two integrable systems on the same symplectic manifold. An important application of this formula is the Ponzano–Regge type of asymptotic of Racah–Wigner coefficients. Dedicated to the memory of P P Kulish.

The Application of Principal Component Analysis Using Fixed Eigenvectors to the Infrared Thermographic Inspection of the Space Shuttle Thermal Protection System

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Winfree, William P.

2006-01-01

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the good material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued when a fixed set of eigenvectors is used to process the thermal data from the RCC materials. These eigen vectors can be generated either from an analytic model of the thermal response of the material under examination, or from a large cross section of experimental data. This paper will provide the details of the analytic model; an overview of the PCA process; as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens. Details of a system that has been developed to allow insitu inspection of a majority of shuttle RCC components will be presented along with the acceptance test results for this system. Additionally, the results of applying this technology to the Space Shuttle Discovery after its return from flight will be presented.

The 2008 U.S. Geological Survey national seismic hazard models and maps for the central and eastern United States

USGS Publications Warehouse

Petersen, Mark D.; Frankel, Arthur D.; Harmsen, Stephen C.; Mueller, Charles S.; Boyd, Oliver S.; Luco, Nicolas; Wheeler, Russell L.; Rukstales, Kenneth S.; Haller, Kathleen M.

2012-01-01

In this paper, we describe the scientific basis for the source and ground-motion models applied in the 2008 National Seismic Hazard Maps, the development of new products that are used for building design and risk analyses, relationships between the hazard maps and design maps used in building codes, and potential future improvements to the hazard maps.

Geologic map of the Seldovia quadrangle, south-central Alaska

USGS Publications Warehouse

Bradley, Dwight C.; Kusky, Timothy M.; Haeussler, Peter J.; Karl, Susan M.; Donley, D. Thomas

1999-01-01

This is a 1:250,000-scale map of the bedrock geology of the Seldovia quadrangle, south-central Alaska. The map area covers the southwestern end of the Kenai Peninsula, including the Kenai Lowlands and Kenai Mountains, on either side of Kachemak Bay. The waters of Cook Inlet cover roughly half of the map area, and a part of the Alaska Peninsula near Iliamna Volcano lies in the extreme northwest corner of the map. The bedrock geology is based on new reconnaissance field work by the U.S. Geological Survey during parts of the 1988-1993 field seasons, and on previous mapping from a number of sources. The new mapping focused on the previously little-known Chugach accretionary complex in the Kenai Mountains. Important new findings include the recognition of mappable subdivisions of the McHugh Complex (a subduction melange of mostly Mesozoic protoliths), more accurate placement of the thrust contact between the McHugh Complex and Valdez Group (Upper Cretaceous trench turbidites), and the recognition of several new near-trench plutons of early Tertiary age.

Spatial Databases of Geological, Geophysical, and Mineral Resource Data Relevant to Sandstone-Hosted Copper Deposits in Central Kazakhstan

USGS Publications Warehouse

Syusyura, Boris; Box, Stephen E.; Wallis, John C.

2010-01-01

Central Kazakhstan is host to one of the world's giant sandstone-hosted copper deposits, the Dzhezkazgan deposit, and several similar, smaller deposits. The United Stated Geological Survey (USGS) is assessing the potential for other, undiscovered deposits of this type in the surrounding region of central Kazakhstan. As part of this effort, Syusyura compiled and partially translated an array of mostly unpublished geologic, geophysical, and mineral resource data for this region in digital format from the archives of the former Union of Soviet Socialists Republics (of which Kazakhstan was one of the member republics until its dissolution in 1991), as well as from later archives of the Republic of Kazakhstan or of the Kazakhstan consulting firm Mining Economic Consulting (MEC). These digital data are primarily map-based displays of information that were transmitted either in ESRI ArcGIS, georeferenced format, or non-georeferenced map image files. Box and Wallis reviewed all the data, translated Cyrillic text where necessary, inspected the maps for consistency, georeferenced the unprojected map images, and reorganized the data into the filename and folder structure of this publication.

Mapping and characterization from aeromagnetic data of the Foum Zguid dolerite Dyke (Anti-Atlas, Morocco) a member of the Central Atlantic Magmatic Province (CAMP)

NASA Astrophysics Data System (ADS)

Bouiflane, Mustapha; Manar, Ahmed; Medina, Fida; Youbi, Nasrrddine; Rimi, Abdelkrim

2017-06-01

A high-resolution aeromagnetic survey was carried out in the Anti- Atlas, Morocco covering the main areas traversed by the Great CAMP Foum Zguid dyke (FZD). This ;doleritic; dyke belongs to the Central Atlantic Magmatic Province (CAMP), a Large Igneous Province which is associated with the fragmentation of the supercontinent Pangaea and the initial stages of rifting of the Central Atlantic Ocean. It also coincides in time with the mass extinction of the Triassic - Jurassic boundary. Based on the study of geological maps and Google Earth satellite images, it appears that the FZD is poorly exposed and, often covered by Quaternary deposits. This work proposes aeromagnetic modelling and interpretation of the FZD in order to better constrain its structural extent. The data have allowed (i) mapping of the dyke over great distances, under the Quaternary deposits and through areas where it was poorly characterized on the geological map; (ii) identifying major tectonic lineaments interpreted as faults; (iii) recognizing magnetic anomalies related to mafic intrusive bodies; and (iv) informing about regional structural context.

Reading Social wMaps.w

ERIC Educational Resources Information Center

Clements, Millard

1982-01-01

What should social studies teachers be trying to teach students how to do? Every culture provides its members with social "maps" that explain how things are--e.g., school materials, advertisements. Teaching students how to read these social "maps" should be the central task for social studies education. (RM)

Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado

USGS Publications Warehouse

Machette, Michael N.; Thompson, Ren A.; Brandt, Theodore R.

2008-01-01

This geologic map presents new polygon (geologic map unit contacts) and line (terrace and lacustrine spit/barrier bar) vector data for a map comprised of four 7.5' quadrangles in the north-central part of the Alamosa, Colorado, 30' x 60' quadrangle. The quadrangles include Baldy, Blanca, Blanca SE, and Lasauses. The map database, compiled at 1:50,000 scale from new 1:24,000-scale mapping, provides geologic coverage of an area of current hydrogeologic, tectonic, and stratigraphic interest. The mapped area is located primarily in Costilla County, but contains portions of Alamosa and Conejos Counties, and includes the town of Blanca in its northeastern part. The map area is mainly underlain by surficial geologic materials (fluvial and lacustrine deposits, and eolian sand), but Tertiary volcanic and volcaniclastic rocks crop out in the San Luis Hills, which are in the central and southern parts of the mapped area. The surficial geology of this area has never been mapped at any scale greater than 1:250,000 (broad reconnaissance), so this new map provides important data for ground-water assessments, engineering geology, and the Quaternary geologic history of the San Luis Basin. Newly discovered shoreline deposits are of particular interest (sands and gravels) that are associated with the high-water stand of Lake Alamosa, a Pliocene to middle Pleistocene lake that occupied the San Luis basin prior to its overflow and cutting of a river gorge through the San Luis Hills. After the lake drained, the Rio Grande system included Colorado drainages for the first time since the Miocene (>5.3 Ma). In addition, Servilleta Basalt, which forms the Basaltic Hills on the east margin of the map area, is dated at 3.79+or-0.17 Ma, consistent with its general age range of 3.67-4.84 Ma. This map provides new geologic information for better understanding ground-water flow paths in and adjacent to the Rio Grande system. The map abuts U.S. Geological Survey Open File Report 2005-1392 (a map of the northwestern part of the Alamosa 30' x 60' quadrangle map) to the west and U.S. Geological Survey Scientific Investigations Map 2965 (Fort Garland 7.5' quadrangle) to the east.

Glocalized New Age Spirituality: A Mental Map of the New Central Bus Station in Tel Aviv, Deciphered through Its Visual Codes and Based on Ethno-Visual Research

ERIC Educational Resources Information Center

Ben-Peshat, Malka; Sitton, Shoshana

2011-01-01

We present here the findings of an ethno-visual research study involving the creation of a mental map of images, artifacts and practices in Tel Aviv's New Central Bus Station. This huge and complex building, part bus station, part shopping mall, has become a stage for multicultural encounters and interactions among diverse communities of users.…

Reported historic asbestos prospects and natural asbestos occurrences in the central United States

USGS Publications Warehouse

Van Gosen, Bradley S.

2006-01-01

This map and its accompanying dataset provide information for 26 natural asbestos occurrences in the Central United States (U.S.), using descriptions found in the geologic literature. Data on location, mineralogy, geology, and relevant literature for each asbestos site are provided. Using the map and digital data in this report, the user can examine the distribution of previously reported asbestos occurrences and their geological characteristics in the Central U.S. This report is part of an ongoing study by the U.S. Geological Survey to identify and map reported natural asbestos occurrences in the U.S., which began with U.S. Geological Survey Open-File Report 2005-1189 (http://pubs.usgs.gov/of/2005/1189/). These reports are intended to provide State and local government agencies and other stakeholders with geologic information on natural occurrences of asbestos in the U.S.

Geologic history of central Chryse Planitia and the Viking 1 landing site, Mars

NASA Technical Reports Server (NTRS)

Craddock, Robert A.; Crumpler, L. S.; Aubele, Jayne C.

1993-01-01

A 1:500,000 scale geologic mapping was undertaken to synthesize the broad-scale geology of Chryse Planitia with the local geology of the Viking 1 landing site. The geology of Mars Transverse Mercators (MTM's) 20047 and 25047 has been presented previously. As part of the goals for the Mars Geologic Mapping program, the rational and scientific objectives for a return mission to Chryse Planitia and the Viking 1 Lander have also been presented. However, in mapping central Chryse Planitia our principle objective was to determine the depositional and erosional history of the Chryse Planitia basin. These results are presented.

Eigenvalues and Eigenvectors: Embodied, Symbolic and Formal Thinking

ERIC Educational Resources Information Center

Thomas, Michael O. J.; Stewart, Sepideh

2011-01-01

Many beginning university students struggle with the new approaches to mathematics that they find in their courses due to a shift in presentation of mathematical ideas, from a procedural approach to concept definitions and deductive derivations, and ideas building upon each other in quick succession. This paper highlights this struggle by…

Some Results on Proper Eigenvalues and Eigenvectors with Applications to Scaling.

ERIC Educational Resources Information Center

McDonald, Roderick P.; And Others

1979-01-01

Problems in avoiding the singularity problem in analyzing matrices for optimal scaling are addressed. Conditions are given under which the stationary points and values of a ratio of quadratic forms in two singular matrices can be obtained by a series of simple matrix operations. (Author/JKS)

A Measure of Standing for Citation Networks within a Wider Environment.

ERIC Educational Resources Information Center

Doreian, Patrick

1994-01-01

Discusses the use of citation networks for constructing measures of the relative standing of journals in scientific journal-to-journal networks. Topics addressed include eigenvectors; measuring the standing of national scientific communities; and an empirical comparison of two measures of standing, one considering the environment and one without…

Simplicity and Typical Rank Results for Three-Way Arrays

ERIC Educational Resources Information Center

ten Berge, Jos M. F.

2011-01-01

Matrices can be diagonalized by singular vectors or, when they are symmetric, by eigenvectors. Pairs of square matrices often admit simultaneous diagonalization, and always admit block wise simultaneous diagonalization. Generalizing these possibilities to more than two (non-square) matrices leads to methods of simplifying three-way arrays by…

An Application of Sylvester's Rank Inequality

ERIC Educational Resources Information Center

Kung, Sidney H.

2011-01-01

Using two well known criteria for the diagonalizability of a square matrix plus an extended form of Sylvester's Rank Inequality, the author presents a new condition for the diagonalization of a real matrix from which one can obtain the eigenvectors by simply multiplying some associated matrices without solving a linear system of simultaneous…

Obtaining eigensolutions for multiple frequency ranges in a single NASTRAN execution

NASA Technical Reports Server (NTRS)

Pamidi, P. R.; Brown, W. K.

1990-01-01

A novel and general procedure for obtaining eigenvalues and eigenvectors for multiple frequency ranges in a single NASTRAN execution is presented. The scheme is applicable to normal modes analyzes employing the FEER and Inverse Power methods of eigenvalue extraction. The procedure is illustrated by examples.

Subsurface Mapping: A Question of Position and Interpretation

ERIC Educational Resources Information Center

Kellie, Andrew C.

2009-01-01

This paper discusses the character and challenges inherent in the graphical portrayal of features in subsurface mapping. Subsurface structures are, by their nature, hidden and must be mapped based on drilling and/or geophysical data. Efficient use of graphical techniques is central to effectively communicating the results of expensive exploration…

A climatology of late-spring freezes in the northeastern United States.

