Personality Predicts Utilization of Mindfulness-Based Stress Reduction During and Post-Intervention in a Community Sample of Older Adults

PubMed Central

Barkan, Tessa; Gallegos, Autumn M.; Turiano, Nicholas A.; Duberstein, Paul R.; Moynihan, Jan A.

2016-01-01

Abstract Objectives: Mindfulness-based stress reduction (MBSR) is a promising intervention for older adults seeking to improve quality of life. More research is needed, however, to determine who is most willing to use the four techniques taught in the program (yoga, sitting meditation, informal meditation, and body scanning). This study evaluated the relationship between the Big Five personality dimensions (neuroticism, extraversion, openness to experience, conscientiousness, and agreeableness) and use of MBSR techniques both during the intervention and at a 6-month follow-up. The hypothesis was that those with higher levels of openness and agreeableness would be more likely to use the techniques. Methods: Participants were a community sample of 100 older adults who received an 8-week manualized MBSR intervention. Personality was assessed at baseline by using the 60-item NEO Five-Factor Inventory. Use of MBSR techniques was assessed through weekly practice logs during the intervention and a 6-month follow-up survey. Regression analyses were used to examine the association between each personality dimension and each indicator of MBSR use both during and after the intervention. Results: As hypothesized, openness and agreeableness predicted greater use of MBSR both during and after the intervention, while controlling for demographic differences in age, educational level, and sex. Openness was related to use of a variety of MBSR techniques during and after the intervention, while agreeableness was related to use of meditation techniques during the intervention. Mediation analysis suggested that personality explained postintervention MBSR use, both directly and by fostering initial uptake of MBSR during treatment. Conclusions: Personality dimensions accounted for individual differences in the use of MBSR techniques during and 6 months after the intervention. Future studies should consider how mental health practitioners would use these findings to target and tailor MBSR interventions to appeal to broader segments of the population. PMID:27031734

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

A Novel Hybrid Dimension Reduction Technique for Undersized High Dimensional Gene Expression Data Sets Using Information Complexity Criterion for Cancer Classification

PubMed Central

Pamukçu, Esra; Bozdogan, Hamparsum; Çalık, Sinan

2015-01-01

Gene expression data typically are large, complex, and highly noisy. Their dimension is high with several thousand genes (i.e., features) but with only a limited number of observations (i.e., samples). Although the classical principal component analysis (PCA) method is widely used as a first standard step in dimension reduction and in supervised and unsupervised classification, it suffers from several shortcomings in the case of data sets involving undersized samples, since the sample covariance matrix degenerates and becomes singular. In this paper we address these limitations within the context of probabilistic PCA (PPCA) by introducing and developing a new and novel approach using maximum entropy covariance matrix and its hybridized smoothed covariance estimators. To reduce the dimensionality of the data and to choose the number of probabilistic PCs (PPCs) to be retained, we further introduce and develop celebrated Akaike's information criterion (AIC), consistent Akaike's information criterion (CAIC), and the information theoretic measure of complexity (ICOMP) criterion of Bozdogan. Six publicly available undersized benchmark data sets were analyzed to show the utility, flexibility, and versatility of our approach with hybridized smoothed covariance matrix estimators, which do not degenerate to perform the PPCA to reduce the dimension and to carry out supervised classification of cancer groups in high dimensions. PMID:25838836

Application of Local Linear Embedding to Nonlinear Exploratory Latent Structure Analysis

ERIC Educational Resources Information Center

Wang, Haonan; Iyer, Hari

2007-01-01

In this paper we discuss the use of a recent dimension reduction technique called Locally Linear Embedding, introduced by Roweis and Saul, for performing an exploratory latent structure analysis. The coordinate variables from the locally linear embedding describing the manifold on which the data reside serve as the latent variable scores. We…

Active Subspaces for Wind Plant Surrogate Modeling

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

King, Ryan N; Quick, Julian; Dykes, Katherine L

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial inductionmore » factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.« less

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Flexible system model reduction and control system design based upon actuator and sensor influence functions

NASA Technical Reports Server (NTRS)

Yam, Yeung; Johnson, Timothy L.; Lang, Jeffrey H.

1987-01-01

A model reduction technique based on aggregation with respect to sensor and actuator influence functions rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the reduced-order plant model and the neglected plant model are derived. For the special case of collocated actuators and sensors, these expressions lead to the derivation of constraints on the controller gains that are, given the validity of the perturbation technique, sufficient to guarantee the stability of the closed-loop system. A case study demonstrates the derivation of stabilizing controllers based on the present technique. The use of control and observation synthesis in modifying the dimension of the reduced-order plant model is also discussed. A numerical example is provided for illustration.

Data Reduction Algorithm Using Nonnegative Matrix Factorization with Nonlinear Constraints

NASA Astrophysics Data System (ADS)

Sembiring, Pasukat

2017-12-01

Processing ofdata with very large dimensions has been a hot topic in recent decades. Various techniques have been proposed in order to execute the desired information or structure. Non- Negative Matrix Factorization (NMF) based on non-negatives data has become one of the popular methods for shrinking dimensions. The main strength of this method is non-negative object, the object model by a combination of some basic non-negative parts, so as to provide a physical interpretation of the object construction. The NMF is a dimension reduction method thathasbeen used widely for numerous applications including computer vision,text mining, pattern recognitions,and bioinformatics. Mathematical formulation for NMF did not appear as a convex optimization problem and various types of algorithms have been proposed to solve the problem. The Framework of Alternative Nonnegative Least Square(ANLS) are the coordinates of the block formulation approaches that have been proven reliable theoretically and empirically efficient. This paper proposes a new algorithm to solve NMF problem based on the framework of ANLS.This algorithm inherits the convergenceproperty of the ANLS framework to nonlinear constraints NMF formulations.

ODF Maxima Extraction in Spherical Harmonic Representation via Analytical Search Space Reduction

PubMed Central

Aganj, Iman; Lenglet, Christophe; Sapiro, Guillermo

2015-01-01

By revealing complex fiber structure through the orientation distribution function (ODF), q-ball imaging has recently become a popular reconstruction technique in diffusion-weighted MRI. In this paper, we propose an analytical dimension reduction approach to ODF maxima extraction. We show that by expressing the ODF, or any antipodally symmetric spherical function, in the common fourth order real and symmetric spherical harmonic basis, the maxima of the two-dimensional ODF lie on an analytically derived one-dimensional space, from which we can detect the ODF maxima. This method reduces the computational complexity of the maxima detection, without compromising the accuracy. We demonstrate the performance of our technique on both artificial and human brain data. PMID:20879302

Data-Driven Model Reduction and Transfer Operator Approximation

NASA Astrophysics Data System (ADS)

Klus, Stefan; Nüske, Feliks; Koltai, Péter; Wu, Hao; Kevrekidis, Ioannis; Schütte, Christof; Noé, Frank

2018-06-01

In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to approximate transfer operators and their eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out similarities and differences between methods developed independently by the dynamical systems, fluid dynamics, and molecular dynamics communities such as time-lagged independent component analysis, dynamic mode decomposition, and their respective generalizations. As a result, extensions and best practices developed for one particular method can be carried over to other related methods.

Black Hole Entropy from Bondi-Metzner-Sachs Symmetry at the Horizon.

PubMed

Carlip, S

2018-03-09

Near the horizon, the obvious symmetries of a black hole spacetime-the horizon-preserving diffeomorphisms-are enhanced to a larger symmetry group with a three-dimensional Bondi-Metzner-Sachs algebra. Using dimensional reduction and covariant phase space techniques, I investigate this augmented symmetry and show that it is strong enough to determine the black hole entropy in any dimension.

Information for patients undergoing treatment for toothwear with resin composite restorations placed at an increased occlusal vertical dimension.

PubMed

Burke, F J Trevor

2014-01-01

Toothwear is affecting increasing numbers of the population. In the past, treatment of patients whose teeth were affected by toothwear often involved the reduction of these teeth for crowns; a severe form of toothwear. Contemporary management of such cases is by the bonding of resin composite restorations to the worn and wearing surfaces, with these restorations being placed at an increased occlusal vertical dimension. The advantage of the technique is its minimal- or non-intervention nature and its high reported degree of patient satisfaction. There are, however, short-term disadvantages to the technique, such as the potential for lisping, pain from the teeth which will be subject to axial orthodontic tooth movement, and difficulty in chewing on the posterior teeth if these are discluded. It is therefore important, as with any treatment, that the advantages and disadvantages are fully explained to the patient. This paper therefore describes the clinical technique and presents a Patient Information Leaflet that the author has used for over five years. Patients should be advised regarding the disadvantages and advantages of any technique.

Effective dimension reduction for sparse functional data

PubMed Central

YAO, F.; LEI, E.; WU, Y.

2015-01-01

Summary We propose a method of effective dimension reduction for functional data, emphasizing the sparse design where one observes only a few noisy and irregular measurements for some or all of the subjects. The proposed method borrows strength across the entire sample and provides a way to characterize the effective dimension reduction space, via functional cumulative slicing. Our theoretical study reveals a bias-variance trade-off associated with the regularizing truncation and decaying structures of the predictor process and the effective dimension reduction space. A simulation study and an application illustrate the superior finite-sample performance of the method. PMID:26566293

Electromyographic evaluation of the 'vertical' dimension: the Learreta TMJ decompression test.

PubMed

Freire Matos, Marcelo; Durst, Andreas C; Freire Matos, Jane Luzia; Learreta, Jorge Alfonso

2011-10-01

The clinical observation of the incisors overbite is the most common form used to evaluate the occlusal vertical dimension (OVD); however, this technique offers poor information about the compression state of the TMJ. In order to obtain such information, it is necessary to evaluate the electrical activity of the elevator muscles using surface electromyography (EMG). In case of a compressive irritation of the joint receptors, the trigeminal nucleus returns an inhibitory motor response of the elevator muscles that can be measured. The Learreta's EMG decompression test is done by measuring the EMG response of the masticatory muscles at maximal occlusion in four different OVD positions in such a way that the reduction of the TMJ pressure, and subsequently, relief of the inhibitory motor response can be studied. The aim of this study is to illustrate this technique, its clinical use and its limitations.

Reducing Water/Hull Drag By Injecting Air Into Grooves

NASA Technical Reports Server (NTRS)

Reed, Jason C.; Bushnell, Dennis M.; Weinstein, Leonard M.

1991-01-01

Proposed technique for reduction of friction drag on hydrodynamic body involves use of grooves and combinations of surfactants to control motion of layer on surface of such body. Surface contains many rows of side-by-side, evenly spaced, longitudinal grooves. Dimensions of grooves and sharpnesses of tips in specific case depends on conditions of flow about vessel. Requires much less air than does microbubble-injection method.

Post-extraction mesio-distal gap reduction assessment by confocal laser scanning microscopy - a clinical 3-month follow-up study.

PubMed

García-Herraiz, Ariadna; Silvestre, Francisco Javier; Leiva-García, Rafael; Crespo-Abril, Fortunato; García-Antón, José

2017-05-01

The aim of this 3-month follow-up study is to quantify the reduction in the mesio-distal gap dimension (MDGD) that occurs after tooth extraction through image analysis of three-dimensional images obtained with the confocal laser scanning microscopy (CLSM) technique. Following tooth extraction, impressions of 79 patients 1 month and 72 patients 3 months after tooth extraction were obtained. Cast models were processed by CLSM, and MDGD changes between time points were measured. The mean mesio-distal gap reduction 1 month after tooth extraction was 343.4 μm and 3 months after tooth extraction was 672.3 μm. The daily mean gap reduction rate during the first term (between baseline and 1 month post-extraction measurements) was 10.3 μm/day and during the second term (between 1 and 3 months) was 5.4 μm/day. The mesio-distal gap reduction is higher during the first month following the extraction and continues in time, but to a lesser extent. When the inter-dental contacts were absent, the mesio-distal gap reduction is lower. When a molar tooth is extracted or the distal tooth to the edentulous space does not occlude with an antagonist, the mesio-distal gap reduction is larger. The consideration of mesio-distal gap dimension changes can help improve dental treatment planning. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Kadomtsev{endash}Petviashvili equation as a source of integrable model equations

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

Maccari, A.

1996-12-01

A new integrable and nonlinear partial differential equation (PDE) in 2+1 dimensions is obtained, by an asymptotically exact reduction method based on Fourier expansion and spatiotemporal rescaling, from the Kadomtsev{endash}Petviashvili equation. The integrability property is explicitly demonstrated, by exhibiting the corresponding Lax pair, that is obtained by applying the reduction technique to the Lax pair of the Kadomtsev{endash}Petviashvili equation. This model equation is likely to be of applicative relevance, because it may be considered a consistent approximation of a large class of nonlinear evolution PDEs. {copyright} {ital 1996 American Institute of Physics.}

Neural Network Machine Learning and Dimension Reduction for Data Visualization

NASA Technical Reports Server (NTRS)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Riblets for aircraft skin-friction reduction

NASA Technical Reports Server (NTRS)

Walsh, Michael J.

1986-01-01

Energy conservation and aerodynamic efficiency are the driving forces behind research into methods to reduce turbulent skin friction drag on aircraft fuselages. Fuselage skin friction reductions as small as 10 percent provide the potential for a 250 million dollar per year fuel savings for the commercial airline fleet. One passive drag reduction concept which is relatively simple to implement and retrofit is that of longitudinally grooved surfaces aligned with the stream velocity. These grooves (riblets) have heights and spacings on the order of the turbulent wall streak and burst dimensions. The riblet performance (8 percent net drag reduction thus far), sensitivity to operational/application considerations such as yaw and Reynolds number variation, an alternative fabrication technique, results of extensive parametric experiments for geometrical optimization, and flight test applications are summarized.

A Review on Dimension Reduction

PubMed Central

Ma, Yanyuan; Zhu, Liping

2013-01-01

Summary Summarizing the effect of many covariates through a few linear combinations is an effective way of reducing covariate dimension and is the backbone of (sufficient) dimension reduction. Because the replacement of high-dimensional covariates by low-dimensional linear combinations is performed with a minimum assumption on the specific regression form, it enjoys attractive advantages as well as encounters unique challenges in comparison with the variable selection approach. We review the current literature of dimension reduction with an emphasis on the two most popular models, where the dimension reduction affects the conditional distribution and the conditional mean, respectively. We discuss various estimation and inference procedures in different levels of detail, with the intention of focusing on their underneath idea instead of technicalities. We also discuss some unsolved problems in this area for potential future research. PMID:23794782

On the dimension of complex responses in nonlinear structural vibrations

NASA Astrophysics Data System (ADS)

Wiebe, R.; Spottswood, S. M.

2016-07-01

The ability to accurately model engineering systems under extreme dynamic loads would prove a major breakthrough in many aspects of aerospace, mechanical, and civil engineering. Extreme loads frequently induce both nonlinearities and coupling which increase the complexity of the response and the computational cost of finite element models. Dimension reduction has recently gained traction and promises the ability to distill dynamic responses down to a minimal dimension without sacrificing accuracy. In this context, the dimensionality of a response is related to the number of modes needed in a reduced order model to accurately simulate the response. Thus, an important step is characterizing the dimensionality of complex nonlinear responses of structures. In this work, the dimensionality of the nonlinear response of a post-buckled beam is investigated. Significant detail is dedicated to carefully introducing the experiment, the verification of a finite element model, and the dimensionality estimation algorithm as it is hoped that this system may help serve as a benchmark test case. It is shown that with minor modifications, the method of false nearest neighbors can quantitatively distinguish between the response dimension of various snap-through, non-snap-through, random, and deterministic loads. The state-space dimension of the nonlinear system in question increased from 2-to-10 as the system response moved from simple, low-level harmonic to chaotic snap-through. Beyond the problem studied herein, the techniques developed will serve as a prescriptive guide in developing fast and accurate dimensionally reduced models of nonlinear systems, and eventually as a tool for adaptive dimension-reduction in numerical modeling. The results are especially relevant in the aerospace industry for the design of thin structures such as beams, panels, and shells, which are all capable of spatio-temporally complex dynamic responses that are difficult and computationally expensive to model.

NeatMap--non-clustering heat map alternatives in R.

PubMed

Rajaram, Satwik; Oono, Yoshi

2010-01-22

The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the detection of hidden structures and relations in the data. However, it is hampered by its use of cluster analysis which does not always respect the intrinsic relations in the data, often requiring non-standardized reordering of rows/columns to be performed post-clustering. This sometimes leads to uninformative and/or misleading conclusions. Often it is more informative to use dimension-reduction algorithms (such as Principal Component Analysis and Multi-Dimensional Scaling) which respect the topology inherent in the data. Yet, despite their proven utility in the analysis of biological data, they are not as widely used. This is at least partially due to the lack of user-friendly visualization methods with the visceral impact of the heat map. NeatMap is an R package designed to meet this need. NeatMap offers a variety of novel plots (in 2 and 3 dimensions) to be used in conjunction with these dimension-reduction techniques. Like the heat map, but unlike traditional displays of such results, it allows the entire dataset to be displayed while visualizing relations between elements. It also allows superimposition of cluster analysis results for mutual validation. NeatMap is shown to be more informative than the traditional heat map with the help of two well-known microarray datasets. NeatMap thus preserves many of the strengths of the clustered heat map while addressing some of its deficiencies. It is hoped that NeatMap will spur the adoption of non-clustering dimension-reduction algorithms.

Realization of State-Space Models for Wave Propagation Simulations

DTIC Science & Technology

2012-01-01

reduction techniques can be applied to reduce the dimension of the model further if warranted. INFRASONIC PROPAGATION MODEL Infrasound is sound below 20...capable of scatter- ing and blocking the propagation. This is because the infrasound wavelengths are near the scales of topographic features. These...and Development Center (ERDC) Big Black Test Site (BBTS) and an infrasound -sensing array at the ERDC Waterways Experiment Station (WES). Both are

Neuroanatomical profiles of alexithymia dimensions and subtypes.

PubMed

Goerlich-Dobre, Katharina Sophia; Votinov, Mikhail; Habel, Ute; Pripfl, Juergen; Lamm, Claus

2015-10-01

Alexithymia, a major risk factor for a range of psychiatric and neurological disorders, has been recognized to comprise two dimensions, a cognitive dimension (difficulties identifying, analyzing, and verbalizing feelings) and an affective one (difficulties emotionalizing and fantasizing). Based on these dimensions, the existence of four distinct alexithymia subtypes has been proposed, but never empirically tested. In this study, 125 participants were assigned to four groups corresponding to the proposed alexithymia subtypes: Type I (impairment on both dimensions), Type II (impairment on the cognitive, but not the affective dimension), Type III (impairment on the affective, but not the cognitive dimension), and Lexithymics (no impairment on either dimension). By means of voxel-based morphometry, associations of the alexithymia dimensions and subtypes with gray and white matter volumes were analyzed. Type I and Type II alexithymia were characterized by gray matter volume reductions in the left amygdala and the thalamus. The cognitive dimension was further linked to volume reductions in the right amygdala, left posterior insula, precuneus, caudate, hippocampus, and parahippocampus. Type III alexithymia was marked by volume reduction in the MCC only, and the affective dimension was further characterized by larger sgACC volume. Moreover, individuals with the intermediate alexithymia Types II and III showed gray matter volume reductions in distinct regions, and had larger corpus callosum volumes compared to Lexithymics. These results substantiate the notion of a differential impact of the cognitive and affective alexithymia dimensions on brain morphology and provide evidence for separable neuroanatomical representations of the different alexithymia subtypes. © 2015 Wiley Periodicals, Inc.

Content Abstract Classification Using Naive Bayes

NASA Astrophysics Data System (ADS)

Latif, Syukriyanto; Suwardoyo, Untung; Aldrin Wihelmus Sanadi, Edwin

2018-03-01

This study aims to classify abstract content based on the use of the highest number of words in an abstract content of the English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10% -90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.

Estimated correlation matrices and portfolio optimization

NASA Astrophysics Data System (ADS)

Pafka, Szilárd; Kondor, Imre

2004-11-01

Correlations of returns on various assets play a central role in financial theory and also in many practical applications. From a theoretical point of view, the main interest lies in the proper description of the structure and dynamics of correlations, whereas for the practitioner the emphasis is on the ability of the models to provide adequate inputs for the numerous portfolio and risk management procedures used in the financial industry. The theory of portfolios, initiated by Markowitz, has suffered from the “curse of dimensions” from the very outset. Over the past decades a large number of different techniques have been developed to tackle this problem and reduce the effective dimension of large bank portfolios, but the efficiency and reliability of these procedures are extremely hard to assess or compare. In this paper, we propose a model (simulation)-based approach which can be used for the systematical testing of all these dimensional reduction techniques. To illustrate the usefulness of our framework, we develop several toy models that display some of the main characteristic features of empirical correlations and generate artificial time series from them. Then, we regard these time series as empirical data and reconstruct the corresponding correlation matrices which will inevitably contain a certain amount of noise, due to the finiteness of the time series. Next, we apply several correlation matrix estimators and dimension reduction techniques introduced in the literature and/or applied in practice. As in our artificial world the only source of error is the finite length of the time series and, in addition, the “true” model, hence also the “true” correlation matrix, are precisely known, therefore in sharp contrast with empirical studies, we can precisely compare the performance of the various noise reduction techniques. One of our recurrent observations is that the recently introduced filtering technique based on random matrix theory performs consistently well in all the investigated cases. Based on this experience, we believe that our simulation-based approach can also be useful for the systematic investigation of several related problems of current interest in finance.

Biatrial reduction plasty with reef imbricate technique as an adjunct to maze procedure for permanent atrial fibrillation associated with giant left atria.

PubMed

Wang, William; Guo, L Ray; Martland, Anne Marie; Feng, Xiao-Dong; Ma, Jie; Feng, Xi Qing

2010-04-01

Success of the modified maze procedure after valvular operation with giant atria and permanent atrial fibrillation (AF) remains suboptimal. We report an aggressive approach for these patients utilizing biatrial reduction plasty with a reef imbricate suture technique concomitantly with valvular and maze procedure for AF. From January 1999 to December 2006, 122 consecutive Chinese patients with permanent AF and biatrial enlargement who required mitral valve+/-tricuspid valve (TV) surgery underwent aggressive left atrial reduction combined with radiofrequency bipolar full maze procedure. Left atrial dimensions were measured by TTE or TEE. There were 71 women (58.1%) and 51 men (41.9%) and their mean age was 45+/-9.5 years. Mean duration of AF was 48.4+/-21.4 months. All patients underwent left atrial reduction plasty with reef imbricate suture technique and full maze procedure. Their preoperative left atria measured 64+/-12 mm in the enlarged left atria (ELA) group and 86+/-17 mm in the giant left atria (GLA). Mitral valve replacement (MVR) combined with TV repair was performed in 102 patients (83%) while 21 patients underwent MVRs combined with aortic valve replacements (17%). Sixty-six (54%) patients required additional procedures and 61 (50%) of the patients also underwent left atrial appendage clot evacuation. Postoperative left atrial size was reduced to 49+/-8 mm (ELA) and 51+/-11 mm (GLA), respectively (P<0.05). Ninety-three of 122 (76%) patients were restored in normal sinus rhythm after one year clinical follow-up. Aggressive biatrial reduction plasty combined with full maze procedure is an effective treatment for patients with permanent AF undergoing concomitant valvular surgery. Further studies utilizing the reef imbricate suture technique for atrial reduction need to subsequently be evaluated.

Model and controller reduction of large-scale structures based on projection methods

NASA Astrophysics Data System (ADS)

Gildin, Eduardo

The design of low-order controllers for high-order plants is a challenging problem theoretically as well as from a computational point of view. Frequently, robust controller design techniques result in high-order controllers. It is then interesting to achieve reduced-order models and controllers while maintaining robustness properties. Controller designed for large structures based on models obtained by finite element techniques yield large state-space dimensions. In this case, problems related to storage, accuracy and computational speed may arise. Thus, model reduction methods capable of addressing controller reduction problems are of primary importance to allow the practical applicability of advanced controller design methods for high-order systems. A challenging large-scale control problem that has emerged recently is the protection of civil structures, such as high-rise buildings and long-span bridges, from dynamic loadings such as earthquakes, high wind, heavy traffic, and deliberate attacks. Even though significant effort has been spent in the application of control theory to the design of civil structures in order increase their safety and reliability, several challenging issues are open problems for real-time implementation. This dissertation addresses with the development of methodologies for controller reduction for real-time implementation in seismic protection of civil structures using projection methods. Three classes of schemes are analyzed for model and controller reduction: nodal truncation, singular value decomposition methods and Krylov-based methods. A family of benchmark problems for structural control are used as a framework for a comparative study of model and controller reduction techniques. It is shown that classical model and controller reduction techniques, such as balanced truncation, modal truncation and moment matching by Krylov techniques, yield reduced-order controllers that do not guarantee stability of the closed-loop system, that is, the reduced-order controller implemented with the full-order plant. A controller reduction approach is proposed such that to guarantee closed-loop stability. It is based on the concept of dissipativity (or positivity) of linear dynamical systems. Utilizing passivity preserving model reduction together with dissipative-LQG controllers, effective low-order optimal controllers are obtained. Results are shown through simulations.

Neo-phalloplasty with re-innervated latissimus dorsi free flap: a functional study of a novel technique.

PubMed

Ranno, R; Veselý, J; Hýza, P; Stupka, I; Justan, I; Dvorák, Z; Monni, N; Novák, P; Ranno, S

2007-01-01

Twenty two patients with gender dysphoria underwent neo-phalloplasties using a novel technique. Latissimus dorsi musculocutaneus re-innervated free flap was used to allow voluntary rigidity of the neo-penis. From the first 22 patients, 18 have obtained motoric function of reconstructed penis; the "paradox erection" was obtained. 14 patients came for examination after a follow-up period of mean 26.4 months. We evaluated the motility and shape changes of neo-phallus measuring its different size and dimension during relax and muscle contraction. The range of neo-phallus length in relaxed position was between 7 and 17 cm (mean 12.2 cm), its circumference in the same position had a range between 13 and 20 cm (mean 13.7 cm). All patients were able to contract the muscle with an average length reduction of 3.08 cm and an average circumference enlargement of 4 cm. In this study, the dimensions and motility were quantified demonstrating the neo-phallus function and size changes during sexual intercourse.

Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE.

PubMed

Jamieson, Andrew R; Giger, Maryellen L; Drukker, Karen; Li, Hui; Yuan, Yading; Bhooshan, Neha

2010-01-01

In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enhanced magnetic resonance imaging with 356 cases, and full-field digital mammography with 245 cases. Two methods for nonlinear DR were explored: Laplacian eigenmaps [M. Belkin and P. Niyogi, "Laplacian eigenmaps for dimensionality reduction and data representation," Neural Comput. 15, 1373-1396 (2003)] and t-distributed stochastic neighbor embedding (t-SNE) [L. van der Maaten and G. Hinton, "Visualizing data using t-SNE," J. Mach. Learn. Res. 9, 2579-2605 (2008)]. These methods attempt to map originally high dimensional feature spaces to more human interpretable lower dimensional spaces while preserving both local and global information. The properties of these methods as applied to breast computer-aided diagnosis (CADx) were evaluated in the context of malignancy classification performance as well as in the visual inspection of the sparseness within the two-dimensional and three-dimensional mappings. Classification performance was estimated by using the reduced dimension mapped feature output as input into both linear and nonlinear classifiers: Markov chain Monte Carlo based Bayesian artificial neural network (MCMC-BANN) and linear discriminant analysis. The new techniques were compared to previously developed breast CADx methodologies, including automatic relevance determination and linear stepwise (LSW) feature selection, as well as a linear DR method based on principal component analysis. Using ROC analysis and 0.632+bootstrap validation, 95% empirical confidence intervals were computed for the each classifier's AUC performance. In the large U.S. data set, sample high performance results include, AUC0.632+ = 0.88 with 95% empirical bootstrap interval [0.787;0.895] for 13 ARD selected features and AUC0.632+ = 0.87 with interval [0.817;0.906] for four LSW selected features compared to 4D t-SNE mapping (from the original 81D feature space) giving AUC0.632+ = 0.90 with interval [0.847;0.919], all using the MCMC-BANN. Preliminary results appear to indicate capability for the new methods to match or exceed classification performance of current advanced breast lesion CADx algorithms. While not appropriate as a complete replacement of feature selection in CADx problems, DR techniques offer a complementary approach, which can aid elucidation of additional properties associated with the data. Specifically, the new techniques were shown to possess the added benefit of delivering sparse lower dimensional representations for visual interpretation, revealing intricate data structure of the feature space.

Visual pattern image sequence coding

NASA Technical Reports Server (NTRS)

Silsbee, Peter; Bovik, Alan C.; Chen, Dapang

1990-01-01

The visual pattern image coding (VPIC) configurable digital image-coding process is capable of coding with visual fidelity comparable to the best available techniques, at compressions which (at 30-40:1) exceed all other technologies. These capabilities are associated with unprecedented coding efficiencies; coding and decoding operations are entirely linear with respect to image size and entail a complexity that is 1-2 orders of magnitude faster than any previous high-compression technique. The visual pattern image sequence coding to which attention is presently given exploits all the advantages of the static VPIC in the reduction of information from an additional, temporal dimension, to achieve unprecedented image sequence coding performance.

Image compression/decompression based on mathematical transform, reduction/expansion, and image sharpening

DOEpatents

Fu, Chi-Yung; Petrich, Loren I.

1997-01-01

An image represented in a first image array of pixels is first decimated in two dimensions before being compressed by a predefined compression algorithm such as JPEG. Another possible predefined compression algorithm can involve a wavelet technique. The compressed, reduced image is then transmitted over the limited bandwidth transmission medium, and the transmitted image is decompressed using an algorithm which is an inverse of the predefined compression algorithm (such as reverse JPEG). The decompressed, reduced image is then interpolated back to its original array size. Edges (contours) in the image are then sharpened to enhance the perceptual quality of the reconstructed image. Specific sharpening techniques are described.

redNumerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods.

PubMed

Köppl, Tobias; Santin, Gabriele; Haasdonk, Bernard; Helmig, Rainer

2018-05-06

In this work, we consider two kinds of model reduction techniques to simulate blood flow through the largest systemic arteries, where a stenosis is located in a peripheral artery i.e. in an artery that is located far away from the heart. For our simulations we place the stenosis in one of the tibial arteries belonging to the right lower leg (right post tibial artery). The model reduction techniques that are used are on the one hand dimensionally reduced models (1-D and 0-D models, the so-called mixed-dimension model) and on the other hand surrogate models produced by kernel methods. Both methods are combined in such a way that the mixed-dimension models yield training data for the surrogate model, where the surrogate model is parametrised by the degree of narrowing of the peripheral stenosis. By means of a well-trained surrogate model, we show that simulation data can be reproduced with a satisfactory accuracy and that parameter optimisation or state estimation problems can be solved in a very efficient way. Furthermore it is demonstrated that a surrogate model enables us to present after a very short simulation time the impact of a varying degree of stenosis on blood flow, obtaining a speedup of several orders over the full model. This article is protected by copyright. All rights reserved.

Detection and tracking of gas plumes in LWIR hyperspectral video sequence data

NASA Astrophysics Data System (ADS)

Gerhart, Torin; Sunu, Justin; Lieu, Lauren; Merkurjev, Ekaterina; Chang, Jen-Mei; Gilles, Jérôme; Bertozzi, Andrea L.

2013-05-01

Automated detection of chemical plumes presents a segmentation challenge. The segmentation problem for gas plumes is difficult due to the diffusive nature of the cloud. The advantage of considering hyperspectral images in the gas plume detection problem over the conventional RGB imagery is the presence of non-visual data, allowing for a richer representation of information. In this paper we present an effective method of visualizing hyperspectral video sequences containing chemical plumes and investigate the effectiveness of segmentation techniques on these post-processed videos. Our approach uses a combination of dimension reduction and histogram equalization to prepare the hyperspectral videos for segmentation. First, Principal Components Analysis (PCA) is used to reduce the dimension of the entire video sequence. This is done by projecting each pixel onto the first few Principal Components resulting in a type of spectral filter. Next, a Midway method for histogram equalization is used. These methods redistribute the intensity values in order to reduce icker between frames. This properly prepares these high-dimensional video sequences for more traditional segmentation techniques. We compare the ability of various clustering techniques to properly segment the chemical plume. These include K-means, spectral clustering, and the Ginzburg-Landau functional.

Sufficient Dimension Reduction for Longitudinally Measured Predictors

PubMed Central

Pfeiffer, Ruth M.; Forzani, Liliana; Bura, Efstathia

2013-01-01

We propose a method to combine several predictors (markers) that are measured repeatedly over time into a composite marker score without assuming a model and only requiring a mild condition on the predictor distribution. Assuming that the first and second moments of the predictors can be decomposed into a time and a marker component via a Kronecker product structure, that accommodates the longitudinal nature of the predictors, we develop first moment sufficient dimension reduction techniques to replace the original markers with linear transformations that contain sufficient information for the regression of the predictors on the outcome. These linear combinations can then be combined into a score that has better predictive performance than the score built under a general model that ignores the longitudinal structure of the data. Our methods can be applied to either continuous or categorical outcome measures. In simulations we focus on binary outcomes and show that our method outperforms existing alternatives using the AUC, the area under the receiver-operator characteristics (ROC) curve, as a summary measure of the discriminatory ability of a single continuous diagnostic marker for binary disease outcomes. PMID:22161635

A regularized approach for geodesic-based semisupervised multimanifold learning.

PubMed

Fan, Mingyu; Zhang, Xiaoqin; Lin, Zhouchen; Zhang, Zhongfei; Bao, Hujun

2014-05-01

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.

Environmental barriers and social participation in individuals with spinal cord injury.

PubMed

Tsai, I-Hsuan; Graves, Daniel E; Chan, Wenyaw; Darkoh, Charles; Lee, Meei-Shyuan; Pompeii, Lisa A

2017-02-01

The study aimed to examine the relationship between environmental barriers and social participation among individuals with spinal cord injury (SCI). Individuals admitted to regional centers of the Model Spinal Cord Injury System in the United States due to traumatic SCI were interviewed and included in the National Spinal Cord Injury Database. This cross-sectional study applied a secondary analysis with a mixed effect model on the data from 3,162 individuals who received interviews from 2000 through 2005. Five dimensions of environmental barriers were estimated using the short form of the Craig Hospital Inventory of Environmental Factors-Short Form (CHIEF-SF). Social participation was measured with the short form of the Craig Handicap Assessment and Reporting Technique-Short Form (CHART-SF) and their employment status. Subscales of environmental barriers were negatively associated with the social participation measures. Each 1 point increase in CHIEF-SF total score (indicated greater environmental barriers) was associated with a 0.82 point reduction in CHART-SF total score (95% CI: -1.07, -0.57) (decreased social participation) and 4% reduction in the odds of being employed. Among the 5 CHIEF-SF dimensions, assistance barriers exhibited the strongest negative association with CHART-SF social participation score when compared to other dimensions, while work/school dimension demonstrated the weakest association with CHART-SF. Environmental barriers are negatively associated with social participation in the SCI population. Working toward eliminating environmental barriers, especially assistance/service barriers, may help enhance social participation for people with SCI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Cluster Correspondence Analysis.

PubMed

van de Velden, M; D'Enza, A Iodice; Palumbo, F

2017-03-01

A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

Integrand-level reduction of loop amplitudes by computational algebraic geometry methods

NASA Astrophysics Data System (ADS)

Zhang, Yang

2012-09-01

We present an algorithm for the integrand-level reduction of multi-loop amplitudes of renormalizable field theories, based on computational algebraic geometry. This algorithm uses (1) the Gröbner basis method to determine the basis for integrand-level reduction, (2) the primary decomposition of an ideal to classify all inequivalent solutions of unitarity cuts. The resulting basis and cut solutions can be used to reconstruct the integrand from unitarity cuts, via polynomial fitting techniques. The basis determination part of the algorithm has been implemented in the Mathematica package, BasisDet. The primary decomposition part can be readily carried out by algebraic geometry softwares, with the output of the package BasisDet. The algorithm works in both D = 4 and D = 4 - 2 ɛ dimensions, and we present some two and three-loop examples of applications of this algorithm.

Evaluation of macrozone dimensions by ultrasound and EBSD techniques

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

Moreau, Andre, E-mail: Andre.Moreau@cnrc-nrc.gc.ca; Toubal, Lotfi; Ecole de technologie superieure, 1100, rue Notre-Dame Ouest, Montreal, QC, Canada H3C 1K3

2013-01-15

Titanium alloys are known to have texture heterogeneities, i.e. regions much larger than the grain dimensions, where the local orientation distribution of the grains differs from one region to the next. The electron backscattering diffraction (EBSD) technique is the method of choice to characterize these macro regions, which are called macrozones. Qualitatively, the images obtained by EBSD show that these macrozones may be larger or smaller, elongated or equiaxed. However, often no well-defined boundaries are observed between the macrozones and it is very hard to obtain objective and quantitative estimates of the macrozone dimensions from these data. In the presentmore » work, we present a novel, non-destructive ultrasonic technique that provides objective and quantitative characteristic dimensions of the macrozones. The obtained dimensions are based on the spatial autocorrelation function of fluctuations in the sound velocity. Thus, a pragmatic definition of macrozone dimensions naturally arises from the ultrasonic measurement. This paper has three objectives: 1) to disclose the novel, non-destructive ultrasonic technique to measure macrozone dimensions, 2) to propose a quantitative and objective definition of macrozone dimensions adapted to and arising from the ultrasonic measurement, and which is also applicable to the orientation data obtained by EBSD, and 3) to compare the macrozone dimensions obtained using the two techniques on two samples of the near-alpha titanium alloy IMI834. In addition, it was observed that macrozones may present a semi-periodical arrangement. - Highlights: Black-Right-Pointing-Pointer Discloses a novel, ultrasonic NDT technique to measure macrozone dimensions Black-Right-Pointing-Pointer Proposes a quantitative and objective definition of macrozone dimensions Black-Right-Pointing-Pointer Compares macrozone dimensions obtained using EBSD and ultrasonics on 2 Ti samples Black-Right-Pointing-Pointer Observes that macrozones may have a semi-periodical arrangement.« less

Image compression/decompression based on mathematical transform, reduction/expansion, and image sharpening

DOEpatents

Fu, C.Y.; Petrich, L.I.

1997-12-30

An image represented in a first image array of pixels is first decimated in two dimensions before being compressed by a predefined compression algorithm such as JPEG. Another possible predefined compression algorithm can involve a wavelet technique. The compressed, reduced image is then transmitted over the limited bandwidth transmission medium, and the transmitted image is decompressed using an algorithm which is an inverse of the predefined compression algorithm (such as reverse JPEG). The decompressed, reduced image is then interpolated back to its original array size. Edges (contours) in the image are then sharpened to enhance the perceptual quality of the reconstructed image. Specific sharpening techniques are described. 22 figs.

Scaling of energy absorbing composite plates

NASA Technical Reports Server (NTRS)

Jackson, Karen; Morton, John; Traffanstedt, Catherine; Boitnott, Richard

1992-01-01

The energy absorption response and crushing characteristics of geometrically scaled graphite-Kevlar epoxy composite plates were investigated. Three different trigger mechanisms including chamfer, notch, and steeple geometries were incorporated into the plate specimens to initiate crushing. Sustained crushing was achieved with a simple test fixture which provided lateral support to prevent global buckling. Values of specific sustained crushing stress (SSCS) were obtained which were comparable to values reported for tube specimens from previously published data. Two sizes of hybrid plates were fabricated; a baseline or model plate, and a full-scale plate with in-plane dimensions scaled by a factor of two. The thickness dimension of the full-scale plates was increased using two different techniques; the ply-level method in which each ply orientation in the baseline laminate stacking sequence is doubled, and the sublaminate technique in which the baseline laminate stacking sequence is repeated as a group. Results indicated that the SSCS is independent of trigger mechanism geometry. However, a reduction in the SSCS of 10-25 percent was observed for the full-scale plates as compared with the baseline specimens, indicating a scaling effect in the crushing response.

Scaling of energy absorbing composite plates

NASA Technical Reports Server (NTRS)

Jackson, Karen; Lavoie, J. Andre; Morton, John

1994-01-01

The energy absorption response and crushing characteristics of geometrically scaled graphite-Kevlar epoxy composite plates were investigated. Two different trigger mechanisms including notch, and steeple geometries were incorporated into the plate specimens to initiate crushing. Sustained crushing was achieved with a new test fixture which provided lateral support to prevent global buckling. Values of specific sustained crushing stress (SSCS) were obtained which were lower than values reported for tube specimens from previously published data. Two sizes of hybrid plates were fabricated; a baseline or model plate, and a full-scale plate with inplane dimensions scaled by a factor of two. The thickness dimension of the full-scale plates was increased using two different techniques: the ply-level method in which each ply orientation in the baseline laminate stacking sequence is doubled, and the sublaminate technique in which the baseline laminate stacking sequence is repeated as a group. Results indicated that the SSCS has a small dependence on trigger mechanism geometry. However, a reduction in the SSCS of 10-25% was observed for the full-scale plates as compared with the baseline specimens, indicating a scaling effect in the crushing response.

Scaling of energy absorbing composite plates

NASA Astrophysics Data System (ADS)

Jackson, Karen; Morton, John; Traffanstedt, Catherine; Boitnott, Richard

The energy absorption response and crushing characteristics of geometrically scaled graphite-Kevlar epoxy composite plates were investigated. Three different trigger mechanisms including chamfer, notch, and steeple geometries were incorporated into the plate specimens to initiate crushing. Sustained crushing was achieved with a simple test fixture which provided lateral support to prevent global buckling. Values of specific sustained crushing stress (SSCS) were obtained which were comparable to values reported for tube specimens from previously published data. Two sizes of hybrid plates were fabricated; a baseline or model plate, and a full-scale plate with in-plane dimensions scaled by a factor of two. The thickness dimension of the full-scale plates was increased using two different techniques; the ply-level method in which each ply orientation in the baseline laminate stacking sequence is doubled, and the sublaminate technique in which the baseline laminate stacking sequence is repeated as a group. Results indicated that the SSCS is independent of trigger mechanism geometry. However, a reduction in the SSCS of 10-25 percent was observed for the full-scale plates as compared with the baseline specimens, indicating a scaling effect in the crushing response.

A strategy for analysis of (molecular) equilibrium simulations: Configuration space density estimation, clustering, and visualization

NASA Astrophysics Data System (ADS)

Hamprecht, Fred A.; Peter, Christine; Daura, Xavier; Thiel, Walter; van Gunsteren, Wilfred F.

2001-02-01

We propose an approach for summarizing the output of long simulations of complex systems, affording a rapid overview and interpretation. First, multidimensional scaling techniques are used in conjunction with dimension reduction methods to obtain a low-dimensional representation of the configuration space explored by the system. A nonparametric estimate of the density of states in this subspace is then obtained using kernel methods. The free energy surface is calculated from that density, and the configurations produced in the simulation are then clustered according to the topography of that surface, such that all configurations belonging to one local free energy minimum form one class. This topographical cluster analysis is performed using basin spanning trees which we introduce as subgraphs of Delaunay triangulations. Free energy surfaces obtained in dimensions lower than four can be visualized directly using iso-contours and -surfaces. Basin spanning trees also afford a glimpse of higher-dimensional topographies. The procedure is illustrated using molecular dynamics simulations on the reversible folding of peptide analoga. Finally, we emphasize the intimate relation of density estimation techniques to modern enhanced sampling algorithms.

Innovative application of virtual display technique in virtual museum

NASA Astrophysics Data System (ADS)

Zhang, Jiankang

2017-09-01

Virtual museum refers to display and simulate the functions of real museum on the Internet in the form of 3 Dimensions virtual reality by applying interactive programs. Based on Virtual Reality Modeling Language, virtual museum building and its effective interaction with the offline museum lie in making full use of 3 Dimensions panorama technique, virtual reality technique and augmented reality technique, and innovatively taking advantages of dynamic environment modeling technique, real-time 3 Dimensions graphics generating technique, system integration technique and other key virtual reality techniques to make sure the overall design of virtual museum.3 Dimensions panorama technique, also known as panoramic photography or virtual reality, is a technique based on static images of the reality. Virtual reality technique is a kind of computer simulation system which can create and experience the interactive 3 Dimensions dynamic visual world. Augmented reality, also known as mixed reality, is a technique which simulates and mixes the information (visual, sound, taste, touch, etc.) that is difficult for human to experience in reality. These technologies make virtual museum come true. It will not only bring better experience and convenience to the public, but also be conducive to improve the influence and cultural functions of the real museum.

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

NASA Astrophysics Data System (ADS)

Cui, Tiangang; Marzouk, Youssef; Willcox, Karen

2016-06-01

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and t-SNE

PubMed Central

Jamieson, Andrew R.; Giger, Maryellen L.; Drukker, Karen; Li, Hui; Yuan, Yading; Bhooshan, Neha

2010-01-01

Purpose: In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enhanced magnetic resonance imaging with 356 cases, and full-field digital mammography with 245 cases. Two methods for nonlinear DR were explored: Laplacian eigenmaps [M. Belkin and P. Niyogi, “Laplacian eigenmaps for dimensionality reduction and data representation,” Neural Comput. 15, 1373–1396 (2003)] and t-distributed stochastic neighbor embedding (t-SNE) [L. van der Maaten and G. Hinton, “Visualizing data using t-SNE,” J. Mach. Learn. Res. 9, 2579–2605 (2008)]. Methods: These methods attempt to map originally high dimensional feature spaces to more human interpretable lower dimensional spaces while preserving both local and global information. The properties of these methods as applied to breast computer-aided diagnosis (CADx) were evaluated in the context of malignancy classification performance as well as in the visual inspection of the sparseness within the two-dimensional and three-dimensional mappings. Classification performance was estimated by using the reduced dimension mapped feature output as input into both linear and nonlinear classifiers: Markov chain Monte Carlo based Bayesian artificial neural network (MCMC-BANN) and linear discriminant analysis. The new techniques were compared to previously developed breast CADx methodologies, including automatic relevance determination and linear stepwise (LSW) feature selection, as well as a linear DR method based on principal component analysis. Using ROC analysis and 0.632+bootstrap validation, 95% empirical confidence intervals were computed for the each classifier’s AUC performance. Results: In the large U.S. data set, sample high performance results include, AUC0.632+=0.88 with 95% empirical bootstrap interval [0.787;0.895] for 13 ARD selected features and AUC0.632+=0.87 with interval [0.817;0.906] for four LSW selected features compared to 4D t-SNE mapping (from the original 81D feature space) giving AUC0.632+=0.90 with interval [0.847;0.919], all using the MCMC-BANN. Conclusions: Preliminary results appear to indicate capability for the new methods to match or exceed classification performance of current advanced breast lesion CADx algorithms. While not appropriate as a complete replacement of feature selection in CADx problems, DR techniques offer a complementary approach, which can aid elucidation of additional properties associated with the data. Specifically, the new techniques were shown to possess the added benefit of delivering sparse lower dimensional representations for visual interpretation, revealing intricate data structure of the feature space. PMID:20175497

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

Evaluation and reduction of magnetic resonance imaging artifacts induced by distinct plates for osseous fixation: an in vitro study @ 3T.

PubMed

Rendenbach, Carsten; Schoellchen, Maximilian; Bueschel, Julie; Gauer, Tobias; Sedlacik, Jan; Kutzner, Daniel; Vallittu, Pekka K; Heiland, Max; Smeets, Ralf; Fiehler, Jens; Siemonsen, Susanne

2018-05-02

To analyze Magnetic Resonance Imaging (MRI) artifact induced at 3 Tesla by bioresorbable, titanium and glass fiber reinforced composite (GFRC) plates for osseous reconstruction. Fixation plates including bioresorbable polymers (Inion CPS, Inion Oy, Tampere, Finland; Rapidsorb, DePuy Synthes, Umkirch, Germany; Resorb X, Gebrueder KLS Martin GmbH, Tuttlingen, Germany), Glass fiber reinforced composite (Skulle Implants Oy, Turku, Finland) and titanium plates of varying thickness and design (DePuy Synthes, Umkirch, Germany) were embedded in agarose gel and a 3T MRI was performed using a standard protocol for head and neck imaging including T1w and T2w sequences. Additionally, different artifact reducing sequence techniques (slice encoding for metal artifact reduction (SEMAC) & ultrashort echotime (UTE)) were used and their impact on the extent of artifacts evaluated for each material. All titanium plates induced significantly more artefacts than resorbable plates in T1w and T2w sequences. Glass fiber-reinforced composites induced the least artefacts in both sequences. The total extent of artefacts increased with plate thickness and height. Plate thickness had no influence on the percentage of overestimation in all three dimensions. Titanium induced artefacts were significantly reduced by both artifact reducing sequence techniques. Polylactide, glass fiber-reinforced composite and magnesium plates produce less susceptibility artefacts in MRI compared to titanium, while the dimensions of titanium plates directly influence artifact extension. SEMAC and UTE significantly reduce metal artefacts at the expense of image resolution.

Application of CRAFT in two-dimensional NMR data processing.

PubMed

Krishnamurthy, Krish; Sefler, Andrea M; Russell, David J

2017-03-01

Two-dimensional (2D) data are typically truncated in both dimensions, but invariably and severely so in the indirect dimension. These truncated FIDs and/or interferograms are extensively zero filled, and Fourier transformation of such zero-filled data is always preceded by a rapidly decaying apodization function. Hence, the frequency line width in the spectrum (at least parallel to the evolution dimension) is almost always dominated by the apodization function. Such apodization-driven line broadening in the indirect (t 1 ) dimension leads to the lack of clear resolution of cross peaks in the 2D spectrum. Time-domain analysis (i.e. extraction of frequency, amplitudes, line width, and phase parameters directly from the FID, in this case via Bayesian modeling into a tabular format) of NMR data is another approach for spectral resonance characterization and quantification. The recently published complete reduction to amplitude frequency table (CRAFT) technique converts the raw FID data (i.e. time-domain data) into a table of frequencies, amplitudes, decay rate constants, and phases. CRAFT analyses of time-domain data require minimal or no apodization prior to extraction of the four parameters. We used the CRAFT processing approach for the decimation of the interferograms and compared the results from a variety of 2D spectra against conventional processing with and without linear prediction. The results show that use of the CRAFT technique to decimate the t 1 interferograms yields much narrower spectral line width of the resonances, circumventing the loss of resolution due to apodization. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Light-cone reduction vs. TsT transformations: a fluid dynamics perspective

NASA Astrophysics Data System (ADS)

Dutta, Suvankar; Krishna, Hare

2018-05-01

We compute constitutive relations for a charged (2+1) dimensional Schrödinger fluid up to first order in derivative expansion, using holographic techniques. Starting with a locally boosted, asymptotically AdS, 4 + 1 dimensional charged black brane geometry, we uplift that to ten dimensions and perform TsT transformations to obtain an effective five dimensional local black brane solution with asymptotically Schrödinger isometries. By suitably implementing the holographic techniques, we compute the constitutive relations for the effective fluid living on the boundary of this space-time and extract first order transport coefficients from these relations. Schrödinger fluid can also be obtained by reducing a charged relativistic conformal fluid over light-cone. It turns out that both the approaches result the same system at the end. Fluid obtained by light-cone reduction satisfies a restricted class of thermodynamics. Here, we see that the charged fluid obtained holographically also belongs to the same restricted class.

Reduced-order modeling for hyperthermia control.

PubMed

Potocki, J K; Tharp, H S

1992-12-01

This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS). These thermal state space models are reduced using the balanced realization technique, and an order reduction criterion is tabulated. Results show that a drastic reduction in model dimension can be achieved using the balanced realization. The reduced-order model is then used to design a reduced-order optimal servomechanism controller for a two-scan input, two thermocouple output tissue model. In addition, a full-order optimal servomechanism controller is designed for comparison and validation purposes. These two controllers are applied to a variety of perturbed tissue thermal models to test the robust nature of the reduced-order controller. A comparison of the two controllers validates the use of open-loop balanced reduced-order models in the design of MIMO hyperthermia controllers.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Prediction With Dimension Reduction of Multiple Molecular Data Sources for Patient Survival.

PubMed

Kaplan, Adam; Lock, Eric F

2017-01-01

Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA). However, the application of PCA is not straightforward for multisource data, wherein multiple sources of 'omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE), an extension of PCA for multisource data, for prediction of differing response types. We conduct illustrative simulations to illustrate the practical advantages and interpretability of our approach. As an application example, we consider predicting survival for patients with glioblastoma multiforme from 3 data sources measuring messenger RNA expression, microRNA expression, and DNA methylation. We also introduce a method to estimate JIVE scores for new samples that were not used in the initial dimension reduction and study its theoretical properties; this method is implemented in the R package R.JIVE on CRAN, in the function jive.predict.

Shark-skin surfaces for fluid-drag reduction in turbulent flow: a review.

PubMed

Dean, Brian; Bhushan, Bharat

2010-10-28

The skin of fast-swimming sharks exhibits riblet structures aligned in the direction of flow that are known to reduce skin friction drag in the turbulent-flow regime. Structures have been fabricated for study and application that replicate and improve upon the natural shape of the shark-skin riblets, providing a maximum drag reduction of nearly 10 per cent. Mechanisms of fluid drag in turbulent flow and riblet-drag reduction theories from experiment and simulation are discussed. A review of riblet-performance studies is given, and optimal riblet geometries are defined. A survey of studies experimenting with riblet-topped shark-scale replicas is also given. A method for selecting optimal riblet dimensions based on fluid-flow characteristics is detailed, and current manufacturing techniques are outlined. Due to the presence of small amounts of mucus on the skin of a shark, it is expected that the localized application of hydrophobic materials will alter the flow field around the riblets in some way beneficial to the goals of increased drag reduction.

An estimating equation approach to dimension reduction for longitudinal data

PubMed Central

Xu, Kelin; Guo, Wensheng; Xiong, Momiao; Zhu, Liping; Jin, Li

2016-01-01

Sufficient dimension reduction has been extensively explored in the context of independent and identically distributed data. In this article we generalize sufficient dimension reduction to longitudinal data and propose an estimating equation approach to estimating the central mean subspace. The proposed method accounts for the covariance structure within each subject and improves estimation efficiency when the covariance structure is correctly specified. Even if the covariance structure is misspecified, our estimator remains consistent. In addition, our method relaxes distributional assumptions on the covariates and is doubly robust. To determine the structural dimension of the central mean subspace, we propose a Bayesian-type information criterion. We show that the estimated structural dimension is consistent and that the estimated basis directions are root-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$n$\\end{document} consistent, asymptotically normal and locally efficient. Simulations and an analysis of the Framingham Heart Study data confirm the effectiveness of our approach. PMID:27017956

New Trends in Television Consumption.

ERIC Educational Resources Information Center

Richeri, Giuseppe

A phenomenon which tends to transform the function and methods of traditional television consumption is the gradual reduction of its "mass" dimensions, which tend to disappear for an increasing share of the audience. This reduction of the mass dimension ranges from fragmentation of the audience to its segmentation, and, in the most…

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

PubMed

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Sequential updating of multimodal hydrogeologic parameter fields using localization and clustering techniques

NASA Astrophysics Data System (ADS)

Sun, Alexander Y.; Morris, Alan P.; Mohanty, Sitakanta

2009-07-01

Estimated parameter distributions in groundwater models may contain significant uncertainties because of data insufficiency. Therefore, adaptive uncertainty reduction strategies are needed to continuously improve model accuracy by fusing new observations. In recent years, various ensemble Kalman filters have been introduced as viable tools for updating high-dimensional model parameters. However, their usefulness is largely limited by the inherent assumption of Gaussian error statistics. Hydraulic conductivity distributions in alluvial aquifers, for example, are usually non-Gaussian as a result of complex depositional and diagenetic processes. In this study, we combine an ensemble Kalman filter with grid-based localization and a Gaussian mixture model (GMM) clustering techniques for updating high-dimensional, multimodal parameter distributions via dynamic data assimilation. We introduce innovative strategies (e.g., block updating and dimension reduction) to effectively reduce the computational costs associated with these modified ensemble Kalman filter schemes. The developed data assimilation schemes are demonstrated numerically for identifying the multimodal heterogeneous hydraulic conductivity distributions in a binary facies alluvial aquifer. Our results show that localization and GMM clustering are very promising techniques for assimilating high-dimensional, multimodal parameter distributions, and they outperform the corresponding global ensemble Kalman filter analysis scheme in all scenarios considered.

Application of CRAFT (complete reduction to amplitude frequency table) in nonuniformly sampled (NUS) 2D NMR data processing.

PubMed

Krishnamurthy, Krish; Hari, Natarajan

2017-09-15

The recently published CRAFT (complete reduction to amplitude frequency table) technique converts the raw FID data (i.e., time domain data) into a table of frequencies, amplitudes, decay rate constants, and phases. It offers an alternate approach to decimate time-domain data, with minimal preprocessing step. It has been shown that application of CRAFT technique to process the t 1 dimension of the 2D data significantly improved the detectable resolution by its ability to analyze without the use of ubiquitous apodization of extensively zero-filled data. It was noted earlier that CRAFT did not resolve sinusoids that were not already resolvable in time-domain (i.e., t 1 max dependent resolution). We present a combined NUS-IST-CRAFT approach wherein the NUS acquisition technique (sparse sampling technique) increases the intrinsic resolution in time-domain (by increasing t 1 max), IST fills the gap in the sparse sampling, and CRAFT processing extracts the information without loss due to any severe apodization. NUS and CRAFT are thus complementary techniques to improve intrinsic and usable resolution. We show that significant improvement can be achieved with this combination over conventional NUS-IST processing. With reasonable sensitivity, the models can be extended to significantly higher t 1 max to generate an indirect-DEPT spectrum that rivals the direct observe counterpart. Copyright © 2017 John Wiley & Sons, Ltd.

Kaluza-Klein cosmology from five-dimensional Lovelock-Cartan theory

NASA Astrophysics Data System (ADS)

Castillo-Felisola, Oscar; Corral, Cristóbal; del Pino, Simón; Ramírez, Francisca

2016-12-01

We study the Kaluza-Klein dimensional reduction of the Lovelock-Cartan theory in five-dimensional spacetime, with a compact dimension of S1 topology. We find cosmological solutions of the Friedmann-Robertson-Walker class in the reduced spacetime. The torsion and the fields arising from the dimensional reduction induce a nonvanishing energy-momentum tensor in four dimensions. We find solutions describing expanding, contracting, and bouncing universes. The model shows a dynamical compactification of the extra dimension in some regions of the parameter space.

Categorical dimensions of human odor descriptor space revealed by non-negative matrix factorization

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

Chennubhotla, Chakra; Castro, Jason

2013-01-01

In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain un- clear. Here, we use non-negative matrix factorization (NMF) - a dimensionality reduction technique - to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor di- mensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner.more » We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures.« less

Dimension reduction method for SPH equations

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

Tartakovsky, Alexandre M.; Scheibe, Timothy D.

