Long-Term Durability of Bioprosthetic Aortic Valves: Implications From 12,569 Implants

PubMed Central

Johnston, Douglas R.; Soltesz, Edward G.; Vakil, Nakul; Rajeswaran, Jeevanantham; Roselli, Eric E.; Sabik, Joseph F.; Smedira, Nicholas G.; Svensson, Lars G.; Lytle, Bruce W.; Blackstone, Eugene H.

2016-01-01

Background Increased life expectancy and younger patients’ desire to avoid lifelong anticoagulation requires a better understanding of bioprosthetic valve failure. This study evaluates risk factors associated with explantation for structural valve deterioration (SVD) in a long-term series of Carpentier-Edwards PERIMOUNT aortic valves (AV). Methods From June 1982 to January 2011, 12,569 patients underwent AV replacement with Edwards Lifesciences Carpentier-Edwards PERIMOUNT stented bovine pericardial prostheses, models 2700PM (n = 310) or 2700 (n = 12,259). Mean age was 71 ± 11 years (range, 18 to 98 years). 93% had native AV disease, 48% underwent concomitant coronary artery bypass grafting, and 26% had additional valve surgery. There were 81,706 patient-years of systematic follow-up data available for analysis. Demographics, intraoperative variables, and 27,386 echocardiographic records were used to identify risks for explant for SVD and assess longitudinal changes in transprosthesis gradients using time-varying covariable analyses. Results Three hundred fifty-four explants were performed, with 41% related to endocarditis and 44% to SVD. Actuarial estimates of explant for SVD at 10 and 20 years were 1.9% and 15% overall, respectively, and in patients younger than 60 years, 5.6% and 46%, respectively. Younger age (p < 0.0001), lipid-lowering drugs (p = 0.002), prosthesis–patient mismatch (p = 0.001), and higher postoperative peak and mean AV gradients were associated with explant for SVD (p < 0.0001). The effect of gradient on SVD was greatest in patients younger than 60 years. Conclusions Durability of the Carpentier-Edwards PERIMOUNT aortic valve is excellent even in younger patients. Explant for SVD is related to gradient at implantation, especially in younger patients. Strategies to reduce early postoperative AV gradients, such as root enlargement or more efficient prostheses, should be considered. PMID:25662439

Application of higher order SVD to vibration-based system identification and damage detection

NASA Astrophysics Data System (ADS)

Chao, Shu-Hsien; Loh, Chin-Hsiung; Weng, Jian-Huang

2012-04-01

Singular value decomposition (SVD) is a powerful linear algebra tool. It is widely used in many different signal processing methods, such principal component analysis (PCA), singular spectrum analysis (SSA), frequency domain decomposition (FDD), subspace identification and stochastic subspace identification method ( SI and SSI ). In each case, the data is arranged appropriately in matrix form and SVD is used to extract the feature of the data set. In this study three different algorithms on signal processing and system identification are proposed: SSA, SSI-COV and SSI-DATA. Based on the extracted subspace and null-space from SVD of data matrix, damage detection algorithms can be developed. The proposed algorithm is used to process the shaking table test data of the 6-story steel frame. Features contained in the vibration data are extracted by the proposed method. Damage detection can then be investigated from the test data of the frame structure through subspace-based and nullspace-based damage indices.

Application of a sparse representation method using K-SVD to data compression of experimental ambient vibration data for SHM

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Kiremidjian, Anne S.

2011-04-01

This paper introduces a data compression method using the K-SVD algorithm and its application to experimental ambient vibration data for structural health monitoring purposes. Because many damage diagnosis algorithms that use system identification require vibration measurements of multiple locations, it is necessary to transmit long threads of data. In wireless sensor networks for structural health monitoring, however, data transmission is often a major source of battery consumption. Therefore, reducing the amount of data to transmit can significantly lengthen the battery life and reduce maintenance cost. The K-SVD algorithm was originally developed in information theory for sparse signal representation. This algorithm creates an optimal over-complete set of bases, referred to as a dictionary, using singular value decomposition (SVD) and represents the data as sparse linear combinations of these bases using the orthogonal matching pursuit (OMP) algorithm. Since ambient vibration data are stationary, we can segment them and represent each segment sparsely. Then only the dictionary and the sparse vectors of the coefficients need to be transmitted wirelessly for restoration of the original data. We applied this method to ambient vibration data measured from a four-story steel moment resisting frame. The results show that the method can compress the data efficiently and restore the data with very little error.

Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation.

PubMed

Grossi, Giuliano; Lanzarotti, Raffaella; Lin, Jianyi

2017-01-01

In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error. Finding the best fitting dictionary remains a very difficult task, leaving the question still open. A well-established heuristic method for tackling this problem is an iterative alternating scheme, adopted for instance in the well-known K-SVD algorithm. Essentially, it consists in repeating two stages; the former promotes sparse coding of the training set and the latter adapts the dictionary to reduce the error. In this paper we present R-SVD, a new method that, while maintaining the alternating scheme, adopts the Orthogonal Procrustes analysis to update the dictionary atoms suitably arranged into groups. Comparative experiments on synthetic data prove the effectiveness of R-SVD with respect to well known dictionary learning algorithms such as K-SVD, ILS-DLA and the online method OSDL. Moreover, experiments on natural data such as ECG compression, EEG sparse representation, and image modeling confirm R-SVD's robustness and wide applicability.

Subsurface structure identification uses derivative analyses of the magnetic data in Candi Umbul-Telomoyo geothermal prospect area

NASA Astrophysics Data System (ADS)

Septyasari, U.; Niasari, S. W.; Maghfira, P. D.

2018-04-01

Telomoyo geothermal prospect area is located in Central Java, Indonesia. One of the manifestations around Telomoyo is a warm spring, called Candi Umbul. The hydrothermal fluids from the manifestation could be from the subsurface flowing up through geological structures. The previous research about 2D magnetic modeling in Candi Umbul showed that there was a normal fault with strike/dip N60°E/45° respectively. This research aims to know the distance boundary and the kind of the geological structure in the study area. We also compared the geological structure direction based on the geologic map and the derivative maps. We used derivative analyses of the magnetic data, i.e. First Horizontal Derivative (FHD) which is the rate of change of the horizontal gradient in the horizontal direction. FHD indicates the boundaries of the geological structure. We also used Second Vertical Derivative (SVD) which is the rate of change of the vertical gradient in the vertical direction. SVD can reveal normal fault or thrust fault. The FHD and SVD maps show that the geological structure boundary has the same direction with the north west-south east geological structure. The geological structure boundary is in 486 m of the local distance. Our result confirms that there is a normal fault in the study area.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure.

