Geometrical eigen-subspace framework based molecular conformation representation for efficient structure recognition and comparison

NASA Astrophysics Data System (ADS)

Li, Xiao-Tian; Yang, Xiao-Bao; Zhao, Yu-Jun

2017-04-01

We have developed an extended distance matrix approach to study the molecular geometric configuration through spectral decomposition. It is shown that the positions of all atoms in the eigen-space can be specified precisely by their eigen-coordinates, while the refined atomic eigen-subspace projection array adopted in our approach is demonstrated to be a competent invariant in structure comparison. Furthermore, a visual eigen-subspace projection function (EPF) is derived to characterize the surrounding configuration of an atom naturally. A complete set of atomic EPFs constitute an intrinsic representation of molecular conformation, based on which the interatomic EPF distance and intermolecular EPF distance can be reasonably defined. Exemplified with a few cases, the intermolecular EPF distance shows exceptional rationality and efficiency in structure recognition and comparison.

Children's Personal Space as a Function of Age and Sex

ERIC Educational Resources Information Center

Lomranz, Jacob; And Others

1975-01-01

Significant differences were found on measures of personal space gathered from 74 3-, 5-, and 7-year-olds when they approached boys or girls of their own age. Three-year-olds kept less distance than 5- or 7-year-olds and all subjects kept less distance from girls than boys. (JMB)

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

Mathematical models for non-parametric inferences from line transect data

USGS Publications Warehouse

Burnham, K.P.; Anderson, D.R.

1976-01-01

A general mathematical theory of line transects is developed which supplies a framework for nonparametric density estimation based on either right angle or sighting distances. The probability of observing a point given its right angle distance (y) from the line is generalized to an arbitrary function g(y). Given only that g(0) = 1, it is shown there are nonparametric approaches to density estimation using the observed right angle distances. The model is then generalized to include sighting distances (r). Let f(y I r) be the conditional distribution of right angle distance given sighting distance. It is shown that nonparametric estimation based only on sighting distances requires we know the transformation of r given by f(0 I r).

The twilight envelope: a user-centered approach to describing roadway illumination at night.

PubMed

Andre, J; Owens, D A

2001-01-01

Visual recognition functions, such as acuity and contrast sensitivity, deteriorate rapidly over the declining luminances found during civil twilight. Thus civil twilight, a critical part of the transition between daylight and darkness, represents lighting conditions that may be useful to describe artificial illumination. Automotive headlamps project a three-dimensional beam that ranges from illumination levels comparable to daylight at the vehicle to the dark limit of civil twilight (3.3 1x) at some distance ahead. This twilight envelope is characterized as a distance beyond which foveal visual functions are severely impaired, and thus it provides a general, functional description of the useful extent of the headlamp beam. This user-centered approach to describing illumination is useful for characterizing visibility when driving at night or in other artificially lit environments. This paper discusses the twilight envelope approach and its application to intervehicle variations in headlamp systems. Actual or potential applications of this research include user-centered description of artificial illumination and driver/pedestrian safety education.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

A statistical approach for inferring the 3D structure of the genome.

PubMed

Varoquaux, Nelle; Ay, Ferhat; Noble, William Stafford; Vert, Jean-Philippe

2014-06-15

Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate 3D models of how chromosomes fold and fit into the nucleus. Many existing inference methods rely on multidimensional scaling (MDS), in which the pairwise distances of the inferred model are optimized to resemble pairwise distances derived directly from the contact counts. These approaches, however, often optimize a heuristic objective function and require strong assumptions about the biophysics of DNA to transform interaction frequencies to spatial distance, and thereby may lead to incorrect structure reconstruction. We propose a novel approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data. We compare two variants of our Poisson method, with or without optimization of the transfer function, to four different MDS-based algorithms-two metric MDS methods using different stress functions, a non-metric version of MDS and ChromSDE, a recently described, advanced MDS method-on a wide range of simulated datasets. We demonstrate that the Poisson models reconstruct better structures than all MDS-based methods, particularly at low coverage and high resolution, and we highlight the importance of optimizing the transfer function. On publicly available Hi-C data from mouse embryonic stem cells, we show that the Poisson methods lead to more reproducible structures than MDS-based methods when we use data generated using different restriction enzymes, and when we reconstruct structures at different resolutions. A Python implementation of the proposed method is available at http://cbio.ensmp.fr/pastis. © The Author 2014. Published by Oxford University Press.

Electronic Coupling Calculations for Bridge-Mediated Charge Transfer Using Constrained Density Functional Theory (CDFT) and Effective Hamiltonian Approaches at the Density Functional Theory (DFT) and Fragment-Orbital Density Functional Tight Binding (FODFTB) Level

DOE PAGES

Gillet, Natacha; Berstis, Laura; Wu, Xiaojing; ...

2016-09-09

In this paper, four methods to calculate charge transfer integrals in the context of bridge-mediated electron transfer are tested. These methods are based on density functional theory (DFT). We consider two perturbative Green's function effective Hamiltonian methods (first, at the DFT level of theory, using localized molecular orbitals; second, applying a tight-binding DFT approach, using fragment orbitals) and two constrained DFT implementations with either plane-wave or local basis sets. To assess the performance of the methods for through-bond (TB)-dominated or through-space (TS)-dominated transfer, different sets of molecules are considered. For through-bond electron transfer (ET), several molecules that were originally synthesizedmore » by Paddon-Row and co-workers for the deduction of electronic coupling values from photoemission and electron transmission spectroscopies, are analyzed. The tested methodologies prove to be successful in reproducing experimental data, the exponential distance decay constant and the superbridge effects arising from interference among ET pathways. For through-space ET, dedicated p-stacked systems with heterocyclopentadiene molecules were created and analyzed on the basis of electronic coupling dependence on donor-acceptor distance, structure of the bridge, and ET barrier height. The inexpensive fragment-orbital density functional tight binding (FODFTB) method gives similar results to constrained density functional theory (CDFT) and both reproduce the expected exponential decay of the coupling with donor-acceptor distances and the number of bridging units. Finally, these four approaches appear to give reliable results for both TB and TS ET and present a good alternative to expensive ab initio methodologies for large systems involving long-range charge transfers.« less

Electronic Coupling Calculations for Bridge-Mediated Charge Transfer Using Constrained Density Functional Theory (CDFT) and Effective Hamiltonian Approaches at the Density Functional Theory (DFT) and Fragment-Orbital Density Functional Tight Binding (FODFTB) Level

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

Gillet, Natacha; Berstis, Laura; Wu, Xiaojing

In this paper, four methods to calculate charge transfer integrals in the context of bridge-mediated electron transfer are tested. These methods are based on density functional theory (DFT). We consider two perturbative Green's function effective Hamiltonian methods (first, at the DFT level of theory, using localized molecular orbitals; second, applying a tight-binding DFT approach, using fragment orbitals) and two constrained DFT implementations with either plane-wave or local basis sets. To assess the performance of the methods for through-bond (TB)-dominated or through-space (TS)-dominated transfer, different sets of molecules are considered. For through-bond electron transfer (ET), several molecules that were originally synthesizedmore » by Paddon-Row and co-workers for the deduction of electronic coupling values from photoemission and electron transmission spectroscopies, are analyzed. The tested methodologies prove to be successful in reproducing experimental data, the exponential distance decay constant and the superbridge effects arising from interference among ET pathways. For through-space ET, dedicated p-stacked systems with heterocyclopentadiene molecules were created and analyzed on the basis of electronic coupling dependence on donor-acceptor distance, structure of the bridge, and ET barrier height. The inexpensive fragment-orbital density functional tight binding (FODFTB) method gives similar results to constrained density functional theory (CDFT) and both reproduce the expected exponential decay of the coupling with donor-acceptor distances and the number of bridging units. Finally, these four approaches appear to give reliable results for both TB and TS ET and present a good alternative to expensive ab initio methodologies for large systems involving long-range charge transfers.« less

Electronic Coupling Calculations for Bridge-Mediated Charge Transfer Using Constrained Density Functional Theory (CDFT) and Effective Hamiltonian Approaches at the Density Functional Theory (DFT) and Fragment-Orbital Density Functional Tight Binding (FODFTB) Level.

PubMed

Gillet, Natacha; Berstis, Laura; Wu, Xiaojing; Gajdos, Fruzsina; Heck, Alexander; de la Lande, Aurélien; Blumberger, Jochen; Elstner, Marcus

2016-10-11

In this article, four methods to calculate charge transfer integrals in the context of bridge-mediated electron transfer are tested. These methods are based on density functional theory (DFT). We consider two perturbative Green's function effective Hamiltonian methods (first, at the DFT level of theory, using localized molecular orbitals; second, applying a tight-binding DFT approach, using fragment orbitals) and two constrained DFT implementations with either plane-wave or local basis sets. To assess the performance of the methods for through-bond (TB)-dominated or through-space (TS)-dominated transfer, different sets of molecules are considered. For through-bond electron transfer (ET), several molecules that were originally synthesized by Paddon-Row and co-workers for the deduction of electronic coupling values from photoemission and electron transmission spectroscopies, are analyzed. The tested methodologies prove to be successful in reproducing experimental data, the exponential distance decay constant and the superbridge effects arising from interference among ET pathways. For through-space ET, dedicated π-stacked systems with heterocyclopentadiene molecules were created and analyzed on the basis of electronic coupling dependence on donor-acceptor distance, structure of the bridge, and ET barrier height. The inexpensive fragment-orbital density functional tight binding (FODFTB) method gives similar results to constrained density functional theory (CDFT) and both reproduce the expected exponential decay of the coupling with donor-acceptor distances and the number of bridging units. These four approaches appear to give reliable results for both TB and TS ET and present a good alternative to expensive ab initio methodologies for large systems involving long-range charge transfers.

Distance-Dependent Multimodal Image Registration for Agriculture Tasks

PubMed Central

Berenstein, Ron; Hočevar, Marko; Godeša, Tone; Edan, Yael; Ben-Shahar, Ohad

2015-01-01

Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use multimodal sensory systems and operate in natural environments. While not limited to any particular modalities; here we focus on systems with visual and thermal sensory inputs. Our approach is based on pre-calibrating a distance-dependent transformation matrix (DDTM) between the sensors; and representing it in a compact way by regressing the distance-dependent coefficients as distance-dependent functions. The DDTM is measured by calculating a projective transformation matrix for varying distances between the sensors and possible targets. To do so we designed a unique experimental setup including unique Artificial Control Points (ACPs) and their detection algorithms for the two sensors. We demonstrate the utility of our approach using different experiments and evaluation criteria. PMID:26308000

A Process-Based Transport-Distance Model of Aeolian Transport

NASA Astrophysics Data System (ADS)

Naylor, A. K.; Okin, G.; Wainwright, J.; Parsons, A. J.

2017-12-01

We present a new approach to modeling aeolian transport based on transport distance. Particle fluxes are based on statistical probabilities of particle detachment and distributions of transport lengths, which are functions of particle size classes. A computational saltation model is used to simulate transport distances over a variety of sizes. These are fit to an exponential distribution, which has the advantages of computational economy, concordance with current field measurements, and a meaningful relationship to theoretical assumptions about mean and median particle transport distance. This novel approach includes particle-particle interactions, which are important for sustaining aeolian transport and dust emission. Results from this model are compared with results from both bulk- and particle-sized-specific transport equations as well as empirical wind tunnel studies. The transport-distance approach has been successfully used for hydraulic processes, and extending this methodology from hydraulic to aeolian transport opens up the possibility of modeling joint transport by wind and water using consistent physics. Particularly in nutrient-limited environments, modeling the joint action of aeolian and hydraulic transport is essential for understanding the spatial distribution of biomass across landscapes and how it responds to climatic variability and change.

Weighted Distance Functions Improve Analysis of High-Dimensional Data: Application to Molecular Dynamics Simulations.

PubMed

Blöchliger, Nicolas; Caflisch, Amedeo; Vitalis, Andreas

2015-11-10

Data mining techniques depend strongly on how the data are represented and how distance between samples is measured. High-dimensional data often contain a large number of irrelevant dimensions (features) for a given query. These features act as noise and obfuscate relevant information. Unsupervised approaches to mine such data require distance measures that can account for feature relevance. Molecular dynamics simulations produce high-dimensional data sets describing molecules observed in time. Here, we propose to globally or locally weight simulation features based on effective rates. This emphasizes, in a data-driven manner, slow degrees of freedom that often report on the metastable states sampled by the molecular system. We couple this idea to several unsupervised learning protocols. Our approach unmasks slow side chain dynamics within the native state of a miniprotein and reveals additional metastable conformations of a protein. The approach can be combined with most algorithms for clustering or dimensionality reduction.

Estimation of distances to stars with stellar parameters from LAMOST

DOE PAGES

Carlin, Jeffrey L.; Liu, Chao; Newberg, Heidi Jo; ...

2015-06-05

Here, we present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and returns a posterior probability density function for each star's absolute magnitude. We tailor this technique specifically to data from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) survey. Because LAMOST obtains roughly 3000 stellar spectra simultaneously within each ~5-degree diameter "plate" that is observed, we can use the stellar parameters of the observed stars to account for the stellar luminosity function and targetmore » selection effects. This removes biasing assumptions about the underlying populations, both due to predictions of the luminosity function from stellar evolution modeling, and from Galactic models of stellar populations along each line of sight. Using calibration data of stars with known distances and stellar parameters, we show that our method recovers distances for most stars within ~20%, but with some systematic overestimation of distances to halo giants. We apply our code to the LAMOST database, and show that the current precision of LAMOST stellar parameters permits measurements of distances with ~40% error bars. This precision should improve as the LAMOST data pipelines continue to be refined.« less

Estimation of distances to stars with stellar parameters from LAMOST

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

Carlin, Jeffrey L.; Liu, Chao; Newberg, Heidi Jo

Here, we present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and returns a posterior probability density function for each star's absolute magnitude. We tailor this technique specifically to data from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) survey. Because LAMOST obtains roughly 3000 stellar spectra simultaneously within each ~5-degree diameter "plate" that is observed, we can use the stellar parameters of the observed stars to account for the stellar luminosity function and targetmore » selection effects. This removes biasing assumptions about the underlying populations, both due to predictions of the luminosity function from stellar evolution modeling, and from Galactic models of stellar populations along each line of sight. Using calibration data of stars with known distances and stellar parameters, we show that our method recovers distances for most stars within ~20%, but with some systematic overestimation of distances to halo giants. We apply our code to the LAMOST database, and show that the current precision of LAMOST stellar parameters permits measurements of distances with ~40% error bars. This precision should improve as the LAMOST data pipelines continue to be refined.« less

Computing distance distributions from dipolar evolution data with overtones: RIDME spectroscopy with Gd(iii)-based spin labels.

PubMed

Keller, Katharina; Mertens, Valerie; Qi, Mian; Nalepa, Anna I; Godt, Adelheid; Savitsky, Anton; Jeschke, Gunnar; Yulikov, Maxim

2017-07-21

Extraction of distance distributions between high-spin paramagnetic centers from relaxation induced dipolar modulation enhancement (RIDME) data is affected by the presence of overtones of dipolar frequencies. As previously proposed, we account for these overtones by using a modified kernel function in Tikhonov regularization analysis. This paper analyzes the performance of such an approach on a series of model compounds with the Gd(iii)-PyMTA complex serving as paramagnetic high-spin label. We describe the calibration of the overtone coefficients for the RIDME kernel, demonstrate the accuracy of distance distributions obtained with this approach, and show that for our series of Gd-rulers RIDME technique provides more accurate distance distributions than Gd(iii)-Gd(iii) double electron-electron resonance (DEER). The analysis of RIDME data including harmonic overtones can be performed using the MATLAB-based program OvertoneAnalysis, which is available as open-source software from the web page of ETH Zurich. This approach opens a perspective for the routine use of the RIDME technique with high-spin labels in structural biology and structural studies of other soft matter.

Validating the Kinematic Wave Approach for Rapid Soil Erosion Assessment and Improved BMP Site Selection to Enhance Training Land Sustainability

DTIC Science & Technology

2014-02-01

installation based on a Euclidean distance allocation and assigned that installation’s threshold values. The second approach used a thin - plate spline ...installation critical nLS+ thresholds involved spatial interpolation. A thin - plate spline radial basis functions (RBF) was selected as the...the interpolation of installation results using a thin - plate spline radial basis function technique. 6.5 OBJECTIVE #5: DEVELOP AND

Influence of a Locomotor Training Approach on Walking Speed and Distance in People With Chronic Spinal Cord Injury: A Randomized Clinical Trial

PubMed Central

Roach, Kathryn E.

2011-01-01

Background Impaired walking limits function after spinal cord injury (SCI), but training-related improvements are possible even in people with chronic motor incomplete SCI. Objective The objective of this study was to compare changes in walking speed and distance associated with 4 locomotor training approaches. Design This study was a single-blind, randomized clinical trial. Setting This study was conducted in a rehabilitation research laboratory. Participants Participants were people with minimal walking function due to chronic SCI. Intervention Participants (n=74) trained 5 days per week for 12 weeks with the following approaches: treadmill-based training with manual assistance (TM), treadmill-based training with stimulation (TS), overground training with stimulation (OG), and treadmill-based training with robotic assistance (LR). Measurements Overground walking speed and distance were the primary outcome measures. Results In participants who completed the training (n=64), there were overall effects for speed (effect size index [d]=0.33) and distance (d=0.35). For speed, there were no significant between-group differences; however, distance gains were greatest with OG. Effect sizes for speed and distance were largest with OG (d=0.43 and d=0.40, respectively). Effect sizes for speed were the same for TM and TS (d=0.28); there was no effect for LR. The effect size for distance was greater with TS (d=0.16) than with TM or LR, for which there was no effect. Ten participants who improved with training were retested at least 6 months after training; walking speed at this time was slower than that at the conclusion of training but remained faster than before training. Limitations It is unknown whether the training dosage and the emphasis on training speed were optimal. Robotic training that requires active participation would likely yield different results. Conclusions In people with chronic motor incomplete SCI, walking speed improved with both overground training and treadmill-based training; however, walking distance improved to a greater extent with overground training. PMID:21051593

An Aggregated Method for Determining Railway Defects and Obstacle Parameters

NASA Astrophysics Data System (ADS)

Loktev, Daniil; Loktev, Alexey; Stepanov, Roman; Pevzner, Viktor; Alenov, Kanat

2018-03-01

The method of combining algorithms of image blur analysis and stereo vision to determine the distance to objects (including external defects of railway tracks) and the speed of moving objects-obstacles is proposed. To estimate the deviation of the distance depending on the blur a statistical approach, logarithmic, exponential and linear standard functions are used. The statistical approach includes a method of estimating least squares and the method of least modules. The accuracy of determining the distance to the object, its speed and direction of movement is obtained. The paper develops a method of determining distances to objects by analyzing a series of images and assessment of depth using defocusing using its aggregation with stereoscopic vision. This method is based on a physical effect of dependence on the determined distance to the object on the obtained image from the focal length or aperture of the lens. In the calculation of the blur spot diameter it is assumed that blur occurs at the point equally in all directions. According to the proposed approach, it is possible to determine the distance to the studied object and its blur by analyzing a series of images obtained using the video detector with different settings. The article proposes and scientifically substantiates new and improved existing methods for detecting the parameters of static and moving objects of control, and also compares the results of the use of various methods and the results of experiments. It is shown that the aggregate method gives the best approximation to the real distances.

A Density Functional for Liquid 3He Based on the Aziz Potential

NASA Astrophysics Data System (ADS)

Barranco, M.; Hernández, E. S.; Mayol, R.; Navarro, J.; Pi, M.; Szybisz, L.

2006-09-01

We propose a new class of density functionals for liquid 3He based on the Aziz helium-helium interaction screened at short distances by the microscopically calculated two-body distribution function g(r). Our aim is to reduce to a minumum the unavoidable phenomenological ingredients inherent to any density functional approach. Results for the homogeneous liquid and droplets are presented and discussed.

Penalized nonparametric scalar-on-function regression via principal coordinates

PubMed Central

Reiss, Philip T.; Miller, David L.; Wu, Pei-Shien; Hua, Wen-Yu

2016-01-01

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This paper introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive modeling software, allows for fast optimal tuning parameter selection and for extensions to multiple functional predictors, exponential family-valued responses, and mixed-effects models. In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model. PMID:29217963

Effect of color on pilot performance and transfer functions using a full-spectrum, calligraphic, color display system

NASA Technical Reports Server (NTRS)

Chase, W. D.

1976-01-01

The use of blue and red color in out-of-window cockpit displays, in full-spectrum calligraphic computer-generated display systems, is studied with attention given to pilot stereographic depth perception and response to visual cues. Displays for vertical approach, with dynamic and frozen-range landing approach and perspective arrays, are analyzed. Pilot transfer function and the transfer function associated with the contrasted approach and perspective arrays are discussed. Out-of-window blue lights are perceived by pilots as indicating greater distance depth, red lights as indicating proximity. The computer-generated chromatic display was adapted to flight simulators for the tests.

Streamwise Versus Spanwise Spacing of Obstacle Arrays: Parametrization of the Effects on Drag and Turbulence

NASA Astrophysics Data System (ADS)

Simón-Moral, Andres; Santiago, Jose Luis; Krayenhoff, E. Scott; Martilli, Alberto

2014-06-01

A Reynolds-averaged Navier-Stokes model is used to investigate the evolution of the sectional drag coefficient and turbulent length scales with the layouts of aligned arrays of cubes. Results show that the sectional drag coefficient is determined by the non-dimensional streamwise distance (sheltering parameter), and the non-dimensional spanwise distance (channelling parameter) between obstacles. This is different than previous approaches that consider only plan area density . On the other hand, turbulent length scales behave similarly to the staggered case (e. g. they are function of only). Analytical formulae are proposed for the length scales and for the sectional drag coefficient as a function of sheltering and channelling parameters, and implemented in a column model. This approach demonstrates good skill in the prediction of vertical profiles of the spatially-averaged horizontal wind speed.

Information Resources Usage in Project Management Digital Learning System

ERIC Educational Resources Information Center

Davidovitch, Nitza; Belichenko, Margarita; Kravchenko, Yurii

2017-01-01

The article combines a theoretical approach to structuring knowledge that is based on the integrated use of fuzzy semantic network theory predicates, Boolean functions, theory of complexity of network structures and some practical aspects to be considered in the distance learning at the university. The paper proposes a methodological approach that…

Trajectory analysis via a geometric feature space approach

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

Rintoul, Mark D.; Wilson, Andrew T.

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Trajectory analysis via a geometric feature space approach

DOE PAGES

Rintoul, Mark D.; Wilson, Andrew T.

2015-10-05

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

PubMed Central

Nguyen, Thu L. N.; Shin, Yoan

2016-01-01

Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

Universal freezing of quantum correlations within the geometric approach

PubMed Central

Cianciaruso, Marco; Bromley, Thomas R.; Roga, Wojciech; Lo Franco, Rosario; Adesso, Gerardo

2015-01-01

Quantum correlations in a composite system can be measured by resorting to a geometric approach, according to which the distance from the state of the system to a suitable set of classically correlated states is considered. Here we show that all distance functions, which respect natural assumptions of invariance under transposition, convexity, and contractivity under quantum channels, give rise to geometric quantifiers of quantum correlations which exhibit the peculiar freezing phenomenon, i.e., remain constant during the evolution of a paradigmatic class of states of two qubits each independently interacting with a non-dissipative decohering environment. Our results demonstrate from first principles that freezing of geometric quantum correlations is independent of the adopted distance and therefore universal. This finding paves the way to a deeper physical interpretation and future practical exploitation of the phenomenon for noisy quantum technologies. PMID:26053239

The determination of pair-distance distribution by double electron-electron resonance: regularization by the length of distance discretization with Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Dzuba, Sergei A.

2016-08-01

Pulsed double electron-electron resonance technique (DEER, or PELDOR) is applied to study conformations and aggregation of peptides, proteins, nucleic acids, and other macromolecules. For a pair of spin labels, experimental data allows for the determination of their distance distribution function, P(r). P(r) is derived as a solution of a first-kind Fredholm integral equation, which is an ill-posed problem. Here, we suggest regularization by increasing the distance discretization length to its upper limit where numerical integration still provides agreement with experiment. This upper limit is found to be well above the lower limit for which the solution instability appears because of the ill-posed nature of the problem. For solving the integral equation, Monte Carlo trials of P(r) functions are employed; this method has an obvious advantage of the fulfillment of the non-negativity constraint for P(r). The regularization by the increasing of distance discretization length for the case of overlapping broad and narrow distributions may be employed selectively, with this length being different for different distance ranges. The approach is checked for model distance distributions and for experimental data taken from literature for doubly spin-labeled DNA and peptide antibiotics.

Novel Approach to Conducting Blast Load Analyses Using Abaqus/Explicit-CEL

DTIC Science & Technology

2010-05-01

versus uncased, effects of afterburning , angle of incidence with respect to incoming shock, nearby geometry/barriers interacting with the shock...2. Blast parameters as a function of scaled distance – from TNT air blast data (DOE/TIC-11268, 1981). Due to inertial effects, the volume of air...positive phase duration) can be determined for a particular scaled distance. Figure 2 was generated from TNT air blast data for bare, spherical charges

Impact of long-range interactions on the disordered vortex lattice

NASA Astrophysics Data System (ADS)

Koopmann, J. A.; Geshkenbein, V. B.; Blatter, G.

2003-07-01

The interaction between the vortex lines in a type-II superconductor is mediated by currents. In the absence of transverse screening this interaction is long ranged, stiffening up the vortex lattice as expressed by the dispersive elastic moduli. The effect of disorder is strongly reduced, resulting in a mean-squared displacement correlator ≡<[u(R,L)-u(0,0)]2> characterized by a mere logarithmic growth with distance. Finite screening cuts the interaction on the scale of the London penetration depth λ and limits the above behavior to distances R<λ. Using a functional renormalization-group approach, we derive the flow equation for the disorder correlation function and calculate the disorder-averaged mean-squared relative displacement ∝ ln2σ(R/a0). The logarithmic growth (2σ=1) in the perturbative regime at small distances [A. I. Larkin and Yu. N. Ovchinnikov, J. Low Temp. Phys. 34, 409 (1979)] crosses over to a sub-logarithmic growth with 2σ=0.348 at large distances.

Asymptotic behaviour of two-point functions in multi-species models

NASA Astrophysics Data System (ADS)

Kozlowski, Karol K.; Ragoucy, Eric

2016-05-01

We extract the long-distance asymptotic behaviour of two-point correlation functions in massless quantum integrable models containing multi-species excitations. For such a purpose, we extend to these models the method of a large-distance regime re-summation of the form factor expansion of correlation functions. The key feature of our analysis is a technical hypothesis on the large-volume behaviour of the form factors of local operators in such models. We check the validity of this hypothesis on the example of the SU (3)-invariant XXX magnet by means of the determinant representations for the form factors of local operators in this model. Our approach confirms the structure of the critical exponents obtained previously for numerous models solvable by the nested Bethe Ansatz.

Approximating the Generalized Voronoi Diagram of Closely Spaced Objects

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

Edwards, John; Daniel, Eric; Pascucci, Valerio

2015-06-22

We present an algorithm to compute an approximation of the generalized Voronoi diagram (GVD) on arbitrary collections of 2D or 3D geometric objects. In particular, we focus on datasets with closely spaced objects; GVD approximation is expensive and sometimes intractable on these datasets using previous algorithms. With our approach, the GVD can be computed using commodity hardware even on datasets with many, extremely tightly packed objects. Our approach is to subdivide the space with an octree that is represented with an adjacency structure. We then use a novel adaptive distance transform to compute the distance function on octree vertices. Themore » computed distance field is sampled more densely in areas of close object spacing, enabling robust and parallelizable GVD surface generation. We demonstrate our method on a variety of data and show example applications of the GVD in 2D and 3D.« less

Towards tests of quark-hadron duality with functional analysis and spectral function data

NASA Astrophysics Data System (ADS)

Boito, Diogo; Caprini, Irinel

2017-04-01

The presence of terms that violate quark-hadron duality in the expansion of QCD Green's functions is a generally accepted fact. Recently, a new approach was proposed for the study of duality violations (DVs), which exploits the existence of a rigorous lower bound on the functional distance, measured in a certain norm, between a "true" correlator and its approximant calculated theoretically along a contour in the complex energy plane. In the present paper, we pursue the investigation of functional-analysis-based tests towards their application to real spectral function data. We derive a closed analytic expression for the minimal functional distance based on the general weighted L2 norm and discuss its relation with the distance measured in the L∞ norm. Using fake data sets obtained from a realistic toy model in which we allow for covariances inspired from the publicly available ALEPH spectral functions, we obtain, by Monte Carlo simulations, the statistical distribution of the strength parameter that measures the magnitude of the DV term added to the usual operator product expansion. The results show that, if the region with large errors near the end point of the spectrum in τ decays is excluded, the functional-analysis-based tests using either L2 or L∞ norms are able to detect, in a statistically significant way, the presence of DVs in realistic spectral function pseudodata.

Learning distance function for regression-based 4D pulmonary trunk model reconstruction estimated from sparse MRI data

NASA Astrophysics Data System (ADS)

Vitanovski, Dime; Tsymbal, Alexey; Ionasec, Razvan; Georgescu, Bogdan; Zhou, Shaohua K.; Hornegger, Joachim; Comaniciu, Dorin

2011-03-01

Congenital heart defect (CHD) is the most common birth defect and a frequent cause of death for children. Tetralogy of Fallot (ToF) is the most often occurring CHD which affects in particular the pulmonary valve and trunk. Emerging interventional methods enable percutaneous pulmonary valve implantation, which constitute an alternative to open heart surgery. While minimal invasive methods become common practice, imaging and non-invasive assessment tools become crucial components in the clinical setting. Cardiac computed tomography (CT) and cardiac magnetic resonance imaging (cMRI) are techniques with complementary properties and ability to acquire multiple non-invasive and accurate scans required for advance evaluation and therapy planning. In contrary to CT which covers the full 4D information over the cardiac cycle, cMRI often acquires partial information, for example only one 3D scan of the whole heart in the end-diastolic phase and two 2D planes (long and short axes) over the whole cardiac cycle. The data acquired in this way is called sparse cMRI. In this paper, we propose a regression-based approach for the reconstruction of the full 4D pulmonary trunk model from sparse MRI. The reconstruction approach is based on learning a distance function between the sparse MRI which needs to be completed and the 4D CT data with the full information used as the training set. The distance is based on the intrinsic Random Forest similarity which is learnt for the corresponding regression problem of predicting coordinates of unseen mesh points. Extensive experiments performed on 80 cardiac CT and MR sequences demonstrated the average speed of 10 seconds and accuracy of 0.1053mm mean absolute error for the proposed approach. Using the case retrieval workflow and local nearest neighbour regression with the learnt distance function appears to be competitive with respect to "black box" regression with immediate prediction of coordinates, while providing transparency to the predictions made.

Learning in First-Year Biology: Approaches of Distance and On-Campus Students

NASA Astrophysics Data System (ADS)

Quinn, Frances Catherine

2011-01-01

This paper aims to extend previous research into learning of tertiary biology, by exploring the learning approaches adopted by two groups of students studying the same first-year biology topic in either on-campus or off-campus "distance" modes. The research involved 302 participants, who responded to a topic-specific version of the Study Process Questionnaire, and in-depth interviews with 16 of these students. Several quantitative analytic techniques, including cluster analysis and Rasch differential item functioning analysis, showed that the younger, on-campus cohort made less use of deep approaches, and more use of surface approaches than the older, off-campus group. At a finer scale, clusters of students within these categories demonstrated different patterns of learning approach. Students' descriptions of their learning approaches at interview provided richer complementary descriptions of the approach they took to their study in the topic, showing how deep and surface approaches were manifested in the study context. These findings are critically analysed in terms of recent literature questioning the applicability of learning approaches theory in mass education, and their implications for teaching and research in undergraduate biology.

SU-F-T-124: Radiation Biological Equivalent Presentations OfLEM-1 and MKM Approaches in the Carbon-Ion Radiotherapy

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

Hsi, W; Jiang, G; Sheng, Y

Purpose: To study the correlations of the radiation biological equivalent doses (BED) along depth and lateral distance between LEM-1 and MKM approaches. Methods: In NIRS-MKM (Microdosimetric Kinetic Model) approach, the prescribed BED, referred as C-Eq, doses aims to present the relative biological effectiveness (RBE) for different energies of carbon-ions on a fixed 10% survival value of HCG cell with respect to convention X-ray. Instead of a fixed 10% survival, the BED doses of LEM-1 (Local Effect Model) approach, referred as X-Eq, aims to present the RBE over the whole survival curve of chordoma-like cell with alpha/beta ratio of 2.0. Themore » relationship of physical doses as a function of C-Eq and X-Eq doses were investigated along depth and lateral distance for various sizes of cubic targets in water irradiated by carbon-ions. Results: At the center of each cubic target, the trends between physical and C-Eq or X-Eq doses can be described by a linear and 2nd order polynomial functions, respectively. Using fit functions can then calculate a scaling factor between C-Eq and X-Eq doses to have similar physical doses. With equalized C-Eq and X-Eq doses at the depth of target center, over- and under-estimated X-Eq to C-Eq are seen for depths before and after the target center, respectively. Near the distal edge along depth, sharp rising of RBE value is observed for X-Eq, but sharp dropping of RBE value is observed for C-Eq. For lateral locations near and just outside 50% dose level, sharp raising of RBE value is also seen for X-Eq, while only minor increasing with fast dropping for C-Eq. Conclusion: An analytical function to model the differences between the CEq and X-Eq doses along depth and lateral distance need to further investigated to explain varied clinic outcome of specific cancers using two different approaches to calculated BED doses.« less

[Conservative and surgical treatment of convergence excess].

PubMed

Ehrt, O

2016-07-01

Convergence excess is a common finding especially in pediatric strabismus. A detailed diagnostic approach has to start after full correction of any hyperopia measured in cycloplegia. It includes measurements of manifest and latent deviation at near and distance fixation, near deviation after relaxation of accommodation with addition of +3 dpt, assessment of binocular function with and without +3 dpt as well as the accommodation range. This diagnostic approach is important for the classification into three types of convergence excess, which require different therapeutic approaches: 1) hypo-accommodative convergence excess is treated with permanent bifocal glasses, 2) norm-accommodative patients should be treated with bifocals which can be weaned over years, especially in patients with good stereopsis and 3) non-accommodative convergence excess and patients with large distance deviations need a surgical approach. The most effective operations include those which reduce the muscle torque, e. g. bimedial Faden operations or Y‑splitting of the medial rectus muscles.

Analysis of spatial correlations in a model two-dimensional liquid through eigenvalues and eigenvectors of atomic-level stress matrices.

PubMed

Levashov, V A; Stepanov, M G

2016-01-01

Considerations of local atomic-level stresses associated with each atom represent a particular approach to address structures of disordered materials at the atomic level. We studied structural correlations in a two-dimensional model liquid using molecular dynamics simulations in the following way. We diagonalized the atomic-level stress tensor of every atom and investigated correlations between the eigenvalues and orientations of the eigenvectors of different atoms as a function of distance between them. It is demonstrated that the suggested approach can be used to characterize structural correlations in disordered materials. In particular, we found that changes in the stress correlation functions on decrease of temperature are the most pronounced for the pairs of atoms with separation distance that corresponds to the first minimum in the pair density function. We also show that the angular dependencies of the stress correlation functions previously reported by Wu et al. [Phys. Rev. E 91, 032301 (2015)10.1103/PhysRevE.91.032301] do not represent the anisotropic Eshelby's stress fields, as it is suggested, but originate in the rotational properties of the stress tensors.

Analytic evaluation of the weighting functions for remote sensing of blackbody planetary atmospheres : the case of limb viewing geometry

NASA Technical Reports Server (NTRS)

Ustinov, Eugene A.

2006-01-01

In a recent publication (Ustinov, 2002), we proposed an analytic approach to evaluation of radiative and geophysical weighting functions for remote sensing of a blackbody planetary atmosphere, based on general linearization approach applied to the case of nadir viewing geometry. In this presentation, the general linearization approach is applied to the limb viewing geometry. The expressions, similar to those obtained in (Ustinov, 2002), are obtained for weighting functions with respect to the distance along the line of sight. Further on, these expressions are converted to the expressions for weighting functions with respect to the vertical coordinate in the atmosphere. Finally, the numerical representation of weighting functions in the form of matrices of partial derivatives of grid limb radiances with respect to the grid values of atmospheric parameters is used for a convolution with the finite field of view of the instrument.

Optimal flight initiation distance.

PubMed

Cooper, William E; Frederick, William G

2007-01-07

Decisions regarding flight initiation distance have received scant theoretical attention. A graphical model by Ydenberg and Dill (1986. The economics of fleeing from predators. Adv. Stud. Behav. 16, 229-249) that has guided research for the past 20 years specifies when escape begins. In the model, a prey detects a predator, monitors its approach until costs of escape and of remaining are equal, and then flees. The distance between predator and prey when escape is initiated (approach distance = flight initiation distance) occurs where decreasing cost of remaining and increasing cost of fleeing intersect. We argue that prey fleeing as predicted cannot maximize fitness because the best prey can do is break even during an encounter. We develop two optimality models, one applying when all expected future contribution to fitness (residual reproductive value) is lost if the prey dies, the other when any fitness gained (increase in expected RRV) during the encounter is retained after death. Both models predict optimal flight initiation distance from initial expected fitness, benefits obtainable during encounters, costs of escaping, and probability of being killed. Predictions match extensively verified predictions of Ydenberg and Dill's (1986) model. Our main conclusion is that optimality models are preferable to break-even models because they permit fitness maximization, offer many new testable predictions, and allow assessment of prey decisions in many naturally occurring situations through modification of benefit, escape cost, and risk functions.

Circuit theory and model-based inference for landscape connectivity

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.

2013-01-01

Circuit theory has seen extensive recent use in the field of ecology, where it is often applied to study functional connectivity. The landscape is typically represented by a network of nodes and resistors, with the resistance between nodes a function of landscape characteristics. The effective distance between two locations on a landscape is represented by the resistance distance between the nodes in the network. Circuit theory has been applied to many other scientific fields for exploratory analyses, but parametric models for circuits are not common in the scientific literature. To model circuits explicitly, we demonstrate a link between Gaussian Markov random fields and contemporary circuit theory using a covariance structure that induces the necessary resistance distance. This provides a parametric model for second-order observations from such a system. In the landscape ecology setting, the proposed model provides a simple framework where inference can be obtained for effects that landscape features have on functional connectivity. We illustrate the approach through a landscape genetics study linking gene flow in alpine chamois (Rupicapra rupicapra) to the underlying landscape.

Parton distributions in the LHC era

NASA Astrophysics Data System (ADS)

Del Debbio, Luigi

2018-03-01

Analyses of LHC (and other!) experiments require robust and statistically accurate determinations of the structure of the proton, encoded in the parton distribution functions (PDFs). The standard description of hadronic processes relies on factorization theorems, which allow a separation of process-dependent short-distance physics from the universal long-distance structure of the proton. Traditionally the PDFs are obtained from fits to experimental data. However, understanding the long-distance properties of hadrons is a nonperturbative problem, and lattice QCD can play a role in providing useful results from first principles. In this talk we compare the different approaches used to determine PDFs, and try to assess the impact of existing, and future, lattice calculations.

A risk analysis approach for using discriminant functions to manage logging-related landslides on granitic terrain

Treesearch

Raymond M. Rice; Norman H. Pillsbury; Kurt W. Schmidt

1985-01-01

Abstract - A linear discriminant function, developed to predict debris avalanches after clearcut logging on a granitic batholith in northwestern California, was tested on data from two batholiths. The equation was inaccurate in predicting slope stability on one of them. A new equation based on slope, crown cover, and distance from a stream (retained from the original...

Functional cerebral distance and the effect of emotional music on spatial rotation scores in undergraduate women and men.

PubMed

Bertsch, Sharon; Knee, H Donald; Webb, Jeffrey L

2011-02-01

The influence of listening to music on subsequent spatial rotation scores has a controversial history. The effect is unreliable, seeming to depend on several as yet unexplored factors. Using a large sample (167 women, 160 men; M age = 18.9 yr.), two related variables were investigated: participants' sex and the emotion conveyed by the music. Participants listened to 90 sec. of music that portrayed emotions of approach (happiness), or withdrawal (anger), or heard no music at all. They then performed a two-dimensional spatial rotation task. No significant difference was found in spatial rotation scores between groups exposed to music and those who were not. However, a significant interaction was found based on the sex of the participants and the emotion portrayed in the music they heard. Women's scores increased (relative to a no-music condition) only after hearing withdrawal-based music, while men's scores increased only after listening to the approach-based music. These changes were explained using the theory of functional cerebral distance.

Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.

PubMed

Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino

2017-01-10

In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.

Thermal form factor approach to the ground-state correlation functions of the XXZ chain in the antiferromagnetic massive regime

NASA Astrophysics Data System (ADS)

Dugave, Maxime; Göhmann, Frank; Kozlowski, Karol K.; Suzuki, Junji

2016-09-01

We use the form factors of the quantum transfer matrix in the zero-temperature limit in order to study the two-point ground-state correlation functions of the XXZ chain in the antiferromagnetic massive regime. We obtain novel form factor series representations of the correlation functions which differ from those derived either from the q-vertex-operator approach or from the algebraic Bethe Ansatz approach to the usual transfer matrix. We advocate that our novel representations are numerically more efficient and allow for a straightforward calculation of the large-distance asymptotic behaviour of the two-point functions. Keeping control over the temperature corrections to the two-point functions we see that these are of order {T}∞ in the whole antiferromagnetic massive regime. The isotropic limit of our result yields a novel form factor series representation for the two-point correlation functions of the XXX chain at zero magnetic field. Dedicated to the memory of Petr Petrovich Kulish.

Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach.

PubMed

Shakouri, Payman; Ordys, Andrzej; Askari, Mohamad R

2012-09-01

In the design of adaptive cruise control (ACC) system two separate control loops - an outer loop to maintain the safe distance from the vehicle traveling in front and an inner loop to control the brake pedal and throttle opening position - are commonly used. In this paper a different approach is proposed in which a single control loop is utilized. The objective of the distance tracking is incorporated into the single nonlinear model predictive control (NMPC) by extending the original linear time invariant (LTI) models obtained by linearizing the nonlinear dynamic model of the vehicle. This is achieved by introducing the additional states corresponding to the relative distance between leading and following vehicles, and also the velocity of the leading vehicle. Control of the brake and throttle position is implemented by taking the state-dependent approach. The model demonstrates to be more effective in tracking the speed and distance by eliminating the necessity of switching between the two controllers. It also offers smooth variation in brake and throttle controlling signal which subsequently results in a more uniform acceleration of the vehicle. The results of proposed method are compared with other ACC systems using two separate control loops. Furthermore, an ACC simulation results using a stop&go scenario are shown, demonstrating a better fulfillment of the design requirements. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Efficiency of Health Care Production in Low-Resource Settings: A Monte-Carlo Simulation to Compare the Performance of Data Envelopment Analysis, Stochastic Distance Functions, and an Ensemble Model

PubMed Central

Giorgio, Laura Di; Flaxman, Abraham D.; Moses, Mark W.; Fullman, Nancy; Hanlon, Michael; Conner, Ruben O.; Wollum, Alexandra; Murray, Christopher J. L.

2016-01-01

Low-resource countries can greatly benefit from even small increases in efficiency of health service provision, supporting a strong case to measure and pursue efficiency improvement in low- and middle-income countries (LMICs). However, the knowledge base concerning efficiency measurement remains scarce for these contexts. This study shows that current estimation approaches may not be well suited to measure technical efficiency in LMICs and offers an alternative approach for efficiency measurement in these settings. We developed a simulation environment which reproduces the characteristics of health service production in LMICs, and evaluated the performance of Data Envelopment Analysis (DEA) and Stochastic Distance Function (SDF) for assessing efficiency. We found that an ensemble approach (ENS) combining efficiency estimates from a restricted version of DEA (rDEA) and restricted SDF (rSDF) is the preferable method across a range of scenarios. This is the first study to analyze efficiency measurement in a simulation setting for LMICs. Our findings aim to heighten the validity and reliability of efficiency analyses in LMICs, and thus inform policy dialogues about improving the efficiency of health service production in these settings. PMID:26812685

Thermal Image Sensing Model for Robotic Planning and Search.

PubMed

Castro Jiménez, Lídice E; Martínez-García, Edgar A

2016-08-08

This work presents a search planning system for a rolling robot to find a source of infra-red (IR) radiation at an unknown location. Heat emissions are observed by a low-cost home-made IR passive visual sensor. The sensor capability for detection of radiation spectra was experimentally characterized. The sensor data were modeled by an exponential model to estimate the distance as a function of the IR image's intensity, and, a polynomial model to estimate temperature as a function of IR intensities. Both theoretical models are combined to deduce a subtle nonlinear exact solution via distance-temperature. A planning system obtains feed back from the IR camera (position, intensity, and temperature) to lead the robot to find the heat source. The planner is a system of nonlinear equations recursively solved by a Newton-based approach to estimate the IR-source in global coordinates. The planning system assists an autonomous navigation control in order to reach the goal and avoid collisions. Trigonometric partial differential equations were established to control the robot's course towards the heat emission. A sine function produces attractive accelerations toward the IR source. A cosine function produces repulsive accelerations against the obstacles observed by an RGB-D sensor. Simulations and real experiments of complex indoor are presented to illustrate the convenience and efficacy of the proposed approach.

Electric conductance of a mechanically strained molecular junction from first principles: Crucial role of structural relaxation and conformation sampling

NASA Astrophysics Data System (ADS)

Nguyen, Huu Chuong; Szyja, Bartłomiej M.; Doltsinis, Nikos L.

2014-09-01

Density functional theory (DFT) based molecular dynamics simulations have been performed of a 1,4-benzenedithiol molecule attached to two gold electrodes. To model the mechanical manipulation in typical break junction and atomic force microscopy experiments, the distance between two electrodes was incrementally increased up to the rupture point. For each pulling distance, the electric conductance was calculated using the DFT nonequilibrium Green's-function approach for a statistically relevant sample of configurations extracted from the simulation. With increasing mechanical strain, the formation of monoatomic gold wires is observed. The conductance decreases by three orders of magnitude as the initial twofold coordination of the thiol sulfur to the gold is reduced to a single S-Au bond at each electrode and the order in the electrodes is destroyed. Independent of the pulling distance, the conductance was found to fluctuate by at least two orders of magnitude depending on the instantaneous junction geometry.

Fuzzy approach for improved recognition of citric acid induced piglet coughing from continuous registration

NASA Astrophysics Data System (ADS)

Van Hirtum, A.; Berckmans, D.

2003-09-01

A natural acoustic indicator of animal welfare is the appearance (or absence) of coughing in the animal habitat. A sound-database of 5319 individual sounds including 2034 coughs was collected on six healthy piglets containing both animal vocalizations and background noises. Each of the test animals was repeatedly placed in a laboratory installation where coughing was induced by nebulization of citric acid. A two-class classification into 'cough' or 'other' was performed by the application of a distance function to a fast Fourier spectral sound analysis. This resulted in a positive cough recognition of 92%. For the whole sound-database however there was a misclassification of 21%. As spectral information up to 10000 Hz is available, an improved overall classification on the same database is obtained by applying the distance function to nine frequency ranges and combining the achieved distance-values in fuzzy rules. For each frequency range clustering threshold is determined by fuzzy c-means clustering.

Backscattering measurement of 6He on 209Bi: Critical interaction distance

NASA Astrophysics Data System (ADS)

Guimarães, V.; Kolata, J. J.; Aguilera, E. F.; Howard, A.; Roberts, A.; Becchetti, F. D.; Torres-Isea, R. O.; Riggins, A.; Febrarro, M.; Scarduelli, V.; de Faria, P. N.; Monteiro, D. S.; Huiza, J. F. P.; Arazi, A.; Hinnefeld, J.; Moro, A. M.; Rossi, E. S.; Morcelle, V.; Barioni, A.

2016-06-01

An elastic backscattering experiment has been performed at energies below the Coulomb barrier to investigate static and dynamic effects in the interaction of 6He with 209Bi. The measured cross sections are presented in terms of the d σ /d σR u t h ratio, as a function of the distance of closest approach on a Rutherford trajectory. The data are compared with a three-body CDCC calculation and good agreement is observed. In addition, the critical distance of interaction was extracted. A larger value was obtained for the exotic 6He nucleus as compared with the weakly bound 6Li and 9Be nuclei and the tightly bound 4He12C, and 16O nuclei.

Pulse EPR distance measurements to study multimers and multimerisation

NASA Astrophysics Data System (ADS)

Ackermann, Katrin; Bode, Bela E.

2018-06-01

Pulse dipolar electron paramagnetic resonance (PD-EPR) has become a powerful tool for structural biology determining distances on the nanometre scale. Recent advances in hardware, methodology, and data analysis have widened the scope to complex biological systems. PD-EPR can be applied to systems containing lowly populated conformers or displaying large intrinsic flexibility, making them all but intractable for cryo-electron microscopy and crystallography. Membrane protein applications are of particular interest due to the intrinsic difficulties for obtaining high-resolution structures of all relevant conformations. Many drug targets involved in critical cell functions are multimeric channels or transporters. Here, common approaches for introducing spin labels for PD-EPR cause the presence of more than two electron spins per multimeric complex. This requires careful experimental design to overcome detrimental multi-spin effects and to secure sufficient distance resolution in presence of multiple distances. In addition to obtaining mere distances, PD-EPR can also provide information on multimerisation degrees allowing to study binding equilibria and to determine dissociation constants.

Biosonar behaviour of free-ranging porpoises.

PubMed

Akamatsu, Tomonari; Wang, Ding; Wang, Kexiong; Naito, Yasuhiko

2005-04-22

Detecting objects in their paths is a fundamental perceptional function of moving organisms. Potential risks and rewards, such as prey, predators, conspecifics or non-biological obstacles, must be detected so that an animal can modify its behaviour accordingly. However, to date few studies have considered how animals in the wild focus their attention. Dolphins and porpoises are known to actively use sonar or echolocation. A newly developed miniature data logger attached to a porpoise allows for individual recording of acoustical search efforts and inspection distance based on echolocation. In this study, we analysed the biosonar behaviour of eight free-ranging finless porpoises (Neophocaena phocaenoides) and demonstrated that these animals inspect the area ahead of them before swimming silently into it. The porpoises inspected distances up to 77 m, whereas their swimming distance without using sonar was less than 20 m. The inspection distance was long enough to ensure a wide safety margin before facing real risks or rewards. Once a potential prey item was detected, porpoises adjusted their inspection distance from the remote target throughout their approach.

Relation of Cloud Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and CloudSat Merged Cloud Vertical Profiles

NASA Technical Reports Server (NTRS)

Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

2009-01-01

A cloud frequency of occurrence matrix is generated using merged cloud vertical profile derived from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical pro les can be related by a set of equations when the correlation distance of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches the random overlap with increasing distance separating cloud layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and CloudSat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The cloud correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when cloud fractions of both layers in a two-cloud layer system are the same.

Corrections Regarding the Impedance of Distance Functions for Several g(d) Functions

ERIC Educational Resources Information Center

Beaman, Jay

1976-01-01

Five functions were introduced for modeling travel behavior in the Beaman article "Distance and the 'Reaction' to Distance as a Function of Distance" published in Vol. 6, No. 3 of "Journal of Leisure Research" with the graphs of the functions printed incorrectly. This is a corrected version. (MM)

The distance function effect on k-nearest neighbor classification for medical datasets.

PubMed

Hu, Li-Yu; Huang, Min-Wei; Ke, Shih-Wen; Tsai, Chih-Fong

2016-01-01

K-nearest neighbor (k-NN) classification is conventional non-parametric classifier, which has been used as the baseline classifier in many pattern classification problems. It is based on measuring the distances between the test data and each of the training data to decide the final classification output. Since the Euclidean distance function is the most widely used distance metric in k-NN, no study examines the classification performance of k-NN by different distance functions, especially for various medical domain problems. Therefore, the aim of this paper is to investigate whether the distance function can affect the k-NN performance over different medical datasets. Our experiments are based on three different types of medical datasets containing categorical, numerical, and mixed types of data and four different distance functions including Euclidean, cosine, Chi square, and Minkowsky are used during k-NN classification individually. The experimental results show that using the Chi square distance function is the best choice for the three different types of datasets. However, using the cosine and Euclidean (and Minkowsky) distance function perform the worst over the mixed type of datasets. In this paper, we demonstrate that the chosen distance function can affect the classification accuracy of the k-NN classifier. For the medical domain datasets including the categorical, numerical, and mixed types of data, K-NN based on the Chi square distance function performs the best.

Characterization of individual stacking faults in a wurtzite GaAs nanowire by nanobeam X-ray diffraction.

PubMed

Davtyan, Arman; Lehmann, Sebastian; Kriegner, Dominik; Zamani, Reza R; Dick, Kimberly A; Bahrami, Danial; Al-Hassan, Ali; Leake, Steven J; Pietsch, Ullrich; Holý, Václav

2017-09-01

Coherent X-ray diffraction was used to measure the type, quantity and the relative distances between stacking faults along the growth direction of two individual wurtzite GaAs nanowires grown by metalorganic vapour epitaxy. The presented approach is based on the general property of the Patterson function, which is the autocorrelation of the electron density as well as the Fourier transformation of the diffracted intensity distribution of an object. Partial Patterson functions were extracted from the diffracted intensity measured along the [000\\bar{1}] direction in the vicinity of the wurtzite 00\\bar{1}\\bar{5} Bragg peak. The maxima of the Patterson function encode both the distances between the fault planes and the type of the fault planes with the sensitivity of a single atomic bilayer. The positions of the fault planes are deduced from the positions and shapes of the maxima of the Patterson function and they are in excellent agreement with the positions found with transmission electron microscopy of the same nanowire.

Characterization of individual stacking faults in a wurtzite GaAs nanowire by nanobeam X-ray diffraction

PubMed Central

Davtyan, Arman; Lehmann, Sebastian; Zamani, Reza R.; Dick, Kimberly A.; Bahrami, Danial; Al-Hassan, Ali; Leake, Steven J.; Pietsch, Ullrich; Holý, Václav

2017-01-01

Coherent X-ray diffraction was used to measure the type, quantity and the relative distances between stacking faults along the growth direction of two individual wurtzite GaAs nanowires grown by metalorganic vapour epitaxy. The presented approach is based on the general property of the Patterson function, which is the autocorrelation of the electron density as well as the Fourier transformation of the diffracted intensity distribution of an object. Partial Patterson functions were extracted from the diffracted intensity measured along the direction in the vicinity of the wurtzite Bragg peak. The maxima of the Patterson function encode both the distances between the fault planes and the type of the fault planes with the sensitivity of a single atomic bilayer. The positions of the fault planes are deduced from the positions and shapes of the maxima of the Patterson function and they are in excellent agreement with the positions found with transmission electron microscopy of the same nanowire. PMID:28862620

Three-dimensional habitat structure and landscape genetics: a step forward in estimating functional connectivity.

PubMed

Milanesi, P; Holderegger, R; Bollmann, K; Gugerli, F; Zellweger, F

2017-02-01

Estimating connectivity among fragmented habitat patches is crucial for evaluating the functionality of ecological networks. However, current estimates of landscape resistance to animal movement and dispersal lack landscape-level data on local habitat structure. Here, we used a landscape genetics approach to show that high-fidelity habitat structure maps derived from Light Detection and Ranging (LiDAR) data critically improve functional connectivity estimates compared to conventional land cover data. We related pairwise genetic distances of 128 Capercaillie (Tetrao urogallus) genotypes to least-cost path distances at multiple scales derived from land cover data. Resulting β values of linear mixed effects models ranged from 0.372 to 0.495, while those derived from LiDAR ranged from 0.558 to 0.758. The identification and conservation of functional ecological networks suffering from habitat fragmentation and homogenization will thus benefit from the growing availability of detailed and contiguous data on three-dimensional habitat structure and associated habitat quality. © 2016 by the Ecological Society of America.