2011-08-26

Smoothed Particle Hydrodynamics model of a complex multiscale processe often results in a system of ODEs with an enormous number of unknowns. Furthermore, a time integration of the SPH equations usually requires time steps that are smaller than the observation time by many orders of magnitude. A direct solution of these ODEs can be extremely expensive. Here we propose a novel dimension reduction method that gives an approximate solution of the SPH ODEs and provides an accurate prediction of the average behavior of the modeled system. The method consists of two main elements. First, effective equationss for evolution of averagemore » variables (e.g. average velocity, concentration and mass of a mineral precipitate) are obtained by averaging the SPH ODEs over the entire computational domain. These effective ODEs contain non-local terms in the form of volume integrals of functions of the SPH variables. Second, a computational closure is used to close the system of the effective equations. The computational closure is achieved via short bursts of the SPH model. The dimension reduction model is used to simulate flow and transport with mixing controlled reactions and mineral precipitation. An SPH model is used model transport at the porescale. Good agreement between direct solutions of the SPH equations and solutions obtained with the dimension reduction method for different boundary conditions confirms the accuracy and computational efficiency of the dimension reduction model. The method significantly accelerates SPH simulations, while providing accurate approximation of the solution and accurate prediction of the average behavior of the system.« less

Support vector machine and principal component analysis for microarray data classification

NASA Astrophysics Data System (ADS)

Astuti, Widi; Adiwijaya

2018-03-01

Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

A Space-Time Signal Decomposition Algorithm for Downlink MIMO DS-CDMA Receivers

NASA Astrophysics Data System (ADS)

Wang, Yung-Yi; Fang, Wen-Hsien; Chen, Jiunn-Tsair

We propose a dimension reduction algorithm for the receiver of the downlink of direct-sequence code-division multiple access (DS-CDMA) systems in which both the transmitters and the receivers employ antenna arrays of multiple elements. To estimate the high order channel parameters, we develop a layered architecture using dimension-reduced parameter estimation algorithms to estimate the frequency-selective multipath channels. In the proposed architecture, to exploit the space-time geometric characteristics of multipath channels, spatial beamformers and constrained (or unconstrained) temporal filters are adopted for clustered-multipath grouping and path isolation. In conjunction with the multiple access interference (MAI) suppression techniques, the proposed architecture jointly estimates the direction of arrivals, propagation delays, and fading amplitudes of the downlink fading multipaths. With the outputs of the proposed architecture, the signals of interest can then be naturally detected by using path-wise maximum ratio combining. Compared to the traditional techniques, such as the Joint-Angle-and-Delay-Estimation (JADE) algorithm for DOA-delay joint estimation and the space-time minimum mean square error (ST-MMSE) algorithm for signal detection, computer simulations show that the proposed algorithm substantially mitigate the computational complexity at the expense of only slight performance degradation.

Coil Compression for Accelerated Imaging with Cartesian Sampling

PubMed Central

Zhang, Tao; Pauly, John M.; Vasanawala, Shreyas S.; Lustig, Michael

2012-01-01

MRI using receiver arrays with many coil elements can provide high signal-to-noise ratio and increase parallel imaging acceleration. At the same time, the growing number of elements results in larger datasets and more computation in the reconstruction. This is of particular concern in 3D acquisitions and in iterative reconstructions. Coil compression algorithms are effective in mitigating this problem by compressing data from many channels into fewer virtual coils. In Cartesian sampling there often are fully sampled k-space dimensions. In this work, a new coil compression technique for Cartesian sampling is presented that exploits the spatially varying coil sensitivities in these non-subsampled dimensions for better compression and computation reduction. Instead of directly compressing in k-space, coil compression is performed separately for each spatial location along the fully-sampled directions, followed by an additional alignment process that guarantees the smoothness of the virtual coil sensitivities. This important step provides compatibility with autocalibrating parallel imaging techniques. Its performance is not susceptible to artifacts caused by a tight imaging fieldof-view. High quality compression of in-vivo 3D data from a 32 channel pediatric coil into 6 virtual coils is demonstrated. PMID:22488589

Nanoporous Anodic Alumina Surface Modification by Electrostatic, Covalent, and Immune Complexation Binding Investigated by Capillary Filling.

PubMed

Eckstein, Chris; Acosta, Laura K; Pol, Laura; Xifré-Pérez, Elisabet; Pallares, Josep; Ferré-Borrull, Josep; Marsal, Lluis F

2018-03-28

The fluid imbibition-coupled laser interferometry (FICLI) technique has been applied to detect and quantify surface changes and pore dimension variations in nanoporous anodic alumina (NAA) structures. FICLI is a noninvasive optical technique that permits the determination of the NAA average pore radius with high accuracy. In this work, the technique is applied after each step of different surface modification paths of the NAA pores: (i) electrostatic immobilization of bovine serum albumin (BSA), (ii) covalent attachment of streptavidin via (3-aminipropyl)-triethoxysilane and glutaraldehyde grafting, and (iii) immune complexation. Results show that BSA attachment can be detected as a reduction in estimated radius from FICLI with high accuracy and reproducibility. In the case of the covalent attachment of streptavidin, FICLI is able to recognize a multilayer formation of the silane and the protein. For immune complexation, the technique is able to detect different antibody-antigen bindings and distinguish different dynamics among different immune species.

Stochastic dynamic analysis of marine risers considering Gaussian system uncertainties

NASA Astrophysics Data System (ADS)

Ni, Pinghe; Li, Jun; Hao, Hong; Xia, Yong

2018-03-01

This paper performs the stochastic dynamic response analysis of marine risers with material uncertainties, i.e. in the mass density and elastic modulus, by using Stochastic Finite Element Method (SFEM) and model reduction technique. These uncertainties are assumed having Gaussian distributions. The random mass density and elastic modulus are represented by using the Karhunen-Loève (KL) expansion. The Polynomial Chaos (PC) expansion is adopted to represent the vibration response because the covariance of the output is unknown. Model reduction based on the Iterated Improved Reduced System (IIRS) technique is applied to eliminate the PC coefficients of the slave degrees of freedom to reduce the dimension of the stochastic system. Monte Carlo Simulation (MCS) is conducted to obtain the reference response statistics. Two numerical examples are studied in this paper. The response statistics from the proposed approach are compared with those from MCS. It is noted that the computational time is significantly reduced while the accuracy is kept. The results demonstrate the efficiency of the proposed approach for stochastic dynamic response analysis of marine risers.

Dimension Reduction of Multivariable Optical Emission Spectrometer Datasets for Industrial Plasma Processes

PubMed Central

Yang, Jie; McArdle, Conor; Daniels, Stephen

2014-01-01

A new data dimension-reduction method, called Internal Information Redundancy Reduction (IIRR), is proposed for application to Optical Emission Spectroscopy (OES) datasets obtained from industrial plasma processes. For example in a semiconductor manufacturing environment, real-time spectral emission data is potentially very useful for inferring information about critical process parameters such as wafer etch rates, however, the relationship between the spectral sensor data gathered over the duration of an etching process step and the target process output parameters is complex. OES sensor data has high dimensionality (fine wavelength resolution is required in spectral emission measurements in order to capture data on all chemical species involved in plasma reactions) and full spectrum samples are taken at frequent time points, so that dynamic process changes can be captured. To maximise the utility of the gathered dataset, it is essential that information redundancy is minimised, but with the important requirement that the resulting reduced dataset remains in a form that is amenable to direct interpretation of the physical process. To meet this requirement and to achieve a high reduction in dimension with little information loss, the IIRR method proposed in this paper operates directly in the original variable space, identifying peak wavelength emissions and the correlative relationships between them. A new statistic, Mean Determination Ratio (MDR), is proposed to quantify the information loss after dimension reduction and the effectiveness of IIRR is demonstrated using an actual semiconductor manufacturing dataset. As an example of the application of IIRR in process monitoring/control, we also show how etch rates can be accurately predicted from IIRR dimension-reduced spectral data. PMID:24451453

Economic Growth and Poverty Reduction: Measurement and Policy Issues. OECD Development Centre Working Paper No. 246

ERIC Educational Resources Information Center

Klasen, Stephan

2005-01-01

The aim of this Working Paper is to broaden the debate on "pro-poor growth". An exclusive focus on the income dimension of poverty has neglected the non-income dimensions. After an examination of prominent views on the linkages between economic growth, inequality, and poverty reduction this paper discusses the proper definition and…

Minimization of nanosatellite low frequency magnetic fields.

PubMed

Belyayev, S M; Dudkin, F L

2016-03-01

Small weight and dimensions of the micro- and nanosatellites constrain researchers to place electromagnetic sensors on short booms or on the satellite body. Therefore the electromagnetic cleanliness of such satellites becomes a central question. This paper describes the theoretical base and practical techniques for determining the parameters of DC and very low frequency magnetic interference sources. One of such sources is satellite magnetization, the reduction of which improves the accuracy and stability of the attitude control system. We present design solutions for magnetically clean spacecraft, testing equipment, and technology for magnetic moment measurements, which are more convenient, efficient, and accurate than the conventional ones.

Simplex-stochastic collocation method with improved scalability

NASA Astrophysics Data System (ADS)

Edeling, W. N.; Dwight, R. P.; Cinnella, P.

2016-04-01

The Simplex-Stochastic Collocation (SSC) method is a robust tool used to propagate uncertain input distributions through a computer code. However, it becomes prohibitively expensive for problems with dimensions higher than 5. The main purpose of this paper is to identify bottlenecks, and to improve upon this bad scalability. In order to do so, we propose an alternative interpolation stencil technique based upon the Set-Covering problem, and we integrate the SSC method in the High-Dimensional Model-Reduction framework. In addition, we address the issue of ill-conditioned sample matrices, and we present an analytical map to facilitate uniformly-distributed simplex sampling.

Integrand reduction for two-loop scattering amplitudes through multivariate polynomial division

NASA Astrophysics Data System (ADS)

Mastrolia, Pierpaolo; Mirabella, Edoardo; Ossola, Giovanni; Peraro, Tiziano

2013-04-01

We describe the application of a novel approach for the reduction of scattering amplitudes, based on multivariate polynomial division, which we have recently presented. This technique yields the complete integrand decomposition for arbitrary amplitudes, regardless of the number of loops. It allows for the determination of the residue at any multiparticle cut, whose knowledge is a mandatory prerequisite for applying the integrand-reduction procedure. By using the division modulo Gröbner basis, we can derive a simple integrand recurrence relation that generates the multiparticle pole decomposition for integrands of arbitrary multiloop amplitudes. We apply the new reduction algorithm to the two-loop planar and nonplanar diagrams contributing to the five-point scattering amplitudes in N=4 super Yang-Mills and N=8 supergravity in four dimensions, whose numerator functions contain up to rank-two terms in the integration momenta. We determine all polynomial residues parametrizing the cuts of the corresponding topologies and subtopologies. We obtain the integral basis for the decomposition of each diagram from the polynomial form of the residues. Our approach is well suited for a seminumerical implementation, and its general mathematical properties provide an effective algorithm for the generalization of the integrand-reduction method to all orders in perturbation theory.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k -NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k -NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

Modeling Complex Chemical Systems: Problems and Solutions

NASA Astrophysics Data System (ADS)

van Dijk, Jan

2016-09-01

Non-equilibrium plasmas in complex gas mixtures are at the heart of numerous contemporary technologies. They typically contain dozens to hundreds of species, involved in hundreds to thousands of reactions. Chemists and physicists have always been interested in what are now called chemical reduction techniques (CRT's). The idea of such CRT's is that they reduce the number of species that need to be considered explicitly without compromising the validity of the model. This is usually achieved on the basis of an analysis of the reaction time scales of the system under study, which identifies species that are in partial equilibrium after a given time span. The first such CRT that has been widely used in plasma physics was developed in the 1960's and resulted in the concept of effective ionization and recombination rates. It was later generalized to systems in which multiple levels are effected by transport. In recent years there has been a renewed interest in tools for chemical reduction and reaction pathway analysis. An example of the latter is the PumpKin tool. Another trend is that techniques that have previously been developed in other fields of science are adapted as to be able to handle the plasma state of matter. Examples are the Intrinsic Low Dimension Manifold (ILDM) method and its derivatives, which originate from combustion engineering, and the general-purpose Principle Component Analysis (PCA) technique. In this contribution we will provide an overview of the most common reduction techniques, then critically assess the pros and cons of the methods that have gained most popularity in recent years. Examples will be provided for plasmas in argon and carbon dioxide.

Assessment of Primary Site Response in Children With High-Risk Neuroblastoma: An International Multicenter Study

PubMed Central

McHugh, Kieran; Naranjo, Arlene; Van Ryn, Collin; Kirby, Chaim; Brock, Penelope; Lyons, Karen A.; States, Lisa J.; Rojas, Yesenia; Miller, Alexandra; Volchenboum, Sam L.; Simon, Thorsten; Krug, Barbara; Sarnacki, Sabine; Valteau-Couanet, Dominique; von Schweinitz, Dietrich; Kammer, Birgit; Granata, Claudio; Pio, Luca; Park, Julie R.; Nuchtern, Jed

2016-01-01

Purpose The International Neuroblastoma Response Criteria (INRC) require serial measurements of primary tumors in three dimensions, whereas the Response Evaluation Criteria in Solid Tumors (RECIST) require measurement in one dimension. This study was conducted to identify the preferred method of primary tumor response assessment for use in revised INRC. Patients and Methods Patients younger than 20 years with high-risk neuroblastoma were eligible if they were diagnosed between 2000 and 2012 and if three primary tumor measurements (antero-posterior, width, cranio-caudal) were recorded at least twice before resection. Responses were defined as ≥ 30% reduction in longest dimension as per RECIST, ≥ 50% reduction in volume as per INRC, or ≥ 65% reduction in volume. Results Three-year event-free survival for all patients (N = 229) was 44% and overall survival was 58%. The sensitivity of both volume response measures (ability to detect responses in patients who survived) exceeded the sensitivity of the single dimension measure, but the specificity of all response measures (ability to identify lack of response in patients who later died) was low. In multivariable analyses, none of the response measures studied was predictive of outcome, and none was predictive of the extent of resection. Conclusion None of the methods of primary tumor response assessment was predictive of outcome. Measurement of three dimensions followed by calculation of resultant volume is more complex than measurement of a single dimension. Primary tumor response in children with high-risk neuroblastoma should therefore be evaluated in accordance with RECIST criteria, using the single longest dimension. PMID:26755515

Dynamic response of RC beams strengthened with near surface mounted Carbon-FRP rods subjected to damage

NASA Astrophysics Data System (ADS)

Capozucca, R.; Blasi, M. G.; Corina, V.

2015-07-01

Near surface mounted (NSM) technique with fiber reinforced polymer (FRP) is becoming a common method in the strengthening of concrete beams. The availability of NSM FRP technique depends on many factors linked to materials and geometry - dimensions of the rods used, type of FRP material employed, rods’ surface configuration, groove size - and to adhesion between concrete and FRP rods. In this paper detection of damage is investigated measuring the natural frequency values of beam in the case of free-free ends. Damage was due both to reduction of adhesion between concrete and carbon-FRP rectangular and circular rods and cracking of concrete under static bending tests on beams. Comparison between experimental and theoretical frequency values evaluating frequency changes due to damage permits to monitor actual behaviour of RC beams strengthened by NSM CFRP rods.

Solid immersion terahertz imaging with sub-wavelength resolution

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Schadko, Aleksander O.; Lebedev, Sergey P.; Tolstoguzov, Viktor L.; Kurlov, Vladimir N.; Reshetov, Igor V.; Spektor, Igor E.; Skorobogatiy, Maksim; Yurchenko, Stanislav O.; Zaytsev, Kirill I.

2017-05-01

We have developed a method of solid immersion THz imaging—a non-contact technique employing the THz beam focused into evanescent-field volume and allowing strong reduction in the dimensions of THz caustic. We have combined numerical simulations and experimental studies to demonstrate a sub-wavelength 0.35λ0-resolution of the solid immersion THz imaging system compared to 0.85λ0-resolution of a standard imaging system, employing only an aspherical singlet. We have discussed the prospective of using the developed technique in various branches of THz science and technology, namely, for THz measurements of solid-state materials featuring sub-wavelength variations of physical properties, for highly accurate mapping of healthy and pathological tissues in THz medical diagnosis, for detection of sub-wavelength defects in THz non-destructive sensing, and for enhancement of THz nonlinear effects.

Drug particle size influence on enteric beads produced by a droplet extrusion/precipitation method.

PubMed

Cerdeira, A M; Gouveia, L F; Goucha, P; Almeida, A J

2000-01-01

The influence of drug particle size on the production of enteric beads by a polymer precipitation technique was investigated. Drug particle dimensions are known to play an important role in most microencapsulation techniques. Bead morphology was greatly influenced by drug particle size, and spherical shaped beads could only be obtained after size reduction of nimesulide crystals. This is confirmed by the angle of repose measurements, which show a significant decrease in theta values when beads are formulated with smaller drug particles. Furthermore, results show that drug encapsulation efficiency and in vitro drug release rates are also greatly dependent on both drug particle size and drug/polymer ratio in the initial suspension. Preparations containing 10.2 microm drug particles show a two-fold increase in the release rates when compared to those prepared with 40 microm particles.

Boosted Kaluza-Klein magnetic monopole

NASA Astrophysics Data System (ADS)

Hashemi, S. Sedigheh; Riazi, Nematollah

2018-06-01

We consider a Kaluza-Klein vacuum solution which is closely related to the Gross-Perry-Sorkin (GPS) magnetic monopole. The solution can be obtained from the Euclidean Taub-NUT solution with an extra compact fifth spatial dimension within the formalism of Kaluza-Klein reduction. We study its physical properties as appearing in (3 + 1) spacetime dimensions, which turns out to be a static magnetic monopole. We then boost the GPS magnetic monopole along the extra dimension, and perform the Kaluza-Klein reduction. The resulting four-dimensional spacetime is a rotating stationary system, with both electric and magnetic fields. In fact, after the boost the magnetic monopole turns into a string connected to a dyon.

Active Subspace Methods for Data-Intensive Inverse Problems

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

Wang, Qiqi

2017-04-27

The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.

Dimensional reduction as a method to obtain dual theories for massive spin two in arbitrary dimensions

NASA Astrophysics Data System (ADS)

Khoudeir, A.; Montemayor, R.; Urrutia, Luis F.

2008-09-01

Using the parent Lagrangian method together with a dimensional reduction from D to (D-1) dimensions, we construct dual theories for massive spin two fields in arbitrary dimensions in terms of a mixed symmetry tensor TA[A1A2…AD-2]. Our starting point is the well-studied massless parent action in dimension D. The resulting massive Stueckelberg-like parent actions in (D-1) dimensions inherit all the gauge symmetries of the original massless action and can be gauge fixed in two alternative ways, yielding the possibility of having a parent action with either a symmetric or a nonsymmetric Fierz-Pauli field eAB. Even though the dual sector in terms of the standard spin two field includes only the symmetrical part e{AB} in both cases, these two possibilities yield different results in terms of the alternative dual field TA[A1A2…AD-2]. In particular, the nonsymmetric case reproduces the Freund-Curtright action as the dual to the massive spin two field action in four dimensions.

Hydrostatic and Flow Measurements on Wrinkled Membrane Walls

NASA Astrophysics Data System (ADS)

Ozsun, Ozgur; Ekinci, Kamil

2013-03-01

In this study, we investigate structural properties of wrinkled silicon nitride (SiN) membranes, under both hydrostatic perturbations and flow conditions, through surface profile measurements. Rectangular SiN membranes with linear dimensions of 15 mm × 1 . 5 mm × 1 μ m are fabricated on a 500 - μ m-thick silicon substrate using standard lithography techniques. These thin, initially flat, tension-dominated membranes are wrinkled by bending the silicon substrate. The wrinkled membranes are subsequently incorporated as walls into rectangular micro-channels, which allow both hydrostatic and flow measurements. The structural response of the wrinkles to hydrostatic pressure provides a measure of the various energy scales in the problem. Flow experiments show that the elastic properties and the structural undulations on a compliant membrane completely dominate the flow, possibly providing drag reduction. These measurements pave the way for building and using compliant walls for drag reduction in micro-channels.

Minimization of nanosatellite low frequency magnetic fields

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

Belyayev, S. M., E-mail: belyayev@isr.lviv.ua; Royal Institute of Technology, Stockholm 11428; Dudkin, F. L.

2016-03-15

Small weight and dimensions of the micro- and nanosatellites constrain researchers to place electromagnetic sensors on short booms or on the satellite body. Therefore the electromagnetic cleanliness of such satellites becomes a central question. This paper describes the theoretical base and practical techniques for determining the parameters of DC and very low frequency magnetic interference sources. One of such sources is satellite magnetization, the reduction of which improves the accuracy and stability of the attitude control system. We present design solutions for magnetically clean spacecraft, testing equipment, and technology for magnetic moment measurements, which are more convenient, efficient, and accuratemore » than the conventional ones.« less

A review on biogenic synthesis of ZnO nanoparticles using plant extracts and microbes: A prospect towards green chemistry.

PubMed

Ahmed, Shakeel; Annu; Chaudhry, Saif Ali; Ikram, Saiqa

2017-01-01

Nanotechnology is emerging as an important area of research with its tremendous applications in all fields of science, engineering, medicine, pharmacy, etc. It involves the materials and their applications having one dimension in the range of 1-100nm. Generally, various techniques are used for syntheses of nanoparticles (NPs) viz. laser ablation, chemical reduction, milling, sputtering, etc. These conventional techniques e.g. chemical reduction method, in which various hazardous chemicals are used for the synthesis of NPs later become liable for innumerable health risks due to their toxicity and endangering serious concerns for environment, while other approaches are expensive, need high energy for the synthesis of NPs. However, biogenic synthesis method to produce NPs is eco-friendly and free of chemical contaminants for biological applications where purity is of concerns. In biological method, different biological entities such as extract, enzymes or proteins of a natural product are used to reduce and stabilised formation of NPs. The nature of these biological entities also influence the structure, shape, size and morphology of synthesized NPs. In this review, biogenic synthesis of zinc oxide (ZnO) NPs, procedures of syntheses, mechanism of formation and their various applications have been discussed. Various entities such as proteins, enzymes, phytochemicals, etc. available in the natural reductants are responsible for synthesis of ZnO NPs. Copyright © 2016 Elsevier B.V. All rights reserved.

Visualization of polymer relaxation in viscoelastic turbulent micro-channel flow.

PubMed

Tai, Jiayan; Lim, Chun Ping; Lam, Yee Cheong

2015-11-13

In micro-channels, the flow of viscous liquids e.g. water, is laminar due to the low Reynolds number in miniaturized dimensions. An aqueous solution becomes viscoelastic with a minute amount of polymer additives; its flow behavior can become drastically different and turbulent. However, the molecules are typically invisible. Here we have developed a novel visualization technique to examine the extension and relaxation of polymer molecules at high flow velocities in a viscoelastic turbulent flow. Using high speed videography to observe the fluorescein labeled molecules, we show that viscoelastic turbulence is caused by the sporadic, non-uniform release of energy by the polymer molecules. This developed technique allows the examination of a viscoelastic liquid at the molecular level, and demonstrates the inhomogeneity of viscoelastic liquids as a result of molecular aggregation. It paves the way for a deeper understanding of viscoelastic turbulence, and could provide some insights on the high Weissenberg number problem. In addition, the technique may serve as a useful tool for the investigations of polymer drag reduction.

Visualization of polymer relaxation in viscoelastic turbulent micro-channel flow

NASA Astrophysics Data System (ADS)

Tai, Jiayan; Lim, Chun Ping; Lam, Yee Cheong

2015-11-01

In micro-channels, the flow of viscous liquids e.g. water, is laminar due to the low Reynolds number in miniaturized dimensions. An aqueous solution becomes viscoelastic with a minute amount of polymer additives; its flow behavior can become drastically different and turbulent. However, the molecules are typically invisible. Here we have developed a novel visualization technique to examine the extension and relaxation of polymer molecules at high flow velocities in a viscoelastic turbulent flow. Using high speed videography to observe the fluorescein labeled molecules, we show that viscoelastic turbulence is caused by the sporadic, non-uniform release of energy by the polymer molecules. This developed technique allows the examination of a viscoelastic liquid at the molecular level, and demonstrates the inhomogeneity of viscoelastic liquids as a result of molecular aggregation. It paves the way for a deeper understanding of viscoelastic turbulence, and could provide some insights on the high Weissenberg number problem. In addition, the technique may serve as a useful tool for the investigations of polymer drag reduction.

Visualization of polymer relaxation in viscoelastic turbulent micro-channel flow

PubMed Central

Tai, Jiayan; Lim, Chun Ping; Lam, Yee Cheong

2015-01-01

In micro-channels, the flow of viscous liquids e.g. water, is laminar due to the low Reynolds number in miniaturized dimensions. An aqueous solution becomes viscoelastic with a minute amount of polymer additives; its flow behavior can become drastically different and turbulent. However, the molecules are typically invisible. Here we have developed a novel visualization technique to examine the extension and relaxation of polymer molecules at high flow velocities in a viscoelastic turbulent flow. Using high speed videography to observe the fluorescein labeled molecules, we show that viscoelastic turbulence is caused by the sporadic, non-uniform release of energy by the polymer molecules. This developed technique allows the examination of a viscoelastic liquid at the molecular level, and demonstrates the inhomogeneity of viscoelastic liquids as a result of molecular aggregation. It paves the way for a deeper understanding of viscoelastic turbulence, and could provide some insights on the high Weissenberg number problem. In addition, the technique may serve as a useful tool for the investigations of polymer drag reduction. PMID:26563615

Applying manifold learning techniques to the CAESAR database

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Patrick, James; Arnold, Gregory; Ferrara, Matthew

2010-04-01

Understanding and organizing data is the first step toward exploiting sensor phenomenology for dismount tracking. What image features are good for distinguishing people and what measurements, or combination of measurements, can be used to classify the dataset by demographics including gender, age, and race? A particular technique, Diffusion Maps, has demonstrated the potential to extract features that intuitively make sense [1]. We want to develop an understanding of this tool by validating existing results on the Civilian American and European Surface Anthropometry Resource (CAESAR) database. This database, provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International, is a rich dataset which includes 40 traditional, anthropometric measurements of 4400 human subjects. If we could specifically measure the defining features for classification, from this database, then the future question will then be to determine a subset of these features that can be measured from imagery. This paper briefly describes the Diffusion Map technique, shows potential for dimension reduction of the CAESAR database, and describes interesting problems to be further explored.

A FMEA clinical laboratory case study: how to make problems and improvements measurable.

PubMed

Capunzo, Mario; Cavallo, Pierpaolo; Boccia, Giovanni; Brunetti, Luigi; Pizzuti, Sante

2004-01-01

The authors have experimented the application of the Failure Mode and Effect Analysis (FMEA) technique in a clinical laboratory. FMEA technique allows: a) to evaluate and measure the hazards of a process malfunction, b) to decide where to execute improvement actions, and c) to measure the outcome of those actions. A small sample of analytes has been studied: there have been determined the causes of the possible malfunctions of the analytical process, calculating the risk probability index (RPI), with a value between 1 and 1,000. Only for the cases of RPI > 400, improvement actions have been implemented that allowed a reduction of RPI values between 25% to 70% with a costs increment of < 1%. FMEA technique can be applied to the processes of a clinical laboratory, even if of small dimensions, and offers a high potential of improvement. Nevertheless, such activity needs a thorough planning because it is complex, even if the laboratory already operates an ISO 9000 Quality Management System.

Large-scale inverse model analyses employing fast randomized data reduction

NASA Astrophysics Data System (ADS)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

Chaos in plasma simulation and experiment

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

Watts, C.; Newman, D.E.; Sprott, J.C.

1993-09-01

We investigate the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas using data from both numerical simulations and experiment. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos. These tools include phase portraits and Poincard sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulate the plasma dynamics. These are -the DEBS code, which models global RFPmore » dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low,dimensional chaos and simple determinism. Experimental data were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or other simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Principal component of explained variance: An efficient and optimal data dimension reduction framework for association studies.

PubMed

Turgeon, Maxime; Oualkacha, Karim; Ciampi, Antonio; Miftah, Hanane; Dehghan, Golsa; Zanke, Brent W; Benedet, Andréa L; Rosa-Neto, Pedro; Greenwood, Celia Mt; Labbe, Aurélie

2018-05-01

The genomics era has led to an increase in the dimensionality of data collected in the investigation of biological questions. In this context, dimension-reduction techniques can be used to summarise high-dimensional signals into low-dimensional ones, to further test for association with one or more covariates of interest. This paper revisits one such approach, previously known as principal component of heritability and renamed here as principal component of explained variance (PCEV). As its name suggests, the PCEV seeks a linear combination of outcomes in an optimal manner, by maximising the proportion of variance explained by one or several covariates of interest. By construction, this method optimises power; however, due to its computational complexity, it has unfortunately received little attention in the past. Here, we propose a general analytical PCEV framework that builds on the assets of the original method, i.e. conceptually simple and free of tuning parameters. Moreover, our framework extends the range of applications of the original procedure by providing a computationally simple strategy for high-dimensional outcomes, along with exact and asymptotic testing procedures that drastically reduce its computational cost. We investigate the merits of the PCEV using an extensive set of simulations. Furthermore, the use of the PCEV approach is illustrated using three examples taken from the fields of epigenetics and brain imaging.

Dimension Reduction With Extreme Learning Machine.

PubMed

Kasun, Liyanaarachchi Lekamalage Chamara; Yang, Yan; Huang, Guang-Bin; Zhang, Zhengyou

2016-08-01

Data may often contain noise or irrelevant information, which negatively affect the generalization capability of machine learning algorithms. The objective of dimension reduction algorithms, such as principal component analysis (PCA), non-negative matrix factorization (NMF), random projection (RP), and auto-encoder (AE), is to reduce the noise or irrelevant information of the data. The features of PCA (eigenvectors) and linear AE are not able to represent data as parts (e.g. nose in a face image). On the other hand, NMF and non-linear AE are maimed by slow learning speed and RP only represents a subspace of original data. This paper introduces a dimension reduction framework which to some extend represents data as parts, has fast learning speed, and learns the between-class scatter subspace. To this end, this paper investigates a linear and non-linear dimension reduction framework referred to as extreme learning machine AE (ELM-AE) and sparse ELM-AE (SELM-AE). In contrast to tied weight AE, the hidden neurons in ELM-AE and SELM-AE need not be tuned, and their parameters (e.g, input weights in additive neurons) are initialized using orthogonal and sparse random weights, respectively. Experimental results on USPS handwritten digit recognition data set, CIFAR-10 object recognition, and NORB object recognition data set show the efficacy of linear and non-linear ELM-AE and SELM-AE in terms of discriminative capability, sparsity, training time, and normalized mean square error.

Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

PubMed

Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

2015-03-01

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

WHIDE—a web tool for visual data mining colocation patterns in multivariate bioimages

PubMed Central

Kölling, Jan; Langenkämper, Daniel; Abouna, Sylvie; Khan, Michael; Nattkemper, Tim W.

2012-01-01

Motivation: Bioimaging techniques rapidly develop toward higher resolution and dimension. The increase in dimension is achieved by different techniques such as multitag fluorescence imaging, Matrix Assisted Laser Desorption / Ionization (MALDI) imaging or Raman imaging, which record for each pixel an N-dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBIs) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this article, we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application. Results: We applied WHIDE to a set of MBI recorded using the multitag fluorescence imaging Toponome Imaging System. The MBI show field of view in tissue sections from a colon cancer study and we compare tissue from normal/healthy colon with tissue classified as tumor. Our results show, that WHIDE efficiently reduces the complexity of the data by mapping each of the pixels to a cluster, referred to as Molecular Co-Expression Phenotypes and provides a structural basis for a sophisticated multimodal visualization, which combines topology preserving pseudocoloring with information visualization. The wide range of WHIDE's applicability is demonstrated with examples from toponome imaging, high content screens and MALDI imaging (shown in the Supplementary Material). Availability and implementation: The WHIDE tool can be accessed via the BioIMAX website http://ani.cebitec.uni-bielefeld.de/BioIMAX/; Login: whidetestuser; Password: whidetest. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: tim.nattkemper@uni-bielefeld.de PMID:22390938

Development and validation of a new questionnaire measuring treatment satisfaction in patients with non-valvular atrial fibrillation: SAFUCA®.

PubMed

Ruiz, Miguel A; González-Porras, José Ramón; Aranguren, José Luis; Franco, Eduardo; Villasante, Fernando; Tuñón, José; González-López, Tomás José; de Salas-Cansado, Marina; Soto, Javier

2017-03-01

To develop a new questionnaire with good psychometric properties to measure satisfaction with medical care in patients with non-valvular atrial fibrillation. The initial instrument was composed of 37 items, arranged in 6 dimensions: efficacy, ease and convenience, impact on daily activities, satisfaction with medical care, undesired effects of medication, and overall satisfaction. Items and dimensions were extracted from reviewing existing instruments, 3 focus groups with chronic patients, and a panel of 8 experts. Additionally, 3 visual analog scales measuring quality of life, effectiveness, and overall satisfaction were administered. A convenience sample of 119 patients was used for item reduction. Classic psychometric theory and item analysis techniques were used (exploratory factor and confirmatory factor analysis, test-retest, and correlation with visual scales). A validation sample of 230 patients was used to assess convergent validity, and an additional 220 patients sample was used to discriminate between treatment and compliance groups. The questionnaire was reduced in length to 25 items, but the impact dimension had split in treatment inconvenience and treatment control. Overall reliability was high (α = 0.861) with acceptable dimensional reliabilities (α = 0.764-0.908). Individual dimensions correlated to varying degrees. Test-retest correlations were high (r = 0.784-0.965), and correlations with visual and already validated scales were substantial. Differences were detected between antivitamin K and new-oral-anticoagulant treatments in several dimensions (p < 0.05). Treatment satisfaction was related with compliance. This new 25-item questionnaire has good psychometric properties for measuring satisfaction with medical care in patients with this condition. It is capable of detecting differences between different treatments.

Model Order Reduction Algorithm for Estimating the Absorption Spectrum

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

Van Beeumen, Roel; Williams-Young, David B.; Kasper, Joseph M.

The ab initio description of the spectral interior of the absorption spectrum poses both a theoretical and computational challenge for modern electronic structure theory. Due to the often spectrally dense character of this domain in the quantum propagator’s eigenspectrum for medium-to-large sized systems, traditional approaches based on the partial diagonalization of the propagator often encounter oscillatory and stagnating convergence. Electronic structure methods which solve the molecular response problem through the solution of spectrally shifted linear systems, such as the complex polarization propagator, offer an alternative approach which is agnostic to the underlying spectral density or domain location. This generality comesmore » at a seemingly high computational cost associated with solving a large linear system for each spectral shift in some discretization of the spectral domain of interest. In this work, we present a novel, adaptive solution to this high computational overhead based on model order reduction techniques via interpolation. Model order reduction reduces the computational complexity of mathematical models and is ubiquitous in the simulation of dynamical systems and control theory. The efficiency and effectiveness of the proposed algorithm in the ab initio prediction of X-ray absorption spectra is demonstrated using a test set of challenging water clusters which are spectrally dense in the neighborhood of the oxygen K-edge. On the basis of a single, user defined tolerance we automatically determine the order of the reduced models and approximate the absorption spectrum up to the given tolerance. We also illustrate that, for the systems studied, the automatically determined model order increases logarithmically with the problem dimension, compared to a linear increase of the number of eigenvalues within the energy window. Furthermore, we observed that the computational cost of the proposed algorithm only scales quadratically with respect to the problem dimension.« less

Conversion of mill-scale waste to nanoscale zero valent iron (nZVI) for 'green' hydrogen generation via metal-steam reforming

NASA Astrophysics Data System (ADS)

Kesavan, Sathees Kumar

The Proton Exchange Membrane Fuel Cells (PEMFCs) are the most preferred and efficient energy conversion devices for automotive applications but demand high purity hydrogen which comes at a premium price. The currently pursued hydrogen generation methods suffer from issues such as, low efficiency, high cost, environmental non-benignity, and, in some cases, commercial non-viability. Many of these drawbacks including the CO contamination and, storage and delivery can be overcome by resorting to metal-steam reforming (MSR) using iron from steel industry's mill-scale waste. A novel solution-based room temperature technique using sodium borohydride (NaBH4) as the reducing agent has been developed that produces highly active nanoscale (30-40 nm) iron particles. A slightly modified version of this technique using a surfactant and water oil microemulsion resulted in the formation of 5 nm Fe particles. By using hydrazine (N2H4) as an inexpensive and more stable (compared to NaBH4) reductant, body centered cubic iron particles with edge dimensions ˜5 nm were obtained under mild solvothermal conditions in ethanol. The nanoscale zero valent iron (nZVI) powder showed improved kinetics and greater propensity for hydrogen generation than the coarser microscale iron obtained through traditional reduction techniques. To initiate and sustain the somewhat endothermic MSR process, a solar concentrator consisting of a convex polyacrylic sheet with aluminum reflective coating was fabricated. This unique combination of mill-scale waste as iron source, hydrazine as the reductant, mild process conditions for nZVI generation and solar energy as the impetus for actuating MSR, obviates several drawbacks plaguing the grand scheme of producing, storing and delivering pure and humidified H2 to a PEMFC stack.

The limited anterior approach of the elbow for open reduction and internal fixation of capitellum fractures. Surgical technique and clinical experience in 2 cases with more than 2 years follow-up.

PubMed

Ballesteros-Betancourt, J R; Fernández-Valencia, J A; García-Tarriño, R; Domingo-Trepat, A; Sastre-Solsona, S; Combalia-Aleu, A; Llusá-Pérez, M

Fractures involving the capitellum can be treated surgically by excision of the fragment, or by reduction and internal fixation with screws, with or without heads. The lateral Kocher approach is the most common approach for open reduction. We believe that the limited anterior approach of the elbow, could be a valid technique for treating these fractures, as it does not involve the detachment of any muscle group or ligament, facilitating the recovery process. A description is presented of the surgical technique, as well as of 2cases with a Bryan-Morrey type 1 fracture (Dubberley type 1A). Two different final quality of life evaluation questionnaires were completed by telephone: the EuroQol Five Dimensions Questionnaire (EQ-5D), and the patient part of the Liverpool Elbow Score (PAQ-LES) questionnaire. The 2patients showed favourable clinical progress at 36 and 24 months, respectively, with an extension/flexion movement arc of -5°/145° and -10°/145°, as well as a pronosupination of 85°/80° and 90°/90°. The 2patients showed radiological consolidation with no signs of osteonecrosis. The EQ-5D score was 0.857 and 0.910 (range: 0.36-1), and a PAQ-SLE of 35 and 35 (range: 17-36), respectively. We believe that the limited anterior approach of the elbow is a technical option to consider for the open surgical treatment of a capitellum fracture, although further studies are needed to demonstrate its superiority and clinical safety compared to the classical lateral Kocher approach. Copyright © 2017 SECOT. Publicado por Elsevier España, S.L.U. All rights reserved.

SparseCT: interrupted-beam acquisition and sparse reconstruction for radiation dose reduction

NASA Astrophysics Data System (ADS)

Koesters, Thomas; Knoll, Florian; Sodickson, Aaron; Sodickson, Daniel K.; Otazo, Ricardo

2017-03-01

State-of-the-art low-dose CT methods reduce the x-ray tube current and use iterative reconstruction methods to denoise the resulting images. However, due to compromises between denoising and image quality, only moderate dose reductions up to 30-40% are accepted in clinical practice. An alternative approach is to reduce the number of x-ray projections and use compressed sensing to reconstruct the full-tube-current undersampled data. This idea was recognized in the early days of compressed sensing and proposals for CT dose reduction appeared soon afterwards. However, no practical means of undersampling has yet been demonstrated in the challenging environment of a rapidly rotating CT gantry. In this work, we propose a moving multislit collimator as a practical incoherent undersampling scheme for compressed sensing CT and evaluate its application for radiation dose reduction. The proposed collimator is composed of narrow slits and moves linearly along the slice dimension (z), to interrupt the incident beam in different slices for each x-ray tube angle (θ). The reduced projection dataset is then reconstructed using a sparse approach, where 3D image gradients are employed to enforce sparsity. The effects of the collimator slits on the beam profile were measured and represented as a continuous slice profile. SparseCT was tested using retrospective undersampling and compared against commercial current-reduction techniques on phantoms and in vivo studies. Initial results suggest that SparseCT may enable higher performance than current-reduction, particularly for high dose reduction factors.

Enhancement of activity of RuSex electrocatalyst by modification with nanostructured iridium towards more efficient reduction of oxygen

NASA Astrophysics Data System (ADS)

Dembinska, Beata; Kiliszek, Malgorzata; Elzanowska, Hanna; Pisarek, Marcin; Kulesza, Pawel J.

2013-12-01

Electrocatalytic activity of carbon (Vulcan XC-72) supported selenium-modified ruthenium, RuSex/C, nanoparticles for reduction of oxygen was enhanced through intentional decoration with iridium nanostructures (dimensions, 2-3 nm). The catalytic materials were characterized in oxygenated 0.5 mol dm-3 H2SO4 using cyclic and rotating ring disk voltammetric techniques as well as using transmission electron microscopy and scanning electron microscopy equipped with X-ray dispersive analyzer. Experiments utilizing gas diffusion electrode aimed at mimicking conditions existing in the low-temperature fuel cell. Upon application of our composite catalytic system, the reduction of oxygen proceeded at more positive potentials, and higher current densities were observed when compared to the behavior of the simple iridium-free system (RuSex/C) investigated under the analogous conditions. The enhancement effect was more pronounced than that one would expect from simple superposition of voltammetric responses for the oxygen reduction at RuSex/C and iridium nanostructures studied separately. Nanostructured iridium acted here as an example of a powerful catalyst for the reduction of H2O2 (rather than O2) and, when combined with such a moderate catalyst as ruthenium-selenium (for O2 reduction), it produced an integrated system of increased electrocatalytic activity in the oxygen reduction process. The proposed system retained its activity in the presence of methanol that could appear in a cathode compartment of alcohol fuel cell.

Reduction of Large Dynamical Systems by Minimization of Evolution Rate

NASA Technical Reports Server (NTRS)

Girimaji, Sharath S.

1999-01-01

Reduction of a large system of equations to a lower-dimensional system of similar dynamics is investigated. For dynamical systems with disparate timescales, a criterion for determining redundant dimensions and a general reduction method based on the minimization of evolution rate are proposed.

Diff-invariant kinetic terms in arbitrary dimensions

NASA Astrophysics Data System (ADS)

Barbero G., J. Fernando; Villaseñor, Eduardo J.

2002-06-01

We study the physical content of quadratic diff-invariant Lagrangians in arbitrary dimensions by using covariant symplectic techniques. This paper extends previous results in dimension four. We discuss the difference between the even and odd dimensional cases.

Incremental online learning in high dimensions.

PubMed

Vijayakumar, Sethu; D'Souza, Aaron; Schaal, Stefan

2005-12-01

Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally efficient and numerically robust, each local model performs the regression analysis with a small number of univariate regressions in selected directions in input space in the spirit of partial least squares regression. We discuss when and how local learning techniques can successfully work in high-dimensional spaces and review the various techniques for local dimensionality reduction before finally deriving the LWPR algorithm. The properties of LWPR are that it (1) learns rapidly with second-order learning methods based on incremental training, (2) uses statistically sound stochastic leave-one-out cross validation for learning without the need to memorize training data, (3) adjusts its weighting kernels based on only local information in order to minimize the danger of negative interference of incremental learning, (4) has a computational complexity that is linear in the number of inputs, and (5) can deal with a large number of-possibly redundant-inputs, as shown in various empirical evaluations with up to 90 dimensional data sets. For a probabilistic interpretation, predictive variance and confidence intervals are derived. To our knowledge, LWPR is the first truly incremental spatially localized learning method that can successfully and efficiently operate in very high-dimensional spaces.

Dimension reduction of frequency-based direct Granger causality measures on short time series.

PubMed

Siggiridou, Elsa; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris

2017-09-01

The mainstream in the estimation of effective brain connectivity relies on Granger causality measures in the frequency domain. If the measure is meant to capture direct causal effects accounting for the presence of other observed variables, as in multi-channel electroencephalograms (EEG), typically the fit of a vector autoregressive (VAR) model on the multivariate time series is required. For short time series of many variables, the estimation of VAR may not be stable requiring dimension reduction resulting in restricted or sparse VAR models. The restricted VAR obtained by the modified backward-in-time selection method (mBTS) is adapted to the generalized partial directed coherence (GPDC), termed restricted GPDC (RGPDC). Dimension reduction on other frequency based measures, such the direct directed transfer function (dDTF), is straightforward. First, a simulation study using linear stochastic multivariate systems is conducted and RGPDC is favorably compared to GPDC on short time series in terms of sensitivity and specificity. Then the two measures are tested for their ability to detect changes in brain connectivity during an epileptiform discharge (ED) from multi-channel scalp EEG. It is shown that RGPDC identifies better than GPDC the connectivity structure of the simulated systems, as well as changes in the brain connectivity, and is less dependent on the free parameter of VAR order. The proposed dimension reduction in frequency measures based on VAR constitutes an appropriate strategy to estimate reliably brain networks within short-time windows. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

NASA Astrophysics Data System (ADS)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

Model reduction for Space Station Freedom

NASA Technical Reports Server (NTRS)

Williams, Trevor

1992-01-01

Model reduction is an important practical problem in the control of flexible spacecraft, and a considerable amount of work has been carried out on this topic. Two of the best known methods developed are modal truncation and internal balancing. Modal truncation is simple to implement but can give poor results when the structure possesses clustered natural frequencies, as often occurs in practice. Balancing avoids this problem but has the disadvantages of high computational cost, possible numerical sensitivity problems, and no physical interpretation for the resulting balanced 'modes'. The purpose of this work is to examine the performance of the subsystem balancing technique developed by the investigator when tested on a realistic flexible space structure, in this case a model of the Permanently Manned Configuration (PMC) of Space Station Freedom. This method retains the desirable properties of standard balancing while overcoming the three difficulties listed above. It achieves this by first decomposing the structural model into subsystems of highly correlated modes. Each subsystem is approximately uncorrelated from all others, so balancing them separately and then combining yields comparable results to balancing the entire structure directly. The operation count reduction obtained by the new technique is considerable: a factor of roughly r(exp 2) if the system decomposes into r equal subsystems. Numerical accuracy is also improved significantly, as the matrices being operated on are of reduced dimension, and the modes of the reduced-order model now have a clear physical interpretation; they are, to first order, linear combinations of repeated-frequency modes.

Chaotic behavior of renal sympathetic nerve activity: effect of baroreceptor denervation and cardiac failure.

PubMed

DiBona, G F; Jones, S Y; Sawin, L L

2000-09-01

Nonlinear dynamic analysis was used to examine the chaotic behavior of renal sympathetic nerve activity in conscious rats subjected to either complete baroreceptor denervation (sinoaortic and cardiac baroreceptor denervation) or induction of congestive heart failure (CHF). The peak interval sequence of synchronized renal sympathetic nerve discharge was extracted and used for analysis. In control rats, this yielded a system whose correlation dimension converged to a low value over the embedding dimension range of 10-15 and whose greatest Lyapunov exponent was positive. Complete baroreceptor denervation was associated with a decrease in the correlation dimension of the system (before 2.65 +/- 0.27, after 1.64 +/- 0.17; P < 0.01) and a reduction in chaotic behavior (greatest Lyapunov exponent: 0.201 +/- 0.008 bits/data point before, 0.177 +/- 0.004 bits/data point after, P < 0.02). CHF, a state characterized by impaired sinoaortic and cardiac baroreceptor regulation of renal sympathetic nerve activity, was associated with a similar decrease in the correlation dimension (control 3.41 +/- 0.23, CHF 2.62 +/- 0.26; P < 0.01) and a reduction in chaotic behavior (greatest Lyapunov exponent: 0.205 +/- 0.048 bits/data point control, 0.136 +/- 0.033 bits/data point CHF, P < 0.02). These results indicate that removal of sinoaortic and cardiac baroreceptor regulation of renal sympathetic nerve activity, occurring either physiologically or pathophysiologically, is associated with a decrease in the correlation dimensions of the system and a reduction in chaotic behavior.

The Impact of Symptom Dimensions on Outcome for Exposure and Ritual Prevention Therapy in Obsessive-Compulsive Disorder

PubMed Central

Williams, Monnica T.; Farris, Samantha G.; Turkheimer, Eric N.; Franklin, Martin E.; Simpson, H. Blair; Liebowitz, Michael; Foa, Edna B.

2014-01-01

Objective Obsessive-compulsive disorder (OCD) is a severe condition with varied symptom presentations. The behavioral treatment with the most empirical support is exposure and ritual prevention (EX/RP). This study examined the impact of symptom dimensions on EX/RP outcomes in OCD patients. Method The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was used to determine primary symptoms for each participant. An exploratory factor analysis (EFA) of 238 patients identified five dimensions: contamination/cleaning, doubts about harm/checking, hoarding, symmetry/ordering, and unacceptable/taboo thoughts (including religious/moral and somatic obsessions among others). A linear regression was conducted on those who had received EX/RP (n = 87) to examine whether scores on the five symptom dimensions predicted post-treatment Y-BOCS scores, accounting for pre-treatment Y-BOCS scores. Results The average reduction in Y-BOCS score was 43.0%, however the regression indicated that unacceptable/taboo thoughts (β = .27, p = .02) and hoarding dimensions (β = .23, p = .04) were associated with significantly poorer EX/RP treatment outcomes. Specifically, patients endorsing religious/moral obsessions, somatic concerns, and hoarding obsessions showed significantly smaller reductions in Y-BOCS severity scores. Conclusions EX/RP was effective for all symptom dimensions, however it was less effective for unacceptable/taboo thoughts and hoarding than for other dimensions. Clinical implications and directions for research are discussed. PMID:24983796

The impact of symptom dimensions on outcome for exposure and ritual prevention therapy in obsessive-compulsive disorder.

PubMed

Williams, Monnica T; Farris, Samantha G; Turkheimer, Eric N; Franklin, Martin E; Simpson, H Blair; Liebowitz, Michael; Foa, Edna B

2014-08-01

Obsessive-compulsive disorder (OCD) is a severe condition with varied symptom presentations. The behavioral treatment with the most empirical support is exposure and ritual prevention (EX/RP). This study examined the impact of symptom dimensions on EX/RP outcomes in OCD patients. The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was used to determine primary symptoms for each participant. An exploratory factor analysis (EFA) of 238 patients identified five dimensions: contamination/cleaning, doubts about harm/checking, hoarding, symmetry/ordering, and unacceptable/taboo thoughts (including religious/moral and somatic obsessions among others). A linear regression was conducted on those who had received EX/RP (n=87) to examine whether scores on the five symptom dimensions predicted post-treatment Y-BOCS scores, accounting for pre-treatment Y-BOCS scores. The average reduction in Y-BOCS score was 43.0%, however the regression indicated that unacceptable/taboo thoughts (β=.27, p=.02) and hoarding dimensions (β=.23, p=.04) were associated with significantly poorer EX/RP treatment outcomes. Specifically, patients endorsing religious/moral obsessions, somatic concerns, and hoarding obsessions showed significantly smaller reductions in Y-BOCS severity scores. EX/RP was effective for all symptom dimensions, however it was less effective for unacceptable/taboo thoughts and hoarding than for other dimensions. Clinical implications and directions for research are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Knowledge Support and Automation for Performance Analysis with PerfExplorer 2.0

DOE PAGES

Huck, Kevin A.; Malony, Allen D.; Shende, Sameer; ...

2008-01-01

The integration of scalable performance analysis in parallel development tools is difficult. The potential size of data sets and the need to compare results from multiple experiments presents a challenge to manage and process the information. Simply to characterize the performance of parallel applications running on potentially hundreds of thousands of processor cores requires new scalable analysis techniques. Furthermore, many exploratory analysis processes are repeatable and could be automated, but are now implemented as manual procedures. In this paper, we will discuss the current version of PerfExplorer, a performance analysis framework which provides dimension reduction, clustering and correlation analysis ofmore » individual trails of large dimensions, and can perform relative performance analysis between multiple application executions. PerfExplorer analysis processes can be captured in the form of Python scripts, automating what would otherwise be time-consuming tasks. We will give examples of large-scale analysis results, and discuss the future development of the framework, including the encoding and processing of expert performance rules, and the increasing use of performance metadata.« less

Dimension reduction and multiscaling law through source extraction

NASA Astrophysics Data System (ADS)

Capobianco, Enrico

2003-04-01

Through the empirical analysis of financial return generating processes one may find features that are common to other research fields, such as internet data from network traffic, physiological studies about human heart beat, speech and sleep recorded time series, geophysics signals, just to mention well-known cases of study. In particular, long range dependence, intermittency, heteroscedasticity are clearly appearing, and consequently power laws and multi-scaling behavior result typical signatures of either the spectral or the time correlation diagnostics. We study these features and the dynamics underlying financial volatility, which can respectively be detected and inferred from high frequency realizations of stock index returns, and show that they vary according to the resolution levels used for both the analysis and the synthesis of the available information. Discovering whether the volatility dynamics are subject to changes in scaling regimes requires the consideration of a model embedding scale-dependent information packets, thus accounting for possible heterogeneous activity occurring in financial markets. Independent component analysis result to be an important tool for reducing the dimension of the problem and calibrating greedy approximation techniques aimed to learn the structure of the underlying volatility.

High dimensional feature reduction via projection pursuit

NASA Technical Reports Server (NTRS)

Jimenez, Luis; Landgrebe, David

1994-01-01

The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many more spectral intervals than previously possible. An example of that technology is the AVIRIS system, which collects image data in 220 bands. As a result of this, new algorithms must be developed in order to analyze the more complex data effectively. Data in a high dimensional space presents a substantial challenge, since intuitive concepts valid in a 2-3 dimensional space to not necessarily apply in higher dimensional spaces. For example, high dimensional space is mostly empty. This results from the concentration of data in the corners of hypercubes. Other examples may be cited. Such observations suggest the need to project data to a subspace of a much lower dimension on a problem specific basis in such a manner that information is not lost. Projection Pursuit is a technique that will accomplish such a goal. Since it processes data in lower dimensions, it should avoid many of the difficulties of high dimensional spaces. In this paper, we begin the investigation of some of the properties of Projection Pursuit for this purpose.

Quantitative high-speed laryngoscopic analysis of vocal fold vibration in fatigued voice of young karaoke singers.

PubMed

Yiu, Edwin M-L; Wang, Gaowu; Lo, Andy C Y; Chan, Karen M-K; Ma, Estella P-M; Kong, Jiangping; Barrett, Elizabeth Ann

2013-11-01

The present study aimed to determine whether there were physiological differences in the vocal fold vibration between nonfatigued and fatigued voices using high-speed laryngoscopic imaging and quantitative analysis. Twenty participants aged from 18 to 23 years (mean, 21.2 years; standard deviation, 1.3 years) with normal voice were recruited to participate in an extended singing task. Vocal fatigue was induced using a singing task. High-speed laryngoscopic image recordings of /i/ phonation were taken before and after the singing task. The laryngoscopic images were semiautomatically analyzed with the quantitative high-speed video processing program to extract indices related to the anteroposterior dimension (length), transverse dimension (width), and the speed of opening and closing. Significant reduction in the glottal length-to-width ratio index was found after vocal fatigue. Physiologically, this indicated either a significantly shorter (anteroposteriorly) or a wider (transversely) glottis after vocal fatigue. The high-speed imaging technique using quantitative analysis has the potential for early identification of vocally fatigued voice. Copyright © 2013 The Voice Foundation. All rights reserved.

Optimization of Selected Remote Sensing Algorithms for Embedded NVIDIA Kepler GPU Architecture

NASA Technical Reports Server (NTRS)

Riha, Lubomir; Le Moigne, Jacqueline; El-Ghazawi, Tarek

2015-01-01

This paper evaluates the potential of embedded Graphic Processing Units in the Nvidias Tegra K1 for onboard processing. The performance is compared to a general purpose multi-core CPU and full fledge GPU accelerator. This study uses two algorithms: Wavelet Spectral Dimension Reduction of Hyperspectral Imagery and Automated Cloud-Cover Assessment (ACCA) Algorithm. Tegra K1 achieved 51 for ACCA algorithm and 20 for the dimension reduction algorithm, as compared to the performance of the high-end 8-core server Intel Xeon CPU with 13.5 times higher power consumption.

Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Wei, Zhiliang; Lin, Liangjie; Ye, Qimiao; Li, Jing; Cai, Shuhui; Chen, Zhong

2015-07-01

The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique.

Chaos and simple determinism in reversed field pinch plasmas: Nonlinear analysis of numerical simulation and experimental data

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

Watts, Christopher A.

In this dissertation the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas is investigated. To properly assess this possibility, data from both numerical simulations and experiment are analyzed. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos in the data. These tools include phase portraits and Poincare sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulatemore » the plasma dynamics. These are the DEBS code, which models global RFP dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low dimensional chaos and simple determinism. Experimental date were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or low simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Analytical study of acoustic response of a semireverberant enclosure with application to active noise control

NASA Technical Reports Server (NTRS)

Parrott, T. L.; Schein, D. B.; Gridley, D.

1985-01-01

The acoustic response of a semireverberant enclosure with two interacting, velocity-prescribed source distributions was analyzed using standard modal analysis techniques with a view toward a better understanding of active noise control. Different source and enclosure dimensions, source separations, and single-wall admittances were studied over representative frequency bandwidths of 10 Hz with source relative phase as a parameter. Results indicate that power radiated into the enclosure agree qualitatively with the spatial average of the mean square pressure, even though the reverberant field is nondiffuse. Decreases in acoustic power can therefore be used to estimate global noise reduction in a nondiffuse semireverberant environment. As might be expected, parametric studies indicate that maximum power reductions of up to 25 dB can be achieved when secondary and primary sources are compact and closely spaced. Although less success is achieved with increasing frequency and source separation or size, significant suppression of up to 8 dB still occurs over the 1 to 2 Hz bandwidth.

Effective dimensional reduction algorithm for eigenvalue problems for thin elastic structures: A paradigm in three dimensions

PubMed Central

Ovtchinnikov, Evgueni E.; Xanthis, Leonidas S.

2000-01-01

We present a methodology for the efficient numerical solution of eigenvalue problems of full three-dimensional elasticity for thin elastic structures, such as shells, plates and rods of arbitrary geometry, discretized by the finite element method. Such problems are solved by iterative methods, which, however, are known to suffer from slow convergence or even convergence failure, when the thickness is small. In this paper we show an effective way of resolving this difficulty by invoking a special preconditioning technique associated with the effective dimensional reduction algorithm (EDRA). As an example, we present an algorithm for computing the minimal eigenvalue of a thin elastic plate and we show both theoretically and numerically that it is robust with respect to both the thickness and discretization parameters, i.e. the convergence does not deteriorate with diminishing thickness or mesh refinement. This robustness is sine qua non for the efficient computation of large-scale eigenvalue problems for thin elastic structures. PMID:10655469

Network community-based model reduction for vortical flows

NASA Astrophysics Data System (ADS)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya G.; Taira, Kunihiko

2018-06-01

A network community-based reduced-order model is developed to capture key interactions among coherent structures in high-dimensional unsteady vortical flows. The present approach is data-inspired and founded on network-theoretic techniques to identify important vortical communities that are comprised of vortical elements that share similar dynamical behavior. The overall interaction-based physics of the high-dimensional flow field is distilled into the vortical community centroids, considerably reducing the system dimension. Taking advantage of these vortical interactions, the proposed methodology is applied to formulate reduced-order models for the inter-community dynamics of vortical flows, and predict lift and drag forces on bodies in wake flows. We demonstrate the capabilities of these models by accurately capturing the macroscopic dynamics of a collection of discrete point vortices, and the complex unsteady aerodynamic forces on a circular cylinder and an airfoil with a Gurney flap. The present formulation is found to be robust against simulated experimental noise and turbulence due to its integrating nature of the system reduction.