PubMed

Zhang, Wen; Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure

PubMed Central

Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods. PMID:27579031

Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol.

PubMed

van Norden, Anouk Gw; de Laat, Karlijn F; Gons, Rob Ar; van Uden, Inge Wm; van Dijk, Ewoud J; van Oudheusden, Lucas Jb; Esselink, Rianne Aj; Bloem, Bastiaan R; van Engelen, Baziel Gm; Zwarts, Machiel J; Tendolkar, Indira; Olde-Rikkert, Marcel G; van der Vlugt, Maureen J; Zwiers, Marcel P; Norris, David G; de Leeuw, Frank-Erik

2011-02-28

Cerebral small vessel disease (SVD) is a frequent finding on CT and MRI scans of elderly people and is related to vascular risk factors and cognitive and motor impairment, ultimately leading to dementia or parkinsonism in some. In general, the relations are weak, and not all subjects with SVD become demented or get parkinsonism. This might be explained by the diversity of underlying pathology of both white matter lesions (WML) and the normal appearing white matter (NAWM). Both cannot be properly appreciated with conventional MRI. Diffusion tensor imaging (DTI) provides alternative information on microstructural white matter integrity. The association between SVD, its microstructural integrity, and incident dementia and parkinsonism has never been investigated. The RUN DMC study is a prospective cohort study on the risk factors and cognitive and motor consequences of brain changes among 503 non-demented elderly, aged between 50-85 years, with cerebral SVD. First follow up is being prepared for July 2011. Participants alive will be included and invited to the research centre to undergo a structured questionnaire on demographics and vascular risk factors, and a cognitive, and motor, assessment, followed by a MRI protocol including conventional MRI, DTI and resting state fMRI. The follow up of the RUN DMC study has the potential to further unravel the causes and possibly better predict the consequences of changes in white matter integrity in elderly with SVD by using relatively new imaging techniques. When proven, these changes might function as a surrogate endpoint for cognitive and motor function in future therapeutic trials. Our data could furthermore provide a better understanding of the pathophysiology of cognitive and motor disturbances in elderly with SVD. The execution and completion of the follow up of our study might ultimately unravel the role of SVD on the microstructural integrity of the white matter in the transition from "normal" aging to cognitive and motor decline and impairment and eventually to incident dementia and parkinsonism.

Acoustooptic linear algebra processors - Architectures, algorithms, and applications

NASA Technical Reports Server (NTRS)

Casasent, D.

1984-01-01

Architectures, algorithms, and applications for systolic processors are described with attention to the realization of parallel algorithms on various optical systolic array processors. Systolic processors for matrices with special structure and matrices of general structure, and the realization of matrix-vector, matrix-matrix, and triple-matrix products and such architectures are described. Parallel algorithms for direct and indirect solutions to systems of linear algebraic equations and their implementation on optical systolic processors are detailed with attention to the pipelining and flow of data and operations. Parallel algorithms and their optical realization for LU and QR matrix decomposition are specifically detailed. These represent the fundamental operations necessary in the implementation of least squares, eigenvalue, and SVD solutions. Specific applications (e.g., the solution of partial differential equations, adaptive noise cancellation, and optimal control) are described to typify the use of matrix processors in modern advanced signal processing.

Depression in small-vessel disease relates to white matter ultrastructural damage, not disability.

PubMed

Brookes, Rebecca L; Herbert, Vanessa; Lawrence, Andrew J; Morris, Robin G; Markus, Hugh S

2014-10-14

To determine whether cerebral small-vessel disease (SVD) is a specific risk factor for depression, whether any association is mediated via white matter damage, and to study the role of depressive symptoms and disability on quality of life (QoL) in this patient group. Using path analyses in cross-sectional data, we modeled the relationships among depression, disability, and QoL in patients with SVD presenting with radiologically confirmed lacunar stroke (n = 100), and replicated results in a second SVD cohort (n = 100). We then compared the same model in a non-SVD stroke cohort (n = 50) and healthy older adults (n = 203). In a further study, to determine the role of white matter damage in mediating the association with depression, a subgroup of patients with SVD (n = 101) underwent diffusion tensor imaging (DTI). Reduced QoL was associated with depression in patients with SVD, but this association was not mediated by disability or cognition; very similar results were found in the replication SVD cohort. In contrast, the non-SVD stroke group and the healthy older adult group showed a direct relationship between disability and depression. The DTI study showed that fractional anisotropy, a marker of white matter damage, was related to depressive symptoms in patients with SVD. These results suggest that in stroke patients without SVD, disability is an important causal factor for depression, whereas in SVD stroke, other factors specific to this stroke subtype have a causal role. White matter damage detected on DTI is one factor that mediates the association between SVD and depression. © 2014 American Academy of Neurology.

Persistence of symptoms in primary somatoform vertigo and dizziness: a disorder "lost" in health care?

PubMed

Tschan, Regine; Best, Christoph; Wiltink, Jörg; Beutel, Manfred E; Dieterich, Marianne; Eckhardt-Henn, Annegret

2013-04-01

The aim of this study was to perform a 3-year follow-up of primary somatoform vertigo and dizziness (SVD) regarding health care use and treatment. Ninety-two patients with dizziness underwent detailed vestibular neurophysiological testing and a Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Psychometric assessments comprised the Vertigo Symptom Scale, the Vertigo Handicap Questionnaire, the SCL-90-R, and the Short-Form-36 Health Survey. At the 3-year follow-up, 65 patients with primary SVD (anxiety, n = 29; depression, n = 14; somatoform disorders, n = 22) were reassessed (70.7% response). The patients improved in symptom severity (p < 0.05), handicap (p < 0.01), and physical quality of life (QoL; p < 0.05) but showed no change in emotional distress. A total of 63.1% (of n = 65) had ongoing SVD. A total of 69.2% (of n = 65) received different forms of treatments. A total of 46.1% (of n = 65) searched redundant medical diagnostic procedures. The patients with decreased coping capacity over time obtained the best prognosis. Primary SVD is an ineffectively treated disorder. Recommendations for specific complaint-oriented psychotherapy programs were given.