Presurgical functional magnetic resonance imaging in patients with brain tumors.

PubMed

Ravn, Søren; Holmberg, Mats; Sørensen, Preben; Frokjaer, Jens B; Carl, Jesper

2016-01-01

Clinical functional magnetic resonance imaging (fMRI) is still an upcoming diagnostic tool because it is time-consuming to perform the post-scan calculations and interpretations. A standardized and easily used method for the clinical assessment of fMRI scans could decrease the workload and make fMRI more attractive for clinical use. To evaluate a standardized clinical approach for distance measurement between benign brain tumors and eloquent cortex in terms of the ability to predict pre- and postoperative neurological deficits after intraoperative neuronavigation-assisted surgery. A retrospective study of 34 patients. The fMRI data were reanalyzed using a standardized distance measurement procedure combining data from both fMRI and three-dimensional T1 MRI scans. The pre- and postoperative neurological status of each patient was obtained from hospital records. Data analysis was performed using logistic regression analysis to determine whether the distance measured between the tumor margin and fMRI activity could serve as a predictor for neurological deficits. An odds ratio of 0.89 mm(-1) (P = 0.03) was found between the risk of preoperative neurological motor deficits and the tumor-fMRI distance. An odds ratio of 0.82 mm(-1) (P = 0.04) was found between the risk of additional postoperative neurological motor deficits and the tumor-fMRI distance. The tumor was radically removed in 10 cases; five patients experienced additional postoperative motor deficits (tumor-fMRI distance <18 mm) and five did not (tumor-fMRI distance >18 mm) (P = 0.008). This study indicates that the distance measured between the tumor margin and fMRI activation could serve as a valuable predictor of neurological motor deficits. © The Foundation Acta Radiologica 2014.

The Importance of Non-accessible Crosslinks and Solvent Accessible Surface Distance in Modeling Proteins with Restraints From Crosslinking Mass Spectrometry*

PubMed Central

Bullock, Joshua Matthew Allen; Schwab, Jannik; Thalassinos, Konstantinos; Topf, Maya

2016-01-01

Crosslinking mass spectrometry (XL-MS) is becoming an increasingly popular technique for modeling protein monomers and complexes. The distance restraints garnered from these experiments can be used alone or as part of an integrative modeling approach, incorporating data from many sources. However, modeling practices are varied and the difference in their usefulness is not clear. Here, we develop a new scoring procedure for models based on crosslink data—Matched and Nonaccessible Crosslink score (MNXL). We compare its performance with that of other commonly-used scoring functions (Number of Violations and Sum of Violation Distances) on a benchmark of 14 protein domains, each with 300 corresponding models (at various levels of quality) and associated, previously published, experimental crosslinks (XLdb). The distances between crosslinked lysines are calculated either as Euclidean distances or Solvent Accessible Surface Distances (SASD) using a newly-developed method (Jwalk). MNXL takes into account whether a crosslink is nonaccessible, i.e. an experimentally observed crosslink has no corresponding SASD in a model due to buried lysines. This metric alone is shown to have a significant impact on modeling performance and is a concept that is not considered at present if only Euclidean distances are used. Additionally, a comparison between modeling with SASD or Euclidean distance shows that SASD is superior, even when factoring out the effect of the nonaccessible crosslinks. Our benchmarking also shows that MNXL outperforms the other tested scoring functions in terms of precision and correlation to Cα-RMSD from the crystal structure. We finally test the MNXL at different levels of crosslink recovery (i.e. the percentage of crosslinks experimentally observed out of all theoretical ones) and set a target recovery of ∼20% after which the performance plateaus. PMID:27150526

Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case.

PubMed

Villalón-Sepúlveda, Gabriel; Torres-Torriti, Miguel; Flores-Calero, Marco

2017-05-25

This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola-Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5 % and 95.4 % for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100 % for both signs. The Viola-Jones approach has detection rates below 20 % for distances between 30 and 48 m, and barely improves in the 20-30 m range with detection rates of up to 60 % . Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems.

Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case

PubMed Central

Villalón-Sepúlveda, Gabriel; Torres-Torriti, Miguel; Flores-Calero, Marco

2017-01-01

This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola–Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5% and 95.4% for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100% for both signs. The Viola–Jones approach has detection rates below 20% for distances between 30 and 48 m, and barely improves in the 20–30 m range with detection rates of up to 60%. Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems. PMID:28587071

The shadow price of substitutable sulfur in the US electric power plant: a distance function approach.

PubMed

Lee, Myunghun

2005-10-01

Given restrictions on sulfur dioxide emissions, a feasible long-run response could involve either an investment in improving boiler fuel-efficiency or a shift to a production process that is effective in removing sulfur dioxide. To allow for the possibility of substitution between sulfur and productive capital, we measure the shadow price of sulfur dioxide as the opportunity cost of lowering sulfur emissions in terms of forgone capital. The input distance function is estimated with data from 51 coal-fired US power units operating between 1977 and 1986. The indirect Morishima elasticities of substitution indicate that the substitutability of capital for sulfur is relatively high. The overall weighted average estimate of the shadow price of sulfur is -0.076 dollars per pound in constant 1976 dollars.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

Study on the Evaluation Method for Fault Displacement: Probabilistic Approach Based on Japanese Earthquake Rupture Data - Principal fault displacements -

NASA Astrophysics Data System (ADS)

Kitada, N.; Inoue, N.; Tonagi, M.

2016-12-01

The purpose of Probabilistic Fault Displacement Hazard Analysis (PFDHA) is estimate fault displacement values and its extent of the impact. There are two types of fault displacement related to the earthquake fault: principal fault displacement and distributed fault displacement. Distributed fault displacement should be evaluated in important facilities, such as Nuclear Installations. PFDHA estimates principal fault and distributed fault displacement. For estimation, PFDHA uses distance-displacement functions, which are constructed from field measurement data. We constructed slip distance relation of principal fault displacement based on Japanese strike and reverse slip earthquakes in order to apply to Japan area that of subduction field. However, observed displacement data are sparse, especially reverse faults. Takao et al. (2013) tried to estimate the relation using all type fault systems (reverse fault and strike slip fault). After Takao et al. (2013), several inland earthquakes were occurred in Japan, so in this time, we try to estimate distance-displacement functions each strike slip fault type and reverse fault type especially add new fault displacement data set. To normalized slip function data, several criteria were provided by several researchers. We normalized principal fault displacement data based on several methods and compared slip-distance functions. The normalized by total length of Japanese reverse fault data did not show particular trend slip distance relation. In the case of segmented data, the slip-distance relationship indicated similar trend as strike slip faults. We will also discuss the relation between principal fault displacement distributions with source fault character. According to slip distribution function (Petersen et al., 2011), strike slip fault type shows the ratio of normalized displacement are decreased toward to the edge of fault. However, the data set of Japanese strike slip fault data not so decrease in the end of the fault. This result indicates that the fault displacement is difficult to appear at the edge of the fault displacement in Japan. This research was part of the 2014-2015 research project `Development of evaluating method for fault displacement` by the Secretariat of Nuclear Regulation Authority (NRA), Japan.

Study of mass flow distribution and chemical composition of comets from solar induced X-ray fluorescence

NASA Technical Reports Server (NTRS)

Gorenstein, P.

1979-01-01

The expected performance of an X-ray detector as an instrument aboard a mission to a comet was evaluated. The functions of the detector are both nondispersive analysis of chemical composition and measurement of mass flow from the comet nucleus. Measurements are to be carried out at a distance from the comet. The approach distances considered are of the order of 1000 km and 100 km. A new type of X-ray detector, a proportional scintillation detector, is considered as an X-ray counter for nondispersive elemental analysis.

A dynamical proximity analysis of interacting galaxy pairs

NASA Technical Reports Server (NTRS)

Chatterjee, Tapan K.

1990-01-01

Using the impulsive approximation to study the velocity changes of stars during disk-sphere collisions and a method due to Bottlinger to study the post collision orbits of stars, the formation of various types of interacting galaxies is studied as a function of the distance of closest approach between the two galaxies.

Ordinary Least Squares and Quantile Regression: An Inquiry-Based Learning Approach to a Comparison of Regression Methods

ERIC Educational Resources Information Center

Helmreich, James E.; Krog, K. Peter

2018-01-01

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex…

Extraction of breast lesions from ultrasound imagery: Bhattacharyya gradient flow approach

NASA Astrophysics Data System (ADS)

Torkaman, Mahsa; Sandhu, Romeil; Tannenbaum, Allen

2018-03-01

Breast cancer is one of the most commonly diagnosed neoplasms among American women and the second leading cause of death among women all over the world. In order to reduce the mortality rate and cost of treatment, early diagnosis and treatment are essential. Accurate and reliable diagnosis is required in order to ensure the most effective treatment and a second opinion is often advisable. In this paper, we address the problem of breast lesion detection from ultrasound imagery by means of active contours, whose evolution is driven by maximizing the Bhattacharyya distance1 between the probability density functions (PDFs). The proposed method was applied to ultrasound breast imagery, and the lesion boundary was obtained by maximizing the distance-based energy functional such that the maximum (optimal contour) is attained at the boundary of the potential lesion. We compared the results of the proposed method quantitatively using the Dice coefficient (similarity index)2 to well-known GrowCut segmentation method3 and demonstrated that Bhattacharyya approach outperforms GrowCut in most of the cases.

Transverse Densities of Octet Baryons from Chiral Effective Field Theory

DOE PAGES

Alarcón, Jose Manuel; Hiller Blin, Astrid N.; Weiss, Christian

2017-03-24

Transverse densities describe the distribution of charge and current at fixed light-front time and provide a frame-independent spatial representation of hadrons as relativistic systems. In this paper, we calculate the transverse densities of the octet baryons at peripheral distances b=O(M π -1) in an approach that combines chiral effective field theory (χχEFT) and dispersion analysis. The densities are represented as dispersive integrals of the imaginary parts of the baryon electromagnetic form factors in the timelike region (spectral functions). The spectral functions on the two-pion cut at t>4Mmore » $$2\\atop{π}$$ are computed using relativistic χEFT with octet and decuplet baryons in the extended on-mass-shell renormalization scheme. The calculations are extended into the ρ-meson mass region using a dispersive method that incorporates the timelike pion form-factor data. The approach allows us to construct densities at distances b>1 fm with controlled uncertainties. Finally, our results provide insight into the peripheral structure of nucleons and hyperons and can be compared with empirical densities and lattice-QCD calculations.« less

Predicting protein complex geometries with a neural network.

PubMed

Chae, Myong-Ho; Krull, Florian; Lorenzen, Stephan; Knapp, Ernst-Walter

2010-03-01

A major challenge of the protein docking problem is to define scoring functions that can distinguish near-native protein complex geometries from a large number of non-native geometries (decoys) generated with noncomplexed protein structures (unbound docking). In this study, we have constructed a neural network that employs the information from atom-pair distance distributions of a large number of decoys to predict protein complex geometries. We found that docking prediction can be significantly improved using two different types of polar hydrogen atoms. To train the neural network, 2000 near-native decoys of even distance distribution were used for each of the 185 considered protein complexes. The neural network normalizes the information from different protein complexes using an additional protein complex identity input neuron for each complex. The parameters of the neural network were determined such that they mimic a scoring funnel in the neighborhood of the native complex structure. The neural network approach avoids the reference state problem, which occurs in deriving knowledge-based energy functions for scoring. We show that a distance-dependent atom pair potential performs much better than a simple atom-pair contact potential. We have compared the performance of our scoring function with other empirical and knowledge-based scoring functions such as ZDOCK 3.0, ZRANK, ITScore-PP, EMPIRE, and RosettaDock. In spite of the simplicity of the method and its functional form, our neural network-based scoring function achieves a reasonable performance in rigid-body unbound docking of proteins. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Perspective Space as a Model for Distance and Size Perception.

PubMed

Erkelens, Casper J

2017-01-01

In the literature, perspective space has been introduced as a model of visual space. Perspective space is grounded on the perspective nature of visual space during both binocular and monocular vision. A single parameter, that is, the distance of the vanishing point, transforms the geometry of physical space into that of perspective space. The perspective-space model predicts perceived angles, distances, and sizes. The model is compared with other models for distance and size perception. Perspective space predicts that perceived distance and size as a function of physical distance are described by hyperbolic functions. Alternatively, power functions have been widely used to describe perceived distance and size. Comparison of power and hyperbolic functions shows that both functions are equivalent within the range of distances that have been judged in experiments. Two models describing perceived distance on the ground plane appear to be equivalent with the perspective-space model too. The conclusion is that perspective space unifies a number of models of distance and size perception.

Perspective Space as a Model for Distance and Size Perception

PubMed Central

2017-01-01

In the literature, perspective space has been introduced as a model of visual space. Perspective space is grounded on the perspective nature of visual space during both binocular and monocular vision. A single parameter, that is, the distance of the vanishing point, transforms the geometry of physical space into that of perspective space. The perspective-space model predicts perceived angles, distances, and sizes. The model is compared with other models for distance and size perception. Perspective space predicts that perceived distance and size as a function of physical distance are described by hyperbolic functions. Alternatively, power functions have been widely used to describe perceived distance and size. Comparison of power and hyperbolic functions shows that both functions are equivalent within the range of distances that have been judged in experiments. Two models describing perceived distance on the ground plane appear to be equivalent with the perspective-space model too. The conclusion is that perspective space unifies a number of models of distance and size perception. PMID:29225765

Bird diversity and dissimilarity show contrasting patterns along heavy metal pollution gradients in the Urals, Russia.

PubMed

Belskii, Eugen A; Mikryukov, Vladimir S

2018-05-07

The effects of industrial pollution on bird diversity have been widely studied using traditional diversity measures, which assume all species to be equivalent. We compared species richness and Shannon index with distance-based measures of taxonomic, functional, and phylogenetic diversity (the abundance-weighted mean nearest taxon distances), which describe within-community dissimilarity at terminal branches. Analysis of dissimilarity can shed light on the processes underlying community assembly, i.e., environmental filtering decreases dissimilarity whereas competitive exclusion increases it. In the 2-year study near Karabash and Revda copper smelters in Russia, point counts of nesting birds and habitat descriptions were taken at 10 sites (40 plots) along each pollution gradient. The abundance and diversity of birds showed good repeatability in both regions. The total density of birds, number of species per plot, and Shannon diversity decreased at high toxic load in both regions. The taxonomic, functional, and phylogenetic nearest taxon distances showed the same pattern within regions. Species dissimilarity within communities increased with pollution in Karabash (due to loss of functionally similar species), but did not change in Revda (due to mass replacement of forest species by species of open habitats). Pollution-induced changes in bird communities near Karabash were greater due to the stronger deterioration of the forest ecosystems and less favorable natural conditions (more arid climate, lower diversity and vitality of the tree stand and understorey) compared to Revda. This study emphasizes the need for a multi-level approach to the analysis of bird communities using traditional indices of diversity, functional, taxonomic, or phylogenetic distances between species and environmental variables.

Two-generation analysis of pollen flow across a landscape. I. Male gamete heterogeneity among females.

PubMed

Smouse, P E; Dyer, R J; Westfall, R D; Sork, V L

2001-02-01

Gene flow is a key factor in the spatial genetic structure in spatially distributed species. Evolutionary biologists interested in microevolutionary processess and conservation biologists interested in the impact of landscape change require a method that measures the real time process of gene movement. We present a novel two-generation (parent-offspring) approach to the study of genetic structure (TwoGener) that allows us to quantify heterogeneity among the male gamete pools sampled by maternal trees scattered across the landscape and to estimate mean pollination distance and effective neighborhood size. First, we describe the model's elements: genetic distance matrices to estimate intergametic distances, molecular analysis of variance to determine whether pollen profiles differ among mothers, and optimal sampling considerations. Second, we evaluate the model's effectiveness by simulating spatially distributed populations. Spatial heterogeneity in male gametes can be estimated by phiFT, a male gametic analogue of Wright's F(ST) and an inverse function of mean pollination distance. We illustrate TwoGener in cases where the male gamete can be categorically or ambiguously determined. This approach does not require the high level of genetic resolution needed by parentage analysis, but the ambiguous case is vulnerable to bias in the absence of adequate genetic resolution. Finally, we apply TwoGener to an empirical study of Quercus alba in Missouri Ozark forests. We find that phiFT = 0.06, translating into about eight effective pollen donors per female and an effective pollination neighborhood as a circle of radius about 17 m. Effective pollen movement in Q. alba is more restricted than previously realized, even though pollen is capable of moving large distances. This case study illustrates that, with a modest investment in field survey and laboratory analysis, the TwoGener approach permits inferences about landscape-level gene movements.

Nonparametric test of consistency between cosmological models and multiband CMB measurements

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

Aghamousa, Amir; Shafieloo, Arman, E-mail: amir@apctp.org, E-mail: shafieloo@kasi.re.kr

2015-06-01

We present a novel approach to test the consistency of the cosmological models with multiband CMB data using a nonparametric approach. In our analysis we calibrate the REACT (Risk Estimation and Adaptation after Coordinate Transformation) confidence levels associated with distances in function space (confidence distances) based on the Monte Carlo simulations in order to test the consistency of an assumed cosmological model with observation. To show the applicability of our algorithm, we confront Planck 2013 temperature data with concordance model of cosmology considering two different Planck spectra combination. In order to have an accurate quantitative statistical measure to compare betweenmore » the data and the theoretical expectations, we calibrate REACT confidence distances and perform a bias control using many realizations of the data. Our results in this work using Planck 2013 temperature data put the best fit ΛCDM model at 95% (∼ 2σ) confidence distance from the center of the nonparametric confidence set while repeating the analysis excluding the Planck 217 × 217 GHz spectrum data, the best fit ΛCDM model shifts to 70% (∼ 1σ) confidence distance. The most prominent features in the data deviating from the best fit ΛCDM model seems to be at low multipoles  18 < ℓ < 26 at greater than 2σ, ℓ ∼ 750 at ∼1 to 2σ and ℓ ∼ 1800 at greater than 2σ level. Excluding the 217×217 GHz spectrum the feature at ℓ ∼ 1800 becomes substantially less significance at ∼1 to 2σ confidence level. Results of our analysis based on the new approach we propose in this work are in agreement with other analysis done using alternative methods.« less

Metallicity-Corrected Tip of the Red Giant Branch Distances to M66 and M96

NASA Astrophysics Data System (ADS)

Mager, Violet; Madore, Barry F.; Freedman, Wendy L.

2018-06-01

We present distances to M66 and M96 obtained through measurements of the tip of the red giant branch (TRGB) in HST ACS/WFC images, and give details of our method. The TRGB can be difficult to determine in color-magnitude diagrams where it is not a hard, well-defined edge. We discuss our approach to this in our edge-detection algorithm. Furthermore, metals affect the magnitude of the TRGB as a function of color, creating a slope to the edge that has been dealt with in the past by applying a red color cut-off. We instead apply a metallicity correction to the data that removes this effect, increasing the number of useable stars and providing a more accurate distance measurement.

Point process statistics in atom probe tomography.

PubMed

Philippe, T; Duguay, S; Grancher, G; Blavette, D

2013-09-01

We present a review of spatial point processes as statistical models that we have designed for the analysis and treatment of atom probe tomography (APT) data. As a major advantage, these methods do not require sampling. The mean distance to nearest neighbour is an attractive approach to exhibit a non-random atomic distribution. A χ(2) test based on distance distributions to nearest neighbour has been developed to detect deviation from randomness. Best-fit methods based on first nearest neighbour distance (1 NN method) and pair correlation function are presented and compared to assess the chemical composition of tiny clusters. Delaunay tessellation for cluster selection has been also illustrated. These statistical tools have been applied to APT experiments on microelectronics materials. Copyright © 2012 Elsevier B.V. All rights reserved.

Accounting for animal movement in estimation of resource selection functions: sampling and data analysis.

PubMed

Forester, James D; Im, Hae Kyung; Rathouz, Paul J

2009-12-01

Patterns of resource selection by animal populations emerge as a result of the behavior of many individuals. Statistical models that describe these population-level patterns of habitat use can miss important interactions between individual animals and characteristics of their local environment; however, identifying these interactions is difficult. One approach to this problem is to incorporate models of individual movement into resource selection models. To do this, we propose a model for step selection functions (SSF) that is composed of a resource-independent movement kernel and a resource selection function (RSF). We show that standard case-control logistic regression may be used to fit the SSF; however, the sampling scheme used to generate control points (i.e., the definition of availability) must be accommodated. We used three sampling schemes to analyze simulated movement data and found that ignoring sampling and the resource-independent movement kernel yielded biased estimates of selection. The level of bias depended on the method used to generate control locations, the strength of selection, and the spatial scale of the resource map. Using empirical or parametric methods to sample control locations produced biased estimates under stronger selection; however, we show that the addition of a distance function to the analysis substantially reduced that bias. Assuming a uniform availability within a fixed buffer yielded strongly biased selection estimates that could be corrected by including the distance function but remained inefficient relative to the empirical and parametric sampling methods. As a case study, we used location data collected from elk in Yellowstone National Park, USA, to show that selection and bias may be temporally variable. Because under constant selection the amount of bias depends on the scale at which a resource is distributed in the landscape, we suggest that distance always be included as a covariate in SSF analyses. This approach to modeling resource selection is easily implemented using common statistical tools and promises to provide deeper insight into the movement ecology of animals.

White-Tailed Deer Response to Vehicle Approach: Evidence of Unclear and Present Danger

PubMed Central

Blackwell, Bradley F.; Seamans, Thomas W.; DeVault, Travis L.

2014-01-01

The fundamental causes of animal-vehicle collisions are unclear, particularly at the level of animal detection of approaching vehicles and decision-making. Deer-vehicle collisions (DVCs) are especially costly in terms of animal mortality, property damage, and safety. Over one year, we exposed free-ranging white-tailed deer (Odocoileus virginianus) to vehicle approach under low ambient light conditions, from varying start distances, and vehicle speeds from 20 km/h to approximately 90 km/h. We modeled flight response by deer to an approaching vehicle and tested four hypotheses: 1) flight-initiation distance (FID) would correlate positively with start distance (indicating a spatial margin of safety); 2) deer would react to vehicle speed using a temporal margin of safety; 3) individuals reacting at greater FIDs would be more likely to cross the path of the vehicle; and 4) crossings would correlate positively with start distance, approach speed, and distance to concealing/refuge cover. We examined deer responses by quantiles. Median FID was 40% of start distance, irrespective of start distance or approach speed. Converting FID to time-to-collision (TTC), median TTC was 4.6 s, but uncorrelated with start distance or approach speed. The likelihood of deer crossing in front of the vehicle was not associated with greater FIDs or other explanatory variables. Because deer flight response to vehicle approach was highly variable, DVCs should be more likely with increasing vehicle speeds because of lower TTCs for a given distance. For road sections characterized by frequent DVCs, we recommend estimating TTC relative to vehicle speed and candidate line-of-sight distances adjusted downward by (1-P), where P represents our findings for the proportion of start distance by which >75% of deer had initiated flight. Where road design or conservation goals limit effectiveness of line-of-sight maintenance, we suggest incorporation of roadway obstacles that force drivers to slow vehicles, in addition to posting advisory speed limits. PMID:25333922

Regional co-location pattern scoping on a street network considering distance decay effects of spatial interaction

PubMed Central

Yu, Wenhao

2017-01-01

Regional co-location scoping intends to identify local regions where spatial features of interest are frequently located together. Most of the previous researches in this domain are conducted on a global scale and they assume that spatial objects are embedded in a 2-D space, but the movement in urban space is actually constrained by the street network. In this paper we refine the scope of co-location patterns to 1-D paths consisting of nodes and segments. Furthermore, since the relations between spatial events are usually inversely proportional to their separation distance, the proposed method introduces the “Distance Decay Effects” to improve the result. Specifically, our approach first subdivides the street edges into continuous small linear segments. Then a value representing the local distribution intensity of events is estimated for each linear segment using the distance-decay function. Each kind of geographic feature can lead to a tessellated network with density attribute, and the generated multiple networks for the pattern of interest will be finally combined into a composite network by calculating the co-location prevalence measure values, which are based on the density variation between different features. Our experiments verify that the proposed approach is effective in urban analysis. PMID:28763496

Thermal Image Sensing Model for Robotic Planning and Search

PubMed Central

Castro Jiménez, Lídice E.; Martínez-García, Edgar A.

2016-01-01

This work presents a search planning system for a rolling robot to find a source of infra-red (IR) radiation at an unknown location. Heat emissions are observed by a low-cost home-made IR passive visual sensor. The sensor capability for detection of radiation spectra was experimentally characterized. The sensor data were modeled by an exponential model to estimate the distance as a function of the IR image’s intensity, and, a polynomial model to estimate temperature as a function of IR intensities. Both theoretical models are combined to deduce a subtle nonlinear exact solution via distance-temperature. A planning system obtains feed back from the IR camera (position, intensity, and temperature) to lead the robot to find the heat source. The planner is a system of nonlinear equations recursively solved by a Newton-based approach to estimate the IR-source in global coordinates. The planning system assists an autonomous navigation control in order to reach the goal and avoid collisions. Trigonometric partial differential equations were established to control the robot’s course towards the heat emission. A sine function produces attractive accelerations toward the IR source. A cosine function produces repulsive accelerations against the obstacles observed by an RGB-D sensor. Simulations and real experiments of complex indoor are presented to illustrate the convenience and efficacy of the proposed approach. PMID:27509510

Performance analysis of a dual-tree algorithm for computing spatial distance histograms

PubMed Central

Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni

2011-01-01

Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753

The ideal subject distance for passport pictures.

PubMed

Verhoff, Marcel A; Witzel, Carsten; Kreutz, Kerstin; Ramsthaler, Frank

2008-07-04

In an age of global combat against terrorism, the recognition and identification of people on document images is of increasing significance. Experiments and calculations have shown that the camera-to-subject distance - not the focal length of the lens - can have a significant effect on facial proportions. Modern passport pictures should be able to function as a reference image for automatic and manual picture comparisons. This requires a defined subject distance. It is completely unclear which subject distance, in the taking of passport photographs, is ideal for the recognition of the actual person. We show here that the camera-to-subject distance that is perceived as ideal is dependent on the face being photographed, even if the distance of 2m was most frequently preferred. So far the problem of the ideal camera-to-subject distance for faces has only been approached through technical calculations. We have, for the first time, answered this question experimentally with a double-blind experiment. Even if there is apparently no ideal camera-to-subject distance valid for every face, 2m can be proposed as ideal for the taking of passport pictures. The first step would actually be the determination of a camera-to-subject distance for the taking of passport pictures within the standards. From an anthropological point of view it would be interesting to find out which facial features allow the preference of a shorter camera-to-subject distance and which allow the preference of a longer camera-to-subject distance.

Communication for extension: developing country experience.

PubMed

Meyer, A J

1985-01-01

This paper characterizes several major approaches to the use of communication in support of agricultural extension and suggests directions for change. The approaches discussed include: direct farmer contact, farmer forums, open broadcasting, advertising and social marketing, print media, multiple channel systems (campaigns and distance teaching), and comprehensive communication systems. Although all programs should be able to use media in interaction with training and the coordination of other inputs, this approach has not been comprehensively implemented in extension programs. There are few examples of cases where multiple methods have been brought together under a comprehensive communications strategy and institutionalized as part of an ongoing extension system. Lessons from social marketing in other sectors have not been exploited, while lessons from distance teaching have been underutilized. In addition, the networking and feedback functions of communication in extenson have not been given adequate attention. There is substantial potential for increasing the coverage and impact of agricultural extension through the more systematic and comprehensive use of communication.

Do breeding phase and detection distance influence the effective area surveyed for northern goshawks?

USGS Publications Warehouse

Roberson, A.M.; Andersen, D.E.; Kennedy, P.L.

2005-01-01

Broadcast surveys using conspecific calls are currently the most effective method for detecting northern goshawks (Accipiter gentilis) during the breeding season. These surveys typically use alarm calls during the nestling phase and juvenile food-begging calls during the fledgling-dependency phase. Because goshawks are most vocal during the courtship phase, we hypothesized that this phase would be an effective time to detect goshawks. Our objective was to improve current survey methodology by evaluating the probability of detecting goshawks at active nests in northern Minnesota in 3 breeding phases and at 4 broadcast distances and to determine the effective area surveyed per broadcast station. Unlike previous studies, we broadcast calls at only 1 distance per trial. This approach better quantifies (1) the relationship between distance and probability of detection, and (2) the effective area surveyed (EAS) per broadcast station. We conducted 99 broadcast trials at 14 active breeding areas. When pooled over all distances, detection rates were highest during the courtship (70%) and fledgling-dependency phases (68%). Detection rates were lowest during the nestling phase (28%), when there appeared to be higher variation in likelihood of detecting individuals. EAS per broadcast station was 39.8 ha during courtship and 24.8 ha during fledgling-dependency. Consequently, in northern Minnesota, broadcast stations may be spaced 712m and 562 m apart when conducting systematic surveys during courtship and fledgling-dependency, respectively. We could not calculate EAS for the nestling phase because probability of detection was not a simple function of distance from nest. Calculation of EAS could be applied to other areas where the probability of detection is a known function of distance.

Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach

ERIC Educational Resources Information Center

Hassan, Moshood Ayinde

2011-01-01

The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…

EEG-based functional networks evoked by acupuncture at ST 36: A data-driven thresholding study

NASA Astrophysics Data System (ADS)

Li, Huiyan; Wang, Jiang; Yi, Guosheng; Deng, Bin; Zhou, Hexi

2017-10-01

This paper investigates how acupuncture at ST 36 modulates the brain functional network. 20 channel EEG signals from 15 healthy subjects are respectively recorded before, during and after acupuncture. The correlation between two EEG channels is calculated by using Pearson’s coefficient. A data-driven approach is applied to determine the threshold, which is performed by considering the connected set, connected edge and network connectivity. Based on such thresholding approach, the functional network in each acupuncture period is built with graph theory, and the associated functional connectivity is determined. We show that acupuncturing at ST 36 increases the connectivity of the EEG-based functional network, especially for the long distance ones between two hemispheres. The properties of the functional network in five EEG sub-bands are also characterized. It is found that the delta and gamma bands are affected more obviously by acupuncture than the other sub-bands. These findings highlight the modulatory effects of acupuncture on the EEG-based functional connectivity, which is helpful for us to understand how it participates in the cortical or subcortical activities. Further, the data-driven threshold provides an alternative approach to infer the functional connectivity under other physiological conditions.

Remediation of information processing following traumatic brain injury: a community-based rehabilitation approach.

PubMed

Ashley, Mark J; Ashley, Jessica; Kreber, Lisa

2012-01-01

Traumatic brain injury (TBI) results in disruption of information processing via damage to primary, secondary, and tertiary cortical regions, as well as, subcortical pathways supporting information flow within and between cortical structures. TBI predominantly affects the anterior frontal poles, anterior temporal poles, white matter tracts and medial temporal structures. Fundamental information processing skills such as attention, perceptual processing, categorization and cognitive distance are concentrated within these same regions and are frequently disrupted following injury. Information processing skills improve in accordance with the extent to which residual frontal and temporal neurons can be encouraged to recruit and bias neuronal networks or the degree to which the functional connectivity of neural networks can be re-established and result in re-emergence or regeneration of specific cognitive skills. Higher-order cognitive processes, i.e., memory, reasoning, problem solving and other executive functions, are dependent upon the integrity of attention, perceptual processing, categorization, and cognitive distance. A therapeutic construct for treatment of attention, perceptual processing, categorization and cognitive distance deficits is presented along with an interventional model for encouragement of re-emergence or regeneration of these fundamental information processing skills.

A spatial model for a stream networks of Citarik River with the environmental variables: potential of hydrogen (PH) and temperature

NASA Astrophysics Data System (ADS)

Bachrudin, A.; Mohamed, N. B.; Supian, S.; Sukono; Hidayat, Y.

2018-03-01

Application of existing geostatistical theory of stream networks provides a number of interesting and challenging problems. Most of statistical tools in the traditional geostatistics have been based on a Euclidean distance such as autocovariance functions, but for stream data is not permissible since it deals with a stream distance. To overcome this autocovariance developed a model based on the distance the flow with using convolution kernel approach (moving average construction). Spatial model for a stream networks is widely used to monitor environmental on a river networks. In a case study of a river in province of West Java, the objective of this paper is to analyze a capability of a predictive on two environmental variables, potential of hydrogen (PH) and temperature using ordinary kriging. Several the empirical results show: (1) The best fit of autocovariance functions for temperature and potential hydrogen (ph) of Citarik River is linear which also yields the smallest root mean squared prediction error (RMSPE), (2) the spatial correlation values between the locations on upstream and on downstream of Citarik river exhibit decreasingly

An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems

PubMed Central

Salcedo-Sanz, S.; Del Ser, J.; Geem, Z. W.

2014-01-01

This paper presents a novel fuzzy clustering technique based on grouping genetic algorithms (GGAs), which are a class of evolutionary algorithms especially modified to tackle grouping problems. Our approach hinges on a GGA devised for fuzzy clustering by means of a novel encoding of individuals (containing elements and clusters sections), a new fitness function (a superior modification of the Davies Bouldin index), specially tailored crossover and mutation operators, and the use of a scheme based on a local search and a parallelization process, inspired from an island-based model of evolution. The overall performance of our approach has been assessed over a number of synthetic and real fuzzy clustering problems with different objective functions and distance measures, from which it is concluded that the proposed approach shows excellent performance in all cases. PMID:24977235

Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images

PubMed Central

Jang, Yeonggul; Jung, Ho Yub; Hong, Youngtaek; Cho, Iksung; Shim, Hackjoon; Chang, Hyuk-Jae

2016-01-01

This paper presents a method for the automatic 3D segmentation of the ascending aorta from coronary computed tomography angiography (CCTA). The segmentation is performed in three steps. First, the initial seed points are selected by minimizing a newly proposed energy function across the Hough circles. Second, the ascending aorta is segmented by geodesic distance transformation. Third, the seed points are effectively transferred through the next axial slice by a novel transfer function. Experiments are performed using a database composed of 10 patients' CCTA images. For the experiment, the ground truths are annotated manually on the axial image slices by a medical expert. A comparative evaluation with state-of-the-art commercial aorta segmentation algorithms shows that our approach is computationally more efficient and accurate under the DSC (Dice Similarity Coefficient) measurements. PMID:26904151

Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

ERIC Educational Resources Information Center

Akhmetova, Daniya Z.

2014-01-01

Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…

Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS

NASA Astrophysics Data System (ADS)

Tien Bui, Dieu; Pradhan, Biswajeet; Lofman, Owe; Revhaug, Inge; Dick, Oystein B.

2012-08-01

The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps. The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.

Biosonar behaviour of free-ranging porpoises

PubMed Central

Akamatsu, Tomonari; Wang, Ding; Wang, Kexiong; Naito, Yasuhiko

2005-01-01

Detecting objects in their paths is a fundamental perceptional function of moving organisms. Potential risks and rewards, such as prey, predators, conspecifics or non-biological obstacles, must be detected so that an animal can modify its behaviour accordingly. However, to date few studies have considered how animals in the wild focus their attention. Dolphins and porpoises are known to actively use sonar or echolocation. A newly developed miniature data logger attached to a porpoise allows for individual recording of acoustical search efforts and inspection distance based on echolocation. In this study, we analysed the biosonar behaviour of eight free-ranging finless porpoises (Neophocaena phocaenoides) and demonstrated that these animals inspect the area ahead of them before swimming silently into it. The porpoises inspected distances up to 77 m, whereas their swimming distance without using sonar was less than 20 m. The inspection distance was long enough to ensure a wide safety margin before facing real risks or rewards. Once a potential prey item was detected, porpoises adjusted their inspection distance from the remote target throughout their approach. PMID:15888412

Learning a Mahalanobis Distance-Based Dynamic Time Warping Measure for Multivariate Time Series Classification.

PubMed

Mei, Jiangyuan; Liu, Meizhu; Wang, Yuan-Fang; Gao, Huijun

2016-06-01

Multivariate time series (MTS) datasets broadly exist in numerous fields, including health care, multimedia, finance, and biometrics. How to classify MTS accurately has become a hot research topic since it is an important element in many computer vision and pattern recognition applications. In this paper, we propose a Mahalanobis distance-based dynamic time warping (DTW) measure for MTS classification. The Mahalanobis distance builds an accurate relationship between each variable and its corresponding category. It is utilized to calculate the local distance between vectors in MTS. Then we use DTW to align those MTS which are out of synchronization or with different lengths. After that, how to learn an accurate Mahalanobis distance function becomes another key problem. This paper establishes a LogDet divergence-based metric learning with triplet constraint model which can learn Mahalanobis matrix with high precision and robustness. Furthermore, the proposed method is applied on nine MTS datasets selected from the University of California, Irvine machine learning repository and Robert T. Olszewski's homepage, and the results demonstrate the improved performance of the proposed approach.

Engineering Attractiveness in the European Educational Environment: Can Distance Education Approaches Make a Difference?

ERIC Educational Resources Information Center

Katzis, Konstantinos; Dimopoulos, Christos; Meletiou-Mavrotheris, Maria; Lasica, Ilona-Elefteryja

2018-01-01

The recent phenomenon of worldwide declining enrolments in engineering-related degrees has led to the gradual decrease in the number of engineering graduates. This decrease occurs at a time of increasing demand in the labour market for highly qualified engineers, who are necessary for the implementation of fundamental societal functions. This…

Performance evaluation of an automatic MGRF-based lung segmentation approach

NASA Astrophysics Data System (ADS)

Soliman, Ahmed; Khalifa, Fahmi; Alansary, Amir; Gimel'farb, Georgy; El-Baz, Ayman

2013-10-01

The segmentation of the lung tissues in chest Computed Tomography (CT) images is an important step for developing any Computer-Aided Diagnostic (CAD) system for lung cancer and other pulmonary diseases. In this paper, we introduce a new framework for validating the accuracy of our developed Joint Markov-Gibbs based lung segmentation approach using 3D realistic synthetic phantoms. These phantoms are created using a 3D Generalized Gauss-Markov Random Field (GGMRF) model of voxel intensities with pairwise interaction to model the 3D appearance of the lung tissues. Then, the appearance of the generated 3D phantoms is simulated based on iterative minimization of an energy function that is based on the learned 3D-GGMRF image model. These 3D realistic phantoms can be used to evaluate the performance of any lung segmentation approach. The performance of our segmentation approach is evaluated using three metrics, namely, the Dice Similarity Coefficient (DSC), the modified Hausdorff distance, and the Average Volume Difference (AVD) between our segmentation and the ground truth. Our approach achieves mean values of 0.994±0.003, 8.844±2.495 mm, and 0.784±0.912 mm3, for the DSC, Hausdorff distance, and the AVD, respectively.

Protocol for evaluating the effects of a therapeutic foot exercise program on injury incidence, foot functionality and biomechanics in long-distance runners: a randomized controlled trial.

PubMed

Matias, Alessandra B; Taddei, Ulisses T; Duarte, Marcos; Sacco, Isabel C N

2016-04-14

Overall performance, particularly in a very popular sports activity such as running, is typically influenced by the status of the musculoskeletal system and the level of training and conditioning of the biological structures. Any change in the musculoskeletal system's biomechanics, especially in the feet and ankles, will strongly influence the biomechanics of runners, possibly predisposing them to injuries. A thorough understanding of the effects of a therapeutic approach focused on feet biomechanics, on strength and functionality of lower limb muscles will contribute to the adoption of more effective therapeutic and preventive strategies for runners. A randomized, prospective controlled and parallel trial with blind assessment is designed to study the effects of a "ground-up" therapeutic approach focused on the foot-ankle complex as it relates to the incidence of running-related injuries in the lower limbs. One hundred and eleven (111) healthy long-distance runners will be randomly assigned to either a control (CG) or intervention (IG) group. IG runners will participate in a therapeutic exercise protocol for the foot-ankle for 8 weeks, with 1 directly supervised session and 3 remotely supervised sessions per week. After the 8-week period, IG runners will keep exercising for the remaining 10 months of the study, supervised only by web-enabled software three times a week. At baseline, 2 months, 4 months and 12 months, all runners will be assessed for running-related injuries (primary outcome), time for the occurrence of the first injury, foot health and functionality, muscle trophism, intrinsic foot muscle strength, dynamic foot arch strain and lower-limb biomechanics during walking and running (secondary outcomes). This is the first randomized clinical trial protocol to assess the effect of an exercise protocol that was designed specifically for the foot-and-ankle complex on running-related injuries to the lower limbs of long-distance runners. We intend to show that the proposed protocol is an innovative and effective approach to decreasing the incidence of injuries. We also expect a lengthening in the time of occurrence of the first injury, an improvement in foot function, an increase in foot muscle mass and strength and beneficial biomechanical changes while running and walking after a year of exercising. Clinicaltrials.gov Identifier NCT02306148 (November 28, 2014) under the name "Effects of Foot Strengthening on the Prevalence of Injuries in Long Distance Runners". Committee of Ethics in Research of the School of Medicine of the University of Sao Paulo (18/03/2015, Protocol # 031/15).

The effect of increasing strength and approach velocity on triple jump performance.

PubMed

Allen, Sam J; Yeadon, M R Fred; King, Mark A

2016-12-08

The triple jump is an athletic event comprising three phases in which the optimal phase ratio (the proportion of each phase to the total distance jumped) is unknown. This study used a planar whole body torque-driven computer simulation model of the ground contact parts of all three phases of the triple jump to investigate the effect of strength and approach velocity on optimal performance. The strength and approach velocity of the simulation model were each increased by up to 30% in 10% increments from baseline data collected from a national standard triple jumper. Increasing strength always resulted in an increased overall jump distance. Increasing approach velocity also typically resulted in an increased overall jump distance but there was a point past which increasing approach velocity without increasing strength did not lead to an increase in overall jump distance. Increasing both strength and approach velocity by 10%, 20%, and 30% led to roughly equivalent increases in overall jump distances. Distances ranged from 14.05m with baseline strength and approach velocity, up to 18.49m with 30% increases in both. Optimal phase ratios were either hop-dominated or balanced, and typically became more balanced when the strength of the model was increased by a greater percentage than its approach velocity. The range of triple jump distances that resulted from the optimisation process suggests that strength and approach velocity are of great importance for triple jump performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

The structural and functional connectivity of the grassland plant Lychnis flos-cuculi

PubMed Central

Aavik, T; Holderegger, R; Bolliger, J

2014-01-01

Understanding the relationship between structural and functional connectivity is essential for successful restoration and conservation management, particularly in intensely managed agricultural landscapes. We evaluated the relationship between structural and functional connectivity of the wetland plant Lychnis flos-cuculi in a fragmented agricultural landscape using landscape genetic and network approaches. First, we studied the effect of structural connectivity, such as geographic distance and various landscape elements (forest, agricultural land, settlements and ditch verges), on gene flow among populations as a measurement of functional connectivity. Second, we examined the effect of structural graph-theoretic connectivity measures on gene flow among populations and on genetic diversity within populations of L. flos-cuculi. Among landscape elements, forests hindered gene flow in L. flos-cuculi, whereas gene flow was independent of geographic distance. Among the structural graph-theoretic connectivity variables, only intrapopulation connectivity, which was based on population size, had a significant positive effect on gene flow, that is, more gene flow took place among larger populations. Unexpectedly, interpopulation connectivity of populations, which takes into account the spatial location and distance among populations, did not influence gene flow in L. flos-cuculi. However, higher observed heterozygosity and lower inbreeding was observed in populations characterised by higher structural interpopulation connectivity. This finding shows that a spatially coherent network of populations is significant for maintaining the genetic diversity of populations. Nevertheless, lack of significant relationships between gene flow and most of the structural connectivity measures suggests that structural connectivity does not necessarily correspond to functional connectivity. PMID:24253937

Green’s functions for a volume source in an elastic half-space

PubMed Central

Zabolotskaya, Evgenia A.; Ilinskii, Yurii A.; Hay, Todd A.; Hamilton, Mark F.

2012-01-01

Green’s functions are derived for elastic waves generated by a volume source in a homogeneous isotropic half-space. The context is sources at shallow burial depths, for which surface (Rayleigh) and bulk waves, both longitudinal and transverse, can be generated with comparable magnitudes. Two approaches are followed. First, the Green’s function is expanded with respect to eigenmodes that correspond to Rayleigh waves. While bulk waves are thus ignored, this approximation is valid on the surface far from the source, where the Rayleigh wave modes dominate. The second approach employs an angular spectrum that accounts for the bulk waves and yields a solution that may be separated into two terms. One is associated with bulk waves, the other with Rayleigh waves. The latter is proved to be identical to the Green’s function obtained following the first approach. The Green’s function obtained via angular spectrum decomposition is analyzed numerically in the time domain for different burial depths and distances to the receiver, and for parameters relevant to seismo-acoustic detection of land mines and other buried objects. PMID:22423682

Hypothesis on the nature of time

NASA Astrophysics Data System (ADS)

Coumbe, D. N.

2015-06-01

We present numerical evidence that fictitious diffusing particles in the causal dynamical triangulation (CDT) approach to quantum gravity exceed the speed of light on small distance scales. We argue this superluminal behavior is responsible for the appearance of dimensional reduction in the spectral dimension. By axiomatically enforcing a scale invariant speed of light we show that time must dilate as a function of relative scale, just as it does as a function of relative velocity. By calculating the Hausdorff dimension of CDT diffusion paths we present a seemingly equivalent dual description in terms of a scale dependent Wick rotation of the metric. Such a modification to the nature of time may also have relevance for other approaches to quantum gravity.

Shot noise in parallel atomic wires from first principles

NASA Astrophysics Data System (ADS)

Lagerqvist, Johan; Chen, Yu-Chang; di Ventra, Massimiliano

2003-03-01

We report first-principles calculations of shot noise in two parallel carbon atomic wires as a function of the wires separation and length. The calculations have been performed with a novel field-theoretic approach to calculate shot noise [1] in terms of the single-particle wavefunctions obtained with density-functional theory.[2] We find that current fluctuations are a non-linear function of the distance between the wires and can be suppressed at wires separations small compared to the independent-wire distance. We discuss these results in terms of the coherence effects between the wires and the interference effects at the contacts. Work supported in part by NSF, Carilion Biomedical Institute and ACS-Petroleum Research Fund. [1] Y.-C. Chen and M. Di Ventra, submitted. [2] N.D. Lang, Phys. Rev. B 52, 5335 (1995); M. Di Ventra and N.D. Lang, Phys. Rev. B 65, 045402 (2002); Z. Yang, A. Tackett and M. Di Ventra, Phys. Rev. B 66, 041405 (2002).

Application of information-theoretic measures to quantitative analysis of immunofluorescent microscope imaging.

PubMed

Shutin, Dmitriy; Zlobinskaya, Olga

2010-02-01

The goal of this contribution is to apply model-based information-theoretic measures to the quantification of relative differences between immunofluorescent signals. Several models for approximating the empirical fluorescence intensity distributions are considered, namely Gaussian, Gamma, Beta, and kernel densities. As a distance measure the Hellinger distance and the Kullback-Leibler divergence are considered. For the Gaussian, Gamma, and Beta models the closed-form expressions for evaluating the distance as a function of the model parameters are obtained. The advantages of the proposed quantification framework as compared to simple mean-based approaches are analyzed with numerical simulations. Two biological experiments are also considered. The first is the functional analysis of the p8 subunit of the TFIIH complex responsible for a rare hereditary multi-system disorder--trichothiodystrophy group A (TTD-A). In the second experiment the proposed methods are applied to assess the UV-induced DNA lesion repair rate. A good agreement between our in vivo results and those obtained with an alternative in vitro measurement is established. We believe that the computational simplicity and the effectiveness of the proposed quantification procedure will make it very attractive for different analysis tasks in functional proteomics, as well as in high-content screening. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Jet-Track Correlation Studies in PbPb and pp at 5.02 TeV

NASA Astrophysics Data System (ADS)

Trauger, Hallie Causey; CMS Collaboration

2017-11-01

Jet-track correlations are used to extend measurements of the properties of jets beyond classic fixed-R jet reconstruction. New measurements with PbPb and pp collision data at √{sNN} = 5.02 TeV, recorded by CMS, are carried out using a statistical approach that allows for a reliable subtraction of the underlying event beyond the typical distance parameters of jet reconstruction. Measurements of correlated particle densities are extended out to ±1.5 units of relative azimuth and pseudorapidity. Double-differential measurements of jet fragmentation functions and jet shapes are presented up to radial distance of R=1 from the jet axis.

The Semantic Distance Task: Quantifying Semantic Distance with Semantic Network Path Length

ERIC Educational Resources Information Center

Kenett, Yoed N.; Levi, Effi; Anaki, David; Faust, Miriam

2017-01-01

Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We…

PANTHER. Trajectory Analysis

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

Rintoul, Mark Daniel; Wilson, Andrew T.; Valicka, Christopher G.

We want to organize a body of trajectories in order to identify, search for, classify and predict behavior among objects such as aircraft and ships. Existing compari- son functions such as the Fr'echet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as total distance traveled and distance be- tween start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generallymore » be mapped easily to behaviors of interest to humans that are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to iden- tify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories, predict destination and apply unsupervised machine learning algorithms.« less

Direct measurement of interaction forces between a single bacterium and a flat plate.

PubMed

Klein, Jonah D; Clapp, Aaron R; Dickinson, Richard B

2003-05-15

A technique for precisely measuring the equilibrium and viscous interaction forces between a single bacterium and a flat surface as functions of separation distance is described. A single-beam gradient optical trap was used to micromanipulate the bacterium against a flat surface while evanescent wave light scattering was used to measure separation distances. Calibrating the optical trap far from the surface allowed the trapped bacterium to be used as a force probe. Equilibrium force-distance profiles were determined by measuring the deflection of the cell from the center of the optical trap at various trap positions. Simultaneously, viscous forces were determined by measuring the relaxation time for the fluctuating bacterium. Absolute distances were determined using a best-fit approximation to the theoretical prediction for the hindered mobility of a diffusing sphere near a wall. Using this approach, forces in the range from 0.01 to 4 pN were measured at near-nanometer resolution between Staphylococcus aureus and glass that was bare or coated with adsorbed protein.

Occupational activity and cognitive reserve: implications in terms of prevention of cognitive aging and Alzheimer’s disease

PubMed Central

Adam, Stéphane; Bonsang, Eric; Grotz, Catherine; Perelman, Sergio

2013-01-01

This paper investigates the relationship between the concept of activity (including both professional and nonprofessional) and cognitive functioning among older European individuals. In this research, we used data collected during the first wave of SHARE (Survey on Health, Ageing and Retirement in Europe), and a measurement approach known as stochastic frontier analysis, derived from the economic literature. SHARE includes a large population (n > 25,000) geographically distributed across Europe, and analyzes several dimensions simultaneously, including physical and mental health activity. The main advantages of stochastic frontier analysis are that it allows estimation of parametric function relating cognitive scores and driving factors at the boundary and disentangles frontier noise and distance to frontier components, as well as testing the effect of potential factors on these distances simultaneously. The analysis reveals that all activities are positively related to cognitive functioning in elderly people. Our results are discussed in terms of prevention of cognitive aging and Alzheimer’s disease, and regarding the potential impact that some retirement programs might have on cognitive functioning in individuals across Europe. PMID:23671387

Suprathermal electron environment of comet 67P/Churyumov-Gerasimenko: Observations from the Rosetta Ion and Electron Sensor

NASA Astrophysics Data System (ADS)

Clark, G.; Broiles, T. W.; Burch, J. L.; Collinson, G. A.; Cravens, T.; Frahm, R. A.; Goldstein, J.; Goldstein, R.; Mandt, K.; Mokashi, P.; Samara, M.; Pollock, C. J.

2015-11-01

Context. The Rosetta spacecraft is currently escorting comet 67P/Churyumov-Gerasimenko until its perihelion approach at 1.2 AU. This mission has provided unprecedented views into the interaction of the solar wind and the comet as a function of heliocentric distance. Aims: We study the interaction of the solar wind and comet at large heliocentric distances (>2 AU) using data from the Rosetta Plasma Consortium Ion and Electron Sensor (RPC-IES). From this we gain insight into the suprathermal electron distribution, which plays an important role in electron-neutral chemistry and dust grain charging. Methods: Electron velocity distribution functions observed by IES fit to functions used to previously characterize the suprathermal electrons at comets and interplanetary shocks. We used the fitting results and searched for trends as a function of cometocentric and heliocentric distance. Results: We find that interaction of the solar wind with this comet is highly turbulent and stronger than expected based on historical studies, especially for this weakly outgassing comet. The presence of highly dynamical suprathermal electrons is consistent with observations of comets (e.g., Giacobinni-Zinner, Grigg-Skjellerup) near 1 AU with higher outgassing rates. However, comet 67P/Churyumov-Gerasimenko is much farther from the Sun and appears to lack an upstream bow shock. Conclusions: The mass loading process, which likely is the cause of these processes, plays a stronger role at large distances from the Sun than previously expected. We discuss the possible mechanisms that most likely are responsible for this acceleration: heating by waves generated by the pick-up ion instability, and the admixture of cometary photoelectrons.

Local structures around the substituted elements in mixed layered oxides

PubMed Central

Akama, Shota; Kobayashi, Wataru; Amaha, Kaoru; Niwa, Hideharu; Nitani, Hiroaki; Moritomo, Yutaka

2017-01-01

The chemical substitution of a transition metal (M) is an effective method to improve the functionality of a material, such as its electrochemical, magnetic, and dielectric properties. The substitution, however, causes local lattice distortion because the difference in the ionic radius (r) modifies the local interatomic distances. Here, we systematically investigated the local structures in the pure (x = 0.0) and mixed (x = 0.05 or 0.1) layered oxides, Na(M1−xM′x)O2 (M and M′ are the majority and minority transition metals, respectively), by means of extended X-ray absorption fine structure (EXAFS) analysis. We found that the local interatomic distance (dM-O) around the minority element approaches that around the majority element to reduces the local lattice distortion. We further found that the valence of the minority Mn changes so that its ionic radius approaches that of the majority M. PMID:28252008

A composite likelihood approach for spatially correlated survival data

PubMed Central

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450

Artificial immune system via Euclidean Distance Minimization for anomaly detection in bearings

NASA Astrophysics Data System (ADS)

Montechiesi, L.; Cocconcelli, M.; Rubini, R.

2016-08-01

In recent years new diagnostics methodologies have emerged, with particular interest into machinery operating in non-stationary conditions. In fact continuous speed changes and variable loads make non-trivial the spectrum analysis. A variable speed means a variable characteristic fault frequency related to the damage that is no more recognizable in the spectrum. To overcome this problem the scientific community proposed different approaches listed in two main categories: model-based approaches and expert systems. In this context the paper aims to present a simple expert system derived from the mechanisms of the immune system called Euclidean Distance Minimization, and its application in a real case of bearing faults recognition. The proposed method is a simplification of the original process, adapted by the class of Artificial Immune Systems, which proved to be useful and promising in different application fields. Comparative results are provided, with a complete explanation of the algorithm and its functioning aspects.

Classical electromagnetic fields from quantum sources in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Holliday, Robert; McCarty, Ryan; Peroutka, Balthazar; Tuchin, Kirill

2017-01-01

Electromagnetic fields are generated in high energy nuclear collisions by spectator valence protons. These fields are traditionally computed by integrating the Maxwell equations with point sources. One might expect that such an approach is valid at distances much larger than the proton size and thus such a classical approach should work well for almost the entire interaction region in the case of heavy nuclei. We argue that, in fact, the contrary is true: due to the quantum diffusion of the proton wave function, the classical approximation breaks down at distances of the order of the system size. We compute the electromagnetic field created by a charged particle described initially as a Gaussian wave packet of width 1 fm and evolving in vacuum according to the Klein-Gordon equation. We completely neglect the medium effects. We show that the dynamics, magnitude and even sign of the electromagnetic field created by classical and quantum sources are different.

A composite likelihood approach for spatially correlated survival data.

PubMed

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.