Treesearch

Brian E. Potter; Thomas W. Cate

1999-01-01

Presents maps of late-spring freeze characteristics for the northeastern and north central United States based on heat-sum thresholds and historic climate data. Discusses patterns seen in the maps. Provides examples and ways these maps could be used by resource managers and research scientists.

World Family Map Project. Prototype Report

ERIC Educational Resources Information Center

Wilcox, W. Bradford; Lippman, Laura; Whitney, Camille

2009-01-01

In 2010, the "World Family Map Project" seeks to launch a research initiative that will track central indicators of family strength around the globe. The "World Family Map Project" (WFMP) would partner with Child Trends, a nonpartisan research organization in Washington, D.C., the Institute of Marriage and Family Canada, and…

Geologic Map and Map Database of Eastern Sonoma and Western Napa Counties, California

USGS Publications Warehouse

Graymer, R.W.; Brabb, E.E.; Jones, D.L.; Barnes, J.; Nicholson, R.S.; Stamski, R.E.

2007-01-01

Introduction This report contains a new 1:100,000-scale geologic map, derived from a set of geologic map databases (Arc-Info coverages) containing information at 1:62,500-scale resolution, and a new description of the geologic map units and structural relations in the map area. Prepared as part of the San Francisco Bay Region Mapping Project, the study area includes the north-central part of the San Francisco Bay region, and forms the final piece of the effort to generate new, digital geologic maps and map databases for an area which includes Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Santa Cruz, Solano, and Sonoma Counties. Geologic mapping in Lake County in the north-central part of the map extent was not within the scope of the Project. The map and map database integrates both previously published reports and new geologic mapping and field checking by the authors (see Sources of Data index map on the map sheet or the Arc-Info coverage eswn-so and the textfile eswn-so.txt). This report contains new ideas about the geologic structures in the map area, including the active San Andreas Fault system, as well as the geologic units and their relations. Together, the map (or map database) and the unit descriptions in this report describe the composition, distribution, and orientation of geologic materials and structures within the study area at regional scale. Regional geologic information is important for analysis of earthquake shaking, liquifaction susceptibility, landslide susceptibility, engineering materials properties, mineral resources and hazards, as well as groundwater resources and hazards. These data also assist in answering questions about the geologic history and development of the California Coast Ranges.

The changing of coastal landform at Chikou barrier island and lagoon coast, Tainan, Southwestern Taiwan

NASA Astrophysics Data System (ADS)

Jen, C.-H.; Chyi, S.-J.; Hsiao, L.-L.; Wu, M.-S.; Lei, H.-F.

2012-04-01

The coast of southwestern Taiwan is mainly made of barriers and lagoons, which are prone to erosional and depositional processes. By using a serial maps, historical survey data, and RTK-GPS survey data, the changes of coast landforms are depicted. The maps being used in this study include (1) 1904 map(1:50000 scale), (2) 1920 map (1:50000 scale), (3) 1921 map (1:25000 scale), (4) 1924 map (1:25000 scale), (5) 1956 map (1:25000 scale), (6) 1975 map with ortho-rectified image (1:5000 scale), (7) 1983 map with ortho-rectified image (1:5000 scale), (8) 1989 map with ortho-rectified image (1:5000 scale), (9) 1992 map with ortho-rectified image (1:5000 scale), (10) 2001 map with ortho-rectified image (1:5000 scale). All maps are scanned and georeferenced to build a GIS archive for digitizing and further analysis. The results show that this coast was made of continuous sand barriers and lagoons. While lagoons were gradually shrinking, the sand barriers had remained stable from 1904 to 1924. After that, lagoons substantially deposited in the southern part and sand barriers became landward. In 1975 map, lagoons vanished and replaced with a tidal flat and tidal creeks. The following maps show that lagoons start to form again and sand barriers moving landward continuously. It is a significant sign of serious erosion in the coast. The RTK-GPS survey data in recent years show more detail of coast erosion and landform changes. The post-typhoon investigation results show that the seaward side of barrier island is eroded largely, especially for the two segments of the central part of the barrier island. Some depositions were found on the top of northern and central part of barrier dune, as well as washovers. In the southern barrier island, the depositions were carried to backshore and were obstructed in front of the bamboo piles and marine solid bags. The survey indicated the areas eroded by storm surge were gradually accumulating except for the beaches separate with plastic sheet piles and marine solid bags, especially the northern section-north, after the Typhoon Megi happened two month. In late February of 2011, there are some deposition on the top of primary dune, backdune and tidal flat. But the parts of seaward beach which wave can reach are continuously eroded, especially the central segment of the barrier island is mostly vulnerable. In particular, the latter part of southern beach was accumulated, concerning with alongshore current transport. In the late winter monsoon season, elevation changes are smaller than in the medium, corresponding with the wave condition. The latter part of south section begin to be eroded, the sediments may be taken away by the southward current. Area A, located the central of barrier island, attacked by wave continuously, elevation of dune decrease constantly, and then overwashed frequently. Keywords: sand barrier and lagoon coast, archive map analysis, RTK-GPS survey, overwash

Seismic hazard map of North and Central America and the Caribbean

USGS Publications Warehouse

Shedlock, K.M.

1999-01-01

Minimization of the loss of life, property damage, and social and economic disruption due to earthquakes depends on reliable estimates of seismic hazard. National, state, and local government, decision makers, engineers, planners, emergency response organizations, builders, universities, and the general public require seismic hazard estimates for land use planning, improved building design and construction (including adoption of building construction codes), emergency response preparedness plans, economic forecasts, housing and employment decisions, and many more types of risk mitigation. The seismic hazard map of North and Central America and the Caribbean is the concatenation of various national and regional maps, involving a suite of approaches. The combined maps and documentation provide a useful regional seismic hazard framework and serve as a resource for any national or regional agency for further detailed studies applicable to their needs. This seismic hazard map depicts Peak Ground Acceleration (PGA) with a 10% chance of exceedance in 50 years. PGA, a short-period ground motion parameter that is proportional to force, is the most commonly mapped ground motion parameter because current building codes that include seismic provisions specify the horizontal force a building should be able to withstand during an earthquake. This seismic hazard map of North and Central America and the Caribbean depicts the likely level of short-period ground motion from earthquakes in a fifty-year window. Short-period ground motions effect short-period structures (e.g., one-to-two story buildings). The highest seismic hazard values in the region generally occur in areas that have been, or are likely to be, the sites of the largest plate boundary earthquakes.

Assessment of groundwater vulnerability in the coastal region of Oman using DRASTIC index method in GIS environment.

PubMed

Jamrah, Ahmad; Al-Futaisi, Ahmed; Rajmohan, Natarajan; Al-Yaroubi, Saif

2008-12-01

A study was carried out to develop a vulnerability map for Barka region in the North Batina of Oman using DRASTIC vulnerability index method in GIS environment. DRASTIC layers were created using data from published reports and the seven DRASTIC layers were processed by the ArcGIS geographic information system. Finally, DRASTIC maps were created for 1995 and 2004 to understand the long-term changes in the vulnerability index. DRASTIC vulnerability maps were evaluated using groundwater quality data such as chemical and biological parameters. DRASTIC vulnerability maps of 1995 and 2004 indicate that the northern part of Barka is more vulnerable to pollution than southern part and the central part of Barka also shows high relative vulnerability which is mostly related to the high conductivity values. Moreover, the changes in water level due to high abstraction rate of groundwater reflect in the vulnerability maps and low vulnerability area is increased in the southern part during 2004 compared to 1995. Moreover, regional distribution maps of nitrate, chloride and total and fecal coliforms are well correlated with DRASTIC vulnerability maps. In contrast to this, even though DRASTIC method predicted the central part of the study region is highly vulnerable, both chemical and biological parameters show lower concentrations in this region compared to coastal belt, which is mainly due to agricultural and urban development. In Barka, urban development and agricultural activities are very high in coastal region compared to southern and central part of the study area. Hence, this study concluded that DRASTIC method is also applicable in coastal region having ubiquitous contamination sources.

Performance of USGS one-year earthquake hazard map for natural and induced seismicity in the central and eastern United States

NASA Astrophysics Data System (ADS)

Brooks, E. M.; Stein, S.; Spencer, B. D.; Salditch, L.; Petersen, M. D.; McNamara, D. E.

2017-12-01

Seismicity in the central United States has dramatically increased since 2008 due to the injection of wastewater produced by oil and gas extraction. In response, the USGS created a one-year probabilistic hazard model and map for 2016 to describe the increased hazard posed to the central and eastern United States. Using the intensity of shaking reported to the "Did You Feel It?" system during 2016, we assess the performance of this model. Assessing the performance of earthquake hazard maps for natural and induced seismicity is conceptually similar but has practical differences. Maps that have return periods of hundreds or thousands of years— as commonly used for natural seismicity— can be assessed using historical intensity data that also span hundreds or thousands of years. Several different features stand out when assessing the USGS 2016 seismic hazard model for the central and eastern United States from induced and natural earthquakes. First, the model can be assessed as a forecast in one year, because event rates are sufficiently high to permit evaluation with one year of data. Second, because these models are projections from the previous year thus implicitly assuming that fluid injection rates remain the same, misfit may reflect changes in human activity. Our results suggest that the model was very successful by the metric implicit in probabilistic hazard seismic assessment: namely, that the fraction of sites at which the maximum shaking exceeded the mapped value is comparable to that expected. The model also did well by a misfit metric that compares the spatial patterns of predicted and maximum observed shaking. This was true for both the central and eastern United States as a whole, and for the region within it with the highest amount of seismicity, Oklahoma and its surrounding area. The model performed least well in northern Texas, over-stating hazard, presumably because lower oil and gas prices and regulatory action reduced the water injection volume relative to the previous year. These results imply that such hazard maps have the potential to be valuable tools for policy makers and regulators in managing the seismic risks associated with unconventional oil and gas production.

Meltwater channel scars and the extent of Mid-Pleistocene glaciation in central Pennsylvania

NASA Astrophysics Data System (ADS)

Marsh, Ben

2017-10-01

High-resolution digital topographic data permit morphological analyses of glacial processes in detail that was previously infeasible. High-level glaciofluvial erosional scars in central Pennsylvania, identified and delimited using LiDAR data, define the approximate ice depth during a pre-Wisconsin advance, > 770,000 BP, on a landscape unaffected by Wisconsin glaciation. Distinctive scars on the prows of anticlinal ridges at 175-350 m above the valley floor locate the levels of subice meltwater channels. A two-component planar GIS model of the ice surface is derived using these features and intersected with a digital model of contemporary topography to create a glacial limit map. The map is compared to published maps, demonstrating the limits of conventional sediment-based mapping. Additional distinctive meltwater features that were cut during deglaciation are modeled in a similar fashion.

Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming

USGS Publications Warehouse

Eppinger, Robert G.; Giles, Stuart A.; Klein, Terry L.

2015-01-01

The U.S. Geological Survey has completed a series of geologic, mineral resource, and environmental assessment studies in the Rocky Mountains of central Colorado, from Leadville eastward to the range front and from New Mexico to the Wyoming border. Regional stream-sediment geochemical maps, useful for assessing mineral resources and environmental effects of historical mining activities, were produced as part of the study. The data portrayed in this 56-parameter portfolio of landscape geochemical maps serve as a geochemical baseline for the region, indicate element abundances characteristic of various lithologic terranes, and identify gross anthropogenic effects of historical mining. However, although reanalyzed in this study by modern, sensitive methods, the majority of the stream-sediment samples were collected in the 1970s. Thus, metal concentrations portrayed in these maps represent stream-sediment geochemistry at the time of collection.

Mapping thermal maturity in the Chainman shale, near Eureka, Nevada, with Landsat Thematic Mapper images

USGS Publications Warehouse

Rowan, L.C.; Pawlewicz, M.J.; Jones, O.D.

1992-01-01

The purpose of this study was to determine if there is a correlation between measurements of organic matter (OM) maturity and laboratory measurements of visible and near-infrared spectral reflectance, and if Landsat Thematic Mapper (TM) images could be used to map maturity. The maturity of Mississippian Chainman Shale samples collected in east-central Nevada and west-central Utah was determined by using vitrinite reflectance and Rock-Eval pyrolysis. TM 4/TM 5 values correspond well to vitrinite reflectance and hydrogen index variations, and therefore this ratio was used to evaluate a TM image of the Eureka, Nevada, area for mapping thermal maturity differences in the Chainman Shale. -from Authors

Appendix A: Ecoprovinces of the Central North American Cordillera and adjacent plains

Treesearch

Dennis A. Demarchi

1994-01-01

The fundamental difference between the map presented here and other regional ecosystem classifications is that this map's ecological units are based on climatic processes rather than vegetation communities (map appears at the end of this appendix). Macroclimatic processes are the physical and thermodynamic interaction between climatic controls, or the relatively...