Compound matrices

NASA Astrophysics Data System (ADS)

Kravvaritis, Christos; Mitrouli, Marilena

2009-02-01

This paper studies the possibility to calculate efficiently compounds of real matrices which have a special form or structure. The usefulness of such an effort lies in the fact that the computation of compound matrices, which is generally noneffective due to its high complexity, is encountered in several applications. A new approach for computing the Singular Value Decompositions (SVD's) of the compounds of a matrix is proposed by establishing the equality (up to a permutation) between the compounds of the SVD of a matrix and the SVD's of the compounds of the matrix. The superiority of the new idea over the standard method is demonstrated. Similar approaches with some limitations can be adopted for other matrix factorizations, too. Furthermore, formulas for the n - 1 compounds of Hadamard matrices are derived, which dodge the strenuous computations of the respective numerous large determinants. Finally, a combinatorial counting technique for finding the compounds of diagonal matrices is illustrated.

The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

NASA Astrophysics Data System (ADS)

Tan, Linglong; Li, Changkai; Wang, Yueqin

2018-04-01

SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

Lifestyle-related disease in Crohn’s disease: Relapse prevention by a semi-vegetarian diet

PubMed Central

Chiba, Mitsuro; Abe, Toru; Tsuda, Hidehiko; Sugawara, Takeshi; Tsuda, Satoko; Tozawa, Haruhiko; Fujiwara, Katsuhiko; Imai, Hideo

2010-01-01

AIM: To investigate whether semi-vegetarian diet (SVD) has a preventive effect against relapse of Crohn’s disease (CD) in patients who have achieved remission, who are a high-risk group for relapse. METHODS: A prospective, single center, 2-year clinical trial was conducted. Twenty-two adult CD patients who achieved clinical remission either medically (n = 17) or surgically (n = 5) and consumed an SVD during hospitalization were advised to continue with an SVD and avoid known high-risk foods for inflammatory bowel disease. The primary endpoint was clinical relapse defined as the appearance of active symptoms of CD. Kaplan-Meier survival analysis was used to calculate the cumulative proportion of patients who had a relapse. A 2-year analysis of relapse rates of patients who followed an SVD and those who did not (an omnivorous diet group) was undertaken. RESULTS: SVD was continued by 16 patients (compliance 73%). Remission was maintained in 15 of 16 patients (94%) in the SVD group vs two of six (33%) in the omnivorous group. Remission rate with SVD was 100% at 1 year and 92% at 2 years. SVD showed significant prevention in the time to relapse compared to that in the omnivorous group (P = 0.0003, log rank test). The concentration of C-reactive protein was normal at the final visit in more than half of the patients in remission who were taking an SVD, who maintained remission during the study (9/15; 60%), who terminated follow-up (8/12; 67%), and who completed 2 years follow-up (7/10; 70%). There was no untoward effect of SVD. CONCLUSION: SVD was highly effective in preventing relapse in CD. PMID:20503448

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)

2001-01-01

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

Effect of dual-focus soft contact lens wear on axial myopia progression in children.

PubMed

Anstice, Nicola S; Phillips, John R

2011-06-01

To test the efficacy of an experimental Dual-Focus (DF) soft contact lens in reducing myopia progression. Prospective, randomized, paired-eye control, investigator-masked trial with cross-over. Forty children, 11-14 years old, with mean spherical equivalent refraction (SER) of -2.71 ± 1.10 diopters (D). Dual-Focus lenses had a central zone that corrected refractive error and concentric treatment zones that created 2.00 D of simultaneous myopic retinal defocus during distance and near viewing. Control was a single vision distance (SVD) lens with the same parameters but without treatment zones. Children wore a DF lens in 1 randomly assigned eye and an SVD lens in the fellow eye for 10 months (period 1). Lens assignment was then swapped between eyes, and lenses were worn for a further 10 months (period 2). Primary outcome was change in SER measured by cycloplegic autorefraction over 10 months. Secondary outcome was a change in axial eye length (AXL) measured by partial coherence interferometry over 10 months. Accommodation wearing DF lenses was assessed using an open-field autorefractor. In period 1, the mean change in SER with DF lenses (-0.44 ± 0.33 D) was less than with SVD lenses (-0.69 ± 0.38 D; P < 0.001); mean increase in AXL was also less with DF lenses (0.11 ± 0.09 mm) than with SVD lenses (0.22 ± 0.10 mm; P < 0.001). In 70% of the children, myopia progression was reduced by 30% or more in the eye wearing the DF lens relative to that wearing the SVD lens. Similar reductions in myopia progression and axial eye elongation were also observed with DF lens wear during period 2. Visual acuity and contrast sensitivity with DF lenses were not significantly different than with SVD lenses. Accommodation to a target at 40 cm was driven through the central distance-correction zone of the DF lens. Dual-Focus lenses provided normal acuity and contrast sensitivity and allowed accommodation to near targets. Myopia progression and eye elongation were reduced significantly in eyes wearing DF lenses. The data suggest that sustained myopic defocus, even when presented to the retina simultaneously with a clear image, can act to slow myopia progression without compromising visual function. Proprietary or commercial disclosure may be found after the references. Copyright © 2011 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Frequency, Risk Factors, and Outcome of Coexistent Small Vessel Disease and Intracranial Arterial Stenosis: Results From the Stenting and Aggressive Medical Management for Preventing Recurrent Stroke in Intracranial Stenosis (SAMMPRIS) Trial.

PubMed

Kwon, Hyung-Min; Lynn, Michael J; Turan, Tanya N; Derdeyn, Colin P; Fiorella, David; Lane, Bethany F; Montgomery, Jean; Janis, L Scott; Rumboldt, Zoran; Chimowitz, Marc I