Drivers' Visual Search Behavior Toward Vulnerable Road Users at Junctions as a Function of Cycling Experience.

PubMed

Robbins, Chloe Jade; Chapman, Peter

2018-06-01

The current study investigated the behavior and visual attention of two groups of drivers with differing pedal cycling experience (pedal cyclists and nonpedal cyclists) towards vulnerable road users at junctions in a driving simulator. Pedal cyclists and motorcyclists are involved in a disproportionate number of crashes given the distance they travel, with a high proportion of these crashes occurring at junctions. Many studies have found that car drivers who also hold a motorcycle license have increased awareness towards motorcycles. The task involved approaching a T-junction and turning right when it was deemed to be safe. In Study 1, the junction was controlled by a give way sign, and in Study 2, the junction was controlled by a stop sign. Each T-junction contained a target vehicle (car, motorcycle, or pedal cycle), approaching from a near, medium, or far distance from the junction. Participants did not look at pedal cycles approaching from a far distance for as long as they looked at approaching motorcycles and cars, despite all vehicles travelling at identical speeds. No differences were found between pedal cyclists and nonpedal cyclists on any visual attention measures, indicating that pedal cycling experience was not associated with differences in drivers' attention toward pedal cycles. Findings have implications for road safety, demonstrating subtle differences in drivers' everyday visual attention toward differing vehicle types. This research has the potential to inform the development of in-car technical assistive systems, improving the safety of vulnerable road users at junctions.

Preliminary ground motion prediction equations for the Central and Eastern United States

NASA Astrophysics Data System (ADS)

Graizer, V.

2014-12-01

At the current stage I used the database created under the Next Generation Attenuations (NGA-East) project by Cramer et al. (2013). In contrast to the active tectonic environment in the Western US (WUS) the strong motion record database for the stable continental environment in the Central and Eastern US (CEUS) is not sufficient to create purely empirical ground motion prediction equations (GMPE) covering required for the PSHA magnitude (4.5

Correlation range in a supercooled liquid via Green-Kubo expression for viscosity, local atomic stresses, and MD simulations

NASA Astrophysics Data System (ADS)

Levashov, Valentin A.; Egami, Takeshi; Morris, James R.

2009-03-01

We present a new approach to the issue of correlation range in supercooled liquids based on Green-Kubo expression for viscosity. The integrand of this expression is the average stress-stress autocorrelation function. This correlation function could be rewritten in terms of correlations among local atomic stresses at different times and distances. The features of the autocorrelation function decay with time depend on temperature and correlation range. Through this approach we can study the development of spatial correlation with time, thus directly addressing the question of dynamic heterogeneity. We performed MD simulations on a single component system of particles interacting through short range pair potential. Our results indicate that even above the crossover temperature correlations extend well beyond the nearest neighbors. Surprisingly we found that the system size effects exist even on relatively large systems. We also address the role of diffusion in decay of stress-stress correlation function.

A nearest neighbour approach by genetic distance to the assignment of individual trees to geographic origin.

PubMed

Degen, Bernd; Blanc-Jolivet, Céline; Stierand, Katrin; Gillet, Elizabeth

2017-03-01

During the past decade, the use of DNA for forensic applications has been extensively implemented for plant and animal species, as well as in humans. Tracing back the geographical origin of an individual usually requires genetic assignment analysis. These approaches are based on reference samples that are grouped into populations or other aggregates and intend to identify the most likely group of origin. Often this grouping does not have a biological but rather a historical or political justification, such as "country of origin". In this paper, we present a new nearest neighbour approach to individual assignment or classification within a given but potentially imperfect grouping of reference samples. This method, which is based on the genetic distance between individuals, functions better in many cases than commonly used methods. We demonstrate the operation of our assignment method using two data sets. One set is simulated for a large number of trees distributed in a 120km by 120km landscape with individual genotypes at 150 SNPs, and the other set comprises experimental data of 1221 individuals of the African tropical tree species Entandrophragma cylindricum (Sapelli) genotyped at 61 SNPs. Judging by the level of correct self-assignment, our approach outperformed the commonly used frequency and Bayesian approaches by 15% for the simulated data set and by 5-7% for the Sapelli data set. Our new approach is less sensitive to overlapping sources of genetic differentiation, such as genetic differences among closely-related species, phylogeographic lineages and isolation by distance, and thus operates better even for suboptimal grouping of individuals. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

PubMed

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of multiplex gene expression maps obtained by voxelation.

PubMed

An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental results confirm the hypothesis that genes with similar gene expression maps might have similar gene functions. The voxelation data takes into account the location information of gene expression level in mouse brain, which is novel in related research. The proposed approach can potentially be used to predict gene functions and provide helpful suggestions to biologists.

Defining functional distance using manifold embeddings of gene ontology annotations

PubMed Central

Lerman, Gilad; Shakhnovich, Boris E.

2007-01-01

Although rigorous measures of similarity for sequence and structure are now well established, the problem of defining functional relationships has been particularly daunting. Here, we present several manifold embedding techniques to compute distances between Gene Ontology (GO) functional annotations and consequently estimate functional distances between protein domains. To evaluate accuracy, we correlate the functional distance to the well established measures of sequence, structural, and phylogenetic similarities. Finally, we show that manual classification of structures into folds and superfamilies is mirrored by proximity in the newly defined function space. We show how functional distances place structure–function relationships in biological context resulting in insight into divergent and convergent evolution. The methods and results in this paper can be readily generalized and applied to a wide array of biologically relevant investigations, such as accuracy of annotation transference, the relationship between sequence, structure, and function, or coherence of expression modules. PMID:17595300

XV-15 Tiltrotor Low Noise Approach Operations

NASA Technical Reports Server (NTRS)

Conner, David A.; Marcolini, Michael A.; Decker, William A.; Cline, John H.; Edwards, Bryan D.; Nicks, Colby O.; Klein, Peter D.

1999-01-01

Acoustic data have been acquired for the XV-15 tiltrotor aircraft performing approach operations for a variety of different approach profile configurations. This flight test program was conducted jointly by NASA, the U.S. Army, and Bell Helicopter Textron, Inc. (BHTI) in June 1997. The XV-15 was flown over a large area microphone array, which was deployed to directly measure the noise footprint produced during actual approach operations. The XV-15 flew realistic approach profiles that culminated in IGE hover over a landing pad. Aircraft tracking and pilot guidance was provided by a Differential Global Positioning System (DGPS) and a flight director system developed at BHTI. Approach profile designs emphasized noise reduction while maintaining handling qualities sufficient for tiltrotor commercial passenger ride comfort and flight safety under Instrument Flight Rules (IFR) conditions. A discussion of the approach profile design philosophy is provided. Five different approach profiles are discussed in detail -- 3 deg., 6 deg., and 9 deg. approaches, and two very different 3 deg. to 9 deg. segmented approaches. The approach profile characteristics are discussed in detail, followed by the noise footprints and handling qualities. Sound exposure levels are also presented on an averaged basis and as a function of the sideline distance for a number of up-range distances from the landing point. A comparison of the noise contour areas is also provided. The results document the variation in tiltrotor noise due to changes in operating condition, and indicate the potential for significant noise reduction using the unique tiltrotor capability of nacelle tilt.

Directional output distance functions: endogenous directions based on exogenous normalization constraints

USDA-ARS?s Scientific Manuscript database

In this paper we develop a model for computing directional output distance functions with endogenously determined direction vectors. We show how this model is related to the slacks-based directional distance function introduced by Fare and Grosskopf and show how to use the slacks-based function to e...

Unified treatment of the luminosity distance in cosmology

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

Yoo, Jaiyul; Scaccabarozzi, Fulvio, E-mail: jyoo@physik.uzh.ch, E-mail: fulvio@physik.uzh.ch

Comparing the luminosity distance measurements to its theoretical predictions is one of the cornerstones in establishing the modern cosmology. However, as shown in Biern and Yoo, its theoretical predictions in literature are often plagued with infrared divergences and gauge-dependences. This trend calls into question the sanity of the methods used to derive the luminosity distance. Here we critically investigate four different methods—the geometric approach, the Sachs approach, the Jacobi mapping approach, and the geodesic light cone (GLC) approach to modeling the luminosity distance, and we present a unified treatment of such methods, facilitating the comparison among the methods and checkingmore » their sanity. All of these four methods, if exercised properly, can be used to reproduce the correct description of the luminosity distance.« less

Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera

PubMed Central

Sim, Sungdae; Sock, Juil; Kwak, Kiho

2016-01-01

LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches. PMID:27338416

Evaluation of the influence of the internal aqueous solvent structure on electrostatic interactions at the protein-solvent interface by nonlocal continuum electrostatic approach.

PubMed

Rubinstein, Alexander; Sherman, Simon

The dielectric properties of the polar solvent on the protein-solvent interface at small intercharge distances are still poorly explored. To deconvolute this problem and to evaluate the pair-wise electrostatic interaction (PEI) energies of the point charges located at the protein-solvent interface we used a nonlocal (NL) electrostatic approach along with a static NL dielectric response function of water. The influence of the aqueous solvent microstructure (determined by a strong nonelectrostatic correlation effect between water dipoles within the orientational Debye polarization mode) on electrostatic interactions at the interface was studied in our work. It was shown that the PEI energies can be significantly higher than the energies evaluated by the classical (local) consideration, treating water molecules as belonging to the bulk solvent with a high dielectric constant. Our analysis points to the existence of a rather extended, effective low-dielectric interfacial water shell on the protein surface. The main dielectric properties of this shell (effective thickness together with distance- and orientation-dependent dielectric permittivity function) were evaluated. The dramatic role of this shell was demonstrated when estimating the protein association rate constants.

Assessing eco-efficiency: A metafrontier directional distance function approach using life cycle analysis

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

Beltrán-Esteve, Mercedes, E-mail: mercedes.beltran@uv.es; Reig-Martínez, Ernest; Estruch-Guitart, Vicent

Sustainability analysis requires a joint assessment of environmental, social and economic aspects of production processes. Here we propose the use of Life Cycle Analysis (LCA), a metafrontier (MF) directional distance function (DDF) approach, and Data Envelopment Analysis (DEA), to assess technological and managerial differences in eco-efficiency between production systems. We use LCA to compute six environmental and health impacts associated with the production processes of nearly 200 Spanish citrus farms belonging to organic and conventional farming systems. DEA is then employed to obtain joint economic-environmental farm's scores that we refer to as eco-efficiency. DDF allows us to determine farms' globalmore » eco-efficiency scores, as well as eco-efficiency scores with respect to specific environmental impacts. Furthermore, the use of an MF helps us to disentangle technological and managerial eco-inefficiencies by comparing the eco-efficiency of both farming systems with regards to a common benchmark. Our core results suggest that the shift from conventional to organic farming technology would allow a potential reduction in environmental impacts of 80% without resulting in any decline in economic performance. In contrast, as regards farmers' managerial capacities, both systems display quite similar mean scores.« less

The effect of sensor spacing on wind measurements at the Shuttle Landing Facility

NASA Technical Reports Server (NTRS)

Merceret, Francis J.

1995-01-01

This document presents results of a field study of the effect of sensor spacing on the validity of wind measurements at the Space Shuttle landing Facility (SLF). Standard measurements are made at one second intervals from 30 foot (9.1m) towers located 500 feet (152m) from the SLF centerline. The centerline winds are not exactly the same as those measured by the towers. This study quantifies the differences as a function of statistics of the observed winds and distance between the measurements and points of interest. The field program used logarithmically spaced portable wind towers to measure wind speed and direction over a range of conditions. Correlations, spectra, moments, and structure functions were computed. A universal normalization for structure functions was devised. The normalized structure functions increase as the 2/3 power of separation distance until an asymptotic value is approached. This occurs at spacings of several hundred feet (about 100m). At larger spacings, the structure functions are bounded by the asymptote. This enables quantitative estimates of the expected differences between the winds at the measurement point and the points of interest to be made from the measured wind statistics. A procedure is provided for making these estimates.

A specialized rehabilitation approach improves mobility in children with osteogenesis imperfecta.

PubMed

Hoyer-Kuhn, H; Semler, O; Stark, C; Struebing, N; Goebel, O; Schoenau, E

2014-12-01

Osteogenesis imperfecta (OI) is a rare disease leading to recurrent fractures, hyperlaxicity of ligaments, short stature and muscular weakness. Physiotherapy is one important treatment approach. The objective of our analysis was to evaluate the effect of a new physiotherapy approach including side alternating whole body vibration on motor function in children with OI. In a retrospective analysis data of 53 children were analyzed. The 12 months approach included 6 months of side alternating whole body vibration training, concomitant physiotherapy, resistance training, treadmill training and 6 months follow up. Primary outcome parameter was the Gross Motor Function Measure after 12 months (M12). 53 children (male: 32; age (mean±SEM): 9.1±0.61, range 2.54-24.81 years) participated in the treatment approach. A significant increase of motor function (GMFM-66 score 55.47±2.45 to 58.67±2.83; p=0.001) and walking distance (47.04 m±6.52 to 63.36±8.25 m (p<0.01) between M0 and M12 was seen. Total body without head bone mineral density increased significantly at M12 (p=0.0189). In the cohort of OI children which participated in the specialized treatment approach improvements of motor function were observed. Therefore this program should be considered as additional therapeutic approach for children with severe OI.

Characterizing left-right gait balance using footstep-induced structural vibrations

NASA Astrophysics Data System (ADS)

Fagert, Jonathon; Mirshekari, Mostafa; Pan, Shijia; Zhang, Pei; Noh, Hae Young

2017-04-01

In this paper, we introduce a method for estimating human left/right walking gait balance using footstep-induced structural vibrations. Understanding human gait balance is an integral component of assessing gait, neurological and musculoskeletal conditions, overall health status, and risk of falls. Existing techniques utilize pressure- sensing mats, wearable devices, and human observation-based assessment by healthcare providers. These existing methods are collectively limited in their operation and deployment; often requiring dense sensor deployment or direct user interaction. To address these limitations, we utilize footstep-induced structural vibration responses. Based on the physical insight that the vibration energy is a function of the force exerted by a footstep, we calculate the vibration signal energy due to a footstep and use it to estimate the footstep force. By comparing the footstep forces while walking, we determine balance. This approach enables non-intrusive gait balance assessment using sparsely deployed sensors. The primary research challenge is that the floor vibration signal energy is also significantly affected by the distance between the footstep location and the vibration sensor; this function is unclear in real-world scenarios and is a mixed function of wave propagation and structure-dependent properties. We overcome this challenge through footstep localization and incorporating structural factors into an analytical force-energy-distance function. This function is estimated through a nonlinear least squares regression analysis. We evaluate the performance of our method with a real-world deployment in a campus building. Our approach estimates footstep forces with a RMSE of 61.0N (8% of participant's body weight), representing a 1.54X improvement over the baseline.

The Bobath Concept in Walking Activity in Chronic Stroke Measured Through the International Classification of Functioning, Disability and Health.

PubMed

Benito García, Miguel; Atín Arratibel, María Ángeles; Terradillos Azpiroz, Maria Estíbaliz

2015-12-01

The aim of this study is to evaluate the effectiveness of a rehabilitation programme based on the Bobath concept in order to improve walking activity in patients with chronic stroke and to show the usefulness of the International Classification of Functioning, Disability and Health (ICF) as a tool for gathering functioning information. This study is a repeated measures study. The setting of this study is an outpatient neurological rehabilitation centre based on a multidisciplinary approach. Twenty-four participants suffering from chronic stroke (>1 year and a half and <5 years post-stroke) and mean age of 65.58 (standard deviation 10.73) were the participants of the study. Multidisciplinary approach based on the Bobath concept principles with three weekly individual physiotherapy sessions of 45 min each over a 6-month period was the intervention for this study. The measures used were Modified Emory Functional Ambulation Profile, 10-m walk test, 6-min walk test, muscle strength testing and subsequent codification of these results into ICF qualifiers. The results of the study showed significant improvement in activities of walking long distances, on different surfaces and around obstacles. There was no significant improvement in the activity of walking short distances or for muscle power functions. A rehabilitation programme based on the Bobath Concept improved walking activities in people with chronic stroke. For this intervention, the use of the ICF qualifiers was sensitive in perceiving post-treatment changes. Copyright © 2014 John Wiley & Sons, Ltd.

Comparison of propagation-based phase-contrast tomography approaches for the evaluation of dentin microstructure

NASA Astrophysics Data System (ADS)

Deyhle, Hans; Weitkamp, Timm; Lang, Sabrina; Schulz, Georg; Rack, Alexander; Zanette, Irene; Müller, Bert

2012-10-01

The complex hierarchical structure of human tooth hard tissues, enamel and dentin, guarantees function for decades. On the micrometer level the dentin morphology is dominated by the tubules, micrometer-narrow channels extending from the dentin-enamel junction to the pulp chamber. Their structure has been extensively studied, mainly with two-dimensional approaches. Dentin tubules are formed during tooth growth and their orientation is linked to the morphology of the nanometer-sized components, which is of interest for example for the development of bio-inspired dental fillings. Therefore, a method has to be identified that can access the three-dimensional organization of the tubules, e.g. density and orientation. Tomographic setups with pixel sizes in the sub-micrometer range allow for the three-dimensional visualization of tooth dentin tubules both in phase and absorption contrast modes. We compare high-resolution tomographic scans reconstructed with propagation based phase retrieval algorithms as well as reconstructions without phase retrieval concerning spatial and density resolution as well as rendering of the dentin microstructure to determine the approach best suited for dentin tubule imaging. Reasonable results were obtained with a single-distance phase retrieval algorithm and a propagation distance of about 75% of the critical distance of d2/λ, where d is the size of the smallest objects identifiable in the specimen and λ is the X-ray wavelength.

Plasmon Ruler with Ångstrom Length Resolution

PubMed Central

Hill, Ryan T.; Mock, Jack J.; Hucknall, Angus; Wolter, Scott D.; Jokerst, Nan M.; Smith, David R.; Chilkoti, Ashutosh

2012-01-01

We demonstrate a plasmon nanoruler using a coupled film-nanoparticle (film-NP) format that is well suited for investigating the sensitivity extremes of plasmonic coupling. Because it is relatively straightforward to functionalize bulk, surface plasmon supporting films such as gold, we are able to precisely control plasmonic gap dimensions by creating ultra-thin molecular spacer layers on the gold films, on top of which we immobilize plasmon resonant nanoparticles (NPs). Each immobilized NP becomes coupled to the underlying film and functions as a plasmon nanoruler, exhibiting a distance-dependent resonance red-shift in its peak plasmon wavelength as it approaches the film. Due to the uniformity of response from the film-NPs to separation distance, we are able to use extinction and scattering measurements from ensembles of film-NPs to characterize the coupling effect over a series of very short separation distances – ranging from 5 – 20 Å – and combine these measurements with similar data from larger separation distances extending out to 27 nm. We find that the film-NP plasmon nanoruler is extremely sensitive at very short film-NP separation distances, yielding spectral shifts as large as 5 nm for every 1 Å change in separation distance. The film-NP coupling at extremely small spacings is so uniform and reliable that we are able to usefully probe gap dimensions where the classical Drude model of the conducting electrons in the metals is no longer descriptive; for gap sizes smaller than a few nanometers, either quantum or semi-classical models of the carrier response must be employed to predict the observed wavelength shifts. We find that, despite the limitations, large field enhancements and extreme sensitivity persist down to even the smallest gap sizes. PMID:22966857

Plasmon ruler with angstrom length resolution.

PubMed

Hill, Ryan T; Mock, Jack J; Hucknall, Angus; Wolter, Scott D; Jokerst, Nan M; Smith, David R; Chilkoti, Ashutosh

2012-10-23

We demonstrate a plasmon nanoruler using a coupled film nanoparticle (film-NP) format that is well-suited for investigating the sensitivity extremes of plasmonic coupling. Because it is relatively straightforward to functionalize bulk surface plasmon supporting films, such as gold, we are able to precisely control plasmonic gap dimensions by creating ultrathin molecular spacer layers on the gold films, on top of which we immobilize plasmon resonant nanoparticles (NPs). Each immobilized NP becomes coupled to the underlying film and functions as a plasmon nanoruler, exhibiting a distance-dependent resonance red shift in its peak plasmon wavelength as it approaches the film. Due to the uniformity of response from the film-NPs to separation distance, we are able to use extinction and scattering measurements from ensembles of film-NPs to characterize the coupling effect over a series of very short separation distances-ranging from 5 to 20 Å-and combine these measurements with similar data from larger separation distances extending out to 27 nm. We find that the film-NP plasmon nanoruler is extremely sensitive at very short film-NP separation distances, yielding spectral shifts as large as 5 nm for every 1 Å change in separation distance. The film-NP coupling at extremely small spacings is so uniform and reliable that we are able to usefully probe gap dimensions where the classical Drude model of the conducting electrons in the metals is no longer descriptive; for gap sizes smaller than a few nanometers, either quantum or semiclassical models of the carrier response must be employed to predict the observed wavelength shifts. We find that, despite the limitations, large field enhancements and extreme sensitivity persist down to even the smallest gap sizes.

Adaptive distance metric learning for diffusion tensor image segmentation.

PubMed

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

PubMed Central

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

Comparative Issues and Methods in Organizational Diagnosis. Report II. The Decision Tree Approach.

DTIC Science & Technology

organizational diagnosis . The advantages and disadvantages of the decision-tree approach generally, and in this study specifically, are examined. A pre-test, using a civilian sample of 174 work groups with Survey of Organizations data, was conducted to assess various decision-tree classification criteria, in terms of their similarity to the distance function used by Bowers and Hausser (1977). The results suggested the use of a large developmental sample, which should result in more distinctly defined boundary lines between classification profiles. Also, the decision matrix

Assessment of imaging quality in magnified phase CT of human bone tissue at the nanoscale

NASA Astrophysics Data System (ADS)

Yu, Boliang; Langer, Max; Pacureanu, Alexandra; Gauthier, Remy; Follet, Helene; Mitton, David; Olivier, Cecile; Cloetens, Peter; Peyrin, Francoise

2017-10-01

Bone properties at all length scales have a major impact on the fracture risk in disease such as osteoporosis. However, quantitative 3D data on bone tissue at the cellular scale are still rare. Here we propose to use magnified X-ray phase nano-CT to quantify bone ultra-structure in human bone, on the new setup developed on the beamline ID16A at the ESRF, Grenoble. Obtaining 3D images requires the application of phase retrieval prior to tomographic reconstruction. Phase retrieval is an ill-posed problem for which various approaches have been developed. Since image quality has a strong impact on the further quantification of bone tissue, our aim here is to evaluate different phase retrieval methods for imaging bone samples at the cellular scale. Samples from femurs of female donors were scanned using magnified phase nano-CT at voxel sizes of 120 and 30 nm with an energy of 33 keV. Four CT scans at varying sample-to-detector distances were acquired for each sample. We evaluated three phase retrieval methods adapted to these conditions: Paganin's method at single distance, Paganin's method extended to multiple distances, and the contrast transfer function (CTF) approach for pure phase objects. These methods were used as initialization to an iterative refinement step. Our results based on visual and quantitative assessment show that the use of several distances (as opposed to single one) clearly improves image quality and the two multi-distance phase retrieval methods give similar results. First results on the segmentation of osteocyte lacunae and canaliculi from such images are presented.

Classification of Company Performance using Weighted Probabilistic Neural Network

NASA Astrophysics Data System (ADS)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

The quantum n-body problem in dimension d ⩾ n – 1: ground state

NASA Astrophysics Data System (ADS)

Miller, Willard, Jr.; Turbiner, Alexander V.; Escobar-Ruiz, M. A.

2018-05-01

We employ generalized Euler coordinates for the n body system in dimensional space, which consists of the centre-of-mass vector, relative (mutual) mass-independent distances r ij and angles as remaining coordinates. We prove that the kinetic energy of the quantum n-body problem for can be written as the sum of three terms: (i) kinetic energy of centre-of-mass, (ii) the second order differential operator which depends on relative distances alone and (iii) the differential operator which annihilates any angle-independent function. The operator has a large reflection symmetry group and in variables is an algebraic operator, which can be written in terms of generators of the hidden algebra . Thus, makes sense of the Hamiltonian of a quantum Euler–Arnold top in a constant magnetic field. It is conjectured that for any n, the similarity-transformed is the Laplace–Beltrami operator plus (effective) potential; thus, it describes a -dimensional quantum particle in curved space. This was verified for . After de-quantization the similarity-transformed becomes the Hamiltonian of the classical top with variable tensor of inertia in an external potential. This approach allows a reduction of the dn-dimensional spectral problem to a -dimensional spectral problem if the eigenfunctions depend only on relative distances. We prove that the ground state function of the n body problem depends on relative distances alone.

On the weight of indels in genomic distances

PubMed Central

2011-01-01

Background Classical approaches to compute the genomic distance are usually limited to genomes with the same content, without duplicated markers. However, differences in the gene content are frequently observed and can reflect important evolutionary aspects. A few polynomial time algorithms that include genome rearrangements, insertions and deletions (or substitutions) were already proposed. These methods often allow a block of contiguous markers to be inserted, deleted or substituted at once but result in distance functions that do not respect the triangular inequality and hence do not constitute metrics. Results In the present study we discuss the disruption of the triangular inequality in some of the available methods and give a framework to establish an efficient correction for two models recently proposed, one that includes insertions, deletions and double cut and join (DCJ) operations, and one that includes substitutions and DCJ operations. Conclusions We show that the proposed framework establishes the triangular inequality in both distances, by summing a surcharge on indel operations and on substitutions that depends only on the number of markers affected by these operations. This correction can be applied a posteriori, without interfering with the already available formulas to compute these distances. We claim that this correction leads to distances that are biologically more plausible. PMID:22151784

On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems

NASA Astrophysics Data System (ADS)

Junge, Oliver; Kevrekidis, Ioannis G.

2017-06-01

We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropriate distance between a suitably selected finite set of points and its image under the dynamics. We demonstrate, through computational experiments, that this approach can successfully converge to approximations of (maximal) invariant sets of arbitrary topology, dimension, and stability, such as, e.g., saddle type invariant sets with complicated dynamics. We further propose to extend this approach by adding a Lennard-Jones type potential term to the objective function, which yields more evenly distributed approximating finite point sets, and illustrate the procedure through corresponding numerical experiments.

On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems.

PubMed

Junge, Oliver; Kevrekidis, Ioannis G

2017-06-01

We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropriate distance between a suitably selected finite set of points and its image under the dynamics. We demonstrate, through computational experiments, that this approach can successfully converge to approximations of (maximal) invariant sets of arbitrary topology, dimension, and stability, such as, e.g., saddle type invariant sets with complicated dynamics. We further propose to extend this approach by adding a Lennard-Jones type potential term to the objective function, which yields more evenly distributed approximating finite point sets, and illustrate the procedure through corresponding numerical experiments.

Level set methods for detonation shock dynamics using high-order finite elements

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

Dobrev, V. A.; Grogan, F. C.; Kolev, T. V.

Level set methods are a popular approach to modeling evolving interfaces. We present a level set ad- vection solver in two and three dimensions using the discontinuous Galerkin method with high-order nite elements. During evolution, the level set function is reinitialized to a signed distance function to maintain ac- curacy. Our approach leads to stable front propagation and convergence on high-order, curved, unstructured meshes. The ability of the solver to implicitly track moving fronts lends itself to a number of applications; in particular, we highlight applications to high-explosive (HE) burn and detonation shock dynamics (DSD). We provide results for two-more » and three-dimensional benchmark problems as well as applications to DSD.« less

Reconsidering Dark Matter

NASA Astrophysics Data System (ADS)

Aisenberg, Sol

2012-02-01

There is a difference between (a) distances of remote standard candles, SN Type Ia, and (b) distances based upon their red shifts. It was believed that these galaxies had accelerated and used Dark Energy. There are 2 assumptions not supported by observations. The first is that the red shifts for remote galaxies are due to the Doppler Effect associated with receding velocity. Hubble only observed red shifts as a function of distances of known stars, and never measured receding velocities. He suggested the Doppler Effect as a cause, but expressed doubt about the suggestion. There are other causes for a red shift - gravity red shift of light from the sun, and loss of photon energy by gravity interaction of photons with dust and gas in interstellar space. The second assumption is that Hubble's linear relationship between the observed red shift and the distance will be valid at very large distances. Increasing red shift corresponds to a decrease of photon energy towards zero, and cannot be used for very remote stars - where the photon energy approaches zero and the red shift dependence becomes nonlinear and asymptotic to a constant value. This predicts the difference between the galaxy distances and the distances determined from their observed red shifts. The recent Nobel Prize (to Schmidt, Reis, and Perlmutter) needs reexamination. Two basic assumptions that are the foundation of their work may not be accurate. Details are in my earlier essays in ``The Misunderstood Universe'', 2009. .

Functionally relevant protein motions: Extracting basin-specific collective coordinates from molecular dynamics trajectories

NASA Astrophysics Data System (ADS)

Pan, Patricia Wang; Dickson, Russell J.; Gordon, Heather L.; Rothstein, Stuart M.; Tanaka, Shigenori

2005-01-01

Functionally relevant motion of proteins has been associated with a number of atoms moving in a concerted fashion along so-called "collective coordinates." We present an approach to extract collective coordinates from conformations obtained from molecular dynamics simulations. The power of this technique for differentiating local structural fuctuations between classes of conformers obtained by clustering is illustrated by analyzing nanosecond-long trajectories for the response regulator protein Spo0F of Bacillus subtilis, generated both in vacuo and using an implicit-solvent representation. Conformational clustering is performed using automated histogram filtering of the inter-Cα distances. Orthogonal (varimax) rotation of the vectors obtained by principal component analysis of these interresidue distances for the members of individual clusters is key to the interpretation of collective coordinates dominating each conformational class. The rotated loadings plots isolate significant variation in interresidue distances, and these are associated with entire mobile secondary structure elements. From this we infer concerted motions of these structural elements. For the Spo0F simulations employing an implicit-solvent representation, collective coordinates obtained in this fashion are consistent with the location of the protein's known active sites and experimentally determined mobile regions.

Visual and skill effects on soccer passing performance, kinematics, and outcome estimations

PubMed Central

Basevitch, Itay; Tenenbaum, Gershon; Land, William M.; Ward, Paul

2015-01-01

The role of visual information and action representations in executing a motor task was examined from a mental representations approach. High-skill (n = 20) and low-skill (n = 20) soccer players performed a passing task to two targets at distances of 9.14 and 18.29 m, under three visual conditions: normal, occluded, and distorted vision (i.e., +4.0 corrective lenses, a visual acuity of approximately 6/75) without knowledge of results. Following each pass, participants estimated the relative horizontal distance from the target as the ball crossed the target plane. Kinematic data during each pass were also recorded for the shorter distance. Results revealed that performance on the motor task decreased as a function of visual information and task complexity (i.e., distance from target) regardless of skill level. High-skill players performed significantly better than low-skill players on both the actual passing and estimation tasks, at each target distance and visual condition. In addition, kinematic data indicated that high-skill participants were more consistent and had different kinematic movement patterns than low-skill participants. Findings contribute to the understanding of the underlying mechanisms required for successful performance in a self-paced, discrete and closed motor task. PMID:25784886

A neural mechanism for detecting the distance of a selected target by modulating the FM sweep rate of biosonar in echolocation of bat.

PubMed

Kamata, Eigo; Inoue, Satoru; Zheng, MeiHong; Kashimori, Yoshiki; Kambara, Takeshi

2004-01-01

Most species of bats making echolocation use frequency modulated (FM) ultrasonic pulses to measure the distance to targets. These bats detect with a high accuracy the arrival time differences between emitted pulses and their echoes generated by targets. In order to clarify the neural mechanism for echolocation, we present neural model of inferior colliculus (IC), medial geniculate body (MGB) and auditory cortex (AC) along which information of echo delay times is processed. The bats increase the downward frequency sweep rate of emitted FM pulse as they approach the target. The functional role of this modulation of sweep rate is not yet clear. In order to investigate the role, we calculated the response properties of our models of IC, MGB, and AC changing the target distance and the sweep rate. We found based on the simulations that the distance of a target in various ranges may be encoded the most clearly into the activity pattern of delay time map network in AC, when the sweep rate of FM pulse used is coincided with the observed value which the bats adopt for each range of target distance.

Localized states in an arbitrarily bent quantum wire (bend-imitating approach)

NASA Astrophysics Data System (ADS)

Vakhnenko, Oleksity O.

1996-02-01

The bend-imitating matching technique is proposed to simplify the quantum mechanical treatment of singly and multiply bent 2D quantum wires of constant width, arbitrary bending angles, arbitrary bending radii and arbitrary distances between the bends. The spectrum of one-electron localized states and its dependence on the bending angle and the bending radius in a singly bent wire is explicitly calculated. Doubly bent wires are shown to possess doubly split localized states. The splitting energies as a function of the distance between the bends and the bending angles and bending radii have also been obtained. A similar description of bent 3D quantum wires and bent optical fibers is expected to be possible.

Learning deep features with adaptive triplet loss for person reidentification

NASA Astrophysics Data System (ADS)

Li, Zhiqiang; Sang, Nong; Chen, Kezhou; Gao, Changxin; Wang, Ruolin

2018-03-01

Person reidentification (re-id) aims to match a specified person across non-overlapping cameras, which remains a very challenging problem. While previous methods mostly focus on feature extraction or metric learning, this paper makes the attempt in jointly learning both the global full-body and local body-parts features of the input persons with a multichannel convolutional neural network (CNN) model, which is trained by an adaptive triplet loss function that serves to minimize the distance between the same person and maximize the distance between different persons. The experimental results show that our approach achieves very promising results on the large-scale Market-1501 and DukeMTMC-reID datasets.

The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia

PubMed Central

Vértes, Petra E.; Stidd, Reva; Lalonde, François; Clasen, Liv; Rapoport, Judith; Giedd, Jay; Bullmore, Edward T.; Gogtay, Nitin

2013-01-01

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive “pruning” of short-distance functional connections in schizophrenia. PMID:22275481

Site-to-Source Finite Fault Distance Probability Distribution in Probabilistic Seismic Hazard and the Relationship Between Minimum Distances

NASA Astrophysics Data System (ADS)

Ortega, R.; Gutierrez, E.; Carciumaru, D. D.; Huesca-Perez, E.

2017-12-01

We present a method to compute the conditional and no-conditional probability density function (PDF) of the finite fault distance distribution (FFDD). Two cases are described: lines and areas. The case of lines has a simple analytical solution while, in the case of areas, the geometrical probability of a fault based on the strike, dip, and fault segment vertices is obtained using the projection of spheres in a piecewise rectangular surface. The cumulative distribution is computed by measuring the projection of a sphere of radius r in an effective area using an algorithm that estimates the area of a circle within a rectangle. In addition, we introduce the finite fault distance metrics. This distance is the distance where the maximum stress release occurs within the fault plane and generates a peak ground motion. Later, we can apply the appropriate ground motion prediction equations (GMPE) for PSHA. The conditional probability of distance given magnitude is also presented using different scaling laws. A simple model of constant distribution of the centroid at the geometrical mean is discussed, in this model hazard is reduced at the edges because the effective size is reduced. Nowadays there is a trend of using extended source distances in PSHA, however it is not possible to separate the fault geometry from the GMPE. With this new approach, it is possible to add fault rupture models separating geometrical and propagation effects.

Orbital Transfer Vehicle Oxygen Turbopump Technology. Final Report, Volume 1. Design, Fabrication, and Hydrostatic Bearing Testing

DTIC Science & Technology

1990-12-01

Temperature Distance Sensors -. ...................... 188 Start Transient 4.5-7 Distance Sensor Signal as a Function of Speed...189 4.5-8 Distance Sensor Signal as a Function of Speed ......................................... 190 4.5-9 Cryogenic Operation of...Distance Sensors at 72,000 RPM ........................ 192 Steady State 4.5-10 Cryogenic Operation of Distance Sensor Through Start

Epizoochorous dispersal by ungulates depends on fur, grooming and social interactions.

PubMed

Liehrmann, Océane; Jégoux, Flore; Guilbert, Marie-Alice; Isselin-Nondedeu, Francis; Saïd, Sonia; Locatelli, Yann; Baltzinger, Christophe

2018-02-01

The transport phase of the animal-mediated plant dispersal process is critical to dispersal effectiveness as it determines the spatial distribution of the diaspores released and their chance for further recruitment. Assessing this specific phase of the dispersal process generally requires combining diaspore retention times with the associated distances covered. Here, we specifically tested the effect of grooming behavior, interindividual contacts and ungulate fur on diaspore retention times and associated dispersal distances for the hooked diaspores of Xanthium strumarium L. experimentally attached to tamed individuals of three ungulate species. We used a comparative approach based on differing fur quality on different body zones of these three ungulates. During 6-hr sessions, we monitored for grooming and social interactions that may induce intended or inadvertent diaspore detachment. Additionally, we proposed innovative approaches to directly assessing diaspore dispersal distances by red deer in situ. Fat-tailed functions fitted diaspore retention time, highlighting the potential for long-distance dispersal events. The longer the hair, the higher the retention capacity of diaspores in the animal's fur. As predicted, donkey retained diaspores longer than red deer and dwarf goat; and we also confirmed that diaspores attached to the short hair of the head fell off more quickly than did those on the other body zones. Dwarf goat groomed more often than both red deer and donkey, but also when it carried diaspores. Up to 14% of the diaspores detached from animal fur after specific grooming behavior. We observed, in controlled conditions, for the first time and for each ungulate species, interindividual transfers of diaspores, representing 5% of the diaspores attached to animals' fur. Our results militate for incorporating animal behavior into plant dispersal modeling approaches.

Characterizing highly dynamic conformational states: The transcription bubble in RNAP-promoter open complex as an example

NASA Astrophysics Data System (ADS)

Lerner, Eitan; Ingargiola, Antonino; Weiss, Shimon

2018-03-01

Bio-macromolecules carry out complicated functions through structural changes. To understand their mechanism of action, the structure of each step has to be characterized. While classical structural biology techniques allow the characterization of a few "structural snapshots" along the enzymatic cycle (usually of stable conformations), they do not cover all (and often fast interconverting) structures in the ensemble, where each may play an important functional role. Recently, several groups have demonstrated that structures of different conformations in solution could be solved by measuring multiple distances between different pairs of residues using single-molecule Förster resonance energy transfer (smFRET) and using them as constrains for hybrid/integrative structural modeling. However, this approach is limited in cases where the conformational dynamics is faster than the technique's temporal resolution. In this study, we combine existing tools that elucidate sub-millisecond conformational dynamics together with hybrid/integrative structural modeling to study the conformational states of the transcription bubble in the bacterial RNA polymerase-promoter open complex (RPo). We measured microsecond alternating laser excitation-smFRET of differently labeled lacCONS promoter dsDNA constructs. We used a combination of burst variance analysis, photon-by-photon hidden Markov modeling, and the FRET-restrained positioning and screening approach to identify two conformational states for RPo. The experimentally derived distances of one conformational state match the known crystal structure of bacterial RPo. The experimentally derived distances of the other conformational state have characteristics of a scrunched RPo. These findings support the hypothesis that sub-millisecond dynamics in the transcription bubble are responsible for transcription start site selection.

New Pedagogical Approaches to Improve Production of Materials in Distance Education.

ERIC Educational Resources Information Center

Mena, Marta

1992-01-01

Analyzes problems involved in the production of instructional materials for distance education and offers new pedagogical approaches to improve production of materials for distance education. Discusses past, present, and future methods used to design instructional materials, proposes models to aid in the production of instructional materials, and…

Research in Distance Education: A System Modeling Approach.

ERIC Educational Resources Information Center

Saba, Farhad; Twitchell, David

1988-01-01

Describes how a computer simulation research method can be used for studying distance education systems. Topics discussed include systems research in distance education; a technique of model development using the System Dynamics approach and DYNAMO simulation language; and a computer simulation of a prototype model. (18 references) (LRW)

The externally corrected coupled cluster approach with four- and five-body clusters from the CASSCF wave function.

PubMed

Xu, Enhua; Li, Shuhua

2015-03-07

An externally corrected CCSDt (coupled cluster with singles, doubles, and active triples) approach employing four- and five-body clusters from the complete active space self-consistent field (CASSCF) wave function (denoted as ecCCSDt-CASSCF) is presented. The quadruple and quintuple excitation amplitudes within the active space are extracted from the CASSCF wave function and then fed into the CCSDt-like equations, which can be solved in an iterative way as the standard CCSDt equations. With a size-extensive CASSCF reference function, the ecCCSDt-CASSCF method is size-extensive. When the CASSCF wave function is readily available, the computational cost of the ecCCSDt-CASSCF method scales as the popular CCSD method (if the number of active orbitals is small compared to the total number of orbitals). The ecCCSDt-CASSCF approach has been applied to investigate the potential energy surface for the simultaneous dissociation of two O-H bonds in H2O, the equilibrium distances and spectroscopic constants of 4 diatomic molecules (F2(+), O2(+), Be2, and NiC), and the reaction barriers for the automerization reaction of cyclobutadiene and the Cl + O3 → ClO + O2 reaction. In most cases, the ecCCSDt-CASSCF approach can provide better results than the CASPT2 (second order perturbation theory with a CASSCF reference function) and CCSDT methods.

Comparative epigenetic and genetic spatial structure of the perennial herb Helleborus foetidus: Isolation by environment, isolation by distance, and functional trait divergence.

PubMed

Herrera, Carlos M; Medrano, Mónica; Bazaga, Pilar

2017-08-16

Epigenetic variation can play a role in local adaptation; thus, there should be associations among epigenetic variation, environmental variation, and functional trait variation across populations. This study examines these relationships in the perennial herb Helleborus foetidus (Ranunculaceae). Plants from 10 subpopulations were characterized genetically (AFLP, SSR markers), epigenetically (MSAP markers), and phenotypically (20 functional traits). Habitats were characterized using six environmental variables. Isolation-by-distance (IBD) and isolation-by-environment (IBE) patterns of genetic and epigenetic divergence were assessed, as was the comparative explanatory value of geographical and environmental distance as predictors of epigenetic, genetic, and functional differentiation. Subpopulations were differentiated genetically, epigenetically, and phenotypically. Genetic differentiation was best explained by geographical distance, while epigenetic differentiation was best explained by environmental distance. Divergence in functional traits was correlated with environmental and epigenetic distances, but not with geographical and genetic distances. Results are compatible with the hypothesis that epigenetic IBE and functional divergence reflected responses to environmental variation. Spatial analyses simultaneously considering epigenetic, genetic, phenotypic and environmental information provide a useful tool to evaluate the role of environmental features as drivers of natural epigenetic variation between populations. © 2017 Botanical Society of America.

Geometric comparison of popular mixture-model distances.

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

Mitchell, Scott A.

2010-09-01

Statistical Latent Dirichlet Analysis produces mixture model data that are geometrically equivalent to points lying on a regular simplex in moderate to high dimensions. Numerous other statistical models and techniques also produce data in this geometric category, even though the meaning of the axes and coordinate values differs significantly. A distance function is used to further analyze these points, for example to cluster them. Several different distance functions are popular amongst statisticians; which distance function is chosen is usually driven by the historical preference of the application domain, information-theoretic considerations, or by the desirability of the clustering results. Relatively littlemore » consideration is usually given to how distance functions geometrically transform data, or the distances algebraic properties. Here we take a look at these issues, in the hope of providing complementary insight and inspiring further geometric thought. Several popular distances, {chi}{sup 2}, Jensen - Shannon divergence, and the square of the Hellinger distance, are shown to be nearly equivalent; in terms of functional forms after transformations, factorizations, and series expansions; and in terms of the shape and proximity of constant-value contours. This is somewhat surprising given that their original functional forms look quite different. Cosine similarity is the square of the Euclidean distance, and a similar geometric relationship is shown with Hellinger and another cosine. We suggest a geodesic variation of Hellinger. The square-root projection that arises in Hellinger distance is briefly compared to standard normalization for Euclidean distance. We include detailed derivations of some ratio and difference bounds for illustrative purposes. We provide some constructions that nearly achieve the worst-case ratios, relevant for contours.« less

The accuracy of assessment of walking distance in the elective spinal outpatients setting.

PubMed

Okoro, Tosan; Qureshi, Assad; Sell, Beulah; Sell, Philip

2010-02-01

Self reported walking distance is a clinically relevant measure of function. The aim of this study was to define patient accuracy and understand factors that might influence perceived walking distance in an elective spinal outpatients setting. A prospective cohort study. 103 patients were asked to perform one test of distance estimation and 2 tests of functional distance perception using pre-measured landmarks. Standard spine specific outcomes included the patient reported claudication distance, Oswestry disability index (ODI), Low Back Outcome Score (LBOS), visual analogue score (VAS) for leg and back, and other measures. There are over-estimators and under-estimators. Overall, the accuracy to within 9.14 metres (m) (10 yards) was poor at only 5% for distance estimation and 40% for the two tests of functional distance perception. Distance: Actual distance 111 m; mean response 245 m (95% CI 176.3-314.7), Functional test 1 actual distance 29.2 m; mean response 71.7 m (95% CI 53.6-88.9) Functional test 2 actual distance 19.6 m; mean response 47.4 m (95% CI 35.02-59.95). Surprisingly patients over 60 years of age (n = 43) are twice as accurate with each test performed compared to those under 60 (n = 60) (average 70% overestimation compared to 140%; p = 0.06). Patients in social class I (n = 18) were more accurate than those in classes II-V (n = 85): There was a positive correlation between poor accuracy and increasing MZD (Pearson's correlation coefficient 0.250; p = 0.012). ODI, LBOS and other parameters measured showed no correlation. Subjective distance perception and estimation is poor in this population. Patients over 60 and those with a professional background are more accurate but still poor.

Protein function prediction using neighbor relativity in protein-protein interaction network.

PubMed

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Van Vleet, Mary J.; Misquitta, Alston J.; Stone, Anthony J.

Short-range repulsion within inter-molecular force fields is conventionally described by either Lennard-Jones or Born-Mayer forms. Despite their widespread use, these simple functional forms are often unable to describe the interaction energy accurately over a broad range of inter-molecular distances, thus creating challenges in the development of ab initio force fields and potentially leading to decreased accuracy and transferability. Herein, we derive a novel short-range functional form based on a simple Slater-like model of overlapping atomic densities and an iterated stockholder atom (ISA) partitioning of the molecular electron density. We demonstrate that this Slater-ISA methodology yields a more accurate, transferable, andmore » robust description of the short-range interactions at minimal additional computational cost compared to standard Lennard-Jones or Born-Mayer approaches. Lastly, we show how this methodology can be adapted to yield the standard Born-Mayer functional form while still retaining many of the advantages of the Slater-ISA approach.« less

Modelling the Constraints of Spatial Environment in Fauna Movement Simulations: Comparison of a Boundaries Accurate Function and a Cost Function

NASA Astrophysics Data System (ADS)

Jolivet, L.; Cohen, M.; Ruas, A.

2015-08-01

Landscape influences fauna movement at different levels, from habitat selection to choices of movements' direction. Our goal is to provide a development frame in order to test simulation functions for animal's movement. We describe our approach for such simulations and we compare two types of functions to calculate trajectories. To do so, we first modelled the role of landscape elements to differentiate between elements that facilitate movements and the ones being hindrances. Different influences are identified depending on landscape elements and on animal species. Knowledge were gathered from ecologists, literature and observation datasets. Second, we analysed the description of animal movement recorded with GPS at fine scale, corresponding to high temporal frequency and good location accuracy. Analysing this type of data provides information on the relation between landscape features and movements. We implemented an agent-based simulation approach to calculate potential trajectories constrained by the spatial environment and individual's behaviour. We tested two functions that consider space differently: one function takes into account the geometry and the types of landscape elements and one cost function sums up the spatial surroundings of an individual. Results highlight the fact that the cost function exaggerates the distances travelled by an individual and simplifies movement patterns. The geometry accurate function represents a good bottom-up approach for discovering interesting areas or obstacles for movements.

Anesthesia modifies subthreshold critical slowing down in a stochastic Hodgkin-Huxley-like model with inhibitory synaptic input

NASA Astrophysics Data System (ADS)

Bukoski, Alex; Steyn-Ross, D. A.; Pickett, Ashley F.; Steyn-Ross, Moira L.

2018-06-01

The dynamics of a stochastic type-I Hodgkin-Huxley-like point neuron model exposed to inhibitory synaptic noise are investigated as a function of distance from spiking threshold and the inhibitory influence of the general anesthetic agent propofol. The model is biologically motivated and includes the effects of intrinsic ion-channel noise via a stochastic differential equation description as well as inhibitory synaptic noise modeled as multiple Poisson-distributed impulse trains with saturating response functions. The effect of propofol on these synapses is incorporated through this drug's principal influence on fast inhibitory neurotransmission mediated by γ -aminobutyric acid (GABA) type-A receptors via reduction of the synaptic response decay rate. As the neuron model approaches spiking threshold from below, we track membrane voltage fluctuation statistics of numerically simulated stochastic trajectories. We find that for a given distance from spiking threshold, increasing the magnitude of anesthetic-induced inhibition is associated with augmented signatures of critical slowing: fluctuation amplitudes and correlation times grow as spectral power is increasingly focused at 0 Hz. Furthermore, as a function of distance from threshold, anesthesia significantly modifies the power-law exponents for variance and correlation time divergences observable in stochastic trajectories. Compared to the inverse square root power-law scaling of these quantities anticipated for the saddle-node bifurcation of type-I neurons in the absence of anesthesia, increasing anesthetic-induced inhibition results in an observable exponent <-0.5 for variance and >-0.5 for correlation time divergences. However, these behaviors eventually break down as distance from threshold goes to zero with both the variance and correlation time converging to common values independent of anesthesia. Compared to the case of no synaptic input, linearization of an approximating multivariate Ornstein-Uhlenbeck model reveals these effects to be the consequence of an additional slow eigenvalue associated with synaptic activity that competes with those of the underlying point neuron in a manner that depends on distance from spiking threshold.

The Evolution of a Contextual Approach to Therapy: From Comprehensive Distancing to ACT

ERIC Educational Resources Information Center

Zettle, Robert D.

2011-01-01

This paper traces the developmental history of acceptance and commitment therapy (ACT) from its beginning as comprehensive distancing to its current form and status. It is maintained that technical differences between the two approaches are overshadowed by ones of conceptualization. Comprehensive distancing emerged from efforts to extend Skinner's…

Freeform lens generation for quasi-far-field successive illumination targets

NASA Astrophysics Data System (ADS)

Zhuang, Zhenfeng; Thibault, Simon

2018-07-01

A predefined mapping to tailor one or more freeform surfaces is employed to build a freeform illumination system. The emergent rays from the light source corresponding to the prescribed target mesh for a pre-determined lighting distance are mapped by a point-to-point algorithm with respect to the freeform optics, which involves limiting design flexibility. To tackle the problem of design limitation and find the optimum design results, a freeform lens is exploited to produce the desired rectangular illumination distribution at successive target planes at quasi-far-field lighting distances. It is generated using numerical solutions to find out an initial starting point, and an appropriate approach to obtain variables for parameterization of the freeform surface is introduced. The relative standard deviation, which is a useful figure of merit for the analysis, is set up as merit function with respect to illumination non-uniformity at the successive sampled target planes. Therefore, the irradiance distribution in terms of the specific lighting distance range can be ensured by the proposed scheme. A design example of a freeform illumination system, composed of a spherical surface and a freeform surface, is given to produce desired irradiance distribution within the lighting distance range. An optical performance with low non-uniformity and high efficiency is achieved. Compared with the conventional approach, the uniformity of the sampled targets is dramatically enhanced; meanwhile, a design result with a large tolerance of LED size is offered.

A Secondary Spatial Analysis of Gun Violence near Boston Schools: a Public Health Approach.

PubMed

Barboza, Gia

2018-06-01

School neighborhood violence continues to be a major public health problem among urban students. A large body of research addresses violence at school; however, fewer studies have explored concentrations of violence in areas proximal to schools. This study aimed to quantify the concentration of shootings near schools to elucidate the place-based dynamics that may be focal points for violence prevention. Geocoded databases of shooting and school locations were used to examine locational patterns of firearm shootings and elementary, middle, and high schools in Boston, Massachusetts. Analyses utilized spatial statistics for point pattern data including distance matrix and K function methodology to quantify the degree of spatial dependence of shootings around schools. Results suggested that between 2012 and 2015, there were 678 shooting incidents in Boston; the average density was 5.1 per square kilometer. The nearest neighbor index (NNI = 0.335 km, p < .001, O = 0.95 km, E = 0.28 km) and G function analysis revealed a clustered pattern of gun shooting incidents indicative of a spatially non-random process. The mean and median distance from any school to the nearest shooting location was 0.35 and 0.33 km, respectively. A majority (56%, 74/133) of schools in Boston had at least one shooting incident within 400 m, a distance that would take about 5 min to walk if traveling by foot. The bivariate K function indicated that a significantly greater number of shootings were clustered within short distances from schools than would be expected under a null hypothesis of no spatial dependence. Implications for students attending schools in racially homogenous neighborhoods across all income levels are discussed.

The cluster-cluster correlation function. [of galaxies

NASA Technical Reports Server (NTRS)

Postman, M.; Geller, M. J.; Huchra, J. P.

1986-01-01

The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.

A mixed-mode traffic assignment model with new time-flow impedance function

NASA Astrophysics Data System (ADS)

Lin, Gui-Hua; Hu, Yu; Zou, Yuan-Yang

2018-01-01

Recently, with the wide adoption of electric vehicles, transportation network has shown different characteristics and been further developed. In this paper, we present a new time-flow impedance function, which may be more realistic than the existing time-flow impedance functions. Based on this new impedance function, we present an optimization model for a mixed-mode traffic network in which battery electric vehicles (BEVs) and gasoline vehicles (GVs) are chosen. We suggest two approaches to handle the model: One is to use the interior point (IP) algorithm and the other is to employ the sequential quadratic programming (SQP) algorithm. Three numerical examples are presented to illustrate the efficiency of these approaches. In particular, our numerical results show that more travelers prefer to choosing BEVs when the distance limit of BEVs is long enough and the unit operating cost of GVs is higher than that of BEVs, and the SQP algorithm is faster than the IP algorithm.

B-spline tight frame based force matching method

NASA Astrophysics Data System (ADS)

Yang, Jianbin; Zhu, Guanhua; Tong, Dudu; Lu, Lanyuan; Shen, Zuowei

2018-06-01

In molecular dynamics simulations, compared with popular all-atom force field approaches, coarse-grained (CG) methods are frequently used for the rapid investigations of long time- and length-scale processes in many important biological and soft matter studies. The typical task in coarse-graining is to derive interaction force functions between different CG site types in terms of their distance, bond angle or dihedral angle. In this paper, an ℓ1-regularized least squares model is applied to form the force functions, which makes additional use of the B-spline wavelet frame transform in order to preserve the important features of force functions. The B-spline tight frames system has a simple explicit expression which is useful for representing our force functions. Moreover, the redundancy of the system offers more resilience to the effects of noise and is useful in the case of lossy data. Numerical results for molecular systems involving pairwise non-bonded, three and four-body bonded interactions are obtained to demonstrate the effectiveness of our approach.

Why GPS makes distances bigger than they are

PubMed Central

Ranacher, Peter; Brunauer, Richard; Trutschnig, Wolfgang; Van der Spek, Stefan; Reich, Siegfried

2016-01-01

ABSTRACT Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected. PMID:27019610

An Integrated Spin-Labeling/Computational-Modeling Approach for Mapping Global Structures of Nucleic Acids.