Map of surficial deposits and materials in the eastern and central United States (east of 102 degrees West longitude)

USGS Publications Warehouse

Fullerton, David S.; Bush, Charles A.; Pennell, Jean N.

2003-01-01

This data set contains surficial geologic units in the Eastern and Central United States, as well as a glacial limit line showing the position of maximum glacial advance during various geologic time periods. The geologic units represent surficial deposits and other surface materials that accumulated or formed during the past 2+ million years, such as soils, alluvium, and glacial deposits. These surface materials are referred to collectively by many geologists as regolith, the mantle of fragmented and generally unconsolidated material that overlies the bedrock foundation of a continent. This data set and the printed map produced from it, U.S. Geological Survey (USGS) Geologic Investigation Series I-2789, were based on 31 published maps in the USGS's Quaternary Geologic Atlas of the United States map series (USGS Miscellaneous Investigations Series I-1420). The data were compiled at 1:1,000,000 scale, to be viewed as a digital map at 1:2,000,000 nominal scale and to be printed as a conventional paper map at 1:2,500,000 scale.

Soil amplification maps for estimating earthquake ground motions in the Central US

USGS Publications Warehouse

Bauer, R.A.; Kiefer, J.; Hester, N.

2001-01-01

The State Geologists of the Central United States Earthquake Consortium (CUSEC) are developing maps to assist State and local emergency managers and community officials in evaluating the earthquake hazards for the CUSEC region. The state geological surveys have worked together to produce a series of maps that show seismic shaking potential for eleven 1 X 2 degree (scale 1:250 000 or 1 in. ??? 3.9 miles) quadrangles that cover the high-risk area of the New Madrid Seismic Zone in eight states. Shear wave velocity values for the surficial materials were gathered and used to classify the soils according to their potential to amplify earthquake ground motions. Geologic base maps of surficial materials or 3-D material maps, either existing or produced for this project, were used in conjunction with shear wave velocities to classify the soils for the upper 15-30 m. These maps are available in an electronic form suitable for inclusion in the federal emergency management agency's earthquake loss estimation program (HAZUS). ?? 2001 Elsevier Science B.V. All rights reserved.

Geologic map of the southern Funeral Mountains including nearby groundwater discharge sites in Death Valley National Park, California and Nevada

USGS Publications Warehouse

Fridrich, C.J.; Thompson, R.A.; Slate, J.L.; Berry, M.E.; Machette, M.N.

2012-01-01

This 1:50,000-scale geologic map covers the southern part of the Funeral Mountains, and adjoining parts of four structural basins—Furnace Creek, Amargosa Valley, Opera House, and central Death Valley—in California and Nevada. It extends over three full 7.5-minute quadrangles, and parts of eleven others—an area of about 1,000 square kilometers (km2). The boundaries of this map were drawn to include all of the known proximal hydrogeologic features that may affect the flow of groundwater that discharges from springs of the Furnace Creek basin, in the west-central part of the map. These springs provide the main potable water supply for Death Valley National Park. Major hydrogeologic features shown on this map include: (1) springs of the Furnace Creek basin, (2) a large Pleistocene groundwater discharge mound in the northeastern part of the map, (3) the exposed extent of limestones and dolomites that constitute the Paleozoic carbonate aquifer, and (4) the exposed extent of the alluvial conglomerates that constitute the Funeral Formation aquifer.

Geologic map of the Basque-Cantabrian Basin and a new tectonic interpretation of the Basque Arc

NASA Astrophysics Data System (ADS)

Ábalos, B.

2016-11-01

A new printable 1/200.000 bedrock geological map of the onshore Basque-Cantabrian Basin is presented, aimed to contribute to future geologic developments in the central segment of the Pyrenean-Cantabrian Alpine orogenic system. It is accompanied in separate appendixes by a historic report on the precedent geological maps and by a compilation above 350 bibliographic citations of maps and academic reports (usually overlooked or ignored) that are central to this contribution. Structural scrutiny of the map permits to propose a new tectonic interpretation of the Basque Arc, implementing previously published partial reconstructions. It is presented as a printable 1/400.000 tectonic map. The Basque Arc consists of various thrust slices that can expose at the surface basement rocks (Palaeozoic to Lower Triassic) and their sedimentary cover (uppermost Triassic to Tertiary), from which they are detached by intervening (Upper Triassic) evaporites and associated rocks. The slice-bounding thrusts are in most cases reactivated normal faults active during Meso-Cenozoic sedimentation that can be readily related to basement discontinuities generated during the Hercynian orogeny.

Surficial Geologic Map of the Ashby-Lowell-Sterling-Billerica 11-Quadrangle Area in Northeast-Central Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.

2007-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of eleven 7.5-minute quadrangles (total 505 mi2) in northeast-central Massachusetts. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock, and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), a regional map at 1:50,000 scale (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Automating the selection of standard parallels for conic map projections

NASA Astrophysics Data System (ADS)

Šavriǒ, Bojan; Jenny, Bernhard

2016-05-01

Conic map projections are appropriate for mapping regions at medium and large scales with east-west extents at intermediate latitudes. Conic projections are appropriate for these cases because they show the mapped area with less distortion than other projections. In order to minimize the distortion of the mapped area, the two standard parallels of conic projections need to be selected carefully. Rules of thumb exist for placing the standard parallels based on the width-to-height ratio of the map. These rules of thumb are simple to apply, but do not result in maps with minimum distortion. There also exist more sophisticated methods that determine standard parallels such that distortion in the mapped area is minimized. These methods are computationally expensive and cannot be used for real-time web mapping and GIS applications where the projection is adjusted automatically to the displayed area. This article presents a polynomial model that quickly provides the standard parallels for the three most common conic map projections: the Albers equal-area, the Lambert conformal, and the equidistant conic projection. The model defines the standard parallels with polynomial expressions based on the spatial extent of the mapped area. The spatial extent is defined by the length of the mapped central meridian segment, the central latitude of the displayed area, and the width-to-height ratio of the map. The polynomial model was derived from 3825 maps-each with a different spatial extent and computationally determined standard parallels that minimize the mean scale distortion index. The resulting model is computationally simple and can be used for the automatic selection of the standard parallels of conic map projections in GIS software and web mapping applications.

Preliminary evaluation of the 15 October 1972 ERTS-1 imagery of east central Ohio (scene 1034-15415)

NASA Technical Reports Server (NTRS)

Pettyjohn, W. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Results of a general, physical interpretation of ERTS-1 imagery of east central Ohio are presented. Special emphasis is placed upon geologic features, such as linear features and hydrologic features. Man-made features are included as a matter of interest and image location. The interpretation is compared to available maps of the area and from this an assessment that ERTS-1 is potentially useful for updating and producing geological maps.

Commercial Agriculture and Modern Transport in Central America.

ERIC Educational Resources Information Center

Horst, Oscar H.

1981-01-01

Describes an exercise for use in college-level geography courses dealing with the tandem development of transport networks and commercial agriculture in Central America. Using six maps, the author shows the parallels between highway and railroad construction and commercial crops, (coffee, bananas, and cotton) in Central America between 1855-1975.…

Golden Matrix Families

ERIC Educational Resources Information Center

Fontaine, Anne; Hurley, Susan

2011-01-01

This student research project explores the properties of a family of matrices of zeros and ones that arises from the study of the diagonal lengths in a regular polygon. There is one family for each n greater than 2. A series of exercises guides the student to discover the eigenvalues and eigenvectors of the matrices, which leads in turn to…

Multidimensional spectral load balancing

DOEpatents

Hendrickson, Bruce A.; Leland, Robert W.

1996-12-24

A method of and apparatus for graph partitioning involving the use of a plurality of eigenvectors of the Laplacian matrix of the graph of the problem for which load balancing is desired. The invention is particularly useful for optimizing parallel computer processing of a problem and for minimizing total pathway lengths of integrated circuits in the design stage.

On Using the Average Intercorrelation Among Predictor Variables and Eigenvector Orientation to Choose a Regression Solution.

ERIC Educational Resources Information Center

Mugrage, Beverly; And Others

Three ridge regression solutions are compared with ordinary least squares regression and with principal components regression using all components. Ridge regression, particularly the Lawless-Wang solution, out-performed ordinary least squares regression and the principal components solution on the criteria of stability of coefficient and closeness…

An Application of the Vandermonde Determinant

ERIC Educational Resources Information Center

Xu, Junqin; Zhao, Likuan

2006-01-01

Eigenvalue is an important concept in Linear Algebra. It is well known that the eigenvectors corresponding to different eigenvalues of a square matrix are linear independent. In most of the existing textbooks, this result is proven using mathematical induction. In this note, a new proof using Vandermonde determinant is given. It is shown that this…

Statistics of pressure fluctuations in decaying isotropic turbulence.

PubMed

Kalelkar, Chirag

2006-04-01

We present results from a systematic direct-numerical simulation study of pressure fluctuations in an unforced, incompressible, homogeneous, and isotropic three-dimensional turbulent fluid. At cascade completion, isosurfaces of low pressure are found to be organized as slender filaments, whereas the predominant isostructures appear sheetlike. We exhibit several results, including plots of probability distributions of the spatial pressure difference, the pressure-gradient norm, and the eigenvalues of the pressure-Hessian tensor. Plots of the temporal evolution of the mean pressure-gradient norm, and the mean eigenvalues of the pressure-Hessian tensor are also exhibited. We find the statistically preferred orientations between the eigenvectors of the pressure-Hessian tensor, the pressure gradient, the eigenvectors of the strain-rate tensor, the vorticity, and the velocity. Statistical properties of the nonlocal part of the pressure-Hessian tensor are also exhibited. We present numerical tests (in the viscous case) of some conjectures of Ohkitani [Phys. Fluids A 5, 2570 (1993)] and Ohkitani and Kishiba [Phys. Fluids 7, 411 (1995)] concerning the pressure-Hessian and the strain-rate tensors, for the unforced, incompressible, three-dimensional Euler equations.

The general linear inverse problem - Implication of surface waves and free oscillations for earth structure.

NASA Technical Reports Server (NTRS)

Wiggins, R. A.

1972-01-01

The discrete general linear inverse problem reduces to a set of m equations in n unknowns. There is generally no unique solution, but we can find k linear combinations of parameters for which restraints are determined. The parameter combinations are given by the eigenvectors of the coefficient matrix. The number k is determined by the ratio of the standard deviations of the observations to the allowable standard deviations in the resulting solution. Various linear combinations of the eigenvectors can be used to determine parameter resolution and information distribution among the observations. Thus we can determine where information comes from among the observations and exactly how it constraints the set of possible models. The application of such analyses to surface-wave and free-oscillation observations indicates that (1) phase, group, and amplitude observations for any particular mode provide basically the same type of information about the model; (2) observations of overtones can enhance the resolution considerably; and (3) the degree of resolution has generally been overestimated for many model determinations made from surface waves.

Cross-correlation matrix analysis of Chinese and American bank stocks in subprime crisis

NASA Astrophysics Data System (ADS)

Zhu, Shi-Zhao; Li, Xin-Li; Nie, Sen; Zhang, Wen-Qing; Yu, Gao-Feng; Han, Xiao-Pu; Wang, Bing-Hong

2015-05-01

In order to study the universality of the interactions among different markets, we analyze the cross-correlation matrix of the price of the Chinese and American bank stocks. We then find that the stock prices of the emerging market are more correlated than that of the developed market. Considering that the values of the components for the eigenvector may be positive or negative, we analyze the differences between two markets in combination with the endogenous and exogenous events which influence the financial markets. We find that the sparse pattern of components of eigenvectors out of the threshold value has no change in American bank stocks before and after the subprime crisis. However, it changes from sparse to dense for Chinese bank stocks. By using the threshold value to exclude the external factors, we simulate the interactions in financial markets. Project supported by the National Natural Science Foundation of China (Grant Nos. 11275186, 91024026, and FOM2014OF001) and the University of Shanghai for Science and Technology (USST) of Humanities and Social Sciences, China (Grant Nos. USST13XSZ05 and 11YJA790231).

Systemic risk and spatiotemporal dynamics of the US housing market

PubMed Central

Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2014-01-01

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975–2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles. PMID:24413626

CAVE3: A general transient heat transfer computer code utilizing eigenvectors and eigenvalues

NASA Technical Reports Server (NTRS)

Palmieri, J. V.; Rathjen, K. A.