2016-01-01

Intracranial arterial stenosis (ICAS) and small vessel disease (SVD) may coexist. There are limited data on the frequency and risk factors for coexistent SVD and the effect of SVD on stroke recurrence in patients receiving medical treatment for ICAS. To investigate the frequency and risk factors for SVD and the effect of SVD on stroke recurrence in patients with ICAS. A post hoc analysis of the Stenting and Aggressive Medical Management for Preventing Recurrent Stroke in Intracranial Stenosis (SAMMPRIS) study, a prospective, multicenter clinical trial. Among 451 participants, 313 (69.4%) had baseline brain magnetic resonance imaging scans read centrally for SVD that was defined by any of the following: old lacunar infarction, grade 2 to 3 on the Fazekas scale (for high-grade white matter hyperintensities), or microbleeds. Patient enrollment in SAMMPRIS began November 25, 2008, and follow-up ended on April 30, 2013. Data analysis for the present study was performed from May 13, 2014, to July 29, 2015. Risk factors in patients with vs without SVD and the association between SVD and other baseline risk factors with any ischemic stroke and ischemic stroke in the territory of the stenotic artery determined using proportional hazards regression. Of 313 patients, 155 individuals (49.5%) had SVD noted on baseline magnetic resonance imaging. Variables that were significantly higher in patients with SVD, reported as mean (SD), included age, 63.5 (10.5) years (P < .001), systolic blood pressure, 149 (22) mm Hg (P < .001), glucose level, 130 (50) mg/dL (P = .03), and lower Montreal Cognitive Assessment scores (median, ≥24 [interquartile range, 20-26]; P = .02).Other significant variables were the number of patients with diabetes mellitus (88 of 155 [56.8%]; P = .003), coronary artery disease (46 [29.7%]; P = .004), stroke before the qualifying event (59 [38.1%]; P < .001), old infarct in the territory of the stenotic intracranial artery (88 [56.8%]; P < .001), and receiving antithrombotic therapy at the time of the qualifying event (109 [70.3%]; P = .005). The association between SVD and any ischemic stroke was nearly significant in the direction of a higher risk (18 [23.7%]); P = .07) for patients with SVD. On bivariate analysis, SVD was not associated with an increased risk on multivariable analyses (hazard ratio, 1.7 [95% CI, 0.8-3.8]; P = .20). In addition, SVD was not associated with an increased risk of stroke in the territory on either bivariate or multivariable analyses. Although SVD is common in patients with ICAS, the presence of SVD on baseline magnetic resonance imaging is not independently associated with an increased risk of stroke in patients with ICAS. clinicaltrials.gov Identifier: NCT00576693.

Comparison of two SVD-based color image compression schemes.

PubMed

Li, Ying; Wei, Musheng; Zhang, Fengxia; Zhao, Jianli

2017-01-01

Color image compression is a commonly used process to represent image data as few bits as possible, which removes redundancy in the data while maintaining an appropriate level of quality for the user. Color image compression algorithms based on quaternion are very common in recent years. In this paper, we propose a color image compression scheme, based on the real SVD, named real compression scheme. First, we form a new real rectangular matrix C according to the red, green and blue components of the original color image and perform the real SVD for C. Then we select several largest singular values and the corresponding vectors in the left and right unitary matrices to compress the color image. We compare the real compression scheme with quaternion compression scheme by performing quaternion SVD using the real structure-preserving algorithm. We compare the two schemes in terms of operation amount, assignment number, operation speed, PSNR and CR. The experimental results show that with the same numbers of selected singular values, the real compression scheme offers higher CR, much less operation time, but a little bit smaller PSNR than the quaternion compression scheme. When these two schemes have the same CR, the real compression scheme shows more prominent advantages both on the operation time and PSNR.

Comparison of two SVD-based color image compression schemes

PubMed Central

Li, Ying; Wei, Musheng; Zhang, Fengxia; Zhao, Jianli

2017-01-01

Color image compression is a commonly used process to represent image data as few bits as possible, which removes redundancy in the data while maintaining an appropriate level of quality for the user. Color image compression algorithms based on quaternion are very common in recent years. In this paper, we propose a color image compression scheme, based on the real SVD, named real compression scheme. First, we form a new real rectangular matrix C according to the red, green and blue components of the original color image and perform the real SVD for C. Then we select several largest singular values and the corresponding vectors in the left and right unitary matrices to compress the color image. We compare the real compression scheme with quaternion compression scheme by performing quaternion SVD using the real structure-preserving algorithm. We compare the two schemes in terms of operation amount, assignment number, operation speed, PSNR and CR. The experimental results show that with the same numbers of selected singular values, the real compression scheme offers higher CR, much less operation time, but a little bit smaller PSNR than the quaternion compression scheme. When these two schemes have the same CR, the real compression scheme shows more prominent advantages both on the operation time and PSNR. PMID:28257451

Clinical characteristics and outcomes with rivaroxaban vs. warfarin in patients with non-valvular atrial fibrillation but underlying native mitral and aortic valve disease participating in the ROCKET AF trial.

PubMed

Breithardt, Günter; Baumgartner, Helmut; Berkowitz, Scott D; Hellkamp, Anne S; Piccini, Jonathan P; Stevens, Susanna R; Lokhnygina, Yuliya; Patel, Manesh R; Halperin, Jonathan L; Singer, Daniel E; Hankey, Graeme J; Hacke, Werner; Becker, Richard C; Nessel, Christopher C; Mahaffey, Kenneth W; Fox, Keith A A; Califf, Robert M

2014-12-14

We investigated clinical characteristics and outcomes of patients with significant valvular disease (SVD) in the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) trial. ROCKET AF excluded patients with mitral stenosis or artificial valve prostheses. We used Cox regression to adjust comparisons for potential confounders. Among 14 171 patients, 2003 (14.1%) had SVD; they were older and had more comorbidities than patients without SVD. The rate of stroke or systemic embolism with rivaroxaban vs. warfarin was consistent among patients with SVD [2.01 vs. 2.43%; hazard ratio (HR) 0.83, 95% confidence interval (CI) 0.55-1.27] and without SVD (1.96 vs. 2.22%; HR 0.89, 95% CI 0.75-1.07; interaction P = 0.76). However, rates of major and non-major clinically relevant bleeding with rivaroxaban vs. warfarin were higher in patients with SVD (19.8% rivaroxaban vs. 16.8% warfarin; HR 1.25, 95% CI 1.05-1.49) vs. those without (14.2% rivaroxaban vs. 14.1% warfarin; HR 1.01, 95% CI 0.94-1.10; interaction P = 0.034), even when controlling for risk factors and potential confounders. In intracranial haemorrhage, there was no interaction between patients with and without SVD where the overall rate was lower among those randomized to rivaroxaban. Many patients with 'non-valvular atrial fibrillation' have significant valve lesions. Their risk of stroke is similar to that of patients without SVD after controlling for stroke risk factors. Efficacy of rivaroxaban vs. warfarin was similar in patients with and without SVD; however, the observed risk of bleeding was higher with rivaroxaban in patients with SVD but was the same among those without SVD. Atrial fibrillation patients with and without SVD experience the same stroke-preventive benefit of oral anticoagulants. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Cardiology.

Clinical characteristics and outcomes with rivaroxaban vs. warfarin in patients with non-valvular atrial fibrillation but underlying native mitral and aortic valve disease participating in the ROCKET AF trial

PubMed Central

Breithardt, Günter; Baumgartner, Helmut; Berkowitz, Scott D.; Hellkamp, Anne S.; Piccini, Jonathan P.; Stevens, Susanna R.; Lokhnygina, Yuliya; Patel, Manesh R.; Halperin, Jonathan L.; Singer, Daniel E.; Hankey, Graeme J.; Hacke, Werner; Becker, Richard C.; Nessel, Christopher C.; Mahaffey, Kenneth W.; Fox, Keith A. A.; Califf, Robert M.