PubMed

Tangprasertchai, Narin S; Zhang, Xiaojun; Ding, Yuan; Tham, Kenneth; Rohs, Remo; Haworth, Ian S; Qin, Peter Z

2015-01-01

The technique of site-directed spin labeling (SDSL) provides unique information on biomolecules by monitoring the behavior of a stable radical tag (i.e., spin label) using electron paramagnetic resonance (EPR) spectroscopy. In this chapter, we describe an approach in which SDSL is integrated with computational modeling to map conformations of nucleic acids. This approach builds upon a SDSL tool kit previously developed and validated, which includes three components: (i) a nucleotide-independent nitroxide probe, designated as R5, which can be efficiently attached at defined sites within arbitrary nucleic acid sequences; (ii) inter-R5 distances in the nanometer range, measured via pulsed EPR; and (iii) an efficient program, called NASNOX, that computes inter-R5 distances on given nucleic acid structures. Following a general framework of data mining, our approach uses multiple sets of measured inter-R5 distances to retrieve "correct" all-atom models from a large ensemble of models. The pool of models can be generated independently without relying on the inter-R5 distances, thus allowing a large degree of flexibility in integrating the SDSL-measured distances with a modeling approach best suited for the specific system under investigation. As such, the integrative experimental/computational approach described here represents a hybrid method for determining all-atom models based on experimentally-derived distance measurements. © 2015 Elsevier Inc. All rights reserved.

An Integrated Spin-Labeling/Computational-Modeling Approach for Mapping Global Structures of Nucleic Acids

PubMed Central

Tangprasertchai, Narin S.; Zhang, Xiaojun; Ding, Yuan; Tham, Kenneth; Rohs, Remo; Haworth, Ian S.; Qin, Peter Z.

2015-01-01

The technique of site-directed spin labeling (SDSL) provides unique information on biomolecules by monitoring the behavior of a stable radical tag (i.e., spin label) using electron paramagnetic resonance (EPR) spectroscopy. In this chapter, we describe an approach in which SDSL is integrated with computational modeling to map conformations of nucleic acids. This approach builds upon a SDSL tool kit previously developed and validated, which includes three components: (i) a nucleotide-independent nitroxide probe, designated as R5, which can be efficiently attached at defined sites within arbitrary nucleic acid sequences; (ii) inter-R5 distances in the nanometer range, measured via pulsed EPR; and (iii) an efficient program, called NASNOX, that computes inter-R5 distances on given nucleic acid structures. Following a general framework of data mining, our approach uses multiple sets of measured inter-R5 distances to retrieve “correct” all-atom models from a large ensemble of models. The pool of models can be generated independently without relying on the inter-R5 distances, thus allowing a large degree of flexibility in integrating the SDSL-measured distances with a modeling approach best suited for the specific system under investigation. As such, the integrative experimental/computational approach described here represents a hybrid method for determining all-atom models based on experimentally-derived distance measurements. PMID:26477260

Topology guided demons registration with local rigidity preservation.

PubMed

Chaojie Zheng; Xiuying Wang; Dagan Feng

2016-08-01

Demons has been well recognized for its deformable registration capability. However, it might lead to misregistration due to the large spatial distance between the expected corresponding contents or erroneous diffusion tendency. In this paper, we propose a new energy function with topology energy, distance function and demons energy for deformable registration. The new energy function incorporates topological relationships to guide the correct diffusion and deformation, and contributes to local rigidity preservation. The distance function contributes to pulling the corresponding regions into accurate alignment despite of a possible large distance gap. The method was validated on synthetic, phantom and real medical image data.

Exogenous testosterone decreases men's personal distance in a social threat context.

PubMed

Wagels, Lisa; Radke, Sina; Goerlich, Katharina Sophia; Habel, Ute; Votinov, Mikhail

2017-04-01

Testosterone can motivate human approach and avoidance behavior. Specifically, the conscious recognition of and implicit reaction to angry facial expressions is influenced by testosterone. The study tested whether exogenous testosterone modulates the personal distance (PD) humans prefer in a social threat context. 82 healthy male participants underwent either transdermal testosterone (testosterone group) or placebo application (placebo group). Each participant performed a computerized stop-distance task before (T1) and 3.5h after (T2) treatment, during which they indicated how closely they would approach a human, animal or virtual character with varying emotional expression. Men's PD towards humans and animals varied as a function of their emotional expression. In the testosterone group, a pre-post comparison indicated that the administration of 50mg testosterone was associated with a small but significant reduction of men's PD towards aggressive individuals. Men in the placebo group did not change the initially chosen PD after placebo application independent of the condition. However comparing the testosterone and placebo group after testosterone administration did not reveal significant differences. While the behavioral effect was small and only observed as within-group effect it was repeatedly and selectively shown for men's PD choices towards an angry woman, angry man and angry dog in the testosterone group. In line with the literature, our findings in young men support the influential role of exogenous testosterone on male's approach behavior during social confrontations. Copyright © 2017 Elsevier Inc. All rights reserved.

Big geo data surface approximation using radial basis functions: A comparative study

NASA Astrophysics Data System (ADS)

Majdisova, Zuzana; Skala, Vaclav

2017-12-01

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in n-dimensional space. It is a non-separable approximation, as it is based on the distance between two points. This method leads to the solution of an overdetermined linear system of equations. In this paper the RBF approximation methods are briefly described, a new approach to the RBF approximation of big datasets is presented, and a comparison for different Compactly Supported RBFs (CS-RBFs) is made with respect to the accuracy of the computation. The proposed approach uses symmetry of a matrix, partitioning the matrix into blocks and data structures for storage of the sparse matrix. The experiments are performed for synthetic and real datasets.

Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities †

PubMed Central

Murdani, Muhammad Harist; Hong, Bonghee

2018-01-01

In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc) and neighborhood proximity (Top-K). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space. PMID:29587366

Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities †.

PubMed

Murdani, Muhammad Harist; Kwon, Joonho; Choi, Yoon-Ho; Hong, Bonghee

2018-03-24

In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes ( Ad-Hoc ) and neighborhood proximity ( Top-K ). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Physical adsorption at the nanoscale: Towards controllable scaling of the substrate-adsorbate van der Waals interaction

NASA Astrophysics Data System (ADS)

Ambrosetti, Alberto; Silvestrelli, Pier Luigi; Tkatchenko, Alexandre

2017-06-01

The Lifshitz-Zaremba-Kohn (LZK) theory is commonly considered as the correct large-distance limit for the van der Waals (vdW) interaction of adsorbates (atoms, molecules, or nanoparticles) with solid substrates. In the standard approximate form, implicitly based on local dielectric functions, the LZK approach predicts universal power laws for vdW interactions depending only on the dimensionality of the interacting objects. However, recent experimental findings are challenging the universality of this theoretical approach at finite distances of relevance for nanoscale assembly. Here, we present a combined analytical and numerical many-body study demonstrating that physical adsorption can be significantly enhanced at the nanoscale. Regardless of the band gap or the nature of the adsorbate specie, we find deviations from conventional LZK power laws that extend to separation distances of up to 10-20 nm. Comparison with recent experimental observations of ultra-long-ranged vdW interactions in the delamination of graphene from a silicon substrate reveals qualitative agreement with the present theory. The sensitivity of vdW interactions to the substrate response and to the adsorbate characteristic excitation frequency also suggests that adsorption strength can be effectively tuned in experiments, paving the way to an improved control of physical adsorption at the nanoscale.

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

Master curves and radial distribution functions for shear dilatancy of liquid n-hexadecane via nonequilibrium molecular dynamics simulations.

PubMed

Tseng, Huan-Chang; Wu, Jiann-Shing; Chang, Rong-Yeu

2009-04-28

Shear dilatancy, a significant nonlinear behavior of nonequilibrium thermodynamics states, has been observed in nonequilibrium molecular dynamics (NEMD) simulations for liquid n-hexadecane fluid under extreme shear conditions. The existence of shear dilatancy is relevant to the relationship between the imposed shear rate gamma and the critical shear rate gamma(c). Consequently, as gammagamma(c), the intermolecular distance is lengthened substantially by strong shear deformation breaking the equilibrium thermodynamic state so that shear dilatancy takes place. Notably, a characteristic shear rate gamma(m), which depends on the root mean square molecular velocity and the average free molecular distance, is found in nonequilibrium thermodynamics state curves. Studies of the variations in the intermolecular radial distribution function (RDF) with respect to the shear rate provide a direct measure of the variation in the degree of intermolecular separation. Additionally, the variations of the RDF curve in the microscopic regime are consistent with those of the nonequilibrium thermodynamic state in the macroscopic world. By inspecting the overall shape of the RDF curve, it can be readily corroborated that the fluid of interest exists in the liquid state. More importantly, both primary characteristic values, the equilibrium thermodynamic state variable and a particular shear rate of gamma(p), are determined cautiously, with gamma(p) depending on the gamma(m) value and the square root of pressure. Thereby, the nonequilibrium thermodynamic state curves can be normalized as temperature-, pressure-, and density-invariant master curves, formulated by applying the Cross constitutive equation. Clearly, gamma(c) occurs at which a reduced shear rate gamma/gamma(p) approaches 0.1. Furthermore, the trends in the rates of shear dilatancy in both the constant-pressure and constant-volume NEMD systems under isothermal conditions conform to the cyclic rule of pressure, as a function of density and shear rate.

DD-HDS: A method for visualization and exploration of high-dimensional data.

PubMed

Lespinats, Sylvain; Verleysen, Michel; Giron, Alain; Fertil, Bernard

2007-09-01

Mapping high-dimensional data in a low-dimensional space, for example, for visualization, is a problem of increasingly major concern in data analysis. This paper presents data-driven high-dimensional scaling (DD-HDS), a nonlinear mapping method that follows the line of multidimensional scaling (MDS) approach, based on the preservation of distances between pairs of data. It improves the performance of existing competitors with respect to the representation of high-dimensional data, in two ways. It introduces (1) a specific weighting of distances between data taking into account the concentration of measure phenomenon and (2) a symmetric handling of short distances in the original and output spaces, avoiding false neighbor representations while still allowing some necessary tears in the original distribution. More precisely, the weighting is set according to the effective distribution of distances in the data set, with the exception of a single user-defined parameter setting the tradeoff between local neighborhood preservation and global mapping. The optimization of the stress criterion designed for the mapping is realized by "force-directed placement" (FDP). The mappings of low- and high-dimensional data sets are presented as illustrations of the features and advantages of the proposed algorithm. The weighting function specific to high-dimensional data and the symmetric handling of short distances can be easily incorporated in most distance preservation-based nonlinear dimensionality reduction methods.

Selecting Research Areas and Research Design Approaches in Distance Education: Process Issues

ERIC Educational Resources Information Center

Passi, B. K.; Mishra, Sudarshan

2004-01-01

The purpose of this paper is to study the process used for selecting research areas and methodological approaches in distance education in India. Experts from the field of distance education in India were interviewed at length, with the aim of collecting qualitative data on opinions on process-issues for selecting areas for research, research…

The Hybridization of Distance Learning in Brazil: An Approach Imposed by Culture.

ERIC Educational Resources Information Center

Litto, Fredric Michael

2002-01-01

Higher education institutions in Brazil are seriously behind in the use of distance education largely because of the highly centralized control by the Ministry of Education. Hybridization, or the combination of face-to-face and distance learning techniques, is not motivated by pedagogical choice, but rather the only legally permitted approach in…

Insensitivity of The Distance Ladder Hubble Constant Determination to Cepheid Calibration Modeling Choices

NASA Astrophysics Data System (ADS)

Follin, B.; Knox, L.

2018-03-01

Recent determination of the Hubble constant via Cepheid-calibrated supernovae by Riess et al. (2016) (R16) find ˜3σ tension with inferences based on cosmic microwave background temperature and polarization measurements from Planck. This tension could be an indication of inadequacies in the concordance ΛCDM model. Here we investigate the possibility that the discrepancy could instead be due to systematic bias or uncertainty in the Cepheid calibration step of the distance ladder measurement by R16. We consider variations in total-to-selective extinction of Cepheid flux as a function of line-of-sight, hidden structure in the period-luminosity relationship, and potentially different intrinsic colour distributions of Cepheids as a function of host galaxy. Considering all potential sources of error, our final determination of H0 = 73.3 ± 1.7 km/s/Mpc (not including systematic errors from the treatment of geometric distances or Type Ia Supernovae) shows remarkable robustness and agreement with R16. We conclude systematics from the modelling of Cepheid photometry, including Cepheid selection criteria, cannot explain the observed tension between Cepheid-variable and CMB-based inferences of the Hubble constant. Considering a `model-independent' approach to relating Cepheids in galaxies with known distances to Cepheids in galaxies hosting a Type Ia supernova and finding agreement with the R16 result, we conclude no generalization of the model relating anchor and host Cepheid magnitude measurements can introduce significant bias in the H0 inference.

Insensitivity of the distance ladder Hubble constant determination to Cepheid calibration modelling choices

NASA Astrophysics Data System (ADS)

Follin, B.; Knox, L.

2018-07-01

Recent determination of the Hubble constant via Cepheid-calibrated supernovae by Riess et al.find ˜3σ tension with inferences based on cosmic microwave background (CMB) temperature and polarization measurements from Planck. This tension could be an indication of inadequacies in the concordance Λcold dark matter model. Here, we investigate the possibility that the discrepancy could instead be due to systematic bias or uncertainty in the Cepheid calibration step of the distance ladder measurement by Riess et al. We consider variations in total-to-selective extinction of Cepheid flux as a function of line of sight, hidden structure in the period-luminosity relationship, and potentially different intrinsic colour distributions of Cepheids as a function of host galaxy. Considering all potential sources of error, our final determination of H0 = 73.3 ± 1.7 km s-1Mpc-1 (not including systematic errors from the treatment of geometric distances or Type Ia supernovae) shows remarkable robustness and agreement with Riess et al. We conclude systematics from the modelling of Cepheid photometry, including Cepheid selection criteria, cannot explain the observed tension between Cepheid-variable and CMB-based inferences of the Hubble constant. Considering a `model-independent' approach to relating Cepheids in galaxies with known distances to Cepheids in galaxies hosting a Type Ia supernova and finding agreement with the Riess et al. result, we conclude no generalization of the model relating anchor and host Cepheid magnitude measurements can introduce significant bias in the H0 inference.

Fluorescence-based classification of Caribbean coral reef organisms and substrates

USGS Publications Warehouse

Zawada, David G.; Mazel, Charles H.

2014-01-01

A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: ‘optimally-picked’ and ‘evenly-spaced.’ The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled water-column attenuation. The classification results from both tests indicate that a high degree of separability among the 15 fluorescent-spectra functional groups is possible using only a modest number of spectral bands.

Spatio-temporal analysis of aftershock sequences in terms of Non Extensive Statistical Physics.

NASA Astrophysics Data System (ADS)

Chochlaki, Kalliopi; Vallianatos, Filippos

2017-04-01

Earth's seismicity is considered as an extremely complicated process where long-range interactions and fracturing exist (Vallianatos et al., 2016). For this reason, in order to analyze it, we use an innovative methodological approach, introduced by Tsallis (Tsallis, 1988; 2009), named Non Extensive Statistical Physics. This approach introduce a generalization of the Boltzmann-Gibbs statistical mechanics and it is based on the definition of Tsallis entropy Sq, which maximized leads the the so-called q-exponential function that expresses the probability distribution function that maximizes the Sq. In the present work, we utilize the concept of Non Extensive Statistical Physics in order to analyze the spatiotemporal properties of several aftershock series. Marekova (Marekova, 2014) suggested that the probability densities of the inter-event distances between successive aftershocks follow a beta distribution. Using the same data set we analyze the inter-event distance distribution of several aftershocks sequences in different geographic regions by calculating non extensive parameters that determine the behavior of the system and by fitting the q-exponential function, which expresses the degree of non-extentivity of the investigated system. Furthermore, the inter-event times distribution of the aftershocks as well as the frequency-magnitude distribution has been analyzed. The results supports the applicability of Non Extensive Statistical Physics ideas in aftershock sequences where a strong correlation exists along with memory effects. References C. Tsallis, Possible generalization of Boltzmann-Gibbs statistics, J. Stat. Phys. 52 (1988) 479-487. doi:10.1007/BF01016429 C. Tsallis, Introduction to nonextensive statistical mechanics: Approaching a complex world, 2009. doi:10.1007/978-0-387-85359-8. E. Marekova, Analysis of the spatial distribution between successive earthquakes in aftershocks series, Annals of Geophysics, 57, 5, doi:10.4401/ag-6556, 2014 F. Vallianatos, G. Papadakis, G. Michas, Generalized statistical mechanics approaches to earthquakes and tectonics. Proc. R. Soc. A, 472, 20160497, 2016.

Benchmarking Distance Control and Virtual Drilling for Lateral Skull Base Surgery.

PubMed

Voormolen, Eduard H J; Diederen, Sander; van Stralen, Marijn; Woerdeman, Peter A; Noordmans, Herke Jan; Viergever, Max A; Regli, Luca; Robe, Pierre A; Berkelbach van der Sprenkel, Jan Willem

2018-01-01

Novel audiovisual feedback methods were developed to improve image guidance during skull base surgery by providing audiovisual warnings when the drill tip enters a protective perimeter set at a distance around anatomic structures ("distance control") and visualizing bone drilling ("virtual drilling"). To benchmark the drill damage risk reduction provided by distance control, to quantify the accuracy of virtual drilling, and to investigate whether the proposed feedback methods are clinically feasible. In a simulated surgical scenario using human cadavers, 12 unexperienced users (medical students) drilled 12 mastoidectomies. Users were divided into a control group using standard image guidance and 3 groups using distance control with protective perimeters of 1, 2, or 3 mm. Damage to critical structures (sigmoid sinus, semicircular canals, facial nerve) was assessed. Neurosurgeons performed another 6 mastoidectomy/trans-labyrinthine and retro-labyrinthine approaches. Virtual errors as compared with real postoperative drill cavities were calculated. In a clinical setting, 3 patients received lateral skull base surgery with the proposed feedback methods. Users drilling with distance control protective perimeters of 3 mm did not damage structures, whereas the groups using smaller protective perimeters and the control group injured structures. Virtual drilling maximum cavity underestimations and overestimations were 2.8 ± 0.1 and 3.3 ± 0.4 mm, respectively. Feedback methods functioned properly in the clinical setting. Distance control reduced the risks of drill damage proportional to the protective perimeter distance. Errors in virtual drilling reflect spatial errors of the image guidance system. These feedback methods are clinically feasible. Copyright © 2017 Elsevier Inc. All rights reserved.

The sensory ecology of ocean navigation.

PubMed

Lohmann, Kenneth J; Lohmann, Catherine M F; Endres, Courtney S

2008-06-01

How animals guide themselves across vast expanses of open ocean, sometimes to specific geographic areas, has remained an enduring mystery of behavioral biology. In this review we briefly contrast underwater oceanic navigation with terrestrial navigation and summarize the advantages and constraints of different approaches used to analyze animal navigation in the sea. In addition, we highlight studies and techniques that have begun to unravel the sensory cues that underlie navigation in sea turtles, salmon and other ocean migrants. Environmental signals of importance include geomagnetic, chemical and hydrodynamic cues, perhaps supplemented in some cases by celestial cues or other sources of information that remain to be discovered. An interesting similarity between sea turtles and salmon is that both have been hypothesized to complete long-distance reproductive migrations using navigational systems composed of two different suites of mechanisms that function sequentially over different spatial scales. The basic organization of navigation in these two groups of animals may be functionally similar, and perhaps also representative of other long-distance ocean navigators.

Josephson coupling between superconducting islands on single- and bi-layer graphene

NASA Astrophysics Data System (ADS)

Mancarella, Francesco; Fransson, Jonas; Balatsky, Alexander

2016-05-01

We study the Josephson coupling of superconducting (SC) islands through the surface of single-layer graphene (SLG) and bilayer graphene (BLG) in the long-junction regime, as a function of the distance between the grains, temperature, chemical potential and external (transverse) gate-voltage. For SLG, we provide a comparison with existing literature. The proximity effect is analyzed through a Matsubara Green’s function approach. This represents the first step in a discussion of the conditions for the onset of a granular superconductivity within the film, made possible by Josephson currents flowing between superconductors. To ensure phase coherence over the 2D sample, a random spatial distribution can be assumed for the SC islands on the SLG sheet (or intercalating the BLG sheets). The tunable gate-voltage-induced band gap of BLG affects the asymptotic decay of the Josephson coupling-distance characteristic for each pair of SC islands in the sample, which results in a qualitatively strong field dependence of the relation between Berezinskii-Kosterlitz-Thouless transition critical temperature and gate voltage.

Detectability in Audio-Visual Surveys of Tropical Rainforest Birds: The Influence of Species, Weather and Habitat Characteristics.

PubMed

Anderson, Alexander S; Marques, Tiago A; Shoo, Luke P; Williams, Stephen E

2015-01-01

Indices of relative abundance do not control for variation in detectability, which can bias density estimates such that ecological processes are difficult to infer. Distance sampling methods can be used to correct for detectability, but in rainforest, where dense vegetation and diverse assemblages complicate sampling, information is lacking about factors affecting their application. Rare species present an additional challenge, as data may be too sparse to fit detection functions. We present analyses of distance sampling data collected for a diverse tropical rainforest bird assemblage across broad elevational and latitudinal gradients in North Queensland, Australia. Using audio and visual detections, we assessed the influence of various factors on Effective Strip Width (ESW), an intuitively useful parameter, since it can be used to calculate an estimate of density from count data. Body size and species exerted the most important influence on ESW, with larger species detectable over greater distances than smaller species. Secondarily, wet weather and high shrub density decreased ESW for most species. ESW for several species also differed between summer and winter, possibly due to seasonal differences in calling behavior. Distance sampling proved logistically intensive in these environments, but large differences in ESW between species confirmed the need to correct for detection probability to obtain accurate density estimates. Our results suggest an evidence-based approach to controlling for factors influencing detectability, and avenues for further work including modeling detectability as a function of species characteristics such as body size and call characteristics. Such models may be useful in developing a calibration for non-distance sampling data and for estimating detectability of rare species.

Detectability in Audio-Visual Surveys of Tropical Rainforest Birds: The Influence of Species, Weather and Habitat Characteristics

PubMed Central

Anderson, Alexander S.; Marques, Tiago A.; Shoo, Luke P.; Williams, Stephen E.

2015-01-01

Indices of relative abundance do not control for variation in detectability, which can bias density estimates such that ecological processes are difficult to infer. Distance sampling methods can be used to correct for detectability, but in rainforest, where dense vegetation and diverse assemblages complicate sampling, information is lacking about factors affecting their application. Rare species present an additional challenge, as data may be too sparse to fit detection functions. We present analyses of distance sampling data collected for a diverse tropical rainforest bird assemblage across broad elevational and latitudinal gradients in North Queensland, Australia. Using audio and visual detections, we assessed the influence of various factors on Effective Strip Width (ESW), an intuitively useful parameter, since it can be used to calculate an estimate of density from count data. Body size and species exerted the most important influence on ESW, with larger species detectable over greater distances than smaller species. Secondarily, wet weather and high shrub density decreased ESW for most species. ESW for several species also differed between summer and winter, possibly due to seasonal differences in calling behavior. Distance sampling proved logistically intensive in these environments, but large differences in ESW between species confirmed the need to correct for detection probability to obtain accurate density estimates. Our results suggest an evidence-based approach to controlling for factors influencing detectability, and avenues for further work including modeling detectability as a function of species characteristics such as body size and call characteristics. Such models may be useful in developing a calibration for non-distance sampling data and for estimating detectability of rare species. PMID:26110433

Incorporation of physical constraints in optimal surface search for renal cortex segmentation

NASA Astrophysics Data System (ADS)

Li, Xiuli; Chen, Xinjian; Yao, Jianhua; Zhang, Xing; Tian, Jie

2012-02-01

In this paper, we propose a novel approach for multiple surfaces segmentation based on the incorporation of physical constraints in optimal surface searching. We apply our new approach to solve the renal cortex segmentation problem, an important but not sufficiently researched issue. In this study, in order to better restrain the intensity proximity of the renal cortex and renal column, we extend the optimal surface search approach to allow for varying sampling distance and physical separation constraints, instead of the traditional fixed sampling distance and numerical separation constraints. The sampling distance of each vertex-column is computed according to the sparsity of the local triangular mesh. Then the physical constraint learned from a priori renal cortex thickness is applied to the inter-surface arcs as the separation constraints. Appropriate varying sampling distance and separation constraints were learnt from 6 clinical CT images. After training, the proposed approach was tested on a test set of 10 images. The manual segmentation of renal cortex was used as the reference standard. Quantitative analysis of the segmented renal cortex indicates that overall segmentation accuracy was increased after introducing the varying sampling distance and physical separation constraints (the average true positive volume fraction (TPVF) and false positive volume fraction (FPVF) were 83.96% and 2.80%, respectively, by using varying sampling distance and physical separation constraints compared to 74.10% and 0.18%, respectively, by using fixed sampling distance and numerical separation constraints). The experimental results demonstrated the effectiveness of the proposed approach.

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

NASA Astrophysics Data System (ADS)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

Cyber Asynchronous versus Blended Cyber Approach in Distance English Learning

ERIC Educational Resources Information Center

Ge, Zi-Gang

2012-01-01

This study aims to compare the single cyber asynchronous learning approach with the blended cyber learning approach in distance English education. Two classes of 70 students participated in this study, which lasted one semester of about four months, with one class using the blended approach for their English study and the other only using the…

What Would Batman Do? Self-Distancing Improves Executive Function in Young Children

ERIC Educational Resources Information Center

White, Rachel E.; Carlson, Stephanie M.

2016-01-01

This experimental research assessed the influence of graded levels of self-distancing--psychological distancing from one's egocentric perspective--on executive function (EF) in young children. Three- (n = 48) and 5-year-old (n = 48) children were randomly assigned to one of four manipulations of distance from the self (from proximal to distal:…

The Segue K giant survey. II. A catalog of distance determinations for the Segue K giants in the galactic halo

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

Xue, Xiang-Xiang; Rix, Hans-Walter; Ma, Zhibo

2014-04-01

We present an online catalog of distance determinations for 6036 K giants, most of which are members of the Milky Way's stellar halo. Their medium-resolution spectra from the Sloan Digital Sky Survey/Sloan Extension for Galactic Understanding and Exploration are used to derive metallicities and rough gravity estimates, along with radial velocities. Distance moduli are derived from a comparison of each star's apparent magnitude with the absolute magnitude of empirically calibrated color-luminosity fiducials, at the observed (g – r){sub 0} color and spectroscopic [Fe/H]. We employ a probabilistic approach that makes it straightforward to properly propagate the errors in metallicities, magnitudes,more » and colors into distance uncertainties. We also fold in prior information about the giant-branch luminosity function and the different metallicity distributions of the SEGUE K-giant targeting sub-categories. We show that the metallicity prior plays a small role in the distance estimates, but that neglecting the luminosity prior could lead to a systematic distance modulus bias of up to 0.25 mag, compared to the case of using the luminosity prior. We find a median distance precision of 16%, with distance estimates most precise for the least metal-poor stars near the tip of the red giant branch. The precision and accuracy of our distance estimates are validated with observations of globular and open clusters. The stars in our catalog are up to 125 kpc from the Galactic center, with 283 stars beyond 50 kpc, forming the largest available spectroscopic sample of distant tracers in the Galactic halo.« less

SU-E-T-39: A Logistic Function-Based Model to Predict Organ-At-Risk (OAR) DVH in IMRT Treatment Planning

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

Chen, S; Zhang, H; Zhang, B

2015-06-15

Purpose: To investigate the feasibility of a logistic function-based model to predict organ-at-risk (OAR) DVH for IMRT planning. The predicted DVHs are compared to achieved DVHs by expert treatment planners. Methods: A logistic function is used to model the OAR dose-gradient function. This function describes the percentage of the prescription dose as a function of the normal distance to PTV surface. The slope of dose-gradient function is function of relative spatial orientation of the PTV and OARs. The OAR DVH is calculated using the OAR dose-gradient function assuming that the dose is same for voxels with same normal distance tomore » PTV. Ten previously planned prostate IMRT plans were selected to build the model, and the following plan parameters were calculated as possible features to the model: the PTV maximum/minimum dose, PTV volume, bladder/rectum volume in the radiation field, percentage of bladder/rectum overlapping with PTV, and the distance between the bladder/rectum centroid and PTV. The bladder/rectum dose-gradient function was modeled and applied on 10 additional test cases, and the predicted and achieved clinical bladder/rectum DVHs were compared: V70 (percentage of volume receiving 70Gy and above), V65, V60, V55, V50, V45, V40. Results: The following parameters were selected as model features: PTV volume, and distance of centroid of rectum/bladder to PTV. The model was tested with 10 additional patients. For bladder, the absolute difference (mean±standard deviation) between predicted and clinical DVHs is V70=−0.3±3.2, V65=−0.8±3.9, V60=1.5±4.3, V55=1.7±5.3, V50=−0.6±6.4, V45=0.6±6.5, and V40=0.9±5.7, the correlation coefficient is 0.96; for rectum, the difference is V70=1.5±3.8, V65=1.2±4.2, V60=−0.1±5.3, V55=1.0±6.6, V50=1.6±8.7, V45=1.9±9.8, and V40=1.5±10.1, and the correlation coefficient is 0.87. Conclusion: The OAR DVH can be accurately predicted using the OAR dose-gradient function in IMRT plans. This approach may be used as a quality control tool and aid less experienced planners determine benchmarks for plan quality.« less

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

Burke, J.V.

The published work on exact penalization is indeed vast. Recently this work has indicated an intimate relationship between exact penalization, Lagrange multipliers, and problem stability or calmness. In the present work we chronicle this development within a simple idealized problem framework, wherein we unify, extend, and refine much of the known theory. In particular, most of the foundations for constrained optimization are developed with the aid of exact penalization techniques. Our approach is highly geometric and is based upon the elementary subdifferential theory for distance functions. It is assumed that the reader is familiar with the theory of convex setsmore » and functions. 54 refs.« less

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

DOE PAGES

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; ...

2017-10-10

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. Itmore » relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.« less

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

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

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. Itmore » relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.« less

Evolution of specialization: a phylogenetic study of host range in the red milkweed beetle (Tetraopes tetraophthalmus).

PubMed

Rasmann, Sergio; Agrawal, Anurag A

2011-06-01

Specialization is common in most lineages of insect herbivores, one of the most diverse groups of organisms on earth. To address how and why specialization is maintained over evolutionary time, we hypothesized that plant defense and other ecological attributes of potential host plants would predict the performance of a specialist root-feeding herbivore (the red milkweed beetle, Tetraopes tetraophthalmus). Using a comparative phylogenetic and functional trait approach, we assessed the determinants of insect host range across 18 species of Asclepias. Larval survivorship decreased with increasing phylogenetic distance from the true host, Asclepias syriaca, suggesting that adaptation to plant traits drives specialization. Among several root traits measured, only cardenolides (toxic defense chemicals) correlated with larval survival, and cardenolides also explained the phylogenetic distance effect in phylogenetically controlled multiple regression analyses. Additionally, milkweed species having a known association with other Tetraopes beetles were better hosts than species lacking Tetraopes herbivores, and milkweeds with specific leaf area values (a trait related to leaf function and habitat affiliation) similar to those of A. syriaca were better hosts than species having divergent values. We thus conclude that phylogenetic distance is an integrated measure of phenotypic and ecological attributes of Asclepias species, especially defensive cardenolides, which can be used to explain specialization and constraints on host shifts over evolutionary time.

Depth Discrimination Using Rg-to-Sg Spectral Amplitude Ratios for Seismic Events in Utah Recorded at Local Distances

DOE PAGES

Tibi, Rigobert; Koper, Keith D.; Pankow, Kristine L.; ...

2018-03-20

Most of the commonly used seismic discrimination approaches are designed for regional data. Relatively little attention has focused on discriminants for local distances (< 200 km), the range at which the smallest events are recorded. We take advantage of the variety of seismic sources and the existence of a dense regional seismic network in the Utah region to evaluate amplitude ratio seismic discrimination at local distances. First, we explored phase-amplitude Pg-to-Sg ratios for multiple frequency bands to classify events in a dataset that comprises populations of single-shot surface explosions, shallow and deep ripple-fired mining blasts, mining-induced events, and tectonic earthquakes.more » We achieved a limited success. Then, for the same dataset, we combined the Pg-to-Sg phase-amplitude ratios with Sg-to-Rg spectral amplitude ratios in a multivariate quadratic discriminant function (QDF) approach. For two-category, pairwise classification, seven out of ten population pairs show misclassification rates of about 20% or less, with five pairs showing rates of about 10% or less. The approach performs best for the pair involving the populations of single-shot explosions and mining-induced events. By combining both Pg-to-Sg and Rg-to-Sg ratios in the multivariate QDFs, we are able to achieve an average improvement of about 4–14% in misclassification rates compared to Pg-to-Sg ratios alone. When all five event populations are considered simultaneously, as expected, the potential for misclassification increases and our QDF approach using both Pg-to-Sg and Rg-to-Sg ratios achieves an average success rate of about 74%, compared to the rate of about 86% for two-category, pairwise classification.« less

Depth Discrimination Using Rg-to-Sg Spectral Amplitude Ratios for Seismic Events in Utah Recorded at Local Distances

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

Tibi, Rigobert; Koper, Keith D.; Pankow, Kristine L.

Most of the commonly used seismic discrimination approaches are designed for regional data. Relatively little attention has focused on discriminants for local distances (< 200 km), the range at which the smallest events are recorded. We take advantage of the variety of seismic sources and the existence of a dense regional seismic network in the Utah region to evaluate amplitude ratio seismic discrimination at local distances. First, we explored phase-amplitude Pg-to-Sg ratios for multiple frequency bands to classify events in a dataset that comprises populations of single-shot surface explosions, shallow and deep ripple-fired mining blasts, mining-induced events, and tectonic earthquakes.more » We achieved a limited success. Then, for the same dataset, we combined the Pg-to-Sg phase-amplitude ratios with Sg-to-Rg spectral amplitude ratios in a multivariate quadratic discriminant function (QDF) approach. For two-category, pairwise classification, seven out of ten population pairs show misclassification rates of about 20% or less, with five pairs showing rates of about 10% or less. The approach performs best for the pair involving the populations of single-shot explosions and mining-induced events. By combining both Pg-to-Sg and Rg-to-Sg ratios in the multivariate QDFs, we are able to achieve an average improvement of about 4–14% in misclassification rates compared to Pg-to-Sg ratios alone. When all five event populations are considered simultaneously, as expected, the potential for misclassification increases and our QDF approach using both Pg-to-Sg and Rg-to-Sg ratios achieves an average success rate of about 74%, compared to the rate of about 86% for two-category, pairwise classification.« less

The semantic distance task: Quantifying semantic distance with semantic network path length.

PubMed

Kenett, Yoed N; Levi, Effi; Anaki, David; Faust, Miriam

2017-09-01

Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We propose a novel approach to computing semantic distance, based on network science methodology. Path length in a semantic network represents the amount of steps needed to traverse from 1 word in the network to the other. We examine whether path length can be used as a measure of semantic distance, by investigating how path length affect performance in a semantic relatedness judgment task and recall from memory. Our results show a differential effect on performance: Up to 4 steps separating between word-pairs, participants exhibit an increase in reaction time (RT) and decrease in the percentage of word-pairs judged as related. From 4 steps onward, participants exhibit a significant decrease in RT and the word-pairs are dominantly judged as unrelated. Furthermore, we show that as path length between word-pairs increases, success in free- and cued-recall decreases. Finally, we demonstrate how our measure outperforms computational methods measuring semantic distance (LSA and positive pointwise mutual information) in predicting participants RT and subjective judgments of semantic strength. Thus, we provide a computational alternative to computing semantic distance. Furthermore, this approach addresses key issues in cognitive theory, namely the breadth of the spreading activation process and the effect of semantic distance on memory retrieval. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Statistical physics of media processes: Mediaphysics

NASA Astrophysics Data System (ADS)

Kuznetsov, Dmitri V.; Mandel, Igor

2007-04-01

The processes of mass communications in complicated social or sociobiological systems such as marketing, economics, politics, animal populations, etc. as a subject for the special scientific subbranch-“mediaphysics”-are considered in its relation with sociophysics. A new statistical physics approach to analyze these phenomena is proposed. A keystone of the approach is an analysis of population distribution between two or many alternatives: brands, political affiliations, or opinions. Relative distances between a state of a “person's mind” and the alternatives are measures of propensity to buy (to affiliate, or to have a certain opinion). The distribution of population by those relative distances is time dependent and affected by external (economic, social, marketing, natural) and internal (influential propagation of opinions, “word of mouth”, etc.) factors, considered as fields. Specifically, the interaction and opinion-influence field can be generalized to incorporate important elements of Ising-spin-based sociophysical models and kinetic-equation ones. The distributions were described by a Schrödinger-type equation in terms of Green's functions. The developed approach has been applied to a real mass-media efficiency problem for a large company and generally demonstrated very good results despite low initial correlations of factors and the target variable.

On-Board Event-Based State Estimation for Trajectory Approaching and Tracking of a Vehicle

PubMed Central

Martínez-Rey, Miguel; Espinosa, Felipe; Gardel, Alfredo; Santos, Carlos

2015-01-01

For the problem of pose estimation of an autonomous vehicle using networked external sensors, the processing capacity and battery consumption of these sensors, as well as the communication channel load should be optimized. Here, we report an event-based state estimator (EBSE) consisting of an unscented Kalman filter that uses a triggering mechanism based on the estimation error covariance matrix to request measurements from the external sensors. This EBSE generates the events of the estimator module on-board the vehicle and, thus, allows the sensors to remain in stand-by mode until an event is generated. The proposed algorithm requests a measurement every time the estimation distance root mean squared error (DRMS) value, obtained from the estimator's covariance matrix, exceeds a threshold value. This triggering threshold can be adapted to the vehicle's working conditions rendering the estimator even more efficient. An example of the use of the proposed EBSE is given, where the autonomous vehicle must approach and follow a reference trajectory. By making the threshold a function of the distance to the reference location, the estimator can halve the use of the sensors with a negligible deterioration in the performance of the approaching maneuver. PMID:26102489

Combined small-molecule inhibition accelerates the derivation of functional, early-born, cortical neurons from human pluripotent stem cells

PubMed Central

Qi, Yuchen; Zhang, Xin-Jun; Renier, Nicolas; Wu, Zhuhao; Atkin, Talia; Sun, Ziyi; Ozair, M. Zeeshan; Tchieu, Jason; Zimmer, Bastian; Fattahi, Faranak; Ganat, Yosif; Azevedo, Ricardo; Zeltner, Nadja; Brivanlou, Ali H.; Karayiorgou, Maria; Gogos, Joseph; Tomishima, Mark; Tessier-Lavigne, Marc; Shi, Song-Hai; Studer, Lorenz

2017-01-01

Considerable progress has been made in converting human pluripotent stem cells (hPSCs) into functional neurons. However, the protracted timing of human neuron specification and functional maturation remains a key challenge that hampers the routine application of hPSC-derived lineages in disease modeling and regenerative medicine. Using a combinatorial small-molecule screen, we previously identified conditions for the rapid differentiation of hPSCs into peripheral sensory neurons. Here we generalize the approach to central nervous system (CNS) fates by developing a small-molecule approach for accelerated induction of early-born cortical neurons. Combinatorial application of 6 pathway inhibitors induces post-mitotic cortical neurons with functional electrophysiological properties by day 16 of differentiation, in the absence of glial cell co-culture. The resulting neurons, transplanted at 8 days of differentiation into the postnatal mouse cortex, are functional and establish long-distance projections, as shown using iDISCO whole brain imaging. Accelerated differentiation into cortical neuron fates should facilitate hPSC-based strategies for disease modeling and cell therapy in CNS disorders. PMID:28112759

Heuristic lipophilicity potential for computer-aided rational drug design: optimizations of screening functions and parameters.

PubMed

Du, Q; Mezey, P G

1998-09-01

In this research we test and compare three possible atom-based screening functions used in the heuristic molecular lipophilicity potential (HMLP). Screening function 1 is a power distance-dependent function, bi/[formula: see text] Ri-r [formula: see text] gamma, screening function 2 is an exponential distance-dependent function, bi exp(-[formula: see text] Ri-r [formula: see text]/d0), and screening function 3 is a weighted distance-dependent function, sign(bi) exp[-xi [formula: see text] Ri-r [formula: see text]/magnitude of bi)]. For every screening function, the parameters (gamma, d0, and xi) are optimized using 41 common organic molecules of 4 types of compounds: aliphatic alcohols, aliphatic carboxylic acids, aliphatic amines, and aliphatic alkanes. The results of calculations show that screening function 3 cannot give chemically reasonable results, however, both the power screening function and the exponential screening function give chemically satisfactory results. There are two notable differences between screening functions 1 and 2. First, the exponential screening function has larger values in the short distance than the power screening function, therefore more influence from the nearest neighbors is involved using screening function 2 than screening function 1. Second, the power screening function has larger values in the long distance than the exponential screening function, therefore screening function 1 is effected by atoms at long distance more than screening function 2. For screening function 1, the suitable range of parameter gamma is 1.0 < gamma < 3.0, gamma = 2.3 is recommended, and gamma = 2.0 is the nearest integral value. For screening function 2, the suitable range of parameter d0 is 1.5 < d0 < 3.0, and d0 = 2.0 is recommended. HMLP developed in this research provides a potential tool for computer-aided three-dimensional drug design.

A variational approach to liver segmentation using statistics from multiple sources

NASA Astrophysics Data System (ADS)

Zheng, Shenhai; Fang, Bin; Li, Laquan; Gao, Mingqi; Wang, Yi

2018-01-01

Medical image segmentation plays an important role in digital medical research, and therapy planning and delivery. However, the presence of noise and low contrast renders automatic liver segmentation an extremely challenging task. In this study, we focus on a variational approach to liver segmentation in computed tomography scan volumes in a semiautomatic and slice-by-slice manner. In this method, one slice is selected and its connected component liver region is determined manually to initialize the subsequent automatic segmentation process. From this guiding slice, we execute the proposed method downward to the last one and upward to the first one, respectively. A segmentation energy function is proposed by combining the statistical shape prior, global Gaussian intensity analysis, and enforced local statistical feature under the level set framework. During segmentation, the shape of the liver shape is estimated by minimization of this function. The improved Chan-Vese model is used to refine the shape to capture the long and narrow regions of the liver. The proposed method was verified on two independent public databases, the 3D-IRCADb and the SLIVER07. Among all the tested methods, our method yielded the best volumetric overlap error (VOE) of 6.5 +/- 2.8 % , the best root mean square symmetric surface distance (RMSD) of 2.1 +/- 0.8 mm, the best maximum symmetric surface distance (MSD) of 18.9 +/- 8.3 mm in 3D-IRCADb dataset, and the best average symmetric surface distance (ASD) of 0.8 +/- 0.5 mm, the best RMSD of 1.5 +/- 1.1 mm in SLIVER07 dataset, respectively. The results of the quantitative comparison show that the proposed liver segmentation method achieves competitive segmentation performance with state-of-the-art techniques.

Adsorption and dissociation of molecular hydrogen on the (0001) surface of double hexagonal close packed americium

NASA Astrophysics Data System (ADS)

Dholabhai, P. P.; Ray, A. K.

2009-01-01

Hydrogen molecule adsorption on the (0001) surface of double hexagonal packed americium has been studied in detail within the framework of density functional theory using a full-potential all-electron linearized augmented plane wave plus local orbitals method (FP-L/APW+lo). Weak molecular hydrogen adsorptions were observed. Adsorption energies were optimized with respect to the distance of the adsorbates from the surface for three approach positions at three adsorption sites, namely t1 (one-fold top), b2 (two-fold bridge), and h3 (three-fold hollow) sites. Adsorption energies were computed at the scalar-relativistic level (no spin-orbit coupling NSOC) and at the fully relativistic level (with spin-orbit coupling SOC). The most stable configuration corresponds to a horizontal adsorption with the molecular approach being perpendicular to a lattice vector. The surface coverage is equivalent to one-fourth of a monolayer (ML), with the adsorption energies at the NSOC and SOC theoretical levels being 0.0997 eV and 0.1022 eV, respectively. The respective distance of the hydrogen molecule from the surface and hydrogen-hydrogen distance was found to be 2.645 Å and 0.789 Å, respectively. The work functions decreased and the net magnetic moments remained almost unchanged in all cases compared with the corresponding quantities of bare dhcp Am (0001) surface. The adsorbate-substrate interactions have been analyzed in detail using the partial charges inside the muffin-tin spheres, difference charge density distributions, and the local density of states. The effects of adsorption on the Am 5f electron localization-delocalization characteristics have been discussed. Reaction barrier for the dissociation of hydrogen molecule has been presented.

A distance learning model in a physical therapy curriculum.

PubMed

English, T; Harrison, A L; Hart, A L

1998-01-01

In response to the rural health initiative established in 1991, the University of Kentucky has developed an innovative distance learning program of physical therapy instruction that combines classroom lecture and discussion via compressed video technology with laboratory experiences. The authors describe the process of planning, implementing, and evaluating a specific distance learning course in pathomechanics for the professional-level master's-degree physical therapy students at the University of Kentucky. This presentation may serve as a model for teaching distance learning. Descriptions of optimal approaches to preclass preparation, scheduling, course delivery, use of audiovisual aids, use of handout material, and video production are given. Special activities that may enhance or deter the achievement of the learning objectives are outlined, and a problem-solving approach to common problems encountered is presented. An approach to evaluating and comparing course outcomes for the distance learnere is presented. For this particular course, there was no statistically significant difference in the outcome measures utilized to compare the distance learners with the on-site learners.

Joint learning of labels and distance metric.

PubMed

Liu, Bo; Wang, Meng; Hong, Richang; Zha, Zhengjun; Hua, Xian-Sheng

2010-06-01

Machine learning algorithms frequently suffer from the insufficiency of training data and the usage of inappropriate distance metric. In this paper, we propose a joint learning of labels and distance metric (JLLDM) approach, which is able to simultaneously address the two difficulties. In comparison with the existing semi-supervised learning and distance metric learning methods that focus only on label prediction or distance metric construction, the JLLDM algorithm optimizes the labels of unlabeled samples and a Mahalanobis distance metric in a unified scheme. The advantage of JLLDM is multifold: 1) the problem of training data insufficiency can be tackled; 2) a good distance metric can be constructed with only very few training samples; and 3) no radius parameter is needed since the algorithm automatically determines the scale of the metric. Extensive experiments are conducted to compare the JLLDM approach with different semi-supervised learning and distance metric learning methods, and empirical results demonstrate its effectiveness.

Families of one-point interactions resulting from the squeezing limit of the sum of two- and three-delta-like potentials

NASA Astrophysics Data System (ADS)

Zolotaryuk, A. V.

2017-06-01

Several families of one-point interactions are derived from the system consisting of two and three δ-potentials which are regularized by piecewise constant functions. In physical terms such an approximating system represents two or three extremely thin layers separated by some distance. The two-scale squeezing of this heterostructure to one point as both the width of δ-approximating functions and the distance between these functions simultaneously tend to zero is studied using the power parameterization through a squeezing parameter \\varepsilon \\to 0 , so that the intensity of each δ-potential is cj =aj \\varepsilon1-μ , aj \\in {R} , j  =  1, 2, 3, the width of each layer l =\\varepsilon and the distance between the layers r = c\\varepsilon^τ , c  >  0. It is shown that at some values of the intensities a 1, a 2 and a 3, the transmission across the limit point potentials is non-zero, whereas outside these (resonance) values the one-point interactions are opaque splitting the system at the point of singularity into two independent subsystems. Within the interval 1 < μ < 2 , the resonance sets consist of two curves on the (a_1, a_2) -plane and three surfaces in the (a_1, a_2, a_3) -space. As the parameter μ approaches the value μ =2 , three types of splitting the one-point interactions into countable families are observed.

How to calculate H3 better.

PubMed

Pavanello, Michele; Tung, Wei-Cheng; Adamowicz, Ludwik

2009-11-14

Efficient optimization of the basis set is key to achieving a very high accuracy in variational calculations of molecular systems employing basis functions that are explicitly dependent on the interelectron distances. In this work we present a method for a systematic enlargement of basis sets of explicitly correlated functions based on the iterative-complement-interaction approach developed by Nakatsuji [Phys. Rev. Lett. 93, 030403 (2004)]. We illustrate the performance of the method in the variational calculations of H(3) where we use explicitly correlated Gaussian functions with shifted centers. The total variational energy (-1.674 547 421 Hartree) and the binding energy (-15.74 cm(-1)) obtained in the calculation with 1000 Gaussians are the most accurate results to date.

Heuristic lipophilicity potential for computer-aided rational drug design: Optimizations of screening functions and parameters

NASA Astrophysics Data System (ADS)

Du, Qishi; Mezey, Paul G.

1998-09-01

In this research we test and compare three possible atom-basedscreening functions used in the heuristic molecular lipophilicity potential(HMLP). Screening function 1 is a power distance-dependent function, b_{{i}} /| {R_{{i}}- r} |^γ, screening function 2is an exponential distance-dependent function, biexp(-| {R_i- r} |/d_0 , and screening function 3 is aweighted distance-dependent function, {{sign}}( {b_i } ){{exp}}ξ ( {| {R_i- r} |/| {b_i } |} )For every screening function, the parameters (γ ,d0, and ξ are optimized using 41 common organic molecules of 4 types of compounds:aliphatic alcohols, aliphatic carboxylic acids, aliphatic amines, andaliphatic alkanes. The results of calculations show that screening function3 cannot give chemically reasonable results, however, both the powerscreening function and the exponential screening function give chemicallysatisfactory results. There are two notable differences between screeningfunctions 1 and 2. First, the exponential screening function has largervalues in the short distance than the power screening function, thereforemore influence from the nearest neighbors is involved using screeningfunction 2 than screening function 1. Second, the power screening functionhas larger values in the long distance than the exponential screeningfunction, therefore screening function 1 is effected by atoms at longdistance more than screening function 2. For screening function 1, thesuitable range of parameter d0 is 1.5 < d0 < 3.0, and d0 = 2.0 is recommended. HMLP developed in this researchprovides a potential tool for computer-aided three-dimensional drugdesign.

Unsupervised image matching based on manifold alignment.

PubMed

Pei, Yuru; Huang, Fengchun; Shi, Fuhao; Zha, Hongbin

2012-08-01

This paper challenges the issue of automatic matching between two image sets with similar intrinsic structures and different appearances, especially when there is no prior correspondence. An unsupervised manifold alignment framework is proposed to establish correspondence between data sets by a mapping function in the mutual embedding space. We introduce a local similarity metric based on parameterized distance curves to represent the connection of one point with the rest of the manifold. A small set of valid feature pairs can be found without manual interactions by matching the distance curve of one manifold with the curve cluster of the other manifold. To avoid potential confusions in image matching, we propose an extended affine transformation to solve the nonrigid alignment in the embedding space. The comparatively tight alignments and the structure preservation can be obtained simultaneously. The point pairs with the minimum distance after alignment are viewed as the matchings. We apply manifold alignment to image set matching problems. The correspondence between image sets of different poses, illuminations, and identities can be established effectively by our approach.

Face-to-Face or Distance Training: Two Different Approaches To Motivate SMEs to Learn.

ERIC Educational Resources Information Center

Lawless, Naomi; Allan, John; O'Dwyer, Michele

2000-01-01

Two approaches to training for small/medium-sized enterprises were compared: a British distance learning program and an Irish program offering face-to-face training for micro-enterprises. Both used constructivist, collaborative, and reflective methods. Advantages and disadvantages of each approach were identified. (SK)

Distance-Based Functional Diversity Measures and Their Decomposition: A Framework Based on Hill Numbers

PubMed Central

Chiu, Chun-Huo; Chao, Anne

2014-01-01

Hill numbers (or the “effective number of species”) are increasingly used to characterize species diversity of an assemblage. This work extends Hill numbers to incorporate species pairwise functional distances calculated from species traits. We derive a parametric class of functional Hill numbers, which quantify “the effective number of equally abundant and (functionally) equally distinct species” in an assemblage. We also propose a class of mean functional diversity (per species), which quantifies the effective sum of functional distances between a fixed species to all other species. The product of the functional Hill number and the mean functional diversity thus quantifies the (total) functional diversity, i.e., the effective total distance between species of the assemblage. The three measures (functional Hill numbers, mean functional diversity and total functional diversity) quantify different aspects of species trait space, and all are based on species abundance and species pairwise functional distances. When all species are equally distinct, our functional Hill numbers reduce to ordinary Hill numbers. When species abundances are not considered or species are equally abundant, our total functional diversity reduces to the sum of all pairwise distances between species of an assemblage. The functional Hill numbers and the mean functional diversity both satisfy a replication principle, implying the total functional diversity satisfies a quadratic replication principle. When there are multiple assemblages defined by the investigator, each of the three measures of the pooled assemblage (gamma) can be multiplicatively decomposed into alpha and beta components, and the two components are independent. The resulting beta component measures pure functional differentiation among assemblages and can be further transformed to obtain several classes of normalized functional similarity (or differentiation) measures, including N-assemblage functional generalizations of the classic Jaccard, Sørensen, Horn and Morisita-Horn similarity indices. The proposed measures are applied to artificial and real data for illustration. PMID:25000299

Distance-based functional diversity measures and their decomposition: a framework based on Hill numbers.

PubMed

Chiu, Chun-Huo; Chao, Anne

2014-01-01

Hill numbers (or the "effective number of species") are increasingly used to characterize species diversity of an assemblage. This work extends Hill numbers to incorporate species pairwise functional distances calculated from species traits. We derive a parametric class of functional Hill numbers, which quantify "the effective number of equally abundant and (functionally) equally distinct species" in an assemblage. We also propose a class of mean functional diversity (per species), which quantifies the effective sum of functional distances between a fixed species to all other species. The product of the functional Hill number and the mean functional diversity thus quantifies the (total) functional diversity, i.e., the effective total distance between species of the assemblage. The three measures (functional Hill numbers, mean functional diversity and total functional diversity) quantify different aspects of species trait space, and all are based on species abundance and species pairwise functional distances. When all species are equally distinct, our functional Hill numbers reduce to ordinary Hill numbers. When species abundances are not considered or species are equally abundant, our total functional diversity reduces to the sum of all pairwise distances between species of an assemblage. The functional Hill numbers and the mean functional diversity both satisfy a replication principle, implying the total functional diversity satisfies a quadratic replication principle. When there are multiple assemblages defined by the investigator, each of the three measures of the pooled assemblage (gamma) can be multiplicatively decomposed into alpha and beta components, and the two components are independent. The resulting beta component measures pure functional differentiation among assemblages and can be further transformed to obtain several classes of normalized functional similarity (or differentiation) measures, including N-assemblage functional generalizations of the classic Jaccard, Sørensen, Horn and Morisita-Horn similarity indices. The proposed measures are applied to artificial and real data for illustration.

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

USGS Publications Warehouse

Sutherland, Christopher; Fuller, Angela K.; Royle, J. Andrew

2015-01-01

The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale.

PubMed

Buck, Christoph; Kneib, Thomas; Tkaczick, Tobias; Konstabel, Kenn; Pigeot, Iris

2015-12-22

Built environment studies provide broad evidence that urban characteristics influence physical activity (PA). However, findings are still difficult to compare, due to inconsistent measures assessing urban point characteristics and varying definitions of spatial scale. Both were found to influence the strength of the association between the built environment and PA. We simultaneously evaluated the effect of kernel approaches and network-distances to investigate the association between urban characteristics and physical activity depending on spatial scale and intensity measure. We assessed urban measures of point characteristics such as intersections, public transit stations, and public open spaces in ego-centered network-dependent neighborhoods based on geographical data of one German study region of the IDEFICS study. We calculated point intensities using the simple intensity and kernel approaches based on fixed bandwidths, cross-validated bandwidths including isotropic and anisotropic kernel functions and considering adaptive bandwidths that adjust for residential density. We distinguished six network-distances from 500 m up to 2 km to calculate each intensity measure. A log-gamma regression model was used to investigate the effect of each urban measure on moderate-to-vigorous physical activity (MVPA) of 400 2- to 9.9-year old children who participated in the IDEFICS study. Models were stratified by sex and age groups, i.e. pre-school children (2 to <6 years) and school children (6-9.9 years), and were adjusted for age, body mass index (BMI), education and safety concerns of parents, season and valid weartime of accelerometers. Association between intensity measures and MVPA strongly differed by network-distance, with stronger effects found for larger network-distances. Simple intensity revealed smaller effect estimates and smaller goodness-of-fit compared to kernel approaches. Smallest variation in effect estimates over network-distances was found for kernel intensity measures based on isotropic and anisotropic cross-validated bandwidth selection. We found a strong variation in the association between the built environment and PA of children based on the choice of intensity measure and network-distance. Kernel intensity measures provided stable results over various scales and improved the assessment compared to the simple intensity measure. Considering different spatial scales and kernel intensity methods might reduce methodological limitations in assessing opportunities for PA in the built environment.