1978-01-01

The method of solution is a hybrid analytical numerical technique which utilizes eigenvalues and eigenvectors. The method is inherently stable, permitting large time steps even with the best of conductors with the finest of mesh sizes which can provide a factor of five reduction in machine time compared to conventional explicit finite difference methods when structures with small time constants are analyzed over long time periods. This code will find utility in analyzing hypersonic missile and aircraft structures which fall naturally into this class. The code is a completely general one in that problems involving any geometry, boundary conditions and materials can be analyzed. This is made possible by requiring the user to establish the thermal network conductances between nodes. Dynamic storage allocation is used to minimize core storage requirements. This report is primarily a user's manual for CAVE3 code. Input and output formats are presented and explained. Sample problems are included which illustrate the usage of the code as well as establish the validity and accuracy of the method.

Visualization of 3-D tensor fields

NASA Technical Reports Server (NTRS)

Hesselink, L.

1996-01-01

Second-order tensor fields have applications in many different areas of physics, such as general relativity and fluid mechanics. The wealth of multivariate information in tensor fields makes them more complex and abstract than scalar and vector fields. Visualization is a good technique for scientists to gain new insights from them. Visualizing a 3-D continuous tensor field is equivalent to simultaneously visualizing its three eigenvector fields. In the past, research has been conducted in the area of two-dimensional tensor fields. It was shown that degenerate points, defined as points where eigenvalues are equal to each other, are the basic singularities underlying the topology of tensor fields. Moreover, it was shown that eigenvectors never cross each other except at degenerate points. Since we live in a three-dimensional world, it is important for us to understand the underlying physics of this world. In this report, we describe a new method for locating degenerate points along with the conditions for classifying them in three-dimensional space. Finally, we discuss some topological features of three-dimensional tensor fields, and interpret topological patterns in terms of physical properties.

Moving Sound Source Localization Based on Sequential Subspace Estimation in Actual Room Environments

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Suyama, Kenji

This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

Distance and environmental difference in alpine plant communities

USGS Publications Warehouse

Malanson, George P.; Zimmerman, Dale L.; Fagre, Daniel B.

2017-01-01

Differences in plant communities are a response to the abiotic environment, species interactions, and dispersal. The role of geographic distance relative to the abiotic environment is explored for alpine tundra vegetation from 319 plots of four regions along the Rocky Mountain cordillera in the USA. The site by species data were ordinated using nonmetric multidimensional scaling to produce dependent variables for use in best-subsets regression. For independent variables, observations of local topography and microtopography were used as environmental indicators. Two methods of including distance in studies of vegetation and environment are used and contrasted. The relative importance of geographic distance in accounting for the pattern of alpine tundra similarity indicates that location is a factor in plant community composition. Mantel tests provide direct correlations between difference and distance but have known weaknesses. Moran spatial eigenvectors used in regression based approaches have greater geographic specificity, but require another step, ordination, in creating a vegetation variable. While the spatial eigenvectors are generally preferable, where species–environment relations are weak, as seems to be the case for the alpine sites studied here, the fewer abstractions of the Mantel test may be useful.

Beamforming using subspace estimation from a diagonally averaged sample covariance.

PubMed

Quijano, Jorge E; Zurk, Lisa M

2017-08-01

The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.

Fine-scale features in the far-field of a turbulent jet

NASA Astrophysics Data System (ADS)

Buxton, Oliver; Ganapathisubramani, Bharathram

2008-11-01

The structure of a fully turbulent axisymmetric jet, at Reynolds number based on jet exit conditions of 5000, is investigated with cinematographic (1 kHz) stereoscopic PIV in a plane normal to the jet axis. Taylor's hypothesis is employed to calculate all three velocity gradients in the axial direction. The technique's resolution allows all terms of the velocity gradient tensor, hence strain rate tensor and kinetic energy dissipation, to be computed at each point within the plane. The data reveals that the vorticity field is dominated by high enstrophy tube-like structures. Conversely, the dissipation field appears to consist of sheet-like structures. Several criteria for isolating these strongly swirling vortical structures from the background turbulence were employed. One such technique involves isolating points in which the velocity gradient tensor has a real and a pair of complex conjugate eigenvectors. Once identified, the alignment of the various structures with relation to the vorticity vector and the real velocity gradient tensor eigenvector is investigated. The effect of the strain field on the geometry of the structures is also examined.

Betatron motion with coupling of horizontal and vertical degrees of freedom

DOE PAGES

Lebedev, V. A.; Bogacz, S. A.

2010-10-21

Presently, there are two most frequently used parameterezations of linear x-y coupled motion used in the accelerator physics. They are the Edwards-Teng and Mais-Ripken parameterizations. The article is devoted to an analysis of close relationship between the two representations, thus adding a clarity to their physical meaning. It also discusses the relationship between the eigen-vectors, the beta-functions, second order moments and the bilinear form representing the particle ellipsoid in the 4D phase space. Then, it consideres a further development of Mais-Ripken parameteresation where the particle motion is descrabed by 10 parameters: four beta-functions, four alpha-functions and two betatron phase advances.more » In comparison with Edwards-Teng parameterization the chosen parametrization has an advantage that it works equally well for analysis of coupled betatron motion in circular accelerators and in transfer lines. In addition, considered relationship between second order moments, eigen-vectors and beta-functions can be useful in interpreting tracking results and experimental data. As an example, the developed formalizm is applied to the FNAL electron cooler and Derbenev’s vertex-to-plane adapter.« less

Betatron motion with coupling of horizontal and vertical degrees of freedom

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

Lebedev, V. A.; Bogacz, S. A.

Presently, there are two most frequently used parameterezations of linear x-y coupled motion used in the accelerator physics. They are the Edwards-Teng and Mais-Ripken parameterizations. The article is devoted to an analysis of close relationship between the two representations, thus adding a clarity to their physical meaning. It also discusses the relationship between the eigen-vectors, the beta-functions, second order moments and the bilinear form representing the particle ellipsoid in the 4D phase space. Then, it consideres a further development of Mais-Ripken parameteresation where the particle motion is descrabed by 10 parameters: four beta-functions, four alpha-functions and two betatron phase advances.more » In comparison with Edwards-Teng parameterization the chosen parametrization has an advantage that it works equally well for analysis of coupled betatron motion in circular accelerators and in transfer lines. In addition, considered relationship between second order moments, eigen-vectors and beta-functions can be useful in interpreting tracking results and experimental data. As an example, the developed formalizm is applied to the FNAL electron cooler and Derbenev’s vertex-to-plane adapter.« less

Betatron motion with coupling of horizontal and vertical degrees of freedom

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

Lebedev, V.A.; /Fermilab; Bogacz, S.A.

Presently, there are two most frequently used parameterizations of linear x-y coupled motion used in the accelerator physics. They are the Edwards-Teng and Mais-Ripken parameterizations. The article is devoted to an analysis of close relationship between the two representations, thus adding a clarity to their physical meaning. It also discusses the relationship between the eigen-vectors, the beta-functions, second order moments and the bilinear form representing the particle ellipsoid in the 4D phase space. Then, it consideres a further development of Mais-Ripken parameteresation where the particle motion is described by 10 parameters: four beta-functions, four alpha-functions and two betatron phase advances.more » In comparison with Edwards-Teng parameterization the chosen parametrization has an advantage that it works equally well for analysis of coupled betatron motion in circular accelerators and in transfer lines. Considered relationship between second order moments, eigen-vectors and beta-functions can be useful in interpreting tracking results and experimental data. As an example, the developed formalizm is applied to the FNAL electron cooler and Derbenev's vertex-to-plane adapter.« less

Atomistic modeling of the low-frequency mechanical modes and Raman spectra of icosahedral virus capsids

NASA Astrophysics Data System (ADS)

Dykeman, Eric C.; Sankey, Otto F.

2010-02-01

We describe a technique for calculating the low-frequency mechanical modes and frequencies of a large symmetric biological molecule where the eigenvectors of the Hessian matrix are determined with full atomic detail. The method, which follows order N methods used in electronic structure theory, determines the subset of lowest-frequency modes while using group theory to reduce the complexity of the problem. We apply the method to three icosahedral viruses of various T numbers and sizes; the human viruses polio and hepatitis B, and the cowpea chlorotic mottle virus, a plant virus. From the normal-mode eigenvectors, we use a bond polarizability model to predict a low-frequency Raman scattering profile for the viruses. The full atomic detail in the displacement patterns combined with an empirical potential-energy model allows a comparison of the fully atomic normal modes with elastic network models and normal-mode analysis with only dihedral degrees of freedom. We find that coarse-graining normal-mode analysis (particularly the elastic network model) can predict the displacement patterns for the first few (˜10) low-frequency modes that are global and cooperative.

Extending the eigCG algorithm to nonsymmetric Lanczos for linear systems with multiple right-hand sides

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

Abdel-Rehim, A M; Stathopoulos, Andreas; Orginos, Kostas

2014-08-01

The technique that was used to build the EigCG algorithm for sparse symmetric linear systems is extended to the nonsymmetric case using the BiCG algorithm. We show that, similarly to the symmetric case, we can build an algorithm that is capable of computing a few smallest magnitude eigenvalues and their corresponding left and right eigenvectors of a nonsymmetric matrix using only a small window of the BiCG residuals while simultaneously solving a linear system with that matrix. For a system with multiple right-hand sides, we give an algorithm that computes incrementally more eigenvalues while solving the first few systems andmore » then uses the computed eigenvectors to deflate BiCGStab for the remaining systems. Our experiments on various test problems, including Lattice QCD, show the remarkable ability of EigBiCG to compute spectral approximations with accuracy comparable to that of the unrestarted, nonsymmetric Lanczos. Furthermore, our incremental EigBiCG followed by appropriately restarted and deflated BiCGStab provides a competitive method for systems with multiple right-hand sides.« less

Random matrix theory and fund of funds portfolio optimisation

NASA Astrophysics Data System (ADS)

Conlon, T.; Ruskin, H. J.; Crane, M.

2007-08-01

The proprietary nature of Hedge Fund investing means that it is common practise for managers to release minimal information about their returns. The construction of a fund of hedge funds portfolio requires a correlation matrix which often has to be estimated using a relatively small sample of monthly returns data which induces noise. In this paper, random matrix theory (RMT) is applied to a cross-correlation matrix C, constructed using hedge fund returns data. The analysis reveals a number of eigenvalues that deviate from the spectrum suggested by RMT. The components of the deviating eigenvectors are found to correspond to distinct groups of strategies that are applied by hedge fund managers. The inverse participation ratio is used to quantify the number of components that participate in each eigenvector. Finally, the correlation matrix is cleaned by separating the noisy part from the non-noisy part of C. This technique is found to greatly reduce the difference between the predicted and realised risk of a portfolio, leading to an improved risk profile for a fund of hedge funds.

Map and digital database of sedimentary basins and indications of petroleum in the Central Alaska Province

USGS Publications Warehouse

Troutman, Sandra M.; Stanley, Richard G.

2003-01-01

This database and accompanying text depict historical and modern reported occurrences of petroleum both in wells and at the surface within the boundaries of the Central Alaska Province. These data were compiled from previously published and unpublished sources and were prepared for use in the 2002 U.S. Geological Survey petroleum assessment of Central Alaska, Yukon Flats region. Indications of petroleum are described as oil or gas shows in wells, oil or gas seeps, or outcrops of oil shale or oil-bearing rock and include confirmed and unconfirmed reports. The scale of the source map limits the spatial resolution (scale) of the database to 1:2,500,000 or smaller.

Surficial Geologic Map of the Tanacross B-4 Quadrangle, East-Central Alaska

USGS Publications Warehouse

Carrara, Paul E.

2006-01-01

The Tanacross B-4 1:63,360-scale quadrangle, through which the Alaska Highway runs, is in east-central Alaska about 100 mi west of the Yukon border. The surficial geologic mapping in the quadrangle is in support of the 'Geologic Mapping in support of land, resources, and hazards issues in Alaska' Project of the USGS National Cooperative Geologic Mapping Program. The Tanacross B-4 quadrangle contains parts of two physiographic provinces, the Yukon-Tanana Upland and the Northway-Tanana Lowland. The gently rolling hills of the Yukon-Tanana Upland, in the northern and eastern map area, rise to about 3,100 ft. The Northway-Tanana Lowland, in the western and southern map area, contains the westerly flowing Tanana River. Elevations along the floor of the lowland generally range between 1,540 and 1,700 ft. The dominant feature within the map is the Tok fan, which occupies about 20 percent of the map area. This large, nearly featureless fan contains a high percentage of volcanic clasts derived from outside the present-day drainage of the Tok River. The map provides interpretations of the Quaternary surficial deposits and associated geologic hazards in this area of the upper Tanana valley. Because the map area is dominated by various surficial deposits, the map depicts 13 different Quaternary surficial units consisting of man-made, alluvial, colluvial, organic, lacustrine, and eolian deposits. Deposits shown on this map are generally greater than 1 m thick. The map is accompanied by a text containing unit descriptions incorporating information pertaining to material type, location, associated hazards, resource use (if any), and thickness.