2014-01-01

Aims We investigated clinical characteristics and outcomes of patients with significant valvular disease (SVD) in the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) trial. Methods and results ROCKET AF excluded patients with mitral stenosis or artificial valve prostheses. We used Cox regression to adjust comparisons for potential confounders. Among 14 171 patients, 2003 (14.1%) had SVD; they were older and had more comorbidities than patients without SVD. The rate of stroke or systemic embolism with rivaroxaban vs. warfarin was consistent among patients with SVD [2.01 vs. 2.43%; hazard ratio (HR) 0.83, 95% confidence interval (CI) 0.55–1.27] and without SVD (1.96 vs. 2.22%; HR 0.89, 95% CI 0.75–1.07; interaction P = 0.76). However, rates of major and non-major clinically relevant bleeding with rivaroxaban vs. warfarin were higher in patients with SVD (19.8% rivaroxaban vs. 16.8% warfarin; HR 1.25, 95% CI 1.05–1.49) vs. those without (14.2% rivaroxaban vs. 14.1% warfarin; HR 1.01, 95% CI 0.94–1.10; interaction P = 0.034), even when controlling for risk factors and potential confounders. In intracranial haemorrhage, there was no interaction between patients with and without SVD where the overall rate was lower among those randomized to rivaroxaban. Conclusions Many patients with ‘non-valvular atrial fibrillation’ have significant valve lesions. Their risk of stroke is similar to that of patients without SVD after controlling for stroke risk factors. Efficacy of rivaroxaban vs. warfarin was similar in patients with and without SVD; however, the observed risk of bleeding was higher with rivaroxaban in patients with SVD but was the same among those without SVD. Atrial fibrillation patients with and without SVD experience the same stroke-preventive benefit of oral anticoagulants. PMID:25148838

A singular value decomposition approach for improved taxonomic classification of biological sequences

PubMed Central

2011-01-01

Background Singular value decomposition (SVD) is a powerful technique for information retrieval; it helps uncover relationships between elements that are not prima facie related. SVD was initially developed to reduce the time needed for information retrieval and analysis of very large data sets in the complex internet environment. Since information retrieval from large-scale genome and proteome data sets has a similar level of complexity, SVD-based methods could also facilitate data analysis in this research area. Results We found that SVD applied to amino acid sequences demonstrates relationships and provides a basis for producing clusters and cladograms, demonstrating evolutionary relatedness of species that correlates well with Linnaean taxonomy. The choice of a reasonable number of singular values is crucial for SVD-based studies. We found that fewer singular values are needed to produce biologically significant clusters when SVD is employed. Subsequently, we developed a method to determine the lowest number of singular values and fewest clusters needed to guarantee biological significance; this system was developed and validated by comparison with Linnaean taxonomic classification. Conclusions By using SVD, we can reduce uncertainty concerning the appropriate rank value necessary to perform accurate information retrieval analyses. In tests, clusters that we developed with SVD perfectly matched what was expected based on Linnaean taxonomy. PMID:22369633

A pipeline VLSI design of fast singular value decomposition processor for real-time EEG system based on on-line recursive independent component analysis.

PubMed

Huang, Kuan-Ju; Shih, Wei-Yeh; Chang, Jui Chung; Feng, Chih Wei; Fang, Wai-Chi

2013-01-01

This paper presents a pipeline VLSI design of fast singular value decomposition (SVD) processor for real-time electroencephalography (EEG) system based on on-line recursive independent component analysis (ORICA). Since SVD is used frequently in computations of the real-time EEG system, a low-latency and high-accuracy SVD processor is essential. During the EEG system process, the proposed SVD processor aims to solve the diagonal, inverse and inverse square root matrices of the target matrices in real time. Generally, SVD requires a huge amount of computation in hardware implementation. Therefore, this work proposes a novel design concept for data flow updating to assist the pipeline VLSI implementation. The SVD processor can greatly improve the feasibility of real-time EEG system applications such as brain computer interfaces (BCIs). The proposed architecture is implemented using TSMC 90 nm CMOS technology. The sample rate of EEG raw data adopts 128 Hz. The core size of the SVD processor is 580×580 um(2), and the speed of operation frequency is 20MHz. It consumes 0.774mW of power during the 8-channel EEG system per execution time.

Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation

PubMed Central

Grossi, Giuliano; Lin, Jianyi

2017-01-01

In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error. Finding the best fitting dictionary remains a very difficult task, leaving the question still open. A well-established heuristic method for tackling this problem is an iterative alternating scheme, adopted for instance in the well-known K-SVD algorithm. Essentially, it consists in repeating two stages; the former promotes sparse coding of the training set and the latter adapts the dictionary to reduce the error. In this paper we present R-SVD, a new method that, while maintaining the alternating scheme, adopts the Orthogonal Procrustes analysis to update the dictionary atoms suitably arranged into groups. Comparative experiments on synthetic data prove the effectiveness of R-SVD with respect to well known dictionary learning algorithms such as K-SVD, ILS-DLA and the online method OSDL. Moreover, experiments on natural data such as ECG compression, EEG sparse representation, and image modeling confirm R-SVD’s robustness and wide applicability. PMID:28103283

First-principles investigation of the interlayer coupling in chromium-trichloride-a layered magnetic insulator

NASA Astrophysics Data System (ADS)

Kc, Santosh; McGuire, Michael A.; Cooper, Valentino R.

The crystallographic, electronic and magnetic properties of layered CrCl3were investigated using density functional theory. We use the newly developed spin van der Waals density functional (svdW-DF) in order to explore the atomic, electronic and magnetic structure. Our results indicate that treatment of the long-range interlayer forces with the svdW-DF improves the accuracy of crystal structure predictions. The cleavage energy was estimated to be 0.29 J/m2 suggesting that CrCl3 should be cleavable using standard mechanical exfoliation techniques. The inclusion of spin in the non-local vdW-DF allows us to directly probe the coupling between the magnetic structure and lattice degrees of freedom. An understanding of the link between electronic, magnetic and structural properties can be useful for novel device applications such as magnetoelectric devices, spin transistors, and 2D magnet. Research was sponsored by the US DOE, Office of Science, BES, MSED and Early Career Research Programs and used resources at NERSC.