High-order distance-based multiview stochastic learning in image classification.

PubMed

Yu, Jun; Rui, Yong; Tang, Yuan Yan; Tao, Dacheng

2014-12-01

How do we find all images in a larger set of images which have a specific content? Or estimate the position of a specific object relative to the camera? Image classification methods, like support vector machine (supervised) and transductive support vector machine (semi-supervised), are invaluable tools for the applications of content-based image retrieval, pose estimation, and optical character recognition. However, these methods only can handle the images represented by single feature. In many cases, different features (or multiview data) can be obtained, and how to efficiently utilize them is a challenge. It is inappropriate for the traditionally concatenating schema to link features of different views into a long vector. The reason is each view has its specific statistical property and physical interpretation. In this paper, we propose a high-order distance-based multiview stochastic learning (HD-MSL) method for image classification. HD-MSL effectively combines varied features into a unified representation and integrates the labeling information based on a probabilistic framework. In comparison with the existing strategies, our approach adopts the high-order distance obtained from the hypergraph to replace pairwise distance in estimating the probability matrix of data distribution. In addition, the proposed approach can automatically learn a combination coefficient for each view, which plays an important role in utilizing the complementary information of multiview data. An alternative optimization is designed to solve the objective functions of HD-MSL and obtain different views on coefficients and classification scores simultaneously. Experiments on two real world datasets demonstrate the effectiveness of HD-MSL in image classification.

FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network.

PubMed

He, Wei; Pillement, Sebastien; Xu, Du

2017-11-23

Clustering is an efficient approach in a wireless sensor network (WSN) to reduce the energy consumption of nodes and to extend the lifetime of the network. Unfortunately, this approach requires that all cluster heads (CHs) transmit their data to the base station (BS), which gives rise to the long distance communications problem, and in multi-hop routing, the CHs near the BS have to forward data from other nodes that lead those CHs to die prematurely, creating the hot zones problem. Unequal clustering has been proposed to solve these problems. Most of the current algorithms elect CH only by considering their competition radius, leading to unevenly distributed cluster heads. Furthermore, global distances values are needed when calculating the competition radius, which is a tedious task in large networks. To face these problems, we propose a flooding tree uneven clustering protocol (FTUC) suited for large networks. Based on the construction of a tree type sub-network to calculate the minimum and maximum distances values of the network, we then apply the unequal cluster theory. We also introduce referenced position circles to evenly elect cluster heads. Therefore, cluster heads are elected depending on the node's residual energy and their distance to a referenced circle. FTUC builds the best inter-cluster communications route by evaluating a cluster head cost function to find the best next hop to the BS. The simulation results show that the FTUC algorithm decreases the energy consumption of the nodes and balances the global energy consumption effectively, thus extending the lifetime of the network.

Distance Learning.

ERIC Educational Resources Information Center

Orey, Michael; Koenecke, Lynne; Snider, Richard C.; Perkins, Ross A.; Holmes, Glen A.; Lockee, Barbara B.; Moller, Leslie A.; Harvey, Douglas; Downs, Margaret; Godshalk, Veronica M.

2003-01-01

Contains four articles covering trends and issues on distance learning including: the experience of two learners learning via the Internet; a systematic approach to determining the scalability of a distance education program; identifying factors that affect learning community development and performance in asynchronous distance education; and…

Landscape genetics of high mountain frog metapopulations

USGS Publications Warehouse

Murphy, M.A.; Dezzani, R.; Pilliod, D.S.; Storfer, A.

2010-01-01

Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between-site (landscape resistance) landscape characteristics and at-site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between-site and at-site landscape processes in metapopulations of Columbia spotted frogs (Rana luteiventris) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at-site landscape process) and resistance (e.g. between-site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at-site) and topographic complexity (between-site). Conversely, site productivity (as measured by heat load index, at-site) and growing season (as measured by frost-free period between-sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source-sink dynamics. In conclusion, gravity models provide a powerful new modelling approach for examining a wide range of both basic and applied questions in landscape genetics.

Developing an International Distance Education Program: A Blended Learning Approach

ERIC Educational Resources Information Center

Mathur, Ravisha; Oliver, Lisa

2007-01-01

Building a dynamic international distance education program can be a complex operation. The purpose of this paper is to discuss a model for global learning that utilizes a blended learning approach. This paper will describe how a blended learning approach was implemented in an international instructional technology Master's program to the benefit…

What would Batman do? Self-distancing improves executive function in young children.

PubMed

White, Rachel E; Carlson, Stephanie M

2016-05-01

This experimental research assessed the influence of graded levels of self-distancing - psychological distancing from one's egocentric perspective - on executive function (EF) in young children. Three- (n = 48) and 5-year-old (n = 48) children were randomly assigned to one of four manipulations of distance from the self (from proximal to distal: self-immersed, control, third person, and exemplar) on a comprehensive measure of EF. Performance increased as a function of self-distancing across age groups. Follow-up analyses indicated that 5-year-olds were driving this effect. They showed significant improvements in EF with increased distance from the self, outperforming controls both when taking a third person perspective on the self and when taking the perspective of an exemplar other (e.g., Batman) through role play. Three-year-olds, however, did not show increased EF performance as a function of greater distance from the self. Preliminary results suggest that developments in theory of mind might contribute to these age-related differences in efficacy. These findings speak to the importance of psychological distancing in the expression of conscious control over thought and action from a young age and suggest a promising new avenue for early EF intervention. © 2015 John Wiley & Sons Ltd.

Multiphase Interface Tracking with Fast Semi-Lagrangian Contouring.

PubMed

Li, Xiaosheng; He, Xiaowei; Liu, Xuehui; Zhang, Jian J; Liu, Baoquan; Wu, Enhua

2016-08-01

We propose a semi-Lagrangian method for multiphase interface tracking. In contrast to previous methods, our method maintains an explicit polygonal mesh, which is reconstructed from an unsigned distance function and an indicator function, to track the interface of arbitrary number of phases. The surface mesh is reconstructed at each step using an efficient multiphase polygonization procedure with precomputed stencils while the distance and indicator function are updated with an accurate semi-Lagrangian path tracing from the meshes of the last step. Furthermore, we provide an adaptive data structure, multiphase distance tree, to accelerate the updating of both the distance function and the indicator function. In addition, the adaptive structure also enables us to contour the distance tree accurately with simple bisection techniques. The major advantage of our method is that it can easily handle topological changes without ambiguities and preserve both the sharp features and the volume well. We will evaluate its efficiency, accuracy and robustness in the results part with several examples.

Microstructural Abnormalities of Short-Distance White Matter Tracts in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Shukla, Dinesh K.; Keehn, Brandon; Smylie, Daren M.; Muller, Ralph-Axel

2011-01-01

Recent functional connectivity magnetic resonance imaging and diffusion tensor imaging (DTI) studies have suggested atypical functional connectivity and reduced integrity of long-distance white matter fibers in autism spectrum disorder (ASD). However, evidence for short-distance white matter fibers is still limited, despite some speculation of…

Visualization and quantification of magnetic nanoparticles into vesicular systems by combined atomic and magnetic force microscopy

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

Dong, C.; Department of Physics, SAPIENZA University of Rome, Piazzale A. Moro 5, 00185, Rome; Corsetti, S.

2015-06-23

We report a phenomenological approach for the quantification of the diameter of magnetic nanoparticles (MNPs) incorporated in non-ionic surfactant vesicles (niosomes) using magnetic force microscopy (MFM). After a simple specimen preparation, i.e., by putting a drop of solution containing MNPs-loaded niosomes on flat substrates, topography and MFM phase images are collected. To attempt the quantification of the diameter of entrapped MNPs, the method is calibrated on the sole MNPs deposited on the same substrates by analyzing the MFM signal as a function of the MNP diameter (at fixed tip-sample distance) and of the tip-sample distance (for selected MNPs). After calibration,more » the effective diameter of the MNPs entrapped in some niosomes is quantitatively deduced from MFM images.« less

A study of the tolerance block approach to special stratification. [winter wheat in Kansas

NASA Technical Reports Server (NTRS)

Richardson, W. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Twelve winter wheat LACIE segments in Kansas were used to compare the performance of three clustering methods: (1) BCLUST, which uses a spectral distance function to accumulate clusters; (2) blocks-alone, which divides spectral space into equally populated blocks; and (3) block-seeds, which uses spectral means of blocks-alone as seeds for accumulating distance-type clusters. Both BCLUST and block-seeds performed equally well and outperformed blocks-alone significantly. Their average variance ratio of about 0.5 showed imperfect separation of wheat from non-wheat. This result points to the need to explore the achievable crop separability in the spectral/temporal domain, and suggest evaluating derived features rather than data channels as a means to achieve purer spectral strata.

Frustration in protein elastic network models

NASA Astrophysics Data System (ADS)

Lezon, Timothy; Bahar, Ivet

2010-03-01

Elastic network models (ENMs) are widely used for studying the equilibrium dynamics of proteins. The most common approach in ENM analysis is to adopt a uniform force constant or a non-specific distance dependent function to represent the force constant strength. Here we discuss the influence of sequence and structure in determining the effective force constants between residues in ENMs. Using a novel method based on entropy maximization, we optimize the force constants such that they exactly reporduce a subset of experimentally determined pair covariances for a set of proteins. We analyze the optimized force constants in terms of amino acid types, distances, contact order and secondary structure, and we demonstrate that including frustrated interactions in the ENM is essential for accurately reproducing the global modes in the middle of the frequency spectrum.

Laser-modified Coulomb scattering states of an electron in the parabolic quasi-Sturmian-Floquet approach

NASA Astrophysics Data System (ADS)

Zaytsev, A. S.; Zaytsev, S. A.; Ancarani, L. U.; Kouzakov, K. A.

2018-04-01

Electron scattering states in combined Coulomb and laser fields are investigated with a nonperturbative approach based on the Hermitian Floquet theory. Taking into account the Coulomb-specific asymptotic behavior of the electron wave functions at large distances, a Lippmann-Schwinger-Floquet equation is derived in the Kramers-Henneberger frame. Such a scattering-state equation is solved numerically employing a set of parabolic quasi-Sturmian functions which have the great advantage of possessing, by construction, adequately chosen incoming or outgoing Coulomb asymptotic behaviors. Our quasi-Sturmian-Floquet approach is tested with a calculation of triple differential cross sections for a laser-assisted (e ,2 e ) process on atomic hydrogen within a first-order Born treatment of the projectile-atom interaction. Convergence with respect to the number of Floquet-Fourier expansion terms is numerically demonstrated. The illustration shows that the developed method is very efficient for the computation of light-dressed states of an electron moving in a Coulomb potential in the presence of laser radiation.

Distance Education.

ERIC Educational Resources Information Center

ASPBAE Courier, 1984

1984-01-01

This publication is devoted to distance education. "The Future of Distance Teaching Universities in a Worldwide Perspectives" (John S. Daniel) examines challenges likely to face the various countries and regions of the world in the next decade. "An Australian University's Approach to Distance Education--Formal and Non-Formal"…

Why do people move? Enhancing human mobility prediction using local functions based on public records and SNS data.

PubMed

Kim, Jungmin; Park, Juyong; Lee, Wonjae

2018-01-01

The quality of life for people in urban regions can be improved by predicting urban human mobility and adjusting urban planning accordingly. In this study, we compared several possible variables to verify whether a gravity model (a human mobility prediction model borrowed from Newtonian mechanics) worked as well in inner-city regions as it did in intra-city regions. We reviewed the resident population, the number of employees, and the number of SNS posts as variables for generating mass values for an urban traffic gravity model. We also compared the straight-line distance, travel distance, and the impact of time as possible distance values. We defined the functions of urban regions on the basis of public records and SNS data to reflect the diverse social factors in urban regions. In this process, we conducted a dimension reduction method for the public record data and used a machine learning-based clustering algorithm for the SNS data. In doing so, we found that functional distance could be defined as the Euclidean distance between social function vectors in urban regions. Finally, we examined whether the functional distance was a variable that had a significant impact on urban human mobility.

Challenges Facing 3-D Audio Display Design for Multimedia

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Null, Cynthia H. (Technical Monitor)

1998-01-01

The challenges facing successful multimedia presentation depend largely on the expectations of the designer and end user for a given application. Perceptual limitations in distance, elevation and azimuth sound source simulation differ significantly between headphone and cross-talk cancellation loudspeaker listening and therefore must be considered. Simulation of an environmental context is desirable but the quality depends on processing resources and lack of interaction with the host acoustical environment. While techniques such as data reduction of head-related transfer functions have been used widely to improve simulation fidelity, another approach involves determining thresholds for environmental acoustic events. Psychoacoustic studies relevant to this approach are reviewed in consideration of multimedia applications

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

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

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolicmore » network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. As a result, the defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.« less

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation.

PubMed

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra; Ng, Patrick; Khraiwesh, Basel; Jaiswal, Ashish; Jijakli, Kenan; Koussa, Joseph; Nelson, David R; Cai, Hong; Yang, Xinping; Chang, Roger L; Papin, Jason; Yu, Haiyuan; Balaji, Santhanam; Salehi-Ashtiani, Kourosh

2016-07-19

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. The defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

DOE PAGES

Chaiboonchoe, Amphun; Ghamsari, Lila; Dohai, Bushra; ...

2016-06-14

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolicmore » network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. As a result, the defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.« less

Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation

PubMed Central

Xu, Yaomin; Guo, Xingyi; Sun, Jiayang; Zhao, Zhongming

2015-01-01

Motivation: Large-scale cancer genomic studies, such as The Cancer Genome Atlas (TCGA), have profiled multidimensional genomic data, including mutation and expression profiles on a variety of cancer cell types, to uncover the molecular mechanism of cancerogenesis. More than a hundred driver mutations have been characterized that confer the advantage of cell growth. However, how driver mutations regulate the transcriptome to affect cellular functions remains largely unexplored. Differential analysis of gene expression relative to a driver mutation on patient samples could provide us with new insights in understanding driver mutation dysregulation in tumor genome and developing personalized treatment strategies. Results: Here, we introduce the Snowball approach as a highly sensitive statistical analysis method to identify transcriptional signatures that are affected by a recurrent driver mutation. Snowball utilizes a resampling-based approach and combines a distance-based regression framework to assign a robust ranking index of genes based on their aggregated association with the presence of the mutation, and further selects the top significant genes for downstream data analyses or experiments. In our application of the Snowball approach to both synthesized and TCGA data, we demonstrated that it outperforms the standard methods and provides more accurate inferences to the functional effects and transcriptional dysregulation of driver mutations. Availability and implementation: R package and source code are available from CRAN at http://cran.r-project.org/web/packages/DESnowball, and also available at http://bioinfo.mc.vanderbilt.edu/DESnowball/. Contact: zhongming.zhao@vanderbilt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25192743

A full-Bayesian approach to parameter inference from tracer travel time moments and investigation of scale effects at the Cape Cod experimental site

USGS Publications Warehouse

Woodbury, Allan D.; Rubin, Yoram

2000-01-01

A method for inverting the travel time moments of solutes in heterogeneous aquifers is presented and is based on peak concentration arrival times as measured at various samplers in an aquifer. The approach combines a Lagrangian [Rubin and Dagan, 1992] solute transport framework with full‐Bayesian hydrogeological parameter inference. In the full‐Bayesian approach the noise values in the observed data are treated as hyperparameters, and their effects are removed by marginalization. The prior probability density functions (pdfs) for the model parameters (horizontal integral scale, velocity, and log K variance) and noise values are represented by prior pdfs developed from minimum relative entropy considerations. Analysis of the Cape Cod (Massachusetts) field experiment is presented. Inverse results for the hydraulic parameters indicate an expected value for the velocity, variance of log hydraulic conductivity, and horizontal integral scale of 0.42 m/d, 0.26, and 3.0 m, respectively. While these results are consistent with various direct‐field determinations, the importance of the findings is in the reduction of confidence range about the various expected values. On selected control planes we compare observed travel time frequency histograms with the theoretical pdf, conditioned on the observed travel time moments. We observe a positive skew in the travel time pdf which tends to decrease as the travel time distance grows. We also test the hypothesis that there is no scale dependence of the integral scale λ with the scale of the experiment at Cape Cod. We adopt two strategies. The first strategy is to use subsets of the full data set and then to see if the resulting parameter fits are different as we use different data from control planes at expanding distances from the source. The second approach is from the viewpoint of entropy concentration. No increase in integral scale with distance is inferred from either approach over the range of the Cape Cod tracer experiment.

Running and Metabolic Demands of Elite Rugby Union Assessed Using Traditional, Metabolic Power, and Heart Rate Monitoring Methods

PubMed Central

Dubois, Romain; Paillard, Thierry; Lyons, Mark; McGrath, David; Maurelli, Olivier; Prioux, Jacques

2017-01-01

The aims of this study were (1) to analyze elite rugby union game demands using 3 different approaches: traditional, metabolic and heart rate-based methods (2) to explore the relationship between these methods and (3) to explore positional differences between the backs and forwards players. Time motion analysis and game demands of fourteen professional players (24.1 ± 3.4 y), over 5 European challenge cup games, were analyzed. Thresholds of 14.4 km·h-1, 20 W.kg-1 and 85% of maximal heart rate (HRmax) were set for high-intensity efforts across the three methods. The mean % of HRmax was 80.6 ± 4.3 % while 42.2 ± 16.5% of game time was spent above 85% of HRmax with no significant differences between the forwards and the backs. Our findings also show that the backs cover greater distances at high-speed than forwards (% difference: +35.2 ± 6.6%; p<0.01) while the forwards cover more distance than the backs (+26.8 ± 5.7%; p<0.05) in moderate-speed zone (10-14.4 km·h-1). However, no significant difference in high-metabolic power distance was found between the backs and forwards. Indeed, the high-metabolic power distances were greater than high-speed running distances of 24.8 ± 17.1% for the backs, and 53.4 ± 16.0% for the forwards with a significant difference (+29.6 ± 6.0% for the forwards; p<0.001) between the two groups. Nevertheless, nearly perfect correlations were found between the total distance assessed using the traditional approach and the metabolic power approach (r = 0.98). Furthermore, there is a strong association (r = 0.93) between the high-speed running distance (assessed using the traditional approach) and the high-metabolic power distance. The HR monitoring methods demonstrate clearly the high physiological demands of professional rugby games. The traditional and the metabolic-power approaches shows a close correlation concerning their relative values, nevertheless the difference in absolute values especially for the high-intensity thresholds demonstrates that the metabolic power approach may represent an interesting alternative to the traditional approaches used in evaluating the high-intensity running efforts required in rugby union games. Key points Elite/professional rugby union players Heart rate monitoring during official games Metabolic power approach PMID:28344455

An alternative approach to depth of field which avoids the blur circle and uses the pixel pitch

NASA Astrophysics Data System (ADS)

Schuster, Norbert

2015-09-01

Modern thermal imaging systems apply more and more uncooled detectors. High volume applications work with detectors which have a reduced pixel count (typical between 200x150 and 640x480). This shrinks the application of modern image treatment procedures like wave front coding. On the other hand side, uncooled detectors demand lenses with fast F-numbers near 1.0. Which are the limits on resolution if the target to analyze changes its distance to the camera system? The aim to implement lens arrangements without any focusing mechanism demands a deeper quantification of the Depth of Field problem. The proposed Depth of Field approach avoids the classic "accepted image blur circle". It bases on a camera specific depth of focus which is transformed in the object space by paraxial relations. The traditional RAYLEIGH's -criterion bases on the unaberrated Point Spread Function and delivers a first order relation for the depth of focus. Hence, neither the actual lens resolution neither the detector impact is considered. The camera specific depth of focus respects a lot of camera properties: Lens aberrations at actual F-number, detector size and pixel pitch. The through focus MTF is the base of the camera specific depth of focus. It has a nearly symmetric course around the maximum of sharp imaging. The through focus MTF is considered at detector's Nyquist frequency. The camera specific depth of focus is this the axial distance in front and behind of sharp image plane where the through focus MTF is <0.25. This camera specific depth of focus is transferred in the object space by paraxial relations. It follows a general applicable Depth of Field diagram which could be applied to lenses realizing a lateral magnification range -0.05…0. Easy to handle formulas are provided between hyperfocal distance and the borders of the Depth of Field in dependence on sharp distances. These relations are in line with the classical Depth of Field-theory. Thermal pictures, taken by different IR-camera cores, illustrate the new approach. The quite often requested graph "MTF versus distance" choses the half Nyquist frequency as reference. The paraxial transfer of the through focus MTF in object space distorts the MTF-curve: hard drop at closer distances than sharp distance, smooth drop at further distances. The formula of a general Diffraction-Limited-Through-Focus-MTF (DLTF) is deducted. Arbitrary detector-lens combinations could be discussed. Free variables in this analysis are waveband, aperture based F-number (lens) and pixel pitch (detector). The DLTF- discussion provides physical limits and technical requirements. The detector development with pixel pitches smaller than captured wavelength in the LWIR-region generates a special challenge for optical design.

Beyond Born-Mayer: Improved models for short-range repulsion in ab initio force fields

DOE PAGES

Van Vleet, Mary J.; Misquitta, Alston J.; Stone, Anthony J.; ...

2016-06-23

Short-range repulsion within inter-molecular force fields is conventionally described by either Lennard-Jones or Born-Mayer forms. Despite their widespread use, these simple functional forms are often unable to describe the interaction energy accurately over a broad range of inter-molecular distances, thus creating challenges in the development of ab initio force fields and potentially leading to decreased accuracy and transferability. Herein, we derive a novel short-range functional form based on a simple Slater-like model of overlapping atomic densities and an iterated stockholder atom (ISA) partitioning of the molecular electron density. We demonstrate that this Slater-ISA methodology yields a more accurate, transferable, andmore » robust description of the short-range interactions at minimal additional computational cost compared to standard Lennard-Jones or Born-Mayer approaches. Lastly, we show how this methodology can be adapted to yield the standard Born-Mayer functional form while still retaining many of the advantages of the Slater-ISA approach.« less

Imaging of the internal structure of comet 67P/Churyumov-Gerasimenko from radiotomography CONSERT Data (Rosetta Mission) through a full 3D regularized inversion of the Helmholtz equations on functional spaces

NASA Astrophysics Data System (ADS)

Barriot, Jean-Pierre; Serafini, Jonathan; Sichoix, Lydie; Benna, Mehdi; Kofman, Wlodek; Herique, Alain

We investigate the inverse problem of imaging the internal structure of comet 67P/ Churyumov-Gerasimenko from radiotomography CONSERT data by using a coupled regularized inversion of the Helmholtz equations. A first set of Helmholtz equations, written w.r.t a basis of 3D Hankel functions describes the wave propagation outside the comet at large distances, a second set of Helmholtz equations, written w.r.t. a basis of 3D Zernike functions describes the wave propagation throughout the comet with avariable permittivity. Both sets are connected by continuity equations over a sphere that surrounds the comet. This approach, derived from GPS water vapor tomography of the atmosphere,will permit a full 3D inversion of the internal structure of the comet, contrary to traditional approaches that use a discretization of space at a fraction of the radiowave wavelength.

Conditioned empirical orthogonal functions for interpolation of runoff time series along rivers: Application to reconstruction of missing monthly records

NASA Astrophysics Data System (ADS)

Li, Lingqi; Gottschalk, Lars; Krasovskaia, Irina; Xiong, Lihua

2018-01-01

Reconstruction of missing runoff data is of important significance to solve contradictions between the common situation of gaps and the fundamental necessity of complete time series for reliable hydrological research. The conventional empirical orthogonal functions (EOF) approach has been documented to be useful for interpolating hydrological series based upon spatiotemporal decomposition of runoff variation patterns, without additional measurements (e.g., precipitation, land cover). This study develops a new EOF-based approach (abbreviated as CEOF) that conditions EOF expansion on the oscillations at outlet (or any other reference station) of a target basin and creates a set of residual series by removing the dependence on this reference series, in order to redefine the amplitude functions (components). This development allows a transparent hydrological interpretation of the dimensionless components and thereby strengthens their capacities to explain various runoff regimes in a basin. The two approaches are demonstrated on an application of discharge observations from the Ganjiang basin, China. Two alternatives for determining amplitude functions based on centred and standardised series, respectively, are tested. The convergence in the reconstruction of observations at different sites as a function of the number of components and its relation to the characteristics of the site are analysed. Results indicate that the CEOF approach offers an efficient way to restore runoff records with only one to four components; it shows more superiority in nested large basins than at headwater sites and often performs better than the EOF approach when using standardised series, especially in improving infilling accuracy for low flows. Comparisons against other interpolation methods (i.e., nearest neighbour, linear regression, inverse distance weighting) further confirm the advantage of the EOF-based approaches in avoiding spatial and temporal inconsistencies in estimated series.

Clinical Evaluation of Functional Vision of +1.5 Diopters near Addition, Aspheric, Rotational Asymmetric Multifocal Intraocular Lens

PubMed Central

Khoramnia, Rahmin; Attia, Mary Safwat; Koss, Michael Janusz; Linz, Katharina; Auffarth, Gerd Uwe

2016-01-01

Purpose To evaluate postoperative outcomes and visual performance in intermediate distance after implantation of a +1.5 diopters (D) addition, aspheric, rotational asymmetric multifocal intraocular lens (MIOL). Methods Patients underwent bilateral cataract surgery with implantation of an aspheric, asymmetric MIOL with +1.5 D near addition. A complete ophthalmological examination was performed preoperatively and 3 months postoperatively. The main outcome measures were monocular and binocular uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), uncorrected intermediate visual acuity (UIVA), distance corrected intermediate visual acuity (DCIVA), uncorrected near visual acuity (UNVA) and distance corrected keratometry, and manifest refraction. The Salzburg Reading Desk was used to analyze unilateral and bilateral functional vision with uncorrected and corrected reading acuity, reading distance, reading speed, and the smallest log-scaled print size that could be read effectively at near and intermediate distances. Results The study comprised 60 eyes of 30 patients (mean age, 68.30 ± 9.26 years; range, 34 to 80 years). There was significant improvement in UDVA and CDVA. Mean UIVA was 0.01 ± 0.09 logarithm of the minimum angle of resolution (logMAR) and mean DCIVA was -0.02 ± 0.11 logMAR. In Salzburg Reading Desk analysis for UIVA, the mean subjective intermediate distance was 67.58 ± 8.59 cm with mean UIVA of -0.02 ± 0.09 logMAR and mean word count of 96.38 ± 28.32 words/min. Conclusions The new aspheric, asymmetric, +1.5 D near addition MIOL offers good results for distance visual function in combination with good performance for intermediate distances and functional results for near distance. PMID:27729759

Clinical Evaluation of Functional Vision of +1.5 Diopters near Addition, Aspheric, Rotational Asymmetric Multifocal Intraocular Lens.

PubMed

Kretz, Florian Tobias Alwin; Khoramnia, Rahmin; Attia, Mary Safwat; Koss, Michael Janusz; Linz, Katharina; Auffarth, Gerd Uwe

2016-10-01

To evaluate postoperative outcomes and visual performance in intermediate distance after implantation of a +1.5 diopters (D) addition, aspheric, rotational asymmetric multifocal intraocular lens (MIOL). Patients underwent bilateral cataract surgery with implantation of an aspheric, asymmetric MIOL with +1.5 D near addition. A complete ophthalmological examination was performed preoperatively and 3 months postoperatively. The main outcome measures were monocular and binocular uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), uncorrected intermediate visual acuity (UIVA), distance corrected intermediate visual acuity (DCIVA), uncorrected near visual acuity (UNVA) and distance corrected keratometry, and manifest refraction. The Salzburg Reading Desk was used to analyze unilateral and bilateral functional vision with uncorrected and corrected reading acuity, reading distance, reading speed, and the smallest log-scaled print size that could be read effectively at near and intermediate distances. The study comprised 60 eyes of 30 patients (mean age, 68.30 ± 9.26 years; range, 34 to 80 years). There was significant improvement in UDVA and CDVA. Mean UIVA was 0.01 ± 0.09 logarithm of the minimum angle of resolution (logMAR) and mean DCIVA was -0.02 ± 0.11 logMAR. In Salzburg Reading Desk analysis for UIVA, the mean subjective intermediate distance was 67.58 ± 8.59 cm with mean UIVA of -0.02 ± 0.09 logMAR and mean word count of 96.38 ± 28.32 words/min. The new aspheric, asymmetric, +1.5 D near addition MIOL offers good results for distance visual function in combination with good performance for intermediate distances and functional results for near distance.

Aggregation Pattern Transitions by Slightly Varying the Attractive/Repulsive Function

PubMed Central

Cheng, Zhao; Zhang, Hai-Tao; Chen, Michael Z. Q.; Zhou, Tao; Valeyev, Najl V.

2011-01-01

Among collective behaviors of biological swarms and flocks, the attractive/repulsive (A/R) functional links between particles play an important role. By slightly changing the cutoff distance of the A/R function, a drastic transition between two distinct aggregation patterns is observed. More precisely, a large cutoff distance yields a liquid-like aggregation pattern where the particle density decreases monotonously from the inside to the outwards within each aggregated cluster. Conversely, a small cutoff distance produces a crystal-like aggregation pattern where the distance between each pair of neighboring particles remains constant. Significantly, there is an obvious spinodal in the variance curve of the inter-particle distances along the increasing cutoff distances, implying a legible transition pattern between the liquid-like and crystal-like aggregations. This work bridges the aggregation phenomena of physical particles and swarming of organisms in nature upon revealing some common mechanism behind them by slightly varying their inter-individual attractive/repulsive functions, and may find its potential engineering applications, for example, in the formation design of multi-robot systems and unmanned aerial vehicles (UAVs). PMID:21799776

Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Wu, Qingyao; Song, Hengjie; Ye, Bicui

2017-02-06

Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function prediction under a usual assumption, the underlying distribution from testing data (target domain, i.e., TD) is the same as that from training data (source domain, i.e., SD). However, this assumption may be violated in real practice. To tackle this problem, in this paper, we propose a Multi-Instance Metric Transfer Learning (MIMTL) approach for genome-wide protein function prediction. In MIMTL, we first transfer the source domain distribution to the target domain distribution by utilizing the bag weights. Then, we construct a distance metric learning method with the reweighted bags. At last, we develop an alternative optimization scheme for MIMTL. Comprehensive experimental evidence on seven real-world organisms verifies the effectiveness and efficiency of the proposed MIMTL approach over several state-of-the-art methods.

A level set approach for shock-induced α-γ phase transition of RDX

NASA Astrophysics Data System (ADS)

Josyula, Kartik; Rahul; De, Suvranu

2018-02-01

We present a thermodynamically consistent level sets approach based on regularization energy functional which can be directly incorporated into a Galerkin finite element framework to model interface motion. The regularization energy leads to a diffusive form of flux that is embedded within the level sets evolution equation which maintains the signed distance property of the level set function. The scheme is shown to compare well with the velocity extension method in capturing the interface position. The proposed level sets approach is employed to study the α-γphase transformation in RDX single crystal shocked along the (100) plane. Example problems in one and three dimensions are presented. We observe smooth evolution of the phase interface along the shock direction in both models. There is no diffusion of the interface during the zero level set evolution in the three dimensional model. The level sets approach is shown to capture the characteristics of the shock-induced α-γ phase transformation such as stress relaxation behind the phase interface and the finite time required for the phase transformation to complete. The regularization energy based level sets approach is efficient, robust, and easy to implement.

Genetic Algorithm for Solving Fuzzy Shortest Path Problem in a Network with mixed fuzzy arc lengths

NASA Astrophysics Data System (ADS)

Mahdavi, Iraj; Tajdin, Ali; Hassanzadeh, Reza; Mahdavi-Amiri, Nezam; Shafieian, Hosna

2011-06-01

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model.

New approach to calculate the true-coincidence effect of HpGe detector

NASA Astrophysics Data System (ADS)

Alnour, I. A.; Wagiran, H.; Ibrahim, N.; Hamzah, S.; Siong, W. B.; Elias, M. S.

2016-01-01

The corrections for true-coincidence effects in HpGe detector are important, especially at low source-to-detector distances. This work established an approach to calculate the true-coincidence effects experimentally for HpGe detectors of type Canberra GC3018 and Ortec GEM25-76-XLB-C, which are in operation at neutron activation analysis lab in Malaysian Nuclear Agency (NM). The correction for true-coincidence effects was performed close to detector at distances 2 and 5 cm using 57Co, 60Co, 133Ba and 137Cs as standard point sources. The correction factors were ranged between 0.93-1.10 at 2 cm and 0.97-1.00 at 5 cm for Canberra HpGe detector; whereas for Ortec HpGe detector ranged between 0.92-1.13 and 0.95-100 at 2 and 5 cm respectively. The change in efficiency calibration curve of the detector at 2 and 5 cm after correction was found to be less than 1%. Moreover, the polynomial parameters functions were simulated through a computer program, MATLAB in order to find an accurate fit to the experimental data points.

Analytic study of small scale structure on cosmic strings

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

Polchinski, Joseph; Rocha, Jorge V.; Department of Physics, University of California, Santa Barbara, California 93106

2006-10-15

The properties of string networks at scales well below the horizon are poorly understood, but they enter critically into many observables. We argue that in some regimes, stretching will be the only relevant process governing the evolution. In this case, the string two-point function is determined up to normalization: the fractal dimension approaches one at short distance, but the rate of approach is characterized by an exponent that plays an essential role in network properties. The smoothness at short distance implies, for example, that cosmic string lensing images are almost undistorted. We then add in loop production as a perturbationmore » and find that it diverges at small scales. This need not invalidate the stretching model, since the loop production occurs in localized regions, but it implies a complicated fragmentation process. Our ability to model this process is limited, but we argue that loop production peaks a few orders of magnitude below the horizon scale, without the inclusion of gravitational radiation. We find agreement with some features of simulations, and interesting discrepancies that must be resolved by future work.« less

An effective fuzzy kernel clustering analysis approach for gene expression data.

PubMed

Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

2015-01-01

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

Neuromuscular factors associated with decline in long-distance running performance in master athletes.

PubMed

Brisswalter, Jeanick; Nosaka, Kazunori

2013-01-01

This review focuses on neuromuscular factors that may affect endurance performance in master athletes. During the last decade, due to the rapid increase in the number of master or veteran participants in endurance sporting competitions, many studies attempted to identify metabolic factors associated with the decrease in endurance, especially long-distance running performance with ageing, focusing on decreases in maximal oxygen consumption. However, neuromuscular factors have been less studied despite the well-known phenomena of strength loss with ageing. For master athletes to perform better in long-distance running events, it is important to reduce muscle fatigue and/or muscle damage, to improve locomotion efficiency and to facilitate recovery. To date, no consensus exists that regular endurance training is beneficial for improving locomotion efficiency, reducing muscle fatigue and muscle damage, and enhancing recovery capacity in master athletes. Some recent studies seem to indicate that master athletes have similar muscle damage to young athletes, but they require a longer recovery time after a long-distance running event. Further analyses of these parameters in master athletes require more experimental and practical interest from researchers and coaches. In particular, more attention should be directed towards the capacity to maintain muscle function with training and the role of neuromuscular factors in long-distance performance decline with ageing using a more cellular and molecular approach.

Moon illusion and spiral aftereffect: illusions due to the loom-zoom system?

PubMed

Hershenson, M

1982-12-01

The moon illusion and the spiral aftereffect are illusions in which apparent size and apparent distance vary inversely. Because this relationship is exactly opposite to that predicted by the static size--distance invariance hypothesis, the illusions have been called "paradoxical." The illusions may be understood as products of a loom-zoom system, a hypothetical visual subsystem that, in its normal operation, acts according to its structural constraint, the constancy axiom, to produce perceptions that satisfy the constraints of stimulation, the kinetic size--distance invariance hypothesis. When stimulated by its characteristic stimulus of symmetrical expansion or contraction, the loom-zoom system produces the perception of a rigid object moving in depth. If this system is stimulated by a rotating spiral, a negative motion-aftereffect is produced when rotation ceases. If fixation is then shifted to a fixed-sized disc, the aftereffect process alters perceived distance and the loom-zoom system alters perceived size such that the disc appears to expand and approach or to contract and recede, depending on the direction of rotation of the spiral. If the loom-zoom system is stimulated by a moon-terrain configuration, the equidistance tendency produces a foreshortened perceived distance for the moon as an inverse function of elevation and acts in conjunction with the loom-zoom system to produce the increased perceived size of the moon.

Regional statistics in confined two-dimensional decaying turbulence.

PubMed

Házi, Gábor; Tóth, Gábor

2011-06-28

Two-dimensional decaying turbulence in a square container has been simulated using the lattice Boltzmann method. The probability density function (PDF) of the vorticity and the particle distribution functions have been determined at various regions of the domain. It is shown that, after the initial stage of decay, the regional area averaged enstrophy fluctuates strongly around a mean value in time. The ratio of the regional mean and the overall enstrophies increases monotonously with increasing distance from the wall. This function shows a similar shape to the axial mean velocity profile of turbulent channel flows. The PDF of the vorticity peaks at zero and is nearly symmetric considering the statistics in the overall domain. Approaching the wall, the PDFs become skewed owing to the boundary layer.

Exchange and correlation in positronium-molecule scattering

NASA Astrophysics Data System (ADS)

Fabrikant, I. I.; Wilde, R. S.

2018-05-01

Exchange and correlations play a particularly important role in positronium (Ps) collisions with atoms and molecules, since the static potential for Ps interaction with a neutral system is zero. Theoretical description of both effects is a very challenging task. In the present work we use the free-electron-gas model to describe exchange and correlations in Ps collisions with molecules similar to the approach widely used in the theory of electron-molecule collisions. The results for exchange and correlation energies are presented as functions of the Fermi momentum of the electron gas and the Ps incident energy. Using the Thomas-Fermi model, these functions can be converted into exchange and correlation potentials for Ps interaction with molecules as functions of the distance between the projectile and the target.

DShaper: An approach for handling missing low-Q data in pair distribution function analysis of nanostructured systems

DOE PAGES

Olds, Daniel; Wang, Hsiu -Wen; Page, Katharine L.

2015-09-04

In this work we discuss the potential problems and currently available solutions in modeling powder-diffraction based pair-distribution function (PDF) data from systems where morphological feature information content includes distances in the nanometer length scale, such as finite nanoparticles, nanoporous networks, and nanoscale precipitates in bulk materials. The implications of an experimental finite minimum Q-value are addressed by simulation, which also demonstrates the advantages of combining PDF data with small angle scattering data (SAS). In addition, we introduce a simple Fortran90 code, DShaper, which may be incorporated into PDF data fitting routines in order to approximate the so-called shape-function for anymore » atomistic model.« less

Work stress associated cool down reactions among nurses and hospital physicians and their relation to burnout symptoms.

PubMed

Büssing, Arndt; Falkenberg, Zarah; Schoppe, Carina; Recchia, Daniela Rodrigues; Poier, Désirée

2017-08-10

Hospital staff experience high level of work stress and they have to find strategies to adapt and react to it. When they perceive emotional exhaustion and job dissatisfaction in response to constant work stress, one reaction might be emotional withdrawal. This emotional distancing can be seen as an adaptive strategy to keep 'functionality' in the job. Both, perception of emotional exhaustion and emotional distancing as a strategy, can be operationalized as 'Cool Down'. We assume that work stress associated variables are positively associated with Cool Down reactions, while internal and external resources are negatively associated and might function as a buffer against emotional distancing. Moreover, we assume that the perception of stress and work burden might be different between nurses and physicians and women and men, but not their cool down reactions as a strategy. Anonymous cross-sectional survey with standardized instruments among 1384 health care professionals (66% nurses, 34% hospital physicians). Analyses of variance, correlation and also stepwise regression analyses were performed to analyze the influence of demands and resources on Cool Down reactions. As measured with the Cool Down Index (CDI), frequency and strength of Cool Down reactions did not significantly differ between women and men, while women and men differ significantly for their burnout symptoms, stress perception and perceived work burden. With respect to profession, Cool Down and stress perception were not significantly different, but burnout and work burden. For nurses, "Emotional Exhaustion" was the best CDI predictor (51% explained variance), while in physicians it was "Depersonalization" (44% explained variance). Among putative resources which might buffer against Cool Down reactions, only team satisfaction and situational awareness had some influence, but not self-efficacy expectation. The perceptions of emotional exhaustion and distancing of nurses and physicians (and women and men) seems to be different, but not their adaptive Cool Down reactions. Data would support the notion that a structural approach of support would require first to control and eliminate work stressors, and second a multifaceted approach to strengthen and support hospital staff's resources and resilience.

Multispectral plasmon coupling microscopy and its application in bio-imaging

NASA Astrophysics Data System (ADS)

Wang, Hongyun

A broad range of cellular activities, including receptor mediated endocytosis, signaling and receptor clustering, involve multi-body interactions between different cellular functionalities. Many of these interactions are dynamic in nature, making optical tools the method of choice for their investigation. Conventional optical microscopy has a resolution about 300nm, limited by the diffraction of light, which is insufficient to explore processes that occur on nanometer or tens of nanometer length scales. The aim of this thesis is to develop and validate a plasmon coupling microscopy (PCM), which utilizes the distance dependent spectral properties of coupled noble metal nanoparticles (NPs) to resolve distance changes between NP labels on deeply sub-diffraction length scales. This colorimetric approach is augmented with a polarization sensitive analysis of the scattered light of individual dimers to monitor simultaneously distance and orientation changes. The distance dependent polarization anisotropy in discrete dimers is investigated experimentally and theoretically. The performed analysis reveals that the polarization anisotropy is robust even against relatively large refractive index changes. The polarization sensitive PCM is then applied to characterize the lateral spatial organization of mammalian plasma membranes by analyzing the translational and rotational motion as well as the extension of discrete NP dimers during their diffusion on lysed HeLa cell membranes. The membrane is found to be compartmentalized with typical domain sizes on the order of 70nm. The functionality of plasmon coupling based imaging method is expanded further by developing a multispectral imaging modality for a quantitative analysis of the plasmon coupling between many noble metal immunolabels in a large field of view simultaneously. This approach provides information about the spatial organization of the silver nanoparticle labels and thus of targeted EGF receptor densities on the surface of epidermoid carcinoma cells (A431). Finally, multispectral plasmon coupling microscopy is applied to investigate the uptake and subsequent intracellular spatial distribution of silver nanoparticles in murine macrophage cells (J774A.1). The studies reveal that NP uptake is mediated by scavenger receptors and that the intracellular NP association and distribution are heterogeneous among cells in a cellular ensemble. The heterogeneity is demonstrated to be correlated with the maturation status of the macrophages.

Estimating functional connectivity of wildlife habitat and its relevance to ecological risk assessment

USGS Publications Warehouse

Johnson, A.R.; Allen, Craig R.; Simpson, K.A.N.; Kapustka, Lawrence; Biddinger, Gregory R.; Luxon, Matthew; Galbraith, Hector

2004-01-01

Habitat fragmentation is a major threat to the viability of wildlife populations and the maintenance of biodiversity. Fragmentation relates to the sub-division of habitat into disjunct patches. Usually coincident with fragmentation per se is loss of habitat, a reduction in the size of the remnant patches, and increasing distance between patches. Natural and anthropogenic processes leading to habitat fragmentation occur at many spatial scales, and their impacts on wildlife depend on the scales at which species interact with the landscape. The concept of functional connectivity captures this organism-based view of the relative ease of movement or degree of exchange between physically disjunct habitat patches. Functional connectivity of a given habitat arrangement for a given wildlife species depends on details of the organism's life history and behavioral ecology, but, for broad categories of species, quantities such as home range size and dispersal distance scale allometrically with body mass. These relationships can be incorporated into spatial analyses of functional connectivity, which can be quantified by indices or displayed graphically in maps. We review indices and GIS-based approaches to estimating functional connectivity, presenting examples from the literature and our own work on mammalian distributions. Such analyses can be readily incorporated within an ecological risk framework. Estimates of functional connectivity may be useful in a screening-level assessment of the impact of habitat fragmentation relative to other stressors, and may be crucial in detailed population modeling and viability analysis.

Functional connectivity and structural covariance between regions of interest can be measured more accurately using multivariate distance correlation.

PubMed

Geerligs, Linda; Cam-Can; Henson, Richard N

2016-07-15

Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A harmonic analysis approach to joint inversion of P-receiver functions and wave dispersion data in high dense seismic profiles

NASA Astrophysics Data System (ADS)

Molina-Aguilera, A.; Mancilla, F. D. L.; Julià, J.; Morales, J.

2017-12-01

Joint inversion techniques of P-receiver functions and wave dispersion data implicitly assume an isotropic radial stratified earth. The conventional approach invert stacked radial component receiver functions from different back-azimuths to obtain a laterally homogeneous single-velocity model. However, in the presence of strong lateral heterogeneities as anisotropic layers and/or dipping interfaces, receiver functions are considerably perturbed and both the radial and transverse components exhibit back azimuthal dependences. Harmonic analysis methods exploit these azimuthal periodicities to separate the effects due to the isotropic flat-layered structure from those effects caused by lateral heterogeneities. We implement a harmonic analysis method based on radial and transverse receiver functions components and carry out a synthetic study to illuminate the capabilities of the method in isolating the isotropic flat-layered part of receiver functions and constrain the geometry and strength of lateral heterogeneities. The independent of the baz P receiver function are jointly inverted with phase and group dispersion curves using a linearized inversion procedure. We apply this approach to high dense seismic profiles ( 2 km inter-station distance, see figure) located in the central Betics (western Mediterranean region), a region which has experienced complex geodynamic processes and exhibit strong variations in Moho topography. The technique presented here is robust and can be applied systematically to construct a 3-D model of the crust and uppermost mantle across large networks.

Quantifying Similarity and Distance Measures for Vector-Based Datasets: Histograms, Signals, and Probability Distribution Functions

DTIC Science & Technology

2017-02-01

note, a number of different measures implemented in both MATLAB and Python as functions are used to quantify similarity/distance between 2 vector-based...this technical note are widely used and may have an important role when computing the distance and similarity of large datasets and when considering high...throughput processes. In this technical note, a number of different measures implemented in both MAT- LAB and Python as functions are used to

Advanced Techniques for Assessment of Postural and Locomotor Ataxia, Spatial Orientation, and Gaze Stability

NASA Technical Reports Server (NTRS)

Wall, Conrad., III

1999-01-01

In addition to adapting to microgravity, major neurovestibular problems of space flight include postflight difficulties with standing, walking, turning corners, and other activities that require stable upright posture and gaze stability. These difficulties inhibit astronauts' ability to stand or escape from their vehicle during emergencies. The long-ter7n goal of the NSBRI is the development of countermeasures to ameliorate the effects of long duration space flight. These countermeasures must be tested with valid and reliable tools. This project aims to develop quantitative, parametric approaches for assessing gaze stability and spatial orientation during normal gait and when gait is perturbed. Two of this year's most important findings concern head fixation distance and ideal trajectory analysis. During a normal cycle of walking the head moves up and down linearly. A simultaneous angular pitching motion of the head keeps it aligned toward an imaginary point in space at a distance of about one meter in front of a subject and along the line of march. This distance is called the head fixation distance. Head fixation distance provides the fundamental framework necessary for understanding the functional significance of the vestibular reflexes that couple head motion to eye motion. This framework facilitates the intelligent design of counter-measures for the effects of exposure to microgravity upon the vestibular ocular reflexes. Ideal trajectory analysis is a simple candidate countermeasure based upon quantifying body sway during repeated up and down stair stepping. It provides one number that estimates the body sway deviation from an ideal sinusoidal body sway trajectory normalized on the subject's height. This concept has been developed with NSBRI funding in less than one year. These findings are explained in more detail below. Compared to assessments of the vestibuo-ocular reflex, analysis of vestibular effects on locomotor function is relatively less well developed and quantified. We are improving this situation by applying methodologies such as nonlinear orbital stability to quantify responses and by using multivariate statistical approaches to link together the responses across separate tests. In this way we can exploit the information available and increase the ability to discriminate between normal and pathological responses. Measures of stability and orientation are compared to measures such as dynamic visual acuity and with balance function tests. The responses of normal human subjects and of patients having well documented pathophysiologies are being characterized. When these studies are completed, we should have a clearer idea about normal and abnormal patterns of eye, head, and body movements during locomotion and their stability in a wide range of environments. We plan eventually to use this information to validate the efficacy of candidate neurovestibular and neuromuscular rehabilitative techniques. Some representative studies made during this year are summarized.

Measuring neutrino mass imprinted on the anisotropic galaxy clustering

NASA Astrophysics Data System (ADS)

Oh, Minji; Song, Yong-Seon

2017-04-01

The anisotropic galaxy clustering of large scale structure observed by the Baryon Oscillation Spectroscopic Survey Data Release 11 is analyzed to probe the sum of neutrino masses in the small mν lesssim 1 eV limit in which the early broadband shape determined before the last scattering surface is immune from the variation of mν. The signature of mν is imprinted on the altered shape of the power spectrum at later epoch, which provides an opportunity to access the non-trivial mν through the measured anisotropic correlation function in redshift space (hereafter RSD instead of Redshift Space Distortion). The non-linear RSD corrections with massive neutrinos in the quasi linear regime are approximately estimated using one-loop order terms. We suggest an approach to probe mν simultaneously with all other distance measures and coherent growth functions, exploiting this deformation of the early broadband shape of the spectrum at later epoch. If the origin of cosmic acceleration is unknown, mν is poorly determined after marginalizing over all other observables. However, we find that the measured distances and coherent growth functions are minimally affected by the presence of mild neutrino mass. Although the standard model of cosmic acceleration is assumed to be the cosmological constant, the constraint on mν is little improved. Interestingly, the measured Cosmic Microwave Background (hereafter CMB) distance to the last scattering surface sharply slices the degeneracy between the matter content and mν, and the mν is observed to be mν = 0.19+0.28-0.17 eV which is different from massless neutrino at 68% confidence.

Randomized Approaches for Nearest Neighbor Search in Metric Space When Computing the Pairwise Distance Is Extremely Expensive

NASA Astrophysics Data System (ADS)

Wang, Lusheng; Yang, Yong; Lin, Guohui

Finding the closest object for a query in a database is a classical problem in computer science. For some modern biological applications, computing the similarity between two objects might be very time consuming. For example, it takes a long time to compute the edit distance between two whole chromosomes and the alignment cost of two 3D protein structures. In this paper, we study the nearest neighbor search problem in metric space, where the pair-wise distance between two objects in the database is known and we want to minimize the number of distances computed on-line between the query and objects in the database in order to find the closest object. We have designed two randomized approaches for indexing metric space databases, where objects are purely described by their distances with each other. Analysis and experiments show that our approaches only need to compute O(logn) objects in order to find the closest object, where n is the total number of objects in the database.

Quality Assurance in Distance Learning Libraries

ERIC Educational Resources Information Center

Tripathi, Manorama; Jeevan, V. K. J.

2009-01-01

Purpose: The paper aims to study how the present distance learning libraries can improve upon their existing services and introduce new ones to enhance quality of services to distance learners. Design/methodology/approach: The paper includes a review of literature on quality assurance in open and distance education in general and student support…

Distance Education Programs in Social Work: Current and Emerging Trends

ERIC Educational Resources Information Center

Vernon, Robert; Vakalahi, Halaevalu; Pierce, Dean; Pittman-Munke, Peggy; Adkins, Lynn Frantz

2009-01-01

This article reports on current and emerging trends in the use of distance education technologies in social work education. Areas studied include the extent of distance education programs, curricular areas covered, technologies used, pedagogical approaches, intentions for degree-program development, sources of pressure to adopt distance education…

Perception of Peripersonal and Interpersonal Space in Patients with Restrictive-type Anorexia.

PubMed

Nandrino, Jean-Louis; Ducro, Claire; Iachini, Tina; Coello, Yann

2017-05-01

This study examines whether the perception of peripersonal action-space and interpersonal social-space is modified in patients with restrictive-type anorexia in two experimental conditions using videos. First, participants stopped the video of an approaching stimulus when they felt the distance to be comfortable for interacting with it (first-person perspective). Second, participants stopped the video when an observed individual approaching a stimulus, or being approached by it, was at a comfortable distance (third-person perspective). In the first-person perspective, the results showed an estimation of peripersonal space that did not differ from controls when an object was approaching and an increase in interpersonal space compared with controls when a male or female individual was approaching. In the third-person perspective, both individual-object and individual-individual distances were larger in anorexic patients. These results indicate a specific deficit in adjusting interpersonal distances in both the first-person and third-person perspectives. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.

Why do people move? Enhancing human mobility prediction using local functions based on public records and SNS data

PubMed Central

Park, Juyong

2018-01-01

The quality of life for people in urban regions can be improved by predicting urban human mobility and adjusting urban planning accordingly. In this study, we compared several possible variables to verify whether a gravity model (a human mobility prediction model borrowed from Newtonian mechanics) worked as well in inner-city regions as it did in intra-city regions. We reviewed the resident population, the number of employees, and the number of SNS posts as variables for generating mass values for an urban traffic gravity model. We also compared the straight-line distance, travel distance, and the impact of time as possible distance values. We defined the functions of urban regions on the basis of public records and SNS data to reflect the diverse social factors in urban regions. In this process, we conducted a dimension reduction method for the public record data and used a machine learning-based clustering algorithm for the SNS data. In doing so, we found that functional distance could be defined as the Euclidean distance between social function vectors in urban regions. Finally, we examined whether the functional distance was a variable that had a significant impact on urban human mobility. PMID:29432440

Space vehicle approach velocity judgments under simulated visual space conditions

NASA Technical Reports Server (NTRS)

Haines, Richard F.

1987-01-01

Thirty-five volunteers responded when they first perceived an increase in apparent size of a collimated, 2-D image of an Orbiter vehicle. The test variables of interest included the presence of a fixed angular reticle within the field of view (FOV); three initial Orbiter distances; three constant Orbiter approach velocities corresponding to 1.6, 0.8, and 0.4 percent of the initial distance per second; and two background starfield velocities. It was found that: (1) at each initial range, increasing approach velocity led to a larger distance between the eye and Orbiter image at threshold; (2) including the fixed reticle in the FOV produced a smaller distance between the eye and Orbiter image at threshold; and (3) increasing background star velocity during this judgment led to a smaller distance between the eye and Orbiter image at threshold. The last two findings suggest that other detail within the FOV may compete for available attention which otherwise would be available for judging image expansion; thus, the target has to approach the observer nearer than otherwise if these details were present. These findings are discussed in relation to previous research and possible underlying mechanisms.

Use of Distance Education in Dental Hygiene Programs.

ERIC Educational Resources Information Center

Grimes, Ellen B.

2002-01-01

Surveyed dental hygiene programs to determine the prevalence of distance education use. Found that 22 percent have distance education, and that most were satisfied with it as an adequate alternative to traditional approaches. (EV)

Running and Metabolic Demands of Elite Rugby Union Assessed Using Traditional, Metabolic Power, and Heart Rate Monitoring Methods.