Separation of fatty acid methyl esters by GC-online hydrogenation × GC.

PubMed

Delmonte, Pierluigi; Fardin-Kia, Ali Reza; Rader, Jeanne I

2013-02-05

The separation of fatty acid methyl esters (FAME) provided by a 200 m × 0.25 mm SLB-IL111 capillary column is enhanced by adding a second dimension of separation ((2)D) in a GC × GC design. Rather than employing two GC columns of different polarities or using different elution temperatures, the separation in the two-dimensional space is achieved by altering the chemical structure of selected analytes between the two dimensions of separation. A capillary tube coated with palladium is added between the first dimension of separation ((1)D) column and the cryogenic modulator, providing the reduction of unsaturated FAMEs to their fully saturated forms. The (2)D separation is achieved using a 2.5 m × 0.10 mm SLB-IL111 capillary column and separates FAMEs based solely on their carbon skeleton. The two-dimensional separation can be easily interpreted based on the principle that all the saturated FAMEs lie on a straight diagonal line bisecting the separation plane, while the FAMEs with the same carbon skeleton but differing in the number, geometric configuration or position of double bonds lie on lines parallel to the (1)D time axis. This technique allows the separation of trans fatty acids (FAs) and polyunsaturated FAs (PUFAs) in a single experiment and eliminates the overlap between PUFAs with different chain lengths. To our knowledge, this the first example of GC × GC in which a chemical change is instituted between the two dimensions to alter the relative retentions of components and identify unsaturated FAMEs.

Compressed Secret Key Agreement:Maximizing Multivariate Mutual Information per Bit

NASA Astrophysics Data System (ADS)

Chan, Chung

2017-10-01

The multiterminal secret key agreement problem by public discussion is formulated with an additional source compression step where, prior to the public discussion phase, users independently compress their private sources to filter out strongly correlated components for generating a common secret key. The objective is to maximize the achievable key rate as a function of the joint entropy of the compressed sources. Since the maximum achievable key rate captures the total amount of information mutual to the compressed sources, an optimal compression scheme essentially maximizes the multivariate mutual information per bit of randomness of the private sources, and can therefore be viewed more generally as a dimension reduction technique. Single-letter lower and upper bounds on the maximum achievable key rate are derived for the general source model, and an explicit polynomial-time computable formula is obtained for the pairwise independent network model. In particular, the converse results and the upper bounds are obtained from those of the related secret key agreement problem with rate-limited discussion. A precise duality is shown for the two-user case with one-way discussion, and such duality is extended to obtain the desired converse results in the multi-user case. In addition to posing new challenges in information processing and dimension reduction, the compressed secret key agreement problem helps shed new light on resolving the difficult problem of secret key agreement with rate-limited discussion, by offering a more structured achieving scheme and some simpler conjectures to prove.

Photographic measurements in 301 cases of liposuction and abdominoplasty reveal fat reduction without redistribution.

PubMed

Swanson, Eric

2012-08-01

There are no published studies of liposuction or abdominoplasty in a large number of patients using measurements of body dimensions. In the absence of rigorous data, some investigators have proposed that fat returns after liposuction. A prospective study was undertaken among predominantly nonobese consecutive patients undergoing 301 liposuction and abdominoplasty procedures meeting the study criteria (inclusion rate, 70.7 percent). Lower body dimensions were measured using standardized photographs taken before and at least 3 months after surgery. Upper body measurements were compared between women who underwent simultaneous cosmetic breast surgery (n=67) and a group of women who had breast surgery alone (n=78) to investigate the possibility of fat redistribution. The average weight change was a loss of 2.2 lbs after lower body liposuction (p<0.01) and 4.6 lbs when combined with abdominoplasty (p<0.001). Liposuction significantly reduced abdominal, thigh, knee, and arm width (p<0.001). Midabdominal and hip width were more effectively reduced by lipoabdominoplasty than liposuction alone (p<0.001). There was no difference in upper body measurements when comparing patients who had simultaneous liposuction and/or abdominoplasty with patients who had cosmetic breast surgery alone. Measurements in patients with at least 1 year of follow-up (n=46) showed no evidence of fat reaccumulation. Both liposuction and abdominoplasty are valid techniques for long-term fat reduction and improvement of body proportions. There is no evidence of fat regrowth. Therapeutic, III.

Strategies towards an optimized use of the shallow geothermal potential

NASA Astrophysics Data System (ADS)

Schelenz, S.; Firmbach, L.; Kalbacher, T.; Goerke, U.; Kolditz, O.; Dietrich, P.; Vienken, T.

2013-12-01

Thermal use of the shallow subsurface for heat generation, cooling and thermal energy storage is increasingly gaining importance in reconsideration of future energy supplies, e.g. in the course of German energy transition, with application shifting from isolated to intensive use. The planning and dimensioning of (geo-)thermal applications is strongly influenced by the availability of exploration data. Hence, reliable site-specific dimensioning of systems for the thermal use of the shallow subsurface will contribute to an increase in resource efficiency, cost reduction during installation and operation, as well as reduction of environmental impacts and prevention of resource over-exploitation. Despite large cumulative investments that are being made for the utilization of the shallow thermal potential, thermal energy is in many cases exploited without prior on-site exploration and investigation of the local geothermal potential, due to the lack of adequate and cost-efficient exploration techniques. We will present new strategies for an optimized utilization of urban thermal potential, showcased at a currently developed residential neighborhood with high demand for shallow geothermal applications, based on a) enhanced site characterization and b) simulation of different site specific application scenarios. For enhanced site characterization, surface geophysics and vertical high resolution direct push-profiling were combined for reliable determination of aquifer structure and aquifer parameterization. Based on the site characterization, different site specific geothermal application scenarios, including different system types and system configurations, were simulated using OpenGeoSys to guarantee an environmental and economic sustainable thermal use of the shallow subsurface.

Processing of carbamazepine-PEG 4000 solid dispersions with supercritical carbon dioxide: preparation, characterisation, and in vitro dissolution.

PubMed

Moneghini, M; Kikic, I; Voinovich, D; Perissutti, B; Filipović-Grcić, J

2001-07-03

The purpose of this study was to apply the attractive technique of the supercritical fluid to the preparation of solvent-free solid dispersions. In particular, the gas antisolvent crystallisation technique (GAS), using supercritical carbon dioxide as processing medium, has been considered to prepare an enhanced release dosage form for of the poorly soluble carbamazepine, employing PEG 4000 as a hydrophilic carrier. The physical characterisation of the systems using laser granulometer, powder X-ray diffraction, thermal analyses, and scanning electron microscopy was carried out in order to understand the influence of this technological process on the physical status of the drug. The results of the physical characterisation attested a substantial correspondence of the solid state of the drug before and after treatment with GAS technique, whereas a pronounced change in size and morphology of the drug crystals was noticed. The dramatic reduction of the dimensions and the better crystal shape, together with the presence of the hydrophilic polymer determined a remarkable enhancement of the in vitro drug dissolution rate.

The continuous spin representations of the Poincare and super-Poincare groups and their construction by the Inonu-Wigner group contraction

NASA Astrophysics Data System (ADS)

Khan, Abu M. A. S.

We study the continuous spin representation (CSR) of the Poincare group in arbitrary dimensions. In d dimensions, the CSRs are characterized by the length of the light-cone vector and the Dynkin labels of the SO(d-3) short little group which leaves the light-cone vector invariant. In addition to these, a solid angle Od-3 which specifies the direction of the light-cone vector is also required to label the states. We also find supersymmetric generalizations of the CSRs. In four dimensions, the supermultiplet contains one bosonic and one fermionic CSRs which transform into each other under the action of the supercharges. In a five dimensional case, the supermultiplet contains two bosonic and two fermionic CSRs which is like N = 2 supersymmetry in four dimensions. When constructed using Grassmann parameters, the light-cone vector becomes nilpotent. This makes the representation finite dimensional, but at the expense of introducing central charges even though the representation is massless. This leads to zero or negative norm states. The nilpotent constructions are valid only for even dimensions. We also show how the CSRs in four dimensions can be obtained from five dimensions by the combinations of Kaluza-Klein (KK) dimensional reduction and the Inonu-Wigner group contraction. The group contraction is a singular transformation. We show that the group contraction is equivalent to imposing periodic boundary condition along one direction and taking a double singular limit. In this form the contraction parameter is interpreted as the inverse KK radius. We apply this technique to both five dimensional regular massless and massive representations. For the regular massless case, we find that the contraction gives the CSR in four dimensions under a double singular limit and the representation wavefunction is the Bessel function. For the massive case, we use Majorana's infinite component theory as a model for the SO(4) little group. In this case, a triple singular limit is required to yield any CSR in four dimensions. The representation wavefunction is the Bessel function, as expected, but the scale factor is not the length of the light-cone vector. The amplitude and the scale factor are implicit functions of the parameter y which is a ratio of the internal and external coordinates. We also state under what conditions our solutions become identical to Wigner's solution.

All-Possible-Subsets for MANOVA and Factorial MANOVAs: Less than a Weekend Project

ERIC Educational Resources Information Center

Nimon, Kim; Zientek, Linda Reichwein; Kraha, Amanda

2016-01-01

Multivariate techniques are increasingly popular as researchers attempt to accurately model a complex world. MANOVA is a multivariate technique used to investigate the dimensions along which groups differ, and how these dimensions may be used to predict group membership. A concern in a MANOVA analysis is to determine if a smaller subset of…

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Králová, Blanka

2011-12-01

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling.

New Dimensions for the Multicultural Education Course

ERIC Educational Resources Information Center

Gay, Richard

2011-01-01

For the past sixteen years, the Five Dimensions of Multicultural Education, as proposed by James A. Banks (1995), have been accepted in many circles as the primary conceptual framework used in teaching multicultural education courses: content integration, the knowledge construction process, prejudice reduction, an equity pedagogy and an empowering…

A general soft label based linear discriminant analysis for semi-supervised dimensionality reduction.

PubMed

Zhao, Mingbo; Zhang, Zhao; Chow, Tommy W S; Li, Bing

2014-07-01

Dealing with high-dimensional data has always been a major problem in research of pattern recognition and machine learning, and Linear Discriminant Analysis (LDA) is one of the most popular methods for dimension reduction. However, it only uses labeled samples while neglecting unlabeled samples, which are abundant and can be easily obtained in the real world. In this paper, we propose a new dimension reduction method, called "SL-LDA", by using unlabeled samples to enhance the performance of LDA. The new method first propagates label information from the labeled set to the unlabeled set via a label propagation process, where the predicted labels of unlabeled samples, called "soft labels", can be obtained. It then incorporates the soft labels into the construction of scatter matrixes to find a transformed matrix for dimension reduction. In this way, the proposed method can preserve more discriminative information, which is preferable when solving the classification problem. We further propose an efficient approach for solving SL-LDA under a least squares framework, and a flexible method of SL-LDA (FSL-LDA) to better cope with datasets sampled from a nonlinear manifold. Extensive simulations are carried out on several datasets, and the results show the effectiveness of the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fear of Fear and Broad Dimensions of Psychopathology over the Course of Cognitive Behavioural Therapy for Panic Disorder with Agoraphobia in Japan.

PubMed

Ogawa, S; Kondo, M; Ino, K; Ii, T; Imai, R; Furukawa, T A; Akechi, T

2017-12-01

To examine the relationship of fear of fear and broad dimensions of psychopathology in panic disorder with agoraphobia over the course of cognitive behavioural therapy in Japan. A total of 177 Japanese patients with panic disorder with agoraphobia were treated with group cognitive behavioural therapy between 2001 and 2015. We examined associations between the change scores in Agoraphobic Cognitions Questionnaire or Body Sensations Questionnaire and the changes in subscales of Symptom Checklist-90 Revised during cognitive behavioural therapy controlling the change in panic disorder severity using multiple regression analysis. Reduction in Agoraphobic Cognitions Questionnaire score was related to a decrease in all Symptom Checklist-90 Revised (SCL-90-R) subscale scores. Reduction in Body Sensations Questionnaire score was associated with a decrease in anxiety. Reduction in Panic Disorder Severity Scale score was not related to any SCL-90-R subscale changes. Changes in fear of fear, especially maladaptive cognitions, may predict broad dimensions of psychopathology reductions in patients of panic disorder with agoraphobia over the course of cognitive behavioural therapy. For the sake of improving a broader range of psychiatric symptoms in patients of panic disorder with agoraphobia, more attention to maladaptive cognition changes during cognitive behavioural therapy is warranted.

Structured Ordinary Least Squares: A Sufficient Dimension Reduction approach for regressions with partitioned predictors and heterogeneous units.

PubMed

Liu, Yang; Chiaromonte, Francesca; Li, Bing

2017-06-01

In many scientific and engineering fields, advanced experimental and computing technologies are producing data that are not just high dimensional, but also internally structured. For instance, statistical units may have heterogeneous origins from distinct studies or subpopulations, and features may be naturally partitioned based on experimental platforms generating them, or on information available about their roles in a given phenomenon. In a regression analysis, exploiting this known structure in the predictor dimension reduction stage that precedes modeling can be an effective way to integrate diverse data. To pursue this, we propose a novel Sufficient Dimension Reduction (SDR) approach that we call structured Ordinary Least Squares (sOLS). This combines ideas from existing SDR literature to merge reductions performed within groups of samples and/or predictors. In particular, it leads to a version of OLS for grouped predictors that requires far less computation than recently proposed groupwise SDR procedures, and provides an informal yet effective variable selection tool in these settings. We demonstrate the performance of sOLS by simulation and present a first application to genomic data. The R package "sSDR," publicly available on CRAN, includes all procedures necessary to implement the sOLS approach. © 2016, The International Biometric Society.

Organizing symmetry-protected topological phases by layering and symmetry reduction: A minimalist perspective

NASA Astrophysics Data System (ADS)

Xiong, Charles Zhaoxi; Alexandradinata, A.

2018-03-01

It is demonstrated that fermionic/bosonic symmetry-protected topological (SPT) phases across different dimensions and symmetry classes can be organized using geometric constructions that increase dimensions and symmetry-reduction maps that change symmetry groups. Specifically, it is shown that the interacting classifications of SPT phases with and without glide symmetry fit into a short exact sequence, so that the classification with glide is constrained to be a direct sum of cyclic groups of order 2 or 4. Applied to fermionic SPT phases in the Wigner-Dyson class AII, this implies that the complete interacting classification in the presence of glide is Z4⊕Z2⊕Z2 in three dimensions. In particular, the hourglass-fermion phase recently realized in the band insulator KHgSb must be robust to interactions. Generalizations to spatiotemporal glide symmetries are discussed.

Synthetic Minority Oversampling Technique and Fractal Dimension for Identifying Multiple Sclerosis

NASA Astrophysics Data System (ADS)

Zhang, Yu-Dong; Zhang, Yin; Phillips, Preetha; Dong, Zhengchao; Wang, Shuihua

Multiple sclerosis (MS) is a severe brain disease. Early detection can provide timely treatment. Fractal dimension can provide statistical index of pattern changes with scale at a given brain image. In this study, our team used susceptibility weighted imaging technique to obtain 676 MS slices and 880 healthy slices. We used synthetic minority oversampling technique to process the unbalanced dataset. Then, we used Canny edge detector to extract distinguishing edges. The Minkowski-Bouligand dimension was a fractal dimension estimation method and used to extract features from edges. Single hidden layer neural network was used as the classifier. Finally, we proposed a three-segment representation biogeography-based optimization to train the classifier. Our method achieved a sensitivity of 97.78±1.29%, a specificity of 97.82±1.60% and an accuracy of 97.80±1.40%. The proposed method is superior to seven state-of-the-art methods in terms of sensitivity and accuracy.

The attractor dimension of solar decimetric radio pulsations

NASA Technical Reports Server (NTRS)

Kurths, J.; Benz, A. O.; Aschwanden, M. J.

1991-01-01

The temporal characteristics of decimetric pulsations and related radio emissions during solar flares are analyzed using statistical methods recently developed for nonlinear dynamic systems. The results of the analysis is consistent with earlier reports on low-dimensional attractors of such events and yield a quantitative description of their temporal characteristics and hidden order. The estimated dimensions of typical decimetric pulsations are generally in the range of 3.0 + or - 0.5. Quasi-periodic oscillations and sudden reductions may have dimensions as low as 2. Pulsations of decimetric type IV continua have typically a dimension of about 4.

Design and Evaluation of Log-To-Dimension Manufacturing Systems Using System Simulation

Treesearch

Wenjie Lin; D. Earl Kline; Philip A. Araman; Janice K. Wiedenbeck

1995-01-01

In a recent study of alternative dimension manufacturing systems that produce green hardwood dimension directly fromlogs, it was observed that for Grade 2 and 3 red oak logs, up to 78 and 76 percent of the log scale volume could be converted into clear dimension parts. The potential high yields suggest that this processing system can be a promising technique for...

Digital processing of radiographic images

NASA Technical Reports Server (NTRS)

Bond, A. D.; Ramapriyan, H. K.

1973-01-01

Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

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

Krause, Josua; Dasgupta, Aritra; Fekete, Jean-Daniel

Dealing with the curse of dimensionality is a key challenge in high-dimensional data visualization. We present SeekAView to address three main gaps in the existing research literature. First, automated methods like dimensionality reduction or clustering suffer from a lack of transparency in letting analysts interact with their outputs in real-time to suit their exploration strategies. The results often suffer from a lack of interpretability, especially for domain experts not trained in statistics and machine learning. Second, exploratory visualization techniques like scatter plots or parallel coordinates suffer from a lack of visual scalability: it is difficult to present a coherent overviewmore » of interesting combinations of dimensions. Third, the existing techniques do not provide a flexible workflow that allows for multiple perspectives into the analysis process by automatically detecting and suggesting potentially interesting subspaces. In SeekAView we address these issues using suggestion based visual exploration of interesting patterns for building and refining multidimensional subspaces. Compared to the state-of-the-art in subspace search and visualization methods, we achieve higher transparency in showing not only the results of the algorithms, but also interesting dimensions calibrated against different metrics. We integrate a visually scalable design space with an iterative workflow guiding the analysts by choosing the starting points and letting them slice and dice through the data to find interesting subspaces and detect correlations, clusters, and outliers. We present two usage scenarios for demonstrating how SeekAView can be applied in real-world data analysis scenarios.« less

The Mechanisms Underlying Changes in Broad Dimensions of Psychopathology During Cognitive Behavioral Therapy for Social Anxiety Disorder.

PubMed

Ogawa, Sei; Imai, Risa; Suzuki, Masako; Furukawa, Toshi A; Akechi, Tatsuo

2017-12-01

Social anxiety disorder (SAD) patients commonly have broad dimensions of psychopathology. This study investigated the relationship between a wide range of psychopathology and attention or cognitions during cognitive behavioral therapy (CBT) for SAD. We treated 96 SAD patients with group CBT. Using multiple regression analysis, we examined the associations between the changes in broad dimensions of psychopathology and the changes in self-focused attention or maladaptive cognitions in the course of CBT. The reduction in self-focused attention was related to the decreases in somatization, obsessive-compulsive, interpersonal sensitivity, anxiety, phobic anxiety, and global severity index. The reduction in maladaptive cognitions was associated with decreases in interpersonal sensitivity, depression, and global severity index. The present study suggests that changes in self-focused attention and maladaptive cognitions may predict broad dimensions of psychopathology changes in SAD patients over the course of CBT. For the purpose of improving a wide range of psychiatric symptoms with SAD patients in CBT, it may be useful to decrease self-focus attention and maladaptive cognitions.

A Single-Molecule Barcoding System using Nanoslits for DNA Analysis

NASA Astrophysics Data System (ADS)

Jo, Kyubong; Schramm, Timothy M.; Schwartz, David C.

Single DNA molecule approaches are playing an increasingly central role in the analytical genomic sciences because single molecule techniques intrinsically provide individualized measurements of selected molecules, free from the constraints of bulk techniques, which blindly average noise and mask the presence of minor analyte components. Accordingly, a principal challenge that must be addressed by all single molecule approaches aimed at genome analysis is how to immobilize and manipulate DNA molecules for measurements that foster construction of large, biologically relevant data sets. For meeting this challenge, this chapter discusses an integrated approach for microfabricated and nanofabricated devices for the manipulation of elongated DNA molecules within nanoscale geometries. Ideally, large DNA coils stretch via nanoconfinement when channel dimensions are within tens of nanometers. Importantly, stretched, often immobilized, DNA molecules spanning hundreds of kilobase pairs are required by all analytical platforms working with large genomic substrates because imaging techniques acquire sequence information from molecules that normally exist in free solution as unrevealing random coils resembling floppy balls of yarn. However, nanoscale devices fabricated with sufficiently small dimensions fostering molecular stretching make these devices impractical because of the requirement of exotic fabrication technologies, costly materials, and poor operational efficiencies. In this chapter, such problems are addressed by discussion of a new approach to DNA presentation and analysis that establishes scaleable nanoconfinement conditions through reduction of ionic strength; stiffening DNA molecules thus enabling their arraying for analysis using easily fabricated devices that can also be mass produced. This new approach to DNA nanoconfinement is complemented by the development of a novel labeling scheme for reliable marking of individual molecules with fluorochrome labels, creating molecular barcodes, which are efficiently read using fluorescence resonance energy transfer techniques for minimizing noise from unincorporated labels. As such, our integrative approach for the realization of genomic analysis through nanoconfinement, named nanocoding, was demonstrated through the barcoding and mapping of bacterial artificial chromosomal molecules, thereby providing the basis for a high-throughput platform competent for whole genome investigations.

The Correlation Fractal Dimension of Complex Networks

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Liu, Zhenzhen; Wang, Mogei

2013-05-01

The fractality of complex networks is studied by estimating the correlation dimensions of the networks. Comparing with the previous algorithms of estimating the box dimension, our algorithm achieves a significant reduction in time complexity. For four benchmark cases tested, that is, the Escherichia coli (E. Coli) metabolic network, the Homo sapiens protein interaction network (H. Sapiens PIN), the Saccharomyces cerevisiae protein interaction network (S. Cerevisiae PIN) and the World Wide Web (WWW), experiments are provided to demonstrate the validity of our algorithm.

Counting conformal correlators

NASA Astrophysics Data System (ADS)

Kravchuk, Petr; Simmons-Duffin, David

2018-02-01

We introduce simple group-theoretic techniques for classifying conformallyinvariant tensor structures. With them, we classify tensor structures of general n-point functions of non-conserved operators, and n ≥ 4-point functions of general conserved currents, with or without permutation symmetries, and in any spacetime dimension d. Our techniques are useful for bootstrap applications. The rules we derive simultaneously count tensor structures for flat-space scattering amplitudes in d + 1 dimensions.

A Multidimensional Scaling Approach to Developmental Dimensions in Object Permanence and Tracking Stimuli.

ERIC Educational Resources Information Center

Townes-Rosenwein, Linda

This paper discusses a longitudinal, exploratory study of developmental dimensions related to object permanence theory and explains how multidimensional scaling techniques can be used to identify developmental dimensions. Eighty infants, randomly assigned to one of four experimental groups and one of four counterbalanced orders of stimuli, were…

Identification of seedling cabbages and weeds using hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Target detectionis one of research focues for precision chemical application. This study developed a method to identify seedling cabbages and weeds using hyperspectral spectral imaging. In processing the image data, with ENVI software, after dimension reduction, noise reduction, de-correlation for h...

Posterior dental size reduction in hominids: the Atapuerca evidence.

PubMed

Bermúdez de Castro, J M; Nicolas, M E

1995-04-01

In order to reassess previous hypotheses concerning dental size reduction of the posterior teeth during Pleistocene human evolution, current fossil dental evidence is examined. This evidence includes the large sample of hominid teeth found in recent excavations (1984-1993) in the Sima de los Huesos Middle Pleistocene cave site of the Sierra de Atapuerca (Burgos, Spain). The lower fourth premolars and molars of the Atapuerca hominids, probably older than 300 Kyr, have dimensions similar to those of modern humans. Further, these hominids share the derived state of other features of the posterior teeth with modern humans, such as a similar relative molar size and frequent absence of the hypoconulid, thus suggesting a possible case of parallelism. We believe that dietary changes allowed size reduction of the posterior teeth during the Middle Pleistocene, and the present evidence suggests that the selective pressures that operated on the size variability of these teeth were less restrictive than what is assumed by previous models of dental reduction. Thus, the causal relationship between tooth size decrease and changes in food-preparation techniques during the Pleistocene should be reconsidered. Moreover, the present evidence indicates that the differential reduction of the molars cannot be explained in terms of restriction of available growth space. The molar crown area measurements of a modern human sample were also investigated. The results of this study, as well as previous similar analyses, suggest that a decrease of the rate of cell proliferation, which affected the later-forming crown regions to a greater extent, may be the biological process responsible for the general and differential dental size reduction that occurred during human evolution.

Importance of the mitral apparatus for left ventricular function: an experimental approach.

PubMed

Gams, E; Hagl, S; Schad, H; Heimisch, W; Mendler, N; Sebening, F

1992-01-01

In an experimental study of 31 anesthetized dogs the importance of the mitral apparatus for the left ventricular function was investigated. During extracorporeal circulation bileaflet mitral valve prostheses were implanted preserving the mitral subvalvular apparatus. Flexible wires were slung around the chordae tendineae and exteriorized through the left ventricular wall to cut the chordae by electrocautery from the outside when the heart was beating again. External and internal left ventricular dimensions were measured by sonomicrometry, left ventricular stroke volume by electromagnetic flowmeters around the ascending aorta, left ventricular end-diastolic volume by dye dilution technique, and left ventricular pressure by catheter tip manometers. Different preload levels were achieved by volume loading with blood transfusion before and after cutting the chordae tendineae. When the chordae had been divided peak systolic left ventricular pressure did not change. Heart rate only increased at the lowest left ventricular end-diastolic pressures of 3-4 mmHg, but remained unchanged at higher preload levels. Cardiac output decreased significantly up to -9% at left ventricular end-diastolic pressures of 5-10 mmHg, while left ventricular dp/dtmax showed a consistent reduction of up to -15% at any preload level. Significant reductions were also seen in systolic shortening in the left ventricular major axis (by external measurements -27%, by internal recording -43%). Left ventricular end-diastolic dimensions increased in the major axis by +2% when recorded externally, by +10% when measured internally. Systolic and diastolic changes in the minor axis were not consistent and different in the external and internal recordings.(ABSTRACT TRUNCATED AT 250 WORDS)

Correlation Dimension Estimates of Global and Local Temperature Data.

NASA Astrophysics Data System (ADS)

Wang, Qiang

1995-11-01

The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

Chromatographic peak deconvolution of constitutional isomers by multiple-reaction-monitoring mass spectrometry.

PubMed

Trapp, Oliver

2010-02-12

Highly efficient and sophisticated separation techniques are available to analyze complex compound mixtures with superior sensitivities and selectivities often enhanced by a 2nd dimension, e.g. a separation technique or spectroscopic and spectrometric techniques. For enantioselective separations numerous chiral stationary phases (CSPs) exist to cover a broad range of chiral compounds. Despite these advances enantioselective separations can become very challenging for mixtures of stereolabile constitutional isomers, because the on-column interconversion can lead to completely overlapping peak profiles. Typically, multidimensional separation techniques, e.g. multidimensional GC (MDGC), using an achiral 1st separation dimension and transferring selected analytes to a chiral 2nd separation are the method of choice to approach such problems. However, this procedure is very time consuming and only predefined sections of peaks can be transferred by column switching to the second dimension. Here we demonstrate for stereolabile 1,2-dialkylated diaziridines a technique to experimentally deconvolute overlapping gas chromatographic elution profiles of constitutional isomers based on multiple-reaction-monitoring MS (MRM-MS). The here presented technique takes advantage of different fragmentation probabilities and pathways to isolate the elution profile of configurational isomers. Copyright 2009 Elsevier B.V. All rights reserved.

Fractal structures and fractal functions as disease indicators

USGS Publications Warehouse

Escos, J.M; Alados, C.L.; Emlen, J.M.

1995-01-01

Developmental instability is an early indicator of stress, and has been used to monitor the impacts of human disturbance on natural ecosystems. Here we investigate the use of different measures of developmental instability on two species, green peppers (Capsicum annuum), a plant, and Spanish ibex (Capra pyrenaica), an animal. For green peppers we compared the variance in allometric relationship between control plants, and a treatment group infected with the tomato spotted wilt virus. The results show that infected plants have a greater variance about the allometric regression line than the control plants. We also observed a reduction in complexity of branch structure in green pepper with a viral infection. Box-counting fractal dimension of branch architecture declined under stress infection. We also tested the reduction in complexity of behavioral patterns under stress situations in Spanish ibex (Capra pyrenaica). Fractal dimension of head-lift frequency distribution measures predator detection efficiency. This dimension decreased under stressful conditions, such as advanced pregnancy and parasitic infection. Feeding distribution activities reflect food searching efficiency. Power spectral analysis proves to be the most powerful tool for character- izing fractal behavior, revealing a reduction in complexity of time distribution activity under parasitic infection.

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Pattern classification using an olfactory model with PCA feature selection in electronic noses: study and application.

PubMed

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

Automated diagnosis of Alzheimer's disease with multi-atlas based whole brain segmentations

NASA Astrophysics Data System (ADS)

Luo, Yuan; Tang, Xiaoying

2017-03-01

Voxel-based analysis is widely used in quantitative analysis of structural brain magnetic resonance imaging (MRI) and automated disease detection, such as Alzheimer's disease (AD). However, noise at the voxel level may cause low sensitivity to AD-induced structural abnormalities. This can be addressed with the use of a whole brain structural segmentation approach which greatly reduces the dimension of features (the number of voxels). In this paper, we propose an automatic AD diagnosis system that combines such whole brain segmen- tations with advanced machine learning methods. We used a multi-atlas segmentation technique to parcellate T1-weighted images into 54 distinct brain regions and extract their structural volumes to serve as the features for principal-component-analysis-based dimension reduction and support-vector-machine-based classification. The relationship between the number of retained principal components (PCs) and the diagnosis accuracy was systematically evaluated, in a leave-one-out fashion, based on 28 AD subjects and 23 age-matched healthy subjects. Our approach yielded pretty good classification results with 96.08% overall accuracy being achieved using the three foremost PCs. In addition, our approach yielded 96.43% specificity, 100% sensitivity, and 0.9891 area under the receiver operating characteristic curve.

Application of the empirical orthogonal function to study the rainfall pattern in Daerah Istimewa Yogyakarta province

NASA Astrophysics Data System (ADS)

Adi-Kusumo, Fajar; Gunardi, Utami, Herni; Nurjani, Emilya; Sopaheluwakan, Ardhasena; Aluicius, Irwan Endrayanto; Christiawan, Titus

2016-02-01

We consider the Empirical Orthogonal Function (EOF) to study the rainfall pattern in Daerah Istimewa Yogyakarta (DIY) Province, Indonesia. The EOF is one of the important methods to study the dominant pattern of the data using dimension reduction technique. EOF makes possible to reduce the huge dimension of observed data into a smaller one without losing its significant information in order to figures the whole data. The methods is also known as Principal Components Analysis (PCA) which is conducted to find the pattern of the data. DIY Province is one of the province in Indonesia which has special characteristics related to the rainfall pattern. This province has an active volcano, karst, highlands, and also some lower area including beach. This province is bounded by the Indonesian ocean which is one of the important factor to provide the rainfall. We use at least ten years rainfall monthly data of all stations in this area and study the rainfall characteristics based on the four regencies of the province. EOF analysis is conducted to analyze data in order to decide the station groups which have similar characters.

Water Dynamics in Shewanella oneidensis at Ambient and High Pressure using Quasi-Elastic Neutron Scattering

NASA Astrophysics Data System (ADS)

Foglia, Fabrizia; Hazael, Rachael; Simeoni, Giovanna G.; Appavou, Marie-Sousai; Moulin, Martine; Haertlein, Michael; Trevor Forsyth, V.; Seydel, Tilo; Daniel, Isabelle; Meersman, Filip; McMillan, Paul F.

2016-01-01

Quasielastic neutron scattering (QENS) is an ideal technique for studying water transport and relaxation dynamics at pico- to nanosecond timescales and at length scales relevant to cellular dimensions. Studies of high pressure dynamic effects in live organisms are needed to understand Earth’s deep biosphere and biotechnology applications. Here we applied QENS to study water transport in Shewanella oneidensis at ambient (0.1 MPa) and high (200 MPa) pressure using H/D isotopic contrast experiments for normal and perdeuterated bacteria and buffer solutions to distinguish intracellular and transmembrane processes. The results indicate that intracellular water dynamics are comparable with bulk diffusion rates in aqueous fluids at ambient conditions but a significant reduction occurs in high pressure mobility. We interpret this as due to enhanced interactions with macromolecules in the nanoconfined environment. Overall diffusion rates across the cell envelope also occur at similar rates but unexpected narrowing of the QENS signal appears between momentum transfer values Q = 0.7-1.1 Å-1 corresponding to real space dimensions of 6-9 Å. The relaxation time increase can be explained by correlated dynamics of molecules passing through Aquaporin water transport complexes located within the inner or outer membrane structures.

Heat kernel and Weyl anomaly of Schrödinger invariant theory

NASA Astrophysics Data System (ADS)

Pal, Sridip; Grinstein, Benjamín

2017-12-01

We propose a method inspired by discrete light cone quantization to determine the heat kernel for a Schrödinger field theory (Galilean boost invariant with z =2 anisotropic scaling symmetry) living in d +1 dimensions, coupled to a curved Newton-Cartan background, starting from a heat kernel of a relativistic conformal field theory (z =1 ) living in d +2 dimensions. We use this method to show that the Schrödinger field theory of a complex scalar field cannot have any Weyl anomalies. To be precise, we show that the Weyl anomaly Ad+1 G for Schrödinger theory is related to the Weyl anomaly of a free relativistic scalar CFT Ad+2 R via Ad+1 G=2 π δ (m )Ad+2 R , where m is the charge of the scalar field under particle number symmetry. We provide further evidence of the vanishing anomaly by evaluating Feynman diagrams in all orders of perturbation theory. We present an explicit calculation of the anomaly using a regulated Schrödinger operator, without using the null cone reduction technique. We generalize our method to show that a similar result holds for theories with a single time-derivative and with even z >2 .

Water Dynamics in Shewanella oneidensis at Ambient and High Pressure using Quasi-Elastic Neutron Scattering.

PubMed

Foglia, Fabrizia; Hazael, Rachael; Simeoni, Giovanna G; Appavou, Marie-Sousai; Moulin, Martine; Haertlein, Michael; Trevor Forsyth, V; Seydel, Tilo; Daniel, Isabelle; Meersman, Filip; McMillan, Paul F

2016-01-07

Quasielastic neutron scattering (QENS) is an ideal technique for studying water transport and relaxation dynamics at pico- to nanosecond timescales and at length scales relevant to cellular dimensions. Studies of high pressure dynamic effects in live organisms are needed to understand Earth's deep biosphere and biotechnology applications. Here we applied QENS to study water transport in Shewanella oneidensis at ambient (0.1 MPa) and high (200 MPa) pressure using H/D isotopic contrast experiments for normal and perdeuterated bacteria and buffer solutions to distinguish intracellular and transmembrane processes. The results indicate that intracellular water dynamics are comparable with bulk diffusion rates in aqueous fluids at ambient conditions but a significant reduction occurs in high pressure mobility. We interpret this as due to enhanced interactions with macromolecules in the nanoconfined environment. Overall diffusion rates across the cell envelope also occur at similar rates but unexpected narrowing of the QENS signal appears between momentum transfer values Q = 0.7-1.1 Å(-1) corresponding to real space dimensions of 6-9 Å. The relaxation time increase can be explained by correlated dynamics of molecules passing through Aquaporin water transport complexes located within the inner or outer membrane structures.

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

Aliev, Alikram N.; Cebeci, Hakan; Dereli, Tekin

We present an exact solution describing a stationary and axisymmetric object with electromagnetic and dilaton fields. The solution generalizes the usual Kerr-Taub-NUT (Newman-Unti-Tamburino) spacetime in general relativity and is obtained by boosting this spacetime in the fifth dimension and performing a Kaluza-Klein reduction to four dimensions. We also discuss the physical parameters of this solution and calculate its gyromagnetic ratio.

Old Tails and New Trails in High Dimensions

ERIC Educational Resources Information Center

Halevy, Avner

2013-01-01

We discuss the motivation for dimension reduction in the context of the modern data revolution and introduce a key result in this field, the Johnson-Lindenstrauss flattening lemma. Then we leap into high-dimensional space for a glimpse of the phenomenon called concentration of measure, and use it to sketch a proof of the lemma. We end by tying…

Contributing Factors to Driver's Over-trust in a Driving Support System for Workload Reduction

NASA Astrophysics Data System (ADS)

Itoh, Makoto

Avoiding over-trust in machines is a vital issue in order to establish intelligent driver support systems. It is necessary to distinguish systems for workload reduction from systems for accident prevention/mitigation. This study focuses on over-trust in an Adaptive Cruise Control (ACC) system as a typical driving support system for workload reduction. By conducting an experiment, we obtained a case in which a driver trusted the ACC system too much. Concretely speaking, the driver just watched the ACC system crashing into a stopped car even though the ACC system was designed to ignore such stopped cars. This paper investigates possible contributing factors to the driver' s over-trust in the ACC system. The results suggest that emerging trust in the dimension of performance may cause over-trust in the dimension of method or purpose.

A novel approach for dimension reduction of microarray.

PubMed

Aziz, Rabia; Verma, C K; Srivastava, Namita

2017-12-01

This paper proposes a new hybrid search technique for feature (gene) selection (FS) using Independent component analysis (ICA) and Artificial Bee Colony (ABC) called ICA+ABC, to select informative genes based on a Naïve Bayes (NB) algorithm. An important trait of this technique is the optimization of ICA feature vector using ABC. ICA+ABC is a hybrid search algorithm that combines the benefits of extraction approach, to reduce the size of data and wrapper approach, to optimize the reduced feature vectors. This hybrid search technique is facilitated by evaluating the performance of ICA+ABC on six standard gene expression datasets of classification. Extensive experiments were conducted to compare the performance of ICA+ABC with the results obtained from recently published Minimum Redundancy Maximum Relevance (mRMR) +ABC algorithm for NB classifier. Also to check the performance that how ICA+ABC works as feature selection with NB classifier, compared the combination of ICA with popular filter techniques and with other similar bio inspired algorithm such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The result shows that ICA+ABC has a significant ability to generate small subsets of genes from the ICA feature vector, that significantly improve the classification accuracy of NB classifier compared to other previously suggested methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Partial Fourier techniques in single-shot cross-term spatiotemporal encoded MRI.

PubMed

Zhang, Zhiyong; Frydman, Lucio

2018-03-01

Cross-term spatiotemporal encoding (xSPEN) is a single-shot approach with exceptional immunity to field heterogeneities, the images of which faithfully deliver 2D spatial distributions without requiring a priori information or using postacquisition corrections. xSPEN, however, suffers from signal-to-noise ratio penalties due to its non-Fourier nature and due to diffusion losses-especially when seeking high resolution. This study explores partial Fourier transform approaches that, acting along either the readout or the spatiotemporally encoded dimensions, reduce these penalties. xSPEN uses an orthogonal (e.g., z) gradient to read, in direct space, the low-bandwidth (e.g., y) dimension. This substantially changes the nature of partial Fourier acquisitions vis-à-vis conventional imaging counterparts. A suitable theoretical analysis is derived to implement these procedures, along either the spatiotemporally or readout axes. Partial Fourier single-shot xSPEN images were recorded on preclinical and human scanners. Owing to their reduction in the experiments' acquisition times, this approach provided substantial sensitivity gains vis-à-vis previous implementations for a given targeted in-plane resolution. The physical origins of these gains are explained. Partial Fourier approaches, particularly when implemented along the low-bandwidth spatiotemporal dimension, provide several-fold sensitivity advantages at minimal costs to the execution and processing of the single-shot experiments. Magn Reson Med 79:1506-1514, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A principled dimension-reduction method for the population density approach to modeling networks of neurons with synaptic dynamics.

PubMed

Ly, Cheng

2013-10-01

The population density approach to neural network modeling has been utilized in a variety of contexts. The idea is to group many similar noisy neurons into populations and track the probability density function for each population that encompasses the proportion of neurons with a particular state rather than simulating individual neurons (i.e., Monte Carlo). It is commonly used for both analytic insight and as a time-saving computational tool. The main shortcoming of this method is that when realistic attributes are incorporated in the underlying neuron model, the dimension of the probability density function increases, leading to intractable equations or, at best, computationally intensive simulations. Thus, developing principled dimension-reduction methods is essential for the robustness of these powerful methods. As a more pragmatic tool, it would be of great value for the larger theoretical neuroscience community. For exposition of this method, we consider a single uncoupled population of leaky integrate-and-fire neurons receiving external excitatory synaptic input only. We present a dimension-reduction method that reduces a two-dimensional partial differential-integral equation to a computationally efficient one-dimensional system and gives qualitatively accurate results in both the steady-state and nonequilibrium regimes. The method, termed modified mean-field method, is based entirely on the governing equations and not on any auxiliary variables or parameters, and it does not require fine-tuning. The principles of the modified mean-field method have potential applicability to more realistic (i.e., higher-dimensional) neural networks.

WavePacket: A Matlab package for numerical quantum dynamics.II: Open quantum systems, optimal control, and model reduction

NASA Astrophysics Data System (ADS)

Schmidt, Burkhard; Hartmann, Carsten

2018-07-01

WavePacket is an open-source program package for numeric simulations in quantum dynamics. It can solve time-independent or time-dependent linear Schrödinger and Liouville-von Neumann-equations in one or more dimensions. Also coupled equations can be treated, which allows, e.g., to simulate molecular quantum dynamics beyond the Born-Oppenheimer approximation. Optionally accounting for the interaction with external electric fields within the semi-classical dipole approximation, WavePacket can be used to simulate experiments involving tailored light pulses in photo-induced physics or chemistry. Being highly versatile and offering visualization of quantum dynamics 'on the fly', WavePacket is well suited for teaching or research projects in atomic, molecular and optical physics as well as in physical or theoretical chemistry. Building on the previous Part I [Comp. Phys. Comm. 213, 223-234 (2017)] which dealt with closed quantum systems and discrete variable representations, the present Part II focuses on the dynamics of open quantum systems, with Lindblad operators modeling dissipation and dephasing. This part also describes the WavePacket function for optimal control of quantum dynamics, building on rapid monotonically convergent iteration methods. Furthermore, two different approaches to dimension reduction implemented in WavePacket are documented here. In the first one, a balancing transformation based on the concepts of controllability and observability Gramians is used to identify states that are neither well controllable nor well observable. Those states are either truncated or averaged out. In the other approach, the H2-error for a given reduced dimensionality is minimized by H2 optimal model reduction techniques, utilizing a bilinear iterative rational Krylov algorithm. The present work describes the MATLAB version of WavePacket 5.3.0 which is hosted and further developed at the Sourceforge platform, where also extensive Wiki-documentation as well as numerous worked-out demonstration examples with animated graphics can be found.

Quantum Field Theory in (0 + 1) Dimensions

ERIC Educational Resources Information Center

Boozer, A. D.

2007-01-01

We show that many of the key ideas of quantum field theory can be illustrated simply and straightforwardly by using toy models in (0 + 1) dimensions. Because quantum field theory in (0 + 1) dimensions is equivalent to quantum mechanics, these models allow us to use techniques from quantum mechanics to gain insight into quantum field theory. In…

Constrained Metric Learning by Permutation Inducing Isometries.

PubMed

Bosveld, Joel; Mahmood, Arif; Huynh, Du Q; Noakes, Lyle

2016-01-01

The choice of metric critically affects the performance of classification and clustering algorithms. Metric learning algorithms attempt to improve performance, by learning a more appropriate metric. Unfortunately, most of the current algorithms learn a distance function which is not invariant to rigid transformations of images. Therefore, the distances between two images and their rigidly transformed pair may differ, leading to inconsistent classification or clustering results. We propose to constrain the learned metric to be invariant to the geometry preserving transformations of images that induce permutations in the feature space. The constraint that these transformations are isometries of the metric ensures consistent results and improves accuracy. Our second contribution is a dimension reduction technique that is consistent with the isometry constraints. Our third contribution is the formulation of the isometry constrained logistic discriminant metric learning (IC-LDML) algorithm, by incorporating the isometry constraints within the objective function of the LDML algorithm. The proposed algorithm is compared with the existing techniques on the publicly available labeled faces in the wild, viewpoint-invariant pedestrian recognition, and Toy Cars data sets. The IC-LDML algorithm has outperformed existing techniques for the tasks of face recognition, person identification, and object classification by a significant margin.

Volumetric visualization of 3D data

NASA Technical Reports Server (NTRS)

Russell, Gregory; Miles, Richard

1989-01-01

In recent years, there has been a rapid growth in the ability to obtain detailed data on large complex structures in three dimensions. This development occurred first in the medical field, with CAT (computer aided tomography) scans and now magnetic resonance imaging, and in seismological exploration. With the advances in supercomputing and computational fluid dynamics, and in experimental techniques in fluid dynamics, there is now the ability to produce similar large data fields representing 3D structures and phenomena in these disciplines. These developments have produced a situation in which currently there is access to data which is too complex to be understood using the tools available for data reduction and presentation. Researchers in these areas are becoming limited by their ability to visualize and comprehend the 3D systems they are measuring and simulating.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1980-01-01

To facilitate comparison between the four different spatial resolution of the NS-001 MSS data sets, a supervised approach was taken in defining training blocks for each of the different cover types. The training fields representing each cover type category were grouped and this group was clustered to determine the individual spectral classes within each cover type category which would effectively characterize the entire test site. Graphs show the variation in spectral response level with respect to distance in the across track dimension for four sampling intervals. Radar digitization procedures were developd. Flight characteristics and parameters for digitization of radar imagery are tabulated. The statement of work for phase 3 was reviewed and modifications were suggested to meet funding reduction.

A predictor-corrector technique for visualizing unsteady flow

NASA Technical Reports Server (NTRS)

Banks, David C.; Singer, Bart A.

1995-01-01

We present a method for visualizing unsteady flow by displaying its vortices. The vortices are identified by using a vorticity-predictor pressure-corrector scheme that follows vortex cores. The cross-sections of a vortex at each point along the core can be represented by a Fourier series. A vortex can be faithfully reconstructed from the series as a simple quadrilateral mesh, or its reconstruction can be enhanced to indicate helical motion. The mesh can reduce the representation of the flow features by a factor of one thousand or more compared with the volumetric dataset. With this amount of reduction it is possible to implement an interactive system on a graphics workstation to permit a viewer to examine, in three dimensions, the evolution of the vortical structures in a complex, unsteady flow.

Creating metamaterial building blocks with directed photochemical metallization of silver onto DNA origami templates.

PubMed

Hossen, Md Mir; Bendickson, Lee; Palo, Pierre E; Yao, Zhiqi; Nilsen-Hamilton, Marit; Hillier, Andrew C

2018-08-31

DNA origami can be used to create a variety of complex and geometrically unique nanostructures that can be further modified to produce building blocks for applications such as in optical metamaterials. We describe a method for creating metal-coated nanostructures using DNA origami templates and a photochemical metallization technique. Triangular DNA origami forms were fabricated and coated with a thin metal layer by photochemical silver reduction while in solution or supported on a surface. The DNA origami template serves as a localized photosensitizer to facilitate reduction of silver ions directly from solution onto the DNA surface. The metallizing process is shown to result in a conformal metal coating, which grows in height to a self-limiting value with increasing photoreduction steps. Although this coating process results in a slight decrease in the triangle dimensions, the overall template shape is retained. Notably, this coating method exhibits characteristics of self-limiting and defect-filling growth, which results in a metal nanostructure that maps the shape of the original DNA template with a continuous and uniform metal layer and stops growing once all available DNA sites are exhausted.

Network embedding-based representation learning for single cell RNA-seq data.

PubMed

Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

2017-11-02

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap.

PubMed

Spiwok, Vojtěch; Králová, Blanka

2011-12-14

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling. © 2011 American Institute of Physics

Inflation from extra dimensions

NASA Astrophysics Data System (ADS)

Levin, Janna J.

1995-02-01

A gravity-driven inflation is shown to arise from a simple higher-dimensional universe. In vacuum, the shear of n > 1 contracting dimensions is able to inflate the remaining three spatial dimensions. Said another way, the expansion of the 3-volume is accelerated by the contraction of the n-volume. Upon dimensional reduction, the theory is equivalent to a four-dimensional cosmology with a dynamical Planck mass. A connection can therefore be made to recent examples of inflation powered by a dilaton kinetic energy. Unfortunately, the graceful exit problem encountered in dilaton cosmologies will haunt this cosmology as well.

Development of Elderly Quality of Life Index – Eqoli: Item Reduction and Distribution into Dimensions

PubMed Central

Paschoal, Sérgio Márcio Pacheco; Filho, Wilson Jacob; Litvoc, Júlio

2008-01-01

OBJECTIVE To describe item reduction and its distribution into dimensions in the construction process of a quality of life evaluation instrument for the elderly. METHODS The sampling method was chosen by convenience through quotas, with selection of elderly subjects from four programs to achieve heterogeneity in the “health status”, “functional capacity”, “gender”, and “age” variables. The Clinical Impact Method was used, consisting of the spontaneous and elicited selection by the respondents of relevant items to the construct Quality of Life in Old Age from a previously elaborated item pool. The respondents rated each item’s importance using a 5-point Likert scale. The product of the proportion of elderly selecting the item as relevant (frequency) and the mean importance score they attributed to it (importance) represented the overall impact of that item in their quality of life (impact). The items were ordered according to their impact scores and the top 46 scoring items were grouped in dimensions by three experts. A review of the negative items was performed. RESULTS One hundred and ninety three people (122 women and 71 men) were interviewed. Experts distributed the 46 items into eight dimensions. Closely related items were grouped and dimensions not reaching the minimum expected number of items received additional items resulting in eight dimensions and 43 items. DISCUSSION The sample was heterogeneous and similar to what was expected. The dimensions and items demonstrated the multidimensionality of the construct. The Clinical Impact Method was appropriate to construct the instrument, which was named Elderly Quality of Life Index - EQoLI. An accuracy process will be examined in the future. PMID:18438571

Rapid, High-Throughput Tracking of Bacterial Motility in 3D via Phase-Contrast Holographic Video Microscopy

PubMed Central

Cheong, Fook Chiong; Wong, Chui Ching; Gao, YunFeng; Nai, Mui Hoon; Cui, Yidan; Park, Sungsu; Kenney, Linda J.; Lim, Chwee Teck

2015-01-01

Tracking fast-swimming bacteria in three dimensions can be extremely challenging with current optical techniques and a microscopic approach that can rapidly acquire volumetric information is required. Here, we introduce phase-contrast holographic video microscopy as a solution for the simultaneous tracking of multiple fast moving cells in three dimensions. This technique uses interference patterns formed between the scattered and the incident field to infer the three-dimensional (3D) position and size of bacteria. Using this optical approach, motility dynamics of multiple bacteria in three dimensions, such as speed and turn angles, can be obtained within minutes. We demonstrated the feasibility of this method by effectively tracking multiple bacteria species, including Escherichia coli, Agrobacterium tumefaciens, and Pseudomonas aeruginosa. In addition, we combined our fast 3D imaging technique with a microfluidic device to present an example of a drug/chemical assay to study effects on bacterial motility. PMID:25762336

Ultrasonic geometrical characterization of periodically corrugated surfaces.

PubMed

Liu, Jingfei; Declercq, Nico F

2013-04-01

Accurate characterization of the characteristic dimensions of a periodically corrugated surface using ultrasonic imaging technique is investigated both theoretically and experimentally. The possibility of accurately characterizing the characteristic dimensions is discussed. The condition for accurate characterization and the quantitative relationship between the accuracy and its determining parameters are given. The strategies to avoid diffraction effects instigated by the periodical nature of a corrugated surface are also discussed. Major causes of erroneous measurements are theoretically discussed and experimentally illustrated. A comparison is made between the presented results and the optical measurements, revealing acceptable agreement. This work realistically exposes the capability of the proposed ultrasonic technique to accurately characterize the lateral and vertical characteristic dimensions of corrugated surfaces. Both the general principles developed theoretically as well as the proposed practical techniques may serve as useful guidelines to peers. Copyright © 2012 Elsevier B.V. All rights reserved.

The Use of Expressive Techniques in Counseling

ERIC Educational Resources Information Center

Bradley, Loretta J.; Whiting, Peggy; Hendricks, Bret; Parr, Gerald; Jones, Eugene Gordon, Jr.

2008-01-01

This manuscript explores and identifies the use of expressive techniques in counseling. Although verbal techniques are important, sometimes the best of verbal techniques are not sufficient. Creative, expressive techniques can add a new, important dimension to counseling. Such expressive techniques as cinema, art, and music are described to help…

Critical behavior and dimension crossover of pion superfluidity

NASA Astrophysics Data System (ADS)

Wang, Ziyue; Zhuang, Pengfei

2016-09-01

We investigate the critical behavior of pion superfluidity in the framework of the functional renormalization group (FRG). By solving the flow equations in the SU(2) linear sigma model at finite temperature and isospin density, and making comparison with the fixed point analysis of a general O (N ) system with continuous dimension, we find that the pion superfluidity is a second order phase transition subject to an O (2 ) universality class with a dimension crossover from dc=4 to dc=3 . This phenomenon provides a concrete example of dimension reduction in thermal field theory. The large-N expansion gives a temperature independent critical exponent β and agrees with the FRG result only at zero temperature.

Bootstrapping rapidity anomalous dimensions for transverse-momentum resummation

DOE PAGES

Li, Ye; Zhu, Hua Xing

2017-01-11

Soft function relevant for transverse-momentum resummation for Drell-Yan or Higgs production at hadron colliders are computed through to three loops in the expansion of strong coupling, with the help of bootstrap technique and supersymmetric decomposition. The corresponding rapidity anomalous dimension is extracted. Furthermore, an intriguing relation between anomalous dimensions for transverse-momentum resummation and threshold resummation is found.

Dimensions of Quality in Teacher Education: Perception and Practices of Teacher Educators in the Universities of Sindh, Pakistan

ERIC Educational Resources Information Center

Sahito, Zafarullah; Vaisanen, Pertti

2017-01-01

This study was conducted to explore the dimensions of quality education in teacher education departments at universities of Sindh province of Pakistan. The qualitative research approach was employed for data collection and then analysed through thematic-narrative analysis technique. The total eight dimensions of quality were found, as two were…

Human Dimensions in Future Battle Command Systems: A Workshop Report

DTIC Science & Technology

2008-04-01

information processing). These dimensions can best be described anecdotally and metaphorically as: • Battle command is a human-centric...enhance information visualization techniques in the decision tools, including multimodal platforms: video, graphics, symbols, etc. This should be...organization members. Each dimension can metaphorically represent the spatial location of individuals and group thinking in a trajectory of social norms

Dimension Reduction of Hyperspectral Data on Beowulf Clusters

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek

2000-01-01

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operation. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold a great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, which is used widely in remote sensing, is the Principal Components Analysis (PCA). In light of the growing number of spectral channels of modern instruments, the paper reports on the development of a parallel PCA and its implementation on two Beowulf cluster configurations, on with fast Ethernet switch and the other is with a Myrinet interconnection.

Truncated Painlevé expansion: Tanh-traveling wave solutions and reduction of sine-Poisson equation to a quadrature for stationary and nonstationary three-dimensional collisionless cold plasma

NASA Astrophysics Data System (ADS)

Ibrahim, R. S.; El-Kalaawy, O. H.

2006-10-01

The relativistic nonlinear self-consistent equations for a collisionless cold plasma with stationary ions [R. S. Ibrahim, IMA J. Appl. Math. 68, 523 (2003)] are extended to 3 and 3+1 dimensions. The resulting system of equations is reduced to the sine-Poisson equation. The truncated Painlevé expansion and reduction of the partial differential equation to a quadrature problem (RQ method) are described and applied to obtain the traveling wave solutions of the sine-Poisson equation for stationary and nonstationary equations in 3 and 3+1 dimensions describing the charge-density equilibrium configuration model.

Segmentation, classification, and pose estimation of military vehicles in low resolution laser radar images

NASA Astrophysics Data System (ADS)

Neulist, Joerg; Armbruster, Walter

2005-05-01

Model-based object recognition in range imagery typically involves matching the image data to the expected model data for each feasible model and pose hypothesis. Since the matching procedure is computationally expensive, the key to efficient object recognition is the reduction of the set of feasible hypotheses. This is particularly important for military vehicles, which may consist of several large moving parts such as the hull, turret, and gun of a tank, and hence require an eight or higher dimensional pose space to be searched. The presented paper outlines techniques for reducing the set of feasible hypotheses based on an estimation of target dimensions and orientation. Furthermore, the presence of a turret and a main gun and their orientations are determined. The vehicle parts dimensions as well as their error estimates restrict the number of model hypotheses whereas the position and orientation estimates and their error bounds reduce the number of pose hypotheses needing to be verified. The techniques are applied to several hundred laser radar images of eight different military vehicles with various part classifications and orientations. On-target resolution in azimuth, elevation and range is about 30 cm. The range images contain up to 20% dropouts due to atmospheric absorption. Additionally some target retro-reflectors produce outliers due to signal crosstalk. The presented algorithms are extremely robust with respect to these and other error sources. The hypothesis space for hull orientation is reduced to about 5 degrees as is the error for turret rotation and gun elevation, provided the main gun is visible.

A dimension reduction strategy for improving the efficiency of computer-aided detection for CT colonography

NASA Astrophysics Data System (ADS)

Song, Bowen; Zhang, Guopeng; Wang, Huafeng; Zhu, Wei; Liang, Zhengrong

2013-02-01

Various types of features, e.g., geometric features, texture features, projection features etc., have been introduced for polyp detection and differentiation tasks via computer aided detection and diagnosis (CAD) for computed tomography colonography (CTC). Although these features together cover more information of the data, some of them are statistically highly-related to others, which made the feature set redundant and burdened the computation task of CAD. In this paper, we proposed a new dimension reduction method which combines hierarchical clustering and principal component analysis (PCA) for false positives (FPs) reduction task. First, we group all the features based on their similarity using hierarchical clustering, and then PCA is employed within each group. Different numbers of principal components are selected from each group to form the final feature set. Support vector machine is used to perform the classification. The results show that when three principal components were chosen from each group we can achieve an area under the curve of receiver operating characteristics of 0.905, which is as high as the original dataset. Meanwhile, the computation time is reduced by 70% and the feature set size is reduce by 77%. It can be concluded that the proposed method captures the most important information of the feature set and the classification accuracy is not affected after the dimension reduction. The result is promising and further investigation, such as automatically threshold setting, are worthwhile and are under progress.