Data Unfolding with Wiener-SVD Method

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

Tang, W.; Li, X.; Qian, X.

Here, data unfolding is a common analysis technique used in HEP data analysis. Inspired by the deconvolution technique in the digital signal processing, a new unfolding technique based on the SVD technique and the well-known Wiener filter is introduced. The Wiener-SVD unfolding approach achieves the unfolding by maximizing the signal to noise ratios in the effective frequency domain given expectations of signal and noise and is free from regularization parameter. Through a couple examples, the pros and cons of the Wiener-SVD approach as well as the nature of the unfolded results are discussed.

Data Unfolding with Wiener-SVD Method

DOE PAGES

Tang, W.; Li, X.; Qian, X.; ...

2017-10-04

Here, data unfolding is a common analysis technique used in HEP data analysis. Inspired by the deconvolution technique in the digital signal processing, a new unfolding technique based on the SVD technique and the well-known Wiener filter is introduced. The Wiener-SVD unfolding approach achieves the unfolding by maximizing the signal to noise ratios in the effective frequency domain given expectations of signal and noise and is free from regularization parameter. Through a couple examples, the pros and cons of the Wiener-SVD approach as well as the nature of the unfolded results are discussed.

Only White Matter Hyperintensities Predicts Post-Stroke Cognitive Performances Among Cerebral Small Vessel Disease Markers: Results from the TABASCO Study.

PubMed

Molad, Jeremy; Kliper, Efrat; Korczyn, Amos D; Ben Assayag, Einor; Ben Bashat, Dafna; Shenhar-Tsarfaty, Shani; Aizenstein, Orna; Shopin, Ludmila; Bornstein, Natan M; Auriel, Eitan

2017-01-01

White matter hyperintensities (WMH) were shown to predict cognitive decline following stroke or transient ischemic attack (TIA). However, WMH are only one among other radiological markers of cerebral small vessel disease (SVD). The aim of this study was to determine whether adding other SVD markers to WMH improves prediction of post-stroke cognitive performances. Consecutive first-ever stroke or TIA patients (n = 266) from the Tel Aviv Acute Brain Stroke Cohort (TABASCO) study were enrolled. MRI scans were performed within seven days of stroke onset. We evaluated the relationship between cognitive performances one year following stroke, and previously suggested total SVD burden score including WMH, lacunes, cerebral microbleeds (CMB), and perivascular spaces (PVS). Significant negative associations were found between WMH and cognition (p < 0.05). Adding other SVD markers (lacunes, CMB, PVS) to WMH did not improve predication of post-stroke cognitive performances. Negative correlations between SVD burden score and cognitive scores were observed for global cognitive, memory, and visual spatial scores (all p < 0.05). However, following an adjustment for confounders, no associations remained significant. WMH score was associated with poor post-stroke cognitive performance. Adding other SVD markers or SVD burden score, however, did not improve prediction.

Genetic overlap between diagnostic subtypes of ischemic stroke.

PubMed

Holliday, Elizabeth G; Traylor, Matthew; Malik, Rainer; Bevan, Steve; Falcone, Guido; Hopewell, Jemma C; Cheng, Yu-Ching; Cotlarciuc, Ioana; Bis, Joshua C; Boerwinkle, Eric; Boncoraglio, Giorgio B; Clarke, Robert; Cole, John W; Fornage, Myriam; Furie, Karen L; Ikram, M Arfan; Jannes, Jim; Kittner, Steven J; Lincz, Lisa F; Maguire, Jane M; Meschia, James F; Mosley, Thomas H; Nalls, Mike A; Oldmeadow, Christopher; Parati, Eugenio A; Psaty, Bruce M; Rothwell, Peter M; Seshadri, Sudha; Scott, Rodney J; Sharma, Pankaj; Sudlow, Cathie; Wiggins, Kerri L; Worrall, Bradford B; Rosand, Jonathan; Mitchell, Braxton D; Dichgans, Martin; Markus, Hugh S; Levi, Christopher; Attia, John; Wray, Naomi R

2015-03-01

Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses. Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA-SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles. High genetic correlation was identified between LAA and SVD using linear mixed models (rg=0.96, SE=0.47, P=9×10(-4)) and profile scores (rg=0.72; 95% confidence interval, 0.52-0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association (P=1×10(-7)) for single nucleotide polymorphisms near the opioid receptor μ1 (OPRM1) gene. Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes. © 2015 American Heart Association, Inc.

Persistent left superior vena cava in association with sinus venosus defect type of atrial septal defect and partial pulmonary venous return on 64-MDCT

PubMed Central

Disha, Bansal; Prakashini, Koteshwara; Shetty, Ranjan K

2014-01-01

The most common venous abnormality of the thorax is persistent left superior vena cava (PLSVC), incidence being less than 0.5%. However, with congenital heart disease, it is about 6.1%. When the coronary sinus is dilated always search for PLSVC. The coronary sinus may communicate with the left atrium. This is known as an unroofed coronary sinus (UCS) and preoperatively documenting it is important. Of all the congenital cardiac anomalies, the sinus venosus defect (SVD) type of atrial septal defect (ASD) is most commonly associated with PLSVC and accounts for 4–11% of all ASDs. Multidetector CT can easily show all these abnormalities along with haemodynamics. On transoesophageal echocardiography it is difficult to characterise SVD and visualise a coronary sinus because of a limited window, contrast resolution and poor patient compliance. The complex of UCS and PLSVC is one such abnormality and its treatment requires careful assessment of other concomitant cardiac abnormalities to prevent post-treatment haemodynamic complications. PMID:24850552

Spatial Analysis of Gravity Data in the California, Nevada, and Utah (US)

NASA Astrophysics Data System (ADS)

Ferani, NA; Hartantyo, E.; Niasari, SW

2018-04-01

The geological condition of western North America is very complex because of the encounter of three major plates namely North America, Juan de Fuca, and Pacific Plate. The process of Juan de Fuca subduction and Pacific transform against North America plate created many mountains and produced Great Basin that we can see extending across California, Nevada, and Utah. The varied natural condition causes the varied value of gravity anomaly distribution. Using Topex free-air anomaly analyzed with second vertical derivative (SVD), we can analyze the fracture structures that occur in the Great Basin. The results show that the maximal SVD anomaly value is higher than the minimal SVD anomaly value at the western and eastern border of Great Basin. This explains that the two of Great Basin border are normal faults with trend direction NW-SE in the western boundary and NE-SW trending in the eastern boundary. This research result corresponds with the high seismicity data along the fault. Through this research, we can know that topex free-air anomaly data can be used to determine the type and trend of fault on a regional scale.