PubMed

Dubois, Romain; Paillard, Thierry; Lyons, Mark; McGrath, David; Maurelli, Olivier; Prioux, Jacques

2017-03-01

The aims of this study were (1) to analyze elite rugby union game demands using 3 different approaches: traditional, metabolic and heart rate-based methods (2) to explore the relationship between these methods and (3) to explore positional differences between the backs and forwards players. Time motion analysis and game demands of fourteen professional players (24.1 ± 3.4 y), over 5 European challenge cup games, were analyzed. Thresholds of 14.4 km·h -1 , 20 W.kg -1 and 85% of maximal heart rate (HR max ) were set for high-intensity efforts across the three methods. The mean % of HR max was 80.6 ± 4.3 % while 42.2 ± 16.5% of game time was spent above 85% of HR max with no significant differences between the forwards and the backs. Our findings also show that the backs cover greater distances at high-speed than forwards (% difference: +35.2 ± 6.6%; p<0.01) while the forwards cover more distance than the backs (+26.8 ± 5.7%; p<0.05) in moderate-speed zone (10-14.4 km·h -1 ). However, no significant difference in high-metabolic power distance was found between the backs and forwards. Indeed, the high-metabolic power distances were greater than high-speed running distances of 24.8 ± 17.1% for the backs, and 53.4 ± 16.0% for the forwards with a significant difference (+29.6 ± 6.0% for the forwards; p<0.001) between the two groups. Nevertheless, nearly perfect correlations were found between the total distance assessed using the traditional approach and the metabolic power approach (r = 0.98). Furthermore, there is a strong association (r = 0.93) between the high-speed running distance (assessed using the traditional approach) and the high-metabolic power distance. The HR monitoring methods demonstrate clearly the high physiological demands of professional rugby games. The traditional and the metabolic-power approaches shows a close correlation concerning their relative values, nevertheless the difference in absolute values especially for the high-intensity thresholds demonstrates that the metabolic power approach may represent an interesting alternative to the traditional approaches used in evaluating the high-intensity running efforts required in rugby union games.

Operative correction and follow-up of craniofacial duplication.

PubMed

Kotrikova, Bibiana; Hassfeld, Stefan; Steiner, Hans H; Hähnel, Stefan; Krempien, Robert; Mühling, Joachim

2007-03-01

Anterior craniofacial duplication (diprosopus) is an extremely rare form of conjoined twins. The children share a single trunk with normal extremities and varying degrees of facial malformation. Duplication of specific structures, such as the nose (diprosopus dirrhinus), eyes (diprosopus tetraophthalmus), and ears, is possible. The authors present a case of partial facial duplication (diprosopus dirrhinus) in a male infant. The clinical and radiographic findings and the surgical correction and follow-up are described. In a single surgical session, the authors were able to achieve not only a functionally but also an aesthetically acceptable result. In the postoperative course, the child showed nearly normal growth and satisfactory psychosocial and motor development. However, 40 months postoperatively, we noticed a tendency of the orbitae to diverge (i.e., toward hypertelorism). The surgical management of complex craniofacial malformations such as diprosopus needs a precise morphologic analysis of the patient's deformity followed by a clear treatment plan. A staged reconstructive approach is carried out to coincide with facial growth patterns and brain and eye function. If the interorbital distance in our patient increases progressively, a second operation for reduction of the interorbital distance may be necessary.

Approach to atmospheric laser-propagation theory based on the extended Huygens-Fresnel principle and a self-consistency concept.

PubMed

Bochove, Erik J; Rao Gudimetla, V S

2017-01-01

We propose a self-consistency condition based on the extended Huygens-Fresnel principle, which we apply to the propagation kernel of the mutual coherence function of a partially coherent laser beam propagating through a turbulent atmosphere. The assumption of statistical independence of turbulence in neighboring propagation segments leads to an integral equation in the propagation kernel. This integral equation is satisfied by a Gaussian function, with dependence on the transverse coordinates that is identical to the previous Gaussian formulation by Yura [Appl. Opt.11, 1399 (1972)APOPAI0003-693510.1364/AO.11.001399], but differs in the transverse coherence length's dependence on propagation distance, so that this established version violates our self-consistency principle. Our formulation has one free parameter, which in the context of Kolmogorov's theory is independent of turbulence strength and propagation distance. We determined its value by numerical fitting to the rigorous beam propagation theory of Yura and Hanson [J. Opt. Soc. Am. A6, 564 (1989)JOAOD60740-323210.1364/JOSAA.6.000564], demonstrating in addition a significant improvement over other Gaussian models.

Quarkonium polarization and the long distance matrix elements hierarchies using jet substructure

NASA Astrophysics Data System (ADS)

Dai, Lin; Shrivastava, Prashant

2017-08-01

We investigate the quarkonium production mechanisms in jets at the LHC, using the fragmenting jet functions (FJF) approach. Specifically, we discuss the jet energy dependence of the J /ψ production cross section at the LHC. By comparing the cross sections for the different NRQCD production channels (1S0[8], 3S1[8], 3PJ[8], and 3cripts>S1[1]), we find that at fixed values of energy fraction z carried by the J /ψ , if the normalized cross section is a decreasing function of the jet energy, in particular for z >0.5 , then the depolarizing 1S0[8] must be the dominant channel. This makes the prediction made in [Baumgart et al., J. High Energy Phys. 11 (2014) 003, 10.1007/JHEP11(2014)003] for the FJF's also true for the cross section. We also make comparisons between the long distance matrix elements extracted by various groups. This analysis could potentially shed light on the polarization properties of the J /ψ production in high pT region.

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

PubMed

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Adventure Learning: Transformative Hybrid Online Education

ERIC Educational Resources Information Center

Doering, Aaron

2006-01-01

Adventure learning (AL) is a hybrid distance education approach that provides students with opportunities to explore real-world issues through authentic learning experiences within collaborative learning environments. This article defines this online distance education approach, outlines an AL framework, and showcases an AL archetype. In AL…

Optimizing Environmental Monitoring Networks with Direction-Dependent Distance Thresholds.

ERIC Educational Resources Information Center

Hudak, Paul F.

1993-01-01

In the direction-dependent approach to location modeling developed herein, the distance within which a point of demand can find service from a facility depends on direction of measurement. The utility of the approach is illustrated through an application to groundwater remediation. (Author/MDH)

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

PubMed Central

Laurent, Georges St.; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J.L.; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R.R.; Nicolas, Estelle; McCaffrey, Timothy A.; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-01-01

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlincRNAs genes likely function in cis to activate nearby genes. This effect while most pronounced in closely spaced vlincRNA–gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlincRNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. PMID:27001520

Twisted trees and inconsistency of tree estimation when gaps are treated as missing data - The impact of model mis-specification in distance corrections.

PubMed

McTavish, Emily Jane; Steel, Mike; Holder, Mark T

2015-12-01

Statistically consistent estimation of phylogenetic trees or gene trees is possible if pairwise sequence dissimilarities can be converted to a set of distances that are proportional to the true evolutionary distances. Susko et al. (2004) reported some strikingly broad results about the forms of inconsistency in tree estimation that can arise if corrected distances are not proportional to the true distances. They showed that if the corrected distance is a concave function of the true distance, then inconsistency due to long branch attraction will occur. If these functions are convex, then two "long branch repulsion" trees will be preferred over the true tree - though these two incorrect trees are expected to be tied as the preferred true. Here we extend their results, and demonstrate the existence of a tree shape (which we refer to as a "twisted Farris-zone" tree) for which a single incorrect tree topology will be guaranteed to be preferred if the corrected distance function is convex. We also report that the standard practice of treating gaps in sequence alignments as missing data is sufficient to produce non-linear corrected distance functions if the substitution process is not independent of the insertion/deletion process. Taken together, these results imply inconsistent tree inference under mild conditions. For example, if some positions in a sequence are constrained to be free of substitutions and insertion/deletion events while the remaining sites evolve with independent substitutions and insertion/deletion events, then the distances obtained by treating gaps as missing data can support an incorrect tree topology even given an unlimited amount of data. Copyright © 2015 Elsevier Inc. All rights reserved.

Bifocal Stereo for Multipath Person Re-Identification

NASA Astrophysics Data System (ADS)

Blott, G.; Heipke, C.

2017-11-01

This work presents an approach for the task of person re-identification by exploiting bifocal stereo cameras. Present monocular person re-identification approaches show a decreasing working distance, when increasing the image resolution to obtain a higher reidentification performance. We propose a novel 3D multipath bifocal approach, containing a rectilinear lens with larger focal length for long range distances and a fish eye lens of a smaller focal length for the near range. The person re-identification performance is at least on par with 2D re-identification approaches but the working distance of the approach is increased and on average 10% more re-identification performance can be achieved in the overlapping field of view compared to a single camera. In addition, the 3D information is exploited from the overlapping field of view to solve potential 2D ambiguities.

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

The dust environment of 67P/Churyumov-Gerasimenko as seen through Rosetta/OSIRIS

NASA Astrophysics Data System (ADS)

Tubiana, Cecilia; Bertini, Ivano; Deller, Jakob; Drolshagen, Esther; Frattin, Elisa; Güttler, Carsten; Hofmann, Marc; Koschny, Detlef; Oklay, Nilda; Ott, Theresa; Shi, Xian; Sierks, Holger; Vincent, Jean-Baptiste; OSIRIS Team

2016-10-01

The ESA's Rosetta spacecraft had the unique opportunity to stay in the vicinity of the comet for two years, observing how the comet evolved while approaching the Sun, passing through perihelion and then moving outwards. OSIRIS, the Optical, Spectroscopic, and Infrared Remote Imaging System onboard Rosetta, imaged the nucleus and the dust environment of 67/Churyumov-Gerasimenko since the beginning of post-hibernation operations in March 2014. We focus here on dust studies carried on with OSIRIS.Images obtained in different filters in the visible wavelength range have been used to study the unresolved dust coma, investigating its diurnal and seasonal variations and providing insights into the dust composition. A correlation has been found between the level of diurnal activity and the region of the nucleus surface in sunlight, suggesting that the topography and/or composition of the surface play an important role. The overall activity increases while the comet is approaching the Sun, peaking about a month after perihelion. Comparison with ground-based observations will allow to understand if the dust coma behaves in similar ways at small scales - as observed by Rosetta/OSIRIS - and at large scales - as observed from ground. Several times during the mission, we acquired images spanning the phase angle range 0-165 degrees. They are used to determine the dust phase function in different wavelengths, its evolution with heliocentric distance and to investigate the intimate nature of cometary dust aggregates by solving the inverse scattering problem. A large amount of individual aggregates is present in the vicinity of 67P/Churyumov-Gerasimenko. We used OSIRIS NAC and WAC images to determine the aggregate properties: size and distance distributions, colors and rotation. Thanks to observations performed at different heliocentric distances, we address how those properties are changing with heliocentric distance.

Thermally activated rotational disorder in CaMoO 4 nanocrystals

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

Culver, Sean P.; Brutchey, Richard L.

2016-04-12

In this study, a dual-space approach, combining Rietveld and pair distribution function (PDF) analyses, has been applied to temperature-dependent synchrotron X-ray total scattering data collected on vapor diffusion sol–gel derived CaMoO 4 nanocrystals. A sharp transition in Ca–O bond distances in the range of 151–163 K was identified by PDF analysis, which is attributed to the thermal activation of rotational disorder associated with the rigid MoO 4 tetrahedra.

The Current State and TRL Assessment of People Tracking Technology for Video Surveillance Applications

DTIC Science & Technology

2014-09-01

the feature-space used to represent the target. Sometimes we trade off keeping information about one domain of the target in exchange for robustness... Kullback - Leibler distance), can be used as a similarity function between a candidate target and a template. This approach is invariant to changes in scale...basis vectors to adapt to appearance change and learns the visual information that the set of targets have in common, which is used to reduce the

Clinical evaluation of semi-automatic open-source algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action.

PubMed

Wallner, Jürgen; Hochegger, Kerstin; Chen, Xiaojun; Mischak, Irene; Reinbacher, Knut; Pau, Mauro; Zrnc, Tomislav; Schwenzer-Zimmerer, Katja; Zemann, Wolfgang; Schmalstieg, Dieter; Egger, Jan

2018-01-01

Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice. In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance. Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p<0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the two groups. Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.

Self-potential response to periodic pumping test: a numerical study

NASA Astrophysics Data System (ADS)

Konosavsky, Pavel; Maineult, Alexis; Narbut, Mikhail; Titov, Konstantin

2017-09-01

We numerically model self-potential responses associated with periodic pumping test experiments by sequential calculation of the hydraulic response and the coupled electrical potential. We assume the pumping test experiments with a fully saturated confined aquifer. Application of different excitation functions leads to quasi-linear trends in electrical records whose direction and intensity depend on the form of the excitation function. The hydraulic response is phase shifted compared to the excitation function; the phase shift increases quasi-linearly with the distance from the pumping well. For the electrical signals, we investigated separately the cases of conducting and insulating casings of the pumping well. For the conducting casing the electrical signals are larger in magnitude than that for the insulating casing; they reproduce the drawdown signals in the pumping well at any distance from the well and exhibit any phase shift with the increased distance. For the insulating casing, the electrical signals are phase shifted and their shape depends on the distance from the pumping well. Three characteristic regimes were found for the phase shift, φ, with the increased distance and for various hydraulic diffusivity values. At small distances φ increases quasi-linearly; at intermediate distances φ attends the value of π/2 and stay about this value (for relatively small diffusivity values); and at large distances φ attends the value of π and, stay about this value at larger distances. This behaviour of the electrical signals can be explained by two electrical sources of reverse polarity. They are (i) linear, time independent, and located at the pumping interval of the well; and (ii) volumetric, time dependent, with maximum value located in the aquifer at the distance corresponding to maximum variation of the hydraulic head magnitude with time. We also model the variation of the amplitude and phase of the hydraulic and electrical signals with increased excitation function period, and we show the characteristic periods corresponding to transition of the periodic pumping test regime to the classical pumping test regime, when the excitation function is considered as the step-function. This transition depends on the distance from the pumping well and the hydraulic diffusivity value of aquifer. Finally, with this modelling of saturated flow we reproduced in sufficient details the field data previously obtained by Maineult et al.

An intrinsic representation of atomic structure: From clusters to periodic systems

NASA Astrophysics Data System (ADS)

Li, Xiao-Tian; Xu, Shao-Gang; Yang, Xiao-Bao; Zhao, Yu-Jun

2017-10-01

We have improved our distance matrix and eigen-subspace projection function (EPF) [X.-T. Li et al., J. Chem. Phys. 146, 154108 (2017)] to describe the atomic structure for periodic systems. Depicting the local structure of an atom, the EPF turns out to be invariant with respect to the choices of the unit cell and coordinate frame, leading to an intrinsic representation of the crystal with a set of EPFs of the nontrivial atoms. The difference of EPFs reveals the difference of atoms in local structure, while the accumulated difference between two sets of EPFs can be taken as the distance between configurations. Exemplified with the cases of carbon allotropes and boron sheets, our EPF approach shows exceptional rationality and efficiency to distinguish the atomic structures, which is crucial in structure recognition, comparison, and analysis.

An intrinsic representation of atomic structure: From clusters to periodic systems.

PubMed

Li, Xiao-Tian; Xu, Shao-Gang; Yang, Xiao-Bao; Zhao, Yu-Jun

2017-10-14

We have improved our distance matrix and eigen-subspace projection function (EPF) [X.-T. Li et al., J. Chem. Phys. 146, 154108 (2017)] to describe the atomic structure for periodic systems. Depicting the local structure of an atom, the EPF turns out to be invariant with respect to the choices of the unit cell and coordinate frame, leading to an intrinsic representation of the crystal with a set of EPFs of the nontrivial atoms. The difference of EPFs reveals the difference of atoms in local structure, while the accumulated difference between two sets of EPFs can be taken as the distance between configurations. Exemplified with the cases of carbon allotropes and boron sheets, our EPF approach shows exceptional rationality and efficiency to distinguish the atomic structures, which is crucial in structure recognition, comparison, and analysis.

Submandibular approach to the C2-3 disc level: microsurgical anatomy with clinical application.

PubMed

Russo, Antonino; Albanese, Erminia; Quiroga, Monica; Ulm, Arthur J

2009-04-01

Approaching the C2-3 disc level is challenging because of its location behind the mandible and the vital neurovascular structures overlying the area. The purpose of this study was to illustrate in a stepwise fashion the microsurgical anatomy of the submandibular approach to the C2-3 disc. Ten adult formalin-fixed cadaveric specimens (20 sides) were studied. Particular attention was paid to the structures limiting the exposure. The authors measured the distance between the inferior border of the mandible and the marginal mandibular branch of the facial nerve running inferior to the mandible, the distance between the horizontal segment of the hypoglossal nerve and the hyoid bone, and the distance between the horizontal segment of the hypoglossal nerve and the mandible. They compared the location of the superior laryngeal nerve with regard to the submandibular and the standard Smith-Robinson approaches. A clinical case illustrating the usefulness of the surgical technique in this region is presented. The mean distance between the inferior border of the mandible and the lowest point of the marginal mandibular branch of the facial nerve was 6.7 +/- 1.69 mm. The hypoglossal nerve's mean distance above the hyoid bone was 8.4 +/- 1.78 mm and below the mandible was 19.6 +/- 6.39 mm. The internal branch of the superior laryngeal nerve, with respect to the cervical spine, always entered the thyrohyoid membrane just inferior to the C-3 vertebral body. The superior laryngeal nerve was found to be an impediment to approaching the C2-3 disc through the standard Smith-Robinson approach. The submandibular approach provides excellent exposure, with a perpendicular view of the C2-3 disc level. This approach is one of the options to be considered when dealing with high cervical pathologies.

Probability Distributions of Minkowski Distances between Discrete Random Variables.

ERIC Educational Resources Information Center

Schroger, Erich; And Others

1993-01-01

Minkowski distances are used to indicate similarity of two vectors in an N-dimensional space. How to compute the probability function, the expectation, and the variance for Minkowski distances and the special cases City-block distance and Euclidean distance. Critical values for tests of significance are presented in tables. (SLD)

Assessment of auditory distance in a territorial songbird: accurate feat or rule of thumb?

PubMed

Naguib; Klump; Hillmann; Grießmann; Teige

2000-04-01

Territorial passerines presumably benefit from their ability to use auditory cues to judge the distance to singing conspecifics, by increasing the efficiency of their territorial defence. Here, we report data on the approach of male territorial chaffinches, Fringilla coelebs, to a loudspeaker broadcasting conspecific song simulating a rival at various distances by different amounts of song degradation. Songs were degraded digitally in a computer-simulated forest emulating distances of 0, 20, 40, 80 and 120 m. The approach distance of chaffinches towards the loudspeaker increased with increasing amounts of degradation indicating a perceptual representation of differences in distance of a sound source. We discuss the interindividual variation of male responses with respect to constraints resulting from random variation of ranging cues provided by the environmental song degradation, the perception accuracy and the decision rules. Copyright 2000 The Association for the Study of Animal Behaviour.

A new approach to geographic partitioning of probabilistic seismic hazard using seismic source distance with earthquake extreme and perceptibility statistics: an application to the southern Balkan region

NASA Astrophysics Data System (ADS)

Bayliss, T. J.

2016-02-01

The southeastern European cities of Sofia and Thessaloniki are explored as example site-specific scenarios by geographically zoning their individual localized seismic sources based on the highest probabilities of magnitude exceedance. This is with the aim of determining the major components contributing to each city's seismic hazard. Discrete contributions from the selected input earthquake catalogue are investigated to determine those areas that dominate each city's prevailing seismic hazard with respect to magnitude and source-to-site distance. This work is based on an earthquake catalogue developed and described in a previously published paper by the author and components of a magnitude probability density function. Binned magnitude and distance classes are defined using a joint magnitude-distance distribution. The prevailing seismicity to each city-as defined by a child data set extracted from the parent earthquake catalogue for each city considered-is divided into distinct constrained data bins of small discrete magnitude and source-to-site distance intervals. These are then used to describe seismic hazard in terms of uni-variate modal values; that is, M* and D* which are the modal magnitude and modal source-to-site distance in each city's local historical seismicity. This work highlights that Sofia's dominating seismic hazard-that is, the modal magnitudes possessing the highest probabilities of occurrence-is located in zones confined to two regions at 60-80 km and 170-180 km from this city, for magnitude intervals of 5.75-6.00 Mw and 6.00-6.25 Mw respectively. Similarly, Thessaloniki appears prone to highest levels of hazard over a wider epicentral distance interval, from 80 to 200 km in the moment magnitude range 6.00-6.25 Mw.

Padé Approximant and Minimax Rational Approximation in Standard Cosmology

NASA Astrophysics Data System (ADS)

Zaninetti, Lorenzo

2016-02-01

The luminosity distance in the standard cosmology as given by $\\Lambda$CDM and consequently the distance modulus for supernovae can be defined by the Pad\\'e approximant. A comparison with a known analytical solution shows that the Pad\\'e approximant for the luminosity distance has an error of $4\\%$ at redshift $= 10$. A similar procedure for the Taylor expansion of the luminosity distance gives an error of $4\\%$ at redshift $=0.7 $; this means that for the luminosity distance, the Pad\\'e approximation is superior to the Taylor series. The availability of an analytical expression for the distance modulus allows applying the Levenberg--Marquardt method to derive the fundamental parameters from the available compilations for supernovae. A new luminosity function for galaxies derived from the truncated gamma probability density function models the observed luminosity function for galaxies when the observed range in absolute magnitude is modeled by the Pad\\'e approximant. A comparison of $\\Lambda$CDM with other cosmologies is done adopting a statistical point of view.

Re-evaluating causal modeling with mantel tests in landscape genetics

Treesearch

Samuel A. Cushman; Tzeidle N. Wasserman; Erin L. Landguth; Andrew J. Shirk

2013-01-01

The predominant analytical approach to associate landscape patterns with gene flow processes is based on the association of cost distances with genetic distances between individuals. Mantel and partial Mantel tests have been the dominant statistical tools used to correlate cost distances and genetic distances in landscape genetics. However, the inherent high...

College Students' Perceptions of Quality in Distance Education: The Importance of Communication

ERIC Educational Resources Information Center

Ortiz-Rodriguez, Madeline; Telg, Ricky W.; Irani, Tracy; Roberts, T. Grady; Rhoades, Emily

2005-01-01

Quality in distance education has been studied mostly from a top-down approach, from administration and faculty to students. This study was an attempt to understand quality through the eyes of the distance learner. This study identified undergraduate and graduate students' perceptions about quality in distance education, examining factors…

Computer simulation of the last support phase of the long jump.

PubMed

Chow, John W; Hay, James G

2005-01-01

The purpose was to examine the interacting roles played by the approach velocity, the explosive strength (represented by vertical ground reaction force [VGRF]), and the change in angular momentum about a transverse axis through the jumper's center of mass (deltaHzz) during the last support phase of the long jump, using a computer simulation technique. A two-dimensional inverted-pendulum-plus-foot segment model was developed to simulate the last support phase. Using a reference jump derived from a jump performance reported in the literature, the effects of varying individual parameters were studied using sensitivity analyses. In each sensitivity analysis, the kinematic characteristics of the longest jumps with the deltaHzz considered and not considered when the parameter of interest was altered were noted. A sensitivity analysis examining the influence of altering both approach velocity and VGRF at the same time was also conducted. The major findings were that 1) the jump distance was more sensitive to changes in approach velocity (e.g., a 10% increase yielded a 10.0% increase in jump distance) than to changes in the VGRF (e.g., a 10% increase yielded a 7.2% increase in jump distance); 2) the relatively large change in jump distance when both the approach velocity and VGRF were altered (e.g., a 10% increase in both parameters yielded a 20.4% increase in jump distance), suggesting that these two parameters are not independent factors in determining the jump distance; and 3) the jump distance was overestimated if the deltaHzz was not considered in the analysis.

Astrophysics to z approx. 10 with Gravitational Waves

NASA Technical Reports Server (NTRS)

Stebbins, Robin; Hughes, Scott; Lang, Ryan

2007-01-01

The most useful characterization of a gravitational wave detector's performance is the accuracy with which astrophysical parameters of potential gravitational wave sources can be estimated. One of the most important source types for the Laser Interferometer Space Antenna (LISA) is inspiraling binaries of black holes. LISA can measure mass and spin to better than 1% for a wide range of masses, even out to high redshifts. The most difficult parameter to estimate accurately is almost always luminosity distance. Nonetheless, LISA can measure luminosity distance of intermediate-mass black hole binary systems (total mass approx.10(exp 4) solar mass) out to z approx.10 with distance accuracies approaching 25% in many cases. With this performance, LISA will be able to follow the merger history of black holes from the earliest mergers of proto-galaxies to the present. LISA's performance as a function of mass from 1 to 10(exp 7) solar mass and of redshift out to z approx. 30 will be described. The re-formulation of LISA's science requirements based on an instrument sensitivity model and parameter estimation will be described.

Robust valley polarization of helium ion modified atomically thin MoS2

NASA Astrophysics Data System (ADS)

Klein, J.; Kuc, A.; Nolinder, A.; Altzschner, M.; Wierzbowski, J.; Sigger, F.; Kreupl, F.; Finley, J. J.; Wurstbauer, U.; Holleitner, A. W.; Kaniber, M.

2018-01-01

Atomically thin semiconductors have dimensions that are commensurate with critical feature sizes of future optoelectronic devices defined using electron/ion beam lithography. Robustness of their emergent optical and valleytronic properties is essential for typical exposure doses used during fabrication. Here, we explore how focused helium ion bombardement affects the intrinsic vibrational, luminescence and valleytronic properties of atomically thin MoS2 . By probing the disorder dependent vibrational response we deduce the interdefect distance by applying a phonon confinement model. We show that the increasing interdefect distance correlates with disorder-related luminscence arising 180 meV below the neutral exciton emission. We perform ab initio density functional theory of a variety of defect related morphologies, which yield first indications on the origin of the observed additional luminescence. Remarkably, no significant reduction of free exciton valley polarization is observed until the interdefect distance approaches a few nanometers, namely the size of the free exciton Bohr radius. Our findings pave the way for direct writing of sub-10 nm nanoscale valleytronic devices and circuits using focused helium ions.

Critical Casimir effect for colloids close to chemically patterned substrates.

PubMed

Tröndle, M; Kondrat, S; Gambassi, A; Harnau, L; Dietrich, S

2010-08-21

Colloids immersed in a critical or near-critical binary liquid mixture and close to a chemically patterned substrate are subject to normal and lateral critical Casimir forces of dominating strength. For a single colloid, we calculate these attractive or repulsive forces and the corresponding critical Casimir potentials within mean-field theory. Within this approach we also discuss the quality of the Derjaguin approximation and apply it to Monte Carlo simulation data available for the system under study. We find that the range of validity of the Derjaguin approximation is rather large and that it fails only for surface structures which are very small compared to the geometric mean of the size of the colloid and its distance from the substrate. For certain chemical structures of the substrate, the critical Casimir force acting on the colloid can change sign as a function of the distance between the particle and the substrate; this provides a mechanism for stable levitation at a certain distance which can be strongly tuned by temperature, i.e., with a sensitivity of more than 200 nm/K.

Sensitivity analyses of stopping distance for connected vehicles at active highway-rail grade crossings.

PubMed

Hsu, Chung-Jen; Jones, Elizabeth G

2017-02-01

This paper performs sensitivity analyses of stopping distance for connected vehicles (CVs) at active highway-rail grade crossings (HRGCs). Stopping distance is the major safety factor at active HRGCs. A sensitivity analysis is performed for each variable in the function of stopping distance. The formulation of stopping distance treats each variable as a probability density function for implementing Monte Carlo simulations. The result of the sensitivity analysis shows that the initial speed is the most sensitive factor to stopping distances of CVs and non-CVs. The safety of CVs can be further improved by the early provision of onboard train information and warnings to reduce the initial speeds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Plant salt stress status is transmitted systemically via propagating calcium waves

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

Stephan, Aaron B.; Schroeder, Julian I.

The existence and relevance of rapid long distance signaling in plants is evident to any observer of the nastic movements of the Venus flytrap (Dionaea muscipula) or the sensitive plant (Mimosa pudica). However, all plants require the transmission of sensory information from the site of perception to other tissues to adjust their physiological states according to their environment. It is becoming increasingly apparent that rapid long-distance signals exist throughout the plant kingdom and may be responsible for initiating a multitude of physiological responses: electrical “action potentials” have been shown to convey wounding and saltstress information from leaf-to-leaf (1, 2); amore » “hydraulic signal” transmitted by the direction of water movement within the xylem can mediate long-distance signaling of water stress experienced by the roots to the leaves in Arabidopsis (3); and reactive oxygen species (ROS) have been shown to propagate across a plant and carry stimulus-specific information to a variety of stresses (4). In PNAS, Choi et al. (5) use elegant approaches and present advances demonstrating that calcium can function as a long-distance signaling messenger, propagating in waves from roots and carrying salt-stress signals to induce expression of salt tolerance genes in leaves.« less

Close-in characteristics of LH2/LOX reactions

NASA Technical Reports Server (NTRS)

Riehl, W. A.; Ullian, L. J.

1985-01-01

In deriving shock overpressures from space vehicles employing LH2 and LOX, separate methods of analyses and prediction are recommended, as a function of the distance. Three methods of treatment are recommended. For the Far Field - where the expected shock overpressure is less than 40 psi (lambda = 5) - use the classical PYRO approach to determine TNT yield, and employ classical ordnance (Kingery) curve to obtain the overall value. For the Close-In Range, a suggested limit is 3D, or a zone from a distance of three times the tank diameter to the tank wall. Rather than estimate a specific distance from the center of explosion to the target, it is only necessary to estimate whether this could be within one, two, or three diameters away from the wall; i.e., in the 1, 2, or 3D zone. Then assess whether mixing mode is by the PYRO CBGS (spill) mode or CBM (internal mixing) mode. From the zone and mixing mode, the probability of attaining various shock overpressures is determined from the plots provided herein. For the transition zone, between 40 psi and the 3D distance, it is tentatively recommended that both of the preceding methods be used, and to be conservative, the higher resulting value be used.

Approaches to the study of neural coding of sound source location and sound envelope in real environments

PubMed Central

Kuwada, Shigeyuki; Bishop, Brian; Kim, Duck O.

2012-01-01

The major functions of the auditory system are recognition (what is the sound) and localization (where is the sound). Although each of these has received considerable attention, rarely are they studied in combination. Furthermore, the stimuli used in the bulk of studies did not represent sound location in real environments and ignored the effects of reverberation. Another ignored dimension is the distance of a sound source. Finally, there is a scarcity of studies conducted in unanesthetized animals. We illustrate a set of efficient methods that overcome these shortcomings. We use the virtual auditory space method (VAS) to efficiently present sounds at different azimuths, different distances and in different environments. Additionally, this method allows for efficient switching between binaural and monaural stimulation and alteration of acoustic cues singly or in combination to elucidate neural mechanisms underlying localization and recognition. Such procedures cannot be performed with real sound field stimulation. Our research is designed to address the following questions: Are IC neurons specialized to process what and where auditory information? How does reverberation and distance of the sound source affect this processing? How do IC neurons represent sound source distance? Are neural mechanisms underlying envelope processing binaural or monaural? PMID:22754505

Identifying impediments to long-distance mammal migrations.

PubMed

Seidler, Renee G; Long, Ryan A; Berger, Joel; Bergen, Scott; Beckmann, Jon P

2015-02-01

In much of the world, the persistence of long-distance migrations by mammals is threatened by development. Even where human population density is relatively low, there are roads, fencing, and energy development that present barriers to animal movement. If we are to conserve species that rely on long-distance migration, then it is critical that we identify existing migration impediments. To delineate stopover sites associated with anthropogenic development, we applied Brownian bridge movement models to high-frequency locations of pronghorn (Antilocapra americana) in the Greater Yellowstone Ecosystem. We then used resource utilization functions to assess the threats to long-distance migration of pronghorn that were due to fences and highways. Migrating pronghorn avoided dense developments of natural gas fields. Highways with relatively high volumes of traffic and woven-wire sheep fence acted as complete barriers. At crossings with known migration bottlenecks, use of high-quality forage and shrub habitat by pronghorn as they approached the highway was lower than expected based on availability of those resources. In contrast, pronghorn consistently utilized high-quality forage close to the highway at crossings with no known migration bottlenecks. Our findings demonstrate the importance of minimizing development in migration corridors in the future and of mitigating existing pressure on migratory animals by removing barriers, reducing the development footprint, or installing crossing structures. © 2014 Society for Conservation Biology.

Plant salt stress status is transmitted systemically via propagating calcium waves

DOE PAGES

Stephan, Aaron B.; Schroeder, Julian I.

2014-04-29

The existence and relevance of rapid long distance signaling in plants is evident to any observer of the nastic movements of the Venus flytrap (Dionaea muscipula) or the sensitive plant (Mimosa pudica). However, all plants require the transmission of sensory information from the site of perception to other tissues to adjust their physiological states according to their environment. It is becoming increasingly apparent that rapid long-distance signals exist throughout the plant kingdom and may be responsible for initiating a multitude of physiological responses: electrical “action potentials” have been shown to convey wounding and saltstress information from leaf-to-leaf (1, 2); amore » “hydraulic signal” transmitted by the direction of water movement within the xylem can mediate long-distance signaling of water stress experienced by the roots to the leaves in Arabidopsis (3); and reactive oxygen species (ROS) have been shown to propagate across a plant and carry stimulus-specific information to a variety of stresses (4). In PNAS, Choi et al. (5) use elegant approaches and present advances demonstrating that calcium can function as a long-distance signaling messenger, propagating in waves from roots and carrying salt-stress signals to induce expression of salt tolerance genes in leaves.« less

How aquatic water-beetle larvae with small chambered eyes overcome challenges of hunting under water.

PubMed

Stowasser, Annette; Buschbeck, Elke K

2014-11-01

A particularly unusual visual system exists in the visually guided aquatic predator, the Sunburst Diving Beetle, Thermonectus marmoratus (Coleoptera: Dytiscidae). The question arises: how does this peculiar visual system function? A series of experiments suggests that their principal eyes (E1 and E2) are highly specialized for hunting. These eyes are tubular and have relatively long focal lengths leading to high image magnification. Their retinae are linear, and are divided into distinct green-sensitive distal and UV and polarization-sensitive proximal portions. Each distal retina, moreover, has many tiers of photoreceptors with rhabdomeres the long axis of which are peculiarly oriented perpendicular to the light path. Based on detailed optical investigations, the lenses of these eyes are bifocal and project focused images onto specific retinal tiers. Behavioral experiments suggest that these larvae approach prey within their eyes' near-fields, and that they can correctly gauge prey distances even when conventional distance-vision mechanisms are unavailable. In the near-field of these eyes object distance determines which of the many retinal layers receive the best-focused images. This retinal organization could facilitate an unusual distance-vision mechanism. We here summarize past findings and discuss how these eyes allow Thermonectus larvae to be such successful predators.

Identification of landscape features influencing gene flow: How useful are habitat selection models?

USGS Publications Warehouse

Roffler, Gretchen H.; Schwartz, Michael K.; Pilgrim, Kristy L.; Talbot, Sandra L.; Sage, Kevin; Adams, Layne G.; Luikart, Gordon

2016-01-01

Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider explicit assumptions and spatial scales of measurement. We calculated pairwise genetic distance among 301 Dall's sheep (Ovis dalli dalli) in southcentral Alaska using an intensive noninvasive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important during summer (rugged terrain, mid-range elevation) were not influential to effective dispersal. This work underscores that consideration of both habitat selection and landscape genetics models may be useful in developing management strategies to both meet the immediate survival of a species and allow for long-term genetic connectivity.

Delay, Probability, and Social Discounting in a Public Goods Game

ERIC Educational Resources Information Center

Jones, Bryan A.; Rachlin, Howard

2009-01-01

A human social discount function measures the value to a person of a reward to another person at a given social distance. Just as delay discounting is a hyperbolic function of delay, and probability discounting is a hyperbolic function of odds-against, social discounting is a hyperbolic function of social distance. Experiment 1 obtained individual…

A search of impact orbits for near-Earth objects by means of minimization of two target functions product. (Russian Title: Поиск столкновительных орбит астероидов, сближающихся с Землей, с помощью минимизации произведения двух целевых функций)

NASA Astrophysics Data System (ADS)

Baturin, A. P.

2011-07-01

The method of NEO's impact orbits search based on two target functions product minimization is presented. These functions are: a square of asteroid-Earth distance at the moment of close approach and a sum of squares of angular residuals. Besides, the method includes a minimization of asteroid-Earth distance's square in function of time alone when initial motion parameters are fixed. Both minimizations are carrying out in turn each by another. The testing of method has been made on the problem of Apophis's impact orbit search. The results of the testing have depicted an effectivity of presented method in searching of impact orbits for the Apophis's Earth encounters in 2036 and 2037.

Approximate Bayesian computation in large-scale structure: constraining the galaxy-halo connection

NASA Astrophysics Data System (ADS)

Hahn, ChangHoon; Vakili, Mohammadjavad; Walsh, Kilian; Hearin, Andrew P.; Hogg, David W.; Campbell, Duncan

2017-08-01

Standard approaches to Bayesian parameter inference in large-scale structure assume a Gaussian functional form (chi-squared form) for the likelihood. This assumption, in detail, cannot be correct. Likelihood free inferences such as approximate Bayesian computation (ABC) relax these restrictions and make inference possible without making any assumptions on the likelihood. Instead ABC relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter haloes with galaxies. Using specific implementation of ABC supplemented with population Monte Carlo importance sampling, a generative forward model using HOD and a distance metric based on galaxy number density, two-point correlation function and galaxy group multiplicity function, we constrain the HOD parameters of mock observation generated from selected 'true' HOD parameters. The parameter constraints we obtain from ABC are consistent with the 'true' HOD parameters, demonstrating that ABC can be reliably used for parameter inference in LSS. Furthermore, we compare our ABC constraints to constraints we obtain using a pseudo-likelihood function of Gaussian form with MCMC and find consistent HOD parameter constraints. Ultimately, our results suggest that ABC can and should be applied in parameter inference for LSS analyses.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

An Overview and Empirical Comparison of Distance Metric Learning Methods.

PubMed

Moutafis, Panagiotis; Leng, Mengjun; Kakadiaris, Ioannis A

2016-02-16

In this paper, we first offer an overview of advances in the field of distance metric learning. Then, we empirically compare selected methods using a common experimental protocol. The number of distance metric learning algorithms proposed keeps growing due to their effectiveness and wide application. However, existing surveys are either outdated or they focus only on a few methods. As a result, there is an increasing need to summarize the obtained knowledge in a concise, yet informative manner. Moreover, existing surveys do not conduct comprehensive experimental comparisons. On the other hand, individual distance metric learning papers compare the performance of the proposed approach with only a few related methods and under different settings. This highlights the need for an experimental evaluation using a common and challenging protocol. To this end, we conduct face verification experiments, as this task poses significant challenges due to varying conditions during data acquisition. In addition, face verification is a natural application for distance metric learning because the encountered challenge is to define a distance function that: 1) accurately expresses the notion of similarity for verification; 2) is robust to noisy data; 3) generalizes well to unseen subjects; and 4) scales well with the dimensionality and number of training samples. In particular, we utilize well-tested features to assess the performance of selected methods following the experimental protocol of the state-of-the-art database labeled faces in the wild. A summary of the results is presented along with a discussion of the insights obtained and lessons learned by employing the corresponding algorithms.

The impact of recreational boat traffic on Marbled Murrelets (Brachyramphus marmoratus).

PubMed

Bellefleur, Danielle; Lee, Philip; Ronconi, Robert A

2009-01-01

This study evaluated the impact of small boat traffic on reaction distances of Marbled Murrelets (Brachyramphus marmoratus), in the marine waters of Pacific Rim National Park Reserve, British Columbia, Canada. Observers on moving boats recorded the minimum distance the boat came to murrelets on the water, and any disturbance reaction (fly, dive, no reaction). Out of the 7500 interactions 11.7% flew, 30.8% dove and 58.1% exhibited no flushing reaction. Using a product-limit analysis, we developed curves for the proportion of Marbled Murrelets flushing (dive or flight) as a function of reaction distance. Overall, the majority of Marbled Murrelets waited until boats were within 40 m before reacting, with 25% of the population reacting at 29.2m. A stepwise Cox regression indicated that age, boat speed, and boat density (loaded in that order), significantly affected flushing response. More juveniles flushed than adults (70.1 versus 51.7%), but at closer distances. Faster boats caused a greater proportion of birds to flush, and at further distances (25% of birds flushed at 40 m at speeds > 29 kph versus 28m at speeds <12kph). A stepwise logistic regression on diving and flight responses indicated that birds tended to fly completely out of feeding areas at the approach of boats travelling >28.8 kph and later in the season (July and August). Other secondary variables included; boat density and time of day. Discussion focused on possible management actions such as the application of speed limits, set back distances, and exclusion of boat traffic to protect Marbled Murrelets.

Tunable Excited-State Properties and Dynamics as a Function of Pt–Pt Distance in Pyrazolate-Bridged Pt(II) Dimers

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

Brown-Xu, Samantha E.; Kelley, Matthew S. J.; Fransted, Kelly A.

The influence of molecular structure on excited state properties and dynamics of a series of cyclometalated platinum dimers was investigated through a combined experimental and theoretical approach using femtosecond transient absorption (fs TA) spectroscopy and density functional theory (DFT) calculations. The molecules have the general formula [Pt(ppy)(µ-R2pz)]2 where ppy = 2-phenylpyridine, pz = pyrazolate and R = H, Me, Ph, or tBu, and are strongly photoluminescent at room temperature. The distance between the platinum centers in this A frame geometry can be varied depending on the steric bulk of the bridging pyrazolate ligands that exert structural constraints and compress themore » Pt-Pt distance. At large Pt-Pt distances there is little interaction between the subunits and the chromophore behaves similar to a monomer with excited states described as mixtures of ligand-centered and metal-to-ligand charge transfer (LC/MLCT) transitions. When the Pt(II) centers are brought closer together with bulky bridging ligands, they interact through their orbitals and the S1 and T1 states are best characterized as metal metal to ligand charge transfer (MMLCT) in character. The results of the fs TA experiments reveal that intersystem crossing (ISC) occurs on ultrafast timescales (τS1 < 200 fs) while there are two relaxation processes occurring within the triplet manifold, τ1 = 0.5 – 3.2 ps and τ2 = 20 – 70 ps; the longer time constants correspond to the presence of bulkier bridging ligands. DFT calculations illustrate that the Pt-Pt distances further contract in the T1 3MMLCT states, therefore slower relaxation may be related to a larger structural reorganization. Subsequent investigations using faster time resolution are planned to measure the ISC process as well as to identify any potential coherent interaction(s) between the platinum centers that may occur.« less

Atlas-based identification of targets for functional radiosurgery

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

Stancanello, Joseph; Romanelli, Pantaleo; Modugno, Nicola

2006-06-15

Functional disorders of the brain, such as Parkinson's disease, dystonia, epilepsy, and neuropathic pain, may exhibit poor response to medical therapy. In such cases, surgical intervention may become necessary. Modern surgical approaches to such disorders include radio-frequency lesioning and deep brain stimulation (DBS). The subthalamic nucleus (STN) is one of the most useful stereotactic targets available: STN DBS is known to induce substantial improvement in patients with end-stage Parkinson's disease. Other targets include the Globus Pallidus pars interna (GPi) for dystonia and Parkinson's disease, and the centromedian nucleus of the thalamus (CMN) for neuropathic pain. Radiosurgery is an attractive noninvasivemore » alternative to treat some functional brain disorders. The main technical limitation to radiosurgery is that the target can be selected only on the basis of magnetic resonance anatomy without electrophysiological confirmation. The aim of this work is to provide a method for the correct atlas-based identification of the target to be used in functional neurosurgery treatment planning. The coordinates of STN, CMN, and GPi were identified in the Talairach and Tournoux atlas and transformed to the corresponding regions of the Montreal Neurological Institute (MNI) electronic atlas. Binary masks describing the target nuclei were created. The MNI electronic atlas was deformed onto the patient magnetic resonance imaging-T1 scan by applying an affine transformation followed by a local nonrigid registration. The first transformation was based on normalized cross correlation and the second on optimization of a two-part objective function consisting of similarity criteria and weighted regularization. The obtained deformation field was then applied to the target masks. The minimum distance between the surface of an implanted electrode and the surface of the deformed mask was calculated. The validation of the method consisted of comparing the electrode-mask distance to the clinical outcome of the treatments in ten cases of bilateral DBS implants. Electrode placement may have an effect within a radius of stimulation equal to 2 mm, therefore the registration process is considered successful if error is less than 2 mm. The registrations of the MNI atlas onto the patient space succeeded in all cases. The comparison of the distance to the clinical outcome revealed good agreement: where the distance was high (at least in one implant), the clinical outcome was poor; where there was a close correlation between the structures, clinical outcome revealed an improvement of the pathological condition. In conclusion, the proposed method seems to provide a useful tool for the identification of the target nuclei for functional radiosurgery. Also, the method is applicable to other types of functional treatment.« less

Using Genealogical Mapping and Genetic Neighborhood Sizes to Quantify Dispersal Distances in the Neotropical Passerine, the Black-Capped Vireo

PubMed Central

Athrey, Giridhar; Lance, Richard F.; Leberg, Paul L.

2015-01-01

Dispersal is a key demographic process, ultimately responsible for genetic connectivity among populations. Despite its importance, quantifying dispersal within and between populations has proven difficult for many taxa. Even in passerines, which are among the most intensely studied, individual movement and its relation to gene flow remains poorly understood. In this study we used two parallel genetic approaches to quantify natal dispersal distances in a Neotropical migratory passerine, the black-capped vireo. First, we employed a strategy of sampling evenly across the landscape coupled with parentage assignment to map the genealogical relationships of individuals across the landscape, and estimate dispersal distances; next, we calculated Wright’s neighborhood size to estimate gene dispersal distances. We found that a high percentage of captured individuals were assigned at short distances within the natal population, and males were assigned to the natal population more often than females, confirming sex-biased dispersal. Parentage-based dispersal estimates averaged 2400m, whereas gene dispersal estimates indicated dispersal distances ranging from 1600–4200 m. Our study was successful in quantifying natal dispersal distances, linking individual movement to gene dispersal distances, while also providing a detailed look into the dispersal biology of Neotropical passerines. The high-resolution information was obtained with much reduced effort (sampling only 20% of breeding population) compared to mark-resight approaches, demonstrating the potential applicability of parentage-based approaches for quantifying dispersal in other vagile passerine species. PMID:26461257

Impact of geocoding methods on associations between long-term exposure to urban air pollution and lung function.

PubMed

Jacquemin, Bénédicte; Lepeule, Johanna; Boudier, Anne; Arnould, Caroline; Benmerad, Meriem; Chappaz, Claire; Ferran, Joane; Kauffmann, Francine; Morelli, Xavier; Pin, Isabelle; Pison, Christophe; Rios, Isabelle; Temam, Sofia; Künzli, Nino; Slama, Rémy; Siroux, Valérie

2013-09-01

Errors in address geocodes may affect estimates of the effects of air pollution on health. We investigated the impact of four geocoding techniques on the association between urban air pollution estimated with a fine-scale (10 m × 10 m) dispersion model and lung function in adults. We measured forced expiratory volume in 1 sec (FEV1) and forced vital capacity (FVC) in 354 adult residents of Grenoble, France, who were participants in two well-characterized studies, the Epidemiological Study on the Genetics and Environment on Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Home addresses were geocoded using individual building matching as the reference approach and three spatial interpolation approaches. We used a dispersion model to estimate mean PM10 and nitrogen dioxide concentrations at each participant's address during the 12 months preceding their lung function measurements. Associations between exposures and lung function parameters were adjusted for individual confounders and same-day exposure to air pollutants. The geocoding techniques were compared with regard to geographical distances between coordinates, exposure estimates, and associations between the estimated exposures and health effects. Median distances between coordinates estimated using the building matching and the three interpolation techniques were 26.4, 27.9, and 35.6 m. Compared with exposure estimates based on building matching, PM10 concentrations based on the three interpolation techniques tended to be overestimated. When building matching was used to estimate exposures, a one-interquartile range increase in PM10 (3.0 μg/m3) was associated with a 3.72-point decrease in FVC% predicted (95% CI: -0.56, -6.88) and a 3.86-point decrease in FEV1% predicted (95% CI: -0.14, -3.24). The magnitude of associations decreased when other geocoding approaches were used [e.g., for FVC% predicted -2.81 (95% CI: -0.26, -5.35) using NavTEQ, or 2.08 (95% CI -4.63, 0.47, p = 0.11) using Google Maps]. Our findings suggest that the choice of geocoding technique may influence estimated health effects when air pollution exposures are estimated using a fine-scale exposure model.

Surgical treatment of mandibular condyle fractures using the retromandibular anterior transparotid approach and a triangular-positioned double miniplate osteosynthesis technique: A clinical and radiological evaluation of 124 fractures.

PubMed

Dalla Torre, Daniel; Burtscher, Doris; Widmann, Gerlig; Pichler, Albina; Rasse, Michael; Puelacher, Wolfgang

2015-07-01

Different modalities have been described regarding the treatment of mandibular condyle fractures. The most advantageous and safest one is still a topic of discussion. The present analysis describes the combination of a retromandibular, transparotideal approach combined to a triangular-positioned double-miniplate osteosynthesis, with a special regard for the patients' long term outcomes. Clinical data of 102 patients with 124 condyle fractures treated with the mentioned surgical procedure were evaluated. Functional parameters such as the maximal interincisal distance, deviations/deflections, facial nerve function, occlusion as well as complications regarding the parotid gland, osteosynthesis, and esthetics were evaluated 1 week, 2 weeks, 3 months, and 6 months postoperatively. The mean maximal interincisal distance ranged from 38 mm after 1 week to 45 mm after 6 months. Deviations/deflections were seen in 22.5% of the cases 1 week postoperatively and decreased to 2% at 6 months postoperatively. A temporary facial palsy was diagnosed in 3.9% during the first follow-up, whereas no impairment was recorded after 3 or 6 months. At the same time, no patient had occlusional disturbances or complications regarding the parotid gland or the osteosynthesis 6 months postoperatively. Direct fracture visualization and a stable three-dimensional fracture stabilization are the main advantages of the presented combination of a surgical approach and osteosynthesis technique. Additionally, the absence of long-term complications confirms the safety of the procedure. Therefore, it may be considered as a successful treatment option for mandibular condyle fractures. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Receiver Functions From Regional and Near-Teleseismic P Waves

NASA Astrophysics Data System (ADS)

Park, J.; Levin, V.

2001-05-01

P waves from regional-distance earthquakes are complex and reverberatory, as would be expected from a combination of head waves, post-critical crustal reflections and shallow-incident P from the upper mantle. Although developed to analyze steeply-incident teleseismic P waves, receiver function analysis can also retrieve information about crustal structure from regional and near-teleseismic P. Using a new method to estimate receiver functions, based on multiple-taper spectral analysis, regional-distance RFs for GSN stations RAYN and ANTO show broad agreement with teleseismic RFs. At RAYN the moveout of the Moho-converted Ps phase, relative to direct P, follows well the predictions of the IASP91 earth model. The Moho-converted Ps phase shows complexity associated with the transition-zone triplication near Δ =20o and constant delay (zero moveout) as Δ -> 0, consistent with conversion from Pn. Similar behavior is seen for ANTO for events that arrive from the west. For eastern backazimuths the ANTO RFs show features whose moveout is negative as Δ -> 0. This moveout is poorly fit by reverberations in flat layers or by direct scattering from a dipping interface, but is consistent with a topographic scatterer 20--30 km eastward of the ANTO site. Regional receiver functions may therefore be useful in judging whether teleseismic RFs at a particular station are suitable candidates for a 1-D velocity structure inversion. Synthetic seismograms of regional P phases, computed with a locked-mode reflectivity approach, confirm broad features of the RAYN and ANTO regional receiver functions.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

SU-E-T-97: Dependence Of Optically Stimulated Luminescent Dosimeter (OSLD) Out Of Field Response On Volumetric Modulated Arc Therapy (VMAT) Field Modulation

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

Ware, S; Clouser, E

2014-06-01

Purpose: To determine the out of field response of Microstar ii OSLDs as a function of field modulation and distance in VMAT plan delivery. This work has potential application in fetal dose monitoring or measurements on cardiac pacemakers Methods: VMAT plans were created in Eclipse and optimized to varying degrees of modulation. Three plans were chosen to represent low, medium and high degrees of modulation (modulation factors as defined by MU/cGy). Plans were delivered to slabs of solid water with dimensions 60cm length, 30cm width, and 10cm height. For each modulation factor, 2 OSLDs were placed at 1cm depth withmore » out of field distances of 1, 2, 3, 5, 8 and 10cm and the plan delivered isocentrically to a depth of 5cm. This technique was repeated for a Farmer Chamber by incrementing the table by the appropriate distance. The charge readings for the Farmer Chamber were converted to dose and the ratios taken as functions of modulation factors and distances out of field Results: Examination of the results as a function of out of field distance shows a trend of increasing OSLD/Farmer Chamber ratios for all modulation factors. The slopes appear to be roughly equivalent for all modulation factors investigated. Results as a function of modulation showed a downward trend for all out of field distances, with the greatest differences seen at 5cm and 8cm Conclusion: This study demonstrates that the response of OSLD dosimeters change as a function of out of field distance and modulation. The differences seen are within the stated accuracy of the system for the out of field distances and modulations investigated. Additional investigation is warranted to see if the OSLD response changes appreciably with longer out of field distances or wider ranges of modulation.« less

Variations in plasma wave intensity with distance along the electron foreshock boundary at Venus

NASA Technical Reports Server (NTRS)

Crawford, G. K.; Strangeway, R. J.; Russell, C. T.

1991-01-01

Plasma waves are observed in the solar wind upstream of the Venus bow shock by the Pioneer Venus Orbiter. These wave signatures occur during periods when the interplanetary magnetic field through the spacecraft position intersects the bow shock, thereby placing the spacecraft in the foreshock region. Wave intensity is analyzed as a function of distance along the electron foreshock boundary. It is found that the peak wave intensity may increase along the foreshock boundary from the tangent point to a maximum value at several Venus radii, then decrease in intensity with subsequent increase in distance. These observations could be associated with the instability process: the instability of the distribution function increasing with distance from the tangent point to saturation at the peak. Thermalization of the beam for distances beyond this point could reduce the distribution function instability resulting in weaker wave signatures.

[Identification of ecological corridors and its importance by integrating circuit theory].

PubMed

Song, Li Li; Qin, Ming Zhou

2016-10-01

Landscape connectivity is considered as an extraordinarily important factor affecting various ecological processes. The least cost path (LCP) on the basis of minimum cumulative resis-tance model (MCRM) may provide a more efficient approach to identify functional connectivity in heterogeneous landscapes, and is already adopted by the research of landscape functional connecti-vity assessment and ecological corridor simulation. Connectivity model on circuit theory (CMCT) replaced the edges in the graph theory with resistors, cost distance with resistance distance to measure the functional connectivity in heterogeneous landscapes. By means of Linkage Mapper tool and Circuitscape software, the simulated landscape generated from SIMMAP 2.0 software was viewed as the study object in this article, aimed at exploring how to integrate MCRM with CMCT to identify ecological corridors and relative importance of landscape factors. The results showed that two models had their individual advantages and mutual complement. MCRM could effectively identify least cost corridors among habitats. CMCT could effectively identify important landscape factor and pinch point, which had important influence on landscape connectivity. We also found that the position of pinch point was not affected by corridor width, which had obvious advantage in the research of identifying the importance of corridors. The integrated method could provide certain scientific basis for regional ecological protection planning and ecological corridor design.

The Impact of Distance Education on Higher Education: A Case Study of the United States

ERIC Educational Resources Information Center

Caruth, Gail D.; Caruth, Donald L.

2013-01-01

Distance education has been credited for bringing education to students who would not otherwise have educational opportunities. This study used a qualitative case study approach to examine the research to determine the impact of distance education on higher education in the United States. This look into the impact of distance education is…

A Unimodal Model for Double Observer Distance Sampling Surveys.