Top-down constraints on global N2O emissions at optimal resolution: application of a new dimension reduction technique

NASA Astrophysics Data System (ADS)

Wells, Kelley C.; Millet, Dylan B.; Bousserez, Nicolas; Henze, Daven K.; Griffis, Timothy J.; Chaliyakunnel, Sreelekha; Dlugokencky, Edward J.; Saikawa, Eri; Xiang, Gao; Prinn, Ronald G.; O'Doherty, Simon; Young, Dickon; Weiss, Ray F.; Dutton, Geoff S.; Elkins, James W.; Krummel, Paul B.; Langenfelds, Ray; Steele, L. Paul

2018-01-01

We present top-down constraints on global monthly N2O emissions for 2011 from a multi-inversion approach and an ensemble of surface observations. The inversions employ the GEOS-Chem adjoint and an array of aggregation strategies to test how well current observations can constrain the spatial distribution of global N2O emissions. The strategies include (1) a standard 4D-Var inversion at native model resolution (4° × 5°), (2) an inversion for six continental and three ocean regions, and (3) a fast 4D-Var inversion based on a novel dimension reduction technique employing randomized singular value decomposition (SVD). The optimized global flux ranges from 15.9 Tg N yr-1 (SVD-based inversion) to 17.5-17.7 Tg N yr-1 (continental-scale, standard 4D-Var inversions), with the former better capturing the extratropical N2O background measured during the HIAPER Pole-to-Pole Observations (HIPPO) airborne campaigns. We find that the tropics provide a greater contribution to the global N2O flux than is predicted by the prior bottom-up inventories, likely due to underestimated agricultural and oceanic emissions. We infer an overestimate of natural soil emissions in the extratropics and find that predicted emissions are seasonally biased in northern midlatitudes. Here, optimized fluxes exhibit a springtime peak consistent with the timing of spring fertilizer and manure application, soil thawing, and elevated soil moisture. Finally, the inversions reveal a major emission underestimate in the US Corn Belt in the bottom-up inventory used here. We extensively test the impact of initial conditions on the analysis and recommend formally optimizing the initial N2O distribution to avoid biasing the inferred fluxes. We find that the SVD-based approach provides a powerful framework for deriving emission information from N2O observations: by defining the optimal resolution of the solution based on the information content of the inversion, it provides spatial information that is lost when aggregating to political or geographic regions, while also providing more temporal information than a standard 4D-Var inversion.

Predictive spectroscopy and chemical imaging based on novel optical systems

NASA Astrophysics Data System (ADS)

Nelson, Matthew Paul

1998-10-01

This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first-order spectroscopic images, bivariate first-order spectroscopic images, and multivariate first-order spectroscopic images of the temporal development of laser-induced plumes are presented and interpreted. Reconstructed chemical images generated using bivariate and trivariate wavelength techniques, bimodal and trimodal PCA methods, and bimodal and trimodal ITTFA approaches are also included.

Reduction theorems for optimal unambiguous state discrimination of density matrices

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

Raynal, Philippe; Luetkenhaus, Norbert; Enk, Steven J. van

2003-08-01

We present reduction theorems for the problem of optimal unambiguous state discrimination of two general density matrices. We show that this problem can be reduced to that of two density matrices that have the same rank n and are described in a Hilbert space of dimensions 2n. We also show how to use the reduction theorems to discriminate unambiguously between N mixed states (N{>=}2)

The staircase method: integrals for periodic reductions of integrable lattice equations

NASA Astrophysics Data System (ADS)

van der Kamp, Peter H.; Quispel, G. R. W.

2010-11-01

We show, in full generality, that the staircase method (Papageorgiou et al 1990 Phys. Lett. A 147 106-14, Quispel et al 1991 Physica A 173 243-66) provides integrals for mappings, and correspondences, obtained as traveling wave reductions of (systems of) integrable partial difference equations. We apply the staircase method to a variety of equations, including the Korteweg-De Vries equation, the five-point Bruschi-Calogero-Droghei equation, the quotient-difference (QD)-algorithm and the Boussinesq system. We show that, in all these cases, if the staircase method provides r integrals for an n-dimensional mapping, with 2r, then one can introduce q <= 2r variables, which reduce the dimension of the mapping from n to q. These dimension-reducing variables are obtained as joint invariants of k-symmetries of the mappings. Our results support the idea that often the staircase method provides sufficiently many integrals for the periodic reductions of integrable lattice equations to be completely integrable. We also study reductions on other quad-graphs than the regular {\\ Z}^2 lattice, and we prove linear growth of the multi-valuedness of iterates of high-dimensional correspondences obtained as reductions of the QD-algorithm.

QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION.

PubMed

Fan, Jianqing; Ke, Zheng Tracy; Liu, Han; Xia, Lucy

We propose a novel Rayleigh quotient based sparse quadratic dimension reduction method-named QUADRO (Quadratic Dimension Reduction via Rayleigh Optimization)-for analyzing high-dimensional data. Unlike in the linear setting where Rayleigh quotient optimization coincides with classification, these two problems are very different under nonlinear settings. In this paper, we clarify this difference and show that Rayleigh quotient optimization may be of independent scientific interests. One major challenge of Rayleigh quotient optimization is that the variance of quadratic statistics involves all fourth cross-moments of predictors, which are infeasible to compute for high-dimensional applications and may accumulate too many stochastic errors. This issue is resolved by considering a family of elliptical models. Moreover, for heavy-tail distributions, robust estimates of mean vectors and covariance matrices are employed to guarantee uniform convergence in estimating non-polynomially many parameters, even though only the fourth moments are assumed. Methodologically, QUADRO is based on elliptical models which allow us to formulate the Rayleigh quotient maximization as a convex optimization problem. Computationally, we propose an efficient linearized augmented Lagrangian method to solve the constrained optimization problem. Theoretically, we provide explicit rates of convergence in terms of Rayleigh quotient under both Gaussian and general elliptical models. Thorough numerical results on both synthetic and real datasets are also provided to back up our theoretical results.

Partial Least Squares for Discrimination in fMRI Data

PubMed Central

Andersen, Anders H.; Rayens, William S.; Liu, Yushu; Smith, Charles D.

2011-01-01

Multivariate methods for discrimination were used in the comparison of brain activation patterns between groups of cognitively normal women who are at either high or low Alzheimer's disease risk based on family history and apolipoprotein-E4 status. Linear discriminant analysis (LDA) was preceded by dimension reduction using either principal component analysis (PCA), partial least squares (PLS), or a new oriented partial least squares (OrPLS) method. The aim was to identify a spatial pattern of functionally connected brain regions that was differentially expressed by the risk groups and yielded optimal classification accuracy. Multivariate dimension reduction is required prior to LDA when the data contains more feature variables than there are observations on individual subjects. Whereas PCA has been commonly used to identify covariance patterns in neuroimaging data, this approach only identifies gross variability and is not capable of distinguishing among-groups from within-groups variability. PLS and OrPLS provide a more focused dimension reduction by incorporating information on class structure and therefore lead to more parsimonious models for discrimination. Performance was evaluated in terms of the cross-validated misclassification rates. The results support the potential of using fMRI as an imaging biomarker or diagnostic tool to discriminate individuals with disease or high risk. PMID:22227352

The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction

PubMed Central

Williamson, Ross S.; Sahani, Maneesh; Pillow, Jonathan W.

2015-01-01

Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron’s probability of spiking. One popular method, known as maximally informative dimensions (MID), uses an information-theoretic quantity known as “single-spike information” to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP) model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex. PMID:25831448

Nuclear patterns of human breast cancer cells during apoptosis: characterisation by fractal dimension and co-occurrence matrix statistics.

PubMed

Losa, Gabriele A; Castelli, Christian

2005-11-01

An analytical strategy combining fractal geometry and grey-level co-occurrence matrix (GLCM) statistics was devised to investigate ultrastructural changes in oestrogen-insensitive SK-BR3 human breast cancer cells undergoing apoptosis in vitro. Apoptosis was induced by 1 microM calcimycin (A23187 Ca(2+) ionophore) and assessed by measuring conventional cellular parameters during the culture period. SK-BR3 cells entered the early stage of apoptosis within 24 h of treatment with calcimycin, which induced detectable changes in nuclear components, as documented by increased values of most GLCM parameters and by the general reduction of the fractal dimensions. In these affected cells, morphonuclear traits were accompanied by the reduction of distinct gangliosides and loss of unidentifiable glycolipid molecules at the cell surface. All these changes were shown to be involved in apoptosis before the detection of conventional markers, which were only measurable during the active phases of apoptotic cell death. In overtly apoptotic cells treated with 1 microM calcimycin for 72 h, most nuclear components underwent dramatic ultrastructural changes, including marginalisation and condensation of chromatin, as reflected in a significant reduction of their fractal dimensions. Hence, both fractal and GLCM analyses confirm that the morphological reorganisation of nuclei, attributable to a loss of structural complexity, occurs early in apoptosis.

Synthetic dimensions for cold atoms from shaking a harmonic trap

NASA Astrophysics Data System (ADS)

Price, Hannah M.; Ozawa, Tomoki; Goldman, Nathan

2017-02-01

We introduce a simple scheme to implement synthetic dimensions in ultracold atomic gases, which only requires two basic and ubiquitous ingredients: the harmonic trap, which confines the atoms, combined with a periodic shaking. In our approach, standard harmonic oscillator eigenstates are reinterpreted as lattice sites along a synthetic dimension, while the coupling between these lattice sites is controlled by the applied time modulation. The phase of this modulation enters as a complex hopping phase, leading straightforwardly to an artificial magnetic field upon adding a second dimension. We show that this artificial gauge field has important consequences, such as the counterintuitive reduction of average energy under resonant driving, or the realization of quantum Hall physics. Our approach offers significant advantages over previous implementations of synthetic dimensions, providing an intriguing route towards higher-dimensional topological physics and strongly-correlated states.

Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy simulation/probability density function method

NASA Astrophysics Data System (ADS)

Kim, Jeonglae; Pope, Stephen B.

2014-05-01

A turbulent lean-premixed propane-air flame stabilised by a triangular cylinder as a flame-holder is simulated to assess the accuracy and computational efficiency of combined dimension reduction and tabulation of chemistry. The computational condition matches the Volvo rig experiments. For the reactive simulation, the Lagrangian Large-Eddy Simulation/Probability Density Function (LES/PDF) formulation is used. A novel two-way coupling approach between LES and PDF is applied to obtain resolved density to reduce its statistical fluctuations. Composition mixing is evaluated by the modified Interaction-by-Exchange with the Mean (IEM) model. A baseline case uses In Situ Adaptive Tabulation (ISAT) to calculate chemical reactions efficiently. Its results demonstrate good agreement with the experimental measurements in turbulence statistics, temperature, and minor species mass fractions. For dimension reduction, 11 and 16 represented species are chosen and a variant of Rate Controlled Constrained Equilibrium (RCCE) is applied in conjunction with ISAT to each case. All the quantities in the comparison are indistinguishable from the baseline results using ISAT only. The combined use of RCCE/ISAT reduces the computational time for chemical reaction by more than 50%. However, for the current turbulent premixed flame, chemical reaction takes only a minor portion of the overall computational cost, in contrast to non-premixed flame simulations using LES/PDF, presumably due to the restricted manifold of purely premixed flame in the composition space. Instead, composition mixing is the major contributor to cost reduction since the mean-drift term, which is computationally expensive, is computed for the reduced representation. Overall, a reduction of more than 15% in the computational cost is obtained.

Performance criteria for emergency medicine residents: a job analysis.

PubMed

Blouin, Danielle; Dagnone, Jeffrey Damon

2008-11-01

A major role of admission interviews is to assess a candidate's suitability for a residency program. Structured interviews have greater reliability and validity than do unstructured ones. The development of content for a structured interview is typically based on the dimensions of performance that are perceived as important to succeed in a particular line of work. A formal job analysis is normally conducted to determine these dimensions. The dimensions essential to succeed as an emergency medicine (EM) resident have not yet been studied. We aimed to analyze the work of EM residents to determine these essential dimensions. The "critical incident technique" was used to generate scenarios of poor and excellent resident performance. Two reviewers independently read each scenario and labelled the performance dimensions that were reflected in each. All labels assigned to a particular scenario were pooled and reviewed again until a consensus was reached. Five faculty members (25% of our total faculty) comprised the subject experts. Fifty-one incidents were generated and 50 different labels were applied. Eleven dimensions of performance applied to at least 5 incidents. "Professionalism" was the most valued performance dimension, represented in 56% of the incidents, followed by "self-confidence" (22%), "experience" (20%) and "knowledge" (20%). "Professionalism," "self-confidence," "experience" and "knowledge" were identified as the performance dimensions essential to succeed as an EM resident based on our formal job analysis using the critical incident technique. Performing a formal job analysis may assist training program directors with developing admission interviews.

Dynamic condensation of non-classically damped structures using the method of Maclaurin expansion of the frequency response function in Laplace domain

NASA Astrophysics Data System (ADS)

Esmaeilzad, Armin; Khanlari, Karen

2018-07-01

As the number of degrees of freedom (DOFs) in structural dynamic problems becomes larger, the analyzing complexity and CPU usage of computers increase drastically. Condensation (or reduction) method is an efficient technique to reduce the size of the full model or the dimension of the structural matrices by eliminating the unimportant DOFs. After the first presentation of condensation method by Guyan in 1965 for undamped structures, which ignores the dynamic effects of the mass term, various forms of dynamic condensation methods were presented to overcome this issue. Moreover, researchers have tried to expand the dynamic condensation method to non-classically damped structures. Dynamic reduction of such systems is far more complicated than undamped systems. The proposed non-iterative method in this paper is introduced as 'Maclaurin Expansion of the frequency response function in Laplace Domain' (MELD) applied for dynamic reduction of non-classically damped structures. The present approach is implemented in four numerical examples of 2D bending-shear-axial frames with various numbers of stories and spans and also a floating raft isolation system. The results of natural frequencies and dynamic responses of models are compared with each other before and after the dynamic reduction. It is shown that the result accuracy has acceptable convergence in both cases. In addition, it is indicated that the result of the proposed method is more accurate than the results of some other existing condensation methods.

The Challenge of Universal Primary Education: Strategies for Achieving the International Development Targets.

ERIC Educational Resources Information Center

Department for International Development, London (England).

The Department for International Development (DFID) is the British government department responsible for promoting development and the reduction of poverty in sites in developing and transition countries around the world. This paper focuses on the education dimension of poverty reduction, and specifically the attainment of the International…

The influence of ArF excimer laser micromachining on physicochemical properties of bioresorbable poly(L-lactide)

NASA Astrophysics Data System (ADS)

Stepak, Bogusz D.; Antończak, Arkadiusz J.; Szustakiewicz, Konrad; Pezowicz, Celina; Abramski, Krzysztof M.

2016-03-01

The main advantage of laser processing is a non-contact character of material removal and high precision attainable thanks to low laser beam dimensions. This technique enables forming a complex, submillimeter geometrical shapes such as vascular stents which cannot be manufactured using traditional techniques e.g. injection moulding or mechanical treatment. In the domain of nanosecond laser sources, an ArF excimer laser appears as a good candidate for laser micromachining of bioresorbable polymers such as poly(L-lactide). Due to long pulse duration, however, there is a risk of heat diffusion and accumulation in the material. In addition, due to short wavelength (193 nm) photochemical process can modify the chemical composition of ablated surfaces. The motivation for this research was to evaluate the influence of laser micromachining on physicochemical properties of poly(L-lactide). We performed calorimetric analysis of laser machined samples by using differential scanning calorimetry (DSC). It allowed us to find the optimal process parameters for heat affected zone (HAZ) reduction. The chemical composition of the ablated surface was investigated by FTIR in attenuated total reflectance (ATR) mode.

In situ gold nanoparticles formation: contrast agent for dental optical coherence tomography

NASA Astrophysics Data System (ADS)

Braz, Ana K. S.; Araujo, Renato E. de; Ohulchanskyy, Tymish Y.; Shukla, Shoba; Bergey, Earl J.; Gomes, Anderson S. L.; Prasad, Paras N.

2012-06-01

In this work we demonstrate the potential use of gold nanoparticles as contrast agents for the optical coherence tomography (OCT) imaging technique in dentistry. Here, a new in situ photothermal reduction procedure was developed, producing spherical gold nanoparticles inside dentinal layers and tubules. Gold ions were dispersed in the primer of commercially available dental bonding systems. After the application and permeation in dentin by the modified adhesive systems, the dental bonding materials were photopolymerized concurrently with the formation of gold nanoparticles. The gold nanoparticles were visualized by scanning electron microscopy (SEM). The SEM images show the presence of gold nanospheres in the hybrid layer and dentinal tubules. The diameter of the gold nanoparticles was determined to be in the range of 40 to 120 nm. Optical coherence tomography images were obtained in two- and three-dimensions. The distribution of nanoparticles was analyzed and the extended depth of nanosphere production was determined. The results show that the OCT technique, using in situ formed gold nanoparticles as contrast enhancers, can be used to visualize dentin structures in a non-invasive and non-destructive way.

Presurgical cleft lip and palate orthopedics: an overview

PubMed Central

Alzain, Ibtesam; Batwa, Waeil; Cash, Alex; Murshid, Zuhair A

2017-01-01

Patients with cleft lip and/or palate go through a lifelong journey of multidisciplinary care, starting from before birth and extending until adulthood. Presurgical orthopedic (PSO) treatment is one of the earliest stages of this care plan. In this paper we provide a review of the PSO treatment. This review should help general and specialist dentists to better understand the cleft patient care path and to be able to answer patient queries more efficiently. The objectives of this paper were to review the basic principles of PSO treatment, the various types of techniques used in this therapy, and the protocol followed, and to critically evaluate the advantages and disadvantages of some of these techniques. In conclusion, we believe that PSO treatment, specifically nasoalveolar molding, does help to approximate the segments of the cleft maxilla and does reduce the intersegment space in readiness for the surgical closure of cleft sites. However, what we remain unable to prove equivocally at this point is whether the reduction in the dimensions of the cleft presurgically and the manipulation of the nasal complex benefit our patients in the long term. PMID:28615974

Endoscopic transnasal approach for the treatment of isolated medial orbital blow-out fractures: a prospective study of preoperative and postoperative orbital volume change.

PubMed

Kim, KyoungHoon; Song, KyeongHo; Choi, SooJong; Bae, YongChan; Choi, ChiWon; Oh, HeungChan; Lee, JaeWoo; Nam, SuBong

2012-02-01

Endoscopic transnasal reduction is a safe and effective technique for the treatment of blow-out fractures of the medial orbital wall. However, because this approach does not use rigid permanent material for reconstruction of the fractured medial orbital wall, some degree of herniation of the orbital contents may occur after the intraethmoidal packing material is removed. The purpose of this study was to evaluate the change in orbital volume in patients with medial orbital wall fractures treated through an endoscopic transnasal approach. This study was a prospective analysis that includes 20 patients who underwent endoscopic transnasal reduction of medial orbital wall fractures between April 2007 and December 2008. Computer-assisted orbital volume measurements were made using axial computed tomography. The mean (standard deviation [SD]) volume increase was 2.00 (0.92) cm(3) and the mean (SD) dimension of the fractured orbital wall was 2.76 (0.83) cm(2). After endoscopic surgery, an average (SD) volume decrease of 2.15 (0.91) cm(3) was achieved with ethmoid sinus packing. After removal of the packing materials, 1.14 (0.78) cm(3) increase of the orbital volume was observed. The dimension of the orbital wall fracture significantly correlated with the increased preoperative orbital volume (P = 0.002, r = 0.609); the preoperative increase in the orbital volume also significantly correlated with volume relapse after removal of the packing (P = 0.023, r = 0.452). These findings suggest that in broad orbital wall fractures, reconstruction of the orbital wall by rigid materials or prolongation of the packing period should be considered, because orbital volume can increase again after packing removal, and may thus lead to postoperative complications.

Thermodynamic properties of triangle-well fluids in two dimensions: MC and MD simulations.

PubMed

Reyes, Yuri; Bárcenas, Mariana; Odriozola, Gerardo; Orea, Pedro

2016-11-07

With the aim of providing complementary data of the thermodynamics properties of the triangular well potential, the vapor/liquid phase diagrams for such potential with different interaction ranges were calculated in two dimensions by Monte Carlo and molecular dynamics simulations; also, the vapor/liquid interfacial tension was calculated. As reported for other interaction potentials, it was observed that the reduction of the dimensionality makes the phase diagram to shrink. Finally, with the aid of reported data for the same potential in three dimensions, it was observed that this potential does not follow the principle of corresponding states.

An analysis of Isgur-Wise function of heavy-light mesons within a higher dimensional potential model approach

NASA Astrophysics Data System (ADS)

Roy, Sabyasachi; Choudhury, D. K.

2014-03-01

Nambu-Goto action for bosonic string predicts the quark-antiquark potential to be V(r) = -γ/r + σr + μ0. The coefficient γ = π(d - 2)/24 is the Lüscher coefficient of the Lüscher term 7/r, which depends upon the space-time dimension 'd'. Very recently, we have developed meson wave functions in higher dimension with this potential from higher dimensional Schrodinger equation by applying quantum mechanical perturbation technique with both Lüscher term as parent and as perturbation. In this letter, we analyze Isgur-Wise function for heavy-light mesons using these wave functions in higher dimension and make a comparative study on the status of the perturbation technique in both the cases.

Exploring the relationships between free-time management and boredom in leisure.

PubMed

Wang, Wei-Ching; Wu, Chung-Chi; Wu, Chang-Yang; Huan, Tzung-Cheng

2012-04-01

The purpose of the study was to examine the relations of five dimensions of free-time management (including goal setting and evaluating, technique, values, immediate response, and scheduling) with leisure boredom, and whether these factors could predict leisure boredom. A total of 500 undergraduates from a university in southern Taiwan were surveyed with 403 usable questionnaires was returned. Pearson correlation analysis revealed that five dimensions of free-time management had significant negative relationships with leisure boredom. Furthermore, the results of stepwise regression analysis revealed that four dimensions of free-time management were significant contributors to leisure boredom. Finally, we suggested students can avoid boredom by properly planning and organizing leisure time and applying techniques for managing leisure time.

An explicit mixed numerical method for mesoscale model

NASA Technical Reports Server (NTRS)

Hsu, H.-M.

1981-01-01

A mixed numerical method has been developed for mesoscale models. The technique consists of a forward difference scheme for time tendency terms, an upstream scheme for advective terms, and a central scheme for the other terms in a physical system. It is shown that the mixed method is conditionally stable and highly accurate for approximating the system of either shallow-water equations in one dimension or primitive equations in three dimensions. Since the technique is explicit and two time level, it conserves computer and programming resources.

Iterative design of one- and two-dimensional FIR digital filters. [Finite duration Impulse Response

NASA Technical Reports Server (NTRS)

Suk, M.; Choi, K.; Algazi, V. R.

1976-01-01

The paper describes a new iterative technique for designing FIR (finite duration impulse response) digital filters using a frequency weighted least squares approximation. The technique is as easy to implement (via FFT) and as effective in two dimensions as in one dimension, and there are virtually no limitations on the class of filter frequency spectra approximated. An adaptive adjustment of the frequency weight to achieve other types of design approximation such as Chebyshev type design is discussed.

Numerical study of anomalous dynamic scaling behaviour of (1+1)-dimensional Das Sarma-Tamborenea model

NASA Astrophysics Data System (ADS)

Xun, Zhi-Peng; Tang, Gang; Han, Kui; Hao, Da-Peng; Xia, Hui; Zhou, Wei; Yang, Xi-Quan; Wen, Rong-Ji; Chen, Yu-Ling

2010-07-01

In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the (1+1)-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the (1+1)-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L > 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1+1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.

Brief Communication: Buoyancy-Induced Differences in Soot Morphology

NASA Technical Reports Server (NTRS)

Ku, Jerry C.; Griffin, Devon W.; Greenberg, Paul S.; Roma, John

1995-01-01

Reduction or elimination of buoyancy in flames affects the dominant mechanisms driving heat transfer, burning rates and flame shape. The absence of buoyancy produces longer residence times for soot formation, clustering and oxidation. In addition, soot pathlines are strongly affected in microgravity. We recently conducted the first experiments comparing soot morphology in normal and reduced-gravity laminar gas jet diffusion flames. Thermophoretic sampling is a relatively new but well-established technique for studying the morphology of soot primaries and aggregates. Although there have been some questions about biasing that may be induced due to sampling, recent analysis by Rosner et al. showed that the sample is not biased when the system under study is operating in the continuum limit. Furthermore, even if the sampling is preferentially biased to larger aggregates, the size-invariant premise of fractal analysis should produce a correct fractal dimension.

Analysis of the Westland Data Set

NASA Technical Reports Server (NTRS)

Wen, Fang; Willett, Peter; Deb, Somnath

2001-01-01

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Improving spectral resolution in spatial encoding dimension of single-scan nuclear magnetic resonance 2D spin echo correlated spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Liangjie; Wei, Zhiliang; Yang, Jian; Lin, Yanqin; Chen, Zhong

2014-11-01

The spatial encoding technique can be used to accelerate the acquisition of multi-dimensional nuclear magnetic resonance spectra. However, with this technique, we have to make trade-offs between the spectral width and the resolution in the spatial encoding dimension (F1 dimension), resulting in the difficulty of covering large spectral widths while preserving acceptable resolutions for spatial encoding spectra. In this study, a selective shifting method is proposed to overcome the aforementioned drawback. This method is capable of narrowing spectral widths and improving spectral resolutions in spatial encoding dimensions by selectively shifting certain peaks in spectra of the ultrafast version of spin echo correlated spectroscopy (UFSECSY). This method can also serve as a powerful tool to obtain high-resolution correlated spectra in inhomogeneous magnetic fields for its resistance to any inhomogeneity in the F1 dimension inherited from UFSECSY. Theoretical derivations and experiments have been carried out to demonstrate performances of the proposed method. Results show that the spectral width in spatial encoding dimension can be reduced by shortening distances between cross peaks and axial peaks with the proposed method and the expected resolution improvement can be achieved. Finally, the shifting-absent spectrum can be recovered readily by post-processing.

General solution of a cosmological model induced from higher dimensions using a kinematical constraint

NASA Astrophysics Data System (ADS)

Akarsu, Özgür; Dereli, Tekin; Katırcı, Nihan; Sheftel, Mikhail B.

2015-05-01

In a recent study Akarsu and Dereli (Gen. Relativ. Gravit. 45:1211, 2013) discussed the dynamical reduction of a higher dimensional cosmological model which is augmented by a kinematical constraint characterized by a single real parameter, correlating and controlling the expansion of both the external (physical) and internal spaces. In that paper explicit solutions were found only for the case of three dimensional internal space (). Here we derive a general solution of the system using Lie group symmetry properties, in parametric form for arbitrary number of internal dimensions. We also investigate the dynamical reduction of the model as a function of cosmic time for various values of and generate parametric plots to discuss cosmologically relevant results.

Wing download reduction using vortex trapping plates

NASA Technical Reports Server (NTRS)

Light, Jeffrey S.; Stremel, Paul M.; Bilanin, Alan J.

1994-01-01

A download reduction technique using spanwise plates on the upper and lower wing surfaces has been examined. Experimental and analytical techniques were used to determine the download reduction obtained using this technique. Simple two-dimensional wind tunnel testing confirmed the validity of the technique for reducing two-dimensional airfoil drag. Computations using a two-dimensional Navier-Stokes analysis provided insight into the mechanism causing the drag reduction. Finally, the download reduction technique was tested using a rotor and wing to determine the benefits for a semispan configuration representative of a tilt rotor aircraft.

A Reduced Dimension Static, Linearized Kalman Filter and Smoother

NASA Technical Reports Server (NTRS)

Fukumori, I.

1995-01-01

An approximate Kalman filter and smoother, based on approximations of the state estimation error covariance matrix, is described. Approximations include a reduction of the effective state dimension, use of a static asymptotic error limit, and a time-invariant linearization of the dynamic model for error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. Examples of use come from TOPEX/POSEIDON.

Brain gray matter phenotypes across the psychosis dimension

PubMed Central

Ivleva, Elena I.; Bidesi, Anup S.; Thomas, Binu P.; Meda, Shashwath A.; Francis, Alan; Moates, Amanda F.; Witte, Bradley; Keshavan, Matcheri S.; Tamminga, Carol A.

2013-01-01

This study sought to examine whole brain and regional gray matter (GM) phenotypes across the schizophrenia (SZ)–bipolar disorder psychosis dimension using voxel-based morphometry (VBM 8.0 with DARTEL segmentation/normalization) and semi-automated regional parcellation, FreeSurfer (FS 4.3.1/64 bit). 3T T1 MPRAGE images were acquired from 19 volunteers with schizophrenia (SZ), 16 with schizoaffective disorder (SAD), 17 with psychotic bipolar I disorder (BD-P) and 10 healthy controls (HC). Contrasted with HC, SZ showed extensive cortical GM reductions, most pronounced in fronto-temporal regions; SAD had GM reductions overlapping with SZ, albeit less extensive; and BD-P demonstrated no GM differences from HC. Within the psychosis dimension, BD-P showed larger volumes in fronto-temporal and other cortical/subcortical regions compared with SZ, whereas SAD showed intermediate GM volumes. The two volumetric methodologies, VBM and FS, revealed highly overlapping results for cortical GM, but partially divergent results for subcortical volumes (basal ganglia, amygdala). Overall, these findings suggest that individuals across the psychosis dimension show both overlapping and unique GM phenotypes: decreased GM, predominantly in fronto-temporal regions, is characteristic of SZ but not of psychotic BD-P, whereas SAD display GM deficits overlapping with SZ, albeit less extensive. PMID:23177922

Brain gray matter phenotypes across the psychosis dimension.

PubMed

Ivleva, Elena I; Bidesi, Anup S; Thomas, Binu P; Meda, Shashwath A; Francis, Alan; Moates, Amanda F; Witte, Bradley; Keshavan, Matcheri S; Tamminga, Carol A

2012-10-30

This study sought to examine whole brain and regional gray matter (GM) phenotypes across the schizophrenia (SZ)-bipolar disorder psychosis dimension using voxel-based morphometry (VBM 8.0 with DARTEL segmentation/normalization) and semi-automated regional parcellation, FreeSurfer (FS 4.3.1/64 bit). 3T T1 MPRAGE images were acquired from 19 volunteers with schizophrenia (SZ), 16 with schizoaffective disorder (SAD), 17 with psychotic bipolar I disorder (BD-P) and 10 healthy controls (HC). Contrasted with HC, SZ showed extensive cortical GM reductions, most pronounced in fronto-temporal regions; SAD had GM reductions overlapping with SZ, albeit less extensive; and BD-P demonstrated no GM differences from HC. Within the psychosis dimension, BD-P showed larger volumes in fronto-temporal and other cortical/subcortical regions compared with SZ, whereas SAD showed intermediate GM volumes. The two volumetric methodologies, VBM and FS, revealed highly overlapping results for cortical GM, but partially divergent results for subcortical volumes (basal ganglia, amygdala). Overall, these findings suggest that individuals across the psychosis dimension show both overlapping and unique GM phenotypes: decreased GM, predominantly in fronto-temporal regions, is characteristic of SZ but not of psychotic BD-P, whereas SAD display GM deficits overlapping with SZ, albeit less extensive. Published by Elsevier Ireland Ltd.

Continuous spin representations from group contraction

NASA Astrophysics Data System (ADS)

Khan, Abu M.; Ramond, Pierre

2005-05-01

We consider how the continuous spin representation (CSR) of the Poincaré group in four dimensions can be generated by dimensional reduction. The analysis uses the front-form little group in five dimensions, which must yield the Euclidean group E(2), the little group of the CSR. We consider two cases, one is the single spin massless representation of the Poincaré group in five dimensions, the other is the infinite component Majorana equation, which describes an infinite tower of massive states in five dimensions. In the first case, the double singular limit j, R →∞, with j /R fixed, where R is the Kaluza-Klein radius of the fifth dimension, and j is the spin of the particle in five dimensions, yields the CSR in four dimensions. It amounts to the Inönü-Wigner contraction, with the inverse Kaluza-Klein radius as contraction parameter. In the second case, the CSR appears only by taking a triple singular limit, where an internal coordinate of the Majorana theory goes to infinity, while leaving its ratio to the Kaluza-Klein radius fixed.

A Comparison of Accuracy of Matrix Impression System with Putty Reline Technique and Multiple Mix Technique: An In Vitro Study.

PubMed

Kumar, M Praveen; Patil, Suneel G; Dheeraj, Bhandari; Reddy, Keshav; Goel, Dinker; Krishna, Gopi

2015-06-01

The difficulty in obtaining an acceptable impression increases exponentially as the number of abutments increases. Accuracy of the impression material and the use of a suitable impression technique are of utmost importance in the fabrication of a fixed partial denture. This study compared the accuracy of the matrix impression system with conventional putty reline and multiple mix technique for individual dies by comparing the inter-abutment distance in the casts obtained from the impressions. Three groups, 10 impressions each with three impression techniques (matrix impression system, putty reline technique and multiple mix technique) were made of a master die. Typodont teeth were embedded in a maxillary frasaco model base. The left first premolar was removed to create a three-unit fixed partial denture situation and the left canine and second premolar were prepared conservatively, and hatch marks were made on the abutment teeth. The final casts obtained from the impressions were examined under a profile projector and the inter-abutment distance was calculated for all the casts and compared. The results from this study showed that in the mesiodistal dimensions the percentage deviation from master model in Group I was 0.1 and 0.2, in Group II was 0.9 and 0.3, and Group III was 1.6 and 1.5, respectively. In the labio-palatal dimensions the percentage deviation from master model in Group I was 0.01 and 0.4, Group II was 1.9 and 1.3, and Group III was 2.2 and 2.0, respectively. In the cervico-incisal dimensions the percentage deviation from the master model in Group I was 1.1 and 0.2, Group II was 3.9 and 1.7, and Group III was 1.9 and 3.0, respectively. In the inter-abutment dimension of dies, percentage deviation from master model in Group I was 0.1, Group II was 0.6, and Group III was 1.0. The matrix impression system showed more accuracy of reproduction for individual dies when compared with putty reline technique and multiple mix technique in all the three directions, as well as the inter-abutment distance.

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Patterning techniques for next generation IC's

NASA Astrophysics Data System (ADS)

Balasinski, A.

2007-12-01

Reduction of linear critical dimensions (CDs) beyond 45 nm would require significant increase of the complexity of pattern definition process. In this work, we discuss the key successor methodology to the current optical lithography, the Double Patterning Technique (DPT). We compare the complexity of CAD solutions, fab equipment, and wafer processing with its competitors, such as the nanoimprint (NIL) and the extreme UV (EUV) techniques. We also look ahead to the market availability for the product families enabled using the novel patterning solutions. DPT is often recognized as the most viable next generation lithography as it utilizes the existing equipment and processes and is considered a stop-gap solution before the advanced NIL or EUV equipment is developed. Using design for manufacturability (DfM) rules, DPT can drive the k1 factor down to 0.13. However, it faces a variety of challenges, from new mask overlay strategies, to layout pattern split, novel OPC, increased CD tolerances, new etch techniques, as well as long processing time, all of which compromise its return on investment (RoI). In contrast, it can be claimed e.g., that the RoI is the highest for the NIL but this technology bears significant risk. For all novel patterning techniques, the key questions remain: when and how should they be introduced, what is their long-term potential, when should they be replaced, and by what successor technology. We summarize the unpublished results of several panel discussions on DPT at the recent SPIE/BACUS conferences.

Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

PubMed Central

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6∼8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3∼5 pattern classes considering the trade-off between time consumption and classification rate. PMID:22736979

Risk Assessment Using the Three Dimensions of Probability (Likelihood), Severity, and Level of Control

NASA Technical Reports Server (NTRS)

Watson, Clifford

2010-01-01

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the twodimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and threedimensional charting gives a visual confirmation of the relationship between causes and their controls

Risk Assessment Using the Three Dimensions of Probability (Likelihood), Severity, and Level of Control

NASA Technical Reports Server (NTRS)

Watson, Clifford C.

2011-01-01

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.

Risk Presentation Using the Three Dimensions of Likelihood, Severity, and Level of Control

NASA Technical Reports Server (NTRS)

Watson, Clifford

2010-01-01

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the leastwell-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.

Investigation of interpolation techniques for the reconstruction of the first dimension of comprehensive two-dimensional liquid chromatography-diode array detector data.

PubMed

Allen, Robert C; Rutan, Sarah C

2011-10-31

Simulated and experimental data were used to measure the effectiveness of common interpolation techniques during chromatographic alignment of comprehensive two-dimensional liquid chromatography-diode array detector (LC×LC-DAD) data. Interpolation was used to generate a sufficient number of data points in the sampled first chromatographic dimension to allow for alignment of retention times from different injections. Five different interpolation methods, linear interpolation followed by cross correlation, piecewise cubic Hermite interpolating polynomial, cubic spline, Fourier zero-filling, and Gaussian fitting, were investigated. The fully aligned chromatograms, in both the first and second chromatographic dimensions, were analyzed by parallel factor analysis to determine the relative area for each peak in each injection. A calibration curve was generated for the simulated data set. The standard error of prediction and percent relative standard deviation were calculated for the simulated peak for each technique. The Gaussian fitting interpolation technique resulted in the lowest standard error of prediction and average relative standard deviation for the simulated data. However, upon applying the interpolation techniques to the experimental data, most of the interpolation methods were not found to produce statistically different relative peak areas from each other. While most of the techniques were not statistically different, the performance was improved relative to the PARAFAC results obtained when analyzing the unaligned data. Copyright © 2011 Elsevier B.V. All rights reserved.

Milch versus Stimson technique for nonsedated reduction of anterior shoulder dislocation: a prospective randomized trial and analysis of factors affecting success.

PubMed

Amar, Eyal; Maman, Eran; Khashan, Morsi; Kauffman, Ehud; Rath, Ehud; Chechik, Ofir

2012-11-01

The shoulder is regarded as the most commonly dislocated major joint in the human body. Most dislocations can be reduced by simple methods in the emergency department, whereas others require more complicated approaches. We compared the efficacy, safety, pain, and duration of the reduction between the Milch technique and the Stimson technique in treating dislocations. We also identified factors that affected success rate. All enrolled patients were randomized to either the Milch technique or the Stimson technique for dislocated shoulder reduction. The study cohort consisted of 60 patients (mean age, 43.9 years; age range, 18-88 years) who were randomly assigned to treatment by either the Stimson technique (n = 25) or the Milch technique (n = 35). Oral analgesics were available for both groups. The 2 groups were similar in demographics, patient characteristics, and pain levels. The first reduction attempt in the Milch and Stimson groups was successful in 82.8% and 28% of cases, respectively (P < .001), and the mean reduction time was 4.68 and 8.84 minutes, respectively (P = .007). The success rate was found to be affected by the reduction technique, the interval between dislocation occurrence and first reduction attempt, and the pain level on admittance. The success rate and time to achieve reduction without sedation were superior for the Milch technique compared with the Stimson technique. Early implementation of reduction measures and low pain levels at presentation favor successful reduction, which--in combination with oral pain medication--constitutes an acceptable and reasonable management alternative to reduction with sedation. Copyright © 2012 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Applying under-sampling techniques and cost-sensitive learning methods on risk assessment of breast cancer.

PubMed

Hsu, Jia-Lien; Hung, Ping-Cheng; Lin, Hung-Yen; Hsieh, Chung-Ho

2015-04-01

Breast cancer is one of the most common cause of cancer mortality. Early detection through mammography screening could significantly reduce mortality from breast cancer. However, most of screening methods may consume large amount of resources. We propose a computational model, which is solely based on personal health information, for breast cancer risk assessment. Our model can be served as a pre-screening program in the low-cost setting. In our study, the data set, consisting of 3976 records, is collected from Taipei City Hospital starting from 2008.1.1 to 2008.12.31. Based on the dataset, we first apply the sampling techniques and dimension reduction method to preprocess the testing data. Then, we construct various kinds of classifiers (including basic classifiers, ensemble methods, and cost-sensitive methods) to predict the risk. The cost-sensitive method with random forest classifier is able to achieve recall (or sensitivity) as 100 %. At the recall of 100 %, the precision (positive predictive value, PPV), and specificity of cost-sensitive method with random forest classifier was 2.9 % and 14.87 %, respectively. In our study, we build a breast cancer risk assessment model by using the data mining techniques. Our model has the potential to be served as an assisting tool in the breast cancer screening.

Analyzing coastal environments by means of functional data analysis

NASA Astrophysics Data System (ADS)

Sierra, Carlos; Flor-Blanco, Germán; Ordoñez, Celestino; Flor, Germán; Gallego, José R.

2017-07-01

Here we used Functional Data Analysis (FDA) to examine particle-size distributions (PSDs) in a beach/shallow marine sedimentary environment in Gijón Bay (NW Spain). The work involved both Functional Principal Components Analysis (FPCA) and Functional Cluster Analysis (FCA). The grainsize of the sand samples was characterized by means of laser dispersion spectroscopy. Within this framework, FPCA was used as a dimension reduction technique to explore and uncover patterns in grain-size frequency curves. This procedure proved useful to describe variability in the structure of the data set. Moreover, an alternative approach, FCA, was applied to identify clusters and to interpret their spatial distribution. Results obtained with this latter technique were compared with those obtained by means of two vector approaches that combine PCA with CA (Cluster Analysis). The first method, the point density function (PDF), was employed after adapting a log-normal distribution to each PSD and resuming each of the density functions by its mean, sorting, skewness and kurtosis. The second applied a centered-log-ratio (clr) to the original data. PCA was then applied to the transformed data, and finally CA to the retained principal component scores. The study revealed functional data analysis, specifically FPCA and FCA, as a suitable alternative with considerable advantages over traditional vector analysis techniques in sedimentary geology studies.

Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems.

PubMed

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martin, Consuelo; Marcello-Ruiz, Javier; Garcia-Pedrero, Angel; Rodriguez-Esparragon, Dionisio

2017-01-25

Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources' reduction is concerned, remote sensing and image processing techniques could contribute to the management of these natural resources in a practical and cost-effective way, although some improvements are needed for obtaining a higher quality of the information available. An important quality improvement is the fusion at the pixel level. Hence, the objective of this work is to assess which pansharpening technique provides the best fused image for the different types of ecosystems. After a preliminary evaluation of twelve classic and novel fusion algorithms, a total of four pansharpening algorithms was analyzed using six quality indices. The quality assessment was implemented not only for the whole set of multispectral bands, but also for the subset of spectral bands covered by the wavelength range of the panchromatic image and outside of it. A better quality result is observed in the fused image using only the bands covered by the panchromatic band range. It is important to highlight the use of these techniques not only in land and urban areas, but a novel analysis in areas of shallow water ecosystems. Although the algorithms do not show a high difference in land and coastal areas, coastal ecosystems require simpler algorithms, such as fast intensity hue saturation, whereas more heterogeneous ecosystems need advanced algorithms, as weighted wavelet ' à trous ' through fractal dimension maps for shrublands and mixed ecosystems. Moreover, quality map analysis was carried out in order to study the fusion result in each band at the local level. Finally, to demonstrate the performance of these pansharpening techniques, advanced Object-Based (OBIA) support vector machine classification was applied, and a thematic map for the shrubland ecosystem was obtained, which corroborates wavelet ' à trous ' through fractal dimension maps as the best fusion algorithm for this ecosystem.

Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems

PubMed Central

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martin, Consuelo; Marcello-Ruiz, Javier; Garcia-Pedrero, Angel; Rodriguez-Esparragon, Dionisio

2017-01-01

Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources’ reduction is concerned, remote sensing and image processing techniques could contribute to the management of these natural resources in a practical and cost-effective way, although some improvements are needed for obtaining a higher quality of the information available. An important quality improvement is the fusion at the pixel level. Hence, the objective of this work is to assess which pansharpening technique provides the best fused image for the different types of ecosystems. After a preliminary evaluation of twelve classic and novel fusion algorithms, a total of four pansharpening algorithms was analyzed using six quality indices. The quality assessment was implemented not only for the whole set of multispectral bands, but also for the subset of spectral bands covered by the wavelength range of the panchromatic image and outside of it. A better quality result is observed in the fused image using only the bands covered by the panchromatic band range. It is important to highlight the use of these techniques not only in land and urban areas, but a novel analysis in areas of shallow water ecosystems. Although the algorithms do not show a high difference in land and coastal areas, coastal ecosystems require simpler algorithms, such as fast intensity hue saturation, whereas more heterogeneous ecosystems need advanced algorithms, as weighted wavelet ‘à trous’ through fractal dimension maps for shrublands and mixed ecosystems. Moreover, quality map analysis was carried out in order to study the fusion result in each band at the local level. Finally, to demonstrate the performance of these pansharpening techniques, advanced Object-Based (OBIA) support vector machine classification was applied, and a thematic map for the shrubland ecosystem was obtained, which corroborates wavelet ‘à trous’ through fractal dimension maps as the best fusion algorithm for this ecosystem. PMID:28125055

Application of random coherence order selection in gradient-enhanced multidimensional NMR

NASA Astrophysics Data System (ADS)

Bostock, Mark J.; Nietlispach, Daniel

2016-03-01

Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1-norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1-norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended to the full suite of experiments available to modern NMR spectroscopy, allowing resolution enhancements for all indirect dimensions; alone or in combination with NUS, RQD can be used to improve experimental resolution, or shorten experiment times, of considerable benefit to the challenging applications undertaken by modern NMR.

Influence of condition of growth of bacterial colonies on fractal dimension of bacterial speckle patterns

NASA Astrophysics Data System (ADS)

Ulyanov, Alexander S.; Lyapina, Anna M.; Ulianova, Onega V.; Feodorova, Valentina A.

2010-10-01

New field of application of fractal dimensions is proposed. A technique, based on the calculation of fractal dimension, was used for express-diagnostics and identification of bacteria of the vaccine strain Yersinia pestis EV line NIIEG. Purpose of this study was the experimental investigation of properties of speckle patterns, formed under laser illumination of a single colony of the strain that was grown on different agars.

Influence of condition of growth of bacterial colonies on fractal dimension of bacterial speckle patterns

NASA Astrophysics Data System (ADS)

Ulyanov, Alexander S.; Lyapina, Anna M.; Ulianova, Onega V.; Feodorova, Valentina A.

2011-03-01

New field of application of fractal dimensions is proposed. A technique, based on the calculation of fractal dimension, was used for express-diagnostics and identification of bacteria of the vaccine strain Yersinia pestis EV line NIIEG. Purpose of this study was the experimental investigation of properties of speckle patterns, formed under laser illumination of a single colony of the strain that was grown on different agars.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry.

PubMed

Zhao, Yan; Chang, Cheng; Qin, Peibin; Cao, Qichen; Tian, Fang; Jiang, Jing; Li, Xianyu; Yu, Wenfeng; Zhu, Yunping; He, Fuchu; Ying, Wantao; Qian, Xiaohong

2016-01-21

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Double-black-hole solutions of the Einstein-Maxwell-dilaton theory in five dimensions

NASA Astrophysics Data System (ADS)

Stelea, Cristian

2018-01-01

We describe a solution-generating technique that maps a static charged solution of the Einstein-Maxwell theory in four (or five) dimensions to a five-dimensional solution of the Einstein-Maxwell-Dilaton theory. As examples of this technique first we show how to construct the dilatonic version of the Reissner-Nordström solution in five dimensions and then we consider the more general case of the double black hole solutions and describe some of their properties. We found that in the general case the value of the conical singularities in between the black holes is affected by the dilaton's coupling constant to the gauge field and only in the particular case when all charges are proportional to the masses this dependence cancels out.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

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

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Comparison between cylindrical and prismatic lithium-ion cell costs using a process based cost model

NASA Astrophysics Data System (ADS)

Ciez, Rebecca E.; Whitacre, J. F.

2017-02-01

The relative size and age of the US electric vehicle market means that a few vehicles are able to drive market-wide trends in the battery chemistries and cell formats on the road today. Three lithium-ion chemistries account for nearly all of the storage capacity, and half of the cells are cylindrical. However, no specific model exists to examine the costs of manufacturing these cylindrical cells. Here we present a process-based cost model tailored to the cylindrical lithium-ion cells currently used in the EV market. We examine the costs for varied cell dimensions, electrode thicknesses, chemistries, and production volumes. Although cost savings are possible from increasing cell dimensions and electrode thicknesses, economies of scale have already been reached, and future cost reductions from increased production volumes are minimal. Prismatic cells, which are able to further capitalize on the cost reduction from larger formats, can offer further reductions than those possible for cylindrical cells.

The human dimensions of energy use in buildings: A review

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

D'Oca, Simona; Hong, Tianzhen; Langevin, Jared

The “human dimensions” of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplifiedmore » by stakeholders. This work presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building's life cycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights. Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners; enhanced comfort conditions and productivity for building occupants; more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.« less

The human dimensions of energy use in buildings: A review

DOE PAGES

D'Oca, Simona; Hong, Tianzhen; Langevin, Jared

2017-08-19

The “human dimensions” of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplifiedmore » by stakeholders. This work presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building's life cycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights. Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners; enhanced comfort conditions and productivity for building occupants; more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.« less

Analysis of biochemical phase shift oscillators by a harmonic balancing technique.

PubMed

Rapp, P

1976-11-25

The use of harmonic balancing techniques for theoretically investigating a large class of biochemical phase shift oscillators is outlined and the accuracy of this approximate technique for large dimension nonlinear chemical systems is considered. It is concluded that for the equations under study these techniques can be successfully employed to both find periodic solutions and to indicate those cases which can not oscillate. The technique is a general one and it is possible to state a step by step procedure for its application. It has a substantial advantage in producing results which are immediately valid for arbitrary dimension. As the accuracy of the method increases with dimension, it complements classical small dimension methods. The results obtained by harmonic balancing analysis are compared with those obtained by studying the local stability properties of the singular points of the differential equation. A general theorem is derived which identifies those special cases where the results of first order harmonic balancing are identical to those of local stability analysis, and a necessary condition for this equivalence is derived. As a concrete example, the n-dimensional Goodwin oscillator is considered where p, the Hill coefficient of the feedback metabolite, is equal to three and four. It is shown that for p = 3 or 4 and n less than or equal to 4 the approximation indicates that it is impossible to construct a set of physically permissible reaction constants such that the system possesses a periodic solution. However for n greater than or equal to 5 it is always possible to find a large domain in the reaction constant space giving stable oscillations. A means of constructing such a parameter set is given. The results obtained here are compared with previously derived results for p = 1 and p = 2.

Real-time visualization of cross-sectional data in three dimensions

NASA Technical Reports Server (NTRS)

Mayes, Terrence J.; Foley, Theodore T.; Hamilton, Joseph A.; Duncavage, Tom C.

2005-01-01

This paper describes a technique for viewing and interacting with 2-D medical data in three dimensions. The approach requires little pre-processing, runs on personal computers, and has a wide range of application. Implementation details are discussed, examples are presented, and results are summarized.

QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION

PubMed Central

Fan, Jianqing; Ke, Zheng Tracy; Liu, Han; Xia, Lucy

2016-01-01

We propose a novel Rayleigh quotient based sparse quadratic dimension reduction method—named QUADRO (Quadratic Dimension Reduction via Rayleigh Optimization)—for analyzing high-dimensional data. Unlike in the linear setting where Rayleigh quotient optimization coincides with classification, these two problems are very different under nonlinear settings. In this paper, we clarify this difference and show that Rayleigh quotient optimization may be of independent scientific interests. One major challenge of Rayleigh quotient optimization is that the variance of quadratic statistics involves all fourth cross-moments of predictors, which are infeasible to compute for high-dimensional applications and may accumulate too many stochastic errors. This issue is resolved by considering a family of elliptical models. Moreover, for heavy-tail distributions, robust estimates of mean vectors and covariance matrices are employed to guarantee uniform convergence in estimating non-polynomially many parameters, even though only the fourth moments are assumed. Methodologically, QUADRO is based on elliptical models which allow us to formulate the Rayleigh quotient maximization as a convex optimization problem. Computationally, we propose an efficient linearized augmented Lagrangian method to solve the constrained optimization problem. Theoretically, we provide explicit rates of convergence in terms of Rayleigh quotient under both Gaussian and general elliptical models. Thorough numerical results on both synthetic and real datasets are also provided to back up our theoretical results. PMID:26778864

A dimension reduction method for flood compensation operation of multi-reservoir system

NASA Astrophysics Data System (ADS)

Jia, B.; Wu, S.; Fan, Z.

2017-12-01

Multiple reservoirs cooperation compensation operations coping with uncontrolled flood play vital role in real-time flood mitigation. This paper come up with a reservoir flood compensation operation index (ResFCOI), which formed by elements of flood control storage, flood inflow volume, flood transmission time and cooperation operations period, then establish a flood cooperation compensation operations model of multi-reservoir system, according to the ResFCOI to determine a computational order of each reservoir, and lastly the differential evolution algorithm is implemented for computing single reservoir flood compensation optimization in turn, so that a dimension reduction method is formed to reduce computational complexity. Shiguan River Basin with two large reservoirs and an extensive uncontrolled flood area, is used as a case study, results show that (a) reservoirs' flood discharges and the uncontrolled flood are superimposed at Jiangjiaji Station, while the formed flood peak flow is as small as possible; (b) cooperation compensation operations slightly increase in usage of flood storage capacity in reservoirs, when comparing to rule-based operations; (c) it takes 50 seconds in average when computing a cooperation compensation operations scheme. The dimension reduction method to guide flood compensation operations of multi-reservoir system, can make each reservoir adjust its flood discharge strategy dynamically according to the uncontrolled flood magnitude and pattern, so as to mitigate the downstream flood disaster.

Random walks on combs

NASA Astrophysics Data System (ADS)

Durhuus, Bergfinnur; Jonsson, Thordur; Wheater, John F.

2006-02-01

We develop techniques to obtain rigorous bounds on the behaviour of random walks on combs. Using these bounds, we calculate exactly the spectral dimension of random combs with infinite teeth at random positions or teeth with random but finite length. We also calculate exactly the spectral dimension of some fixed non-translationally invariant combs. We relate the spectral dimension to the critical exponent of the mass of the two-point function for random walks on random combs, and compute mean displacements as a function of walk duration. We prove that the mean first passage time is generally infinite for combs with anomalous spectral dimension.

Marginal cost curves for water footprint reduction in irrigated agriculture: a policy and decision making guide for efficient water use in crop production

NASA Astrophysics Data System (ADS)

Chukalla, Abebe; Krol, Maarten; Hoekstra, Arjen

2016-04-01

Reducing water footprints (WF) in irrigated crop production is an essential element in water management, particularly in water-scarce areas. To achieve this, policy and decision making need to be supported with information on marginal cost curves that rank measures to reduce the WF according to their cost-effectiveness and enable the estimation of the cost associated with a certain WF reduction target, e.g. towards a certain reasonable WF benchmark. This paper aims to develop marginal cost curves (MCC) for WF reduction. The AquaCrop model is used to explore the effect of different measures on evapotranspiration and crop yield and thus WF that is used as input in the MCC. Measures relate to three dimensions of management practices: irrigation techniques (furrow, sprinkler, drip and subsurface drip); irrigation strategies (full and deficit irrigation); and mulching practices (no mulching, organic and synthetic mulching). A WF benchmark per crop is calculated as resulting from the best-available production technology. The marginal cost curve is plotted using the ratios of the marginal cost to WF reduction of the measures as ordinate, ranking with marginal costs rise with the increase of the reduction effort. For each measure, the marginal cost to reduce WF is estimated by comparing the associated WF and net present value (NPV) to the reference case (furrow irrigation, full irrigation, no mulching). The NPV for each measure is based on its capital costs, operation and maintenances costs (O&M) and revenues. A range of cases is considered, including: different crops, soil types and different environments. Key words: marginal cost curve, water footprint benchmark, soil water balance, crop growth, AquaCrop

Universal and integrable nonlinear evolution systems of equations in 2+1 dimensions

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

Maccari, A.

1997-08-01

Integrable systems of nonlinear partial differential equations (PDEs) are obtained from integrable equations in 2+1 dimensions, by means of a reduction method of broad applicability based on Fourier expansion and spatio{endash}temporal rescalings, which is asymptotically exact in the limit of weak nonlinearity. The integrability by the spectral transform is explicitly demonstrated, because the corresponding Lax pairs have been derived, applying the same reduction method to the Lax pair of the initial equation. These systems of nonlinear PDEs are likely to be of applicative relevance and have a {open_quotes}universal{close_quotes} character, inasmuch as they may be derived from a very large classmore » of nonlinear evolution equations with a linear dispersive part. {copyright} {ital 1997 American Institute of Physics.}« less

Evaluation of dynamically dimensioned search algorithm for optimizing SWAT by altering sampling distributions and searching range

USDA-ARS?s Scientific Manuscript database

The primary advantage of Dynamically Dimensioned Search algorithm (DDS) is that it outperforms many other optimization techniques in both convergence speed and the ability in searching for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation f...

A Comparison of Holistic versus Decomposed Rating of Position Analysis Questionnaire Work Dimensions.

ERIC Educational Resources Information Center

Butler, Stephanie K.; Harvey, Robert J.

1988-01-01

Examined technique for improving cost-effectiveness of Position Analysis Questionnaire (PAQ) in job analysis. Professional job analysts, industrial psychology graduate students familiar with PAQ, and PAQ-unfamiliar undergraduates made direct holistic ratings of PAQ dimensions for four familiar jobs. Comparison of holistic ratings with decomposed…

Academic Departments and Student Attitudes toward Different Dimensions of Web-based Education.

ERIC Educational Resources Information Center

Federico, Pat-Anthony

2001-01-01

Describes research at the Naval Postgraduate School that investigated student attitudes toward various aspects of Web-based instruction. Results of a survey, which were analyzed using a variety of multivariate and univariate statistical techniques, showed significantly different attitudes toward different dimensions of Web-based education…

Holographic turbulence in a large number of dimensions

NASA Astrophysics Data System (ADS)

Rozali, Moshe; Sabag, Evyatar; Yarom, Amos

2018-04-01

We consider relativistic hydrodynamics in the limit where the number of spatial dimensions is very large. We show that under certain restrictions, the resulting equations of motion simplify significantly. Holographic theories in a large number of dimensions satisfy the aforementioned restrictions and their dynamics are captured by hydrodynamics with a naturally truncated derivative expansion. Using analytic and numerical techniques we analyze two and three-dimensional turbulent flow of such fluids in various regimes and its relation to geometric data.