Depressive symptoms as a predictor of quality of life in cerebral small vessel disease, acting independently of disability; a study in both sporadic SVD and CADASIL

PubMed Central

Brookes, Rebecca L; Willis, Thomas A; Patel, Bhavini; Morris, Robin G; Markus, Hugh S

2013-01-01

Background Cerebral small vessel disease (SVD) causes lacunar stroke, and more recently has been implicated as a cause of depression. Factors causing reduced quality of life (QoL) in SVD, including the relative contributions of disability and depressive symptoms, remain uncertain. Hypothesis Depressive symptoms are a major predictor of reduced QoL in SVD, acting independently of disability. Methods The Stroke-Specific QoL scale was completed by 100 patients with SVD (lacunar stroke with MRI lacunar infarct) and 55 controls. We repeated the protocol in 40 patients with the young onset genetic form of SVD, CADASIL, and 35 controls. Disability (modified Rankin Scale), [instrumental] activities of daily living (IADL, ADL), cognition (Mini Mental State Examination) and depressive symptoms (Geriatric Depression Scale, Montgomery-Åsberg Depression Rating Scale) were measured. Results QoL was significantly lower in SVD than controls: mean (SD), 196.8 (35.2) versus 226.8(15.3), p<.0001. Depressive symptoms were the major predictor of QoL, accounting for 52.9% of variance. The only other independent predictor of QoL was disability, accounting for an additional 18.4%. A similar pattern was found in CADASIL with reduced QoL (202.0(29.7) versus controls (228.6 (13.1); p<.0001), and depressive symptoms accounting for 42.2% of variance. Disability accounted for an additional 17.6%. Relationships between depression and QoL, and disability and QoL, were independent of one another. Conclusions Depressive symptoms, often unrecognized, are a major determinant of reduced QoL in SVD. They account for greater reduction than disability, and the association is independent of disability. This relationship may reflect the proposed causal association between white matter disease and depression. Treatment of depressive symptoms might significantly improve QoL in SVD. PMID:22364606

Drug‐coated balloons for de novo lesions in small coronary arteries: rationale and design of BASKET‐SMALL 2

PubMed Central

Gilgen, Nicole; Farah, Ahmed; Scheller, Bruno; Ohlow, Marc‐Alexander; Mangner, Norman; Weilenmann, Daniel; Wöhrle, Jochen; Jamshidi, Peiman; Leibundgut, Gregor; Möbius‐Winkler, Sven; Zweiker, Robert; Krackhardt, Florian; Butter, Christian; Bruch, Leonhard; Kaiser, Christoph; Hoffmann, Andreas; Rickenbacher, Peter; Mueller, Christian; Stephan, Frank‐Peter; Coslovsky, Michael

2018-01-01

The treatment of coronary small vessel disease (SVD) remains an unresolved issue. Drug‐eluting stents (DES) have limited efficacy due to increased rates of instent‐restenosis, mainly caused by late lumen loss. Drug‐coated balloons (DCB) are a promising technique because native vessels remain structurally unchanged. Basel Stent Kosten‐Effektivitäts Trial: Drug‐Coated Balloons vs. Drug‐Eluting Stents in Small Vessel Interventions (BASKET‐SMALL 2) is a multicenter, randomized, controlled, noninferiority trial of DCB vs DES in native SVD for clinical endpoints. Seven hundred fifty‐eight patients with de novo lesions in vessels <3 mm in diameter and an indication for percutaneous coronary intervention such as stable angina pectoris, silent ischemia, or acute coronary syndromes are randomized 1:1 to angioplasty with DCB vs implantation of a DES after successful initial balloon angioplasty. The primary endpoint is the combination of cardiac death, nonfatal myocardial infarction, and target‐vessel revascularization up to 1 year. Secondary endpoints include stent thrombosis, Bleeding Academic Research Consortium (BARC) type 3 to 5 bleeding, and long‐term outcome up to 3 years. Based on clinical endpoints after 1 year, we plan to assess the noninferiority of DCB compared to DES in patients undergoing primary percutaneous coronary intervention for SVD. Results will be available in the second half of 2018. This study will compare DCB and DES regarding long‐term safety and efficacy for the treatment of SVD in a large all‐comer population. PMID:29527709

Continuous analogues of matrix factorizations

PubMed Central

Townsend, Alex; Trefethen, Lloyd N.

2015-01-01

Analogues of singular value decomposition (SVD), QR, LU and Cholesky factorizations are presented for problems in which the usual discrete matrix is replaced by a ‘quasimatrix’, continuous in one dimension, or a ‘cmatrix’, continuous in both dimensions. Two challenges arise: the generalization of the notions of triangular structure and row and column pivoting to continuous variables (required in all cases except the SVD, and far from obvious), and the convergence of the infinite series that define the cmatrix factorizations. Our generalizations of triangularity and pivoting are based on a new notion of a ‘triangular quasimatrix’. Concerning convergence of the series, we prove theorems asserting convergence provided the functions involved are sufficiently smooth. PMID:25568618

Assessment of structural valve deterioration of transcatheter aortic bioprosthetic balloon-expandable valves using the new European consensus definition.

PubMed

Eltchaninoff, Hélène; Durand, Eric; Avinée, Guillaume; Tron, Christophe; Litzler, Pierre-Yves; Bauer, Fabrice; Dacher, Jean-Nicolas; Werhlin, Camille; Bouhzam, Najime; Bettinger, Nicolas; Candolfi, Pascal; Cribier, Alain

2018-03-30

Durability of transcatheter aortic bioprosthetic valves remains a major issue. Standardised definitions of deterioration and failure of bioprosthetic valves have recently been proposed. The aim of this study was to assess structural transcatheter valve deterioration (SVD) and bioprosthetic valve failure (BVF) using these new definitions. All TAVI patients implanted up to September 2012 with a minimal theoretical five-year follow-up were included. Systematic clinical and echocardiographic follow-up was performed annually. New standardised definitions were used to assess durability of transcatheter aortic bioprosthetic valves. From 2002 to 2012, 378 patients were included. Mean age and logistic EuroSCORE were 83.3±6.8 years and 22.8±13.1%. Thirty-day mortality was 13.2%. Nine patients had SVD including two severe forms and two patients had definite late BVF. The incidence of SVD and BVF at eight years was 3.2% (95% CI: 1.45-6.11) and 0.58% (95% CI: 0.15-2.75), respectively. Even though limited by the poor survival of the very high-risk/compassionate early population, our data do not demonstrate any alarm concerning transcatheter aortic valve durability. Careful prospective assessment in younger and lower-risk patients and comparison with surgical bioprosthetic valves are required for further assessment of the long-term durability of transcatheter valves.