PubMed

Becker, Earl F; Christ, Aaron M

2015-01-01

Distance sampling is a widely used method to estimate animal population size. Most distance sampling models utilize a monotonically decreasing detection function such as a half-normal. Recent advances in distance sampling modeling allow for the incorporation of covariates into the distance model, and the elimination of the assumption of perfect detection at some fixed distance (usually the transect line) with the use of double-observer models. The assumption of full observer independence in the double-observer model is problematic, but can be addressed by using the point independence assumption which assumes there is one distance, the apex of the detection function, where the 2 observers are assumed independent. Aerially collected distance sampling data can have a unimodal shape and have been successfully modeled with a gamma detection function. Covariates in gamma detection models cause the apex of detection to shift depending upon covariate levels, making this model incompatible with the point independence assumption when using double-observer data. This paper reports a unimodal detection model based on a two-piece normal distribution that allows covariates, has only one apex, and is consistent with the point independence assumption when double-observer data are utilized. An aerial line-transect survey of black bears in Alaska illustrate how this method can be applied.

A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

2011-08-01

This paper proposes a novel optimization approach for the least cost design of looped water distribution systems (WDSs). Three distinct steps are involved in the proposed optimization approach. In the first step, the shortest-distance tree within the looped network is identified using the Dijkstra graph theory algorithm, for which an extension is proposed to find the shortest-distance tree for multisource WDSs. In the second step, a nonlinear programming (NLP) solver is employed to optimize the pipe diameters for the shortest-distance tree (chords of the shortest-distance tree are allocated the minimum allowable pipe sizes). Finally, in the third step, the original looped water network is optimized using a differential evolution (DE) algorithm seeded with diameters in the proximity of the continuous pipe sizes obtained in step two. As such, the proposed optimization approach combines the traditional deterministic optimization technique of NLP with the emerging evolutionary algorithm DE via the proposed network decomposition. The proposed methodology has been tested on four looped WDSs with the number of decision variables ranging from 21 to 454. Results obtained show the proposed approach is able to find optimal solutions with significantly less computational effort than other optimization techniques.

Covering Numbers for Semicontinuous Functions

DTIC Science & Technology

2016-04-29

functions, epi-distance, Attouch-Wets topology, epi-convergence, epi-spline, approximation theory . Date: April 29, 2016 1 Introduction Covering numbers of...classes of functions play central roles in parts of information theory , statistics, and applications such as machine learning; see for example [26...probability theory because there the hypo-distance metrizes weak convergence of distribution functions on IRd, which obviously are usc [22]. Thus, as an

Functionalization of quantum rods with oligonucleotides for programmable assembly with DNA origami

NASA Astrophysics Data System (ADS)

Doane, Tennyson L.; Alam, Rabeka; Maye, Mathew M.

2015-02-01

The DNA-mediated self-assembly of CdSe/CdS quantum rods (QRs) onto DNA origami is described. Two QR types with unique optical emission and high polarization were synthesized, and then functionalized with oligonucleotides (ssDNA) using a novel protection-deprotection approach, which harnessed ssDNA's tailorable rigidity and denaturation temperature to increase DNA coverage by reducing non-specific coordination and wrapping. The QR assembly was programmable, and occurred at two different assembly zones that had capture strands in parallel alignment. QRs with different optical properties were assembled, opening up future studies on orientation dependent QR FRET. The QR-origami conjugates could be purified via gel electrophoresis and sucrose gradient ultracentrifugation. Assembly yields, QR stoichiometry and orientation, as well as energy transfer implications were studied in light of QR distances, origami flexibility, and conditions.The DNA-mediated self-assembly of CdSe/CdS quantum rods (QRs) onto DNA origami is described. Two QR types with unique optical emission and high polarization were synthesized, and then functionalized with oligonucleotides (ssDNA) using a novel protection-deprotection approach, which harnessed ssDNA's tailorable rigidity and denaturation temperature to increase DNA coverage by reducing non-specific coordination and wrapping. The QR assembly was programmable, and occurred at two different assembly zones that had capture strands in parallel alignment. QRs with different optical properties were assembled, opening up future studies on orientation dependent QR FRET. The QR-origami conjugates could be purified via gel electrophoresis and sucrose gradient ultracentrifugation. Assembly yields, QR stoichiometry and orientation, as well as energy transfer implications were studied in light of QR distances, origami flexibility, and conditions. Electronic supplementary information (ESI) available: Experimental conditions, DNA origami blueprint and sequences, FRET calculations. Additional Fig. S1-S13. See DOI: 10.1039/c4nr07662a

Auditory spatial representations of the world are compressed in blind humans.

PubMed

Kolarik, Andrew J; Pardhan, Shahina; Cirstea, Silvia; Moore, Brian C J

2017-02-01

Compared to sighted listeners, blind listeners often display enhanced auditory spatial abilities such as localization in azimuth. However, less is known about whether blind humans can accurately judge distance in extrapersonal space using auditory cues alone. Using virtualization techniques, we show that auditory spatial representations of the world beyond the peripersonal space of blind listeners are compressed compared to those for normally sighted controls. Blind participants overestimated the distance to nearby sources and underestimated the distance to remote sound sources, in both reverberant and anechoic environments, and for speech, music, and noise signals. Functions relating judged and actual virtual distance were well fitted by compressive power functions, indicating that the absence of visual information regarding the distance of sound sources may prevent accurate calibration of the distance information provided by auditory signals.

An extended car-following model considering random safety distance with different probabilities

NASA Astrophysics Data System (ADS)

Wang, Jufeng; Sun, Fengxin; Cheng, Rongjun; Ge, Hongxia; Wei, Qi

2018-02-01

Because of the difference in vehicle type or driving skill, the driving strategy is not exactly the same. The driving speeds of the different vehicles may be different for the same headway. Since the optimal velocity function is just determined by the safety distance besides the maximum velocity and headway, an extended car-following model accounting for random safety distance with different probabilities is proposed in this paper. The linear stable condition for this extended traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulting from multiple safety distance in the optimal velocity function. The cases of multiple types of safety distances selected with different probabilities are presented. Numerical results show that the traffic flow with multiple safety distances with different probabilities will be more unstable than that with single type of safety distance, and will result in more stop-and-go phenomena.

Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations

PubMed Central

Brodie, Nicholas I.; Popov, Konstantin I.; Petrotchenko, Evgeniy V.; Dokholyan, Nikolay V.; Borchers, Christoph H.

2017-01-01

We present an integrated experimental and computational approach for de novo protein structure determination in which short-distance cross-linking data are incorporated into rapid discrete molecular dynamics (DMD) simulations as constraints, reducing the conformational space and achieving the correct protein folding on practical time scales. We tested our approach on myoglobin and FK506 binding protein—models for α helix–rich and β sheet–rich proteins, respectively—and found that the lowest-energy structures obtained were in agreement with the crystal structure, hydrogen-deuterium exchange, surface modification, and long-distance cross-linking validation data. Our approach is readily applicable to other proteins with unknown structures. PMID:28695211

Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations.

PubMed

Brodie, Nicholas I; Popov, Konstantin I; Petrotchenko, Evgeniy V; Dokholyan, Nikolay V; Borchers, Christoph H

2017-07-01

We present an integrated experimental and computational approach for de novo protein structure determination in which short-distance cross-linking data are incorporated into rapid discrete molecular dynamics (DMD) simulations as constraints, reducing the conformational space and achieving the correct protein folding on practical time scales. We tested our approach on myoglobin and FK506 binding protein-models for α helix-rich and β sheet-rich proteins, respectively-and found that the lowest-energy structures obtained were in agreement with the crystal structure, hydrogen-deuterium exchange, surface modification, and long-distance cross-linking validation data. Our approach is readily applicable to other proteins with unknown structures.

Gd(III)-Gd(III) EPR distance measurements--the range of accessible distances and the impact of zero field splitting.

PubMed

Dalaloyan, Arina; Qi, Mian; Ruthstein, Sharon; Vega, Shimon; Godt, Adelheid; Feintuch, Akiva; Goldfarb, Daniella

2015-07-28

Gd(III) complexes have emerged as spin labels for distance determination in biomolecules through double-electron-electron resonance (DEER) measurements at high fields. For data analysis, the standard approach developed for a pair of weakly coupled spins with S = 1/2 was applied, ignoring the actual properties of Gd(III) ions, i.e. S = 7/2 and ZFS (zero field splitting) ≠ 0. The present study reports on a careful investigation on the consequences of this approach, together with the range of distances accessible by DEER with Gd(III) complexes as spin labels. The experiments were performed on a series of specifically designed and synthesized Gd-rulers (Gd-PyMTA-spacer-Gd-PyMTA) covering Gd-Gd distances of 2-8 nm. These were dissolved in D2O-glycerol-d8 (0.03-0.10 mM solutions) which is the solvent used for the corresponding experiments on biomolecules. Q- and W-band DEER measurements, followed by data analysis using the standard data analysis approach, used for S = 1/2 pairs gave the distance-distribution curves, of which the absolute maxima agreed very well with the expected distances. However, in the case of the short distances of 2.1 and 2.9 nm, the distance distributions revealed additional peaks. These are a consequence of neglecting the pseudo-secular term in the dipolar Hamiltonian during the data analysis, as is outlined in a theoretical treatment. At distances of 3.4 nm and above, disregarding the pseudo-secular term leads to a broadening of a maximum of 0.4 nm of the distance-distribution curves at half height. Overall, the distances of up to 8.3 nm were determined, and the long evolution time of 16 μs at 10 K indicates that a distance of up to 9.4 nm can be accessed. A large distribution of the ZFS parameter, D, as is found for most Gd(III) complexes in a frozen solution, is crucial for the application of Gd(III) complexes as spin labels for distance determination via Gd(III)-Gd(III) DEER, especially for short distances. The larger ZFS of Gd-PyMTA, in comparison to that of Gd-DOTA, makes Gd-PyMTA a better label for short distances.

Control of the positional relationship between a sample collection instrument and a surface to be analyzed during a sampling procedure with image analysis

DOEpatents

Van Berkel, Gary J.; Kertesz, Vilmos

2011-08-09

A system and method utilizes an image analysis approach for controlling the collection instrument-to-surface distance in a sampling system for use, for example, with mass spectrometric detection. Such an approach involves the capturing of an image of the collection instrument or the shadow thereof cast across the surface and the utilization of line average brightness (LAB) techniques to determine the actual distance between the collection instrument and the surface. The actual distance is subsequently compared to a target distance for re-optimization, as necessary, of the collection instrument-to-surface during an automated surface sampling operation.

Coupling density functional theory to polarizable force fields for efficient and accurate Hamiltonian molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Schwörer, Magnus; Breitenfeld, Benedikt; Tröster, Philipp; Bauer, Sebastian; Lorenzen, Konstantin; Tavan, Paul; Mathias, Gerald

2013-06-01

Hybrid molecular dynamics (MD) simulations, in which the forces acting on the atoms are calculated by grid-based density functional theory (DFT) for a solute molecule and by a polarizable molecular mechanics (PMM) force field for a large solvent environment composed of several 103-105 molecules, pose a challenge. A corresponding computational approach should guarantee energy conservation, exclude artificial distortions of the electron density at the interface between the DFT and PMM fragments, and should treat the long-range electrostatic interactions within the hybrid simulation system in a linearly scaling fashion. Here we describe a corresponding Hamiltonian DFT/(P)MM implementation, which accounts for inducible atomic dipoles of a PMM environment in a joint DFT/PMM self-consistency iteration. The long-range parts of the electrostatics are treated by hierarchically nested fast multipole expansions up to a maximum distance dictated by the minimum image convention of toroidal boundary conditions and, beyond that distance, by a reaction field approach such that the computation scales linearly with the number of PMM atoms. Short-range over-polarization artifacts are excluded by using Gaussian inducible dipoles throughout the system and Gaussian partial charges in the PMM region close to the DFT fragment. The Hamiltonian character, the stability, and efficiency of the implementation are investigated by hybrid DFT/PMM-MD simulations treating one molecule of the water dimer and of bulk water by DFT and the respective remainder by PMM.

Roughness as classicality indicator of a quantum state

NASA Astrophysics Data System (ADS)

Lemos, Humberto C. F.; Almeida, Alexandre C. L.; Amaral, Barbara; Oliveira, Adélcio C.

2018-03-01

We define a new quantifier of classicality for a quantum state, the Roughness, which is given by the L2 (R2) distance between Wigner and Husimi functions. We show that the Roughness is bounded and therefore it is a useful tool for comparison between different quantum states for single bosonic systems. The state classification via the Roughness is not binary, but rather it is continuous in the interval [ 0 , 1 ], being the state more classic as the Roughness approaches to zero, and more quantum when it is closer to the unity. The Roughness is maximum for Fock states when its number of photons is arbitrarily large, and also for squeezed states at the maximum compression limit. On the other hand, the Roughness approaches its minimum value for thermal states at infinite temperature and, more generally, for infinite entropy states. The Roughness of a coherent state is slightly below one half, so we may say that it is more a classical state than a quantum one. Another important result is that the Roughness performs well for discriminating both pure and mixed states. Since the Roughness measures the inherent quantumness of a state, we propose another function, the Dynamic Distance Measure (DDM), which is suitable for measure how much quantum is a dynamics. Using DDM, we studied the quartic oscillator, and we observed that there is a certain complementarity between dynamics and state, i.e. when dynamics becomes more quantum, the Roughness of the state decreases, while the Roughness grows as the dynamics becomes less quantum.

Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators

USGS Publications Warehouse

Parmenter, R.R.; Yates, Terry L.; Anderson, D.R.; Burnham, K.P.; Dunnum, J.L.; Franklin, A.B.; Friggens, M.T.; Lubow, B.C.; Miller, M.; Olson, G.S.; Parmenter, Cheryl A.; Pollard, J.; Rexstad, E.; Shenk, T.M.; Stanley, T.R.; White, Gary C.

2003-01-01

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size (NÌ‚) and effective sampling area (AÌ‚) are used to calculate density (DÌ‚ = NÌ‚/AÌ‚); and models applicable to sampling regimes using distance-sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets (n = 11) were developed using nine rodent species from capture–recapture live-trapping on both trapping grids and trapping webs in four replicate 4.2-ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates (DÌ‚) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities (D) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web-based uniform and half-normal models in program DISTANCE, and the grid-based models Mb and Mbh in program CAPTURE (with AÌ‚ adjusted by species-specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web-based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid-based DÌ‚ analyses using full MMDM values for WÌ‚ area adjustments required a number of theoretical assumptions of uncertain validity, and we therefore viewed their empirical successes with caution. Finally, density estimates from the independent analysts were highly variable, but estimates from web-based approaches had smaller mean square errors and better achieved confidence-interval coverage of D than did grid-based approaches. Our results support the contention that web-based approaches for density estimation of small-mammal populations are both theoretically and empirically superior to grid-based approaches, even when sample size is far less than often recommended. In view of the increasing need for standardized environmental measures for comparisons among ecosystems and through time, analytical models based on distance sampling appear to offer accurate density estimation approaches for research studies involving small-mammal abundances.

Squared Euclidean distance: a statistical test to evaluate plant community change

Treesearch

Raymond D. Ratliff; Sylvia R. Mori

1993-01-01

The concepts and a procedure for evaluating plant community change using the squared Euclidean distance (SED) resemblance function are described. Analyses are based on the concept that Euclidean distances constitute a sample from a population of distances between sampling units (SUs) for a specific number of times and SUs. With different times, the distances will be...

Do Pre-school Distance Educators Require Specialist Training?

ERIC Educational Resources Information Center

Kirk, David

1994-01-01

Recommends implementing specialized preparation for rural preschool teachers to function effectively as distance educators. Addresses differences between urban and rural environments affecting education; the important role of parents as educators in distance education; and the need for distance education preschool teachers to reconceptualize their…

End-to-end distance and contour length distribution functions of DNA helices

NASA Astrophysics Data System (ADS)

Zoli, Marco

2018-06-01

I present a computational method to evaluate the end-to-end and the contour length distribution functions of short DNA molecules described by a mesoscopic Hamiltonian. The method generates a large statistical ensemble of possible configurations for each dimer in the sequence, selects the global equilibrium twist conformation for the molecule, and determines the average base pair distances along the molecule backbone. Integrating over the base pair radial and angular fluctuations, I derive the room temperature distribution functions as a function of the sequence length. The obtained values for the most probable end-to-end distance and contour length distance, providing a measure of the global molecule size, are used to examine the DNA flexibility at short length scales. It is found that, also in molecules with less than ˜60 base pairs, coiled configurations maintain a large statistical weight and, consistently, the persistence lengths may be much smaller than in kilo-base DNA.

KECSA-Movable Type Implicit Solvation Model (KMTISM)

PubMed Central

2015-01-01

Computation of the solvation free energy for chemical and biological processes has long been of significant interest. The key challenges to effective solvation modeling center on the choice of potential function and configurational sampling. Herein, an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA) are developed and utilized to create an implicit solvation model: KECSA-Movable Type Implicit Solvation Model (KMTISM) suitable for the study of chemical and biological systems. KMTISM is an implicit solvation model, but the MT method performs energy sampling at the atom pairwise level. For a specific molecular system, the MT method collects energies from prebuilt databases for the requisite atom pairs at all relevant distance ranges, which by its very construction encodes all possible molecular configurations simultaneously. Unlike traditional statistical energy functions, KECSA converts structural statistical information into categorized atom pairwise interaction energies as a function of the radial distance instead of a mean force energy function. Within the implicit solvent model approximation, aqueous solvation free energies are then obtained from the NVT ensemble partition function generated by the MT method. Validation is performed against several subsets selected from the Minnesota Solvation Database v2012. Results are compared with several solvation free energy calculation methods, including a one-to-one comparison against two commonly used classical implicit solvation models: MM-GBSA and MM-PBSA. Comparison against a quantum mechanics based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12). PMID:25691832

Editing Distance Education Materials. Knowledge Series.

ERIC Educational Resources Information Center

Swales, Christine

Distance education (DE) materials take a learner-centered approach rather than the traditionally content-centered approach of textbooks. This fact has several implications for the editing of DE materials. The role of the editor within the DE organization will depend on the organization's size and structure. The basic features of the DE program or…

An Axiom System for High School Geometry Based on Isometrics.

ERIC Educational Resources Information Center

Beard, Earl M. L.

Presented in this report is an approach to Euclidean geometry that makes use of distance preserving transformations as the primary approach in the development of the proposed course. The foundation of the course consists of an axiom set that is a combination of Binkhoff's, Hilbert's, and Klein's. Transformations and distance preserving…

Reducing The Cost of Transport and Increasing Walking Distance After Stroke: A Randomized Controlled Trial on Fast Locomotor Training Combined With Functional Electrical Stimulation

PubMed Central

Awad, Louis N.; Reisman, Darcy S.; Pohlig, Ryan T.; Binder-Macleod, Stuart A.

2015-01-01

Background Neurorehabilitation efforts have been limited in their ability to restore walking function after stroke. Recent work has demonstrated proof-of-concept for a Functional Electrical Stimulation (FES)-based combination therapy designed to improve poststroke walking by targeting deficits in paretic propulsion. Objectives To determine the effects on the energy cost of walking (EC) and long-distance walking ability of locomotor training that combines fast walking with FES to the paretic ankle musculature (FastFES). Methods Fifty participants >6 months poststroke were randomized to 12 weeks of gait training at self-selected speeds (SS), fast speeds (Fast), or FastFES. Participants’ 6-Minute Walk Test (6MWT) distance and EC at comfortable (EC-CWS) and fast (EC-Fast) walking speeds were measured pretraining, posttraining, and at a 3-month follow-up. A reduction in EC-CWS, independent of changes in speed, was the primary outcome. Also evaluated were group differences in the number of 6MWT responders and moderation by baseline speed. Results When compared with SS and Fast, FastFES produced larger reductions in EC (p’s ≤0.03). FastFES produced reductions of 24% and 19% in EC-CWS and EC-Fast (p’s <0.001), whereas neither Fast nor SS influenced EC. Between-group 6MWT differences were not observed; however, 73% of FastFES and 68% of Fast participants were responders, in contrast to 35% of SS participants. Conclusions Combining fast locomotor training with FES is an effective approach to reducing the high EC of persons poststroke. Surprisingly, differences in 6MWT gains were not observed between groups. Closer inspection of the 6MWT and EC relationship and elucidation of how reduced EC may influence walking-related disability is warranted. PMID:26621366

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

Oh, Minji; Song, Yong-Seon, E-mail: minjioh@kasi.re.kr, E-mail: ysong@kasi.re.kr

The anisotropic galaxy clustering of large scale structure observed by the Baryon Oscillation Spectroscopic Survey Data Release 11 is analyzed to probe the sum of neutrino masses in the small m {sub ν} ∼< 1 eV limit in which the early broadband shape determined before the last scattering surface is immune from the variation of m {sub ν}. The signature of m {sub ν} is imprinted on the altered shape of the power spectrum at later epoch, which provides an opportunity to access the non-trivial m {sub ν} through the measured anisotropic correlation function in redshift space (hereafter RSD insteadmore » of Redshift Space Distortion). The non-linear RSD corrections with massive neutrinos in the quasi linear regime are approximately estimated using one-loop order terms. We suggest an approach to probe m {sub ν} simultaneously with all other distance measures and coherent growth functions, exploiting this deformation of the early broadband shape of the spectrum at later epoch. If the origin of cosmic acceleration is unknown, m {sub ν} is poorly determined after marginalizing over all other observables. However, we find that the measured distances and coherent growth functions are minimally affected by the presence of mild neutrino mass. Although the standard model of cosmic acceleration is assumed to be the cosmological constant, the constraint on m {sub ν} is little improved. Interestingly, the measured Cosmic Microwave Background (hereafter CMB) distance to the last scattering surface sharply slices the degeneracy between the matter content and m {sub ν}, and the m {sub ν} is observed to be m {sub ν} = 0.19{sup +0.28}{sub −0.17} eV which is different from massless neutrino at 68% confidence.« less

Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach

PubMed Central

Appia, Vikram; Ganapathy, Balaji; Yezzi, Anthony; Faber, Tracy

2014-01-01

We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divisions) in an image and then combines these locally accurate segmentation curves to obtain a global segmentation. The training data for our approach consists of training shapes and associated auxiliary (target) masks. The masks indicate the various regions of the shape exhibiting highly correlated variations locally which may be rather independent of the variations in the distant parts of the global shape. Thus, in a sense, we are clustering the variations exhibited in the training data set. We then use a parametric model to implicitly represent each localized segmentation curve as a combination of the local shape priors obtained by representing the training shapes and the masks as a collection of signed distance functions. We also propose a parametric model to combine the locally evolved segmentation curves into a single hybrid (global) segmentation. Finally, we combine the evolution of these semilocal and global parameters to minimize an objective energy function. The resulting algorithm thus provides a globally accurate solution, which retains the local variations in shape. We present some results to illustrate how our approach performs better than the traditional approach with fully global PCA. PMID:25520901

Near or far? It depends on my impression: moral information and spatial behavior in virtual interactions.

PubMed

Iachini, Tina; Pagliaro, Stefano; Ruggiero, Gennaro

2015-10-01

Near body distance is a key component of action and social interaction. Recent research has shown that peripersonal space (reachability-distance for acting with objects) and interpersonal space (comfort-distance for interacting with people) share common mechanisms and reflect the social valence of stimuli. The social psychological literature has demonstrated that information about morality is crucial because it affects impression formation and the intention to approach-avoid others. Here we explore whether peripersonal/interpersonal spaces are modulated by moral information. Thirty-six participants interacted with male/female virtual confederates described by moral/immoral/neutral sentences. The modulation of body space was measured by reachability-distance and comfort-distance while participants stood still or walked toward virtual confederates. Results showed that distance expanded with immorally described confederates and contracted with morally described confederates. This pattern was present in both spaces, although it was stronger in comfort-distance. Consistent with an embodied cognition approach, the findings suggest that high-level socio-cognitive processes are linked to sensorimotor-spatial processes. Copyright © 2015. Published by Elsevier B.V.

A cost-function approach to rival penalized competitive learning (RPCL).

PubMed

Ma, Jinwen; Wang, Taijun

2006-08-01

Rival penalized competitive learning (RPCL) has been shown to be a useful tool for clustering on a set of sample data in which the number of clusters is unknown. However, the RPCL algorithm was proposed heuristically and is still in lack of a mathematical theory to describe its convergence behavior. In order to solve the convergence problem, we investigate it via a cost-function approach. By theoretical analysis, we prove that a general form of RPCL, called distance-sensitive RPCL (DSRPCL), is associated with the minimization of a cost function on the weight vectors of a competitive learning network. As a DSRPCL process decreases the cost to a local minimum, a number of weight vectors eventually fall into a hypersphere surrounding the sample data, while the other weight vectors diverge to infinity. Moreover, it is shown by the theoretical analysis and simulation experiments that if the cost reduces into the global minimum, a correct number of weight vectors is automatically selected and located around the centers of the actual clusters, respectively. Finally, we apply the DSRPCL algorithms to unsupervised color image segmentation and classification of the wine data.

Force Field Accelerated Density Functional Theory Molecular Dynamics for Simulation of Reactive Systems at Extreme Conditions

NASA Astrophysics Data System (ADS)

Lindsey, Rebecca; Goldman, Nir; Fried, Laurence

2017-06-01

Atomistic modeling of chemistry at extreme conditions remains a challenge, despite continuing advances in computing resources and simulation tools. While first principles methods provide a powerful predictive tool, the time and length scales associated with chemistry at extreme conditions (ns and μm, respectively) largely preclude extension of such models to molecular dynamics. In this work, we develop a simulation approach that retains the accuracy of density functional theory (DFT) while decreasing computational effort by several orders of magnitude. We generate n-body descriptions for atomic interactions by mapping forces arising from short density functional theory (DFT) trajectories on to simple Chebyshev polynomial series. We examine the importance of including greater than 2-body interactions, model transferability to different state points, and discuss approaches to ensure smooth and reasonable model shape outside of the distance domain sampled by the DFT training set. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Force Field Accelerated Density Functional Theory Molecular Dynamics for Simulation of Reactive Systems at Extreme Conditions

NASA Astrophysics Data System (ADS)

Lindsey, Rebecca; Goldman, Nir; Fried, Laurence

Understanding chemistry at extreme conditions is crucial in fields including geochemistry, astrobiology, and alternative energy. First principles methods can provide valuable microscopic insights into such systems while circumventing the risks of physical experiments, however the time and length scales associated with chemistry at extreme conditions (ns and μm, respectively) largely preclude extension of such models to molecular dynamics. In this work, we develop a simulation approach that retains the accuracy of density functional theory (DFT) while decreasing computational effort by several orders of magnitude. We generate n-body descriptions for atomic interactions by mapping forces arising from short density functional theory (DFT) trajectories on to simple Chebyshev polynomial series. We examine the importance of including greater than 2-body interactions, model transferability to different state points, and discuss approaches to ensure smooth and reasonable model shape outside of the distance domain sampled by the DFT training set. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Radio Ranging System for Guidance of Approaching Spacecraft

NASA Technical Reports Server (NTRS)

Manikonda, Vikram; vanDoom, Eric

2008-01-01

A radio communication and ranging system has been proposed for determining the relative position and orientations of two approaching spacecraft to provide guidance for docking maneuvers. On Earth, the system could be used similarly for guiding approaching aircraft and for automated positioning of large, heavy objects. In principle, the basic idea is to (1) measure distances between radio transceivers on the two spacecraft and (2) compute the relative position and orientations from the measured distances.

Intrinsic random functions for mitigation of atmospheric effects in terrestrial radar interferometry

NASA Astrophysics Data System (ADS)

Butt, Jemil; Wieser, Andreas; Conzett, Stefan

2017-06-01

The benefits of terrestrial radar interferometry (TRI) for deformation monitoring are restricted by the influence of changing meteorological conditions contaminating the potentially highly precise measurements with spurious deformations. This is especially the case when the measurement setup includes long distances between instrument and objects of interest and the topography affecting atmospheric refraction is complex. These situations are typically encountered with geo-monitoring in mountainous regions, e.g. with glaciers, landslides or volcanoes. We propose and explain an approach for the mitigation of atmospheric influences based on the theory of intrinsic random functions of order k (IRF-k) generalizing existing approaches based on ordinary least squares estimation of trend functions. This class of random functions retains convenient computational properties allowing for rigorous statistical inference while still permitting to model stochastic spatial phenomena which are non-stationary in mean and variance. We explore the correspondence between the properties of the IRF-k and the properties of the measurement process. In an exemplary case study, we find that our method reduces the time needed to obtain reliable estimates of glacial movements from 12 h down to 0.5 h compared to simple temporal averaging procedures.

Calibrating Reach Distance to Visual Targets

ERIC Educational Resources Information Center

Mon-Williams, Mark; Bingham, Geoffrey P.

2007-01-01

The authors investigated the calibration of reach distance by gradually distorting the haptic feedback obtained when participants grasped visible target objects. The authors found that the modified relationship between visually specified distance and reach distance could be captured by a straight-line mapping function. Thus, the relation could be…

Degree of coherence for vectorial electromagnetic fields as the distance between correlation matrices.

PubMed

Luis, Alfredo

2007-04-01

We assess the degree of coherence of vectorial electromagnetic fields in the space-frequency domain as the distance between the cross-spectral density matrix and the identity matrix representing completely incoherent light. This definition is compared with previous approaches. It is shown that this distance provides an upper bound for the degree of coherence and visibility for any pair of scalar waves obtained by linear combinations of the original fields. This same approach emerges when applying a previous definition of global coherence to a Young interferometer.

Spatial transport of electron quantum states with strong attosecond pulses

NASA Astrophysics Data System (ADS)

Chovancova, M.; Agueny, H.; Førre, M.; Kocbach, L.; Hansen, J. P.

2017-11-01

This work follows up the work of Dimitrovsky, Briggs and co-workers on translated electron atomic states by a strong field of an atto-second laser pulse, also described as creation of atoms without a nucleus. Here, we propose a new approach by analyzing the electron states in the Kramers-Henneberger moving frame in the dipole approximation. The wave function follows the displacement vector α (t). This allows arbitrarily shaped pulses, including the model delta-function potentials in the Dimitrovsky and Briggs approach. In the case of final-length single-cycle pulses, we apply both the Kramers-Henneberger moving frame analysis and a full numerical treatment of our 1D model. When the laser pulse frequency exceeds the frequency associated by the energy difference between initial and final states, the entire wavefunction is translated in space nearly without loss of coherence, to a well defined distance from the original position where the ionized core is left behind. This statement is demonstrated on the excited Rydberg states (n = 10, n = 15), where almost no distortion in the transported wave functions has been observed. However, the ground state (n = 1) is visibly distorted during the removal by pulses of reasonable frequencies, as also predicted by Dimitrovsky and Briggs analysis. Our approach allows us to analyze general pulses as well as the model delta-function potentials on the same footing in the Kramers-Henneberger frame.

Novel approach for image skeleton and distance transformation parallel algorithms

NASA Astrophysics Data System (ADS)

Qing, Kent P.; Means, Robert W.

1994-05-01

Image Understanding is more important in medical imaging than ever, particularly where real-time automatic inspection, screening and classification systems are installed. Skeleton and distance transformations are among the common operations that extract useful information from binary images and aid in Image Understanding. The distance transformation describes the objects in an image by labeling every pixel in each object with the distance to its nearest boundary. The skeleton algorithm starts from the distance transformation and finds the set of pixels that have a locally maximum label. The distance algorithm has to scan the entire image several times depending on the object width. For each pixel, the algorithm must access the neighboring pixels and find the maximum distance from the nearest boundary. It is a computational and memory access intensive procedure. In this paper, we propose a novel parallel approach to the distance transform and skeleton algorithms using the latest VLSI high- speed convolutional chips such as HNC's ViP. The algorithm speed is dependent on the object's width and takes (k + [(k-1)/3]) * 7 milliseconds for a 512 X 512 image with k being the maximum distance of the largest object. All objects in the image will be skeletonized at the same time in parallel.

"Hot-wire" microfluidic flowmeter based on a microfiber coupler.

PubMed

Yan, Shao-Cheng; Liu, Zeng-Yong; Li, Cheng; Ge, Shi-Jun; Xu, Fei; Lu, Yan-Qing

2016-12-15

Using an optical microfiber coupler (MC), we present a microfluidic platform for strong direct or indirect light-liquid interaction by wrapping a MC around a functionalized capillary. The light propagating in the MC and the liquid flowing in the capillary can be combined and divorced smoothly, keeping a long-distance interaction without the conflict of input and output coupling. Using this approach, we experimentally demonstrate a "hot-wire" microfluidic flowmeter based on a gold-integrated helical MC device. The microfluid inside the glass channel takes away the heat, then cools the MC and shifts the resonant wavelength. Due to the long-distance interaction and high temperature sensitivity, the proposed microfluidic flowmeter shows an ultrahigh flow rate sensitivity of 2.183 nm/(μl/s) at a flow rate of 1 μl/s. The minimum detectable change of the flow rate is around 9 nl/s at 1 μl/s.

Calculation of rates of exciton dissociation into hot charge-transfer states in model organic photovoltaic interfaces

NASA Astrophysics Data System (ADS)

Vázquez, Héctor; Troisi, Alessandro

2013-11-01

We investigate the process of exciton dissociation in ordered and disordered model donor/acceptor systems and describe a method to calculate exciton dissociation rates. We consider a one-dimensional system with Frenkel states in the donor material and states where charge transfer has taken place between donor and acceptor. We introduce a Green's function approach to calculate the generation rates of charge-transfer states. For disorder in the Frenkel states we find a clear exponential dependence of charge dissociation rates with exciton-interface distance, with a distance decay constant β that increases linearly with the amount of disorder. Disorder in the parameters that describe (final) charge-transfer states has little effect on the rates. Exciton dissociation invariably leads to partially separated charges. In all cases final states are “hot” charge-transfer states, with electron and hole located far from the interface.

Complexes of dipolar excitons in layered quasi-two-dimensional nanostructures

NASA Astrophysics Data System (ADS)

Bondarev, Igor V.; Vladimirova, Maria R.

2018-04-01

We discuss neutral and charged complexes (biexcitons and trions) formed by indirect excitons in layered quasi-two-dimensional semiconductor heterostructures. Indirect excitons—long-lived neutral Coulomb-bound pairs of electrons and holes of different layers—have been known for semiconductor coupled quantum wells and have recently been reported for van der Waals heterostructures such as double bilayer graphene and transition-metal dichalcogenides. Using the configuration space approach, we derive the analytical expressions for the trion and biexciton binding energies as a function of interlayer distance. The method captures essential kinematics of complex formation to reveal significant binding energies, up to a few tens of meV for typical interlayer distances ˜3 -5 Å , with the trion binding energy always being greater than that of the biexciton. Our results can contribute to the understanding of more complex many-body phenomena such as exciton Bose-Einstein condensation and Wigner-like electron-hole crystallization in layered semiconductor heterostructures.

Modified many-body wave function for BCS-BEC crossover in Fermi gases

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

Tan, Shina; Levin, K.

2006-10-15

We present a many-body formalism for BCS-BEC crossover, which represents a modification of the Bardeen-Cooper-Schrieffer-Leggett ground state to include four-fermion and higher correlations. In the Bose-Einstein condensate regime, we show how our approach contains the four-fermion behavior of Petrov et al. and associated scattering length a{sub dd} at short distances and, second, reduces to composite-boson Bogoliubov physics at long distances. It reproduces the Lee-Yang term, whose numerical value is also fixed by a{sub dd}. We have also examined the next term beyond the Lee-Yang correction in a phenomenological fashion, building on cloud size data and collective mode experiments, although onemore » has to view this phenomenological analysis with some caution since experiments are in a state of flux and are performed close to unitarity.« less

Dispersion in Rectangular Networks: Effective Diffusivity and Large-Deviation Rate Function

NASA Astrophysics Data System (ADS)

Tzella, Alexandra; Vanneste, Jacques

2016-09-01

The dispersion of a diffusive scalar in a fluid flowing through a network has many applications including to biological flows, porous media, water supply, and urban pollution. Motivated by this, we develop a large-deviation theory that predicts the evolution of the concentration of a scalar released in a rectangular network in the limit of large time t ≫1 . This theory provides an approximation for the concentration that remains valid for large distances from the center of mass, specifically for distances up to O (t ) and thus much beyond the O (t1 /2) range where a standard Gaussian approximation holds. A byproduct of the approach is a closed-form expression for the effective diffusivity tensor that governs this Gaussian approximation. Monte Carlo simulations of Brownian particles confirm the large-deviation results and demonstrate their effectiveness in describing the scalar distribution when t is only moderately large.

Towards a unifying approach to diversity measures: bridging the gap between the Shannon entropy and Rao's quadratic index.

PubMed

Ricotta, Carlo; Szeidl, Laszlo

2006-11-01

The diversity of a species assemblage has been studied extensively for many decades in relation to its possible connection with ecosystem functioning and organization. In this view most diversity measures, such as Shannon's entropy, rely upon information theory as a basis for the quantification of diversity. Also, traditional diversity measures are computed using species relative abundances and cannot account for the ecological differences between species. Rao first proposed a diversity index, termed quadratic diversity (Q) that incorporates both species relative abundances and pairwise distances between species. Quadratic diversity is traditionally defined as the expected distance between two randomly selected individuals. In this paper, we show that quadratic diversity can be interpreted as the expected conflict among the species of a given assemblage. From this unusual interpretation, it naturally follows that Rao's Q can be related to the Shannon entropy through a generalized version of the Tsallis parametric entropy.

Toward a comprehensive theory for the sweeping of trapped radiation by inert orbiting matter

NASA Technical Reports Server (NTRS)

Fillius, Walker

1988-01-01

There is a need to calculate loss rates when trapped Van Allen radiation encounters inert orbiting material such as planetary rings and satellites. An analytic expression for the probability of a hit in a bounce encounter is available for all cases where the absorber is spherical and the particles are gyrotropically distributed on a cylindrical flux tube. The hit probability is a function of the particle's pitch angle, the size of the absorber, and the distance between flux tube and absorber, when distances are scaled to the gyroradius of a particle moving perpendicular to the magnetic field. Using this expression, hit probabilities have been computed in drift encounters for all regimes of particle energies and absorber sizes. This technique generalizes the approach to sweeping lifetimes, and is particularly suitable for attacking the inverse problem, where one is given a sweeping signature and wants to deduce the properties of the absorber(s).

Local-scale Partitioning of Functional and Phylogenetic Beta Diversity in a Tropical Tree Assemblage.

PubMed

Yang, Jie; Swenson, Nathan G; Zhang, Guocheng; Ci, Xiuqin; Cao, Min; Sha, Liqing; Li, Jie; Ferry Slik, J W; Lin, Luxiang

2015-08-03

The relative degree to which stochastic and deterministic processes underpin community assembly is a central problem in ecology. Quantifying local-scale phylogenetic and functional beta diversity may shed new light on this problem. We used species distribution, soil, trait and phylogenetic data to quantify whether environmental distance, geographic distance or their combination are the strongest predictors of phylogenetic and functional beta diversity on local scales in a 20-ha tropical seasonal rainforest dynamics plot in southwest China. The patterns of phylogenetic and functional beta diversity were generally consistent. The phylogenetic and functional dissimilarity between subplots (10 × 10 m, 20 × 20 m, 50 × 50 m and 100 × 100 m) was often higher than that expected by chance. The turnover of lineages and species function within habitats was generally slower than that across habitats. Partitioning the variation in phylogenetic and functional beta diversity showed that environmental distance was generally a better predictor of beta diversity than geographic distance thereby lending relatively more support for deterministic environmental filtering over stochastic processes. Overall, our results highlight that deterministic processes play a stronger role than stochastic processes in structuring community composition in this diverse assemblage of tropical trees.

Function representation with circle inversion map systems

NASA Astrophysics Data System (ADS)

Boreland, Bryson; Kunze, Herb

2017-01-01

The fractals literature develops the now well-known concept of local iterated function systems (using affine maps) with grey-level maps (LIFSM) as an approach to function representation in terms of the associated fixed point of the so-called fractal transform. While originally explored as a method to achieve signal (and 2-D image) compression, more recent work has explored various aspects of signal and image processing using this machinery. In this paper, we develop a similar framework for function representation using circle inversion map systems. Given a circle C with centre õ and radius r, inversion with respect to C transforms the point p˜ to the point p˜', such that p˜ and p˜' lie on the same radial half-line from õ and d(õ, p˜)d(õ, p˜') = r2, where d is Euclidean distance. We demonstrate the results with an example.

Automatic Rooftop Extraction in Stereo Imagery Using Distance and Building Shape Regularized Level Set Evolution

NASA Astrophysics Data System (ADS)

Tian, J.; Krauß, T.; d'Angelo, P.

2017-05-01

Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.

Swelling of biological and semiflexible polyelectrolytes.

PubMed

Dobrynin, Andrey V; Carrillo, Jan-Michael Y

2009-10-21

We have developed a theoretical model of swelling of semiflexible (biological) polyelectrolytes in salt solutions. Our approach is based on separation of length scales which allowed us to split a chain's electrostatic energy into two parts that describe local and remote electrostatic interactions along the polymer backbone. The local part takes into account interactions between charged monomers that are separated by distances along the polymer backbone shorter than the chain's persistence length. These electrostatic interactions renormalize chain persistence length. The second part includes electrostatic interactions between remote charged pairs along the polymer backbone located at distances larger than the chain persistence length. These interactions are responsible for chain swelling. In the framework of this approach we calculated effective chain persistence length and chain size as a function of the Debye screening length, chain degree of ionization, bare persistence length and chain degree of polymerization. Our crossover expression for the effective chain's persistence length is in good quantitative agreement with the experimental data on DNA. We have been able to fit experimental datasets by using two adjustable parameters: DNA ionization degree (α = 0.15-0.17) and a bare persistence length (l(p) = 40-44 nm).

New approach to calculate the true-coincidence effect of HpGe detector

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

Alnour, I. A., E-mail: aaibrahim3@live.utm.my, E-mail: ibrahim.elnour@yahoo.com; Wagiran, H.; Ibrahim, N.

The corrections for true-coincidence effects in HpGe detector are important, especially at low source-to-detector distances. This work established an approach to calculate the true-coincidence effects experimentally for HpGe detectors of type Canberra GC3018 and Ortec GEM25-76-XLB-C, which are in operation at neutron activation analysis lab in Malaysian Nuclear Agency (NM). The correction for true-coincidence effects was performed close to detector at distances 2 and 5 cm using {sup 57}Co, {sup 60}Co, {sup 133}Ba and {sup 137}Cs as standard point sources. The correction factors were ranged between 0.93-1.10 at 2 cm and 0.97-1.00 at 5 cm for Canberra HpGe detector; whereas for Ortec HpGemore » detector ranged between 0.92-1.13 and 0.95-100 at 2 and 5 cm respectively. The change in efficiency calibration curve of the detector at 2 and 5 cm after correction was found to be less than 1%. Moreover, the polynomial parameters functions were simulated through a computer program, MATLAB in order to find an accurate fit to the experimental data points.« less

StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images.

PubMed

De Backer, A; van den Bos, K H W; Van den Broek, W; Sijbers, J; Van Aert, S

2016-12-01

An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. Copyright © 2016 Elsevier B.V. All rights reserved.

An optimization model to design and manage subsurface drip irrigation system for alfalfa

NASA Astrophysics Data System (ADS)

Kandelous, M.; Kamai, T.; Vrugt, J. A.; Simunek, J.; Hanson, B.; Hopmans, J. W.

2010-12-01

Subsurface drip irrigation (SDI) is one of the most efficient and cost-effective methods for watering alfalfa plants. Lateral installation depth and distance, emitter discharge, and irrigation time and frequency of SDI, in addition to soil and climatic conditions affect alfalfa’s root water uptake and yield. Here we use a multi-objective optimization approach to find optimal SDI strategies. Our approach uses the AMALGAM evolutionary search method, in combination with the HYDRUS-2D unsaturated flow model to maximize water uptake by alfalfa’s plant roots, and minimize loss of irrigation and drainage water to the atmosphere or groundwater. We use a variety of different objective functions to analyze SDI. These criteria include the lateral installation depth and distance, the lateral discharge, irrigation duration, and irrigation frequency. Our framework includes explicit recognition of the soil moisture status during the simulation period to make sure that the top soil is dry for harvesting during the growing season. Initial results show a wide spectrum of optimized SDI strategies for different root distributions, soil textures and climate conditions. The developed tool should be useful in helping farmers optimize their irrigation strategy and design.

Pelvic form and locomotor adaptation in strepsirrhine primates.

PubMed

Lewton, Kristi L

2015-01-01

The pelvic girdle is a complex structure with a critical role in locomotion, but efforts to model the mechanical effects of locomotion on its shape remain difficult. Traditional approaches to understanding form and function include univariate adaptive hypothesis-testing derived from mechanical models. Geometric morphometric (GM) methods can yield novel insight into overall three-dimensional shape similarities and differences across groups, although the utility of GM in assessing functional differences has been questioned. This study evaluates the contributions of both univariate and GM approaches to unraveling the trait-function associations between pelvic form and locomotion. Three-dimensional landmarks were collected on a phylogenetically-broad sample of 180 pelves from nine primate taxa. Euclidean interlandmark distances were calculated to facilitate testing of biomechanical hypotheses, and a principal components (PC) analysis was performed on Procrustes coordinates to examine overall shape differences. Both linear dimensions and PC scores were subjected to phylogenetic ANOVA. Many of the null hypotheses relating linear dimensions to locomotor loading were not rejected. Although both analytical approaches suggest that ilium width and robusticity differ among locomotor groups, the GM analysis also suggests that ischiopubic shape differentiates groups. Although GM provides additional quantitative results beyond the univariate analyses, this study highlights the need for new GM methods to more specifically address functional shape differences among species. Until these methods are developed, it would be prudent to accompany tests of directional biomechanical hypotheses with current GM methods for a more nuanced understanding of shape and function. © 2014 Wiley Periodicals, Inc.

Electro-mechanical sine/cosine generator

NASA Technical Reports Server (NTRS)

Flagge, B. (Inventor)

1972-01-01

An electromechanical device for generating both sine and cosine functions is described. A motor rotates a cylinder about an axis parallel to and a slight distance from the central axis of the cylinder. Two noncontacting displacement sensing devices are placed ninety degrees apart, equal distances from the axis of rotation of the cylinder and short distances above the surface of cylinder. Each of these sensing devices produces an electrical signal proportional to the distance that it is away from the cylinder. Consequently, as the cylinder is rotated the outputs from the two sensing devices are the sine and cosine functions.

Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances.

PubMed

Fort, Florian; Jouany, Claire; Cruz, Pablo

2015-01-01

Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e., ecological niches. We measured a wide range of functional traits (root traits, leaf traits, and whole plant traits) in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species' ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems) are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems) are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance.

Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances

PubMed Central

Fort, Florian; Jouany, Claire; Cruz, Pablo

2015-01-01

Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e., ecological niches. We measured a wide range of functional traits (root traits, leaf traits, and whole plant traits) in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species' ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems) are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems) are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance. PMID:25741353

The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity

PubMed Central

Hallquist, Michael N.; Hwang, Kai; Luna, Beatriz

2013-01-01

Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n = 117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r = .10 – .35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore, distance-related differences in the association of head motion and connectivity estimates were much weaker for the simultaneous filtering approach. We recommend that future RS-fcMRI studies ensure that the frequencies of nuisance regressors and fMRI data match prior to nuisance regression, and we advocate a simultaneous bandpass filtering and nuisance regression strategy that better controls nuisance-related variability. PMID:23747457

Correlation function of the luminosity distances

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

Biern, Sang Gyu; Yoo, Jaiyul, E-mail: sgbiern@physik.uzh.ch, E-mail: jyoo@physik.uzh.ch

We present the correlation function of the luminosity distances in a flat ΛCDM universe. Decomposing the luminosity distance fluctuation into the velocity, the gravitational potential, and the lensing contributions in linear perturbation theory, we study their individual contributions to the correlation function. The lensing contribution is important at large redshift ( z ∼> 0.5) but only for small angular separation (θ ∼< 3°), while the velocity contribution dominates over the other contributions at low redshift or at larger separation. However, the gravitational potential contribution is always subdominant at all scale, if the correct gauge-invariant expression is used. The correlation functionmore » of the luminosity distances depends significantly on the matter content, especially for the lensing contribution, thus providing a novel tool of estimating cosmological parameters.« less

Factors Influencing Cognitive Function in Subjects With COPD.

PubMed

Dag, Ersel; Bulcun, Emel; Turkel, Yakup; Ekici, Aydanur; Ekici, Mehmet

2016-08-01

The aim of this study was to assess the association between cognitive function and age, pulmonary function, comorbidity index, and the 6-min walk distance in subjects with COPD as well as to compare the Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) in terms of their ability to identify cognitive dysfunction in subjects with COPD. A total of 52 individuals with stable COPD were included in this study. Cognitive function was assessed using MMSE and MoCA. Age, body mass index, the Modified Cumulative Illness Rating Scale, 6-min walk distance, arterial blood gases, and pulmonary function tests were assessed and recorded. The range and SD of scores in subjects with COPD were larger with MoCA than with MMSE. MMSE and MoCA scores are associated with 6-min walk distance and comorbidity index in subjects with COPD. General cognitive function measured by MoCA was negatively correlated with the comorbidity index but was positively associated with 6-min walk distance in subjects with COPD after controlling for possible confounding factors in the multivariate model. However, general cognitive function measured by MMSE was not correlated with the comorbidity index and 6-min walk distance in subjects with COPD, after controlling for possible confounding factors in the multivariate model. MoCA may be a more reliable screening test than MMSE in detecting cognitive impairment in subjects with COPD. The addition of cognitive tests on assessment of subjects with COPD can provide further benefit. Copyright © 2016 by Daedalus Enterprises.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.

PubMed

St Laurent, Georges; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J L; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R R; Nicolas, Estelle; McCaffrey, Timothy A; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-04-20

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Adjunct Faculty as Key Stakeholders in Distance Education

ERIC Educational Resources Information Center

Ridge, Alison; Ritt, Elizabeth

2017-01-01

Institutions of higher learning are expanding their academic reach by offering distance education courses and degree programs. Student demand for distance education continues to grow and so does the need for qualified faculty. The literature presents numerous approaches and best practices regarding new faculty orientation and professional…

Plantar Pressure Distribution among Older Persons with Different Types of Foot and Its Correlation with Functional Reach Distance

PubMed Central

2016-01-01

Background. Changes in biomechanical structures of human foot are common in the older person, which may lead to alteration of foot type and plantar pressure distribution. We aimed to examine how foot type affects the plantar pressure distribution and to determine the relationship between plantar pressure distribution and functional reach distance in older persons. Methods. Fifty community-dwelling older persons (age: 69.98 ± 5.84) were categorized into three groups based on the Foot Posture Index. The plantar pressure (max⁡P) and contact area were analyzed using Footscan® RSScan platform. The Kruskal-Wallis test was used to compare the plantar pressure between foot types and Spearman's correlation coefficient was used to correlate plantar pressure with the functional reach distance. Results. There were significant differences of max⁡P in the forefoot area across all foot types. The post hoc analysis found significantly lower max⁡P in the pronated foot compared to the supinated foot. A high linear rank correlation was found between functional reach distance and max⁡P of the rearfoot region of the supinated foot. Conclusions. These findings suggested that types of the foot affect the plantar maximal pressure in older persons with functional reach distance showing some associations. PMID:27980874

The representation of spacetime through steep time functions

NASA Astrophysics Data System (ADS)

Minguzzi, Ettore

2018-02-01

In a recent work I showed that the family of smooth steep time functions can be used to recover the order, the topology and the (Lorentz-Finsler) distance of spacetime. In this work I present the main ideas entering the proof of the (smooth) distance formula, particularly the product trick which converts metric statements into causal ones. The paper ends with a second proof of the distance formula valid for globally hyperbolic Lorentzian spacetimes.

A Distance Education Model for Training Substance Abuse Treatment Providers in Cognitive-Behavioral Therapy

ERIC Educational Resources Information Center

Watson, Donnie W.; Rawson, Richard R.; Rataemane, Solomon; Shafer, Michael S.; Obert, Jeanne; Bisesi, Lorrie; Tanamly, Susie

2003-01-01

This paper presents a rationale for the use of a distance education approach in the clinical training of community substance abuse treatment providers. Developing and testing new approaches to the clinical training and supervision of providers is important in the substance abuse treatment field where new information is always available. A…

Reactions to Approach-Distance in Overweight and Normal Weight College Females.

ERIC Educational Resources Information Center

Rogers, Ruth Ann; Thomas, Georgelle

Research has found that the need for personal space is greater for normal persons who are interacting with stigmatized persons, such as overweight people, and that one who is identified as deviant may be more sensitive to environmental cues and react more strongly to affective stimuli. To investigate the reactions to approach/distance among…

Human Estimation of Slope, Distance, and Height of Terrain in Simulated Lunar Conditions

DTIC Science & Technology

2009-02-01

directions. During the Apollo 14 hike to Cone Crater, Astronaut Mitchell recognized the crater “Old Nameless ” and judged its distance as 200 – 300...and Mitchell approached Station B2 during their climb of Cone Crater in Apollo 14, they approached a larger crater, thought to be “Old Nameless ” [44

Learner-Centered Online Courses/Programs in Gerontology and Geriatrics: New Responses to Changing Needs of Health Professionals

ERIC Educational Resources Information Center

Cotter, J. James; Welleford, E. Ayn; Drain, Cecil B.

2008-01-01

This article describes recent trends that have led to an emphasis on a learner-centered approach to gerontology and geriatrics education especially in distance-based education. A learner-centered approach to education has combined with technological advances to stimulate distance-enhanced education for students in geriatric and gerontology…

Theory and Practice in the Teaching of Composition: Processing, Distancing, and Modeling.

ERIC Educational Resources Information Center

Myers, Miles, Ed.; Gray, James, Ed.

Intended to show teachers how their approaches to the teaching of writing reflect a particular area of research and to show researchers how the intuitions of teachers reflect research findings, the articles in this book are classified according to three approaches to writing: processing, distancing, and modeling. After an introductory essay that…

Studying Distance Students: Methods, Findings, Actions

ERIC Educational Resources Information Center

Wahl, Diane; Avery, Beth; Henry, Lisa

2013-01-01

University of North Texas (UNT) Libraries began studying the library needs of distance learners in 2009 using a variety of approaches to explore and confirm these needs as well as obtain input into how to meet them. Approaches used to date include analysis of both quantitative and qualitative responses by online students to the LibQUAL+[R] surveys…

Learning in First-Year Biology: Approaches of Distance and On-Campus Students

ERIC Educational Resources Information Center

Quinn, Frances Catherine

2011-01-01

This paper aims to extend previous research into learning of tertiary biology, by exploring the learning approaches adopted by two groups of students studying the same first-year biology topic in either on-campus or off-campus "distance" modes. The research involved 302 participants, who responded to a topic-specific version of the Study Process…

Whatever Happened to the Silent Scientific Revolution?--Research, Theory and Practice in Distance Education.

ERIC Educational Resources Information Center

Morgan, Alistair

The point of departure for this article is the title of a book edited by David Fetterman, "Qualitative Approaches to Educational Evaluation--The Silent Scientific Revolution." This article addresses the question of how the shift to a qualitative, phenomenological approach has impinged on research and evaluation in distance education.…

Hybrid Visible Light and Ultrasound-Based Sensor for Distance Estimation

PubMed Central

Rabadan, Jose; Guerra, Victor; Rodríguez, Rafael; Rufo, Julio; Luna-Rivera, Martin; Perez-Jimenez, Rafael

2017-01-01

Distance estimation plays an important role in location-based services, which has become very popular in recent years. In this paper, a new short range cricket sensor-based approach is proposed for indoor location applications. This solution uses Time Difference of Arrival (TDoA) between an optical and an ultrasound signal which are transmitted simultaneously, to estimate the distance from the base station to the mobile receiver. The measurement of the TDoA at the mobile receiver endpoint is proportional to the distance. The use of optical and ultrasound signals instead of the conventional radio wave signal makes the proposed approach suitable for environments with high levels of electromagnetic interference or where the propagation of radio frequencies is entirely restricted. Furthermore, unlike classical cricket systems, a double-way measurement procedure is introduced, allowing both the base station and mobile node to perform distance estimation simultaneously. PMID:28208584

VizieR Online Data Catalog: Close encounters to the Sun in Gaia DR1 (Bailer-Jones, 2018)

NASA Astrophysics Data System (ADS)

Bailer-Jones, C. A. L.