Automatic Black-Box Model Order Reduction using Radial Basis Functions

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

Stephanson, M B; Lee, J F; White, D A

Finite elements methods have long made use of model order reduction (MOR), particularly in the context of fast freqeucny sweeps. In this paper, we discuss a black-box MOR technique, applicable to a many solution methods and not restricted only to spectral responses. We also discuss automated methods for generating a reduced order model that meets a given error tolerance. Numerical examples demonstrate the effectiveness and wide applicability of the method. With the advent of improved computing hardware and numerous fast solution techniques, the field of computational electromagnetics are progressed rapidly in terms of the size and complexity of problems thatmore » can be solved. Numerous applications, however, require the solution of a problem for many different configurations, including optimization, parameter exploration, and uncertainly quantification, where the parameters that may be changed include frequency, material properties, geometric dimensions, etc. In such cases, thousands of solutions may be needed, so solve times of even a few minutes can be burdensome. Model order reduction (MOR) may alleviate this difficulty by creating a small model that can be evaluated quickly. Many MOR techniques have been applied to electromagnetic problems over the past few decades, particularly in the context of fast frequency sweeps. Recent works have extended these methods to allow more than one parameter and to allow the parameters to represent material and geometric properties. There are still limitations with these methods, however. First, they almost always assume that the finite element method is used to solve the problem, so that the system matrix is a known function of the parameters. Second, although some authors have presented adaptive methods (e.g., [2]), the order of the model is often determined before the MOR process begins, with little insight about what order is actually needed to reach the desired accuracy. Finally, it not clear how to efficiently extend most methods to the multiparameter case. This paper address the above shortcomings be developing a method that uses a block-box approach to the solution method, is adaptive, and is easily extensible to many parameters.« less

Catalan speakers' perception of word stress in unaccented contexts.

PubMed

Ortega-Llebaria, Marta; del Mar Vanrell, Maria; Prieto, Pilar

2010-01-01

In unaccented contexts, formant frequency differences related to vowel reduction constitute a consistent cue to word stress in English, whereas in languages such as Spanish that have no systematic vowel reduction, stress perception is based on duration and intensity cues. This article examines the perception of word stress by speakers of Central Catalan, in which, due to its vowel reduction patterns, words either alternate stressed open vowels with unstressed mid-central vowels as in English or contain no vowel quality cues to stress, as in Spanish. Results show that Catalan listeners perceive stress based mainly on duration cues in both word types. Other cues pattern together with duration to make stress perception more robust. However, no single cue is absolutely necessary and trading effects compensate for a lack of differentiation in one dimension by changes in another dimension. In particular, speakers identify longer mid-central vowels as more stressed than shorter open vowels. These results and those obtained in other stress-accent languages provide cumulative evidence that word stress is perceived independently of pitch accents by relying on a set of cues with trading effects so that no single cue, including formant frequency differences related to vowel reduction, is absolutely necessary for stress perception.

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Seawater infiltration effect on thermal degradation of fiber reinforced epoxy composites

NASA Astrophysics Data System (ADS)

Ibrahim, Mohd Haziq Izzuddin bin; Hassan, Mohamad Zaki bin; Ibrahim, Ikhwan; Rashidi, Ahmad Hadi Mohamed; Nor, Siti Fadzilah M.; Daud, Mohd Yusof Md

2018-05-01

Seawater salinity has been associated with the reduction of polymer structure durability. The aim of this study is to investigate the change in thermal degradation of fiber reinforced epoxy composite due to the presence of seawater. Carbon fiber, carbon/kevlar, fiberglass, and jute that reinforced with epoxy resin was laminated through hand-layup technique. Initially, these specimen was sectioned to 5×5 mm dimension, then immersed in seawater and distilled water at room temperature until it has thoroughly saturated. Following, the thermal degradation analysis using Differential Scanning Calorimetry (DSC), the thermic changes due to seawater infiltration was defined. The finding shows that moisture absorption reduces the glass transition temperature (Tg) of fiber reinforced epoxy composite. However, the glass transition temperature (Tg) of seawater infiltrated laminate composite is compareable with distilled water infiltrated laminate composite. The carbon fiber reinfored epoxy has the highest glass transition temperature out of all specimen.

Lead-acid batteries with polymer-structured electrodes for electric-vehicle applications

NASA Astrophysics Data System (ADS)

Soria, M. L.; Fullea, J.; Sáez, F.; Trinidad, F.

Some years ago a consortium of enterprises and a university from different European countries and industrial sectors was established to work together in the development of lighter lead-acid batteries for electrical and conventional vehicles with new innovative materials and process techniques, with the final goal of increasing the energy density by means of a battery weight reduction. Its main idea was to substitute the heavy lead alloy grids (mechanical support of the active masses and collectors of the current produced during the charge and discharge reactions) by lightweight metallised polymeric network structures (PNS) with reduced mesh dimensions in comparison to conventional grids. The network was then coated with conductive materials and corrosion resistant layers to conduct the current flow. In this paper, the electrode characteristics and the design features of the batteries prepared in the project will be described and their electrical performance presented.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

High quality factor GaAs microcavity with buried bullseye defects

NASA Astrophysics Data System (ADS)

Winkler, K.; Gregersen, N.; Häyrynen, T.; Bradel, B.; Schade, A.; Emmerling, M.; Kamp, M.; Höfling, S.; Schneider, C.

2018-05-01

The development of high quality factor solid-state microcavities with low mode volumes has paved the way towards on-chip cavity quantum electrodynamics experiments and the development of high-performance nanophotonic devices. Here, we report on the implementation of a new kind of solid-state vertical microcavity, which allows for confinement of the electromagnetic field in the lateral direction without deep etching. The confinement originates from a local elongation of the cavity layer imprinted in a shallow etch and epitaxial overgrowth technique. We show that it is possible to improve the quality factor of such microcavities by a specific in-plane bullseye geometry consisting of a set of concentric rings with subwavelength dimensions. This design results in a smooth effective lateral photonic potential and therefore in a reduction of lateral scattering losses, which makes it highly appealing for experiments in the framework of exciton-polariton physics demanding tight spatial confinement.

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Chemical characterization of 4140 steel implanted by nitrogen ions

NASA Astrophysics Data System (ADS)

Niño, E. D. V.; Pinto, J. L.; Dugar-Zhabon, V.; Henao, J. A.

2012-06-01

AISI SAE 4140 steel samples of different surface roughness which are implanted with 20 keV and 30 keV nitrogen ions at a dose of 1017 ions/cm2 are studied. The crystal phases of nitrogen compositions of the implanted samples, obtained with help of an x-ray diffraction method, are confronted with the data reported by the International Centre for Diffraction Data (ICDD) PDF-2. The implantation treatment is realized in high-voltage pulsed discharges at low pressures. The crystal structure of the implanted solid surfaces is analyzed by the x-ray diffraction technique which permits to identify the possible newly formed compounds and to identify any change in the surface structure of the treated samples. A decrease in the intensity of the plane (110), a reduction of the cell unity in values of 2-theta and a diminishing of the crystallite dimensions in comparison with non-implanted samples are observed.

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

NASA Astrophysics Data System (ADS)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

NASA Astrophysics Data System (ADS)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

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.

Minimal spanning trees at the percolation threshold: A numerical calculation

NASA Astrophysics Data System (ADS)

Sweeney, Sean M.; Middleton, A. Alan

2013-09-01

The fractal dimension of minimal spanning trees on percolation clusters is estimated for dimensions d up to d=5. A robust analysis technique is developed for correlated data, as seen in such trees. This should be a robust method suitable for analyzing a wide array of randomly generated fractal structures. The trees analyzed using these techniques are built using a combination of Prim's and Kruskal's algorithms for finding minimal spanning trees. This combination reduces memory usage and allows for simulation of larger systems than would otherwise be possible. The path length fractal dimension ds of MSTs on critical percolation clusters is found to be compatible with the predictions of the perturbation expansion developed by T. S. Jackson and N. Read [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.81.021131 81, 021131 (2010)].

Linear dimension reduction and Bayes classification

NASA Technical Reports Server (NTRS)

Decell, H. P., Jr.; Odell, P. L.; Coberly, W. A.

1978-01-01

An explicit expression for a compression matrix T of smallest possible left dimension K consistent with preserving the n variate normal Bayes assignment of X to a given one of a finite number of populations and the K variate Bayes assignment of TX to that population was developed. The Bayes population assignment of X and TX were shown to be equivalent for a compression matrix T explicitly calculated as a function of the means and covariances of the given populations.

The Relation between Perceived Social Support and Anxiety in Patients under Hemodialysis.

PubMed

Davaridolatabadi, Elham; Abdeyazdan, Gholamhossein

2016-03-01

The increase in the number of patients under hemodialysis treatment is a universal problem. With regard to the fact that there have been few social-psychological studies conducted on patients under hemodialysis treatment, the current study was conducted to investigate anxiety and perceived social support and the relation between them among these patients. This cross-sectional study was conducted on 126 patients under hemodialysis treatment in Isfahan in 2012. After randomly selecting a hospital with a hemodialysis ward, purposive sampling was conducted. Data collection tools included state-trait anxiety and perceived social support inventory. The data were analyzed using the Spearman correlation coefficient. Among the participants, 68.3% received average perceived social support. In addition, perceiving the tangible dimension of support was lower compared to other dimensions (Mean 40.02). Level of trait and state anxiety (65 and 67.5%) of over half of the participants was average. There was in inverse relationship between state and trait anxiety and total perceived social support and emotional and information dimensions (r = -0.340, r = -0.229). State and trait anxiety had the highest relation with emotional and information dimension of social support, respectively. Patients under hemodialysis treatment suffer from numerous psychological and social problems. Low awareness and emotional problems result in the increase of anxiety and reduction of perceived social support. Reduction of social support has negative effect on treatment outcomes.

Factors associated with changes in vaginal length and diameter during pelvic radiotherapy for cervical cancer.

PubMed

Martins, Jumara; Vaz, Ana Francisca; Grion, Regina Celia; Esteves, Sérgio Carlos Barros; Costa-Paiva, Lúcia; Baccaro, Luiz Francisco

2017-12-01

This study reports the incidence and factors associated with vaginal stenosis and changes in vaginal dimensions after pelvic radiotherapy for cervical cancer. A descriptive longitudinal study with 139 women with cervical cancer was conducted from January 2013 to November 2015. The outcome variables were vaginal stenosis assessed using the Common Terminology Criteria for Adverse Events (CTCAE v3.0) and changes in vaginal diameter and length after the end of radiotherapy. Independent variables were the characteristics of the neoplasm, clinical and sociodemographic data. Bivariate analysis was carried out using χ 2 , Kruskal-Wallis and Mann-Whitney's test. Multiple analysis was carried out using Poisson regression and a generalized linear model. Most women (50.4%) had stage IIIB tumors. According to CTCAE v3.0 scale, 30.2% had no stenosis, 69.1% had grade 1 and 0.7% had grade 2 stenosis after radiotherapy. Regarding changes in vaginal measures, the mean variation in diameter was - 0.6 (± 1.7) mm and the mean variation in length was - 0.6 (± 1.3) cm. In the final statistical model, having tumoral invasion of the vaginal walls (coefficient + 0.73, p < 0.01) and diabetes (coefficient + 1.16; p < 0.01) were associated with lower vaginal stenosis and lower reduction of vaginal dimensions. Advanced clinical stage (coefficient + 1.44; p = 0.02) and receiving brachytherapy/teletherapy (coefficient - 1.17, p < 0.01) were associated with higher reduction of vaginal dimensions. Most women had mild vaginal stenosis with slight reductions in both diameter and length of the vaginal canal. Women with tumoral invasion of the vagina have an increase in vaginal length soon after radiotherapy due to a reduction in tumoral volume.

Objective characterization of airway dimensions using image processing.

PubMed

Pepper, Victoria K; Francom, Christian; Best, Cameron A; Onwuka, Ekene; King, Nakesha; Heuer, Eric; Mahler, Nathan; Grischkan, Jonathan; Breuer, Christopher K; Chiang, Tendy

2016-12-01

With the evolution of medical and surgical management for pediatric airway disorders, the development of easily translated techniques of measuring airway dimensions can improve the quantification of outcomes of these interventions. We have developed a technique that improves the ability to characterize endoscopic airway dimensions using common bronchoscopic equipment and an open-source image-processing platform. We validated our technique of Endoscopic Airway Measurement (EAM) using optical instruments in simulation tracheas. We then evaluated EAM in a large animal model (Ovis aries, n = 5), comparing tracheal dimensions obtained with EAM to measurements obtained via 3-D fluoroscopic reconstruction. The animal then underwent resection of the measured segment, and direct measurement of this segment was performed and compared to radiographic measurements and those obtained using EAM. The simulation tracheas had a direct measurement of 13.6, 18.5, and 24.2 mm in diameter. The mean difference of diameter in simulation tracheas between direct measurements and measurements obtained using EAM was 0.70 ± 0.57 mm. The excised ovine tracheas had an average diameter of 18.54 ± 0.68 mm. The percent difference in diameter obtained from EAM and from 3-D fluoroscopic reconstruction when compared to measurement of the excised tracheal segment was 4.98 ± 2.43% and 10.74 ± 4.07% respectively. Comparison of these three measurements (EAM, measurement of resected trachea, 3-D fluoroscopic reconstruction) with repeated measures ANOVA demonstrated no statistical significance. Endoscopic airway measurement (EAM) provides equivalent measurements of the airway with the improved versatility of measuring non-circular and multi-level dimensions. Using optical bronchoscopic instruments and open-source image-processing software, our data supports preclinical and clinical translation of an accessible technique to provide objective quantification of airway diameter. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rocket launcher: A novel reduction technique for posterior hip dislocations and review of current literature.

PubMed

Dan, Michael; Phillips, Alfred; Simonian, Marcus; Flannagan, Scott

2015-06-01

We provide a review of literature on reduction techniques for posterior hip dislocations and present our experience with a novel technique for the reduction of acute posterior hip dislocations in the ED, 'the rocket launcher' technique. We present our results with six patients with prosthetic posterior hip dislocation treated in our rural ED. We recorded patient demographics. The technique involves placing the patient's knee over the shoulder, and holding the lower leg like a 'Rocket Launcher' allow the physician's shoulder to work as a fulcrum, in an ergonomically friendly manner for the reducer. We used Fisher's t-test for cohort analysis between reduction techniques. Of our patients, the mean age was 74 years (range 66 to 85 years). We had a 83% success rate. The one patient who the 'rocket launcher' failed in, was a hemi-arthroplasty patient who also failed all other closed techniques and needed open reduction. When compared with Allis (62% success rate), Whistler (60% success rate) and Captain Morgan (92% success rate) techniques, there was no statistically significant difference in the successfulness of the reduction techniques. There were no neurovascular or periprosthetic complications. We have described a reduction technique for posterior hip dislocations. Placing the patient's knee over the shoulder, and holding the lower leg like a 'Rocket Launcher' allow the physician's shoulder to work as a fulcrum, thus mechanically and ergonomically superior to standard techniques. © 2015 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Topological electronic liquids: Electronic physics of one dimension beyond the one spatial dimension

NASA Astrophysics Data System (ADS)

Wiegmann, P. B.

1999-06-01

There is a class of electronic liquids in dimensions greater than 1 that shows all essential properties of one-dimensional electronic physics. These are topological liquids-correlated electronic systems with a spectral flow. Compressible topological electronic liquids are superfluids. In this paper we present a study of a conventional model of a topological superfluid in two spatial dimensions. This model is thought to be relevant to a doped Mott insulator. We show how the spectral flow leads to the superfluid hydrodynamics and how the orthogonality catastrophe affects off-diagonal matrix elements. We also compute the major electronic correlation functions. Among them are the spectral function, the pair wave function, and various tunneling amplitudes. To compute correlation functions we develop a method of current algebra-an extension of the bosonization technique of one spatial dimension. In order to emphasize a similarity between electronic liquids in one dimension and topological liquids in dimensions greater than 1, we first review the Fröhlich-Peierls mechanism of ideal conductivity in one dimension and then extend the physics and the methods into two spatial dimensions.

Performance Analysis of Hospital Managers Using Fuzzy AHP and Fuzzy TOPSIS: Iranian Experience.

PubMed

Shafii, Milad; Hosseini, Seyed Mostafa; Arab, Mohammad; Asgharizadeh, Ezzatollah; Farzianpour, Fereshteh

2015-06-12

Hospitals are complex organizations that require strong and effective management. The success of such organizations depends on the performance of managers. This study provides a comprehensive set of indicators to assess the performance of hospital managers in Iranian Ministry of Health owned hospitals. This research was a cross-sectional study. First, reviewing the literature and using experts' viewpoints and convening a panel of experts, the dimensions of performance have been selected and came in the form of a performance model. Then, using Fuzzy Analytic Hierarchy Process (FAHP), the chosen dimensions were weighted. Finally, based on the weighted performance dimensions, a questionnaire was designed and after confirming the reliability and validity, through a census, 407 senior and middle managers from 10 hospitals in Yazd, Iran completed it and performance of CEOs in these hospitals was evaluated using the Fuzzy Technique for Order Preference by Similarity Ideal Solution (FTOPSIS). To measure the performance of hospital managers, a performance assessment model consisted of 19 sub-dimensions in 5 main dimensions (Functional, Professional, Organizational, Individual and Human) was developed. The functional area had the most weight and the individual area had the least weight, as well. The hospital managers had different performance levels in each category and sub-dimensions. In terms of overall performance, the hospital managers C and H had the best and the worst performance, respectively. The use of appropriate dimensions for performance, prioritizing them and evaluating the performance of hospital managers using appropriate techniques, can play an effective role in the selection of qualified managers, identifying strengths and weaknesses in performance and continuous improvement of them.

Influence of the Laser Spot Size, Focal Beam Profile, and Tissue Type on the Lipid Signals Obtained by MALDI-MS Imaging in Oversampling Mode

NASA Astrophysics Data System (ADS)

Wiegelmann, Marcel; Dreisewerd, Klaus; Soltwisch, Jens

2016-12-01

To improve the lateral resolution in matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) beyond the dimensions of the focal laser spot oversampling techniques are employed. However, few data are available on the effect of the laser spot size and its focal beam profile on the ion signals recorded in oversampling mode. To investigate these dependencies, we produced 2 times six spots with dimensions between 30 and 200 μm. By optional use of a fundamental beam shaper, square flat-top and Gaussian beam profiles were compared. MALDI-MSI data were collected using a fixed pixel size of 20 μm and both pixel-by-pixel and continuous raster oversampling modes on a QSTAR mass spectrometer. Coronal mouse brain sections coated with 2,5-dihydroxybenzoic acid matrix were used as primary test systems. Sizably higher phospholipid ion signals were produced with laser spots exceeding a dimension of 100 μm, although the same amount of material was essentially ablated from the 20 μm-wide oversampling pixel at all spot size settings. Only on white matter areas of the brain these effects were less apparent to absent. Scanning electron microscopy images showed that these findings can presumably be attributed to different matrix morphologies depending on tissue type. We propose that a transition in the material ejection mechanisms from a molecular desorption at large to ablation at smaller spot sizes and a concomitant reduction in ion yields may be responsible for the observed spot size effects. The combined results indicate a complex interplay between tissue type, matrix crystallization, and laser-derived desorption/ablation and finally analyte ionization.

Influence of the Laser Spot Size, Focal Beam Profile, and Tissue Type on the Lipid Signals Obtained by MALDI-MS Imaging in Oversampling Mode.

PubMed

Wiegelmann, Marcel; Dreisewerd, Klaus; Soltwisch, Jens

2016-12-01

To improve the lateral resolution in matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) beyond the dimensions of the focal laser spot oversampling techniques are employed. However, few data are available on the effect of the laser spot size and its focal beam profile on the ion signals recorded in oversampling mode. To investigate these dependencies, we produced 2 times six spots with dimensions between ~30 and 200 μm. By optional use of a fundamental beam shaper, square flat-top and Gaussian beam profiles were compared. MALDI-MSI data were collected using a fixed pixel size of 20 μm and both pixel-by-pixel and continuous raster oversampling modes on a QSTAR mass spectrometer. Coronal mouse brain sections coated with 2,5-dihydroxybenzoic acid matrix were used as primary test systems. Sizably higher phospholipid ion signals were produced with laser spots exceeding a dimension of ~100 μm, although the same amount of material was essentially ablated from the 20 μm-wide oversampling pixel at all spot size settings. Only on white matter areas of the brain these effects were less apparent to absent. Scanning electron microscopy images showed that these findings can presumably be attributed to different matrix morphologies depending on tissue type. We propose that a transition in the material ejection mechanisms from a molecular desorption at large to ablation at smaller spot sizes and a concomitant reduction in ion yields may be responsible for the observed spot size effects. The combined results indicate a complex interplay between tissue type, matrix crystallization, and laser-derived desorption/ablation and finally analyte ionization. Graphical Abstract ᅟ.

A Comparison of Accuracy of Matrix Impression System with Putty Reline Technique and Multiple Mix Technique: An In Vitro Study

PubMed Central

Kumar, M Praveen; Patil, Suneel G; Dheeraj, Bhandari; Reddy, Keshav; Goel, Dinker; Krishna, Gopi

2015-01-01

Background: The difficulty in obtaining an acceptable impression increases exponentially as the number of abutments increases. Accuracy of the impression material and the use of a suitable impression technique are of utmost importance in the fabrication of a fixed partial denture. This study compared the accuracy of the matrix impression system with conventional putty reline and multiple mix technique for individual dies by comparing the inter-abutment distance in the casts obtained from the impressions. Materials and Methods: Three groups, 10 impressions each with three impression techniques (matrix impression system, putty reline technique and multiple mix technique) were made of a master die. Typodont teeth were embedded in a maxillary frasaco model base. The left first premolar was removed to create a three-unit fixed partial denture situation and the left canine and second premolar were prepared conservatively, and hatch marks were made on the abutment teeth. The final casts obtained from the impressions were examined under a profile projector and the inter-abutment distance was calculated for all the casts and compared. Results: The results from this study showed that in the mesiodistal dimensions the percentage deviation from master model in Group I was 0.1 and 0.2, in Group II was 0.9 and 0.3, and Group III was 1.6 and 1.5, respectively. In the labio-palatal dimensions the percentage deviation from master model in Group I was 0.01 and 0.4, Group II was 1.9 and 1.3, and Group III was 2.2 and 2.0, respectively. In the cervico-incisal dimensions the percentage deviation from the master model in Group I was 1.1 and 0.2, Group II was 3.9 and 1.7, and Group III was 1.9 and 3.0, respectively. In the inter-abutment dimension of dies, percentage deviation from master model in Group I was 0.1, Group II was 0.6, and Group III was 1.0. Conclusion: The matrix impression system showed more accuracy of reproduction for individual dies when compared with putty reline technique and multiple mix technique in all the three directions, as well as the inter-abutment distance. PMID:26124599

Defining Malaysian Knowledge Society: Results from the Delphi Technique

NASA Astrophysics Data System (ADS)

Hamid, Norsiah Abdul; Zaman, Halimah Badioze

This paper outlines the findings of research where the central idea is to define the term Knowledge Society (KS) in Malaysian context. The research focuses on three important dimensions, namely knowledge, ICT and human capital. This study adopts a modified Delphi technique to seek the important dimensions that can contribute to the development of Malaysian's KS. The Delphi technique involved ten experts in a five-round iterative and controlled feedback procedure to obtain consensus on the important dimensions and to verify the proposed definition of KS. The finding shows that all three dimensions proposed initially scored high and moderate consensus. Round One (R1) proposed an initial definition of KS and required comments and inputs from the panel. These inputs were then used to develop items for a R2 questionnaire. In R2, 56 out of 73 items scored high consensus and in R3, 63 out of 90 items scored high. R4 was conducted to re-rate the new items, in which 8 out of 17 items scored high. Other items scored moderate consensus and no item scored low or no consensus in all rounds. The final round (R5) was employed to verify the final definition of KS. Findings and discovery of this study are significant to the definition of KS and the development of a framework in the Malaysian context.

Psychometric and Edumetric Validity of Dimensions of Geomorphological Knowledge Which Are Tapped by Concept Mapping.

ERIC Educational Resources Information Center

Hoz, Ron; Bowman, Dan; Chacham, Tova

1997-01-01

Students (N=14) in a geomorphology course took an objective geomorphology test, the tree construction task, and the Standardized Concept Structuring Analysis Technique (SConSAT) version of concept mapping. Results suggest that the SConSAT knowledge structure dimensions have moderate to good construct validity. Contains 82 references. (DDR)

The human dimensions of urban greenways: planning for recreation and related experiences

Treesearch

Paul H. Gobster; Lynne M. Westpahl

2004-01-01

In this paper, we summarize findings from a series of interrelated studies that examine an urban greenway, the 150 mile Chicago River corridor in Chicago, USA, from multiple perspectives, stakeholder viewpoints, and methodological techniques. Six interdependent "human dimensions" of greenways are identified in the studies: cleanliness, naturalness, aesthetics...

Examining the Organizational Cynicism among Teachers at Schools: A Mixed Methods Study

ERIC Educational Resources Information Center

Levent, Faruk; Keser, Sitar

2016-01-01

The purpose of this study is to examine the organizational cynicism among teachers at schools. In this study, which was conducted by a mixed method, "the Organizational Cynicism Scale for Teachers" was used in the quantitative dimension, while a semi-structured interviewing technique was used in the qualitative dimension. The…

Using Logistic Approximations of Marginal Trace Lines to Develop Short Assessments

ERIC Educational Resources Information Center

Stucky, Brian D.; Thissen, David; Edelen, Maria Orlando

2013-01-01

Test developers often need to create unidimensional scales from multidimensional data. For item analysis, "marginal trace lines" capture the relation with the general dimension while accounting for nuisance dimensions and may prove to be a useful technique for creating short-form tests. This article describes the computations needed to obtain…

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

PubMed Central

Charland, Patrick; Léger, Pierre-Majorique; Sénécal, Sylvain; Courtemanche, François; Mercier, Julien; Skelling, Yannick; Labonté-Lemoyne, Elise

2015-01-01

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: behavioral, emotional and cognitive. They observed that individual types of engagement had not been studied in conjunction, and little information was available about interactions or synergy between the dimensions; consequently, more studies would contribute to creating finely tuned teaching interventions. Benefiting from the recent technological advances in neurosciences, this paper presents a recently developed methodology to gather and synchronize data on multidimensional engagement during learning tasks. The technique involves the collection of (a) electroencephalography, (b) electrodermal, (c) eye-tracking, and (d) facial emotion recognition data on four different computers. This led to synchronization issues for data collected from multiple sources. Post synchronization in specialized integration software gives researchers a better understanding of the dynamics between the multiple dimensions of engagement. For curriculum developers, these data could provide informed guidelines for achieving better instruction/learning efficiency. This technique also opens up possibilities in the field of brain-computer interactions, where adaptive learning or assessment environments could be developed. PMID:26167712

A systematic comparison of the closed shoulder reduction techniques.

PubMed

Alkaduhimi, H; van der Linde, J A; Willigenburg, N W; van Deurzen, D F P; van den Bekerom, M P J

2017-05-01

To identify the optimal technique for closed reduction for shoulder instability, based on success rates, reduction time, complication risks, and pain level. A PubMed and EMBASE query was performed, screening all relevant literature of closed reduction techniques mentioning the success rate written in English, Dutch, German, and Arabic. Studies with a fracture dislocation or lacking information on success rates for closed reduction techniques were excluded. We used the modified Coleman Methodology Score (CMS) to assess the quality of included studies and excluded studies with a poor methodological quality (CMS < 50). Finally, a meta-analysis was performed on the data from all studies combined. 2099 studies were screened for their title and abstract, of which 217 studies were screened full-text and finally 13 studies were included. These studies included 9 randomized controlled trials, 2 retrospective comparative studies, and 2 prospective non-randomized comparative studies. A combined analysis revealed that the scapular manipulation is the most successful (97%), fastest (1.75 min), and least painful reduction technique (VAS 1,47); the "Fast, Reliable, and Safe" (FARES) method also scores high in terms of successful reduction (92%), reduction time (2.24 min), and intra-reduction pain (VAS 1.59); the traction-countertraction technique is highly successful (95%), but slower (6.05 min) and more painful (VAS 4.75). For closed reduction of anterior shoulder dislocations, the combined data from the selected studies indicate that scapular manipulation is the most successful and fastest technique, with the shortest mean hospital stay and least pain during reduction. The FARES method seems the best alternative.

Use of Extended Flute Techniques in Flute Education in Turkey

ERIC Educational Resources Information Center

Sakin, Ajda Senol

2018-01-01

Extended flute techniques, which are frequently found in contemporary flute literature, carry the flute to a different dimension, pushing the boundaries of composers and performers. Although the number of pieces containing these techniques in the world has increased rapidly, along with Turkish flute repertoire, written Turkish sources about…

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

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

Choi, Youngsoo; Carlberg, Kevin Thomas

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over allmore » space and time in a weighted ℓ 2-norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.« less

The "clover technique" as a novel approach for correction of post-traumatic tricuspid regurgitation.

PubMed

Alfieri, O; De Bonis, M; Lapenna, E; Agricola, E; Quarti, A; Maisano, F

2003-07-01

To describe a novel technique, named "clover," to correct complex post-traumatic tricuspid valve lesions. Five patients with severe post-traumatic tricuspid insufficiency underwent valve reconstruction with the clover technique, a new surgical approach that consists of stitching together the middle point of the free edges of the tricuspid leaflets, producing a clover-shaped valve. The mechanism of tricuspid regurgitation was complex in all patients, and right ventricular function was always moderately to severely depressed. An echocardiographic study was performed after cardiopulmonary bypass, at discharge, and at follow-up. Cardiopulmonary bypass time was 32 +/- 6.3 minutes and crossclamp time was 23 +/- 7.4. There was no hospital mortality or morbidity. Intraoperative transesophageal and predischarge transthoracic echocardiography showed perfect results in all patients. No late deaths occurred. At the latest follow-up, extending to 14.2 months (mean 11.3; median 12.4), all patients were asymptomatic (New York Heart Association class I) with trivial (2 patients) or no residual regurgitation (3 patients) on 2-dimensional echocardiogram. No transvalvular gradient was revealed in any patient. A significant reduction of the right ventricular end-diastolic dimensions was noted as well (from 54 +/- 7.1 mm to 40 +/- 7.5 mm, P <.001). In this preliminary experience, the clover technique increased the feasibility of tricuspid valve repair in case of severe traumatic tricuspid valve insufficiency, leading to very satisfactory mid-term results even in the presence of complex lesions or dilatation and deterioration of the right ventricle.

Nanoscale electrode arrays produced with microscale lithographic techniques for use in biomedical sensing applications.

PubMed

Terry, Jonathan G; Schmüser, Ilka; Underwood, Ian; Corrigan, Damion K; Freeman, Neville J; Bunting, Andrew S; Mount, Andrew R; Walton, Anthony J

2013-12-01

A novel technique for the production of nanoscale electrode arrays that uses standard microfabrication processes and micron-scale photolithography is reported here in detail. These microsquare nanoband edge electrode (MNEE) arrays have been fabricated with highly reproducible control of the key array dimensions, including the size and pitch of the individual elements and, most importantly, the width of the nanoband electrodes. The definition of lateral features to nanoscale dimensions typically requires expensive patterning techniques that are complex and low-throughput. However, the fabrication methodology used here relies on the fact that vertical dimensions (i.e. layer thicknesses) have long been manufacturable at the nanoscale using thin film deposition techniques that are well established in mainstream microelectronics. The authors report for the first time two aspects that highlight the particular suitability of these MNEE array systems for probe monolayer biosensing. The first is simulation, which shows the enhanced sensitivity to the redox reaction of the solution redox couple. The second is the enhancement of probe film functionalisation observed for the probe film model molecule, 6-mercapto-1-hexanol compared with microsquare electrodes. Such surface modification for specific probe layer biosensing and detection is of significance for a wide range of biomedical and other sensing and analytical applications.

Study to design and develop remote manipulator system

NASA Technical Reports Server (NTRS)

Hill, J. W.; Sword, A. J.

1973-01-01

Human performance measurement techniques for remote manipulation tasks and remote sensing techniques for manipulators are described for common manipulation tasks, performance is monitored by means of an on-line computer capable of measuring the joint angles of both master and slave arms as a function of time. The computer programs allow measurements of the operator's strategy and physical quantities such as task time and power consumed. The results are printed out after a test run to compare different experimental conditions. For tracking tasks, we describe a method of displaying errors in three dimensions and measuring the end-effector position in three dimensions.

A decentralized linear quadratic control design method for flexible structures

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1990-01-01

A decentralized suboptimal linear quadratic control design procedure which combines substructural synthesis, model reduction, decentralized control design, subcontroller synthesis, and controller reduction is proposed for the design of reduced-order controllers for flexible structures. The procedure starts with a definition of the continuum structure to be controlled. An evaluation model of finite dimension is obtained by the finite element method. Then, the finite element model is decomposed into several substructures by using a natural decomposition called substructuring decomposition. Each substructure, at this point, still has too large a dimension and must be reduced to a size that is Riccati-solvable. Model reduction of each substructure can be performed by using any existing model reduction method, e.g., modal truncation, balanced reduction, Krylov model reduction, or mixed-mode method. Then, based on the reduced substructure model, a subcontroller is designed by an LQ optimal control method for each substructure independently. After all subcontrollers are designed, a controller synthesis method called substructural controller synthesis is employed to synthesize all subcontrollers into a global controller. The assembling scheme used is the same as that employed for the structure matrices. Finally, a controller reduction scheme, called the equivalent impulse response energy controller (EIREC) reduction algorithm, is used to reduce the global controller to a reasonable size for implementation. The EIREC reduced controller preserves the impulse response energy of the full-order controller and has the property of matching low-frequency moments and low-frequency power moments. An advantage of the substructural controller synthesis method is that it relieves the computational burden associated with dimensionality. Besides that, the SCS design scheme is also a highly adaptable controller synthesis method for structures with varying configuration, or varying mass and stiffness properties.

Recognizing human activities using appearance metric feature and kinematics feature

NASA Astrophysics Data System (ADS)

Qian, Huimin; Zhou, Jun; Lu, Xinbiao; Wu, Xinye

2017-05-01

The problem of automatically recognizing human activities from videos through the fusion of the two most important cues, appearance metric feature and kinematics feature, is considered. And a system of two-dimensional (2-D) Poisson equations is introduced to extract the more discriminative appearance metric feature. Specifically, the moving human blobs are first detected out from the video by background subtraction technique to form a binary image sequence, from which the appearance feature designated as the motion accumulation image and the kinematics feature termed as centroid instantaneous velocity are extracted. Second, 2-D discrete Poisson equations are employed to reinterpret the motion accumulation image to produce a more differentiated Poisson silhouette image, from which the appearance feature vector is created through the dimension reduction technique called bidirectional 2-D principal component analysis, considering the balance between classification accuracy and time consumption. Finally, a cascaded classifier based on the nearest neighbor classifier and two directed acyclic graph support vector machine classifiers, integrated with the fusion of the appearance feature vector and centroid instantaneous velocity vector, is applied to recognize the human activities. Experimental results on the open databases and a homemade one confirm the recognition performance of the proposed algorithm.

Data-driven in computational plasticity

NASA Astrophysics Data System (ADS)

Ibáñez, R.; Abisset-Chavanne, E.; Cueto, E.; Chinesta, F.

2018-05-01

Computational mechanics is taking an enormous importance in industry nowadays. On one hand, numerical simulations can be seen as a tool that allows the industry to perform fewer experiments, reducing costs. On the other hand, the physical processes that are intended to be simulated are becoming more complex, requiring new constitutive relationships to capture such behaviors. Therefore, when a new material is intended to be classified, an open question still remains: which constitutive equation should be calibrated. In the present work, the use of model order reduction techniques are exploited to identify the plastic behavior of a material, opening an alternative route with respect to traditional calibration methods. Indeed, the main objective is to provide a plastic yield function such that the mismatch between experiments and simulations is minimized. Therefore, once the experimental results just like the parameterization of the plastic yield function are provided, finding the optimal plastic yield function can be seen either as a traditional optimization or interpolation problem. It is important to highlight that the dimensionality of the problem is equal to the number of dimensions related to the parameterization of the yield function. Thus, the use of sparse interpolation techniques seems almost compulsory.

Examining deterrence of adult sex crimes: A semi-parametric intervention time series approach.

PubMed

Park, Jin-Hong; Bandyopadhyay, Dipankar; Letourneau, Elizabeth

2014-01-01

Motivated by recent developments on dimension reduction (DR) techniques for time series data, the association of a general deterrent effect towards South Carolina (SC)'s registration and notification (SORN) policy for preventing sex crimes was examined. Using adult sex crime arrestee data from 1990 to 2005, the the idea of Central Mean Subspace (CMS) is extended to intervention time series analysis (CMS-ITS) to model the sequential intervention effects of 1995 (the year SC's SORN policy was initially implemented) and 1999 (the year the policy was revised to include online notification) on the time series spectrum. The CMS-ITS model estimation was achieved via kernel smoothing techniques, and compared to interrupted auto-regressive integrated time series (ARIMA) models. Simulation studies and application to the real data underscores our model's ability towards achieving parsimony, and to detect intervention effects not earlier determined via traditional ARIMA models. From a public health perspective, findings from this study draw attention to the potential general deterrent effects of SC's SORN policy. These findings are considered in light of the overall body of research on sex crime arrestee registration and notification policies, which remain controversial.

SU-E-J-81: Adaptive Radiotherapy for IMRT Head & Neck Patient in AKUH

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

Yousuf, A; Qureshi, B; Qadir, A

2015-06-15

Purpose: In this study we proposed Adaptive radiotherapy for IMRT patients which will brought an additional dimension to the management of patients with H&N cancer in Aga Khan University Hospital. Methods: In this study 5 Head and Neck (H&N) patients plan where selected, who’s Re-CT were done during the course of their treatment, they were simulated with IMRT technique to learn the consequence of anatomical changes that may occur during the treatment, as they are more dramatic changes can occur as compare to conventional treatment. All the organ at risk were drawn according RTOG guidelines and doses were checked asmore » per NCCN guidelines. Results: The reduction in size of Planning target volume (PTV) is more than 20% in all the cases which leads to 3 to 5 % overdose to normal tissues and Organ at Risk. Conclusion: Through this study we would like to emphasis the importance of Adaptive Radiotherapy practice in all IMRT (H&N) patients, although prospective studies are required with larger sample sizes to address the safety and the clinical effect of such approaches on patient outcome, also one need to develop protocols before implementation of this technique in practice.« less

Application of copulas to improve covariance estimation for partial least squares.

PubMed

D'Angelo, Gina M; Weissfeld, Lisa A

2013-02-20

Dimension reduction techniques, such as partial least squares, are useful for computing summary measures and examining relationships in complex settings. Partial least squares requires an estimate of the covariance matrix as a first step in the analysis, making this estimate critical to the results. In addition, the covariance matrix also forms the basis for other techniques in multivariate analysis, such as principal component analysis and independent component analysis. This paper has been motivated by an example from an imaging study in Alzheimer's disease where there is complete separation between Alzheimer's and control subjects for one of the imaging modalities. This separation occurs in one block of variables and does not occur with the second block of variables resulting in inaccurate estimates of the covariance. We propose the use of a copula to obtain estimates of the covariance in this setting, where one set of variables comes from a mixture distribution. Simulation studies show that the proposed estimator is an improvement over the standard estimators of covariance. We illustrate the methods from the motivating example from a study in the area of Alzheimer's disease. Copyright © 2012 John Wiley & Sons, Ltd.

An Experimental Investigation into Additive Manufacturing-Induced Residual Stresses in 316L Stainless Steel

NASA Astrophysics Data System (ADS)

Wu, Amanda S.; Brown, Donald W.; Kumar, Mukul; Gallegos, Gilbert F.; King, Wayne E.

2014-12-01

Additive manufacturing (AM) technology provides unique opportunities for producing net-shape geometries at the macroscale through microscale processing. This level of control presents inherent trade-offs necessitating the establishment of quality controls aimed at minimizing undesirable properties, such as porosity and residual stresses. Here, we perform a parametric study into the effects of laser scanning pattern, power, speed, and build direction in powder bed fusion AM on residual stress. In an effort to better understand the factors influencing macroscale residual stresses, a destructive surface residual stress measurement technique (digital image correlation in conjunction with build plate removal and sectioning) has been coupled with a nondestructive volumetric evaluation method ( i.e., neutron diffraction). Good agreement between the two measurement techniques is observed. Furthermore, a reduction in residual stress is obtained by decreasing scan island size, increasing island to wall rotation to 45 deg, and increasing applied energy per unit length (laser power/speed). Neutron diffraction measurements reveal that, while in-plane residual stresses are affected by scan island rotation, axial residual stresses are unchanged. We attribute this in-plane behavior to misalignment between the greatest thermal stresses (scan direction) and largest part dimension.

Locating landmarks on high-dimensional free energy surfaces

PubMed Central

Chen, Ming; Yu, Tang-Qing; Tuckerman, Mark E.

2015-01-01

Coarse graining of complex systems possessing many degrees of freedom can often be a useful approach for analyzing and understanding key features of these systems in terms of just a few variables. The relevant energy landscape in a coarse-grained description is the free energy surface as a function of the coarse-grained variables, which, despite the dimensional reduction, can still be an object of high dimension. Consequently, navigating and exploring this high-dimensional free energy surface is a nontrivial task. In this paper, we use techniques from multiscale modeling, stochastic optimization, and machine learning to devise a strategy for locating minima and saddle points (termed “landmarks”) on a high-dimensional free energy surface “on the fly” and without requiring prior knowledge of or an explicit form for the surface. In addition, we propose a compact graph representation of the landmarks and connections between them, and we show that the graph nodes can be subsequently analyzed and clustered based on key attributes that elucidate important properties of the system. Finally, we show that knowledge of landmark locations allows for the efficient determination of their relative free energies via enhanced sampling techniques. PMID:25737545

Reducing particle dimensions of chunkwood.

Treesearch

Robert C. Radcliffe

1990-01-01

Presents and compares the chunkwood sizes obtainable with the USDA Forest Service prototype wood chunker using four different blade configurations, and the results of further chunkwood reduction with three methods totally separate from the chunking process.

The Effect of Atrial Fibrillation Ablation Techniques on P Wave Duration and P Wave Dispersion.

PubMed

Furniss, Guy O; Panagopoulos, Dimitrios; Kanoun, Sadeek; Davies, Edward J; Tomlinson, David R; Haywood, Guy A

2018-02-14

A reduction in surface electrocardiogram (ECG) P wave duration and dispersion is associated with improved outcomes in atrial fibrillation ablation. We investigated the effects of different ablation strategies on P wave duration and dispersion, hypothesising that extensive left atrial (LA) ablation with left atrial posterior wall isolation would give a greater reduction in P wave duration than more limited ablation techniques. A retrospective analysis of ECGs from patients who have undergone atrial fibrillation (AF) ablation was performed and pre-procedural sinus rhythm ECGs were compared with the post procedure ECGs. Maximal P wave duration was measured in leads I or II, minimum P wave duration in any lead and values were calculated for P wave duration and dispersion. Left atrial dimensions and medications at the time of ECG were documented. Ablation strategies compared were; pulmonary vein isolation (PVI) for paroxysmal atrial fibrillation (PAF) and the persistent AF (PsAF) ablation strategies of pulmonary vein isolation plus additional linear lesions (Lines), left atrial posterior wall isolation via catheter (PWI) and left atrial posterior wall isolation via staged surgical and catheter ablation (Hybrid). Sixty-nine patients' ECGs were analysed: 19 PVI, 21 Lines, 14 PWI, 15 Hybrid. Little correlation was seen between pre-procedure left atrial size and P wave duration (r=0.24) but LA size and P wave duration was larger in PsAF patients. A significant difference was seen in P wave reduction driven by Hybrid AF ablation (p<0.005) and Lines (<0.02). There was no difference amongst P wave dispersion between groups but the largest reduction was seen in the Hybrid ablation group. P wave duration increased with duration of continuous atrial fibrillation. Hybrid AF ablation significantly reduced P wave duration and dispersion compared to other ablation strategies including posterior wall isolation via catheter despite this being the same lesion set. Copyright © 2018 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

Model-based reinforcement learning with dimension reduction.

PubMed

Tangkaratt, Voot; Morimoto, Jun; Sugiyama, Masashi

2016-12-01

The goal of reinforcement learning is to learn an optimal policy which controls an agent to acquire the maximum cumulative reward. The model-based reinforcement learning approach learns a transition model of the environment from data, and then derives the optimal policy using the transition model. However, learning an accurate transition model in high-dimensional environments requires a large amount of data which is difficult to obtain. To overcome this difficulty, in this paper, we propose to combine model-based reinforcement learning with the recently developed least-squares conditional entropy (LSCE) method, which simultaneously performs transition model estimation and dimension reduction. We also further extend the proposed method to imitation learning scenarios. The experimental results show that policy search combined with LSCE performs well for high-dimensional control tasks including real humanoid robot control. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparisons of non-Gaussian statistical models in DNA methylation analysis.

PubMed

Ma, Zhanyu; Teschendorff, Andrew E; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-06-16

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance.

Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis

PubMed Central

Ma, Zhanyu; Teschendorff, Andrew E.; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-01-01

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance. PMID:24937687

Novel, in-situ Raman and fluorescence measurement techniques: Imaging using optical waveguides

NASA Astrophysics Data System (ADS)

Carter, Jerry Chance

The following dissertation describes the development of methods for performing standoff and in- situ Raman and fluorescence spectroscopy for chemical imaging and non-imaging analytical applications. The use of Raman spectroscopy for the in- situ identification of crack cocaine and cocaine.HCl using a fiberoptic Raman probe and a portable Raman spectrograph has been demonstrated. We show that the Raman spectra of both forms of cocaine are easily distinguishable from common cutting agents and impurities such as benzocaine and lidocaine. We have also demonstrated the use of Raman spectroscopy for in-situ identification of drugs separated by thin layer chromatography. We have investigated the use of small, transportable, Raman systems for standoff Raman spectroscopy (e.g. <20 m). For this work, acousto-optical (AOTF) and liquid crystal tunable filters (LCTF) are being used both with, and in place of dispersive spectrographs and fixed filtering devices. In addition, we improved the flexibility of the system by the use of a modified holographic fiber-optic probe for light and image collection. A comparison of tunable filter technologies for standoff Raman imaging is discussed along with the merits of image transfer devices using small diameter image guides. A standoff Raman imaging system has been developed that utilizes a unique polymer collection mirror. The techniques used to produce these mirrors make it easy to design low f/# polymer mirrors. The performance of a low f/# polymer mirror system for standoff Raman chemical imaging has been demonstrated and evaluated. We have also demonstrated remote Raman hyperspectral imaging using a dimension-reduction, 2-dimensional (2-D) to 1-dimensional (1-D), fiber optic array. In these studies, a modified holographic fiber-optic probe was combined with the dimension-reduction fiber array for remote Raman imaging. The utility of this setup for standoff Raman imaging is demonstrated by monitoring the polymerization of dibromostyrene. To further demonstrate the utility of in- situ spectral imaging, we have shown that small diameter (350 μm) image guides can be used for in-situ measurements of analyte transport in thin membranes. This has been applied to the measurement of H2O diffusion in Nafion™ membranes using the luminescent compound, [Ru(phen)2dppz] 2+, which is a H2O indicator.

Two dimensional laser induced fluorescence in the gas phase: a spectroscopic tool for studying molecular spectroscopy and dynamics

NASA Astrophysics Data System (ADS)

Gascooke, Jason R.; Lawrance, Warren D.

2017-11-01

Two dimensional laser induced fluorescence (2D-LIF) extends the usual laser induced fluorescence technique by adding a second dimension, the wavelength at which excited states emit, thereby significantly enhancing the information that can be extracted. It allows overlapping absorption features, whether they arise from within the same molecule or from different molecules in a mixture, to be associated with their appropriate "parent" state and/or molecule. While the first gas phase version of the technique was published a decade ago, the technique is in its infancy, having been exploited by only a few groups to date. However, its potential in gas phase spectroscopy and dynamics is significant. In this article we provide an overview of the technique and illustrate its potential with examples, with a focus on those utilising high resolution in the dispersed fluorescence dimension.

Bone Replacement Materials and Techniques Used for Achieving Vertical Alveolar Bone Augmentation

PubMed Central

Sheikh, Zeeshan; Sima, Corneliu; Glogauer, Michael

2015-01-01

Alveolar bone augmentation in vertical dimension remains the holy grail of periodontal tissue engineering. Successful dental implant placement for restoration of edentulous sites depends on the quality and quantity of alveolar bone available in all spatial dimensions. There are several surgical techniques used alone or in combination with natural or synthetic graft materials to achieve vertical alveolar bone augmentation. While continuously improving surgical techniques combined with the use of auto- or allografts provide the most predictable clinical outcomes, their success often depends on the status of recipient tissues. The morbidity associated with donor sites for auto-grafts makes these techniques less appealing to both patients and clinicians. New developments in material sciences offer a range of synthetic replacements for natural grafts to address the shortcoming of a second surgical site and relatively high resorption rates. This narrative review focuses on existing techniques, natural tissues and synthetic biomaterials commonly used to achieve vertical bone height gain in order to successfully restore edentulous ridges with implant-supported prostheses.

Probing plasmons in three dimensions by combining complementary spectroscopies in a scanning transmission electron microscope

DOE PAGES

Hachtel, Jordan A.; Marvinney, Claire; Mouti, Anas; ...

2016-03-02

The nanoscale optical response of surface plasmons in three-dimensional metallic nanostructures plays an important role in many nanotechnology applications, where precise spatial and spectral characteristics of plasmonic elements control device performance. Electron energy loss spectroscopy (EELS) and cathodoluminescence (CL) within a scanning transmission electron microscope have proven to be valuable tools for studying plasmonics at the nanoscale. Each technique has been used separately, producing three-dimensional reconstructions through tomography, often aided by simulations for complete characterization. Here we demonstrate that the complementary nature of the two techniques, namely that EELS probes beam-induced electronic excitations while CL probes radiative decay, allows usmore » to directly obtain a spatially- and spectrally-resolved picture of the plasmonic characteristics of nanostructures in three dimensions. Furthermore, the approach enables nanoparticle-by-nanoparticle plasmonic analysis in three dimensions to aid in the design of diverse nanoplasmonic applications.« less

Conscious motor processing and movement self-consciousness: two dimensions of personality that influence laparoscopic training.

PubMed

Malhotra, Neha; Poolton, Jamie M; Wilson, Mark R; Fan, Joe K M; Masters, Rich S W

2014-01-01

Identifying personality factors that account for individual differences in surgical training and performance has practical implications for surgical education. Movement-specific reinvestment is a potentially relevant personality factor that has a moderating effect on laparoscopic performance under time pressure. Movement-specific reinvestment has 2 dimensions, which represent an individual's propensity to consciously control movements (conscious motor processing) or to consciously monitor their 'style' of movement (movement self-consciousness). This study aimed at investigating the moderating effects of the 2 dimensions of movement-specific reinvestment in the learning and updating (cross-handed technique) of laparoscopic skills. Medical students completed the Movement-Specific Reinvestment Scale, a psychometric assessment tool that evaluates the conscious motor processing and movement self-consciousness dimensions of movement-specific reinvestment. They were then trained to a criterion level of proficiency on a fundamental laparoscopic skills task and were tested on a novel cross-handed technique. Completion times were recorded for early-learning, late-learning, and cross-handed trials. Propensity for movement self-consciousness but not conscious motor processing was a significant predictor of task completion times both early (p = 0.036) and late (p = 0.002) in learning, but completion times during the cross-handed trials were predicted by the propensity for conscious motor processing (p = 0.04) rather than movement self-consciousness (p = 0.21). Higher propensity for movement self-consciousness is associated with slower performance times on novel and well-practiced laparoscopic tasks. For complex surgical techniques, however, conscious motor processing plays a more influential role in performance than movement self-consciousness. The findings imply that these 2 dimensions of movement-specific reinvestment have a differential influence in the learning and updating of laparoscopic skills. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

NASA Astrophysics Data System (ADS)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

The effect of osteotomy dimension on osseointegration to resorbable media-treated implants: a study in the sheep.

PubMed

Galli, Silvia; Jimbo, Ryo; Tovar, Nick; Yoo, Daniel Y; Anchieta, Rodolfo B; Yamaguchi, Satoshi; Coelho, Paulo G

2015-03-01

The drilling technique and the surface characteristics are known to influence the healing times of oral implants. The influence of osteotomy dimension on osseointegration of microroughned implant surfaces treated with resorbable blasting media was tested in an in vivo model. Ninety-six implants (ø4.5 mm, 8 mm in length) with resorbable blasting media-treated surfaces were placed in the ileum of six sheep. The final osteotomy diameters were 4.6 mm (reamer), 4.1 mm (loose), 3.7 mm (medium), and 3.2 mm (tight). After three and six weeks of healing, the implants were biomechanically tested and histologically evaluated. Statistical analysis was performed using Page L trend test for ordered and paired sample and linear regression, with significance level at p < 0.05. An overall increase in all dependent variables was observed with the reduction of osteotomy diameter. In addition, all osseointegration scores increased over time. At three weeks, the retention was significantly higher for smaller osteotomies. The histological sections depicted intimate contact of bone with all the implant surfaces and osteoblast lines were visible in all sections. The resorbable blasting media microroughed surfaces achieved successful osseointegration for all the instrumentation procedures tested, with higher osseointegration scores for the high insertion torque group. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Supersymmetric electric-magnetic duality in D =3 +3 and D =5 +5 dimensions as foundation of self-dual supersymmetric Yang-Mills theory

NASA Astrophysics Data System (ADS)

Nishino, Hitoshi; Rajpoot, Subhash

2016-05-01

We present electric-magnetic (EM)-duality formulations for non-Abelian gauge groups with N =1 supersymmetry in D =3 +3 and 5 +5 space-time dimensions. We show that these systems generate self-dual N =1 supersymmetric Yang-Mills (SDSYM) theory in D =2 +2 . For a N =2 supersymmetric EM-dual system in D =3 +3 , we have the Yang-Mills multiplet (Aμ I,λA I) and a Hodge-dual multiplet (Bμν ρ I,χA I) , with an auxiliary tensors Cμν ρ σ I and Kμ ν. Here, I is the adjoint index, while A is for the doublet of S p (1 ). The EM-duality conditions are Fμν I=(1 /4 !)ɛμν ρ σ τ λGρσ τ λ I with its superpartner duality condition λA I=-χA I . Upon appropriate dimensional reduction, this system generates SDSYM in D =2 +2 . This system is further generalized to D =5 +5 with the EM-duality condition Fμν I=(1 /8 !)ɛμν ρ1⋯ρ8Gρ1⋯ρ8 I with its superpartner condition λI=-χI . Upon appropriate dimensional reduction, this theory also generates SDSYM in D =2 +2 . As long as we maintain Lorentz covariance, D =5 +5 dimensions seems to be the maximal space-time dimensions that generate SDSYM in D =2 +2 . Namely, EM-dual system in D =5 +5 serves as the Master Theory of all supersymmetric integrable models in dimensions 1 ≤D ≤3 .

Resolution enhancement in in vivo NMR spectroscopy: detection of intermolecular zero-quantum coherences

NASA Astrophysics Data System (ADS)

Faber, Cornelius; Pracht, Eberhard; Haase, Axel

2003-04-01

Intermolecular zero-quantum coherences are insensitive to magnetic field inhomogeneities. For this reason we have applied the HOMOGENIZED sequence [Vathyam et al., Science 272 (1996) 92] to phantoms containing metabolites at low concentrations, phantoms with air inclusions, an intact grape, and the head of a rat in vivo at 750 MHz. In the 1H-spectra, the water signal is efficiently suppressed and line broadening due to susceptibility gradients is effectively removed along the indirectly detected dimension. We have obtained a 1H-spectrum of a 2.5 mM solution of γ-aminobutyric acid in 12 min scan time. In the phantom with air inclusions a reduction of line widths from 0.48 ppm in the direct dimension to 0.07 ppm in the indirect dimension was observed, while in a deshimmed grape the reduction was from 1.4 to 0.07 ppm. In a spectrum of the grape we were able to resolve glucose resonances at 0.3 ppm from the water in 6 min scan time. J-coupling information was partly retained. In the in vivo spectra of the rat brain five major metabolites were observed.

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

Dimensions of the scala tympani in the human and cat with reference to cochlear implants.

PubMed

Hatsushika, S; Shepherd, R K; Tong, Y C; Clark, G M; Funasaka, S

1990-11-01

The width, height, and cross-sectional area of the scala tympani in both the human and cat were measured to provide dimensional information relevant to the design of scala tympani electrode arrays. Both the height and width of the human scala tympani decreased rapidly within the first 1.5 mm from the round window. Thereafter, they exhibit a gradual reduction in their dimension with increasing distance from the round window. The cross-sectional area of the human scala tympani reflects the changes observed in both the height and width. In contrast, the cat scala tympani exhibits a rapid decrease in its dimensions over the first 6 to 8 mm from the round window. However, beyond this point the cat scala tympani also exhibits a more gradual decrease in its dimensions. Finally, the width of the scala tympani, in both human and cat, is consistently greater than the height.

An error bound for a discrete reduced order model of a linear multivariable system

NASA Technical Reports Server (NTRS)

Al-Saggaf, Ubaid M.; Franklin, Gene F.

1987-01-01

The design of feasible controllers for high dimension multivariable systems can be greatly aided by a method of model reduction. In order for the design based on the order reduction to include a guarantee of stability, it is sufficient to have a bound on the model error. Previous work has provided such a bound for continuous-time systems for algorithms based on balancing. In this note an L-infinity bound is derived for model error for a method of order reduction of discrete linear multivariable systems based on balancing.

Feature combinations and the divergence criterion

NASA Technical Reports Server (NTRS)

Decell, H. P., Jr.; Mayekar, S. M.

1976-01-01

Classifying large quantities of multidimensional remotely sensed agricultural data requires efficient and effective classification techniques and the construction of certain transformations of a dimension reducing, information preserving nature. The construction of transformations that minimally degrade information (i.e., class separability) is described. Linear dimension reducing transformations for multivariate normal populations are presented. Information content is measured by divergence.

Distraction of facets with intraarticular spacers as treatment for lumbar canal stenosis: report on a preliminary experience with 21 cases.