The Ebstorf Map: tradition and contents of a medieval picture of the world

NASA Astrophysics Data System (ADS)

Pischke, G.

2014-07-01

The Ebstorf Map (Wilke, 2001; Kugler, 2007; Wolf, 2004, 2006, 2007, 2009a, b), the largest medieval map of the world whose original has been lost, is not only a geographical map. In the Middle Ages, a map contained mystic, historical and religious motifs. Of central importance is Jesus Christ, who, in the Ebstorf Map, is part of the earth. The Ebstorf Map contains the knowledge of the time of its creation; it can be used for example as an atlas, as a chronicle of the world, or as an illustrated Bible.

The auditory cortex hosts network nodes influential for emotion processing: An fMRI study on music-evoked fear and joy

PubMed Central

Skouras, Stavros; Lohmann, Gabriele

2018-01-01

Sound is a potent elicitor of emotions. Auditory core, belt and parabelt regions have anatomical connections to a large array of limbic and paralimbic structures which are involved in the generation of affective activity. However, little is known about the functional role of auditory cortical regions in emotion processing. Using functional magnetic resonance imaging and music stimuli that evoke joy or fear, our study reveals that anterior and posterior regions of auditory association cortex have emotion-characteristic functional connectivity with limbic/paralimbic (insula, cingulate cortex, and striatum), somatosensory, visual, motor-related, and attentional structures. We found that these regions have remarkably high emotion-characteristic eigenvector centrality, revealing that they have influential positions within emotion-processing brain networks with “small-world” properties. By contrast, primary auditory fields showed surprisingly strong emotion-characteristic functional connectivity with intra-auditory regions. Our findings demonstrate that the auditory cortex hosts regions that are influential within networks underlying the affective processing of auditory information. We anticipate our results to incite research specifying the role of the auditory cortex—and sensory systems in general—in emotion processing, beyond the traditional view that sensory cortices have merely perceptual functions. PMID:29385142

Quantifying uncertainty in climate change science through empirical information theory.

PubMed

Majda, Andrew J; Gershgorin, Boris

2010-08-24

Quantifying the uncertainty for the present climate and the predictions of climate change in the suite of imperfect Atmosphere Ocean Science (AOS) computer models is a central issue in climate change science. Here, a systematic approach to these issues with firm mathematical underpinning is developed through empirical information theory. An information metric to quantify AOS model errors in the climate is proposed here which incorporates both coarse-grained mean model errors as well as covariance ratios in a transformation invariant fashion. The subtle behavior of model errors with this information metric is quantified in an instructive statistically exactly solvable test model with direct relevance to climate change science including the prototype behavior of tracer gases such as CO(2). Formulas for identifying the most sensitive climate change directions using statistics of the present climate or an AOS model approximation are developed here; these formulas just involve finding the eigenvector associated with the largest eigenvalue of a quadratic form computed through suitable unperturbed climate statistics. These climate change concepts are illustrated on a statistically exactly solvable one-dimensional stochastic model with relevance for low frequency variability of the atmosphere. Viable algorithms for implementation of these concepts are discussed throughout the paper.

Uniform function constants of motion and their first-order perturbation

NASA Astrophysics Data System (ADS)

Prato, Domingo; Hamity, Victor H.

2005-05-01

The main purpose of this work is to present some uniform function constants of motion rather than the well-known quantities arising from spacetime symmetries. These constants are usually associated with the intrinsic characteristics of the trajectories of a particle in a central potential field. We treat two cases. The first is the Lenz vector which sometimes is found in the literature [1, 2]; the other is associated with the isotropic harmonic oscillator, of relative importance in some simple models of the classical molecular interaction. The first example is applied to describe the perturbation of the trajectories in the Rutherford scattering and the precession of the Keplerian orbit of a planet. In the other case the conserved quantity is a symmetric tensor. We find the eigenvectors and eigenvalues of that tensor while at the same time we obtain the solution to the problem of calculating the rotation rate of the orbits in first order of a perturbation parameter in the potential energy, by performing a simple coordinate transformation in the Cartesian plane. We think that the present work addresses many aspects of mechanics with a didactical interest in other physics or mathematics courses.

Individual and Network Factors Associated With Prevalent Hepatitis C Infection Among Rural Appalachian Injection Drug Users

PubMed Central

Lofwall, Michelle R.; Frost, Simon D. W.; Oser, Carrie B.; Leukefeld, Carl G.; Crosby, Richard A.

2013-01-01

Objectives. We determined the factors associated with hepatitis C (HCV) infection among rural Appalachian drug users. Methods. This study included 394 injection drug users (IDUs) participating in a study of social networks and infectious disease risk in Appalachian Kentucky. Trained staff conducted HCV, HIV, and herpes simplex-2 virus (HSV-2) testing, and an interviewer-administered questionnaire measured self-reported risk behaviors and sociometric network characteristics. Results. The prevalence of HCV infection was 54.6% among rural IDUs. Lifetime factors independently associated with HCV infection included HSV-2, injecting for 5 or more years, posttraumatic stress disorder, injection of cocaine, and injection of prescription opioids. Recent (past-6-month) correlates of HCV infection included sharing of syringes (adjusted odds ratio = 2.24; 95% confidence interval = 1.32, 3.82) and greater levels of eigenvector centrality in the drug network. Conclusions. One factor emerged that was potentially unique to rural IDUs: the association between injection of prescription opioids and HCV infection. Therefore, preventing transition to injection, especially among prescription opioid users, may curb transmission, as will increased access to opioid maintenance treatment, novel treatments for cocaine dependence, and syringe exchange. PMID:23153148

A picture is worth a thousand words: maps of HIV indicators to inform research, programs, and policy from NA-ACCORD and CCASAnet clinical cohorts.

PubMed

Althoff, Keri N; Rebeiro, Peter F; Hanna, David B; Padgett, Denis; Horberg, Michael A; Grinsztejn, Beatriz; Abraham, Alison G; Hogg, Robert; Gill, M John; Wolff, Marcelo J; Mayor, Angel; Rachlis, Anita; Williams, Carolyn; Sterling, Timothy R; Kitahata, Mari M; Buchacz, Kate; Thorne, Jennifer E; Cesar, Carina; Cordero, Fernando M; Rourke, Sean B; Sierra-Madero, Juan; Pape, Jean W; Cahn, Pedro; McGowan, Catherine

2016-01-01

Maps are powerful tools for visualization of differences in health indicators by geographical region, but multi-country maps of HIV indicators do not exist, perhaps due to lack of consistent data across countries. Our objective was to create maps of four HIV indicators in North, Central, and South American countries. Using data from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) and the Caribbean, Central, and South America network for HIV epidemiology (CCASAnet), we mapped median CD4 at presentation for HIV clinical care, proportion retained in HIV primary care, proportion prescribed antiretroviral therapy (ART), and the proportion with suppressed plasma HIV viral load (VL) from 2010 to 2012 for North, Central, and South America. The 15 Canadian and US clinical cohorts and 7 clinical cohorts in Argentina, Brazil, Chile, Haiti, Honduras, Mexico, and Peru represented approximately 2-7% of persons known to be living with HIV in these countries. Study populations were selected for each indicator: median CD4 at presentation for care was estimated among 14,811 adults; retention was estimated among 87,979 adults; ART use was estimated among 84,757 adults; and suppressed VL was estimated among 51,118 adults. Only three US states and the District of Columbia had a median CD4 at presentation >350 cells/mm(3). Haiti, Mexico, and several states had >85% retention in care; lower (50-74%) retention in care was observed in the US West, South, and Mid-Atlantic, and in Argentina, Brazil, and Peru. ART use was highest (90%) in Mexico. The percentages of patients with suppressed VL in the US South and Northeast were lower than in most of Central and South America. These maps provide visualization of gaps in the quality of HIV care and allow for comparison between and within countries as well as monitoring policy and programme goals within geographical boundaries.

A picture is worth a thousand words: maps of HIV indicators to inform research, programs, and policy from NA-ACCORD and CCASAnet clinical cohorts

PubMed Central

Althoff, Keri N; Rebeiro, Peter F; Hanna, David B; Padgett, Denis; Horberg, Michael A; Grinsztejn, Beatriz; Abraham, Alison G; Hogg, Robert; Gill, M John; Wolff, Marcelo J; Mayor, Angel; Rachlis, Anita; Williams, Carolyn; Sterling, Timothy R; Kitahata, Mari M; Buchacz, Kate; Thorne, Jennifer E; Cesar, Carina; Cordero, Fernando M; Rourke, Sean B; Sierra-Madero, Juan; Pape, Jean W; Cahn, Pedro; McGowan, Catherine

2016-01-01

Introduction Maps are powerful tools for visualization of differences in health indicators by geographical region, but multi-country maps of HIV indicators do not exist, perhaps due to lack of consistent data across countries. Our objective was to create maps of four HIV indicators in North, Central, and South American countries. Methods Using data from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) and the Caribbean, Central, and South America network for HIV epidemiology (CCASAnet), we mapped median CD4 at presentation for HIV clinical care, proportion retained in HIV primary care, proportion prescribed antiretroviral therapy (ART), and the proportion with suppressed plasma HIV viral load (VL) from 2010 to 2012 for North, Central, and South America. The 15 Canadian and US clinical cohorts and 7 clinical cohorts in Argentina, Brazil, Chile, Haiti, Honduras, Mexico, and Peru represented approximately 2–7% of persons known to be living with HIV in these countries. Results Study populations were selected for each indicator: median CD4 at presentation for care was estimated among 14,811 adults; retention was estimated among 87,979 adults; ART use was estimated among 84,757 adults; and suppressed VL was estimated among 51,118 adults. Only three US states and the District of Columbia had a median CD4 at presentation >350 cells/mm3. Haiti, Mexico, and several states had >85% retention in care; lower (50–74%) retention in care was observed in the US West, South, and Mid-Atlantic, and in Argentina, Brazil, and Peru. ART use was highest (90%) in Mexico. The percentages of patients with suppressed VL in the US South and Northeast were lower than in most of Central and South America. Conclusions These maps provide visualization of gaps in the quality of HIV care and allow for comparison between and within countries as well as monitoring policy and programme goals within geographical boundaries. PMID:27049052

The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing

PubMed Central

Chang, Po-Yen; Su, Ta-Shun; Shih, Chi-Tin; Lo, Chung-Chuan

2017-01-01

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of “atypical” neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the “typical” neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex. PMID:28443014

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Identification of cardiac rhythm features by mathematical analysis of vector fields.

PubMed

Fitzgerald, Tamara N; Brooks, Dana H; Triedman, John K

2005-01-01

Automated techniques for locating cardiac arrhythmia features are limited, and cardiologists generally rely on isochronal maps to infer patterns in the cardiac activation sequence during an ablation procedure. Velocity vector mapping has been proposed as an alternative method to study cardiac activation in both clinical and research environments. In addition to the visual cues that vector maps can provide, vector fields can be analyzed using mathematical operators such as the divergence and curl. In the current study, conduction features were extracted from velocity vector fields computed from cardiac mapping data. The divergence was used to locate ectopic foci and wavefront collisions, and the curl to identify central obstacles in reentrant circuits. Both operators were applied to simulated rhythms created from a two-dimensional cellular automaton model, to measured data from an in situ experimental canine model, and to complex three-dimensional human cardiac mapping data sets. Analysis of simulated vector fields indicated that the divergence is useful in identifying ectopic foci, with a relatively small number of vectors and with errors of up to 30 degrees in the angle measurements. The curl was useful for identifying central obstacles in reentrant circuits, and the number of velocity vectors needed increased as the rhythm became more complex. The divergence was able to accurately identify canine in situ pacing sites, areas of breakthrough activation, and wavefront collisions. In data from human arrhythmias, the divergence reliably estimated origins of electrical activity and wavefront collisions, but the curl was less reliable at locating central obstacles in reentrant circuits, possibly due to the retrospective nature of data collection. The results indicate that the curl and divergence operators applied to velocity vector maps have the potential to add valuable information in cardiac mapping and can be used to supplement human pattern recognition.

HapMap tagSNP transferability in multiple populations: general guidelines

PubMed Central

Xing, Jinchuan; Witherspoon, David J.; Watkins, W. Scott; Zhang, Yuhua; Tolpinrud, Whitney; Jorde, Lynn B.