2017-08-01

The table gives the perihelion (closest approach) parameters of stars in the Gaia-DR1 TGAS catalogue which are found by numerical integration through a Galactic potential to approach within 10pc of the Sun. These parameters are the time (relative to the Gaia measurement epoch), heliocentric distance, and heliocentric speed of the star at perihelion. Uncertainties in these have been calculated by a Monte Carlo sampling of the data to give the posterior probability density function (PDF) over the parameters. For each parameter three summary values of this PDF are reported: the median, the 5% lower bound, the 95% upper bound. The latter two give a 90% confidence interval. The table also reports the probability that each star approaches the Sun within 0.5, 1.0, and 2.0pc, as well as the measured parallax, proper motion, and radial velocity (plus uncertainties) of the stars. Table 3 in the article lists the first 20 lines of this data table (stars with median perihelion distances below 2pc). Some stars are duplicated in this table, i.e. there are rows with the same ID, but different data. Stars with problematic data have not been removed, so some encounters are not reliable. Most IDs are Tycho, but in a few cases they are Hipparcos. (1 data file).

Cardiac Multi-detector CT Segmentation Based on Multiscale Directional Edge Detector and 3D Level Set.

PubMed

Antunes, Sofia; Esposito, Antonio; Palmisano, Anna; Colantoni, Caterina; Cerutti, Sergio; Rizzo, Giovanna

2016-05-01

Extraction of the cardiac surfaces of interest from multi-detector computed tomographic (MDCT) data is a pre-requisite step for cardiac analysis, as well as for image guidance procedures. Most of the existing methods need manual corrections, which is time-consuming. We present a fully automatic segmentation technique for the extraction of the right ventricle, left ventricular endocardium and epicardium from MDCT images. The method consists in a 3D level set surface evolution approach coupled to a new stopping function based on a multiscale directional second derivative Gaussian filter, which is able to stop propagation precisely on the real boundary of the structures of interest. We validated the segmentation method on 18 MDCT volumes from healthy and pathologic subjects using manual segmentation performed by a team of expert radiologists as gold standard. Segmentation errors were assessed for each structure resulting in a surface-to-surface mean error below 0.5 mm and a percentage of surface distance with errors less than 1 mm above 80%. Moreover, in comparison to other segmentation approaches, already proposed in previous work, our method presented an improved accuracy (with surface distance errors less than 1 mm increased of 8-20% for all structures). The obtained results suggest that our approach is accurate and effective for the segmentation of ventricular cavities and myocardium from MDCT images.

Stardust Dynamic Science at Wild 2: First Look

NASA Technical Reports Server (NTRS)

Anderson, J. D.; Lau, E. L.; Clark, B. C.; Asmar, S. W.

2004-01-01

The Dynamic Science investigation on the STARDUST mission has been described previously. The data delivered by the STARDUST Project is multifold, but basically it consists of radio Doppler data from the Deep Space Network (DSN) and attitude control data (ACS) from the spacecraft. Doppler data were successfully recorded by JPL's Navigation System (closed-loop data) and also by its Radio Science System (open-loop data) at DSN stations DSS43 near Canberra Australia and at DSS14 at Goldstone California. Attitude control data were also successfully delivered to the Dynamic Science Team. Here we describe a preliminary analysis of the data. Beyond a closest approach distance of 150 km, a Doppler detection of a the Wild 2 nucleus mass was not expected. The current best estimate of the closest approach distance is 236.4 km, and as expected, any mass signal in the Doppler data is hopelessly buried in the noise. We have attempted to fit the data to a mass model with no success. However, analysis of the Doppler data and the ACS data for particle impacts on the spacecraft's Whipple shields is in progress, and will be reported at the meeting. The DSS43 closed-loop Doppler residuals are plotted as a function of time from the current best estimate of the time of Wild 2 closest approach, 2 January 2004, 19:43:11.7 UTC, Earth-receive time at the station.

Using Finance Policy To Reduce Barriers to Distance Learning. A Report and Recommendations in a Series on Distance Learning Policy Issues.

ERIC Educational Resources Information Center

Southern Regional Education Board, Atlanta, GA.

This study explored the ways in which state and system financing policies can advance the use of distance learning technologies and the goals outlined in other reports by the Distance Learning Policy Laboratory more effectively. The subcommittee on finance that examined the issue approached the task by establishing a framework that considered:…

Distance Mapping in Proteins Using Fluorescence Spectroscopy: The Tryptophan-Induced Quenching (TrIQ) Method

PubMed Central

Mansoor, Steven E.; DeWitt, Mark A.; Farrens, David L.

2014-01-01

Studying the interplay between protein structure and function remains a daunting task. Especially lacking are methods for measuring structural changes in real time. Here we report our most recent improvements to a method that can be used to address such questions. This method, which we now call Tryptophan induced quenching (TrIQ), provides a straightforward, sensitive and inexpensive way to address questions of conformational dynamics and short-range protein interactions. Importantly, TrIQ only occurs over relatively short distances (~5 to 15 Å), making it complementary to traditional fluorescence resonance energy transfer (FRET) methods that occur over distances too large for precise studies of protein structure. As implied in the name, TrIQ measures the efficient quenching induced in some fluorophores by tryptophan (Trp). We present here our analysis of the TrIQ effect for five different fluorophores that span a range of sizes and spectral properties. Each probe was attached to four different cysteine residues on T4 lysozyme and the extent of TrIQ caused by a nearby Trp was measured. Our results show that for smaller probes, TrIQ is distance dependent. Moreover, we also demonstrate how TrIQ data can be analyzed to determine the fraction of fluorophores involved in a static, non-fluorescent complex with Trp. Based on this analysis, our study shows that each fluorophore has a different TrIQ profile, or "sphere of quenching", which correlates with its size, rotational flexibility, and the length of attachment linker. This TrIQ-based "sphere of quenching" is unique to every Trp-probe pair and reflects the distance within which one can expect to see the TrIQ effect. It provides a straightforward, readily accessible approach for mapping distances within proteins and monitoring conformational changes using fluorescence spectroscopy. PMID:20886836

Pairing call-response surveys and distance sampling for a mammalian carnivore

USGS Publications Warehouse

Hansen, Sara J. K.; Frair, Jacqueline L.; Underwood, Harold B.; Gibbs, James P.

2015-01-01

Density estimates accounting for differential animal detectability are difficult to acquire for wide-ranging and elusive species such as mammalian carnivores. Pairing distance sampling with call-response surveys may provide an efficient means of tracking changes in populations of coyotes (Canis latrans), a species of particular interest in the eastern United States. Blind field trials in rural New York State indicated 119-m linear error for triangulated coyote calls, and a 1.8-km distance threshold for call detectability, which was sufficient to estimate a detection function with precision using distance sampling. We conducted statewide road-based surveys with sampling locations spaced ≥6 km apart from June to August 2010. Each detected call (be it a single or group) counted as a single object, representing 1 territorial pair, because of uncertainty in the number of vocalizing animals. From 524 survey points and 75 detections, we estimated the probability of detecting a calling coyote to be 0.17 ± 0.02 SE, yielding a detection-corrected index of 0.75 pairs/10 km2 (95% CI: 0.52–1.1, 18.5% CV) for a minimum of 8,133 pairs across rural New York State. Importantly, we consider this an index rather than true estimate of abundance given the unknown probability of coyote availability for detection during our surveys. Even so, pairing distance sampling with call-response surveys provided a novel, efficient, and noninvasive means of monitoring populations of wide-ranging and elusive, albeit reliably vocal, mammalian carnivores. Our approach offers an effective new means of tracking species like coyotes, one that is readily extendable to other species and geographic extents, provided key assumptions of distance sampling are met.

Topics on distance correlation, feature screening and lifetime expectancy with application to Beaver Dam eye study data

NASA Astrophysics Data System (ADS)

Kong, Jing

This thesis includes 4 pieces of work. In Chapter 1, we present the work with a method for examining mortality as it is seen to run in families, and lifestyle factors that are also seen to run in families, in a subpopulation of the Beaver Dam Eye Study that has died by 2011. We find significant distance correlations between death ages, lifestyle factors, and family relationships. Considering only sib pairs compared to unrelated persons, distance correlation between siblings and mortality is, not surprisingly, stronger than that between more distantly related family members and mortality. Chapter 2 introduces a feature screening procedure with the use of distance correlation and covariance. We demonstrate a property for distance covariance, which is incorporated in a novel feature screening procedure based on distance correlation as a stopping criterion. The approach is further implemented to two real examples, namely the famous small round blue cell tumors data and the Cancer Genome Atlas ovarian cancer data Chapter 3 pays attention to the right censored human longevity data and the estimation of lifetime expectancy. We propose a general framework of backward multiple imputation for estimating the conditional lifetime expectancy function and the variance of the estimator in the right censoring setting and prove the properties of the estimator. In addition, we apply the method to the Beaver Dam eye study data to study human longevity, where the expected human lifetime are modeled with smoothing spline ANOVA based on the covariates including baseline age, gender, lifestyle factors and disease variables. Chapter 4 compares two imputation methods for right censored data, namely the famous Buckley-James estimator and the backward imputation method proposed in Chapter 3 and shows that backward imputation method is less biased and more robust with heterogeneity.

An ensemble framework for clustering protein-protein interaction networks.

PubMed

Asur, Sitaram; Ucar, Duygu; Parthasarathy, Srinivasan

2007-07-01

Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. Supplementary data are available at Bioinformatics online.

Visual impairment at baseline is associated with future poor physical functioning among middle-aged women: The Study of Women's Health Across the Nation, Michigan Site.

PubMed

Chandrasekaran, Navasuja; Harlow, Sioban; Moroi, Sayoko; Musch, David; Peng, Qing; Karvonen-Gutierrez, Carrie

2017-02-01

Emerging evidence suggests that the prevalence rates of poor functioning and of disability are increasing among middle-aged individuals. Visual impairment is associated with poor functioning among older adults but little is known about the impact of vision on functioning during midlife. The objective of this study was to assess the impact of visual impairment on future physical functioning among middle-aged women. In this longitudinal study, the sample consisted of 483 women aged 42 to 56 years, from the Michigan site of the Study of Women's Health Across the Nation. At baseline, distance and near vision were measured using a Titmus vision screener. Visual impairment was defined as visual acuity worse than 20/40. Physical functioning was measured up to 10 years later using performance-based measures, including a 40-foot timed walk, timed stair climb and forward reach. Women with impaired distance vision at baseline had 2.81 centimeters less forward reach distance (95% confidence interval (CI): -4.19, -1.42) and 4.26s longer stair climb time (95% CI: 2.73, 5.79) at follow-up than women without impaired distance vision. Women with impaired near vision also had less forward reach distance (2.26 centimeters, 95% CI: -3.30, -1.21) than those without impaired near vision. Among middle-aged women, visual impairment is a marker of poor physical functioning. Routine eye testing and vision correction may help improve physical functioning among midlife individuals. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Visual Impairment at Baseline is Associated with Future Poor Physical Functioning Among Middle-Aged Women: The Study of Women's Health Across the Nation, Michigan site

PubMed Central

Chandrasekaran, Navasuja; Harlow, Sioban; Moroi, Sayoko; Musch, David; Peng, Qing; Karvonen-Gutierrez, Carrie

2016-01-01

Objectives Emerging evidence suggests that the prevalence rates of poor functioning and of disability are increasing among middle-aged individuals. Visual impairment is associated with poor functioning among older adults but little is known about the impact of vision on functioning during midlife. The objective of this study was to assess the impact of visual impairment on future physical functioning among middle-aged women. Study design In this longitudinal study, the sample consisted of 483 women aged 42 to 56 years, from the Michigan site of the Study of Women's Health Across the Nation. Main Outcome Measures At baseline, distance and near vision were measured using a Titmus vision screener. Visual impairment was defined as visual acuity worse than 20/40. Physical functioning was measured up to 10 years later using performance-based measures, including a 40-foot timed walk, timed stair climb and forward reach. Results Women with impaired distance vision at baseline had 2.81 centimeters less forward reach distance (95% confidence interval (CI): −4.19,−1.42) and 4.26 seconds longer stair climb time (95% CI: 2.73, 5.79) at follow-up than women without impaired distance vision. Women with impaired near vision also had less forward reach distance (2.26 centimeters, 95% CI: −3.30,−1.21) than those without impaired near vision. Conclusion Among middle-aged women, visual impairment is a marker of poor physical functioning. Routine eye testing and vision correction may help improve physical functioning among midlife individuals. PMID:28041592

Equivalence Testing of Complex Particle Size Distribution Profiles Based on Earth Mover's Distance.

PubMed

Hu, Meng; Jiang, Xiaohui; Absar, Mohammad; Choi, Stephanie; Kozak, Darby; Shen, Meiyu; Weng, Yu-Ting; Zhao, Liang; Lionberger, Robert

2018-04-12

Particle size distribution (PSD) is an important property of particulates in drug products. In the evaluation of generic drug products formulated as suspensions, emulsions, and liposomes, the PSD comparisons between a test product and the branded product can provide useful information regarding in vitro and in vivo performance. Historically, the FDA has recommended the population bioequivalence (PBE) statistical approach to compare the PSD descriptors D50 and SPAN from test and reference products to support product equivalence. In this study, the earth mover's distance (EMD) is proposed as a new metric for comparing PSD particularly when the PSD profile exhibits complex distribution (e.g., multiple peaks) that is not accurately described by the D50 and SPAN descriptor. EMD is a statistical metric that measures the discrepancy (distance) between size distribution profiles without a prior assumption of the distribution. PBE is then adopted to perform statistical test to establish equivalence based on the calculated EMD distances. Simulations show that proposed EMD-based approach is effective in comparing test and reference profiles for equivalence testing and is superior compared to commonly used distance measures, e.g., Euclidean and Kolmogorov-Smirnov distances. The proposed approach was demonstrated by evaluating equivalence of cyclosporine ophthalmic emulsion PSDs that were manufactured under different conditions. Our results show that proposed approach can effectively pass an equivalent product (e.g., reference product against itself) and reject an inequivalent product (e.g., reference product against negative control), thus suggesting its usefulness in supporting bioequivalence determination of a test product to the reference product which both possess multimodal PSDs.

Motivation and temporal distance: effect on cognitive and affective manifestations.

PubMed

Bjørnebekk, Gunnar; Gjesme, Torgrim

2009-10-01

The implications of temporal distance on motivation-related concepts were examined. The results of an experiment, based on 585 Grade 6 students, indicated that both positive (approach) and negative (avoidance) motivation increased as the future goal or event approached in time. This increase in approach and avoidance motivation influenced the performance of the pupils differently. For pupils with success orientation, the performance increased. For pupils with failure orientation, the performance remained about the same.

Skyshine at neutron energies less than or equal to 400 MeV

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

Alsmiller, A.G. Jr.; Barish, J.; Childs, R.L.

1980-10-01

The dose equivalent at an air-ground interface as a function of distance from an assumed azimuthally symmetric point source of neutrons can be calculated as a double integral. The integration is over the source strength as a function of energy and polar angle weighted by an importance function that depends on the source variables and on the distance from the source to the filed point. The neutron importance function for a source 15 m above the ground emitting only into the upper hemisphere has been calculated using the two-dimensional discrete ordinates code, DOT, and the first collision source code, GRTUNCL,more » in the adjoint mode. This importance function is presented for neutron energies less than or equal to 400 MeV, for source cosine intervals of 1 to .8, .8 to .6 to .4, .4 to .2 and .2 to 0, and for various distances from the source to the field point. As part of the adjoint calculations a photon importance function is also obtained. This importance function for photon energies less than or equal to 14 MEV and for various source cosine intervals and source-to-field point distances is also presented. These importance functions may be used to obtain skyshine dose equivalent estimates for any known source energy-angle distribution.« less

Effective distances for epidemics spreading on complex networks.

PubMed

Iannelli, Flavio; Koher, Andreas; Brockmann, Dirk; Hövel, Philipp; Sokolov, Igor M

2017-01-01

We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general network-based measures derived from random walks theory. Using the daily air-traffic transportation data we perform numerical experiments to compare the infection arrival time with this alternative metric that is obtained by accounting for multiple walks instead of only the most probable path. The comparison with direct simulations reveals a higher correlation compared to the shortest-path approach used previously. In addition our method allows to connect fundamental observables in epidemic spreading with the cumulant-generating function of the hitting time for a Markov chain. Our results provides a general and computationally efficient approach using only algebraic methods.

Effective distances for epidemics spreading on complex networks

NASA Astrophysics Data System (ADS)

Iannelli, Flavio; Koher, Andreas; Brockmann, Dirk; Hövel, Philipp; Sokolov, Igor M.

2017-01-01

We show that the recently introduced logarithmic metrics used to predict disease arrival times on complex networks are approximations of more general network-based measures derived from random walks theory. Using the daily air-traffic transportation data we perform numerical experiments to compare the infection arrival time with this alternative metric that is obtained by accounting for multiple walks instead of only the most probable path. The comparison with direct simulations reveals a higher correlation compared to the shortest-path approach used previously. In addition our method allows to connect fundamental observables in epidemic spreading with the cumulant-generating function of the hitting time for a Markov chain. Our results provides a general and computationally efficient approach using only algebraic methods.

Scaling of flow distance in random self-similar channel networks

USGS Publications Warehouse

Troutman, B.M.

2005-01-01

Natural river channel networks have been shown in empirical studies to exhibit power-law scaling behavior characteristic of self-similar and self-affine structures. Of particular interest is to describe how the distribution of distance to the outlet changes as a function of network size. In this paper, networks are modeled as random self-similar rooted tree graphs and scaling of distance to the root is studied using methods in stochastic branching theory. In particular, the asymptotic expectation of the width function (number of nodes as a function of distance to the outlet) is derived under conditions on the replacement generators. It is demonstrated further that the branching number describing rate of growth of node distance to the outlet is identical to the length ratio under a Horton-Strahler ordering scheme as order gets large, again under certain restrictions on the generators. These results are discussed in relation to drainage basin allometry and an application to an actual drainage network is presented. ?? World Scientific Publishing Company.

On the atomic structure of liquid Ni-Si alloys: a neutron diffraction study

NASA Astrophysics Data System (ADS)

Gruner, S.; Marczinke, J.; Hennet, L.; Hoyer, W.; Cuello, G. J.

2009-09-01

The atomic structure of the liquid NiSi and NiSi2 alloys is investigated by means of neutron diffraction experiments with isotopic substitution. From experimental data-sets obtained using four Ni isotopes, partial structure factors and pair correlation functions are obtained by applying a reverse Monte Carlo modelling approach. Both alloys were found to exhibit a strong tendency to hetero-coordination within the first coordination shell. In particular, covalent Si-Si bonds with somewhat greater distances seem to influence the structure of the liquid NiSi alloy.

On the atomic structure of liquid Ni-Si alloys: a neutron diffraction study.

PubMed

Gruner, S; Marczinke, J; Hennet, L; Hoyer, W; Cuello, G J

2009-09-23

The atomic structure of the liquid NiSi and NiSi(2) alloys is investigated by means of neutron diffraction experiments with isotopic substitution. From experimental data-sets obtained using four Ni isotopes, partial structure factors and pair correlation functions are obtained by applying a reverse Monte Carlo modelling approach. Both alloys were found to exhibit a strong tendency to hetero-coordination within the first coordination shell. In particular, covalent Si-Si bonds with somewhat greater distances seem to influence the structure of the liquid NiSi alloy.

Neural Decoding and "Inner" Psychophysics: A Distance-to-Bound Approach for Linking Mind, Brain, and Behavior.

PubMed

Ritchie, J Brendan; Carlson, Thomas A

2016-01-01

A fundamental challenge for cognitive neuroscience is characterizing how the primitives of psychological theory are neurally implemented. Attempts to meet this challenge are a manifestation of what Fechner called "inner" psychophysics: the theory of the precise mapping between mental quantities and the brain. In his own time, inner psychophysics remained an unrealized ambition for Fechner. We suggest that, today, multivariate pattern analysis (MVPA), or neural "decoding," methods provide a promising starting point for developing an inner psychophysics. A cornerstone of these methods are simple linear classifiers applied to neural activity in high-dimensional activation spaces. We describe an approach to inner psychophysics based on the shared architecture of linear classifiers and observers under decision boundary models such as signal detection theory. Under this approach, distance from a decision boundary through activation space, as estimated by linear classifiers, can be used to predict reaction time in accordance with signal detection theory, and distance-to-bound models of reaction time. Our "neural distance-to-bound" approach is potentially quite general, and simple to implement. Furthermore, our recent work on visual object recognition suggests it is empirically viable. We believe the approach constitutes an important step along the path to an inner psychophysics that links mind, brain, and behavior.

Developing Distance Learning Courses in a "Traditional" University.

ERIC Educational Resources Information Center

Lawton, Sally; Barnes, Richard

1998-01-01

Comparison of distance learning that was developed with a business-planning approach (market research, cost-benefit analysis, feasibility study, strategic marketing) with one that did not use these techniques showed that business planning ensures that distance-learning courses are not viewed as a "cheap" option. The method identifies…

Instructional Design for Distance Training.

ERIC Educational Resources Information Center

Carter, John F.

Distance education, especially in the form of correspondence study, is not a new phenomenon, but the success of the British Open University has given it a new image. Distance education programs have been developed to respond to a variety of societal and educational situations for which traditional classroom-based approaches are less feasible. They…

Writing for Distance Education. Samples Booklet.

ERIC Educational Resources Information Center

International Extension Coll., Cambridge (England).

Approaches to the format, design, and layout of printed instructional materials for distance education are illustrated in 36 samples designed to accompany the manual, "Writing for Distance Education." Each sample is presented on a single page with a note pointing out its key features. Features illustrated include use of typescript layout, a comic…

Postsecondary Distance Education in Mexico and Worldwide: Issues and Considerations

ERIC Educational Resources Information Center

Becerra, Bertha Leticia Gonzalez; Almendra, Manuel Pio Rosales; Flores, Jose Daniel Corona

2012-01-01

Postsecondary distance education has attracted increasing attention in recent years, an understandable change when one considers that innovative approaches to distance education have offered opportunities to overcome some of the key challenges in traditional "brick and mortar" education. Nonetheless, there are a plethora of issues that…

36 CFR 13.920 - Wildlife distance conditions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 36 Parks, Forests, and Public Property 1 2014-07-01 2014-07-01 false Wildlife distance conditions... Provisions § 13.920 Wildlife distance conditions. (a) Bears. The following are prohibited: (1) Approaching within 300 yards of a bear; or (2) Engaging in photography within 300 yards of a bear. (b) Other wildlife...

36 CFR 13.920 - Wildlife distance conditions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 36 Parks, Forests, and Public Property 1 2012-07-01 2012-07-01 false Wildlife distance conditions... Provisions § 13.920 Wildlife distance conditions. (a) Bears. The following are prohibited: (1) Approaching within 300 yards of a bear; or (2) Engaging in photography within 300 yards of a bear. (b) Other wildlife...

36 CFR 13.604 - Wildlife distance conditions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 36 Parks, Forests, and Public Property 1 2012-07-01 2012-07-01 false Wildlife distance conditions. 13.604 Section 13.604 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... § 13.604 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards is...

36 CFR 13.1206 - Wildlife distance conditions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 36 Parks, Forests, and Public Property 1 2012-07-01 2012-07-01 false Wildlife distance conditions. 13.1206 Section 13.1206 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... Provisions § 13.1206 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards...

36 CFR 13.1206 - Wildlife distance conditions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Wildlife distance conditions. 13.1206 Section 13.1206 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... Provisions § 13.1206 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards...

36 CFR 13.604 - Wildlife distance conditions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 36 Parks, Forests, and Public Property 1 2011-07-01 2011-07-01 false Wildlife distance conditions. 13.604 Section 13.604 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... § 13.604 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards is...

36 CFR 13.920 - Wildlife distance conditions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 36 Parks, Forests, and Public Property 1 2011-07-01 2011-07-01 false Wildlife distance conditions... Provisions § 13.920 Wildlife distance conditions. (a) Bears. The following are prohibited: (1) Approaching within 300 yards of a bear; or (2) Engaging in photography within 300 yards of a bear. (b) Other wildlife...

36 CFR 13.604 - Wildlife distance conditions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Wildlife distance conditions. 13.604 Section 13.604 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... § 13.604 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards is...

36 CFR 13.1206 - Wildlife distance conditions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 36 Parks, Forests, and Public Property 1 2014-07-01 2014-07-01 false Wildlife distance conditions. 13.1206 Section 13.1206 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... Provisions § 13.1206 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards...

36 CFR 13.604 - Wildlife distance conditions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 36 Parks, Forests, and Public Property 1 2013-07-01 2013-07-01 false Wildlife distance conditions. 13.604 Section 13.604 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... § 13.604 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards is...

36 CFR 13.920 - Wildlife distance conditions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 36 Parks, Forests, and Public Property 1 2013-07-01 2013-07-01 false Wildlife distance conditions... Provisions § 13.920 Wildlife distance conditions. (a) Bears. The following are prohibited: (1) Approaching within 300 yards of a bear; or (2) Engaging in photography within 300 yards of a bear. (b) Other wildlife...

36 CFR 13.604 - Wildlife distance conditions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 36 Parks, Forests, and Public Property 1 2014-07-01 2014-07-01 false Wildlife distance conditions. 13.604 Section 13.604 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... § 13.604 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards is...

36 CFR 13.1206 - Wildlife distance conditions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 36 Parks, Forests, and Public Property 1 2011-07-01 2011-07-01 false Wildlife distance conditions. 13.1206 Section 13.1206 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... Provisions § 13.1206 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards...

36 CFR 13.920 - Wildlife distance conditions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Wildlife distance conditions... Provisions § 13.920 Wildlife distance conditions. (a) Bears. The following are prohibited: (1) Approaching within 300 yards of a bear; or (2) Engaging in photography within 300 yards of a bear. (b) Other wildlife...

36 CFR 13.1206 - Wildlife distance conditions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 36 Parks, Forests, and Public Property 1 2013-07-01 2013-07-01 false Wildlife distance conditions. 13.1206 Section 13.1206 Parks, Forests, and Public Property NATIONAL PARK SERVICE, DEPARTMENT OF THE... Provisions § 13.1206 Wildlife distance conditions. (a) Approaching a bear or any large mammal within 50 yards...

Online Pedagogy: Principles for Supporting Effective Distance Education

ERIC Educational Resources Information Center

Scheer, Stephanie B.; Terry, Krista P.; Doolittle, Peter E.; Hicks, David

2004-01-01

Distance education has become a major form of education in the United States. This surge in popularity has launched a plethora of scholarship emphasizing the distillation of those strategies which inform effective, learning experiences in the distance environment. A growing consensus among researchers recognizes the need for a holistic approach to…

Distance Learning in Scientific and Professional Fields of Communication (Interdisciplinary Approach)

ERIC Educational Resources Information Center

Skorikova, Tatyana Petrovna; Khromova, Sergey Sergeevich; Dneprovskaya, Natalia Vitalievna

2016-01-01

Modern level of informational technologies development allows the authors of educational courses to decrease their dependence from technical specialists and to independently develop distance-learning courses and their separate online components, which require special methodical learning. The aim of present study is to develop a distance-learning…

Supervising Doctorates at a Distance: Three Trans-Tasman Stories

ERIC Educational Resources Information Center

Andrew, Martin

2012-01-01

Purpose: The purpose of this paper is to describe the challenges of post-traditional, distance PhD supervision and suggest pedagogical interventions to bridge the distance. The paper investigates the skills and understandings necessary for mediating the supervisor-supervisee dyad within faceless encounters. Design/methodology/approach: Grounded in…

Research in Distance Education: A System Modeling Approach.

ERIC Educational Resources Information Center

Saba, Farhad; Twitchell, David

This demonstration of the use of a computer simulation research method based on the System Dynamics modeling technique for studying distance education reviews research methods in distance education, including the broad categories of conceptual and case studies, and presents a rationale for the application of systems research in this area. The…

A novel surrogate-based approach for optimal design of electromagnetic-based circuits

NASA Astrophysics Data System (ADS)

Hassan, Abdel-Karim S. O.; Mohamed, Ahmed S. A.; Rabie, Azza A.; Etman, Ahmed S.

2016-02-01

A new geometric design centring approach for optimal design of central processing unit-intensive electromagnetic (EM)-based circuits is introduced. The approach uses norms related to the probability distribution of the circuit parameters to find distances from a point to the feasible region boundaries by solving nonlinear optimization problems. Based on these normed distances, the design centring problem is formulated as a max-min optimization problem. A convergent iterative boundary search technique is exploited to find the normed distances. To alleviate the computation cost associated with the EM-based circuits design cycle, space-mapping (SM) surrogates are used to create a sequence of iteratively updated feasible region approximations. In each SM feasible region approximation, the centring process using normed distances is implemented, leading to a better centre point. The process is repeated until a final design centre is attained. Practical examples are given to show the effectiveness of the new design centring method for EM-based circuits.

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

Protein Loop Structure Prediction Using Conformational Space Annealing.

PubMed

Heo, Seungryong; Lee, Juyong; Joo, Keehyoung; Shin, Hang-Cheol; Lee, Jooyoung

2017-05-22

We have developed a protein loop structure prediction method by combining a new energy function, which we call E PLM (energy for protein loop modeling), with the conformational space annealing (CSA) global optimization algorithm. The energy function includes stereochemistry, dynamic fragment assembly, distance-scaled finite ideal gas reference (DFIRE), and generalized orientation- and distance-dependent terms. For the conformational search of loop structures, we used the CSA algorithm, which has been quite successful in dealing with various hard global optimization problems. We assessed the performance of E PLM with two widely used loop-decoy sets, Jacobson and RAPPER, and compared the results against the DFIRE potential. The accuracy of model selection from a pool of loop decoys as well as de novo loop modeling starting from randomly generated structures was examined separately. For the selection of a nativelike structure from a decoy set, E PLM was more accurate than DFIRE in the case of the Jacobson set and had similar accuracy in the case of the RAPPER set. In terms of sampling more nativelike loop structures, E PLM outperformed E DFIRE for both decoy sets. This new approach equipped with E PLM and CSA can serve as the state-of-the-art de novo loop modeling method.

Spatiotemporal Interpolation for Environmental Modelling

PubMed Central

Susanto, Ferry; de Souza, Paulo; He, Jing

2016-01-01

A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania’s South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497

Ionic diffusion and space charge polarization in structural characterization of biological tissues.

PubMed

Jastrzebska, M; Kocot, A

2004-06-01

In this study, a new approach to the analysis of the low-frequency (1-10(7) Hz) dielectric spectra of biological tissue, has been described. The experimental results are interpreted in terms of ionic diffusion and space charge polarization according to Sawada's theory. The new presentation of dielectric spectra, i.e. ([Formula: see text]) [Formula: see text] has been used. This method results in peaks which are narrower and better resolved than both the measured loss peaks and an alternative loss quantity [Formula: see text]. The presented method and Sawada's expression have been applied to the analysis of changes in the spatial molecular structure of a collagen fibril network in pericardium tissue exposed to glutaraldehyde (GA), with respect to the native tissue. The diffusion coefficient of ions was estimated on the basis of a dielectric dispersion measurement for an aqueous NaCl solution with a well-calibrated distance between the electrodes. The fitting procedure of a theoretical function to the experimental data allowed us to determine three diffusive relaxation regions with three structural distance parameters d(s), describing the spatial arrangement of collagen fibrils in pericardium tissue. It has been found that a significant decrease in the structural distance d(s) from 87 nm to 45 nm may correspond to a reduction in the interfibrillar distance within GA cross-linked tissue.

Experimental demonstration of quantum digital signatures over 43 dB channel loss using differential phase shift quantum key distribution.

PubMed

Collins, Robert J; Amiri, Ryan; Fujiwara, Mikio; Honjo, Toshimori; Shimizu, Kaoru; Tamaki, Kiyoshi; Takeoka, Masahiro; Sasaki, Masahide; Andersson, Erika; Buller, Gerald S

2017-06-12

Ensuring the integrity and transferability of digital messages is an important challenge in modern communications. Although purely mathematical approaches exist, they usually rely on the computational complexity of certain functions, in which case there is no guarantee of long-term security. Alternatively, quantum digital signatures offer security guaranteed by the physical laws of quantum mechanics. Prior experimental demonstrations of quantum digital signatures in optical fiber have typically been limited to operation over short distances and/or operated in a laboratory environment. Here we report the experimental transmission of quantum digital signatures over channel losses of up to 42.8 ± 1.2 dB in a link comprised of 90 km of installed fiber with additional optical attenuation introduced to simulate longer distances. The channel loss of 42.8 ± 1.2 dB corresponds to an equivalent distance of 134.2 ± 3.8 km and this represents the longest effective distance and highest channel loss that quantum digital signatures have been shown to operate over to date. Our theoretical model indicates that this represents close to the maximum possible channel attenuation for this quantum digital signature protocol, defined as the loss for which the signal rate is comparable to the dark count rate of the detectors.

Distancing, not embracing, the Distancing-Embracing model of art reception.

PubMed

Davies, Stephen

2017-01-01

Despite denials in the target article, the Distancing-Embracing model appeals to compensatory ideas in explaining the appeal of artworks that elicit negative affect. The model also appeals to the deflationary effects of psychological distancing. Having pointed to the famous rejection in the 1960s of the view that aesthetic experience involves psychological distancing, I suggest that "distance" functions here as a weak metaphor that cannot sustain the explanatory burden the theory demands of it.

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

PubMed

Gorban, A N; Mirkes, E M; Zinovyev, A

2016-12-01

Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0

Analysing designed experiments in distance sampling

Treesearch

Stephen T. Buckland; Robin E. Russell; Brett G. Dickson; Victoria A. Saab; Donal N. Gorman; William M. Block

2009-01-01

Distance sampling is a survey technique for estimating the abundance or density of wild animal populations. Detection probabilities of animals inherently differ by species, age class, habitats, or sex. By incorporating the change in an observer's ability to detect a particular class of animals as a function of distance, distance sampling leads to density estimates...

Estimating Commute Distances of U.S. Army Reservists by Regional and Unit Characteristics

DTIC Science & Technology

1990-09-01

multiple regression equation is used to estimate the parameters of the commute distance distribution as a function of reserve center and market ...used to estimate the parameters of the commute distance distribution as a function of reserve center and market characteristics. The results of the...recruiting personnel to meet unit fill rates. An important objective of the USAREC is to identify market areas that will support new reserve units [Ref. 2:p

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

NASA Technical Reports Server (NTRS)

Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Distance learning in discriminative vector quantization.

PubMed

Schneider, Petra; Biehl, Michael; Hammer, Barbara

2009-10-01

Discriminative vector quantization schemes such as learning vector quantization (LVQ) and extensions thereof offer efficient and intuitive classifiers based on the representation of classes by prototypes. The original methods, however, rely on the Euclidean distance corresponding to the assumption that the data can be represented by isotropic clusters. For this reason, extensions of the methods to more general metric structures have been proposed, such as relevance adaptation in generalized LVQ (GLVQ) and matrix learning in GLVQ. In these approaches, metric parameters are learned based on the given classification task such that a data-driven distance measure is found. In this letter, we consider full matrix adaptation in advanced LVQ schemes. In particular, we introduce matrix learning to a recent statistical formalization of LVQ, robust soft LVQ, and we compare the results on several artificial and real-life data sets to matrix learning in GLVQ, a derivation of LVQ-like learning based on a (heuristic) cost function. In all cases, matrix adaptation allows a significant improvement of the classification accuracy. Interestingly, however, the principled behavior of the models with respect to prototype locations and extracted matrix dimensions shows several characteristic differences depending on the data sets.

Bioengineered-inorganic nanosystems for nanophotonics and bio-nanotechnology

NASA Astrophysics Data System (ADS)

Leong, Kirsty; Zin, Melvin T.; Ma, Hong; Huang, Fei; Sarikaya, Mehmet; Jen, Alex K.

2008-08-01

Here we nanoengineered tunable quantum dot and cationic conjugated polymer nanoarrays based on surface plasmon enhanced fluorescence where we achieved a 15-fold and 25-fold increase in their emission intensities, respectively. These peptide mediated hybrid systems were fabricated by horizontally tuning the localized surface plasmon resonance of gold nanoarrays and laterally tuning the distance of the fluorophore from the metal surface. This approach permits a comprehensive control both laterally (i.e., lithographically defined gold nanoarrays) and vertically (i.e., QD/CCP-metal distance) of the collectively behaving QD-NP and CP-NP assemblies by way of biomolecular recognition. The highest photoluminescence was achieved when the quantum dots and cationic conjugated polymers were self-assembled at a distance of 16.00 nm and 18.50 nm from the metal surface, respectively. Specifically, we demonstrated the spectral tuning of plasmon resonant metal nanoarrays and the self-assembly of protein-functionalized QDs/CCPs in a step-wise fashion with a concomitant incremental increase in separation from the metal surface through biotin-streptavidin spacer units. These well-controlled self-assembled patterned arrays provide highly organized architectures for improving optoelectronic devices and/or increasing the sensitivity of bio-chemical sensors.

Quantifying Nucleic Acid Ensembles with X-ray Scattering Interferometry.

PubMed

Shi, Xuesong; Bonilla, Steve; Herschlag, Daniel; Harbury, Pehr

2015-01-01

The conformational ensemble of a macromolecule is the complete description of the macromolecule's solution structures and can reveal important aspects of macromolecular folding, recognition, and function. However, most experimental approaches determine an average or predominant structure, or follow transitions between states that each can only be described by an average structure. Ensembles have been extremely difficult to experimentally characterize. We present the unique advantages and capabilities of a new biophysical technique, X-ray scattering interferometry (XSI), for probing and quantifying structural ensembles. XSI measures the interference of scattered waves from two heavy metal probes attached site specifically to a macromolecule. A Fourier transform of the interference pattern gives the fractional abundance of different probe separations directly representing the multiple conformation states populated by the macromolecule. These probe-probe distance distributions can then be used to define the structural ensemble of the macromolecule. XSI provides accurate, calibrated distance in a model-independent fashion with angstrom scale sensitivity in distances. XSI data can be compared in a straightforward manner to atomic coordinates determined experimentally or predicted by molecular dynamics simulations. We describe the conceptual framework for XSI and provide a detailed protocol for carrying out an XSI experiment. © 2015 Elsevier Inc. All rights reserved.

Statistical and Clustering Based Rules Extraction Approaches for Fuzzy Model to Estimate Academic Performance in Distance Education

ERIC Educational Resources Information Center

Yildiz, Osman; Bal, Abdullah; Gulsecen, Sevinc

2015-01-01

The demand for distance education has been increasing at a rapid pace all around the world. This, in turn, places a special importance on the need for the development of more distance education systems. However, there is an alarming rise in the number of distance education students that drop out of the system without asking for any help. The…

Learning object-to-class kernels for scene classification.

PubMed

Zhang, Lei; Zhen, Xiantong; Shao, Ling

2014-08-01

High-level image representations have drawn increasing attention in visual recognition, e.g., scene classification, since the invention of the object bank. The object bank represents an image as a response map of a large number of pretrained object detectors and has achieved superior performance for visual recognition. In this paper, based on the object bank representation, we propose the object-to-class (O2C) distances to model scene images. In particular, four variants of O2C distances are presented, and with the O2C distances, we can represent the images using the object bank by lower-dimensional but more discriminative spaces, called distance spaces, which are spanned by the O2C distances. Due to the explicit computation of O2C distances based on the object bank, the obtained representations can possess more semantic meanings. To combine the discriminant ability of the O2C distances to all scene classes, we further propose to kernalize the distance representation for the final classification. We have conducted extensive experiments on four benchmark data sets, UIUC-Sports, Scene-15, MIT Indoor, and Caltech-101, which demonstrate that the proposed approaches can significantly improve the original object bank approach and achieve the state-of-the-art performance.

Dynamic feet distance: A new functional assessment during treadmill locomotion in normal and thoracic spinal cord injured rats.

PubMed

Diogo, Camila Cardoso; Costa, Luís Maltez da; Pereira, José Eduardo; Filipe, Vítor; Couto, Pedro Alexandre; Magalhães, Luís G; Geuna, Stefano; Armada-da-Silva, Paulo A; Maurício, Ana Colette; Varejão, Artur Severo

2017-09-29

Of all the detrimental effects of spinal cord injury (SCI), one of the most devastating is the disruption of the ability to perform functional movement. Very little is known on the recovery of hindlimb joint kinematics after clinically-relevant contusive thoracic lesion in experimental animal models. A new functional assessment instrument, the dynamic feet distance (DFD) was used to describe the distance between the two feet throughout the gait cycle in normal and affected rodents. The purpose of this investigation was the evaluation and characterization of the DFD during treadmill locomotion in normal and T9 contusion injured rats, using three-dimensional (3D) instrumented gait analysis. Despite that normal and injured rats showed a similar pattern in the fifth metatarsal head joints distance excursion, we found a significantly wider distance between the feet during the entire gait cycle following spinal injury. This is the first study to quantify the distance between the two feet, throughout the gait cycle, and the biomechanical adjustments made between limbs in laboratory rodents after nervous system injury. Copyright © 2017 Elsevier B.V. All rights reserved.

Adding Value to Education for Sustainability in Africa with Inquiry-Based Approaches in Open and Distance Learning

ERIC Educational Resources Information Center

Pretorius, Rudi; Lombard, Andrea; Khotoo, Anisa

2016-01-01

Purpose: Inquiry-based approaches can potentially enrich sustainability learning in any educational context, more so in open and distance learning (ODL--perceived as theoretically inclined) and in regions of educational need (such as the Global South, of which Africa forms part). The purpose of this paper is to map the benefits and challenges of…

Designing Low Carbon Higher Education Systems: Environmental Impacts of Campus and Distance Learning Systems

ERIC Educational Resources Information Center

Roy, Robin; Potter, Stephen; Yarrow, Karen

2008-01-01

Purpose: This paper aims to summarise the methods and main findings of a study of the environmental impacts of providing higher education (HE) courses by campus-based and distance/open-learning methods. Design/methodology/approach: The approach takes the form of an environmental audit, with data from surveys of 20 UK courses--13 campus-based,…

Distance Education Examination Management in a Lowly Resourced North-Eastern Region of Zambia: a Phenomenological Approach

ERIC Educational Resources Information Center

Simui, Francis; Chibale, Henry; Namangala, Boniface

2017-01-01

This paper focuses on the management of distance education examination in a lowly resourced North-Eastern region of Zambia. The study applies Hermeneutic Phenomenology approach to generate and make sense of the data. It is the lived experiences of 2 invigilators and 66 students purposively selected that the study draws its insights from. Meaning…

Determination of Distance Distribution Functions by Singlet-Singlet Energy Transfer

PubMed Central

Cantor, Charles R.; Pechukas, Philip

1971-01-01

The efficiency of energy transfer between two chromophores can be used to define an apparent donor-acceptor distance, which in flexible systems will depend on the R0 of the chromophores. If efficiency is measured as a function of R0, it will be possible to determine the actual distribution function of donor-acceptor distances. Numerical procedures are described for extracting this information from experimental data. They should be most useful for distribution functions with mean values from 20-30 Å (2-3 nm). This technique should provide considerably more detailed information on end-to-end distributions of oligomers than has hitherto been available. It should also be useful for describing, in detail, conformational flexibility in other large molecules. PMID:16591942

The influence of parent's body mass index on peer selection: an experimental approach using virtual reality.

PubMed

Martarelli, Corinna S; Borter, Natalie; Bryjova, Jana; Mast, Fred W; Munsch, Simone

2015-11-30

Relatively little is known about the influence of psychosocial factors, such as familial role modeling and social network on the development and maintenance of childhood obesity. We investigated peer selection using an immersive virtual reality environment. In a virtual schoolyard, children were confronted with normal weight and overweight avatars either eating or playing. Fifty-seven children aged 7-13 participated. Interpersonal distance to the avatars, child's BMI, self-perception, eating behavior and parental BMI were assessed. Parental BMI was the strongest predictor for the children's minimal distance to the avatars. Specifically, a higher mothers' BMI was associated with greater interpersonal distance and children approached closer to overweight eating avatars. A higher father's BMI was associated with a lower interpersonal distance to the avatars. These children approached normal weight playing and overweight eating avatar peers closest. The importance of parental BMI for the child's social approach/avoidance behavior can be explained through social modeling mechanisms. Differential effects of paternal and maternal BMI might be due to gender specific beauty ideals. Interventions to promote social interaction with peer groups could foster weight stabilization or weight loss in children. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Heisenberg symmetry and collective modes of one dimensional unitary correlated fermions

NASA Astrophysics Data System (ADS)

Abhinav, Kumar; Chandrasekhar, B.; Vyas, Vivek M.; Panigrahi, Prasanta K.

2017-02-01

The correlated fermionic many-particle system, near infinite scattering length, reveals an underlying Heisenberg symmetry in one dimension, as compared to an SO (2 , 1) symmetry in two dimensions. This facilitates an exact map from the interacting to the non-interacting system, both with and without a harmonic trap, and explains the short-distance scaling behavior of the wave-function. Taking advantage of the phenomenological Calogero-Sutherland-type interaction, motivated by the density functional approach, we connect the ground-state energy shift, to many-body correlation effect. For the excited states, modes at integral values of the harmonic frequency ω are predicted in one dimension, in contrast to the breathing modes with frequency 2ω in two dimensions.

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

Conn, A. R.; Parker, Q. A.; Zucker, D. B.

In 'A Bayesian Approach to Locating the Red Giant Branch Tip Magnitude (Part I)', a new technique was introduced for obtaining distances using the tip of the red giant branch (TRGB) standard candle. Here we describe a useful complement to the technique with the potential to further reduce the uncertainty in our distance measurements by incorporating a matched-filter weighting scheme into the model likelihood calculations. In this scheme, stars are weighted according to their probability of being true object members. We then re-test our modified algorithm using random-realization artificial data to verify the validity of the generated posterior probability distributionsmore » (PPDs) and proceed to apply the algorithm to the satellite system of M31, culminating in a three-dimensional view of the system. Further to the distributions thus obtained, we apply a satellite-specific prior on the satellite distances to weight the resulting distance posterior distributions, based on the halo density profile. Thus in a single publication, using a single method, a comprehensive coverage of the distances to the companion galaxies of M31 is presented, encompassing the dwarf spheroidals Andromedas I-III, V, IX-XXVII, and XXX along with NGC 147, NGC 185, M33, and M31 itself. Of these, the distances to Andromedas XXIV-XXVII and Andromeda XXX have never before been derived using the TRGB. Object distances are determined from high-resolution tip magnitude posterior distributions generated using the Markov Chain Monte Carlo technique and associated sampling of these distributions to take into account uncertainties in foreground extinction and the absolute magnitude of the TRGB as well as photometric errors. The distance PPDs obtained for each object both with and without the aforementioned prior are made available to the reader in tabular form. The large object coverage takes advantage of the unprecedented size and photometric depth of the Pan-Andromeda Archaeological Survey. Finally, a preliminary investigation into the satellite density distribution within the halo is made using the obtained distance distributions. For simplicity, this investigation assumes a single power law for the density as a function of radius, with the slope of this power law examined for several subsets of the entire satellite sample.« less

The minimum distance approach to classification

NASA Technical Reports Server (NTRS)

Wacker, A. G.; Landgrebe, D. A.

1971-01-01

The work to advance the state-of-the-art of miminum distance classification is reportd. This is accomplished through a combination of theoretical and comprehensive experimental investigations based on multispectral scanner data. A survey of the literature for suitable distance measures was conducted and the results of this survey are presented. It is shown that minimum distance classification, using density estimators and Kullback-Leibler numbers as the distance measure, is equivalent to a form of maximum likelihood sample classification. It is also shown that for the parametric case, minimum distance classification is equivalent to nearest neighbor classification in the parameter space.

Verification of endocrinological functions at a short distance between parametric speakers and the human body.

PubMed

Lee, Soomin; Katsuura, Tetsuo; Shimomura, Yoshihiro

2011-01-01

In recent years, a new type of speaker called the parametric speaker has been used to generate highly directional sound, and these speakers are now commercially available. In our previous study, we verified that the burden of the parametric speaker was lower than that of the general speaker for endocrine functions. However, nothing has yet been demonstrated about the effects of the shorter distance than 2.6 m between parametric speakers and the human body. Therefore, we investigated the distance effect on endocrinological function and subjective evaluation. Nine male subjects participated in this study. They completed three consecutive sessions: a 20-min quiet period as a baseline, a 30-min mental task period with general speakers or parametric speakers, and a 20-min recovery period. We measured salivary cortisol and chromogranin A (CgA) concentrations. Furthermore, subjects took the Kwansei-gakuin Sleepiness Scale (KSS) test before and after the task and also a sound quality evaluation test after it. Four experiments, one with a speaker condition (general speaker and parametric speaker), the other with a distance condition (0.3 m and 1.0 m), were conducted, respectively, at the same time of day on separate days. We used three-way repeated measures ANOVA (speaker factor × distance factor × time factor) to examine the effects of the parametric speaker. We found that the endocrinological functions were not significantly different between the speaker condition and the distance condition. The results also showed that the physiological burdens increased with progress in time independent of the speaker condition and distance condition.

Phloem proteomics reveals new lipid-binding proteins with a putative role in lipid-mediated signaling

DOE PAGES

Barbaglia, Allison M.; Tamot, Banita; Greve, Veronica; ...

2016-04-28

Global climate changes inversely affect our ability to grow the food required for an increasing world population. To combat future crop loss due to abiotic stress, we need to understand the signals responsible for changes in plant development and the resulting adaptations, especially the signaling molecules traveling long-distance through the plant phloem. Using a proteomics approach, we had identified several putative lipid-binding proteins in the phloem exudates. Simultaneously, we identified several complex lipids as well as jasmonates. These findings prompted us to propose that phloem (phospho-) lipids could act as long-distance developmental signals in response to abiotic stress, and thatmore » they are released, sensed, and moved by phloem lipid-binding proteins (Benning et al., 2012). Indeed, the proteins we identified include lipases that could release a signaling lipid into the phloem, putative receptor components, and proteins that could mediate lipid-movement. To test this possible protein-based lipid-signaling pathway, three of the proteins, which could potentially act in a relay, are characterized here: (I) a putative GDSL-motif lipase (II) a PIG-P-like protein, with a possible receptor-like function; (III) and PLAFP (phloem lipid-associated family protein), a predicted lipid-binding protein of unknown function. Here we show that all three proteins bind lipids, in particular phosphatidic acid (PtdOH), which is known to participate in intracellular stress signaling. Genes encoding these proteins are expressed in the vasculature, a prerequisite for phloem transport. Cellular localization studies show that the proteins are not retained in the endoplasmic reticulum but surround the cell in a spotted pattern that has been previously observed with receptors and plasmodesmatal proteins. Abiotic signals that induce the production of PtdOH also regulate the expression of GDSL-lipase and PLAFP, albeit in opposite patterns. Our findings suggest that while all three proteins are indeed lipid-binding and act in the vasculature possibly in a function related to long-distance signaling, the three proteins do not act in the same but rather in distinct pathways. Furthermore, it points toward PLAFP as a prime candidate to investigate long-distance lipid signaling in the plant drought response.« less

Phloem proteomics reveals new lipid-binding proteins with a putative role in lipid-mediated signaling

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

Barbaglia, Allison M.; Tamot, Banita; Greve, Veronica

Global climate changes inversely affect our ability to grow the food required for an increasing world population. To combat future crop loss due to abiotic stress, we need to understand the signals responsible for changes in plant development and the resulting adaptations, especially the signaling molecules traveling long-distance through the plant phloem. Using a proteomics approach, we had identified several putative lipid-binding proteins in the phloem exudates. Simultaneously, we identified several complex lipids as well as jasmonates. These findings prompted us to propose that phloem (phospho-) lipids could act as long-distance developmental signals in response to abiotic stress, and thatmore » they are released, sensed, and moved by phloem lipid-binding proteins (Benning et al., 2012). Indeed, the proteins we identified include lipases that could release a signaling lipid into the phloem, putative receptor components, and proteins that could mediate lipid-movement. To test this possible protein-based lipid-signaling pathway, three of the proteins, which could potentially act in a relay, are characterized here: (I) a putative GDSL-motif lipase (II) a PIG-P-like protein, with a possible receptor-like function; (III) and PLAFP (phloem lipid-associated family protein), a predicted lipid-binding protein of unknown function. Here we show that all three proteins bind lipids, in particular phosphatidic acid (PtdOH), which is known to participate in intracellular stress signaling. Genes encoding these proteins are expressed in the vasculature, a prerequisite for phloem transport. Cellular localization studies show that the proteins are not retained in the endoplasmic reticulum but surround the cell in a spotted pattern that has been previously observed with receptors and plasmodesmatal proteins. Abiotic signals that induce the production of PtdOH also regulate the expression of GDSL-lipase and PLAFP, albeit in opposite patterns. Our findings suggest that while all three proteins are indeed lipid-binding and act in the vasculature possibly in a function related to long-distance signaling, the three proteins do not act in the same but rather in distinct pathways. Furthermore, it points toward PLAFP as a prime candidate to investigate long-distance lipid signaling in the plant drought response.« less

Determining the Minimal Clinically Important Difference for 6-Minute Walk Distance in Fibromyalgia.

PubMed

Kaleth, Anthony S; Slaven, James E; Ang, Dennis C

2016-10-01

The aim of this study was to estimate the minimal clinically important difference (MCID) for 6-min walk distance (6MWD) in patients with fibromyalgia. Data from a recently completed trial that included 187 patients who completed the 6-min walk test, Fibromyalgia Impact Questionnaire (FIQ), and Short-Form 36 (SF36) at 12 and 36 wks were used to examine longitudinal changes in 6MWD. An anchor-based approach that used linear regression analyses was used to determine the MCID for 6MWD, using the total FIQ score (FIQ-Total) and SF36-physical function domain as clinical anchors. The mean (SD) change in 6MWD from baseline to week 36 was 34.4 (65.2) m (P < 0.001). The anchor-based MCIDs for the 6MWD were 156 and 167 m for the FIQ and SF36-physical function domain, respectively. These MCIDs correspond with clinically meaningful improvements in FIQ (14% reduction) and SF36-physical function domain (10-point increase). The MCID for 6MWD in patients with fibromyalgia was 156 to 167 m. These findings provide the first evidence of the change in 6MWD that is perceived by patients to be clinically meaningful. Further research using other MCID calculation methods is needed to refine estimates of the MCID for 6MWD in patients with fibromyalgia.

Multivariate localization methods for ensemble Kalman filtering

NASA Astrophysics Data System (ADS)

Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

2015-05-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Distance Learning Courses on the Web: The Authoring Approach.

ERIC Educational Resources Information Center

Santos, Neide; Diaz, Alicia; Bibbo, Luis Mariano

This paper proposes a framework for supporting the authoring process of distance learning courses. An overview of distance learning courses and the World Wide Web is presented. The proposed framework is then described, including: (1) components of the framework--a hypermedia design methodology for authoring the course, links to related Web sites,…

Automated Categorization Scheme for Digital Libraries in Distance Learning: A Pattern Recognition Approach

ERIC Educational Resources Information Center

Gunal, Serkan

2008-01-01

Digital libraries play a crucial role in distance learning. Nowadays, they are one of the fundamental information sources for the students enrolled in this learning system. These libraries contain huge amount of instructional data (text, audio and video) offered by the distance learning program. Organization of the digital libraries is…

Distance Learning for Mobile Internet Users

ERIC Educational Resources Information Center

Necat, Beran

2007-01-01

This paper provides an overview on the current state of art in the field of Distance learning for mobile users. It mentions a large range of technologies, services and approaches that may be used to bring distance learning to mobile internet users. These technologies are supposed to considerably increase innovative e-learning solutions for the…