PubMed

Goel, Atul; Shah, Abhidha; Jadhav, Madan; Nama, Santhosh

2013-12-01

The authors report their experience in treating 21 patients by using a novel form of treatment of lumbar degenerative disease that leads to canal stenosis. The surgery involved distraction of the facets using specially designed Goel intraarticular spacers and was aimed at arthrodesis of the spinal segment in a distracted position. The operation is based on the premise that subtle and longstanding facet instability, joint space reduction, and subsequent facet override had a profound and primary influence in the pathogenesis of degenerative lumbar canal stenosis. The surgical technique and the rationale for treatment are discussed. Between April 2006 and January 2011, 21 cases of lumbar degenerative disease resulting in characteristic lumbar canal stenosis were treated in the authors' department with the proposed technique. The patients were prospectively analyzed. There were 15 men and 6 women who ranged in age from 48 to 71 years (mean 58 years). Nine patients underwent 1-level and 12 patients underwent 2-level treatment. Surgery involved wide opening of the articular joint, denuding of the articular capsule/endplate cartilage, distraction of the facets, and forced impaction of Goel intraarticular spacers. Bone graft pieces obtained by sectioning the spinous processes were placed within and over the joint and in the midline over the adequately prepared host area of laminae. The Oswestry Disability Index and visual analog scale were used to clinically assess the patients before and after surgery and at follow-up. The alterations in the physical architecture of spinal canal and intervertebral foramen dimensions were evaluated before and after placement of the intrafacet implant and after at least 6 months of follow-up. All patients had varying degrees of relief from symptoms of local back pain and radiculopathy. Impaction of spacers within the facet joints resulted in an increase in the spinal canal and intervertebral root canal dimensions (mean 2.33 mm), reduction of buckling of the ligamentum flavum, and reduction of the extent of bulge of the disc into the spinal canal. The procedure resulted in firm stabilization and fixation of the spinal segment and provided a ground for arthrodesis. No patient worsened neurologically after treatment. During the follow-up period, all patients had evidence of segmental bone fusion. No patient underwent reexploration or further surgery of the lumbar spine. Impaction of the spacers within the articular cavity after facet distraction resulted in reversal of several effects of spine degeneration that had caused spinal and root canal stenosis. The safe, firm, and secure stabilization at the fulcrum of lumbar spinal movements provided a ground for segmental spinal arthrodesis. The immediate postoperative and lasting recovery from symptoms suggests the validity of the procedure.

The Sine Method: An Alternative Height Measurement Technique

Treesearch

Don C. Bragg; Lee E. Frelich; Robert T. Leverett; Will Blozan; Dale J. Luthringer

2011-01-01

Height is one of the most important dimensions of trees, but few observers are fully aware of the consequences of the misapplication of conventional height measurement techniques. A new approach, the sine method, can improve height measurement by being less sensitive to the requirements of conventional techniques (similar triangles and the tangent method). We studied...

New Teaching Techniques to Improve Critical Thinking. The Diaprove Methodology

ERIC Educational Resources Information Center

Saiz, Carlos; Rivas, Silvia F.

2016-01-01

The objective of this research is to ascertain whether new instructional techniques can improve critical thinking. To achieve this goal, two different instruction techniques (ARDESOS--group 1--and DIAPROVE--group 2--) were studied and a pre-post assessment of critical thinking in various dimensions such as argumentation, inductive reasoning,…

Optical nondestructive dynamic measurements of wafer-scale encapsulated nanofluidic channels.

PubMed

Liberman, Vladimir; Smith, Melissa; Weaver, Isaac; Rothschild, Mordechai

2018-05-20

Nanofluidic channels are of great interest for DNA sequencing, chromatography, and drug delivery. However, metrology of embedded or sealed nanochannels and measurement of their fill-state have remained extremely challenging. Existing techniques have been restricted to optical microscopy, which suffers from insufficient resolution, or scanning electron microscopy, which cannot measure sealed or embedded channels without cleaving the sample. Here, we demonstrate a novel method for accurately extracting nanochannel cross-sectional dimensions and monitoring fluid filling, utilizing spectroscopic ellipsometric scatterometry, combined with rigorous electromagnetic simulations. Our technique is capable of measuring channel dimensions with better than 5-nm accuracy and assessing channel filling within seconds. The developed technique is, thus, well suited for both process monitoring of channel fabrication as well as for studying complex phenomena of fluid flow through nanochannel structures.

[Control of vertical dimension in the Root technique. Part 2. Class II].

PubMed

Labarrère, H

2005-03-01

Hyperdivergent, or high angle, Class II skeletal malocclusions require a reduction in that angle so that an optimal counter-reduction of the mandible can be obtained. Four of these types of cases are analyzed here to show: in the first, treated without extractions, the limitations of this approach: the poor esthetic result derives from the incomplete retraction of incisors because of the occlusal deficits further correction would have incurred; in the second, treated with extractions of upper and lower first bicuspids, that a reduction of the angles SNM from 45 degrees to 40 degrees, FMA from 27 degrees to 24 degrees and ANB from 90 to 40 was obtained; in the third case, treated with extractions of the upper first bicuspids and the lower second bicuspids, that a counter-rotation of the mandible was required in order not to aggravate the esthetic problem while the dental deformity was being corrected. Angle SNM was reduced from 30 degrees to 25 degrees, FMA from 26 degrees to 20 degrees, and ANB from 7 degrees to 2 degrees; and, in the fourth case, where an atypical extraction scheme was elected, that an effective orthodonticsurgical alternative is available. Thanks to an anchorage conception specifically designed for this case by T. Root allowing for extraction of upper first molars, angle SNM was reduced from 38 degrees to 35 degrees, FMA was changed from 28 degrees to 23 degrees, and ANB dropped from 10 degrees to 3.5 degrees.

Performance Analysis of Hospital Managers Using Fuzzy AHP and Fuzzy TOPSIS: Iranian Experience

PubMed Central

Shafii, Milad; Hosseini, Seyed Mostafa; Arab, Mohammad; Asgharizadeh, Ezzatollah; Farzianpour, Fereshteh

2016-01-01

Background and Objectives: Hospitals are complex organizations that require strong and effective management. The success of such organizations depends on the performance of managers. This study provides a comprehensive set of indicators to assess the performance of hospital managers in Iranian Ministry of Health owned hospitals. Methods: This research was a cross-sectional study. First, reviewing the literature and using experts’ viewpoints and convening a panel of experts, the dimensions of performance have been selected and came in the form of a performance model. Then, using Fuzzy Analytic Hierarchy Process (FAHP), the chosen dimensions were weighted. Finally, based on the weighted performance dimensions, a questionnaire was designed and after confirming the reliability and validity, through a census, 407 senior and middle managers from 10 hospitals in Yazd, Iran completed it and performance of CEOs in these hospitals was evaluated using the Fuzzy Technique for Order Preference by Similarity Ideal Solution (FTOPSIS). Results: To measure the performance of hospital managers, a performance assessment model consisted of 19 sub-dimensions in 5 main dimensions (Functional, Professional, Organizational, Individual and Human) was developed. The functional area had the most weight and the individual area had the least weight, as well. The hospital managers had different performance levels in each category and sub-dimensions. In terms of overall performance, the hospital managers C and H had the best and the worst performance, respectively. Conclusions: The use of appropriate dimensions for performance, prioritizing them and evaluating the performance of hospital managers using appropriate techniques, can play an effective role in the selection of qualified managers, identifying strengths and weaknesses in performance and continuous improvement of them. PMID:26383216

Unsupervised Feature Selection Based on the Morisita Index for Hyperspectral Images

NASA Astrophysics Data System (ADS)

Golay, Jean; Kanevski, Mikhail

2017-04-01

Hyperspectral sensors are capable of acquiring images with hundreds of narrow and contiguous spectral bands. Compared with traditional multispectral imagery, the use of hyperspectral images allows better performance in discriminating between land-cover classes, but it also results in large redundancy and high computational data processing. To alleviate such issues, unsupervised feature selection techniques for redundancy minimization can be implemented. Their goal is to select the smallest subset of features (or bands) in such a way that all the information content of a data set is preserved as much as possible. The present research deals with the application to hyperspectral images of a recently introduced technique of unsupervised feature selection: the Morisita-Based filter for Redundancy Minimization (MBRM). MBRM is based on the (multipoint) Morisita index of clustering and on the Morisita estimator of Intrinsic Dimension (ID). The fundamental idea of the technique is to retain only the bands which contribute to increasing the ID of an image. In this way, redundant bands are disregarded, since they have no impact on the ID. Besides, MBRM has several advantages over benchmark techniques: in addition to its ability to deal with large data sets, it can capture highly-nonlinear dependences and its implementation is straightforward in any programming environment. Experimental results on freely available hyperspectral images show the good effectiveness of MBRM in remote sensing data processing. Comparisons with benchmark techniques are carried out and random forests are used to assess the performance of MBRM in reducing the data dimensionality without loss of relevant information. References [1] C. Traina Jr., A.J.M. Traina, L. Wu, C. Faloutsos, Fast feature selection using fractal dimension, in: Proceedings of the XV Brazilian Symposium on Databases, SBBD, pp. 158-171, 2000. [2] J. Golay, M. Kanevski, A new estimator of intrinsic dimension based on the multipoint Morisita index, Pattern Recognition 48(12), pp. 4070-4081, 2015. [3] J. Golay, M. Kanevski, Unsupervised feature selection based on the Morisita estimator of intrinsic dimension, arXiv:1608.05581, 2016.

Growing Cobalt Silicide Columns In Silicon

NASA Technical Reports Server (NTRS)

Fathauer, Obert W.

1991-01-01

Codeposition by molecular-beam epitaxy yields variety of structures. Proposed fabrication process produces three-dimensional nanometer-sized structures on silicon wafers. Enables control of dimensions of metal and semiconductor epitaxial layers in three dimensions instead of usual single dimension (perpendicular to the plane of the substrate). Process used to make arrays of highly efficient infrared sensors, high-speed transistors, and quantum wires. For fabrication of electronic devices, both shapes and locations of columns controlled. One possible technique for doing this electron-beam lithography, see "Making Submicron CoSi2 Structures on Silicon Substrates" (NPO-17736).

Recreational music-making: an integrative group intervention for reducing burnout and improving mood states in first year associate degree nursing students: insights and economic impact.

PubMed

Bittman, Barry B; Snyder, Cherie; Bruhn, Karl T; Liebfreid, Fran; Stevens, Christine K; Westengard, James; Umbach, Paul O

2004-01-01

The challenges of providing exemplary undergraduate nursing education cannot be underestimated in an era when burnout and negative mood states predictably lead to alarming rates of academic as well as career attrition. While the multi-dimensional nature of this complex issue has been extensively elucidated, few rational strategies exist to reverse a disheartening trend recognizable early in the educational process that subsequently threatens to undermine the future viability of quality healthcare. This controlled prospective crossover study examined the impact of a 6-session Recreational Music-making (RMM) protocol on burnout and mood dimensions as well as Total Mood Disturbance (TMD) in first year associate level nursing students. A total of 75 first year associate degree nursing students from Allegany College of Maryland (ACM) participated in a 6-session RMM protocol focusing on group support and stress reduction utilizing a specific group drumming protocol. Burnout and mood dimensions were assessed with the Maslach Burnout Inventory and the Profile of Mood States respectively. Statistically significant reductions of multiple burnout and mood dimensions as well as TMD scores were noted. Potential annual cost savings for the typical associate degree nursing program (16,800 dollars) and acute care hospital (322,000 dollars) were projected by an independent economic analysis firm. A cost-effective 6-session RMM protocol reduces burnout and mood dimensions as well as TMD in associate degree nursing students.

Collisions of ideal gas molecules with a rough/fractal surface. A computational study.

PubMed

Panczyk, Tomasz

2007-02-01

The frequency of collisions of ideal gas molecules (argon) with a rough surface has been studied. The rough/fractal surface was created using random deposition technique. By applying various depositions, the roughness of the surface was controlled and, as a measure of the irregularity, the fractal dimensions of the surfaces were determined. The surfaces were next immersed in argon (under pressures 2 x 10(3) to 2 x 10(5) Pa) and the numbers of collisions with these surfaces were counted. The calculations were carried out using a simplified molecular dynamics simulation technique (only hard core repulsions were assumed). As a result, it was stated that the frequency of collisions is a linear function of pressure for all fractal dimensions studied (D = 2, ..., 2.5). The frequency per unit pressure is quite complex function of the fractal dimension; however, the changes of that frequency with the fractal dimension are not strong. It was found that the frequency of collisions is controlled by the number of weakly folded sites on the surfaces and there is some mapping between the shape of adsorption energy distribution functions and this number of weakly folded sites. The results for the rough/fractal surfaces were compared with the prediction given by the Langmuir-Hertz equation (valid for smooth surface), generally the departure from the Langmuir-Hertz equation is not higher than 48% for the studied systems (i.e. for the surfaces created using the random deposition technique).

Characterization of hydrogel printer for direct cell-laden scaffolds

NASA Astrophysics Data System (ADS)

Whulanza, Yudan; Arsyan, Rendria; Saragih, Agung Shamsuddin

2018-02-01

The additive manufacturing technology has been massively developed since the last decade. The technology was previously known as rapid prototyping techniques that aimed to produce a prototyping product in fast and economical way. Currently, this technique is also applied to fabricate microstructure utilized in tissue engineering technology. Here, we introduce a 3D printer which using hydrogel gelatin to realize cell laden scaffold with dimension around 50-100 µm. However, in order to fabricate such a precise dimension, an optimum working parameters are required to control the physical properties of gelatin. At the end of our study, we formulated the best parameters to perform the product as we desired.

Efficient Parameter Searches for Colloidal Materials Design with Digital Alchemy

NASA Astrophysics Data System (ADS)

Dodd, Paul, M.; Geng, Yina; van Anders, Greg; Glotzer, Sharon C.

Optimal colloidal materials design is challenging, even for high-throughput or genomic approaches, because the design space provided by modern colloid synthesis techniques can easily have dozens of dimensions. In this talk we present the methodology of an inverse approach we term ''digital alchemy'' to perform rapid searches of design-paramenter spaces with up to 188 dimensions that yield thermodynamically optimal colloid parameters for target crystal structures with up to 20 particles in a unit cell. The method relies only on fundamental principles of statistical mechanics and Metropolis Monte Carlo techniques, and yields particle attribute tolerances via analogues of familiar stress-strain relationships.

3D-liquid chromatography as a complex mixture characterization tool for knowledge-based downstream process development.

PubMed

Hanke, Alexander T; Tsintavi, Eleni; Ramirez Vazquez, Maria Del Pilar; van der Wielen, Luuk A M; Verhaert, Peter D E M; Eppink, Michel H M; van de Sandt, Emile J A X; Ottens, Marcel

2016-09-01

Knowledge-based development of chromatographic separation processes requires efficient techniques to determine the physicochemical properties of the product and the impurities to be removed. These characterization techniques are usually divided into approaches that determine molecular properties, such as charge, hydrophobicity and size, or molecular interactions with auxiliary materials, commonly in the form of adsorption isotherms. In this study we demonstrate the application of a three-dimensional liquid chromatography approach to a clarified cell homogenate containing a therapeutic enzyme. Each separation dimension determines a molecular property relevant to the chromatographic behavior of each component. Matching of the peaks across the different separation dimensions and against a high-resolution reference chromatogram allows to assign the determined parameters to pseudo-components, allowing to determine the most promising technique for the removal of each impurity. More detailed process design using mechanistic models requires isotherm parameters. For this purpose, the second dimension consists of multiple linear gradient separations on columns in a high-throughput screening compatible format, that allow regression of isotherm parameters with an average standard error of 8%. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1283-1291, 2016. © 2016 American Institute of Chemical Engineers.

Low-derivative operators of the Standard Model effective field theory via Hilbert series methods

NASA Astrophysics Data System (ADS)

Lehman, Landon; Martin, Adam

2016-02-01

In this work, we explore an extension of Hilbert series techniques to count operators that include derivatives. For sufficiently low-derivative operators, we conjecture an algorithm that gives the number of invariant operators, properly accounting for redundancies due to the equations of motion and integration by parts. Specifically, the conjectured technique can be applied whenever there is only one Lorentz invariant for a given partitioning of derivatives among the fields. At higher numbers of derivatives, equation of motion redundancies can be removed, but the increased number of Lorentz contractions spoils the subtraction of integration by parts redundancies. While restricted, this technique is sufficient to automatically recreate the complete set of invariant operators of the Standard Model effective field theory for dimensions 6 and 7 (for arbitrary numbers of flavors). At dimension 8, the algorithm does not automatically generate the complete operator set; however, it suffices for all but five classes of operators. For these remaining classes, there is a well defined procedure to manually determine the number of invariants. Assuming our method is correct, we derive a set of 535 dimension-8 N f = 1 operators.

Diffusion maps for high-dimensional single-cell analysis of differentiation data.

PubMed

Haghverdi, Laleh; Buettner, Florian; Theis, Fabian J

2015-09-15

Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages. Here, we propose the use of diffusion maps to deal with the problem of defining differentiation trajectories. We adapt this method to single-cell data by adequate choice of kernel width and inclusion of uncertainties or missing measurement values, which enables the establishment of a pseudotemporal ordering of single cells in a high-dimensional gene expression space. We expect this output to reflect cell differentiation trajectories, where the data originates from intrinsic diffusion-like dynamics. Starting from a pluripotent stage, cells move smoothly within the transcriptional landscape towards more differentiated states with some stochasticity along their path. We demonstrate the robustness of our method with respect to extrinsic noise (e.g. measurement noise) and sampling density heterogeneities on simulated toy data as well as two single-cell quantitative polymerase chain reaction datasets (i.e. mouse haematopoietic stem cells and mouse embryonic stem cells) and an RNA-Seq data of human pre-implantation embryos. We show that diffusion maps perform considerably better than Principal Component Analysis and are advantageous over other techniques for non-linear dimension reduction such as t-distributed Stochastic Neighbour Embedding for preserving the global structures and pseudotemporal ordering of cells. The Matlab implementation of diffusion maps for single-cell data is available at https://www.helmholtz-muenchen.de/icb/single-cell-diffusion-map. fbuettner.phys@gmail.com, fabian.theis@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Phaedra, a protocol-driven system for analysis and validation of high-content imaging and flow cytometry.

PubMed

Cornelissen, Frans; Cik, Miroslav; Gustin, Emmanuel

2012-04-01

High-content screening has brought new dimensions to cellular assays by generating rich data sets that characterize cell populations in great detail and detect subtle phenotypes. To derive relevant, reliable conclusions from these complex data, it is crucial to have informatics tools supporting quality control, data reduction, and data mining. These tools must reconcile the complexity of advanced analysis methods with the user-friendliness demanded by the user community. After review of existing applications, we realized the possibility of adding innovative new analysis options. Phaedra was developed to support workflows for drug screening and target discovery, interact with several laboratory information management systems, and process data generated by a range of techniques including high-content imaging, multicolor flow cytometry, and traditional high-throughput screening assays. The application is modular and flexible, with an interface that can be tuned to specific user roles. It offers user-friendly data visualization and reduction tools for HCS but also integrates Matlab for custom image analysis and the Konstanz Information Miner (KNIME) framework for data mining. Phaedra features efficient JPEG2000 compression and full drill-down functionality from dose-response curves down to individual cells, with exclusion and annotation options, cell classification, statistical quality controls, and reporting.

Radiation dose reduction in digital breast tomosynthesis (DBT) by means of deep-learning-based supervised image processing

NASA Astrophysics Data System (ADS)

Liu, Junchi; Zarshenas, Amin; Qadir, Ammar; Wei, Zheng; Yang, Limin; Fajardo, Laurie; Suzuki, Kenji

2018-03-01

To reduce cumulative radiation exposure and lifetime risks for radiation-induced cancer from breast cancer screening, we developed a deep-learning-based supervised image-processing technique called neural network convolution (NNC) for radiation dose reduction in DBT. NNC employed patched-based neural network regression in a convolutional manner to convert lower-dose (LD) to higher-dose (HD) tomosynthesis images. We trained our NNC with quarter-dose (25% of the standard dose: 12 mAs at 32 kVp) raw projection images and corresponding "teaching" higher-dose (HD) images (200% of the standard dose: 99 mAs at 32 kVp) of a breast cadaver phantom acquired with a DBT system (Selenia Dimensions, Hologic, CA). Once trained, NNC no longer requires HD images. It converts new LD images to images that look like HD images; thus the term "virtual" HD (VHD) images. We reconstructed tomosynthesis slices on a research DBT system. To determine a dose reduction rate, we acquired 4 studies of another test phantom at 4 different radiation doses (1.35, 2.7, 4.04, and 5.39 mGy entrance dose). Structural SIMilarity (SSIM) index was used to evaluate the image quality. For testing, we collected half-dose (50% of the standard dose: 32+/-14 mAs at 33+/-5 kVp) and full-dose (standard dose: 68+/-23 mAs at 33+/-5 kvp) images of 10 clinical cases with the DBT system at University of Iowa Hospitals and Clinics. NNC converted half-dose DBT images of 10 clinical cases to VHD DBT images that were equivalent to full dose DBT images. Our cadaver phantom experiment demonstrated 79% dose reduction.

Chromium (VI) reduction in acetate- and molasses-amended natural media: empirical model development

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

Hansen, Scott; Boukhalfa, Hakim; Karra, Satish

Stimulating indigenous microbes to reduce heavy metals from highly toxic oxidized species to more benign reduced species is a promising groundwater remediation technique that has already seen successful field applications. Designing such a bio-remediation scheme requires a model incorporating the kinetics of nonlinear bio-geochemical interactions between multiple species. With this motivation, we performed a set of microcosm experiments in natural sediments and their indigenous pore water and microbes, generating simultaneous time series for concentrations of Cr(VI), an electron donor (both molasses and acetate were considered), and biomass. Molasses was found to undergo a rapid direct abiotic reaction which eliminated allmore » Cr(VI) before any biomass had time to grow. This was not found in the acetate microcosms, and a distinct zero-order bio-reduction process was observed. Existing models were found inappropriate and a new set of three coupled governing equations representing these process dynamics were developed and their parameters calibrated against the time series from the acetate-amended microcosms. Cell suspension batch experiments were also performed to calibrate bio-reduction rates in the absence of electron donor and sediment. The donor used to initially grow the cells (molasses or acetate) was found not to impact the reduction rate constants in suspension, which were orders of magnitude larger than those explaining the natural media microcosm experiments. This suggests the limited utility of kinetics determined in suspension for remedial design. Scoping studies on the natural media microcosms were also performed, suggesting limited impact of foreign abiotic material and minimal effect of diffusion limitation in the vertical dimension. These analyses may be of independent value to future researchers.« less

Comparative study to evaluate the accuracy of polyether occlusal bite registration material and occlusal registration wax as a guide for occlusal reduction during tooth preparation.

PubMed

Joshi, Niranjan; Shetty, Sridhar N; Prasad, Krishna D

2013-01-01

The use of different materials and techniques has been studied to decide the safest quantum of reduction of the occlusal surfaces. However, these methods provide limited information as to the actual amount of reduction with limitations in accuracy, accessibility and complexity. The objective of this study was to compare and evaluate the reliability of the most commonly used occlusal registration wax that with polyether bite registration material as a guide for occlusal reduction required during tooth preparations. For the purpose of this study, 25 abutment teeth requiring tooth preparation for fixed prosthesis were selected and tooth preparations carried out. Modeling wax strips of specific dimensions were placed onto the cast of prepared tooth, which was mounted on maximum intercuspation on the articulator and the articulator was closed. The thickness of the wax registration was measured at three zones namely two functional cusps and central fossa. Similar measurements were made using the polyether bite registration material and prosthesis at the same zones. The data was tabulated and was subjected to statistical analysis using anova test and Tukey honestly significant difference test. The differences in thickness between wax record and prosthesis by 0.1346 mm, whereas the difference between polyether and prosthesis was 0.02 mm with a P value of 0.042, which is statistically significant. This means that the wax record was 8.25% larger than the prosthesis while polyether was just 1.27% larger than the prosthesis. The clinical significance of the above analysis is that Ramitec polyether bite registration material is most suitable material when compared with commonly used modeling wax during the tooth preparation.

Social Dimension of WEB 2.0 in Teacher Education: Focus on Peer-Learning

ERIC Educational Resources Information Center

Zascerinska, Jelena; Ahrens, Andreas

2010-01-01

The research deals with the analysis of efficiency of teaching techniques with the use of the social dimension of Web 2.0 within the English for Specific Purposes course in pre-school and primary teacher education that would help students to become more cognizant and more responsive to the emerging needs of the market for educational services and…

Quality of physical therapy from a patient's perspective; factor analysis on web-based survey data revealed three dimensions on patient experiences with physical therapy.

PubMed

Scholte, Marijn; Calsbeek, Hilly; Nijhuis-van der Sanden, Maria W G; Braspenning, Jozé

2014-06-18

Assessing quality of care from the patient's perspective has changed from patient satisfaction to the more general term patient experience, as satisfaction measures turned out to be less discriminative due to high scores. Literature describes four to ten dimensions of patient experience, tailored to specific conditions or types of care. Given the administrative burden on patients, less dimensions and items could increase feasibility. Ten dimensions of patient experiences with physical therapy (PT) were proposed in the Netherlands in a consensus-based process with patients, physical therapists, health insurers, and policy makers. The aim of this paper is to detect the number of dimensions from data of a field study using factor analysis at item level. A web-based survey yielded data of 2,221 patients from 52 PT practices on 41 items. Principal component factor analysis at item level was used to assess the proposed distinction between the ten dimensions. Factor analysis revealed two dimensions: 'personal interaction' and 'practice organisation'. The dimension 'patient reported outcome' was artificially established. The three dimensions 'personal interaction' (14 items) (median(practice level) = 91.1; IQR = 2.4), 'practice organisation' (9 items) (median(practice level) = 88.9; IQR = 6.0) and 'outcome' (3 items) (median(practice level) = 80.6; IQR = 19.5) reduced the number of dimensions from ten to three and the number of items by more than a third. Factor analysis revealed three dimensions and achieved an item reduction of more than a third. It is a relevant step in the development process of a quality measurement tool to reduce respondent burden, increase clarity, and promote feasibility.

The First Trial of the P Technique in Psychotherapy Research: A Still-Lively Legacy.

ERIC Educational Resources Information Center

Luborsky, Lester

1995-01-01

Reexamines a 49-year-old study of P technique applied to a psychotherapy patient with a recurrent physical symptom. Explores dimensions of psychotherapeutic change as well as the context for the recurrent symptom. Illustrates the contributions from applying the P technique to psychotherapy research, to psychosomatic medicine, and to personality…

Fast 2D NMR Spectroscopy for In vivo Monitoring of Bacterial Metabolism in Complex Mixtures.

PubMed

Dass, Rupashree; Grudzia Ż, Katarzyna; Ishikawa, Takao; Nowakowski, Michał; Dȩbowska, Renata; Kazimierczuk, Krzysztof

2017-01-01

The biological toolbox is full of techniques developed originally for analytical chemistry. Among them, spectroscopic experiments are very important source of atomic-level structural information. Nuclear magnetic resonance (NMR) spectroscopy, although very advanced in chemical and biophysical applications, has been used in microbiology only in a limited manner. So far, mostly one-dimensional 1 H experiments have been reported in studies of bacterial metabolism monitored in situ . However, low spectral resolution and limited information on molecular topology limits the usability of these methods. These problems are particularly evident in the case of complex mixtures, where spectral peaks originating from many compounds overlap and make the interpretation of changes in a spectrum difficult or even impossible. Often a suite of two-dimensional (2D) NMR experiments is used to improve resolution and extract structural information from internuclear correlations. However, for dynamically changing sample, like bacterial culture, the time-consuming sampling of so-called indirect time dimensions in 2D experiments is inefficient. Here, we propose the technique known from analytical chemistry and structural biology of proteins, i.e., time-resolved non-uniform sampling. The method allows application of 2D (and multi-D) experiments in the case of quickly varying samples. The indirect dimension here is sparsely sampled resulting in significant reduction of experimental time. Compared to conventional approach based on a series of 1D measurements, this method provides extraordinary resolution and is a real-time approach to process monitoring. In this study, we demonstrate the usability of the method on a sample of Escherichia coli culture affected by ampicillin and on a sample of Propionibacterium acnes , an acne causing bacterium, mixed with a dose of face tonic, which is a complicated, multi-component mixture providing complex NMR spectrum. Through our experiments we determine the exact concentration and time at which the anti-bacterial agents affect the bacterial metabolism. We show, that it is worth to extend the NMR toolbox for microbiology by including techniques of 2D z-TOCSY, for total "fingerprinting" of a sample and 2D 13 C-edited HSQC to monitor changes in concentration of metabolites in selected metabolic pathways.

Exploring multicollinearity using a random matrix theory approach.

PubMed

Feher, Kristen; Whelan, James; Müller, Samuel

2012-01-01

Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with `low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.

An improved technique for the 2H/1H analysis of urines from diabetic volunteers

USGS Publications Warehouse

Coplen, T.B.; Harper, I.T.

1994-01-01

The H2-H2O ambient-temperature equilibration technique for the determination of 2H/1H ratios in urinary waters from diabetic subjects provides improved accuracy over the conventional Zn reduction technique. The standard deviation, ~ 1-2???, is at least a factor of three better than that of the Zn reduction technique on urinary waters from diabetic volunteers. Experiments with pure water and solutions containing glucose, urea and albumen indicate that there is no measurable bias in the hydrogen equilibration technique.The H2-H2O ambient-temperature equilibration technique for the determination of 2H/1H ratios in urinary waters from diabetic subjects provides improved accuracy over the conventional Zn reduction technique. The standard deviation, approximately 1-2%, is at least a factor of three better than that of the Zn reduction technique on urinary waters from diabetic volunteers. Experiments with pure water and solutions containing glucose, urea and albumen indicate that there is no measurable bias in the hydrogen equilibration technique.

Inverse-dispersion technique for assessing lagoon gas emissions

USDA-ARS?s Scientific Manuscript database

Measuring gas emissions from treatment lagoons and storage ponds poses challenging conditions for existing micrometeorological techniques because of non-ideal wind conditions, such as those induced by trees and crops surrounding the lagoons, and lagoons with dimensions too small to establish equilib...

DIMENSIONS OF SIMULATION.

ERIC Educational Resources Information Center

CRAWFORD, MEREDITH P.

OPEN AND CLOSED LOOP SIMULATION IS DISCUSSED FROM THE VIEWPOINT OF RESEARCH AND DEVELOPMENT IN TRAINING TECHNIQUES. AREAS DISCUSSED INCLUDE--(1) OPEN-LOOP ENVIRONMENTAL SIMULATION, (2) SIMULATION NOT INVOLVING PEOPLE, (3) ANALYSIS OF OCCUPATIONS, (4) SIMULATION FOR TRAINING, (5) REAL-SIZE SYSTEM SIMULATION, (6) TECHNIQUES OF MINIATURIZATION, AND…

AKSZ construction from reduction data

NASA Astrophysics Data System (ADS)

Bonechi, Francesco; Cabrera, Alejandro; Zabzine, Maxim

2012-07-01

We discuss a general procedure to encode the reduction of the target space geometry into AKSZ sigma models. This is done by considering the AKSZ construction with target the BFV model for constrained graded symplectic manifolds. We investigate the relation between this sigma model and the one with the reduced structure. We also discuss several examples in dimension two and three when the symmetries come from Lie group actions and systematically recover models already proposed in the literature.

Evaluation of a reduced section modulus model for determining effects of incising on bending strength and stiffness of structural lumber

Treesearch

Roland Hernandez; Jerrold E. Winandy

2005-01-01

A quantitative model is presented for evaluating the effects of incising on the bending strength and stiffness of structural dimension lumber. This model is based on the premise that bending strength and stiffness are reduced when lumber is incised, and the extent of this reduction is related to the reduction in moment of inertia of the bending members. Measurements of...

A massive Feynman integral and some reduction relations for Appell functions

NASA Astrophysics Data System (ADS)

Shpot, M. A.

2007-12-01

New explicit expressions are derived for the one-loop two-point Feynman integral with arbitrary external momentum and masses m12 and m22 in D dimensions. The results are given in terms of Appell functions, manifestly symmetric with respect to the masses mi2. Equating our expressions with previously known results in terms of Gauss hypergeometric functions yields reduction relations for the involved Appell functions that are apparently new mathematical results.

The difference of drainage channel dimensions at Kopelma Darussalam on the land with and without the use of Bio Pores

NASA Astrophysics Data System (ADS)

Yulianur, Alfiansyah; Fauzi, Amir; Humaira, Zaitun

2018-05-01

The changes of land use and diminishing of open field that persistently occur are projected to cause rates acceleration of runoff, which decreases the opportunity for rainwater to infiltrate. It has an impact on the surface runoff into the channels, which eventually may lead to overflow and inundate the surrounding area. Some efforts are required to increase the infiltration of rainfall. Thus, bio pore could be one of the most effective methods to be implemented. The objective of this study is to evaluate the effect of bio pore towards the reduction of runoff discharge into the drainage channel and to determine whether that reduction could lead to effectively lessen the channels’ dimension. This study is commenced at Kopelma Darussalam in the southern part where there were several spots that submerged by inundation flood during the rainy season, namely Sektor Timur area. Rational modification formula is used to calculate the surface runoff discharge on the land without the use of bio pore. Meanwhile, runoff discharge on the land with the use of bio pores is calculated by the use of water balance formula. The number of bio pores that have planned in Sektor Timur area is 3350 bio pores with the diameter of each is ∅10 cm and 80 cm in depth. The result indicates that those bio pores can reduce the runoff discharge on average of 27% and its’ reduction lead to the decrease of drainage channel dimension for the average of 26.9%.

Exploring dimensions of access to medical care.

PubMed Central

Andersen, R M; McCutcheon, A; Aday, L A; Chiu, G Y; Bell, R

1983-01-01

This paper examines the dimensions of the access concept with particular attention to the extent to which more parsimonious indicators of access can be developed. This process is especially useful to health policy makers, planners and researchers in need of cost-effective social indicators of access to monitor the need for and impact of innovative health care programs. Three stages of data reduction are used in the analysis, resulting in a reduced set of key indicators of the concept. Implication for subsequent data collection and measurement of access are discussed. PMID:6841113

Gravity and the Spin-2 Planar Schrödinger Equation

NASA Astrophysics Data System (ADS)

Bergshoeff, Eric A.; Rosseel, Jan; Townsend, Paul K.

2018-04-01

A Schrödinger equation proposed for the Girvin-MacDonald-Platzman gapped spin-2 mode of fractional quantum Hall states is found from a novel nonrelativistic limit, applicable only in 2 +1 dimensions, of the massive spin-2 Fierz-Pauli field equations. It is also found from a novel null reduction of the linearized Einstein field equations in 3 +1 dimensions, and in this context a uniform distribution of spin-2 particles implies, via a Brinkmann-wave solution of the nonlinear Einstein equations, a confining harmonic oscillator potential for the individual particles.

Robust Derivation of Risk Reduction Strategies

NASA Technical Reports Server (NTRS)

Richardson, Julian; Port, Daniel; Feather, Martin

2007-01-01

Effective risk reduction strategies can be derived mechanically given sufficient characterization of the risks present in the system and the effectiveness of available risk reduction techniques. In this paper, we address an important question: can we reliably expect mechanically derived risk reduction strategies to be better than fixed or hand-selected risk reduction strategies, given that the quantitative assessment of risks and risk reduction techniques upon which mechanical derivation is based is difficult and likely to be inaccurate? We consider this question relative to two methods for deriving effective risk reduction strategies: the strategic method defined by Kazman, Port et al [Port et al, 2005], and the Defect Detection and Prevention (DDP) tool [Feather & Cornford, 2003]. We performed a number of sensitivity experiments to evaluate how inaccurate knowledge of risk and risk reduction techniques affect the performance of the strategies computed by the Strategic Method compared to a variety of alternative strategies. The experimental results indicate that strategies computed by the Strategic Method were significantly more effective than the alternative risk reduction strategies, even when knowledge of risk and risk reduction techniques was very inaccurate. The robustness of the Strategic Method suggests that its use should be considered in a wide range of projects.

Visualizing phylogenetic tree landscapes.

PubMed

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D projections significantly increase the fit between the tree-to-tree distances and can facilitate the interpretation of the relationship among phylogenetic trees. We demonstrate that the choice of dimensionality reduction method can significantly influence the spatial relationship among a large set of competing phylogenetic trees. We highlight the importance of selecting a dimensionality reduction method to visualize large multi-locus phylogenetic landscapes and demonstrate that 3D projections of mitochondrial tree landscapes better capture the relationship among the trees being compared.

Computational procedures for evaluating the sensitivity derivatives of vibration frequencies and Eigenmodes of framed structures

NASA Technical Reports Server (NTRS)

Fetterman, Timothy L.; Noor, Ahmed K.

1987-01-01

Computational procedures are presented for evaluating the sensitivity derivatives of the vibration frequencies and eigenmodes of framed structures. Both a displacement and a mixed formulation are used. The two key elements of the computational procedure are: (a) Use of dynamic reduction techniques to substantially reduce the number of degrees of freedom; and (b) Application of iterative techniques to improve the accuracy of the derivatives of the eigenmodes. The two reduction techniques considered are the static condensation and a generalized dynamic reduction technique. Error norms are introduced to assess the accuracy of the eigenvalue and eigenvector derivatives obtained by the reduction techniques. The effectiveness of the methods presented is demonstrated by three numerical examples.

Sub-50 nm metrology on extreme ultra violet chemically amplified resist—A systematic assessment

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

Maas, D. J., E-mail: diederik.maas@tno.nl; Herfst, R.; Veldhoven, E. van

2015-10-15

With lithographic patterning dimensions decreasing well below 50 nm, it is of high importance to understand metrology at such small scales. This paper presents results obtained from dense arrays of contact holes (CHs) with various Critical Dimension (CD) between 15 and 50 nm, as patterned in a chemically amplified resist using an ASML EUV scanner and measured at ASML and TNO. To determine the differences between various (local) CD metrology techniques, we conducted an experiment using optical scatterometry, CD-Scanning Electron Microscopy (CD-SEM), Helium ion Microscopy (HIM), and Atomic Force Microscopy (AFM). CD-SEM requires advanced beam scan strategies to mitigate samplemore » charging; the other tools did not need that. We discuss the observed main similarities and differences between the various techniques. To this end, we assessed the spatial frequency content in the raw images for SEM, HIM, and AFM. HIM and AFM resolve the highest spatial frequencies, which are attributed to the more localized probe-sample interaction for these techniques. Furthermore, the SEM, HIM, and AFM waveforms are analyzed in detail. All techniques show good mutual correlation, albeit the reported CD values systematically differ significantly. HIM systematically reports a 25% higher CD uniformity number than CD-SEM for the same arrays of CHs, probably because HIM has a higher resolution than the CD-SEM used in this assessment. A significant speed boost for HIM and AFM is required before these techniques are to serve the demanding industrial metrology applications like optical critical dimension and CD-SEM do nowadays.« less

Sub-50 nm metrology on extreme ultra violet chemically amplified resist—A systematic assessment

NASA Astrophysics Data System (ADS)

Maas, D. J.; Fliervoet, T.; Herfst, R.; van Veldhoven, E.; Meessen, J.; Vaenkatesan, V.; Sadeghian, H.

2015-10-01

With lithographic patterning dimensions decreasing well below 50 nm, it is of high importance to understand metrology at such small scales. This paper presents results obtained from dense arrays of contact holes (CHs) with various Critical Dimension (CD) between 15 and 50 nm, as patterned in a chemically amplified resist using an ASML EUV scanner and measured at ASML and TNO. To determine the differences between various (local) CD metrology techniques, we conducted an experiment using optical scatterometry, CD-Scanning Electron Microscopy (CD-SEM), Helium ion Microscopy (HIM), and Atomic Force Microscopy (AFM). CD-SEM requires advanced beam scan strategies to mitigate sample charging; the other tools did not need that. We discuss the observed main similarities and differences between the various techniques. To this end, we assessed the spatial frequency content in the raw images for SEM, HIM, and AFM. HIM and AFM resolve the highest spatial frequencies, which are attributed to the more localized probe-sample interaction for these techniques. Furthermore, the SEM, HIM, and AFM waveforms are analyzed in detail. All techniques show good mutual correlation, albeit the reported CD values systematically differ significantly. HIM systematically reports a 25% higher CD uniformity number than CD-SEM for the same arrays of CHs, probably because HIM has a higher resolution than the CD-SEM used in this assessment. A significant speed boost for HIM and AFM is required before these techniques are to serve the demanding industrial metrology applications like optical critical dimension and CD-SEM do nowadays.

A novel and efficient technique for identification and classification of GPCRs.

PubMed

Gupta, Ravi; Mittal, Ankush; Singh, Kuldip

2008-07-01

G-protein coupled receptors (GPCRs) play a vital role in different biological processes, such as regulation of growth, death, and metabolism of cells. GPCRs are the focus of significant amount of current pharmaceutical research since they interact with more than 50% of prescription drugs. The dipeptide-based support vector machine (SVM) approach is the most accurate technique to identify and classify the GPCRs. However, this approach has two major disadvantages. First, the dimension of dipeptide-based feature vector is equal to 400. The large dimension makes the classification task computationally and memory wise inefficient. Second, it does not consider the biological properties of protein sequence for identification and classification of GPCRs. In this paper, we present a novel-feature-based SVM classification technique. The novel features are derived by applying wavelet-based time series analysis approach on protein sequences. The proposed feature space summarizes the variance information of seven important biological properties of amino acids in a protein sequence. In addition, the dimension of the feature vector for proposed technique is equal to 35. Experiments were performed on GPCRs protein sequences available at GPCRs Database. Our approach achieves an accuracy of 99.9%, 98.06%, 97.78%, and 94.08% for GPCR superfamily, families, subfamilies, and subsubfamilies (amine group), respectively, when evaluated using fivefold cross-validation. Further, an accuracy of 99.8%, 97.26%, and 97.84% was obtained when evaluated on unseen or recall datasets of GPCR superfamily, families, and subfamilies, respectively. Comparison with dipeptide-based SVM technique shows the effectiveness of our approach.

Effects of turbinoplasty versus outfracture and bipolar cautery on the compensatory inferior turbinate hypertrophy in septoplasty patients.

PubMed

Bozan, Aykut; Eriş, Hüseyin Naim; Dizdar, Denizhan; Göde, Sercan; Taşdelen, Bahar; Alpay, Hayrettin Cengiz

2018-05-18

The most common cause of septoplasty failure is inferior turbinate hypertrophy that is not treated properly. Several techniques have been described to date: total or partial turbinectomy, submucosal resection (surgical or with a microdebrider), with turbinate outfracture being some of those. In this study, we compared the pre- and postoperative lower turbinate volumes using computed tomography in patients who had undergone septoplasty and compensatory lower turbinate turbinoplasty with those treated with outfracture and bipolar cauterization. This retrospective study enrolled 66 patients (37 men, 29 women) who were admitted to our otorhinolaryngology clinic between 2010 and 2017 because of nasal obstruction and who were operated on for nasal septum deviation. The patients who underwent turbinoplasty due to compensatory lower turbinate hypertrophy were the turbinoplasty group; Outfracture and bipolar cauterization were separated as the out fracture group. Compensatory lower turbinate volumes of all patients participating in the study (mean age 34.0±12.4 years, range 17-61 years) were assessed by preoperative and postoperative 2 month coronal and axial plane paranasal computed tomography. The transverse and longitudinal dimensions of the postoperative turbinoplasty group were significantly lower than those of the out-fracture group (p=0.004). In both groups the lower turbinate volumes were significantly decreased (p=0.002, p<0.001 in order). The postoperative volume of the turbinate on the deviated side of the patients was significantly increased: tubinoplasty group (p=0.033). Both turbinoplasty and outfracture are effective volume-reduction techniques. However, the turbinoplasty method results in more reduction of the lower turbinate volume than outfracture and bipolar cauterization. Copyright © 2018 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Material saving by means of CWR technology using optimization techniques

NASA Astrophysics Data System (ADS)

Pérez, Iñaki; Ambrosio, Cristina

2017-10-01

Material saving is currently a must for the forging companies, as material costs sum up to 50% for parts made of steel and up to 90% in other materials like titanium. For long products, cross wedge rolling (CWR) technology can be used to obtain forging preforms with a suitable distribution of the material along its own axis. However, defining the correct preform dimensions is not an easy task and it could need an intensive trial-and-error campaign. To speed up the preform definition, it is necessary to apply optimization techniques on Finite Element Models (FEM) able to reproduce the material behaviour when being rolled. Meta-models Assisted Evolution Strategies (MAES), that combine evolutionary algorithms with Kriging meta-models, are implemented in FORGE® software and they allow reducing optimization computation costs in a relevant way. The paper shows the application of these optimization techniques to the definition of the right preform for a shaft from a vehicle of the agricultural sector. First, the current forging process, based on obtaining the forging preform by means of an open die forging operation, is showed. Then, the CWR preform optimization is developed by using the above mentioned optimization techniques. The objective is to reduce, as much as possible, the initial billet weight, so that a calculation of flash weight reduction due to the use of the proposed preform is stated. Finally, a simulation of CWR process for the defined preform is carried out to check that most common failures (necking, spirals,..) in CWR do not appear in this case.

Imprint process performance for patterned media at densities greater than 1Tb/in2

NASA Astrophysics Data System (ADS)

Ye, Zhengmao; Carden, Scott; Hellebrekers, Paul; LaBrake, Dwayne; Resnick, Douglas J.; Melliar-Smith, M.; Sreenivasan, S. V.

2012-03-01

The use of bit pattern media beyond densities of 1Tb/in2 requires the ability to pattern dimensions to sub 10nm. This paper describes the techniques used to reach these dimensions with imprint lithography and avoid such challenges as pattern collapse, by developing improved resist materials with higher strength, and utilizing a reverse tone J-FIL/R process.

Singularities at the contact point of two kissing Neumann balls

NASA Astrophysics Data System (ADS)

Nazarov, Sergey A.; Taskinen, Jari

2018-02-01

We investigate eigenfunctions of the Neumann Laplacian in a bounded domain Ω ⊂Rd, where a cuspidal singularity is caused by a cavity consisting of two touching balls, or discs in the planar case. We prove that the eigenfunctions with all of their derivatives are bounded in Ω ‾, if the dimension d equals 2, but in dimension d ≥ 3 their gradients have a strong singularity O (| x - O|-α), α ∈ (0 , 2 -√{ 2 } ] at the point of tangency O. Our study is based on dimension reduction and other asymptotic procedures, as well as the Kondratiev theory applied to the limit differential equation in the punctured hyperplane R d - 1 ∖ O. We also discuss other shapes producing thinning gaps between touching cavities.

Functional traits, convergent evolution, and periodic tables of niches.

PubMed

Winemiller, Kirk O; Fitzgerald, Daniel B; Bower, Luke M; Pianka, Eric R

2015-08-01

Ecology is often said to lack general theories sufficiently predictive for applications. Here, we examine the concept of a periodic table of niches and feasibility of niche classification schemes from functional trait and performance data. Niche differences and their influence on ecological patterns and processes could be revealed effectively by first performing data reduction/ordination analyses separately on matrices of trait and performance data compiled according to logical associations with five basic niche 'dimensions', or aspects: habitat, life history, trophic, defence and metabolic. Resultant patterns then are integrated to produce interpretable niche gradients, ordinations and classifications. Degree of scheme periodicity would depend on degrees of niche conservatism and convergence causing species clustering across multiple niche dimensions. We analysed a sample data set containing trait and performance data to contrast two approaches for producing niche schemes: species ordination within niche gradient space, and niche categorisation according to trait-value thresholds. Creation of niche schemes useful for advancing ecological knowledge and its applications will depend on research that produces functional trait and performance datasets directly related to niche dimensions along with criteria for data standardisation and quality. As larger databases are compiled, opportunities will emerge to explore new methods for data reduction, ordination and classification. © 2015 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Positive and negative dimensions of weight control motivation.

PubMed

Stotland, S; Larocque, M; Sadikaj, G

2012-01-01

This study examined weight control motivation among patients (N=5460 females and 547 males) who sought weight loss treatment with family physicians. An eight-item measure assessed the frequency of thoughts and feelings related to weight control "outcome" (e.g. expected physical and psychological benefits) and "process" (e.g. resentment and doubt). Factor analysis supported the existence of two factors, labeled Positive and Negative motivation. Positive motivation was high (average frequency of thoughts about benefits was 'every day') and stable throughout treatment, while Negative motivation declined rapidly and then stabilized. The determinants of changes in the Positive and Negative dimensions during treatment were examined within 3 time frames: first month, months 2-6, and 6-12. Maintenance of high scores on Positive motivation was associated with higher BMI and more disturbed eating habits. Early reductions in Negative motivation were greater for those starting treatment with higher weight and more disturbed eating habits, but less depression and stress, while later reductions in Negative motivation were predicted by improvements in eating habits, weight, stress and perfectionism. Clinicians treating obesity should be sensitive to fluctuations in both motivational dimensions, as they are likely to play a central role in determining long-term behavior and weight change. Copyright © 2011 Elsevier Ltd. All rights reserved.

From two-dimension to one-dimension: the curvature effect of silicon-doped graphene and carbon nanotubes for oxygen reduction reaction.

PubMed

Zhang, Peng; Hou, Xiuli; Mi, Jianli; He, Yanqiong; Lin, Lin; Jiang, Qing; Dong, Mingdong

2014-09-07

For the goal of practical industrial development of fuel cells, inexpensive, sustainable, and highly efficient electrocatalysts for oxygen reduction reactions (ORR) are highly desirable alternatives to platinum (Pt) and other rare metals. In this work, based on density functional theory, silicon (Si)-doped carbon nanotubes (CNTs) and graphene as metal-free, low cost, and high-performance electrocatalysts for ORR are studied systematically. It is found that the curvature effect plays an important role in the adsorption and reduction of oxygen. The adsorption of O2 becomes weaker as the curvature varies from positive values (outside CNTs) to negative values (inside CNTs). The free energy change of the rate-determining step of ORR on the concave inner surface of Si-doped CNTs is smaller than that on the counterpart of Si-doped graphene, while that on the convex outer surface of Si-doped CNTs is larger than that on Si-doped graphene. Uncovering this new ORR mechanism on silicon-doped carbon electrodes is significant as the same principle could be applied to the development of various other metal-free efficient ORR catalysts for fuel cell applications.

Materials, Manufacturing and Test Development of a Composite Fan Blade Leading Edge Subcomponent for Improved Impact Resistance

NASA Technical Reports Server (NTRS)

Handschuh, Katherine M.; Miller, Sandi G.; Sinnott, Matthew J.; Kohlman, Lee W.; Roberts, Gary D.; Pereira, J. Michael; Ruggeri, Charles R.

2014-01-01

Application of polymer matrix composite materials for jet engine fan blades is becoming attractive as an alternative to metallic blades; particularly for large engines where significant weight savings are recognized on moving to a composite structure. However, the weight benefit of the composite of is offset by a reduction of aerodynamic efficiency resulting from a necessary increase in blade thickness; relative to the titanium blades. Blade dimensions are largely driven by resistance to damage on bird strike. Further development of the composite material is necessary to allow composite blade designs to approximate the dimensions of a metallic fan blade. The reduction in thickness over the state of the art composite blades is expected to translate into structural weight reduction, improved aerodynamic efficiency, and therefore reduced fuel consumption. This paper presents test article design, subcomponent blade leading edge fabrication, test method development, and initial results from ballistic impact of a gelatin projectile on the leading edge of composite fan blades. The simplified test article geometry was developed to realistically simulate a blade leading edge while decreasing fabrication complexity. Impact data is presented on baseline composite blades and toughened blades; where a considerable improvement to impact resistance was recorded.

Materials, Manufacturing, and Test Development of a Composite Fan Blade Leading Edge Subcomponent for Improved Impact Resistance

NASA Technical Reports Server (NTRS)

Miller, Sandi G.; Handschuh, Katherine; Sinnott, Matthew J.; Kohlman, Lee W.; Roberts, Gary D.; Martin, Richard E.; Ruggeri, Charles R.; Pereira, J. Michael

2015-01-01

Application of polymer matrix composite materials for jet engine fan blades is becoming attractive as an alternative to metallic blades; particularly for large engines where significant weight savings are recognized on moving to a composite structure. However, the weight benefit of the composite is offset by a reduction of aerodynamic efficiency resulting from a necessary increase in blade thickness; relative to the titanium blades. Blade dimensions are largely driven by resistance to damage on bird strike. Further development of the composite material is necessary to allow composite blade designs to approximate the dimensions of a metallic fan blade. The reduction in thickness over the state of the art composite blades is expected to translate into structural weight reduction, improved aerodynamic efficiency, and therefore reduced fuel consumption. This paper presents test article design, subcomponent blade leading edge fabrication, test method development, and initial results from ballistic impact of a gelatin projectile on the leading edge of composite fan blades. The simplified test article geometry was developed to realistically simulate a blade leading edge while decreasing fabrication complexity. Impact data is presented on baseline composite blades and toughened blades; where a considerable improvement to impact resistance was recorded.

Comparison of the direct and indirect reduction techniques during the surgical management of posterior malleolar fractures.

PubMed

Shi, Hong-Fei; Xiong, Jin; Chen, Yi-Xin; Wang, Jun-Fei; Qiu, Xu-Sheng; Huang, Jie; Gui, Xue-Yang; Wen, Si-Yuan; Wang, Yin-He

2017-03-14

The optimal method for the reduction and fixation of posterior malleolar fracture (PMF) remains inconclusive. Currently, both of the indirect and direct reduction techniques are widely used. We aimed to compare the reduction quality and clinical outcome of posterior malleolar fracture managed with the direct reduction technique through posterolateral approach or the indirect reduction technique using ligamentotaxis. Patients with a PMF involving over 25% of the articular surface were recruited and assigned to the direct reduction (DR) group or the indirect reduction (IR) group. Following reduction and fixation of the fracture, the quality of fracture reduction was evaluated in post-operative CT images. Clinical and radiological follow-ups were performed at 6 weeks, 3 months, 6 months, 12 months, and then at 6 month-intervals postoperatively. Functional outcome (AOFAS score), ankle range of motion, and Visual Analog Scale (VAS) were evaluated at the last follow-up. Statistical differences were compared between the DR and IR groups considering the patient demographics, quality of fracture reduction, AOFAS score, and VAS. Totally 116 patients were included, wherein 64 cases were assigned to the DR group and 52 cases were assigned to the IR group. The quality of fracture reduction was significant higher in the DR group (P = 0.038). In the patients who completed a minimum of 12 months' follow-up, a median AOFAS score of 87 was recorded in the DR group, which was significantly higher than that recorded in the IR group (a median score of 80). The ankle range of motion was slightly better in the DR group, with the mean dorsiflexion restriction recorded to be 5.2° and 6.1° in the DR and IR group respectively (P = 0.331). Similar VAS score was observed in the two groups (P = 0.419). The direct reduction technique through a posterolateral approach provide better quality of fracture reduction and functional outcome in the management of PMF over 25% of articular surface, as compared with the indirect reduction technique using ligamentotaxis. NCT02801474 (retrospectively registered, June 2016, ClinicalTrails.gov).

A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy.

PubMed

Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen

2018-01-05

With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP approach is tested and compared with MultiPlan on three clinical cases of varying complexities. In general, the plans generated by the SVDLP achieve steeper dose gradient, better conformity and less damage to normal tissues. In conclusion, the SVDLP approach effectively improves the quality of treatment plan due to the use of the complete beam search space. This challenging optimization problem with the complete beam search space is effectively handled by the proposed SVD acceleration.

A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy

NASA Astrophysics Data System (ADS)

Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen

2018-01-01

With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP approach is tested and compared with MultiPlan on three clinical cases of varying complexities. In general, the plans generated by the SVDLP achieve steeper dose gradient, better conformity and less damage to normal tissues. In conclusion, the SVDLP approach effectively improves the quality of treatment plan due to the use of the complete beam search space. This challenging optimization problem with the complete beam search space is effectively handled by the proposed SVD acceleration.

Los Angeles congestion reduction demonstration (Metro ExpressLanes) program. National evaluation : safety data test plan.

DOT National Transportation Integrated Search

1999-07-01

This document presents human factors guidelines for designers, owners operators, and planners involved in the development and operation of traffic management centers. Dimensions of the work environment affecting operator and system performance are ad...

Fabrication of microgrooves with excimer laser ablation techniques for plastic optical fiber array alignment purposes

NASA Astrophysics Data System (ADS)

Naessens, Kris; Van Hove, An; Coosemans, Thierry; Verstuyft, Steven; Ottevaere, Heidi; Vanwassenhove, Luc; Van Daele, Peter; Baets, Roel G.

2000-06-01

Laser ablation is extremely well suited for rapid prototyping and proves to be a versatile technique delivering high accuracy dimensioning and repeatability of features in a wide diversity of materials. In this paper, we present laser ablation as a fabrication method for micro machining in of arrays consisting of precisely dimensioned U-grooves in dedicated polycarbonate and polymethylmetacrylate plates. The dependency of the performance on various parameters is discussed. The fabricated plates are used to hold optical fibers by means of a UV-curable adhesive. Stacking and gluing of the plates allows the assembly of a 2D connector of plastic optical fibers for short distance optical interconnects.

Using the neutral zone to obtain maxillomandibular relationship records for complete denture patients.

PubMed

Alfano, S G; Leupold, R J

2001-06-01

A technique for obtaining maxillomandibular registration for complete denture patients is presented. The maxillary rim is formed with the use of conventional techniques. The mandibular rim is made from modeling plastic impression compound on a record base formed by the patient into the neutral zone. The mandibular rim then is reheated, and the patient determines the occlusal vertical dimension by swallowing. An imprint of the maxillary rim is made on the mandibular rim at the occlusal vertical dimension. The posterior extent of the mandibular rim is relieved 1 mm. Orientation notches are placed in both rims, and centric relation is recorded with a fast-setting vinyl polysiloxane material.

Environmental Barriers and Social Participation in Individuals With Spinal Cord Injury

PubMed Central

Tsai, I-Hsuan; Graves, Daniel E.; Chan, Wenyaw; Darkoh, Charles; Lee, Meei-Shyuan; Pompeii, Lisa A.

2018-01-01

Objective The study aimed to examine the relationship between environmental barriers and social participation among individuals with spinal cord injury (SCI). Method Individuals admitted to regional centers of the Model Spinal Cord Injury System in the United States due to traumatic SCI were interviewed and included in the National Spinal Cord Injury Database. This cross-sectional study applied a secondary analysis with a mixed effect model on the data from 3,162 individuals who received interviews from 2000 through 2005. Five dimensions of environmental barriers were estimated using the short form of the Craig Hospital Inventory of Environmental Factors—Short Form (CHIEF-SF). Social participation was measured with the short form of the Craig Handicap Assessment and Reporting Technique—Short Form (CHART-SF) and their employment status. Results Subscales of environmental barriers were negatively associated with the social participation measures. Each 1 point increase in CHIEF-SF total score (indicated greater environmental barriers) was associated with a 0.82 point reduction in CHART-SF total score (95% CI: −1.07, −0.57) (decreased social participation) and 4% reduction in the odds of being employed. Among the 5 CHIEF-SF dimensions, assistance barriers exhibited the strongest negative association with CHART-SF social participation score when compared to other dimensions, while work/school dimension demonstrated the weakest association with CHART-SF. Conclusions Environmental barriers are negatively associated with social participation in the SCI population. Working toward eliminating environmental barriers, especially assistance/service barriers, may help enhance social participation for people with SCI. PMID:28045281

Synergistic action of protease-modulating matrix and autologous growth factors in healing of diabetic foot ulcers. A prospective randomized trial.