2008-01-01

This PDF receipt will only be used as the basis for generating PubMed Central (PMC) documents. PMC documents will be made available for review after conversion (approx. 2–3 weeks time). Any corrections that need to be made will be done at that time. No materials will be released to PMC without the approval of an author. Only the PMC documents will appear on PubMed Central -- this PDF Receipt will not appear on PubMed Central. Linkage disequilibrium (LD) has received much recent attention because of its value in localizing disease-causing genes. Due to the extensive LD between neighboring loci in the human genome, it is believed that a subset of the single nucleotide polymorphisms in a region (tagSNPs) can be selected to capture most of the remaining SNP variants. In this study, we examined LD patterns and HapMap tagSNP transferability in more than 300 individuals. A South Indian and an African Mbuti Pygmy population sample were included to evaluate the performance of HapMap tagSNPs in geographically distinct and genetically isolated populations. Our results show that HapMap tagSNPs selected with r2 >= 0.8 can capture more than 85% of the SNPs in populations that are from the same continental group. Combined tagSNPs from HapMap CEU and CHB+JPT serve as the best reference for the Indian sample. The HapMap YRI are a sufficient reference for tagSNP selection in the Pygmy sample. In addition to our findings, we reviewed over 25 recent studies of tagSNP transferability and propose a general guideline for selecting tagSNPs from HapMap populations. PMID:18482828

Analysis of structural correlations in a model binary 3D liquid through the eigenvalues and eigenvectors of the atomic stress tensors.

PubMed

Levashov, V A

2016-03-07

It is possible to associate with every atom or molecule in a liquid its own atomic stress tensor. These atomic stress tensors can be used to describe liquids' structures and to investigate the connection between structural and dynamic properties. In particular, atomic stresses allow to address atomic scale correlations relevant to the Green-Kubo expression for viscosity. Previously correlations between the atomic stresses of different atoms were studied using the Cartesian representation of the stress tensors or the representation based on spherical harmonics. In this paper we address structural correlations in a 3D model binary liquid using the eigenvalues and eigenvectors of the atomic stress tensors. This approach allows to interpret correlations relevant to the Green-Kubo expression for viscosity in a simple geometric way. On decrease of temperature the changes in the relevant stress correlation function between different atoms are significantly more pronounced than the changes in the pair density function. We demonstrate that this behaviour originates from the orientational correlations between the eigenvectors of the atomic stress tensors. We also found correlations between the eigenvalues of the same atomic stress tensor. For the studied system, with purely repulsive interactions between the particles, the eigenvalues of every atomic stress tensor are positive and they can be ordered: λ1 ≥ λ2 ≥ λ3 ≥ 0. We found that, for the particles of a given type, the probability distributions of the ratios (λ2/λ1) and (λ3/λ2) are essentially identical to each other in the liquids state. We also found that λ2 tends to be equal to the geometric average of λ1 and λ3. In our view, correlations between the eigenvalues may represent "the Poisson ratio effect" at the atomic scale.

Effect of the interconnected network structure on the epidemic threshold.

PubMed

Wang, Huijuan; Li, Qian; D'Agostino, Gregorio; Havlin, Shlomo; Stanley, H Eugene; Van Mieghem, Piet

2013-08-01

Most real-world networks are not isolated. In order to function fully, they are interconnected with other networks, and this interconnection influences their dynamic processes. For example, when the spread of a disease involves two species, the dynamics of the spread within each species (the contact network) differs from that of the spread between the two species (the interconnected network). We model two generic interconnected networks using two adjacency matrices, A and B, in which A is a 2N×2N matrix that depicts the connectivity within each of two networks of size N, and B a 2N×2N matrix that depicts the interconnections between the two. Using an N-intertwined mean-field approximation, we determine that a critical susceptible-infected-susceptible (SIS) epidemic threshold in two interconnected networks is 1/λ(1)(A+αB), where the infection rate is β within each of the two individual networks and αβ in the interconnected links between the two networks and λ(1)(A+αB) is the largest eigenvalue of the matrix A+αB. In order to determine how the epidemic threshold is dependent upon the structure of interconnected networks, we analytically derive λ(1)(A+αB) using a perturbation approximation for small and large α, the lower and upper bound for any α as a function of the adjacency matrix of the two individual networks, and the interconnections between the two and their largest eigenvalues and eigenvectors. We verify these approximation and boundary values for λ(1)(A+αB) using numerical simulations, and determine how component network features affect λ(1)(A+αB). We note that, given two isolated networks G(1) and G(2) with principal eigenvectors x and y, respectively, λ(1)(A+αB) tends to be higher when nodes i and j with a higher eigenvector component product x(i)y(j) are interconnected. This finding suggests essential insights into ways of designing interconnected networks to be robust against epidemics.

A robust variant of block Jacobi-Davidson for extracting a large number of eigenpairs: Application to grid-based real-space density functional theory

NASA Astrophysics Data System (ADS)

Lee, M.; Leiter, K.; Eisner, C.; Breuer, A.; Wang, X.

2017-09-01

In this work, we investigate a block Jacobi-Davidson (J-D) variant suitable for sparse symmetric eigenproblems where a substantial number of extremal eigenvalues are desired (e.g., ground-state real-space quantum chemistry). Most J-D algorithm variations tend to slow down as the number of desired eigenpairs increases due to frequent orthogonalization against a growing list of solved eigenvectors. In our specification of block J-D, all of the steps of the algorithm are performed in clusters, including the linear solves, which allows us to greatly reduce computational effort with blocked matrix-vector multiplies. In addition, we move orthogonalization against locked eigenvectors and working eigenvectors outside of the inner loop but retain the single Ritz vector projection corresponding to the index of the correction vector. Furthermore, we minimize the computational effort by constraining the working subspace to the current vectors being updated and the latest set of corresponding correction vectors. Finally, we incorporate accuracy thresholds based on the precision required by the Fermi-Dirac distribution. The net result is a significant reduction in the computational effort against most previous block J-D implementations, especially as the number of wanted eigenpairs grows. We compare our approach with another robust implementation of block J-D (JDQMR) and the state-of-the-art Chebyshev filter subspace (CheFSI) method for various real-space density functional theory systems. Versus CheFSI, for first-row elements, our method yields competitive timings for valence-only systems and 4-6× speedups for all-electron systems with up to 10× reduced matrix-vector multiplies. For all-electron calculations on larger elements (e.g., gold) where the wanted spectrum is quite narrow compared to the full spectrum, we observe 60× speedup with 200× fewer matrix-vector multiples vs. CheFSI.

A robust variant of block Jacobi-Davidson for extracting a large number of eigenpairs: Application to grid-based real-space density functional theory.

PubMed

Lee, M; Leiter, K; Eisner, C; Breuer, A; Wang, X

2017-09-21

In this work, we investigate a block Jacobi-Davidson (J-D) variant suitable for sparse symmetric eigenproblems where a substantial number of extremal eigenvalues are desired (e.g., ground-state real-space quantum chemistry). Most J-D algorithm variations tend to slow down as the number of desired eigenpairs increases due to frequent orthogonalization against a growing list of solved eigenvectors. In our specification of block J-D, all of the steps of the algorithm are performed in clusters, including the linear solves, which allows us to greatly reduce computational effort with blocked matrix-vector multiplies. In addition, we move orthogonalization against locked eigenvectors and working eigenvectors outside of the inner loop but retain the single Ritz vector projection corresponding to the index of the correction vector. Furthermore, we minimize the computational effort by constraining the working subspace to the current vectors being updated and the latest set of corresponding correction vectors. Finally, we incorporate accuracy thresholds based on the precision required by the Fermi-Dirac distribution. The net result is a significant reduction in the computational effort against most previous block J-D implementations, especially as the number of wanted eigenpairs grows. We compare our approach with another robust implementation of block J-D (JDQMR) and the state-of-the-art Chebyshev filter subspace (CheFSI) method for various real-space density functional theory systems. Versus CheFSI, for first-row elements, our method yields competitive timings for valence-only systems and 4-6× speedups for all-electron systems with up to 10× reduced matrix-vector multiplies. For all-electron calculations on larger elements (e.g., gold) where the wanted spectrum is quite narrow compared to the full spectrum, we observe 60× speedup with 200× fewer matrix-vector multiples vs. CheFSI.

Effect of the interconnected network structure on the epidemic threshold

NASA Astrophysics Data System (ADS)

Wang, Huijuan; Li, Qian; D'Agostino, Gregorio; Havlin, Shlomo; Stanley, H. Eugene; Van Mieghem, Piet

2013-08-01

Most real-world networks are not isolated. In order to function fully, they are interconnected with other networks, and this interconnection influences their dynamic processes. For example, when the spread of a disease involves two species, the dynamics of the spread within each species (the contact network) differs from that of the spread between the two species (the interconnected network). We model two generic interconnected networks using two adjacency matrices, A and B, in which A is a 2N×2N matrix that depicts the connectivity within each of two networks of size N, and B a 2N×2N matrix that depicts the interconnections between the two. Using an N-intertwined mean-field approximation, we determine that a critical susceptible-infected-susceptible (SIS) epidemic threshold in two interconnected networks is 1/λ1(A+αB), where the infection rate is β within each of the two individual networks and αβ in the interconnected links between the two networks and λ1(A+αB) is the largest eigenvalue of the matrix A+αB. In order to determine how the epidemic threshold is dependent upon the structure of interconnected networks, we analytically derive λ1(A+αB) using a perturbation approximation for small and large α, the lower and upper bound for any α as a function of the adjacency matrix of the two individual networks, and the interconnections between the two and their largest eigenvalues and eigenvectors. We verify these approximation and boundary values for λ1(A+αB) using numerical simulations, and determine how component network features affect λ1(A+αB). We note that, given two isolated networks G1 and G2 with principal eigenvectors x and y, respectively, λ1(A+αB) tends to be higher when nodes i and j with a higher eigenvector component product xiyj are interconnected. This finding suggests essential insights into ways of designing interconnected networks to be robust against epidemics.

Using Perturbation Theory to Reduce Noise in Diffusion Tensor Fields

PubMed Central

Bansal, Ravi; Staib, Lawrence H.; Xu, Dongrong; Laine, Andrew F.; Liu, Jun; Peterson, Bradley S.

2009-01-01

We propose the use of Perturbation theory to reduce noise in Diffusion Tensor (DT) fields. Diffusion Tensor Imaging (DTI) encodes the diffusion of water molecules along different spatial directions in a positive-definite, 3 × 3 symmetric tensor. Eigenvectors and eigenvalues of DTs allow the in vivo visualization and quantitative analysis of white matter fiber bundles across the brain. The validity and reliability of these analyses are limited, however, by the low spatial resolution and low Signal-to-Noise Ratio (SNR) in DTI datasets. Our procedures can be applied to improve the validity and reliability of these quantitative analyses by reducing noise in the tensor fields. We model a tensor field as a three-dimensional Markov Random Field and then compute the likelihood and the prior terms of this model using Perturbation theory. The prior term constrains the tensor field to be smooth, whereas the likelihood term constrains the smoothed tensor field to be similar to the original field. Thus, the proposed method generates a smoothed field that is close in structure to the original tensor field. We evaluate the performance of our method both visually and quantitatively using synthetic and real-world datasets. We quantitatively assess the performance of our method by computing the SNR for eigenvalues and the coherence measures for eigenvectors of DTs across tensor fields. In addition, we quantitatively compare the performance of our procedures with the performance of one method that uses a Riemannian distance to compute the similarity between two tensors, and with another method that reduces noise in tensor fields by anisotropically filtering the diffusion weighted images that are used to estimate diffusion tensors. These experiments demonstrate that our method significantly increases the coherence of the eigenvectors and the SNR of the eigenvalues, while simultaneously preserving the fine structure and boundaries between homogeneous regions, in the smoothed tensor field. PMID:19540791

Spatial-spectral preprocessing for endmember extraction on GPU's

NASA Astrophysics Data System (ADS)

Jimenez, Luis I.; Plaza, Javier; Plaza, Antonio; Li, Jun

2016-10-01

Spectral unmixing is focused in the identification of spectrally pure signatures, called endmembers, and their corresponding abundances in each pixel of a hyperspectral image. Mainly focused on the spectral information contained in the hyperspectral images, endmember extraction techniques have recently included spatial information to achieve more accurate results. Several algorithms have been developed for automatic or semi-automatic identification of endmembers using spatial and spectral information, including the spectral-spatial endmember extraction (SSEE) where, within a preprocessing step in the technique, both sources of information are extracted from the hyperspectral image and equally used for this purpose. Previous works have implemented the SSEE technique in four main steps: 1) local eigenvectors calculation in each sub-region in which the original hyperspectral image is divided; 2) computation of the maxima and minima projection of all eigenvectors over the entire hyperspectral image in order to obtain a candidates pixels set; 3) expansion and averaging of the signatures of the candidate set; 4) ranking based on the spectral angle distance (SAD). The result of this method is a list of candidate signatures from which the endmembers can be extracted using various spectral-based techniques, such as orthogonal subspace projection (OSP), vertex component analysis (VCA) or N-FINDR. Considering the large volume of data and the complexity of the calculations, there is a need for efficient implementations. Latest- generation hardware accelerators such as commodity graphics processing units (GPUs) offer a good chance for improving the computational performance in this context. In this paper, we develop two different implementations of the SSEE algorithm using GPUs. Both are based on the eigenvectors computation within each sub-region of the first step, one using the singular value decomposition (SVD) and another one using principal component analysis (PCA). Based on our experiments with hyperspectral data sets, high computational performance is observed in both cases.

Geologic Map of Upper Cretaceous and Tertiary Strata and Coal Stratigraphy of the Paleocene Fort Union Formation, Rawlins-Little Snake River Area, South-Central Wyoming

USGS Publications Warehouse

Hettinger, R.D.; Honey, J.G.; Ellis, M.S.; Barclay, C.S.V.; East, J.A.

2008-01-01

This report provides a map and detailed descriptions of geologic formations for a 1,250 square mile region in the Rawlins-Little Snake River coal field in the eastern part of the Washakie and Great Divide Basins of south-central Wyoming. Mapping of geologic formations and coal beds was conducted at a scale of 1:24,000 and compiled at a scale of 1:100,000. Emphasis was placed on coal-bearing strata of the China Butte and Overland Members of the Paleocene Fort Union Formation. Surface stratigraphic sections were measured and described and well logs were examined to determine the lateral continuity of individual coal beds; the coal-bed stratigraphy is shown on correlation diagrams. A structure contour and overburden map constructed on the uppermost coal bed in the China Butte Member is also provided.

Mapping gradients of community composition with nearest-neighbour imputation: extending plot data for landscape analysis

Treesearch

Janet L. Ohmann; Matthew J. Gregory; Emilie B. Henderson; Heather M. Roberts

2011-01-01

Question: How can nearest-neighbour (NN) imputation be used to develop maps of multiple species and plant communities? Location: Western and central Oregon, USA, but methods are applicable anywhere. Methods: We demonstrate NN imputation by mapping woody plant communities for >100 000 km2 of diverse forests and woodlands. Species abundances on...

Mind Maps as Classroom Exercises

ERIC Educational Resources Information Center

Budd, John W.

2004-01-01

A Mind Map is an outline in which the major categories radiate from a central image and lesser categories are portrayed as branches of larger branches. The author describes an in-class exercise in which small groups of students each create a Mind Map for a specific topic. This exercise is another example of an active and collaborative learning…

Modal Contributions to Heat Conduction across Crystalline and Amorphous Si/Ge Interfaces

NASA Astrophysics Data System (ADS)

Gordiz, Kiarash; Henry, Asegun

Until now, our entire understanding of interfacial heat transfer has been based on the phonon gas model and Landauer formalism. Based on this framework, it is difficult to offer any intuition on heat transfer between two solid materials if one side of the interface is an amorphous structure. Here, using the interface conductance modal analysis (ICMA) method, we investigate the modal contributions to thermal interface conductance (TIC) through crystalline (c) and amorphous (a) Si/Ge interfaces. It is revealed that around 15% of the conductance through the cSi/cGe interface arises from less than 0.1% of the modes of vibration in the structure that exist between 12-13THz and because of their large eigenvectors around the interface are classified as interfacial modes. Correlation maps show that these interfacial modes exhibit strong correlations with all the other modes. The physics behind this strong coupling ability is studied by calculating the mode-level harmonic and anharmonic energy distribution among all the atoms in the system. It is found that these interfacial modes are enabled by the large degree of anharmonicity near the interface, which is higher than the bulk and ultimately allows this small group of modes to couple to other modes of vibration. In addition, unlike the cSi/cGe, correlation maps for aSi/cGe, cSi/aGe, and aSi/aGe interfaces show that the majority of contributions to TIC arise from auto-correlations instead of cross-correlations. The provided analysis sheds light on the nature of localized vibrations at interfaces and can be enlightening for other investigations of localization.

Mapping lake level changes using ICESat/GLAS satellite laser altimetry data: a case study in arid regions of central Asia

NASA Astrophysics Data System (ADS)

Li, JunLi; Fang, Hui; Yang, Liao

2011-12-01

Lakes in arid regions of Central Asia act as essential components of regional water cycles, providing sparse but valuable water resource for the fragile ecological environments and human lives. Lakes in Central Asia are sensitive to climate change and human activities, and great changes have been found since 1960s. Mapping and monitoring these inland lakes would improve our understanding of mechanism of lake dynamics and climatic impacts. ICESat/GLAS satellite laser altimetry provides an efficient tool of continuously measuring lake levels in these poorly surveyed remote areas. An automated mapping scheme of lake level changes is developed based on GLAS altimetry products, and the spatial and temporal characteristics of 9 typical lakes in Central Asia are analyzed to validate the level accuracies. The results show that ICESat/GLAS has a good performance of lake level monitoring, whose patterns of level changes are the same as those of field observation, and the max differences between GLAS and field data is 3cm. Based on the results, it is obvious that alpine lakes are increasing greatly in lake levels during 2003-2009 due to climate change, while open lakes with dams and plain endorheic lakes decrease dramatically in water levels due to human activities, which reveals the overexploitation of water resource in Central Asia.

Publications - PDF 98-37A v. 1.1 | Alaska Division of Geological &

Science.gov Websites

main content DGGS PDF 98-37A v. 1.1 Publication Details Title: Geologic map of the Tanana A-1 and A-2 ., 1998, Geologic map of the Tanana A-1 and A-2 quadrangles, central Alaska: Alaska Division of Geological & Other Oversized Sheets Maps & Other Oversized Sheets Sheet 1 Preliminary geologic map of the

Topographic steep central islands following excimer laser photorefractive keratectomy

NASA Astrophysics Data System (ADS)

Krueger, Ronald R.; McDonnell, Peter J.

1994-06-01

The purpose of this study is to demonstrate that topographic irregularities in the form of central islands of higher refractive power can be seen following excimer laser refractive surgery. We reviewed the computerized corneal topographic maps of 35 patients undergoing excimer laser PRK for compound myopic astigmatism or anisometropia from 8/91 to 8/93 at the USC/Doheny Eye Institute. The topographic maps were generated by the Computed Anatomy Corneal Modeling System, and central islands were defined as topographic areas of steepening of at least 3 diopters and 3 mm in diameter. A grading system was developed based on the presence of central islands during the postoperative period. Visually significant topographic steep central islands may be seen in over 50% of patients at 1 month following excimer laser PRK, and persist at 3 months in up to 24% of patients without nitrogen gas blowing. Loss of best corrected visual acuity or ghosting is associated with island formation, and may prolong visual rehabilitation after excimer laser PRK.

The Central Symmetry Analysis of Wrinkle Ridges in Lunar Mare Serenitatis

NASA Astrophysics Data System (ADS)

Yao, Meijuan; Chen, Jianping

2018-03-01

Wrinkle ridges are one of the most common structures usually found in lunar mare basalts, and their formations are closely related to the lunar mare. In this paper, wrinkle ridges in Mare Serenitatis were identified and mapped via high-resolution data acquired from SELENE, and a quantitative method was introduced to analyze the degree of central symmetry of the wrinkle ridges distributed in a concentric or radial pattern. Meanwhile, two methods were used to measure the lengths and orientations of wrinkle ridges before calculating their central symmetry value. Based on the mapped wrinkle ridges, we calculated the central symmetry value of the wrinkle ridges for the whole Mare Serenitatis as well as for the four circular ridge systems proposed by a previous study via this method. We also analyzed the factors that would cause discrepancies when calculating the central symmetry value. The results indicate that the method can be used to quantitatively analyze the degree of central symmetry of the linear features that were concentrically or radially oriented and can reflect the stress field characteristics.

Whole-genome mapping reveals a large chromosomal inversion on Iberian Brucella suis biovar 2 strains.

PubMed

Ferreira, Ana Cristina; Dias, Ricardo; de Sá, Maria Inácia Corrêa; Tenreiro, Rogério

2016-08-30

Optical mapping is a technology able to quickly generate high resolution ordered whole-genome restriction maps of bacteria, being a proven approach to search for diversity among bacterial isolates. In this work, optical whole-genome maps were used to compare closely-related Brucella suis biovar 2 strains. This biovar is the unique isolated in domestic pigs and wild boars in Portugal and Spain and most of the strains share specific molecular characteristics establishing an Iberian clonal lineage that can be differentiated from another lineage mainly isolated in several Central European countries. We performed the BamHI whole-genome optical maps of five B. suis biovar 2 field strains, isolated from wild boars in Portugal and Spain (three from the Iberian lineage and two from the Central European one) as well as of the reference strain B. suis biovar 2 ATCC 23445 (Central European lineage, Denmark). Each strain showed a distinct, highly individual configuration of 228-231 BamHI fragments. Nevertheless, a low divergence was globally observed in chromosome II (1.6%) relatively to chromosome I (2.4%). Optical mapping also disclosed genomic events associated with B. suis strains in chromosome I, namely one indel (3.5kb) and one large inversion (944kb). By using targeted-PCR in a set of 176 B. suis strains, including all biovars and haplotypes, the indel was found to be specific of the reference strain ATCC 23445 and the large inversion was shown to be an exclusive genomic marker of the Iberian clonal lineage of biovar 2. Copyright © 2016 Elsevier B.V. All rights reserved.

Mental disorder recovery correlated with centralities and interactions on an online social network

PubMed Central

Sayama, Hiroki

2015-01-01

Recent research has established both a theoretical basis and strong empirical evidence that effective social behavior plays a beneficial role in the maintenance of physical and psychological well-being of people. To test whether social behavior and well-being are also associated in online communities, we studied the correlations between the recovery of patients with mental disorders and their behaviors in online social media. As the source of the data related to the social behavior and progress of mental recovery, we used PatientsLikeMe (PLM), the world’s first open-participation research platform for the development of patient-centered health outcome measures. We first constructed an online social network structure based on patient-to-patient ties among 200 patients obtained from PLM. We then characterized patients’ online social activities by measuring the numbers of “posts and views” and “helpful marks” each patient obtained. The patients’ recovery data were obtained from their self-reported status information that was also available on PLM. We found that some node properties (in-degree, eigenvector centrality and PageRank) and the two online social activity measures were significantly correlated with patients’ recovery. Furthermore, we re-collected the patients’ recovery data two months after the first data collection. We found significant correlations between the patients’ social behaviors and the second recovery data, which were collected two months apart. Our results indicated that social interactions in online communities such as PLM were significantly associated with the current and future recoveries of patients with mental disorders. PMID:26312174

Mapping Global Citizenship

ERIC Educational Resources Information Center

Stein, Sharon

2015-01-01

The demand to cultivate global citizenship is frequently invoked as central to colleges' and universities' internationalization efforts. However, the term "global citizenship" remains undertheorized in the context of U.S. higher education. This article maps and engages three common global citizenship positions--entrepreneurial, liberal…

Computing Principal Eigenvectors of Large Web Graphs: Algorithms and Accelerations Related to PageRank and HITS

ERIC Educational Resources Information Center

Nagasinghe, Iranga

2010-01-01

This thesis investigates and develops a few acceleration techniques for the search engine algorithms used in PageRank and HITS computations. PageRank and HITS methods are two highly successful applications of modern Linear Algebra in computer science and engineering. They constitute the essential technologies accounted for the immense growth and…

Optical Eigenvector.

DTIC Science & Technology

1984-10-01

it necessary and identify by blckci -. mbrr, ’At tile bneginninp, of this contract , bot], -,-j- .lc the rest of the optical community imagined * that...simple analog optical computer,, could produce satisfactory solutions to elgenproblems. Earl’ - in this contract we improved optical computing... contract both we and the rest of the optical community imagined that simple analog optical computers could produce . satisfactory solutions to

Residuals-Based Subgraph Detection with Cue Vertices

DTIC Science & Technology

2015-11-30

Workshop, 2012, pp. 129–132. [5] M. E. J. Newman , “Finding community structure in networks using the eigenvectors of matrices,” Phys. Rev. E, vol. 74, no...from Data, vol. 1, no. 1, 2007. [7] M. W. Mahoney , L. Orecchia, and N. K. Vishnoi, “A spectral algorithm for improving graph partitions,” CoRR, vol. abs

Singularly Perturbed Equations in the Critical Case.

DTIC Science & Technology

1980-02-01

asymptotic properties of the differential equation (1) in the noncritical case (all ReXi (t) ɘ) . We will consider the critical case (k 0) ; the...the inequality (3), that is, ReXi (t,a) < 0 (58) The matrix ca(t,a) , consisting of the eigenvectors corresponding to w 0 , now has the form I (P -(t

The use of complete sets of orthogonal operators in spectroscopic studies

NASA Astrophysics Data System (ADS)

Raassen, A. J. J.; Uylings, P. H. M.