PubMed

Kakagia, Despoina D; Kazakos, Konstantinos J; Xarchas, Konstantinos C; Karanikas, Michael; Georgiadis, George S; Tripsiannis, Gregory; Manolas, Constantinos

2007-01-01

This study tests the hypothesis that addition of a protease-modulating matrix enhances the efficacy of autologous growth factors in diabetic ulcers. Fifty-one patients with chronic diabetic foot ulcers were managed as outpatients at the Democritus University Hospital of Alexandroupolis and followed up for 8 weeks. All target ulcers were > or = 2.5 cm in any one dimension and had been previously treated only with moist gauze. Patients were randomly allocated in three groups of 17 patients each: Group A was treated only with the oxidized regenerated cellulose/collagen biomaterial (Promogran, Johnson & Johnson, New Brunswick, NJ), Group B was treated only with autologous growth factors delivered by Gravitational Platelet Separation System (GPS, Biomet), and Group C was managed by a combination of both. All ulcers were digitally photographed at initiation of the study and then at change of dressings once weekly. Computerized planimetry (Texas Health Science Center ImageTool, Version 3.0) was used to assess ulcer dimensions that were analyzed for homogeneity and significance using the Statistical Package for Social Sciences, Version 13.0. Post hoc analysis revealed that there was significantly greater reduction of all three dimensions of the ulcers in Group C compared to Groups A and B (all P<.001). Although reduction of ulcer dimensions was greater in Group A than in Group B, these differences did not reach statistical significance. It is concluded that protease-modulating dressings act synergistically with autologous growth factors and enhance their efficacy in diabetic foot ulcers.

Load-bearing capacity of all-ceramic posterior inlay-retained fixed dental prostheses.

PubMed

Puschmann, Djamila; Wolfart, Stefan; Ludwig, Klaus; Kern, Matthias

2009-06-01

The purpose of this in vitro study was to compare the quasi-static load-bearing capacity of all-ceramic resin-bonded three-unit inlay-retained fixed dental prostheses (IRFDPs) made from computer-aided design/computer-aided manufacturing (CAD/CAM)-manufactured yttria-stabilized tetragonal zirconia polycrystals (Y-TZP) frameworks with two different connector dimensions, with and without fatigue loading. Twelve IRFDPs each were made with connector dimensions 3 x 3 mm(2) (width x height) (control group) and 3 x 2 mm(2) (test group). Inlay-retained fixed dental prostheses were adhesively cemented on identical metal-models using composite resin cement. Subgroups of six specimens each were fatigued with maximal 1,200,000 loading cycles in a chewing simulator with a weight load of 25 kg and a load frequency of 1.5 Hz. The load-bearing capacity was tested in a universal testing machine for IRFDPs without fatigue loading and for IRFDPs that had not already fractured during fatigue loading. During fatigue testing one IRFDP (17%) of the test group failed. Under both loading conditions, IRFDPs of the control group exhibited statistically significantly higher load-bearing capacities than the test group. Fatigue loading reduced the load-bearing capacity in both groups. Considering the maximum chewing forces in the molar region, it seems possible to use zirconia ceramic as a core material for IRFDPs with a minimum connector dimension of 9 mm(2). A further reduction of the connector dimensions to 6 mm(2) results in a significant reduction of the load-bearing capacity.

PAPR reduction in FBMC using an ACE-based linear programming optimization

NASA Astrophysics Data System (ADS)

van der Neut, Nuan; Maharaj, Bodhaswar TJ; de Lange, Frederick; González, Gustavo J.; Gregorio, Fernando; Cousseau, Juan

2014-12-01

This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filter bank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reduction active constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing (OFDM), to an FBMC implementation as the main contribution. The four techniques introduced can be split up into two: linear programming optimization ACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming (LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach and provide a theoretical upper bound on achievable performance for the overlapping ACE techniques. The overlapping ACE techniques on the other hand can handle symbol by symbol processing. Furthermore, as a result of FBMC properties, the proposed techniques do not require side information transmission. The PAPR performance of the techniques is shown to match, or in some cases improve, on current PAPR techniques for FBMC. Initial analysis of the computational complexity of the SGP techniques indicates that the complexity issues with PAPR reduction in FBMC implementations can be addressed. The out-of-band interference introduced by the techniques is investigated. As a result, it is shown that the interference can be compensated for, whilst still maintaining decent PAPR performance. Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated to ensure that the trade-off in terms of BER degradation is not too severe. As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are ideal candidates for practical implementation in systems employing the low-complexity polyphase implementation of FBMC modulators. The methods are shown to offer significant PAPR reduction and increase the feasibility of FBMC as a replacement modulation system for OFDM.

Social dimensions of science-humanitarian collaboration: lessons from Padang, Sumatra, Indonesia.

PubMed

Shannon, Rachel; Hope, Max; McCloskey, John; Crowley, Dominic; Crichton, Peter

2014-07-01

This paper contains a critical exploration of the social dimensions of the science-humanitarian relationship. Drawing on literature on the social role of science and on the social dimensions of humanitarian practice, it analyses a science-humanitarian partnership for disaster risk reduction (DRR) in Padang, Sumatra, Indonesia, an area threatened by tsunamigenic earthquakes. The paper draws on findings from case study research that was conducted between 2010 and 2011. The case study illustrates the social processes that enabled and hindered collaboration between the two spheres, including the informal partnership of local people and scientists that led to the co-production of earthquake and tsunami DRR and limited organisational capacity and support in relation to knowledge exchange. The paper reflects on the implications of these findings for science-humanitarian partnering in general, and it assesses the value of using a social dimensions approach to understand scientific and humanitarian dialogue. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Flexible multibody simulation of automotive systems with non-modal model reduction techniques

NASA Astrophysics Data System (ADS)

Shiiba, Taichi; Fehr, Jörg; Eberhard, Peter

2012-12-01

The stiffness of the body structure of an automobile has a strong relationship with its noise, vibration, and harshness (NVH) characteristics. In this paper, the effect of the stiffness of the body structure upon ride quality is discussed with flexible multibody dynamics. In flexible multibody simulation, the local elastic deformation of the vehicle has been described traditionally with modal shape functions. Recently, linear model reduction techniques from system dynamics and mathematics came into the focus to find more sophisticated elastic shape functions. In this work, the NVH-relevant states of a racing kart are simulated, whereas the elastic shape functions are calculated with modern model reduction techniques like moment matching by projection on Krylov-subspaces, singular value decomposition-based reduction techniques, and combinations of those. The whole elastic multibody vehicle model consisting of tyres, steering, axle, etc. is considered, and an excitation with a vibration characteristics in a wide frequency range is evaluated in this paper. The accuracy and the calculation performance of those modern model reduction techniques is investigated including a comparison of the modal reduction approach.

The three-body problem with short-range interactions

NASA Astrophysics Data System (ADS)

Nielsen, E.; Fedorov, D. V.; Jensen, A. S.; Garrido, E.

2001-06-01

The quantum mechanical three-body problem is studied for general short-range interactions. We work in coordinate space to facilitate accurate computations of weakly bound and spatially extended systems. Hyperspherical coordinates are used in both the interpretation and as an integral part of the numerical method. Universal properties and model independence are discussed throughout the report. We present an overview of the hyperspherical adiabatic Faddeev equations. The wave function is expanded on hyperspherical angular eigenfunctions which in turn are found numerically using the Faddeev equations. We generalize the formalism to any dimension of space d greater or equal to two. We present two numerical techniques for solving the Faddeev equations on the hypersphere. These techniques are effective for short and intermediate/large distances including use for hard core repulsive potentials. We study the asymptotic limit of large hyperradius and derive the analytic behaviour of the angular eigenvalues and eigenfunctions. We discuss four applications of the general method. We first analyze the Efimov and Thomas effects for arbitrary angular momenta and for arbitrary dimensions d. Second we apply the method to extract the general behaviour of weakly bound three-body systems in two dimensions. Third we illustrate the method in three dimensions by structure computations of Borromean halo nuclei, the hypertriton and helium molecules. Fourth we investigate in three dimensions three-body continuum properties of Borromean halo nuclei and recombination reactions of helium atoms as an example of direct relevance for the stability of Bose-Einstein condensates.

Cross-linked lysozyme crystal templated synthesis of Au nanoparticles as high-performance recyclable catalysts.

PubMed

Liang, Miao; Wang, Libing; Liu, Xia; Qi, Wei; Su, Rongxin; Huang, Renliang; Yu, Yanjun; He, Zhimin

2013-06-21

Bio-nanomaterials fabricated using a bioinspired templating technique represent a novel class of composite materials with diverse applications in biomedical, electronic devices, drug delivery, and catalysis. In this study, Au nanoparticles (NPs) are synthesized within the solvent channels of cross-linked lysozyme crystals (CLLCs) in situ without the introduction of extra chemical reagents or physical treatments. The as-prepared AuNPs-in-protein crystal hybrid materials are characterized by light microscopy, transmission electron microscopy, x-ray diffraction, and Fourier-transform infrared spectroscopy analyses. Small AuNPs with narrow size distribution reveal the restriction effects of the porous structure in the lysozyme crystals. These composite materials are proven to be active heterogeneous catalysts for the reduction of 4-nitrophenol to 4-aminophenol. These catalysts can be easily recovered and reused at least 20 times because of the physical stability and macro-dimension of CLLCs. This work is the first to use CLLCs as a solid biotemplate for the preparation of recyclable high-performance catalysts.

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

USGS Publications Warehouse

Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

2013-01-01

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

Prediction of Mutagenicity of Chemicals from Their Calculated Molecular Descriptors: A Case Study with Structurally Homogeneous versus Diverse Datasets.

PubMed

Basak, Subhash C; Majumdar, Subhabrata

2015-01-01

Variation in high-dimensional data is often caused by a few latent factors, and hence dimension reduction or variable selection techniques are often useful in gathering useful information from the data. In this paper we consider two such recent methods: Interrelated two-way clustering and envelope models. We couple these methods with traditional statistical procedures like ridge regression and linear discriminant analysis, and apply them on two data sets which have more predictors than samples (i.e. n < p scenario) and several types of molecular descriptors. One of these datasets consists of a congeneric group of Amines while the other has a much diverse collection compounds. The difference of prediction results between these two datasets for both the methods supports the hypothesis that for a congeneric set of compounds, descriptors of a certain type are enough to provide good QSAR models, but as the data set grows diverse including a variety of descriptors can improve model quality considerably.

Recent Improvements in Semi-Span Testing at the National Transonic Facility (Invited)

NASA Technical Reports Server (NTRS)

Gatlin, G. M.; Tomek, W. G.; Payne, F. M.; Griffiths, R. C.

2006-01-01

Three wind tunnel investigations of a commercial transport, high-lift, semi-span configuration have recently been conducted in the National Transonic Facility at the NASA Langley Research Center. Throughout the course of these investigations multiple improvements have been developed in the facility semi-span test capability. The primary purpose of the investigations was to assess Reynolds number scale effects on a modern commercial transport configuration up to full-scale flight test conditions (Reynolds numbers on the order of 27 million). The tests included longitudinal aerodynamic studies at subsonic takeoff and landing conditions across a range of Reynolds numbers from that available in conventional wind tunnels up to flight conditions. The purpose of this paper is to discuss lessons learned and improvements incorporated into the semi-span testing process. Topics addressed include enhanced thermal stabilization and moisture reduction procedures, assessments and improvements in model sealing techniques, compensation of model reference dimensions due to test temperature, significantly improved semi-span model access capability, and assessments of data repeatability.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Biomaterials and cells for neural tissue engineering: Current choices.

PubMed

Sensharma, Prerana; Madhumathi, G; Jayant, Rahul D; Jaiswal, Amit K

2017-08-01

The treatment of nerve injuries has taken a new dimension with the development of tissue engineering techniques. Prior to tissue engineering, suturing and surgery were the only options for effective treatment. With the advent of tissue engineering, it is now possible to design a scaffold that matches the exact biological and mechanical properties of the tissue. This has led to substantial reduction in the complications posed by surgeries and suturing to the patients. New synthetic and natural polymers are being applied to test their efficiency in generating an ideal scaffold. Along with these, cells and growth factors are also being incorporated to increase the efficiency of a scaffold. Efforts are being made to devise a scaffold that is biodegradable, biocompatible, conducting and immunologically inert. The ultimate goal is to exactly mimic the extracellular matrix in our body, and to elicit a combination of biochemical, topographical and electrical cues via various polymers, cells and growth factors, using which nerve regeneration can efficiently occur. Copyright © 2017 Elsevier B.V. All rights reserved.

Cross-linked lysozyme crystal templated synthesis of Au nanoparticles as high-performance recyclable catalysts

NASA Astrophysics Data System (ADS)

Liang, Miao; Wang, Libing; Liu, Xia; Qi, Wei; Su, Rongxin; Huang, Renliang; Yu, Yanjun; He, Zhimin

2013-06-01

Bio-nanomaterials fabricated using a bioinspired templating technique represent a novel class of composite materials with diverse applications in biomedical, electronic devices, drug delivery, and catalysis. In this study, Au nanoparticles (NPs) are synthesized within the solvent channels of cross-linked lysozyme crystals (CLLCs) in situ without the introduction of extra chemical reagents or physical treatments. The as-prepared AuNPs-in-protein crystal hybrid materials are characterized by light microscopy, transmission electron microscopy, x-ray diffraction, and Fourier-transform infrared spectroscopy analyses. Small AuNPs with narrow size distribution reveal the restriction effects of the porous structure in the lysozyme crystals. These composite materials are proven to be active heterogeneous catalysts for the reduction of 4-nitrophenol to 4-aminophenol. These catalysts can be easily recovered and reused at least 20 times because of the physical stability and macro-dimension of CLLCs. This work is the first to use CLLCs as a solid biotemplate for the preparation of recyclable high-performance catalysts.

Effect of hydrogen addition on soot formation in an ethylene/air premixed flame

NASA Astrophysics Data System (ADS)

De Iuliis, S.; Maffi, S.; Migliorini, F.; Cignoli, F.; Zizak, G.

2012-03-01

The effect of hydrogen addition to fuel in soot formation and growth mechanisms is investigated in a rich ethylene/air premixed flame. To this purpose, three-angle scattering and extinction measurements are carried out in flames with different hydrogen contents. By applying the Rayleigh-Debye-Gans theory and the fractal-like description, soot concentration and morphology, with the evaluation of radius of gyration, volume-mean diameter and primary particle diameter are retrieved. To derive fractal parameters such as fractal dimension and fractal prefactor to be used for optical measurements, sampling technique and TEM analysis are performed. In addition, data concerning soot morphology obtained from TEM analysis are compared with the optical results. A good agreement in the value of the primary particle diameter between optical and ex-situ measurements is found. Significant effects of hydrogen addition are detected and presented in this work. In particular, hydrogen addition to fuel is responsible for a reduction in soot concentration, radius of gyration and primary particle diameter.

Chain dynamics and nanoparticle motion in attractive polymer nanocomposites subjected to large deformations.

PubMed

Senses, Erkan; Tyagi, Madhusudan; Natarajan, Bharath; Narayanan, Suresh; Faraone, Antonio

2017-11-08

The effect of large deformation on the chain dynamics in attractive polymer nanocomposites was investigated using neutron scattering techniques. Quasi-elastic neutron backscattering measurements reveal a substantial reduction of polymer mobility in the presence of attractive, well-dispersed nanoparticles. In addition, large deformations are observed to cause a further slowing down of the Rouse rates at high particle loadings, where the interparticle spacings are slightly smaller than the chain dimensions, i.e. in the strongly confined state. No noticeable change, however, was observed for a lightly confined system. The reptation tube diameter, measured by neutron spin echo, remained unchanged after shear, suggesting that the level of chain-chain entanglements is not significantly affected. The shear-induced changes in the interparticle bridging reflect the slow nanoparticle motion measured by X-ray photon correlation spectroscopy. These results provide a first step for understanding how large shear can significantly affect the segmental motion in nanocomposites and open up new opportunities for designing mechanically responsive soft materials.

Chain dynamics and nanoparticle motion in attractive polymer nanocomposites subjected to large deformations

DOE PAGES

Senses, Erkan; Tyagi, Madhusudan; Natarajan, Bharath; ...

2017-09-28

The effect of large deformation on the chain dynamics in attractive polymer nanocomposites was investigated using neutron scattering techniques. Quasielastic neutron backscattering measurements reveal a substantial reduction of polymer mobility in the presence of attractive, well-dispersed nanoparticles. Additionally, large deformations are observed to cause a further slowing down of the Rouse rates at high particle loadings, where the interparticle spacings are slightly smaller than the chain dimensions, i.e. in the strongly confined state. No noticeable change, however, was observed for a lightly confined system. The reptation tube diameter, measured by neutron spin echo, remained unchanged after shear, suggesting that themore » level of chain-chain entanglements is not significantly affected. The shearinduced changes in the interparticle bridging reflects on the slow nanoparticle motion measured by X-ray photon correlation spectroscopy. These results provide a first step for understanding how large shear can significantly affect the segmental motion in nanocomposites and open up new opportunities for designing mechanically responsive soft materials.« less

Polypyrrole Coated Cellulosic Substrate Modified by Copper Oxide as Electrode for Nitrate Electroreduction

NASA Astrophysics Data System (ADS)

Hamam, A.; Oukil, D.; Dib, A.; Hammache, H.; Makhloufi, L.; Saidani, B.

2015-08-01

The aim of this work is to synthesize polypyrrole (PPy) films on nonconducting cellulosic substrate and modified by copper oxide particles for use in the nitrate electroreduction process. Firstly, the chemical polymerization of polypyrrole onto cellulosic substrate is conducted by using FeCl3 as an oxidant and pyrrole as monomer. The thickness and topography of the different PPy films obtained were estimated using a profilometer apparatus. The electrochemical reactivity of the obtained electrodes was tested by voltamperometry technique and electrochemical impedance spectroscopy. Secondly, the modification of the PPy film surface by incorporation of copper oxide particles is conducted by applying a galvanostatic procedure from a CuCl2 solution. The SEM, EDX and XRD analysis showed the presence of CuO particles in the polymer films with dimensions less than 50 nm. From cyclic voltamperometry experiments, the composite activity for the nitrate electroreduction reaction was evaluated and the peak of nitrate reduction is found to vary linearly with initial nitrate concentration.

Chain dynamics and nanoparticle motion in attractive polymer nanocomposites subjected to large deformations

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

Senses, Erkan; Tyagi, Madhusudan; Natarajan, Bharath

The effect of large deformation on the chain dynamics in attractive polymer nanocomposites was investigated using neutron scattering techniques. Quasielastic neutron backscattering measurements reveal a substantial reduction of polymer mobility in the presence of attractive, well-dispersed nanoparticles. Additionally, large deformations are observed to cause a further slowing down of the Rouse rates at high particle loadings, where the interparticle spacings are slightly smaller than the chain dimensions, i.e. in the strongly confined state. No noticeable change, however, was observed for a lightly confined system. The reptation tube diameter, measured by neutron spin echo, remained unchanged after shear, suggesting that themore » level of chain-chain entanglements is not significantly affected. The shearinduced changes in the interparticle bridging reflects on the slow nanoparticle motion measured by X-ray photon correlation spectroscopy. These results provide a first step for understanding how large shear can significantly affect the segmental motion in nanocomposites and open up new opportunities for designing mechanically responsive soft materials.« less

Test of 3D CT reconstructions by EM + TV algorithm from undersampled data

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

Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da

2013-05-06

Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry withmore » alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.« less

Exploring the CAESAR database using dimensionality reduction techniques

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Raymer, Michael L.

2012-06-01

The Civilian American and European Surface Anthropometry Resource (CAESAR) database containing over 40 anthropometric measurements on over 4000 humans has been extensively explored for pattern recognition and classification purposes using the raw, original data [1-4]. However, some of the anthropometric variables would be impossible to collect in an uncontrolled environment. Here, we explore the use of dimensionality reduction methods in concert with a variety of classification algorithms for gender classification using only those variables that are readily observable in an uncontrolled environment. Several dimensionality reduction techniques are employed to learn the underlining structure of the data. These techniques include linear projections such as the classical Principal Components Analysis (PCA) and non-linear (manifold learning) techniques, such as Diffusion Maps and the Isomap technique. This paper briefly describes all three techniques, and compares three different classifiers, Naïve Bayes, Adaboost, and Support Vector Machines (SVM), for gender classification in conjunction with each of these three dimensionality reduction approaches.

Quantification of normative ranges and baseline predictors of aortoventricular interface dimensions using multi-detector computed tomographic imaging in patients without aortic valve disease.

PubMed

Gooley, Robert P; Cameron, James D; Soon, Jennifer; Loi, Duncan; Chitale, Gauri; Syeda, Rifath; Meredith, Ian T

2015-09-01

Multidetector computed tomographic (MDCT) assessment of the aortoventricular interface has gained increased importance with the advent of minimally invasive treatment modalities for aortic and mitral valve disease. This has included a standardised technique of identifying a plane through the nadir of each coronary cusp, the basal plane, and taking further measurements in relation to this plane. Despite this there is no published data defining normal ranges for these aortoventricular metrics in a healthy cohort. This study seeks to quantify normative ranges for MDCT derived aortoventricular dimensions and evaluate baseline demographic and anthropomorphic associates of these measurements in a normal cohort. 250 consecutive patients undergoing MDCT coronary angiography were included. Aortoventricular dimensions at multiple levels of the aortoventricular interface were assessed and normative ranges quantified. Multivariate linear regression was performed to identify baseline predictors of each metric. The mean age was 59±12 years. The basal plane was eccentric (EI=0.22±0.06) while the left ventricular outflow tract was more eccentric (EI=0.32±0.06), with no correlation to gender, age or hypertension. Male gender, height and body mass index were consistent independent predictors of larger aortoventricular dimensions at all anatomical levels, while age was predictive of supra-annular measurements. Male gender, height and BMI are independent predictors of all aortoventricular dimensions while age predicts only supra-annular dimensions. Use of defined metrics such as the basal plane and formation of normative ranges for these metrics allows reference for clinical reporting and for future research studies by using a standardised measurement technique. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Reference right atrial dimensions and volume estimation by steady state free precession cardiovascular magnetic resonance

PubMed Central

2013-01-01

Background Cardiovascular magnetic resonance (CMR) steady state free precession (SSFP) cine sequences with high temporal resolution and improved post-processing can accurately measure RA dimensions. We used this technique to define ranges for normal RA volumes and dimensions normalized, when necessary, to the influence of gender, body surface area (BSA) and age, and also to define the best 2D images-derived predictors of RA enlargement. Methods For definition of normal ranges of RA volume we studied 120 healthy subjects (60 men, 60 women; 20 subjects per age decile from 20 to 80 years), after careful exclusion of cardiovascular abnormality. We also studied 120 patients (60 men, 60 women; age range 20 to 80 years) with a clinical indication for CMR in order to define the best 1D and 2D predictors of RA enlargement. Data were generated from SSFP cine CMR, with 3-dimensional modeling, including tracking of the atrioventricular ring motion and time-volume curves analysis. Results In the group of healthy individuals, age influenced RA 2-chamber area and transverse diameter. Gender influenced most absolute RA dimensions and volume. Interestingly, right atrial volumes did not change with age and gender when indexed to body surface area. New CMR normal ranges for RA dimensions were modeled and displayed for clinical use with normalization for BSA and gender and display of parameter variation with age. Finally, the best 2D images-derived independent predictors of RA enlargement were indexed area and indexed longitudinal diameter in the 2-chamber view. Conclusion Reference RA dimensions and predictors of RA enlargement are provided using state-of-the-art CMR techniques. PMID:23566426

Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research

PubMed Central

Golino, Hudson F.; Epskamp, Sacha

2017-01-01

The estimation of the correct number of dimensions is a long-standing problem in psychometrics. Several methods have been proposed, such as parallel analysis (PA), Kaiser-Guttman’s eigenvalue-greater-than-one rule, multiple average partial procedure (MAP), the maximum-likelihood approaches that use fit indexes as BIC and EBIC and the less used and studied approach called very simple structure (VSS). In the present paper a new approach to estimate the number of dimensions will be introduced and compared via simulation to the traditional techniques pointed above. The approach proposed in the current paper is called exploratory graph analysis (EGA), since it is based on the graphical lasso with the regularization parameter specified using EBIC. The number of dimensions is verified using the walktrap, a random walk algorithm used to identify communities in networks. In total, 32,000 data sets were simulated to fit known factor structures, with the data sets varying across different criteria: number of factors (2 and 4), number of items (5 and 10), sample size (100, 500, 1000 and 5000) and correlation between factors (orthogonal, .20, .50 and .70), resulting in 64 different conditions. For each condition, 500 data sets were simulated using lavaan. The result shows that the EGA performs comparable to parallel analysis, EBIC, eBIC and to Kaiser-Guttman rule in a number of situations, especially when the number of factors was two. However, EGA was the only technique able to correctly estimate the number of dimensions in the four-factor structure when the correlation between factors were .7, showing an accuracy of 100% for a sample size of 5,000 observations. Finally, the EGA was used to estimate the number of factors in a real dataset, in order to compare its performance with the other six techniques tested in the simulation study. PMID:28594839

Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research.

PubMed

Golino, Hudson F; Epskamp, Sacha

2017-01-01

The estimation of the correct number of dimensions is a long-standing problem in psychometrics. Several methods have been proposed, such as parallel analysis (PA), Kaiser-Guttman's eigenvalue-greater-than-one rule, multiple average partial procedure (MAP), the maximum-likelihood approaches that use fit indexes as BIC and EBIC and the less used and studied approach called very simple structure (VSS). In the present paper a new approach to estimate the number of dimensions will be introduced and compared via simulation to the traditional techniques pointed above. The approach proposed in the current paper is called exploratory graph analysis (EGA), since it is based on the graphical lasso with the regularization parameter specified using EBIC. The number of dimensions is verified using the walktrap, a random walk algorithm used to identify communities in networks. In total, 32,000 data sets were simulated to fit known factor structures, with the data sets varying across different criteria: number of factors (2 and 4), number of items (5 and 10), sample size (100, 500, 1000 and 5000) and correlation between factors (orthogonal, .20, .50 and .70), resulting in 64 different conditions. For each condition, 500 data sets were simulated using lavaan. The result shows that the EGA performs comparable to parallel analysis, EBIC, eBIC and to Kaiser-Guttman rule in a number of situations, especially when the number of factors was two. However, EGA was the only technique able to correctly estimate the number of dimensions in the four-factor structure when the correlation between factors were .7, showing an accuracy of 100% for a sample size of 5,000 observations. Finally, the EGA was used to estimate the number of factors in a real dataset, in order to compare its performance with the other six techniques tested in the simulation study.

Simple and rapid system for two-dimensional gel electrophoresis technique: A laboratory exercise for high school students.

PubMed

Maurye, Praveen; Basu, Arpita; Biswas, Jayanta Kumar; Bandyopadhyay, Tapas Kumar; Naskar, Malay

2018-02-28

Polyacrylamide gel electrophoresis (PAGE) is the most classical technique favored worldwide for resolution of macromolecules in many biochemistry laboratories due to its incessant advanced developments and wide modifications. These ever-growing advancements in the basic laboratory equipments lead to emergence of many expensive, complex, and tricky laboratory equipments. Practical courses of biochemistry at high school or undergraduate levels are often affected by these complications. Two dimensional gel electrophoresis technique (2D-PAGE) used for resolving thousands of proteins in a gel is a combination of isoelectric focusing (first dimension gel electrophoresis technique) and sodium-dodecylsulphate PAGE (second dimension gel electrophoresis technique or SDS-PAGE). Two different laboratory equipments are needed to carry out effective 2D-PAGE technique, which also invites extra burden to the school laboratory. Here, we describe a low cost, time saving and simple gel cassette for protein 2D-PAGE technique that uses easily fabricated components and routine off-the-shelf materials. The performance of the apparatus was verified in a practical exercise by a group of high school students with positive outcomes. © 2018 by The International Union of Biochemistry and Molecular Biology, 2018. © 2018 The International Union of Biochemistry and Molecular Biology.

Hybrid numerical method for solution of the radiative transfer equation in one, two, or three dimensions.

PubMed

Reinersman, Phillip N; Carder, Kendall L

2004-05-01

A hybrid method is presented by which Monte Carlo (MC) techniques are combined with an iterative relaxation algorithm to solve the radiative transfer equation in arbitrary one-, two-, or three-dimensional optical environments. The optical environments are first divided into contiguous subregions, or elements. MC techniques are employed to determine the optical response function of each type of element. The elements are combined, and relaxation techniques are used to determine simultaneously the radiance field on the boundary and throughout the interior of the modeled environment. One-dimensional results compare well with a standard radiative transfer model. The light field beneath and adjacent to a long barge is modeled in two dimensions and displayed. Ramifications for underwater video imaging are discussed. The hybrid model is currently capable of providing estimates of the underwater light field needed to expedite inspection of ship hulls and port facilities.

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

A simple method using two-step hot embossing technique with shrinking for fabrication of cross microchannels on PMMA substrate and its application to electrophoretic separation of amino acids in functional drinks.

PubMed

Wiriyakun, Natta; Nacapricha, Duangjai; Chantiwas, Rattikan

2016-12-01

This work presents a simple hot embossing method with a shrinking procedure to produce cross-shape microchannels on poly(methyl methacrylate) (PMMA) substrate for the fabrication of an electrophoresis chip. The proposed method employed a simple two-step hot embossing technique, carried out consecutively on the same piece of substrate to make the crossing channels. Studies of embossing conditions, i.e. temperature, pressure and time, were carried out to investigate their effects on the dimension of the microchannels. Applying a simple shrinking procedure reduced the size of the channels from 700±20µm wide×150±5µm deep to 250±10µm wide×30±2µm deep, i.e. 80% and 64% reduction in the depth and width, respectively. Thermal fusion was employed to bond the PMMA substrate with a PMMA cover plate to produce the microfluidic device. Replication of microchip was achieved by precise control of conditions in the fabrication process (pressure, temperature and time), resulting in lower than 7% RSD of channel dimension, width and depth (n =10 devices). The method was simple and robust without the use of expensive equipment to construct the microstructure on a thermoplastic substrate. The PMMA microchip was used for demonstration of amine functionalization on the PMMA surface, measurement of electroosmotic flow and for electrophoretic separation of amino acids in functional drink samples. The precision of migration time and peak area of the amino acids, Lys, Ile and Phe at 125μM to 500μM, were in the range 3.2-4.2% RSD (n=9 devices) and 4.5-5.3% RSD (n=9 devices), respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Integration of adaptive guided filtering, deep feature learning, and edge-detection techniques for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Gao, Bing

2017-11-01

The integration of an edge-preserving filtering technique in the classification of a hyperspectral image (HSI) has been proven effective in enhancing classification performance. This paper proposes an ensemble strategy for HSI classification using an edge-preserving filter along with a deep learning model and edge detection. First, an adaptive guided filter is applied to the original HSI to reduce the noise in degraded images and to extract powerful spectral-spatial features. Second, the extracted features are fed as input to a stacked sparse autoencoder to adaptively exploit more invariant and deep feature representations; then, a random forest classifier is applied to fine-tune the entire pretrained network and determine the classification output. Third, a Prewitt compass operator is further performed on the HSI to extract the edges of the first principal component after dimension reduction. Moreover, the regional growth rule is applied to the resulting edge logical image to determine the local region for each unlabeled pixel. Finally, the categories of the corresponding neighborhood samples are determined in the original classification map; then, the major voting mechanism is implemented to generate the final output. Extensive experiments proved that the proposed method achieves competitive performance compared with several traditional approaches.

Localised electrochemical impedance measurements of a polymer electrolyte fuel cell using a reference electrode array to give cathode-specific measurements and examine membrane hydration dynamics

NASA Astrophysics Data System (ADS)

Engebretsen, Erik; Hinds, Gareth; Meyer, Quentin; Mason, Tom; Brightman, Edward; Castanheira, Luis; Shearing, Paul R.; Brett, Daniel J. L.

2018-04-01

Advances in bespoke diagnostic techniques for polymer electrolyte fuel cells continue to provide unique insight into the internal operation of these devices and lead to improved performance and durability. Localised measurements of current density have proven to be extremely useful in designing better fuel cells and identifying optimal operating strategies, with electrochemical impedance spectroscopy (EIS) now routinely used to deconvolute the various losses in fuel cells. Combining the two techniques provides another dimension of understanding, but until now each localised EIS has been based on 2-electrode measurements, composed of both the anode and cathode responses. This work shows that a reference electrode array can be used to give individual electrode-specific EIS responses, in this case the cathode is focused on to demonstrate the approach. In addition, membrane hydration dynamics are studied under current load steps from open circuit voltage. A three-stage process is identified associated with an initial rapid reduction in membrane resistance after 10 s of applying a current step, followed by a slower ramp to approximately steady state, which was achieved after ∼250 s. These results support previously published work that has looked at membrane swelling dynamics and reveal that membrane hydration/membrane resistance is highly heterogeneous.

A review on machine learning principles for multi-view biological data integration.

PubMed

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

Simulation of white light generation and near light bullets using a novel numerical technique

NASA Astrophysics Data System (ADS)

Zia, Haider

2018-01-01

An accurate and efficient simulation has been devised, employing a new numerical technique to simulate the derivative generalised non-linear Schrödinger equation in all three spatial dimensions and time. The simulation models all pertinent effects such as self-steepening and plasma for the non-linear propagation of ultrafast optical radiation in bulk material. Simulation results are compared to published experimental spectral data of an example ytterbium aluminum garnet system at 3.1 μm radiation and fits to within a factor of 5. The simulation shows that there is a stability point near the end of the 2 mm crystal where a quasi-light bullet (spatial temporal soliton) is present. Within this region, the pulse is collimated at a reduced diameter (factor of ∼2) and there exists a near temporal soliton at the spatial center. The temporal intensity within this stable region is compressed by a factor of ∼4 compared to the input. This study shows that the simulation highlights new physical phenomena based on the interplay of various linear, non-linear and plasma effects that go beyond the experiment and is thus integral to achieving accurate designs of white light generation systems for optical applications. An adaptive error reduction algorithm tailor made for this simulation will also be presented in appendix.

Reflections on conformal spectra

DOE PAGES

Kim, Hyungrok; Kravchuk, Petr; Ooguri, Hirosi

2016-04-29

Here, we use modular invariance and crossing symmetry of conformal field theory to reveal approximate reflection symmetries in the spectral decompositions of the partition function in two dimensions in the limit of large central charge and of the four-point function in any dimension in the limit of large scaling dimensions Δ 0 of external operators. We use these symmetries to motivate universal upper bounds on the spectrum and the operator product expansion coefficients, which we then derive by independent techniques. Some of the bounds for four-point functions are valid for finite Δ 0 as well as for large Δ 0.more » We discuss a similar symmetry in a large spacetime dimension limit. Finally, we comment on the analogue of the Cardy formula and sparse light spectrum condition for the four-point function.« less

WavePacket: A Matlab package for numerical quantum dynamics. I: Closed quantum systems and discrete variable representations

NASA Astrophysics Data System (ADS)

Schmidt, Burkhard; Lorenz, Ulf

2017-04-01

WavePacket is an open-source program package for the numerical simulation of quantum-mechanical dynamics. It can be used to solve time-independent or time-dependent linear Schrödinger and Liouville-von Neumann-equations in one or more dimensions. Also coupled equations can be treated, which allows to simulate molecular quantum dynamics beyond the Born-Oppenheimer approximation. Optionally accounting for the interaction with external electric fields within the semiclassical dipole approximation, WavePacket can be used to simulate experiments involving tailored light pulses in photo-induced physics or chemistry. The graphical capabilities allow visualization of quantum dynamics 'on the fly', including Wigner phase space representations. Being easy to use and highly versatile, WavePacket is well suited for the teaching of quantum mechanics as well as for research projects in atomic, molecular and optical physics or in physical or theoretical chemistry. The present Part I deals with the description of closed quantum systems in terms of Schrödinger equations. The emphasis is on discrete variable representations for spatial discretization as well as various techniques for temporal discretization. The upcoming Part II will focus on open quantum systems and dimension reduction; it also describes the codes for optimal control of quantum dynamics. The present work introduces the MATLAB version of WavePacket 5.2.1 which is hosted at the Sourceforge platform, where extensive Wiki-documentation as well as worked-out demonstration examples can be found.

Health-Related Quality of Life of the General German Population in 2015: Results from the EQ-5D-5L.

PubMed

Huber, Manuel B; Felix, Julia; Vogelmann, Martin; Leidl, Reiner

2017-04-16

The EQ-5D-5L is a widely used generic instrument to measure health-related quality of life. This study evaluates health perception in a representative sample of the general German population from 2015. To compare results over time, a component analysis technique was used that separates changes in the description and valuation of health states. The whole sample and also subgroups, stratified by sociodemographic parameters as well as disease affliction, were analyzed. In total, 2040 questionnaires (48.4% male, mean age 47.3 year) were included. The dimension with the lowest number of reported problems was self-care (93.0% without problems), and the dimension with the highest proportion of impairment was pain/discomfort (71.2% without problems). Some 64.3% of the study population were identified as problem-free. The visual analog scale (VAS) mean for all participants was 85.1. Low education was connected with significantly lower VAS scores, but the effect was small. Depression, heart disease, and diabetes had a strong significant negative effect on reported VAS means. Results were slightly better than those in a similar 2012 survey; the most important driver was the increase in the share of the study population that reported to be problem-free. In international comparisons, health perception of the general German population is relatively high and, compared with previous German studies, fairly stable over recent years. Elderly and sick people continue to report significant reductions in perceived health states.

Variation in electrical properties of gamma irradiated cadmium selenate nanowires

NASA Astrophysics Data System (ADS)

Chauhan, R. P.; Rana, Pallavi; Narula, Chetna; Panchal, Suresh; Choudhary, Ritika

2016-07-01

Preparation of low-dimensional materials attracts more and more interest in the last few years, mainly due to the wide field of potential commercial applications ranging from life sciences, medicine and biotechnology to communication and electronics. One-dimensional systems are the smallest dimension structures that can be used for efficient transport of electrons and thus expected to be critical to the function and integration of nanoscale devices. Nanowires with well controlled morphology and extremely high aspect ratio can be obtained by replicating a nanoporous polymer ion-track membrane with cylindrical pores of controlled dimensions. With this technique, materials can be deposited within the pores of the membrane by electrochemical reduction of the desired ion. In the present study, cadmium selenate nanowires were synthesized potentiostatically via template method. These synthesized nanowires were then exposed to gamma rays by using a 60Co source at the Inter University Accelerator Centre, New Delhi, India. Structural, morphological, electrical and elemental characterizations were made in order to analyze the effect of gamma irradiation on the synthesized nanowires. I-V measurements of cadmium selenate nanowires, before and after irradiation were made with the help of Keithley 2400 source meter and Ecopia probe station. A significant change in the electrical conductivity of cadmium selenate nanowires was found after gamma irradiation. The crystallography of the synthesized nanowires was also studied using a Rigaku X-ray diffractrometer equipped with Cu-Kα radiation. XRD patterns of irradiated samples showed no variation in the peak positions or phase change.

Investigation of thermal conduction in symmetric and asymmetric nanoporous structures

NASA Astrophysics Data System (ADS)

Yu, Ziqi; Ferrer-Argemi, Laia; Lee, Jaeho

2017-12-01

Nanoporous structures with a critical dimension comparable to or smaller than the phonon mean free path have demonstrated significant thermal conductivity reductions that are attractive for thermoelectric applications, but the presence of various geometric parameters complicates the understanding of governing mechanisms. Here, we use a ray tracing technique to investigate phonon boundary scattering phenomena in Si nanoporous structures of varying pore shapes, pore alignments, and pore size distributions, and identify mechanisms that are primarily responsible for thermal conductivity reductions. Our simulation results show that the neck size, or the smallest distance between nearest pores, is the key parameter in understanding nanoporous structures of varying pore shapes and the same porosities. When the neck size and the porosity are both identical, asymmetric pore shapes provide a lower thermal conductivity compared with symmetric pore shapes, due to localized heat fluxes. Asymmetric nanoporous structures show possibilities of realizing thermal rectification even with fully diffuse surface boundaries, in which optimal arrangements of triangular pores show a rectification ratio up to 13 when the injection angles are optimally controlled. For symmetric nanoporous structures, hexagonal-lattice pores achieve larger thermal conductivity reductions than square-lattice pores due to the limited line of sight for phonons. We also show that nanoporous structures of alternating pore size distributions from large to small pores yield a lower thermal conductivity compared with those of uniform pore size distributions in the given porosity. These findings advance the understanding of phonon boundary scattering phenomena in complex geometries and enable optimal designs of artificial nanostructures for thermoelectric energy harvesting and solid-state cooling systems.

Leadership Enhancement through Mind Management by Meditation--A Scientific Yogic Technique

ERIC Educational Resources Information Center

Selvi, B. Tamil; Thangarajathi, S.

2010-01-01

Good education is the product of good administration and the administration is not simply a managerial occupation. It demands new dimensions of knowledge, techniques and skills. Today administrators are confronting a variety of problems in their respective organizations. The complex environments of the educational institutions require leaders and…

Alternative Assessment Techniques for Blended and Online Courses

ERIC Educational Resources Information Center

Litchfield, Brenda C.; Dempsey, John V.

2013-01-01

Alternative assessment techniques are essential for increasing student learning in blended and online courses. Rather than simply answer multiple-choice questions, students can choose activities in an academic contract. By using a contract, students will be active participants in their own learning. Contracts add a dimension of authenticity to…

An Evaluation of Fractal Surface Measurement Methods for Characterizing Landscape Complexity from Remote-Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina Siu-Ngan; Qiu, Hong-Lie; Quattrochi, Dale A.; Emerson, Charles W.; Arnold, James E. (Technical Monitor)

2001-01-01

The rapid increase in digital data volumes from new and existing sensors necessitates the need for efficient analytical tools for extracting information. We developed an integrated software package called ICAMS (Image Characterization and Modeling System) to provide specialized spatial analytical functions for interpreting remote sensing data. This paper evaluates the three fractal dimension measurement methods: isarithm, variogram, and triangular prism, along with the spatial autocorrelation measurement methods Moran's I and Geary's C, that have been implemented in ICAMS. A modified triangular prism method was proposed and implemented. Results from analyzing 25 simulated surfaces having known fractal dimensions show that both the isarithm and triangular prism methods can accurately measure a range of fractal surfaces. The triangular prism method is most accurate at estimating the fractal dimension of higher spatial complexity, but it is sensitive to contrast stretching. The variogram method is a comparatively poor estimator for all of the surfaces, particularly those with higher fractal dimensions. Similar to the fractal techniques, the spatial autocorrelation techniques are found to be useful to measure complex images but not images with low dimensionality. These fractal measurement methods can be applied directly to unclassified images and could serve as a tool for change detection and data mining.

Reliable Cellular Automata with Self-Organization

NASA Astrophysics Data System (ADS)

Gács, Peter

2001-04-01

In a probabilistic cellular automaton in which all local transitions have positive probability, the problem of keeping a bit of information indefinitely is nontrivial, even in an infinite automaton. Still, there is a solution in 2 dimensions, and this solution can be used to construct a simple 3-dimensional discrete-time universal fault-tolerant cellular automaton. This technique does not help much to solve the following problems: remembering a bit of information in 1 dimension; computing in dimensions lower than 3; computing in any dimension with non-synchronized transitions. Our more complex technique organizes the cells in blocks that perform a reliable simulation of a second (generalized) cellular automaton. The cells of the latter automaton are also organized in blocks, simulating even more reliably a third automaton, etc. Since all this (a possibly infinite hierarchy) is organized in "software," it must be under repair all the time from damage caused by errors. A large part of the problem is essentially self-stabilization recovering from a mess of arbitrary size and content. The present paper constructs an asynchronous one-dimensional fault-tolerant cellular automaton, with the further feature of "self-organization." The latter means that unless a large amount of input information must be given, the initial configuration can be chosen homogeneous.

Effect of age and cone dimensions on cervical regeneration: an Italian multicentric prospective observational study

PubMed Central

Ciavattini, Andrea; Delli Carpini, Giovanni; Moriconi, Lorenzo; Clemente, Nicolò; Montik, Nina; De Vincenzo, Rosa; Del Fabro, Anna; Buttignol, Monica; Ricci, Caterina; Moro, Francesca; Sopracordevole, Francesco

2018-01-01

Objectives To evaluate cervical regeneration at 6 months following excisional treatment for high-grade cervical intraepithelial neoplasia (CIN), and to investigate the effect of cone dimensions, age of patients and technique of excision on the efficacy of the regeneration process. Design Prospective observational multicentric study. Setting Three tertiary care and research centres. Participants Among the 197 eligible women of childbearing age, older than 25 years of age, undergoing for the first time a loop electrosurgical excision procedure or carbon dioxide laser cervical excision for a high-grade CIN at the colposcopy-directed cervical punch biopsy, and with a final diagnosis of high-grade CIN, 165 completed the 6-month follow-up and were included in the analysis. Primary outcome measures The cervical length and volume regeneration (%) after 6 months from procedure were determined by three-dimensional ultrasound, and the correlation of regeneration with cone dimensions, age and excision technique was evaluated. Results The mean±SD cervical length regeneration at 6 months was 89.5%±6.3% and the mean±SD cervical volume regeneration was 86.3%±13.2%. At the multivariate analysis, a significant and independent inverse correlation between excised cone length and cervical regeneration emerged (r=−0.39, P<0.001). A significantly negative trend in length regeneration at 6 months from procedure with an increasing class of cone length was found (P<0.001). No significant association was found in relation with patient age at the time of procedure or with the technique of excision. Conclusions Cervical length regeneration at 6 months from excisional treatments is negatively affected by an increasing cone length but not from the age of the patient or the technique of excision. While still achieving equal clinical efficacy, it is crucial to contain cone dimensions, in order to favour a greater length regeneration, reducing the cervical harm and the potential future obstetric complications. PMID:29555794

Roughness and uniformity improvements on self-aligned quadruple patterning technique for 10nm node and beyond by wafer stress engineering

NASA Astrophysics Data System (ADS)

Liu, Eric; Ko, Akiteru; O'Meara, David; Mohanty, Nihar; Franke, Elliott; Pillai, Karthik; Biolsi, Peter

2017-05-01

Dimension shrinkage has been a major driving force in the development of integrated circuit processing over a number of decades. The Self-Aligned Quadruple Patterning (SAQP) technique is widely adapted for sub-10nm node in order to achieve the desired feature dimensions. This technique provides theoretical feasibility of multiple pitch-halving from 193nm immersion lithography by using various pattern transferring steps. The major concept of this approach is to a create spacer defined self-aligned pattern by using single lithography print. By repeating the process steps, double, quadruple, or octuple are possible to be achieved theoretically. In these small architectures, line roughness control becomes extremely important since it may contribute to a significant portion of process and device performance variations. In addition, the complexity of SAQP in terms of processing flow makes the roughness improvement indirective and ineffective. It is necessary to discover a new approach in order to improve the roughness in the current SAQP technique. In this presentation, we demonstrate a novel method to improve line roughness performances on 30nm pitch SAQP flow. We discover that the line roughness performance is strongly related to stress management. By selecting different stress level of film to be deposited onto the substrate, we can manipulate the roughness performance in line and space patterns. In addition, the impact of curvature change by applied film stress to SAQP line roughness performance is also studied. No significant correlation is found between wafer curvature and line roughness performance. We will discuss in details the step-by-step physical performances for each processing step in terms of critical dimension (CD)/ critical dimension uniformity (CDU)/line width roughness (LWR)/line edge roughness (LER). Finally, we summarize the process needed to reach the full wafer performance targets of LWR/LER in 1.07nm/1.13nm on 30nm pitch line and space pattern.

Consistent Pauli reduction on group manifolds

DOE PAGES

Baguet, A.; Pope, Christopher N.; Samtleben, H.

2016-01-01

We prove an old conjecture by Duff, Nilsson, Pope and Warner asserting that the NSNS sector of supergravity (and more general the bosonic string) allows for a consistent Pauli reduction on any d-dimensional group manifold G, keeping the full set of gauge bosons of the G×G isometry group of the bi-invariant metric on G. The main tool of the construction is a particular generalised Scherk–Schwarz reduction ansatz in double field theory which we explicitly construct in terms of the group's Killing vectors. Examples include the consistent reduction from ten dimensions on S3×S3 and on similar product spaces. The construction ismore » another example of globally geometric non-toroidal compactifications inducing non-geometric fluxes.« less

Properties of dimension witnesses and their semidefinite programming relaxations

NASA Astrophysics Data System (ADS)

Mironowicz, Piotr; Li, Hong-Wei; Pawłowski, Marcin

2014-08-01

In this paper we develop a method for investigating semi-device-independent randomness expansion protocols that was introduced in Li et al. [H.-W. Li, P. Mironowicz, M. Pawłowski, Z.-Q. Yin, Y.-C. Wu, S. Wang, W. Chen, H.-G. Hu, G.-C. Guo, and Z.-F. Han, Phys. Rev. A 87, 020302(R) (2013), 10.1103/PhysRevA.87.020302]. This method allows us to lower bound, with semi-definite programming, the randomness obtained from random number generators based on dimension witnesses. We also investigate the robustness of some randomness expanders using this method. We show the role of an assumption about the trace of the measurement operators and a way to avoid it. The method is also generalized to systems of arbitrary dimension and for a more general form of dimension witnesses than in our previous paper. Finally, we introduce a procedure of dimension witness reduction, which can be used to obtain from an existing witness a new one with a higher amount of certifiable randomness. The presented methods find an application for experiments [J. Ahrens, P. Badziag, M. Pawlowski, M. Zukowski, and M. Bourennane, Phys. Rev. Lett. 112, 140401 (2014), 10.1103/PhysRevLett.112.140401].

Factor analytic reduction of the carotid-cardiac baroreflex parameters

NASA Technical Reports Server (NTRS)

Ludwig, David A.

1989-01-01

An accepted method for measuring the responsiveness of the carotid-cardiac baroreflex to arterial pressure changes is to artificially stimulate the baroreceptors in the neck. This is accomplished by using a pressurized neck cuff which constricts and distends the carotid artery and subsequently stimulates the baroreceptors. Nine physiological responses to this type of stimulation are quantified and used as indicators of the baroreflex. Thirty male humans between the ages 27 and 46 underwent the carotid-cardiac baroreflex test. The data for the nine response parameters were analyzed by principle component factor analysis. The results of this analysis indicated that 93 percent of the total variance across all nine parameters could be explained in four dimensions. Examination of the factor loadings following an orthogonal rotation of the principle components indicated four well defined dimensions. The first two dimensions reflected location points for R-R interval and carotid distending pressure respectively. The third dimension was composed of measures reflecting the gain of the reflex. The fourth dimension was the ratio of the resting R-R interval to R-R interval during simulated hypertension. The data suggests that the analysis of all nine baroreflex parameters is redundant.

Domain decomposition for a mixed finite element method in three dimensions

USGS Publications Warehouse

Cai, Z.; Parashkevov, R.R.; Russell, T.F.; Wilson, J.D.; Ye, X.

2003-01-01

We consider the solution of the discrete linear system resulting from a mixed finite element discretization applied to a second-order elliptic boundary value problem in three dimensions. Based on a decomposition of the velocity space, these equations can be reduced to a discrete elliptic problem by eliminating the pressure through the use of substructures of the domain. The practicality of the reduction relies on a local basis, presented here, for the divergence-free subspace of the velocity space. We consider additive and multiplicative domain decomposition methods for solving the reduced elliptic problem, and their uniform convergence is established.

Analysis of radiation-induced small Cu particle cluster formation in aqueous CuCl2

USGS Publications Warehouse

Jayanetti, Sumedha; Mayanovic, Robert A.; Anderson, Alan J.; Bassett, William A.; Chou, I.-Ming

2001-01-01

Radition-induced small Cu particle cluster formation in aqueous CuCl2 was analyzed. It was noticed that nearest neighbor distance increased with the increase in the time of irradiation. This showed that the clusters approached the lattice dimension of bulk copper. As the average cluster size approached its bulk dimensions, an increase in the nearest neighbor coordination number was found with the decrease in the surface to volume ratio. Radiolysis of water by incident x-ray beam led to the reduction of copper ions in the solution to themetallic state.

Methods of Sparse Modeling and Dimensionality Reduction to Deal with Big Data

DTIC Science & Technology

2015-04-01

supervised learning (c). Our framework consists of two separate phases: (a) first find an initial space in an unsupervised manner; then (b) utilize label...model that can learn thousands of topics from a large set of documents and infer the topic mixture of each document, 2) a supervised dimension reduction...model that can learn thousands of topics from a large set of documents and infer the topic mixture of each document, (i) a method of supervised

Head-and-face anthropometric survey of Chinese workers.

PubMed

Du, Lili; Zhuang, Ziqing; Guan, Hongyu; Xing, Jingcai; Tang, Xianzhi; Wang, Limin; Wang, Zhenglun; Wang, Haijiao; Liu, Yuewei; Su, Wenjin; Benson, Stacey; Gallagher, Sean; Viscusi, Dennis; Chen, Weihong

2008-11-01

Millions of workers in China rely on respirators and other personal protective equipment to reduce the risk of injury and occupational diseases. However, it has been >25 years since the first survey of facial dimensions for Chinese adults was published, and it has never been completely updated. Thus, an anthropometric survey of Chinese civilian workers was conducted in 2006. A total of 3000 subjects (2026 males and 974 females) between the ages of 18 and 66 years old was measured using traditional techniques. Nineteen facial dimensions, height, weight, neck circumference, waist circumference and hip circumference were measured. A stratified sampling plan of three age strata and two gender strata was implemented. Linear regression analysis was used to evaluate the possible effects of gender, age, occupation and body size on facial dimensions. The regression coefficients for gender indicated that for all anthropometric dimensions, males had significantly larger measurements than females. As body mass index increased, dimensions measured increased significantly. Construction workers and miners had significantly smaller measurements than individuals employed in healthcare or manufacturing for a majority of dimensions. Five representative indexes of facial dimension (face length, face width, nose protrusion, bigonial breadth and nasal root breadth) were selected based on correlation and cluster analysis of all dimensions. Through comparison with the facial dimensions of American subjects, this study indicated that Chinese civilian workers have shorter face length, smaller nose protrusion, larger face width and longer lip length.

[Development and testing of a preparedness and response capacity questionnaire in public health emergency for Chinese provincial and municipal governments].

PubMed

Hu, Guo-Qing; Rao, Ke-Qin; Sun, Zhen-Qiu

2008-12-01

To develop a capacity questionnaire in public health emergency for Chinese local governments. Literature reviews, conceptual modelling, stake-holder analysis, focus group, interview, and Delphi technique were employed together to develop the questionnaire. Classical test theory and case study were used to assess the reliability and validity. (1) A 2-dimension conceptual model was built. A preparedness and response capacity questionnaire in public health emergency with 10 dimensions and 204 items, was developed. (2) Reliability and validity results. Internal consistency: except for dimension 3 and 8, the Cronbach's alpha coefficient of other dimensions was higher than 0.60. The alpha coefficients of dimension 3 and dimension 8 were 0.59 and 0.39 respectively; Content validity: the questionnaire was recognized by the investigatees; Construct validity: the Spearman correlation coefficients among the 10 dimensions fluctuated around 0.50, ranging from 0.26 to 0.75 (P<0.05); Discrimination validity: comparisons of 10 dimensions among 4 provinces did not show statistical significance using One-way analysis of variance (P>0.05). Criterion-related validity: case study showed significant difference among the 10 dimensions in Beijing between February 2003 (before SARS event) and November 2005 (after SARS event). The preparedness and response capacity questionnaire in public health emergency is a reliable and valid tool, which can be used in all provinces and municipalities in China.

Radar cross-section reduction based on an iterative fast Fourier transform optimized metasurface

NASA Astrophysics Data System (ADS)

Song, Yi-Chuan; Ding, Jun; Guo, Chen-Jiang; Ren, Yu-Hui; Zhang, Jia-Kai

2016-07-01

A novel polarization insensitive metasurface with over 25 dB monostatic radar cross-section (RCS) reduction is introduced. The proposed metasurface is comprised of carefully arranged unit cells with spatially varied dimension, which enables approximate uniform diffusion of incoming electromagnetic (EM) energy and reduces the threat from bistatic radar system. An iterative fast Fourier transform (FFT) method for conventional antenna array pattern synthesis is innovatively applied to find the best unit cell geometry parameter arrangement. Finally, a metasurface sample is fabricated and tested to validate RCS reduction behavior predicted by full wave simulation software Ansys HFSSTM and marvelous agreement is observed.

Elastic mismatch induced reduction of the thermal conductivity of silicon with aluminum nano-inclusions

NASA Astrophysics Data System (ADS)

Donovan, Brian F.; Jensen, Wade A.; Chen, Long; Giri, Ashutosh; Poon, S. Joseph; Floro, Jerrold A.; Hopkins, Patrick E.

2018-05-01

We use aluminum nano-inclusions in silicon to demonstrate the dominance of elastic modulus mismatch induced scattering in phonon transport. We use time domain thermoreflectance to measure the thermal conductivity of thin films of silicon co-deposited with aluminum via molecular beam epitaxy resulting in a Si film with 10% clustered Al inclusions with nanoscale dimensions and a reduction in thermal conductivity of over an order of magnitude. We compare these results with well-known models in order to demonstrate that the reduction in the thermal transport is driven by elastic mismatch effects induced by aluminum in the system.

A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics

NASA Technical Reports Server (NTRS)

Tian, Yuan; Liu, Zhuo; Klasky, Scott; Wang, Bin; Abbasi, Hasan; Zhou, Shujia; Podhorszki, Norbert; Clune, Tom; Logan, Jeremy; Yu, Weikuan

2013-01-01

In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.

Engineered plant biomass feedstock particles

DOEpatents

Dooley, James H [Federal Way, WA; Lanning, David N [Federal Way, WA; Broderick, Thomas F [Lake Forest Park, WA

2011-10-11

A novel class of flowable biomass feedstock particles with unusually large surface areas that can be manufactured in remarkably uniform sizes using low-energy comminution techniques. The feedstock particles are roughly parallelepiped in shape and characterized by a length dimension (L) aligned substantially with the grain direction and defining a substantially uniform distance along the grain, a width dimension (W) normal to L and aligned cross grain, and a height dimension (H) normal to W and L. The particles exhibit a disrupted grain structure with prominent end and surface checks that greatly enhances their skeletal surface area as compared to their envelope surface area. The L.times.H dimensions define a pair of substantially parallel side surfaces characterized by substantially intact longitudinally arrayed fibers. The W.times.H dimensions define a pair of substantially parallel end surfaces characterized by crosscut fibers and end checking between fibers. The L.times.W dimensions define a pair of substantially parallel top surfaces characterized by some surface checking between longitudinally arrayed fibers. The feedstock particles are manufactured from a variety of plant biomass materials including wood, crop residues, plantation grasses, hemp, bagasse, and bamboo.

Instantons in Lifshitz field theories

NASA Astrophysics Data System (ADS)

Fujimori, Toshiaki; Nitta, Muneto

2015-10-01

BPS instantons are discussed in Lifshitz-type anisotropic field theories. We consider generalizations of the sigma model/Yang-Mills instantons in renormalizable higher dimensional models with the classical Lifshitz scaling invariance. In each model, BPS instanton equation takes the form of the gradient flow equations for "the superpotential" defining "the detailed balance condition". The anisotropic Weyl rescaling and the coset space dimensional reduction are used to map rotationally symmetric instantons to vortices in two-dimensional anisotropic systems on the hyperbolic plane. As examples, we study anisotropic BPS baby Skyrmion 1+1 dimensions and BPS Skyrmion in 2+1 dimensions, for which we take Kähler 1-form and the Wess-Zumiono-Witten term as the superpotentials, respectively, and an anisotropic generalized Yang-Mills instanton in 4 + 1 dimensions, for which we take the Chern-Simons term as the superpotential.

Comparative sonographic evaluation of the anteroposterior dimensions of the pancreas in diabetics and nondiabetics.

PubMed

Agabi, J O; Akhigbe, A O

2016-01-01

The pancreas is an insulin-producing gland and is prone to varying degrees of destruction and change in patients with diabetes mellitus (DM). Various morphological changes including reduction in the pancreas dimensions have been described in DM. To determine pancreatic anteroposterior (AP) dimensions in diabetics by sonography and compare with nondiabetics. To also evaluate the correlation of the AP dimensions with patient's anthropometry, as well as the duration of the disease in comparison with nondiabetics. This is a comparative cross-sectional study involving 150 diabetics with 150 sex and age matched healthy normoglycemic group used as controls. Sonographic measurements of the AP dimensions of the pancreatic head, body, and tail of both study groups were performed with the use of 3.5 MHz curvilinear array transducer of a SonoAce X4 ultrasound machine. Data were analyzed using Statistical Package for Social Sciences version 17 (SPSS Inc., Chicago, IL, USA). A statistical test was considered significant at P ≤ 0.05 and 95% confidence interval. Pancreas AP dimensions were significantly smaller in diabetics compared to those of the controls. The mean dimensions were 1.91 ± 0.26 cm, 0.95 ± 0.12 cm, and 0.91 ± 0.11 cm for the head, body, and tail, respectively, in diabetics and 2.32 ± 0.22 cm, 1.43 ± 0.19 cm, and 1.34 ± 0.20 cm in the control (P < 0.001 in all cases). The dimensions were also significantly smaller in the Type 1 diabetics compared to Type 2 (P < 0.001 in all cases). The mean duration of illness for the Types 1 and 2 diabetics were 3.09 ± 1.38 and 3.78 ± 3.12 years, respectively. Longer duration of illness was associated with smaller pancreas body and tail dimensions, while pancreas head dimension was not significantly affected by the duration of illness. Diabetics have smaller pancreas AP dimensions compared to the normal population.

A combination of selected mapping and clipping to increase energy efficiency of OFDM systems

PubMed Central

Lee, Byung Moo; Rim, You Seung

2017-01-01

We propose an energy efficient combination design for OFDM systems based on selected mapping (SLM) and clipping peak-to-average power ratio (PAPR) reduction techniques, and show the related energy efficiency (EE) performance analysis. The combination of two different PAPR reduction techniques can provide a significant benefit in increasing EE, because it can take advantages of both techniques. For the combination, we choose the clipping and SLM techniques, since the former technique is quite simple and effective, and the latter technique does not cause any signal distortion. We provide the structure and the systematic operating method, and show the various analyzes to derive the EE gain based on the combined technique. Our analysis show that the combined technique increases the EE by 69% compared to no PAPR reduction, and by 19.34% compared to only using SLM technique. PMID:29023591

Mapping gas-phase organic reactivity and concomitant secondary organic aerosol formation: chemometric dimension reduction techniques for the deconvolution of complex atmospheric data sets

NASA Astrophysics Data System (ADS)

Wyche, K. P.; Monks, P. S.; Smallbone, K. L.; Hamilton, J. F.; Alfarra, M. R.; Rickard, A. R.; McFiggans, G. B.; Jenkin, M. E.; Bloss, W. J.; Ryan, A. C.; Hewitt, C. N.; MacKenzie, A. R.

2015-07-01

Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i.e. toluene) oxidation and "more realistic" plant mesocosm systems, demonstrates that such an ensemble of chemometric mapping has the potential to be used for the classification of more complex spectra of unknown origin. More specifically, the addition of mesocosm data from fig and birch tree experiments shows that isoprene and monoterpene emitting sources, respectively, can be mapped onto the statistical model structure and their positional vectors can provide insight into their biological sources and controlling oxidative chemistry. The potential to extend the methodology to the analysis of ambient air is discussed using results obtained from a zero-dimensional box model incorporating mechanistic data obtained from the Master Chemical Mechanism (MCMv3.2). Such an extension to analysing ambient air would prove a powerful asset in assisting with the identification of SOA sources and the elucidation of the underlying chemical mechanisms involved.

Ultrasonic-assisted chemical reduction synthesis and structural characterization of copper nanoparticles

NASA Astrophysics Data System (ADS)

Anh-Nga, Nguyen T.; Tuan-Anh, Nguyen; Thanh-Quoc, Nguyen; Ha, Do Tuong

2018-04-01

Copper nanoparticles, due to their special properties, small dimensions and low-cost preparation, have many potential applications such as in optical, electronics, catalysis, sensors, antibacterial agents. In this study, copper nanoparticles were synthesized by chemical reduction method with different conditions in order to investigate the optimum conditions which gave the smallest (particle diameter) dimensions. The synthesis step used copper (II) acetate salt as precursor, ascorbic acid as reducing agent, glycerin and polyvinylpyrrolidone (PVP) as protector and stabilizer. The assistance of ultrasonic was were considered as the significant factor affecting the size of the synthesized particles. The results showed that the copper nanoparticles have been successfully synthesized with the diameter as small as 20-40 nm and the conditions of ultrasonic waves were 48 kHz of frequency, 20 minutes of treated time and 65-70 °C of temperature. The synthesized copper nanoparticles were characterized by optical absorption spectrum, scanning electron microscopy (SEM), and Fourier Transform Infrared Spectrometry.

Sparse partial least squares regression for simultaneous dimension reduction and variable selection

PubMed Central

Chun, Hyonho; Keleş, Sündüz

2010-01-01

Partial least squares regression has been an alternative to ordinary least squares for handling multicollinearity in several areas of scientific research since the 1960s. It has recently gained much attention in the analysis of high dimensional genomic data. We show that known asymptotic consistency of the partial least squares estimator for a univariate response does not hold with the very large p and small n paradigm. We derive a similar result for a multivariate response regression with partial least squares. We then propose a sparse partial least squares formulation which aims simultaneously to achieve good predictive performance and variable selection by producing sparse linear combinations of the original predictors. We provide an efficient implementation of sparse partial least squares regression and compare it with well-known variable selection and dimension reduction approaches via simulation experiments. We illustrate the practical utility of sparse partial least squares regression in a joint analysis of gene expression and genomewide binding data. PMID:20107611

Liposuction-assisted four pedicle-based breast reduction (LAFPBR): A new safer technique of breast reduction for elderly patients.

PubMed

La Padula, Simone; Hersant, Barbara; Noel, Warren; Meningaud, Jean Paul

2018-05-01

As older people increasingly care for their body image and remain active longer, the demand for reduction mammaplasty is increasing in this population. Only a few studies of reduction mammaplasty have specifically focussed on the outcomes in elderly women. We developed a new breast reduction technique: the Liposuction-Assisted Four Pedicle-Based Breast Reduction (LAFPBR) that is especially indicated for elderly patients. The aim of this paper was to describe the LAFPBR technique and to determine whether it could be considered a safer option for elderly patients compared to the superomedial pedicle (SMP) technique. A retrospective study included sixty-two women aged 60 years and over who underwent bilateral breast reduction mammaplasty. Thirty-one patients underwent LAFPBR and 31 patients were operated using the SMP technique. Complications and patient satisfaction in both groups were analysed. Patient satisfaction was measured using a validated questionnaire: the client satisfaction questionnaire 8 (CSQ-8). The LAFPBR technique required less operating time, and avoided significant blood loss. Six minor complications were observed in SMP patients. No LAFPBR women developed a procedure-related complication. Patient satisfaction was high with a mean score of 29.65 in LAFPBR patients and 28.68 in SMP patients. The LAFPBR is an easy procedure that appears safer than SMP and results in a high satisfaction rate in elderly women. Copyright © 2018 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

NMR relaxation dispersion of Miglyol molecules confined inside polymeric micro-capsules.

PubMed

Nechifor, Ruben; Ardelean, Ioan; Mattea, Carlos; Stapf, Siegfried; Bogdan, Mircea

2011-11-01

Frequency dependent NMR relaxation studies have been carried out on Miglyol molecules confined inside core shell polymeric capsules to obtain a correlation between capsule dimension and the measurable parameters. The polymeric capsules were prepared using an interfacial polymerization technique for three different concentrations of Miglyol. It was shown that the variation of Miglyol concentration influences the capsule dimension. Their average size was estimated using the pulsed field gradient diffusometry technique. The relaxation dispersion curves were obtained at room temperature by a combined use of a fast field cycling instrument and a high-field instrument. The frequency dependence of relaxation rate shows a transition from a diffusion-limited to a surface-limited relaxation regime. Copyright © 2011 John Wiley & Sons, Ltd.

Biomimetic approaches to control soluble concentration gradients in biomaterials.

PubMed

Nguyen, Eric H; Schwartz, Michael P; Murphy, William L

2011-04-08

Soluble concentration gradients play a critical role in controlling tissue formation during embryonic development. The importance of soluble signaling in biology has motivated engineers to design systems that allow precise and quantitative manipulation of gradient formation in vitro. Engineering techniques have increasingly moved to the third dimension in order to provide more physiologically relevant models to study the biological role of gradient formation and to guide strategies for controlling new tissue formation for therapeutic applications. This review provides an overview of efforts to design biomimetic strategies for soluble gradient formation, with a focus on microfluidic techniques and biomaterials approaches for moving gradient generation to the third dimension. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determination of Probe Volume Dimensions in Coherent Measurement Techniques

NASA Technical Reports Server (NTRS)

Tedder, Sarah A.; Weikl, Markus C.; Seeger, Thomas; Leipertz, Alfred

2008-01-01

When investigating combustion phenomena with pump-probe techniques, the spatial resolution is given by the overlapping region of the laser beams and thus defines the probe volume size. The size of this probe volume becomes important when the length scales of interest are on the same order or smaller. In this work, we present a new approach to measure the probe volume in three dimensions (3-D), which can be used to determine the probe volume length, diameter, and shape. The optical arrangement and data evaluation are demonstrated for a dual-pump dual-broadband coherent anti-Stokes Raman scattering (CARS) setup which is used for combustion diagnostics. This new approach offers a simple, quick alternative with more capabilities than formerly used probe volume measurement methods.

Study of a two-dimension transient heat propagation in cylindrical coordinates by means of two finite difference methods

NASA Astrophysics Data System (ADS)

Dumencu, A.; Horbaniuc, B.; Dumitraşcu, G.

2016-08-01

The analytical approach of unsteady conduction heat transfer under actual conditions represent a very difficult (if not insurmountable) problem due to the issues related to finding analytical solutions for the conduction heat transfer equation. Various techniques have been developed in order to overcome these difficulties, among which the alternate directions method and the decomposition method. Both of them are particularly suited for two-dimension heat propagation. The paper deals with both techniques in order to verify whether the results provided are in good accordance. The studied case consists of a long hollow cylinder, and considers that the time-dependent temperature field varies both in the radial and the axial directions. The implicit technique is used in both methods and involves the simultaneous solving of a set of equations for all of the nodes for each time step successively for each of the two directions. Gauss elimination is used to obtain the solution of the set, representing the nodal temperatures. After using the two techniques the results show a very good agreement, and since the decomposition is easier to use in terms of computer code and running time, this technique seems to be more recommendable.

Balloon osteoplasty--a new technique for reduction and stabilisation of impression fractures in the tibial plateau: a cadaver study and first clinical application.

PubMed

Ahrens, Philipp; Sandmann, Gunther; Bauer, Jan; König, Benjamin; Martetschläger, Frank; Müller, Dirk; Siebenlist, Sebastian; Kirchhoff, Chlodwig; Neumaier, Markus; Biberthaler, Peter; Stöckle, Ulrich; Freude, Thomas

2012-09-01

Fractures of the tibial plateau are among the most severe injuries of the knee joint and lead to advanced gonarthrosis if the reduction does not restore perfect joint congruency. Many different reduction techniques focusing on open surgical procedures have been described in the past. In this context we would like to introduce a novel technique which was first tested in a cadaver setup and has undergone its successful first clinical application. Since kyphoplasty demonstrated effective ways of anatomical correction in spine fractures, we adapted the inflatable instruments and used the balloon technique to reduce depressed fragments of the tibial plateau. The technique enabled us to restore a congruent cartilage surface and bone reduction. In this technique we see a useful new method to reduce depressed fractures of the tibial plateau with the advantages of low collateral damage as it is known from minimally invasive procedures.

Comparative analysis of ex-situ and operando X-ray diffraction experiments for lithium insertion materials

NASA Astrophysics Data System (ADS)

Brant, William R.; Li, Dan; Gu, Qinfen; Schmid, Siegbert

2016-01-01

A comparative study of ex-situ and operando X-ray diffraction techniques using the fast lithium ion conductor Li0.18Sr0.66Ti0.5Nb0.5O3 is presented. Ex-situ analysis of synchrotron X-ray diffraction data suggests that a single phase material exists for all discharges to as low as 0.422 V. For samples discharged to 1 V or lower, i.e. with higher lithium content, it is possible to determine the lithium position from the X-ray data. However, operando X-ray diffraction from a coin cell reveals that a kinetically driven two phase region occurs during battery cycling below 1 V. Through monitoring the change in unit cell dimension during electrochemical cycling the dynamics of lithium insertion are explored. A reduction in the rate of unit cell expansion of 22(2)% part way through the first discharge and 13(1)% during the second discharge is observed. This reduction may be caused by a drop in lithium diffusion into the bulk material for higher lithium contents. A more significant change is a jump in the unit cell expansion by 60(2)% once the lithium content exceeds one lithium ion per vacant site. It is suggested that this jump is caused by damping of octahedral rotations, thus establishing a link between lithium content and octahedral rotations.

Spaced antenna drift

NASA Technical Reports Server (NTRS)

Royrvik, O.

1983-01-01

It has been suggested that the spaced antenna drift (SAD) technique could be successfully used by VHF radars and that it would be superior to a Doppler-beam-swinging (DBS) technique because it would take advantage of the aspect sensitivity of the scattered signal, and might also benefit from returns from single meteors. It appears, however, that the technique suffers from several limitations. On the basis of one SAD experiment performed at the very large Jicamarca radar, it is concluded that the SAD technique can be compared in accuracy to the DBS technique only if small antenna dimensions are used.

Identification of key factors in consumers' adoption behavior of intelligent medical terminals based on a hybrid modified MADM model for product improvement.

PubMed

Liu, Yupeng; Chen, Yifei; Tzeng, Gwo-Hshiung

2017-09-01

As a new application technology of the Internet of Things (IoT), intelligent medical treatment has attracted the attention of both nations and industries through its promotion of medical informatisation, modernisation, and intelligentisation. Faced with a wide variety of intelligent medical terminals, consumers may be affected by various factors when making purchase decisions. To examine and evaluate the key influential factors (and their interrelationships) of consumer adoption behavior for improving and promoting intelligent medical terminals toward achieving set aspiration level in each dimension and criterion. A hybrid modified Multiple Attribute Decision-Making (MADM) model was used for this study, based on three components: (1) the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, to build an influential network relationship map (INRM) at both 'dimensions' and 'criteria' levels; (2) the DEMATEL-based analytic network process (DANP) method, to determine the interrelationships and influential weights among the criteria and identify the source-influential factors; and (3) the modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to evaluate and improve for reducing the performance gaps to meet the consumers' needs for continuous improvement and sustainable products-development. First, a consensus on the influential factors affecting consumers' adoption of intelligent medical terminals was collected from experts' opinion in practical experience. Next, the interrelationships and influential weights of DANP among dimensions/criteria based on the DEMATEL technique were determined. Finally, two intelligent medicine bottles (AdhereTech, A 1 alternative; and Audio/Visual Alerting Pillbox, A 2 alternative) were reviewed as the terminal devices to verify the accuracy of the MADM model and evaluate its performance on each criterion for improving the total certification gaps by systematics according to the modified VIKOR method based on an INRM. In this paper, the criteria and dimensions used to improve the evaluation framework are validated. The systematic evaluation in index system is constructed on the basis of five dimensions and corresponding ten criteria. Influential weights of all criteria ranges from 0.037 to 0.152, which shows the rank of criteria importance. The evaluative framework were validated synthetically and scientifically. INRM (influential network relation map) was obtained from experts' opinion through DEMATEL technique shows complex interrelationship among factors. At the dimension level, the environmental dimension influences other dimensions the most, whereas the security dimension is most influenced by others. So the improvement order of environmental dimension is prior to security dimension. The newly constructed approach was still further validated by the results of the empirical case, where performance gap improvement strategies were analyzed for decision-makers. The modified VIKOR method was especially validated for solving real-world problems in intelligent medical terminal improvement processes. For this paper, A 1 performs better than A 2 , however, promotion mix, brand factor, and market environment are shortcomings faced by both A 1 and A 2 . In addition, A 2 should be improved in the wireless network technology, and the objective contact with a high degree of gaps. Based on the evaluation index system and the integrated model proposed here, decision-makers in enterprises can identify gaps when promoting intelligent medical terminals, from which they can get valuable advice to improve consumer adoption. Additionally, an INRM and the influential weights of DANP can be combined using the modified VIKOR method as integrated weightings to determine how to reduce gaps and provide the best improvement strategies for reaching set aspiration levels. Copyright © 2017 Elsevier B.V. All rights reserved.

Dimensions of schizophrenia and their time course of response to a second generation antipsychotic olanzapine-A clinical study.

PubMed

Birur, Badari; Thirthalli, Jagadisha; Janakiramaiah, N; Shelton, Richard C; Gangadhar, Bangalore N

2016-12-01

The pattern of symptom response to second generation antipsychotics (SGAs) has not been studied extensively. Understanding the time course of symptom response would help to rationally monitor patient progress. To determine the short-term differential time course of response of symptom dimensions of first episode schizophrenia viz., negative, positive symptoms and 5 factors of anergia, thought disturbance, activation, paranoid-belligerence and depression to treatment with SGA olanzapine. 57 drug naive patients with schizophrenia were treated for 4 weeks with olanzapine 10mg/day, increased to 20mg/day in 1 week. Weight was recorded and ratings with the Positive and Negative Syndrome scale (PANSS), the Simpson Angus Scale (SAS) were performed weekly. 43 patients completed 4 weeks of assessment. Scores on all of the dimensions improved. By the end of week 1, only positive syndrome, thought disturbance and paranoid-belligerence dimensions improved. Maximum improvement was seen with paranoid-belligerence by week 1, followed by positive syndrome in week 2, and depression at week 3. The percentage improvement in positive syndrome was significantly greater than negative. Over 4 weeks there was a mean weight gain of 2kg and there were significant extrapyramidal symptoms. Olanzapine produced reduction in all dimensions, but the pace of responding of individual dimensions differed. Longer-term studies comparing SGAs with first generation antipsychotics are needed. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of Proportional Integral and Optimized Proportional Integral Controllers for Resistance Spot Welding System (RSWS) - A Performance Perspective

NASA Astrophysics Data System (ADS)

Rama Subbanna, S.; Suryakalavathi, M., Dr.

2017-08-01

This paper is an attempt to accomplish a performance analysis of the different control techniques on spikes reduction method applied on the medium frequency transformer based DC spot welding system. Spike reduction is an important factor to be considered while spot welding systems are concerned. During normal RSWS operation welding transformer’s magnetic core can become saturated due to the unbalanced resistances of both transformer secondary windings and different characteristics of output rectifier diodes, which causes current spikes and over-current protection switch-off of the entire system. The current control technique is a piecewise linear control technique that is inspired from the DC-DC converter control algorithms to register a novel spike reduction method in the MFDC spot welding applications. Two controllers that were used for the spike reduction portion of the overall applications involve the traditional PI controller and Optimized PI controller. Care is taken such that the current control technique would maintain a reduced spikes in the primary current of the transformer while it reduces the Total Harmonic Distortion. The performance parameter that is involved in the spikes reduction technique is the THD, Percentage of current spike reduction for both techniques. Matlab/SimulinkTM based simulation is carried out for the MFDC RSWS with KW and results are tabulated for the PI and Optimized PI controllers and a tradeoff analysis is carried out.

[Balloon osteoplasty as reduction technique in the treatment of tibial head fractures].

PubMed

Freude, T; Kraus, T M; Sandmann, G H

2015-10-01

Tibial plateau fractures requiring surgery are severe injuries of the lower extremities. Depending on the fracture pattern, the age of the patient, the range of activity and the bone quality there is a broad variation in adequate treatment.  This article reports on an innovative treatment concept to address split depression fractures (Schatzker type II) and depression fractures (Schatzker type III) of the tibial head using the balloon osteoplasty technique for fracture reduction. Using the balloon technique achieves a precise and safe fracture reduction. This internal osteoplasty combines a minimal invasive percutaneous approach with a gently rise of the depressed area and the associated protection of the stratum regenerativum below the articular cartilage surface. This article lights up the surgical procedure using the balloon technique in tibia depression fractures. Using the balloon technique a precise and safe fracture reduction can be achieved. This internal osteoplasty combines a minimally invasive percutaneous approach with a gentle raising of the depressed area and the associated protection of the regenerative layer below the articular cartilage surface. Fracture reduction by use of a tamper results in high peak forces over small areas, whereas by using the balloon the forces are distributed over a larger area causing less secondary stress to the cartilage tissue. This less invasive approach might help to achieve a better long-term outcome with decreased secondary osteoarthritis due to the precise and chondroprotective reduction technique.

Perception Expansion Training: An Approach to Conflict Reduction.

ERIC Educational Resources Information Center

Huseman, Richard C.

Interpersonal conflict in organizations is due to differences in perception of organizational sub-group systems operations. Such conflict can be reduced through implementation of "PET," perception expansion training. PET procedures will determine the dimensions of conflict situations and bring into play interacting group therapy which expands the…

Chaos and Robustness in a Single Family of Genetic Oscillatory Networks

PubMed Central

Fu, Daniel; Tan, Patrick; Kuznetsov, Alexey; Molkov, Yaroslav I.

2014-01-01

Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with delay. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows the range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with highly-regular periods likely have solely negative feedback. PMID:24667178

Density matrix renormalization group study of a three-orbital Hubbard model with spin-orbit coupling in one dimension

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

Kaushal, Nitin; Herbrych, Jacek W.; Nocera, Alberto

Using the density matrix renormalization group technique we study the effect of spin-orbit coupling on a three-orbital Hubbard model in the (t 2g) 4 sector and in one dimension. Fixing the Hund coupling to a robust value compatible with some multiorbital materials, we present the phase diagram varying the Hubbard U and spin-orbit coupling λ, at zero temperature. Our results are shown to be qualitatively similar to those recently reported using the dynamical mean-field theory in higher dimensions, providing a robust basis to approximate many-body techniques. Among many results, we observe an interesting transition from an orbital-selective Mott phase tomore » an excitonic insulator with increasing λ at intermediate U. In the strong U coupling limit, we find a nonmagnetic insulator with an effective angular momentum <(J eff) 2>≠0 near the excitonic phase, smoothly connected to the <(J eff) 2>=0 regime. In conclusion, we also provide a list of quasi-one-dimensional materials where the physics discussed in this paper could be realized.« less

Density matrix renormalization group study of a three-orbital Hubbard model with spin-orbit coupling in one dimension

NASA Astrophysics Data System (ADS)

Kaushal, Nitin; Herbrych, Jacek; Nocera, Alberto; Alvarez, Gonzalo; Moreo, Adriana; Reboredo, F. A.; Dagotto, Elbio

2017-10-01

Using the density matrix renormalization group technique we study the effect of spin-orbit coupling on a three-orbital Hubbard model in the (t2g) 4 sector and in one dimension. Fixing the Hund coupling to a robust value compatible with some multiorbital materials, we present the phase diagram varying the Hubbard U and spin-orbit coupling λ , at zero temperature. Our results are shown to be qualitatively similar to those recently reported using the dynamical mean-field theory in higher dimensions, providing a robust basis to approximate many-body techniques. Among many results, we observe an interesting transition from an orbital-selective Mott phase to an excitonic insulator with increasing λ at intermediate U . In the strong U coupling limit, we find a nonmagnetic insulator with an effective angular momentum 〈(Jeff)2〉≠0 near the excitonic phase, smoothly connected to the 〈(Jeff)2〉=0 regime. We also provide a list of quasi-one-dimensional materials where the physics discussed in this paper could be realized.

Density matrix renormalization group study of a three-orbital Hubbard model with spin-orbit coupling in one dimension

DOE PAGES

Kaushal, Nitin; Herbrych, Jacek W.; Nocera, Alberto; ...

2017-10-09

Using the density matrix renormalization group technique we study the effect of spin-orbit coupling on a three-orbital Hubbard model in the (t 2g) 4 sector and in one dimension. Fixing the Hund coupling to a robust value compatible with some multiorbital materials, we present the phase diagram varying the Hubbard U and spin-orbit coupling λ, at zero temperature. Our results are shown to be qualitatively similar to those recently reported using the dynamical mean-field theory in higher dimensions, providing a robust basis to approximate many-body techniques. Among many results, we observe an interesting transition from an orbital-selective Mott phase tomore » an excitonic insulator with increasing λ at intermediate U. In the strong U coupling limit, we find a nonmagnetic insulator with an effective angular momentum <(J eff) 2>≠0 near the excitonic phase, smoothly connected to the <(J eff) 2>=0 regime. In conclusion, we also provide a list of quasi-one-dimensional materials where the physics discussed in this paper could be realized.« less

Damage characterization in dimension limestone cladding using noncollinear ultrasonic wave mixing

NASA Astrophysics Data System (ADS)

McGovern, Megan; Reis, Henrique

2016-01-01

A method capable of characterizing artificial weathering damage in dimension stone cladding using access to one side only is presented. Dolomitic limestone test samples with increasing levels of damage were created artificially by exposing undamaged samples to increasing temperature levels of 100°C, 200°C, 300°C, 400°C, 500°C, 600°C, and 700°C for a 90 min period of time. Using access to one side only, these test samples were nondestructively evaluated using a nonlinear approach based upon noncollinear wave mixing, which involves mixing two critically refracted dilatational ultrasonic waves. Criteria were used to assure that the detected scattered wave originated via wave interaction in the limestone and not from nonlinearities in the testing equipment. Bending tests were used to evaluate the flexure strength of beam samples extracted from the artificially weathered samples. It was observed that the percentage of strength reduction is linearly correlated (R2=98) with the temperature to which the specimens were exposed; it was noted that samples exposed to 400°C and 600°C had a strength reduction of 60% and 90%, respectively. It was also observed that results from the noncollinear wave mixing approach correlated well (R2=0.98) with the destructively obtained percentage of strength reduction.

Simultaneous fabrication of very high aspect ratio positive nano- to milliscale structures.

PubMed

Chen, Long Qing; Chan-Park, Mary B; Zhang, Qing; Chen, Peng; Li, Chang Ming; Li, Sai

2009-05-01

A simple and inexpensive technique for the simultaneous fabrication of positive (i.e., protruding), very high aspect (>10) ratio nanostructures together with micro- or millistructures is developed. The method involves using residual patterns of thin-film over-etching (RPTO) to produce sub-micro-/nanoscale features. The residual thin-film nanopattern is used as an etching mask for Si deep reactive ion etching. The etched Si structures are further reduced in size by Si thermal oxidation to produce amorphous SiO(2), which is subsequently etched away by HF. Two arrays of positive Si nanowalls are demonstrated with this combined RPTO-SiO(2)-HF technique. One array has a feature size of 150 nm and an aspect ratio of 26.7 and another has a feature size of 50 nm and an aspect ratio of 15. No other parallel reduction technique can achieve such a very high aspect ratio for 50-nm-wide nanowalls. As a demonstration of the technique to simultaneously achieve nano- and milliscale features, a simple Si nanofluidic master mold with positive features with dimensions varying continuously from 1 mm to 200 nm and a highest aspect ratio of 6.75 is fabricated; the narrow 200-nm section is 4.5 mm long. This Si master mold is then used as a mold for UV embossing. The embossed open channels are then closed by a cover with glue bonding. A high aspect ratio is necessary to produce unblocked closed channels after the cover bonding process of the nanofluidic chip. The combined method of RPTO, Si thermal oxidation, and HF etching can be used to make complex nanofluidic systems and nano-/micro-/millistructures for diverse applications.

Surgical Navigation Technology Based on Augmented Reality and Integrated 3D Intraoperative Imaging: A Spine Cadaveric Feasibility and Accuracy Study.

PubMed

Elmi-Terander, Adrian; Skulason, Halldor; Söderman, Michael; Racadio, John; Homan, Robert; Babic, Drazenko; van der Vaart, Nijs; Nachabe, Rami

2016-11-01

A cadaveric laboratory study. The aim of this study was to assess the feasibility and accuracy of thoracic pedicle screw placement using augmented reality surgical navigation (ARSN). Recent advances in spinal navigation have shown improved accuracy in lumbosacral pedicle screw placement but limited benefits in the thoracic spine. 3D intraoperative imaging and instrument navigation may allow improved accuracy in pedicle screw placement, without the use of x-ray fluoroscopy, and thus opens the route to image-guided minimally invasive therapy in the thoracic spine. ARSN encompasses a surgical table, a motorized flat detector C-arm with intraoperative 2D/3D capabilities, integrated optical cameras for augmented reality navigation, and noninvasive patient motion tracking. Two neurosurgeons placed 94 pedicle screws in the thoracic spine of four cadavers using ARSN on one side of the spine (47 screws) and free-hand technique on the contralateral side. X-ray fluoroscopy was not used for either technique. Four independent reviewers assessed the postoperative scans, using the Gertzbein grading. Morphometric measurements of the pedicles axial and sagittal widths and angles, as well as the vertebrae axial and sagittal rotations were performed to identify risk factors for breaches. ARSN was feasible and superior to free-hand technique with respect to overall accuracy (85% vs. 64%, P < 0.05), specifically significant increases of perfectly placed screws (51% vs. 30%, P < 0.05) and reductions in breaches beyond 4 mm (2% vs. 25%, P < 0.05). All morphometric dimensions, except for vertebral body axial rotation, were risk factors for larger breaches when performed with the free-hand method. ARSN without fluoroscopy was feasible and demonstrated higher accuracy than free-hand technique for thoracic pedicle screw placement. N/A.

ND 2 AV: N-dimensional data analysis and visualization analysis for the National Ignition Campaign

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

Bremer, Peer -Timo; Maljovec, Dan; Saha, Avishek

Here, one of the biggest challenges in high-energy physics is to analyze a complex mix of experimental and simulation data to gain new insights into the underlying physics. Currently, this analysis relies primarily on the intuition of trained experts often using nothing more sophisticated than default scatter plots. Many advanced analysis techniques are not easily accessible to scientists and not flexible enough to explore the potentially interesting hypotheses in an intuitive manner. Furthermore, results from individual techniques are often difficult to integrate, leading to a confusing patchwork of analysis snippets too cumbersome for data exploration. This paper presents a case study on how a combination of techniques from statistics, machine learning, topology, and visualization can have a significant impact in the field of inertial confinement fusion. We present themore » $$\\mathrm{ND}^2\\mathrm{AV}$$: N-dimensional data analysis and visualization framework, a user-friendly tool aimed at exploiting the intuition and current workflow of the target users. The system integrates traditional analysis approaches such as dimension reduction and clustering with state-of-the-art techniques such as neighborhood graphs and topological analysis, and custom capabilities such as defining combined metrics on the fly. All components are linked into an interactive environment that enables an intuitive exploration of a wide variety of hypotheses while relating the results to concepts familiar to the users, such as scatter plots. $$\\mathrm{ND}^2\\mathrm{AV}$$ uses a modular design providing easy extensibility and customization for different applications. $$\\mathrm{ND}^2\\mathrm{AV}$$ is being actively used in the National Ignition Campaign and has already led to a number of unexpected discoveries.« less

ND 2 AV: N-dimensional data analysis and visualization analysis for the National Ignition Campaign

DOE PAGES

Bremer, Peer -Timo; Maljovec, Dan; Saha, Avishek; ...

2015-07-01

Here, one of the biggest challenges in high-energy physics is to analyze a complex mix of experimental and simulation data to gain new insights into the underlying physics. Currently, this analysis relies primarily on the intuition of trained experts often using nothing more sophisticated than default scatter plots. Many advanced analysis techniques are not easily accessible to scientists and not flexible enough to explore the potentially interesting hypotheses in an intuitive manner. Furthermore, results from individual techniques are often difficult to integrate, leading to a confusing patchwork of analysis snippets too cumbersome for data exploration. This paper presents a case study on how a combination of techniques from statistics, machine learning, topology, and visualization can have a significant impact in the field of inertial confinement fusion. We present themore » $$\\mathrm{ND}^2\\mathrm{AV}$$: N-dimensional data analysis and visualization framework, a user-friendly tool aimed at exploiting the intuition and current workflow of the target users. The system integrates traditional analysis approaches such as dimension reduction and clustering with state-of-the-art techniques such as neighborhood graphs and topological analysis, and custom capabilities such as defining combined metrics on the fly. All components are linked into an interactive environment that enables an intuitive exploration of a wide variety of hypotheses while relating the results to concepts familiar to the users, such as scatter plots. $$\\mathrm{ND}^2\\mathrm{AV}$$ uses a modular design providing easy extensibility and customization for different applications. $$\\mathrm{ND}^2\\mathrm{AV}$$ is being actively used in the National Ignition Campaign and has already led to a number of unexpected discoveries.« less

Accuracy of a reformulated fast-set vinyl polysiloxane impression material using dual-arch trays.

PubMed

Kang, Alex H; Johnson, Glen H; Lepe, Xavier; Wataha, John C

2009-05-01

A common technique used for making crown impressions involves use of a vinyl polysiloxane impression material in combination with a dual-arch tray. A leading dental manufacturer has reformulated its vinyl polysiloxane (VPS) impression line, but the accuracy of the new material has not been verified. The purpose of this study was to assess the accuracy of reformulated VPS impression materials using the single-step dual-arch impression technique. Dual-arch impressions were made on a typodont containing a master stainless steel standard crown preparation die, from which gypsum working dies were formed, recovered, and measured. The impression materials evaluated were Imprint 3 Penta Putty with Quick Step Regular Body (IP-0); Imprint 3 Penta Quick Step Heavy Body with Quick Step Light Body (IP-1); Aquasil Ultra Rigid Fast Set with LV Fast Set (AQ-1); and Aquasil Ultra Heavy Fast Set with XLV Fast Set (AQ-2) (n=10). All impressions were disinfected with CaviCide spray for 10 minutes prior to pouring with type IV gypsum. Buccolingual (BL), mesiodistal (MD), and occlusogingival (OG) dimensions were measured and compared to the master die using an optical measuring microscope. Linear dimensional change was also assessed for IP-0 and AQ-1 at 1 and 24 hours based on ANSI/ADA Specification No. 19. Single-factor ANOVA with Dunnett's T3 multiple comparisons was used to compare BL, MD, and OG changes, with hypothesis testing at alpha=.05. A repeated-measures ANOVA was used to compare linear dimensional changes. There were statistical differences among the 4 impression systems for 3 of 4 dimensions of the master die. IP-0 working dies were significantly larger in MD and OG-L dimensions but significantly smaller in the BL dimension. IP-1 working dies were significantly smaller in the BL dimension compared to the master die. With the exception of IP-0, differences detected were small and clinically insignificant. No significant differences were observed for linear dimensional change. The single-step dual-arch impression technique produced working dies that were smaller in 3 of the 4 dimensions measured and may require additional die relief to achieve appropriate fit of cast restorations. Overall accuracy was acceptable for all impression groups with the exception of IP-0.

Technique for systematic bone reduction for fixed implant-supported prosthesis in the edentulous maxilla.

PubMed

Bidra, Avinash S

2015-06-01

Bone reduction for maxillary fixed implant-supported prosthodontic treatment is often necessary to either gain prosthetic space or to conceal the prosthesis-tissue junction in patients with excessive gingival display (gummy smile). Inadequate bone reduction is often a cause of prosthetic failure due to material fractures, poor esthetics, or inability to perform oral hygiene procedures due to unfavorable ridge lap prosthetic contours. Various instruments and techniques are available for bone reduction. It would be helpful to have an accurate and efficient method for bone reduction at the time of surgery and subsequently create a smooth bony platform. This article presents a straightforward technique for systematic bone reduction by transferring the patient's maximum smile line, recorded clinically, to a clear radiographic smile guide for treatment planning using cone beam computed tomography (CBCT). The patient's smile line and the amount of required bone reduction are transferred clinically by marking bone with a sterile stationery graphite wood pencil at the time of surgery. This technique can help clinicians to accurately achieve the desired bone reduction during surgery, and provide confidence that the diagnostic and treatment planning goals have been achieved. Copyright © 2015 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

A Comparative Evaluation of the Linear Dimensional Accuracy of Four Impression Techniques using Polyether Impression Material.

PubMed

Manoj, Smita Sara; Cherian, K P; Chitre, Vidya; Aras, Meena

2013-12-01

There is much discussion in the dental literature regarding the superiority of one impression technique over the other using addition silicone impression material. However, there is inadequate information available on the accuracy of different impression techniques using polyether. The purpose of this study was to assess the linear dimensional accuracy of four impression techniques using polyether on a laboratory model that simulates clinical practice. The impression material used was Impregum Soft™, 3 M ESPE and the four impression techniques used were (1) Monophase impression technique using medium body impression material. (2) One step double mix impression technique using heavy body and light body impression materials simultaneously. (3) Two step double mix impression technique using a cellophane spacer (heavy body material used as a preliminary impression to create a wash space with a cellophane spacer, followed by the use of light body material). (4) Matrix impression using a matrix of polyether occlusal registration material. The matrix is loaded with heavy body material followed by a pick-up impression in medium body material. For each technique, thirty impressions were made of a stainless steel master model that contained three complete crown abutment preparations, which were used as the positive control. Accuracy was assessed by measuring eight dimensions (mesiodistal, faciolingual and inter-abutment) on stone dies poured from impressions of the master model. A two-tailed t test was carried out to test the significance in difference of the distances between the master model and the stone models. One way analysis of variance (ANOVA) was used for multiple group comparison followed by the Bonferroni's test for pair wise comparison. The accuracy was tested at α = 0.05. In general, polyether impression material produced stone dies that were smaller except for the dies produced from the one step double mix impression technique. The ANOVA revealed a highly significant difference for each dimension measured (except for the inter-abutment distance between the first and the second die) between any two groups of stone models obtained from the four impression techniques. Pair wise comparison for each measurement did not reveal any significant difference (except for the faciolingual distance of the third die) between the casts produced using the two step double mix impression technique and the matrix impression system. The two step double mix impression technique produced stone dies that showed the least dimensional variation. During fabrication of a cast restoration, laboratory procedures should not only compensate for the cement thickness, but also for the increase or decrease in die dimensions.

Strain Gauge Balance Calibration and Data Reduction at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Ferris, A. T. Judy

1999-01-01

This paper will cover the standard force balance calibration and data reduction techniques used at Langley Research Center. It will cover balance axes definition, balance type, calibration instrumentation, traceability of standards to NIST, calibration loading procedures, balance calibration mathematical model, calibration data reduction techniques, balance accuracy reporting, and calibration frequency.

Recreational music-making: a cost-effective group interdisciplinary strategy for reducing burnout and improving mood states in long-term care workers.

PubMed

Bittman, Barry; Bruhn, Karl T; Stevens, Christine; Westengard, James; Umbach, Paul O

2003-01-01

This controlled, prospective, randomized study examined the clinical and potential economic impact of a 6-session Recreational Music-making (RMM) protocol on burnout and mood dimensions, as well as on Total Mood Disturbance (TMD) in an interdisciplinary group of long-term care workers. A total of 112 employees participated in a 6-session RMM protocol focusing on building support, communication, and interdisciplinary respect utilizing group drumming and keyboard accompaniment. Changes in burnout and mood dimensions were assessed with the Maslach Burnout Inventory and the Profile of Mood States respectively. Cost savings were projected by an independent consulting firm, which developed an economic impact model. Statistically-significant reductions of multiple burnout and mood dimensions, as well as TMD scores, were noted. Economic-impact analysis projected cost savings of $89,100 for a single typical 100-bed facility, with total annual potential savings to the long-term care industry of $1.46 billion. A cost-effective, 6-session RMM protocol reduces burnout and mood dimensions, as well as TMD, in long-term care workers.

Phases and stability of non-uniform black strings

NASA Astrophysics Data System (ADS)

Emparan, Roberto; Luna, Raimon; Martínez, Marina; Suzuki, Ryotaku; Tanabe, Kentaro

2018-05-01

We construct solutions of non-uniform black strings in dimensions from D ≈ 9 all the way up to D = ∞, and investigate their thermodynamics and dynamical stability. Our approach employs the large- D perturbative expansion beyond the leading order, including corrections up to 1 /D 4. Combining both analytical techniques and relatively simple numerical solution of ODEs, we map out the ranges of parameters in which non-uniform black strings exist in each dimension and compute their thermodynamics and quasinormal modes with accuracy. We establish with very good precision the existence of Sorkin's critical dimension and we prove that not only the thermodynamic stability, but also the dynamic stability of the solutions changes at it.

Lyapunov dimension formula for the global attractor of the Lorenz system

NASA Astrophysics Data System (ADS)

Leonov, G. A.; Kuznetsov, N. V.; Korzhemanova, N. A.; Kusakin, D. V.

2016-12-01

The exact Lyapunov dimension formula for the Lorenz system for a positive measure set of parameters, including classical values, was analytically obtained first by G.A. Leonov in 2002. Leonov used the construction technique of special Lyapunov-type functions, which was developed by him in 1991 year. Later it was shown that the consideration of larger class of Lyapunov-type functions permits proving the validity of this formula for all parameters, of the system, such that all the equilibria of the system are hyperbolically unstable. In the present work it is proved the validity of the formula for Lyapunov dimension for a wider variety of parameters values including all parameters, which satisfy the classical physical limitations.

[From fundamental research to clinical development: a review of orthodontics].

PubMed

Zhao, Zhi-he; Bai, Ding

2011-11-01

In recent years, new approaches to the diagnosis and treatment of malocclusion have emerged. The diagnostic and therapeutic techniques of orthodontics have evolved from two dimensions to five dimensions with the development of computer technology, auto-machining and imaging. Furthermore, interdisciplinary study has become the driving force for the advancement of fundamental research in orthodontics. The mechanisms of malocclusion and orthodontic tooth movement have been extensively studied to the details at the level of cells and molecules.

Tools and Techniques for Adding Fault Tolerance to Distributed and Parallel Programs

DTIC Science & Technology

1991-12-07

is rapidly approaching dimensions where fault tolerance can no longer be ignored. No matter how reliable the i .nd~ividual components May be, the...The scale of parallel computing systems is rapidly approaching dimensions where 41to’- erance can no longer be ignored. No matter how relitble the...those employed in the Tandem [71 and Stratus [35] systems, is clearly impractical. * No matter how reliable the individual components are, the sheer

An approach to enhance pnetCDF performance in ...

EPA Pesticide Factsheets

Data intensive simulations are often limited by their I/O (input/output) performance, and "novel" techniques need to be developed in order to overcome this limitation. The software package pnetCDF (parallel network Common Data Form), which works with parallel file systems, was developed to address this issue by providing parallel I/O capability. This study examines the performance of an application-level data aggregation approach which performs data aggregation along either row or column dimension of MPI (Message Passing Interface) processes on a spatially decomposed domain, and then applies the pnetCDF parallel I/O paradigm. The test was done with three different domain sizes which represent small, moderately large, and large data domains, using a small-scale Community Multiscale Air Quality model (CMAQ) mock-up code. The examination includes comparing I/O performance with traditional serial I/O technique, straight application of pnetCDF, and the data aggregation along row and column dimension before applying pnetCDF. After the comparison, "optimal" I/O configurations of this application-level data aggregation approach were quantified. Data aggregation along the row dimension (pnetCDFcr) works better than along the column dimension (pnetCDFcc) although it may perform slightly worse than the straight pnetCDF method with a small number of processors. When the number of processors becomes larger, pnetCDFcr outperforms pnetCDF significantly. If the number of proces

Sizing Single Cantilever Beam Specimens for Characterizing Facesheet/Core Peel Debonding in Sandwich Structure

NASA Technical Reports Server (NTRS)

Ratcliffe, James G.

2010-01-01

This paper details part of an effort focused on the development of a standardized facesheet/core peel debonding test procedure. The purpose of the test is to characterize facesheet/core peel in sandwich structure, accomplished through the measurement of the critical strain energy release rate associated with the debonding process. The specific test method selected for the standardized test procedure utilizes a single cantilever beam (SCB) specimen configuration. The objective of the current work is to develop a method for establishing SCB specimen dimensions. This is achieved by imposing specific limitations on specimen dimensions, with the objectives of promoting a linear elastic specimen response, and simplifying the data reduction method required for computing the critical strain energy release rate associated with debonding. The sizing method is also designed to be suitable for incorporation into a standardized test protocol. Preliminary application of the resulting sizing method yields practical specimen dimensions.

Generalised Eisenhart lift of the Toda chain

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

Cariglia, Marco, E-mail: marco@iceb.ufop.br; Gibbons, Gary, E-mail: g.w.gibbons@damtp.cam.ac.uk

The Toda chain of nearest neighbour interacting particles on a line can be described both in terms of geodesic motion on a manifold with one extra dimension, the Eisenhart lift, or in terms of geodesic motion in a symmetric space with several extra dimensions. We examine the relationship between these two realisations and discover that the symmetric space is a generalised, multi-particle Eisenhart lift of the original problem that reduces to the standard Eisenhart lift. Such generalised Eisenhart lift acts as an inverse Kaluza-Klein reduction, promoting coupling constants to momenta in higher dimension. In particular, isometries of the generalised liftmore » metric correspond to energy preserving transformations that mix coordinates and coupling constants. A by-product of the analysis is that the lift of the Toda Lax pair can be used to construct higher rank Killing tensors for both the standard and generalised lift metrics.« less

Inter-correlations between Cloninger's temperament dimensions-- a meta-analysis.

PubMed

Miettunen, Jouko; Lauronen, Erika; Kantojärvi, Liisa; Veijola, Juha; Joukamaa, Matti

2008-07-15

The Temperament and Character Inventory (TCI) was developed to measure the following temperament dimensions: novelty seeking (NS), harm avoidance (HA), reward dependence (RD) and persistence (P). These four dimensions of temperament were originally proposed to be independent of one another. In this study the inter-relationships between the dimensions were studied with meta-analytic techniques. We also studied the effects of sociodemographic factors (location of the study, mean age and gender distribution) on correlations between temperament dimensions. We searched studies on healthy (non-clinical) populations that used the TCI (version 9), and that had a required sample size of at least 100. The search resulted in 16 articles. The resulted pooled correlation coefficient was medium level between NS and HA (-0.27). Correlations were small for HA-P (-0.20), NS-P (-0.14), NS-RD (0.10), RD-P (0.05) and HA-RD (0.04). In meta-regression, the correlation NS-P was significantly affected by the location of the study (Asian/other) and by the gender distribution of the sample. In the HA-P correlation, the mean age of the sample affected the correlation. In conclusion, we found a medium level negative correlation between NS and HA; other correlations between the dimensions were small. These findings mainly support Cloninger's theory of independent dimensions.

Fractal analysis as a potential tool for surface morphology of thin films

NASA Astrophysics Data System (ADS)

Soumya, S.; Swapna, M. S.; Raj, Vimal; Mahadevan Pillai, V. P.; Sankararaman, S.

2017-12-01

Fractal geometry developed by Mandelbrot has emerged as a potential tool for analyzing complex systems in the diversified fields of science, social science, and technology. Self-similar objects having the same details in different scales are referred to as fractals and are analyzed using the mathematics of non-Euclidean geometry. The present work is an attempt to correlate fractal dimension for surface characterization by Atomic Force Microscopy (AFM). Taking the AFM images of zinc sulphide (ZnS) thin films prepared by pulsed laser deposition (PLD) technique, under different annealing temperatures, the effect of annealing temperature and surface roughness on fractal dimension is studied. The annealing temperature and surface roughness show a strong correlation with fractal dimension. From the regression equation set, the surface roughness at a given annealing temperature can be calculated from the fractal dimension. The AFM images are processed using Photoshop and fractal dimension is calculated by box-counting method. The fractal dimension decreases from 1.986 to 1.633 while the surface roughness increases from 1.110 to 3.427, for a change of annealing temperature 30 ° C to 600 ° C. The images are also analyzed by power spectrum method to find the fractal dimension. The study reveals that the box-counting method gives better results compared to the power spectrum method.

Counselling for burnout in Norwegian doctors: one year cohort study.

PubMed

Rø, Karin E Isaksson; Gude, Tore; Tyssen, Reidar; Aasland, Olaf G

2008-11-11

To investigate levels and predictors of change in dimensions of burnout after an intervention for stressed doctors. Cohort study followed by self reported assessment at one year. Norwegian resource centre. 227 doctors participating in counselling intervention, 2003-5. Counselling (lasting one day (individual) or one week (group based)) aimed at motivating reflection on and acknowledgement of the doctors' situation and personal needs. Levels of burnout (Maslach burnout inventory) and predictors of reduction in emotional exhaustion investigated by linear regression. 185 doctors (81%, 88 men, 97 women) completed one year follow-up. The mean level of emotional exhaustion (scale 1-5) was significantly reduced from 3.00 (SD 0.94) to 2.53 (SD 0.76) (t=6.76, P<0.001), similar to the level found in a representative sample of 390 Norwegian doctors. Participants had reduced their working hours by 1.6 hours/week (SD 11.4). There was a considerable reduction in the proportion of doctors on full time sick leave, from 35% (63/182) at baseline to 6% (10/182) at follow-up and a parallel increase in the proportion who had undergone psychotherapy, from 20% (36/182) to 53% (97/182). In the whole cohort, reduction in emotional exhaustion was independently associated with reduced number of work hours/week (beta=0.17, P=0.03), adjusted for sex, age, and personality dimensions. Among men "satisfaction with the intervention" (beta=0.25, P=0.04) independently predicted reduction in emotional exhaustion. A short term counselling intervention could contribute to reduction in emotional exhaustion in doctors. This was associated with reduced working hours for the whole cohort and, in men, was predicted by satisfaction with the intervention.

Sparse Representation Based Classification with Structure Preserving Dimension Reduction

DTIC Science & Technology

2014-03-13

dictionary learning [39] used stochastic approximations to update dictionary with a large data set. Laplacian score dictionary ( LSD ) [58], which is based on...vol. 4. 2003. p. 864–7. 47. Shaw B, Jebara T. Structure preserving embedding. In: The 26th annual international conference on machine learning, ICML

The Multiplicative Zak Transform, Dimension Reduction, and Wavelet Analysis of LIDAR Data

DTIC Science & Technology

2010-01-01

systems is likely to fail. Auslander, Eichmann , Gertner, and Tolimieri defined a multiplicative Zak transform [1], mimicking the construction of the Gabor...L. Auslander, G. Eichmann , I. Gertner and R. Tolimieri, “Time-Frequency Analysis and Synthesis of Non-Stationary Signals,” Proc. Soc. Photo-Opt. In

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

Baguet, A.; Pope, Christopher N.; Samtleben, H.

We prove an old conjecture by Duff, Nilsson, Pope and Warner asserting that the NSNS sector of supergravity (and more general the bosonic string) allows for a consistent Pauli reduction on any d-dimensional group manifold G, keeping the full set of gauge bosons of the G×G isometry group of the bi-invariant metric on G. The main tool of the construction is a particular generalised Scherk–Schwarz reduction ansatz in double field theory which we explicitly construct in terms of the group's Killing vectors. Examples include the consistent reduction from ten dimensions on S3×S3 and on similar product spaces. The construction ismore » another example of globally geometric non-toroidal compactifications inducing non-geometric fluxes.« less

Height-selective etching for regrowth of self-aligned contacts using MBE

NASA Astrophysics Data System (ADS)

Burek, G. J.; Wistey, M. A.; Singisetti, U.; Nelson, A.; Thibeault, B. J.; Bank, S. R.; Rodwell, M. J. W.; Gossard, A. C.

2009-03-01

Advanced III-V transistors require unprecedented low-resistance contacts in order to simultaneously scale bandwidth, fmax and ft with the physical active region [M.J.W. Rodwell, M. Le, B. Brar, in: Proceedings of the IEEE, 96, 2008, p. 748]. Low-resistance contacts have been previously demonstrated using molecular beam epitaxy (MBE), which provides active doping above 4×10 19 cm -3 and permits in-situ metal deposition for the lowest resistances [U. Singisetti, M.A. Wistey, J.D. Zimmerman, B.J. Thibeault, M.J.W. Rodwell, A.C. Gossard, S.R. Bank, Appl. Phys. Lett., submitted]. But MBE is a blanket deposition technique, and applying MBE regrowth to deep-submicron lateral device dimensions is difficult even with advanced lithography techniques. We present a simple method for selectively etching undesired regrowth from the gate or mesa of a III-V MOSFET or laser, resulting in self-aligned source/drain contacts regardless of the device dimensions. This turns MBE into an effectively selective area growth technique.

Contour metrology using critical dimension atomic force microscopy

NASA Astrophysics Data System (ADS)

Orji, Ndubuisi G.; Dixson, Ronald G.; Vladár, András E.; Ming, Bin; Postek, Michael T.

2012-03-01

The critical dimension atomic force microscope (CD-AFM), which is used as a reference instrument in lithography metrology, has been proposed as a complementary instrument for contour measurement and verification. Although data from CD-AFM is inherently three dimensional, the planar two-dimensional data required for contour metrology is not easily extracted from the top-down CD-AFM data. This is largely due to the limitations of the CD-AFM method for controlling the tip position and scanning. We describe scanning techniques and profile extraction methods to obtain contours from CD-AFM data. We also describe how we validated our technique, and explain some of its limitations. Potential sources of error for this approach are described, and a rigorous uncertainty model is presented. Our objective is to show which data acquisition and analysis methods could yield optimum contour information while preserving some of the strengths of CD-AFM metrology. We present comparison of contours extracted using our technique to those obtained from the scanning electron microscope (SEM), and the helium ion microscope (HIM).

Rapid prototyping of nanofluidic systems using size-reduced electrospun nanofibers for biomolecular analysis.

PubMed

Park, Seung-Min; Huh, Yun Suk; Szeto, Kylan; Joe, Daniel J; Kameoka, Jun; Coates, Geoffrey W; Edel, Joshua B; Erickson, David; Craighead, Harold G

2010-11-05

Biomolecular transport in nanofluidic confinement offers various means to investigate the behavior of biomolecules in their native aqueous environments, and to develop tools for diverse single-molecule manipulations. Recently, a number of simple nanofluidic fabrication techniques has been demonstrated that utilize electrospun nanofibers as a backbone structure. These techniques are limited by the arbitrary dimension of the resulting nanochannels due to the random nature of electrospinning. Here, a new method for fabricating nanofluidic systems from size-reduced electrospun nanofibers is reported and demonstrated. As it is demonstrated, this method uses the scanned electrospinning technique for generation of oriented sacrificial nanofibers and exposes these nanofibers to harsh, but isotropic etching/heating environments to reduce their cross-sectional dimension. The creation of various nanofluidic systems as small as 20 nm is demonstrated, and practical examples of single biomolecular handling, such as DNA elongation in nanochannels and fluorescence correlation spectroscopic analysis of biomolecules passing through nanochannels, are provided.

A Diagnostic Technique for Formulating Market Strategies in Higher Education Based on Relative Competitive Position.

ERIC Educational Resources Information Center

Dolinsky, Arthur L.; Quazi, Hesan A.

1994-01-01

Importance-performance analysis, a marketing research technique using analysis of consumer attitudes toward salient product or service attributes, is found useful for colleges and universities in developing marketing strategies, particularly when competition is considered as an important dimension. Data are drawn from a survey of 252 students at 1…

[Principles of MR-guided interventions, surgery, navigation, and robotics].

PubMed

Melzer, A

2010-08-01

The application of magnetic resonance imaging (MRI) as an imaging technique in interventional and surgical techniques provides a new dimension of soft tissue-oriented precise procedures without exposure to ionizing radiation and nephrotoxic allergenic, iodine-containing contrast agents. The technical capabilities of MRI in combination with interventional devices and systems, navigation, and robotics are discussed.

A Comparison of Local Variance, Fractal Dimension, and Moran's I as Aids to Multispectral Image Classification

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Sig-NganLam, Nina; Quattrochi, Dale A.

2004-01-01

The accuracy of traditional multispectral maximum-likelihood image classification is limited by the skewed statistical distributions of reflectances from the complex heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze Landsat 7 imagery of Atlanta, Georgia. Although segmentation of panchromatic images is possible using indicators of spatial complexity, different land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification. The addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Toward theoretical understanding of the fertility preservation decision-making process: examining information processing among young women with cancer.

PubMed

Hershberger, Patricia E; Finnegan, Lorna; Altfeld, Susan; Lake, Sara; Hirshfeld-Cytron, Jennifer

2013-01-01

Young women with cancer now face the complex decision about whether to undergo fertility preservation. Yet little is known about how these women process information involved in making this decision. The purpose of this article is to expand theoretical understanding of the decision-making process by examining aspects of information processing among young women diagnosed with cancer. Using a grounded theory approach, 27 women with cancer participated in individual, semistructured interviews. Data were coded and analyzed using constant-comparison techniques that were guided by 5 dimensions within the Contemplate phase of the decision-making process framework. In the first dimension, young women acquired information primarily from clinicians and Internet sources. Experiential information, often obtained from peers, occurred in the second dimension. Preferences and values were constructed in the third dimension as women acquired factual, moral, and ethical information. Women desired tailored, personalized information that was specific to their situation in the fourth dimension; however, women struggled with communicating these needs to clinicians. In the fifth dimension, women offered detailed descriptions of clinician behaviors that enhance or impede decisional debriefing. Better understanding of theoretical underpinnings surrounding women's information processes can facilitate decision support and improve clinical care.

Incorporating anthropometry into design of ear-related products.

PubMed

Liu, Bor-Shong

2008-01-01

To achieve mass customization and collaborative product design, human factors and ergonomics should play a key development role. The purpose of this study was to provide product designers with the anthropometic dimensions of outer ears for different demographic data, including gender and age. The second purpose was to compare the dimensions of various ear-related products (i.e., earphone, bluetooth earphone and ear-cup earphone) with the anthropometic database and recommend appropriate solutions for design. Two hundred subjects aged 20-59 was selected for this study and divided into four age stratifications. Further, three different dimensions of the outer ear (i.e., the earhole length, the ear connection length and the length of the pinna) were measured by superimposed grid photographic technique. The analysis of variance (ANOVA) was used to investigate the effects of gender, and age on ear dimensions. The results showed that all ear dimensions had significant gender effects. A comparison between the anthropometric dimensions and those of current products revealed that most current ear-related products need to be redesigned using anthropometric data. The shapes of earhole and pinna are not circular. Consequently, ear products need to be elongated so that users may feel more comfortably and not have the product slip off easily.