1996-01-01

Complete sets of orthogonal operators are used to calculate eigenvalues and eigenvector compositions in complex spectra. The latter are used to transform the LS-transition matrix into realistic intermediate coupling transition probabilities. Calculated transition probabilities for some close lying levels in Ni V and Fe III illustrate the power of the complete orthogonal operator approach.

Exploring the potential offered by legacy soil databases for ecosystem services mapping of Central African soils

NASA Astrophysics Data System (ADS)

Verdoodt, Ann; Baert, Geert; Van Ranst, Eric

2014-05-01

Central African soil resources are characterised by a large variability, ranging from stony, shallow or sandy soils with poor life-sustaining capabilities to highly weathered soils that recycle and support large amounts of biomass. Socio-economic drivers within this largely rural region foster inappropriate land use and management, threaten soil quality and finally culminate into a declining soil productivity and increasing food insecurity. For the development of sustainable land use strategies targeting development planning and natural hazard mitigation, decision makers often rely on legacy soil maps and soil profile databases. Recent development cooperation financed projects led to the design of soil information systems for Rwanda, D.R. Congo, and (ongoing) Burundi. A major challenge is to exploit these existing soil databases and convert them into soil inference systems through an optimal combination of digital soil mapping techniques, land evaluation tools, and biogeochemical models. This presentation aims at (1) highlighting some key characteristics of typical Central African soils, (2) assessing the positional, geographic and semantic quality of the soil information systems, and (3) revealing its potential impacts on the use of these datasets for thematic mapping of soil ecosystem services (e.g. organic carbon storage, pH buffering capacity). Soil map quality is assessed considering positional and semantic quality, as well as geographic completeness. Descriptive statistics, decision tree classification and linear regression techniques are used to mine the soil profile databases. Geo-matching as well as class-matching approaches are considered when developing thematic maps. Variability in inherent as well as dynamic soil properties within the soil taxonomic units is highlighted. It is hypothesized that within-unit variation in soil properties highly affects the use and interpretation of thematic maps for ecosystem services mapping. Results will mainly be based on analyses done in Rwanda, but can be complemented with ongoing research results or prospects for Burundi.

Geographical Gradients in Argentinean Terrestrial Mammal Species Richness and Their Environmental Correlates

PubMed Central

Márquez, Ana L.; Real, Raimundo; Kin, Marta S.; Guerrero, José Carlos; Galván, Betina; Barbosa, A. Márcia; Olivero, Jesús; Palomo, L. Javier; Vargas, J. Mario; Justo, Enrique

2012-01-01

We analysed the main geographical trends of terrestrial mammal species richness (SR) in Argentina, assessing how broad-scale environmental variation (defined by climatic and topographic variables) and the spatial form of the country (defined by spatial filters based on spatial eigenvector mapping (SEVM)) influence the kinds and the numbers of mammal species along these geographical trends. We also evaluated if there are pure geographical trends not accounted for by the environmental or spatial factors. The environmental variables and spatial filters that simultaneously correlated with the geographical variables and SR were considered potential causes of the geographic trends. We performed partial correlations between SR and the geographical variables, maintaining the selected explanatory variables statistically constant, to determine if SR was fully explained by them or if a significant residual geographic pattern remained. All groups and subgroups presented a latitudinal gradient not attributable to the spatial form of the country. Most of these trends were not explained by climate. We used a variation partitioning procedure to quantify the pure geographic trend (PGT) that remained unaccounted for. The PGT was larger for latitudinal than for longitudinal gradients. This suggests that historical or purely geographical causes may also be relevant drivers of these geographical gradients in mammal diversity. PMID:23028254

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation

PubMed Central

MANEL, STÉPHANIE; GUGERLI, FELIX; THUILLER, WILFRIED; ALVAREZ, NADIR; LEGENDRE, PIERRE; HOLDEREGGER, ROLF; GIELLY, LUDOVIC; TABERLET, PIERRE

2014-01-01

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran’s eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps. PMID:22680783

Preparation of a flood-risk environmental index: case study of eight townships in Changhua County, Taiwan.

PubMed

Peng, Szu-Hsien

2018-02-26

To evaluate flood-prone areas, correlation analysis of flooding factors for the quantitative evaluation of hazard degree was determined to assist in further disaster prevention management. This study used flood-prone areas in 35 villages over eight townships (Changhua, Huatan, Yuanlin, Xiushui, Puyan, Hemei, Dacun, and Erlin) in Changhua County as research samples. Linear combination was used to evaluate flood-prone environmental indices, and an expert questionnaire was designed by using the analytic hierarchy process and the Delphi method to determine the weights of factors. These factors were then used to calculate the eigenvector of a pairwise comparison matrix to obtain the weights for the risk assessment criteria. Through collection of disaster cases, with particular focus on specifically protected areas where flooding has occurred or is likely to occur, public adaptation and response capabilities were evaluated by using an interview questionnaire that contains the items of perceived disaster risk, resource acquisition capability, adaptation capability, and environment understanding and disaster prevention education. Overlays in a geographic information system were used to analyze the flood-risk degree in villages and to construct a distribution map that contains flood-prone environment indices. The results can assist local governments in understanding the risk degree of various administrative areas to aid them in developing effective mitigation plans.

Geologic Map and Engineering Properties of the Surficial Deposits of the Tok Area, East-Central Alaska

USGS Publications Warehouse

Carrara, Paul E.

2007-01-01

The Tok area 1:100,000-scale map, through which the Alaska Highway runs, is in east-central Alaska about 160 km west of the Yukon border. The surficial geologic mapping in the map area is in support of the 'Geologic Mapping in support of land, resources, and hazards issues in Alaska' Project of the USGS National Cooperative Geologic Mapping Program. The Tok map area contains parts of three physiographic provinces, the Alaska Range, the Yukon-Tanana Upland, and the Northway-Tanana Lowland. The high, rugged, glaciated landscape of the eastern Alaska Range dominates the southwestern map area. The highest peak, an unnamed summit at the head of Cathedral Rapids Creek No. 2, rises to 2166 m. The gently rolling hills of the Yukon-Tanana Upland, in the northern map area, rise to about 1000 m. The Northway-Tanana Lowland contains the valley of the westerly flowing Tanana River. Elevations along the floor of the lowland generally range between 470 and 520 m. The dominant feature within the map is the Tok fan, which occupies about 20 percent of the map area. This large (450 km2), nearly featureless fan contains a high percentage of volcanic clasts derived from outside the present-day drainage of the Tok River. Because the map area is dominated by various surficial deposits, the map depicts 26 different surficial units consisting of man-made, alluvial, colluvial, eolian, lacustrine, organic, glaciofluvial, glacial, and periglacial deposits. The accompanying table provides information concerning the various units including their properties, characteristics, resource potential, and associated hazards in this area of the upper Tanana valley.

Indoor radon variations in central Iran and its geostatistical map

NASA Astrophysics Data System (ADS)

Hadad, Kamal; Mokhtari, Javad

2015-02-01

We present the results of 2 year indoor radon survey in 10 cities of Yazd province in Central Iran (covering an area of 80,000 km2). We used passive diffusive samplers with LATEX polycarbonate films as Solid State Nuclear Track Detector (SSNTD). This study carried out in central Iran where there are major minerals and uranium mines. Our results indicate that despite few extraordinary high concentrations, average annual concentrations of indoor radon are within ICRP guidelines. When geostatistical spatial distribution of radon mapped onto geographical features of the province it was observed that risk of high radon concentration increases near the Saqand, Bafq, Harat and Abarkooh cities, this depended on the elevation and vicinity of the ores and mines.

Mineral deposits of Central America, with a section on manganese deposits of Panama

USGS Publications Warehouse

Roberts, Ralph Jackson; Irving, Earl Montgomery; Simons, F.S.

1957-01-01

The mineral deposits of Central America were studied between 1942 and 1945, in cooperation with the United States Department of State and the Foreign Economic Administration. Emphasis was originally placed on the study of strategic-mineral deposits, especially of antimony, chromite, manganese, quartz, and mica, but deposits of other minerals that offered promise of significant future production were also studied. A brief appraisal of the base-metal deposits was made, and deposits of iron ore in Honduras and of lead and zinc ores in Guatemala were mapped. In addition, studies were made of the regional geology of some areas, data were collected from many sources, and a new map of the geology of Central America was compiled.

An ab initio study of the conformational energy map of acetylcholine

NASA Astrophysics Data System (ADS)

Segall, M. D.; Payne, M. C.; Boyes, R. N.

An ab initio density functional theory study is reported of the conformational energy map of acetylcholine, with respect to the two central dihedral angles of the molecule. The acetylcholine molecule pays a central role in neurotransmission and has been studied widely using semi-empirical computational modelling. The ab initio results are compared with a number of previous investigations and with experiment. The ab initio data indicate that the most stable conformation of acetylcholine is the trans , gauche arrangement of the central dihedral angles. Furthermore, Mulliken population analysis of the electronic structure of the molecule in this conformation indicates that the positive charge of the molecule is spread over the exterior of the cationic head of the molecule.

Publications - PIR 2015-6 | Alaska Division of Geological & Geophysical

Science.gov Websites

content DGGS PIR 2015-6 Publication Details Title: Geologic map of the Talkeetna Mountains C-4 Quadrangle ., Freeman, L.K., and Lande, L.L., 2015, Geologic map of the Talkeetna Mountains C-4 Quadrangle and adjoining Sheets Sheet 1 Geologic map of the Talkeetna Mountains C-4 Quadrangle and adjoining areas, central Alaska

Geologic map of the Kechumstuk fault zone in the Mount Veta area, Fortymile mining district, east-central Alaska

USGS Publications Warehouse

Day, Warren C.; O’Neill, J. Michael; Dusel-Bacon, Cynthia; Aleinikoff, John N.; Siron, Christopher R.

2014-01-01

This map was developed by the U.S. Geological Survey Mineral Resources Program to depict the fundamental geologic features for the western part of the Fortymile mining district of east-central Alaska, and to delineate the location of known bedrock mineral prospects and their relationship to rock types and structural features. This geospatial map database presents a 1:63,360-scale geologic map for the Kechumstuk fault zone and surrounding area, which lies 55 km northwest of Chicken, Alaska. The Kechumstuk fault zone is a northeast-trending zone of faults that transects the crystalline basement rocks of the Yukon-Tanana Upland of the western part of the Fortymile mining district. The crystalline basement rocks include Paleozoic metasedimentary and metaigneous rocks as well as granitoid intrusions of Triassic, Jurassic, and Cretaceous age. The geologic units represented by polygons in this dataset are based on new geologic mapping and geochronological data coupled with an interpretation of regional and new geophysical data collected by the Alaska Department of Natural Resources, Division of Geological and Geophysical Surveys. The geochronological data are reported in the accompanying geologic map text and represent new U-Pb dates on zircons collected from the igneous and metaigneous units within the map area.

Surficial Geologic Map of the Clinton-Concord-Grafton-Medfield 12-Quadrangle Area in East Central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; Stone, Byron D.

2006-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of twelve 7.5-minute quadrangles (total 660 square miles) in east-central Massachusetts. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (grain size, sedimentary structures, mineral and rock-particle composition), constructional geomorphic features, stratigraphic relationships, and age. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock, and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), a regional map at 1:50,000 scale (PDF), quadrangle maps at 1:24,000 scale (12 PDF files), GIS data layers (ArcGIS shapefiles), scanned topographic base maps (TIF), metadata for the GIS layers, and a readme.txt file.

Development of regional liquefaction-induced deformation hazard maps

USGS Publications Warehouse

Rosinski, A.; Knudsen, K.-L.; Wu, J.; Seed, R.B.; Real, C.R.; ,

2004-01-01

This paper describes part of a project to assess the feasibility of producing regional (1:24,000-scale) liquefaction hazard maps that are based-on potential liquefaction-induced deformation. The study area is the central Santa Clara Valley, at the south end of San Francisco Bay in Central California. The information collected and used includes: a) detailed Quaternary geological mapping, b) over 650 geotechnical borings, c) probabilistic earthquake shaking information, and d) ground-water levels. Predictions of strain can be made using either empirical formulations or numerical simulations. In this project lateral spread displacements are estimated and new empirical relations to estimate future volumetric and shear strain are used. Geotechnical boring data to are used to: (a) develop isopach maps showing the thickness of sediment thatis likely to liquefy and deform under earthquake shaking; and (b) assess the variability in engineering properties within and between geologic map units. Preliminary results reveal that late Holocene deposits are likely to experience the greatest liquefaction-induced strains, while Holocene and late Pleistocene deposits are likely to experience significantly less horizontal and vertical strain in future earthquakes. Development of maps based on these analyses is feasible.