Age-Specific Associations of Renal Impairment With Magnetic Resonance Imaging Markers of Cerebral Small Vessel Disease in Transient Ischemic Attack and Stroke.

PubMed

Liu, Bian; Lau, Kui Kai; Li, Linxin; Lovelock, Caroline; Liu, Ming; Kuker, Wilhelm; Rothwell, Peter M

2018-04-01

It has been hypothesized that cerebral small vessel disease (SVD) and chronic renal impairment may be part of a multisystem small-vessel disorder, but their association may simply be as a result of shared risk factors (eg, hypertension) rather than to a systemic susceptibility to premature SVD. However, most previous studies were hospital based, most had inadequate adjustment for hypertension, many were confined to patients with lacunar stroke, and none stratified by age. In a population-based study of transient ischemic attack and ischemic stroke (OXVASC [Oxford Vascular Study]), we evaluated the magnetic resonance imaging markers of cerebral SVD, including lacunes, white matter hyperintensities, cerebral microbleeds, and enlarged perivascular space. We studied the age-specific associations of renal impairment (estimated glomerular filtration rate <60 mL/min per 1.73 m 2 ) and total SVD burden (total SVD score) adjusting for age, sex, vascular risk factors, and premorbid blood pressure (mean blood pressure during 15 years preevent). Of 1080 consecutive patients, 1028 (95.2%) had complete magnetic resonance imaging protocol and creatinine measured at baseline. Renal impairment was associated with total SVD score (odds ratio [OR], 2.16; 95% confidence interval [CI], 1.69-2.75; P <0.001), but only at age <60 years (<60 years: OR, 3.97; 95% CI, 1.69-9.32; P =0.002; 60-79 years: OR, 1.01; 95% CI, 0.72-1.41; P =0.963; ≥80 years: OR, 0.95; 95% CI, 0.59-1.54; P =0.832). The overall association of renal impairment and total SVD score was also attenuated after adjustment for age, sex, history of hypertension, diabetes mellitus, and premorbid average systolic blood pressure (adjusted OR, 0.76; 95% CI, 0.56-1.02; P =0.067), but the independent association of renal impairment and total SVD score at age <60 years was maintained (adjusted OR, 3.11; 95% CI, 1.21-7.98; P =0.018). Associations of renal impairment and SVD were consistent for each SVD marker at age <60 years but were strongest for cerebral microbleeds (OR, 5.84; 95% CI, 1.45-23.53; P =0.013) and moderate-severe periventricular white matter hyperintensities (OR, 6.28; 95% CI, 1.54-25.63; P =0.010). The association of renal impairment and cerebral SVD was attenuated with adjustment for shared risk factors at older ages, but remained at younger ages, consistent with a shared susceptibility to premature disease. © 2018 The Authors.

Brain atrophy and cerebral small vessel disease: a prospective follow-up study.

PubMed

Nitkunan, Arani; Lanfranconi, Silvia; Charlton, Rebecca A; Barrick, Thomas R; Markus, Hugh S

2011-01-01

cerebral small vessel disease (SVD) is the most common cause of vascular dementia. Interest in the use of surrogate markers is increasing. The aims of this study were to determine if brain volume was different between patients with SVD and control subjects, whether it correlated with cognition in SVD, and whether changes in brain volume could be detected during prospective follow-up. thirty-five patients (mean age, 68.8 years) who had a lacunar stroke and radiological evidence of confluent leukoaraiosis and 70 age- and gender-matched control subjects were recruited. Whole-brain T1-weighted imaging and neuropsychological testing were performed after 1 year on all patients and after 2 years for the control subjects. Fully automated software was used to determine brain volume and percentage brain volume change. An executive function score was derived. there was a significant difference in brain volume between the patients with SVD and control subjects (mean ± SD [mL] 1529 ± 84 versus 1573 ± 69, P=0.019). In the patients with SVD, there was a significant association between brain volume and executive function (r=0.501, P<0.05). The mean ± SD yearly brain atrophy rate for patients with SVD and control subjects was significantly different (-0.914% ± 0.8% versus -0.498% ± 0.4%, respectively, P=0.017). No change in executive function score was detected over this period. brain volume is reduced in SVD and a decline is detectable prospectively. The correlation with executive function at a cross-sectional level and the change in brain volume with time are both promising for the use of brain atrophy as a surrogate marker of SVD progression.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

Cerebral small vessel disease, medial temporal lobe atrophy and cognitive status in patients with ischaemic stroke and transient ischaemic attack.

PubMed

Arba, F; Quinn, T; Hankey, G J; Ali, M; Lees, K R; Inzitari, D

2017-02-01

Small vessel disease (SVD) and Alzheimer's disease (AD) are two common causes of cognitive impairment and dementia, traditionally considered as distinct processes. The relationship between radiological features suggestive of AD and SVD was explored, and the association of each of these features with cognitive status at 1 year was investigated in patients with stroke or transient ischaemic attack. Anonymized data were accessed from the Virtual International Stroke Trials Archive (VISTA). Medial temporal lobe atrophy (MTA; a marker of AD) and markers of SVD were rated using validated ordinal visual scales. Cognitive status was evaluated with the Mini Mental State Examination (MMSE) 1 year after the index stroke. Logistic regression models were used to investigate independent associations between (i) baseline SVD features and MTA and (ii) all baseline neuroimaging features and cognitive status 1 year post-stroke. In all, 234 patients were included, mean (±SD) age 65.7 ± 13.1 years, 145 (62%) male. Moderate to severe MTA was present in 104 (44%) patients. SVD features were independently associated with MTA (P < 0.001). After adjusting for age, sex, disability after stroke, hypertension and diabetes mellitus, MTA was the only radiological feature independently associated with cognitive impairment, defined using thresholds of MMSE ≤ 26 (odds ratio 1.94; 95% confidence interval 1.28-2.94) and MMSE ≤ 23 (odds ratio 2.31; 95% confidence interval 1.48-3.62). In patients with ischaemic cerebrovascular disease, SVD features are associated with MTA, which is a common finding in stroke survivors. SVD and AD type neurodegeneration coexist, but the AD marker MTA, rather than SVD markers, is associated with post-stroke cognitive impairment. © 2016 EAN.

[Serological examinations for swine vesicular disease (SVD) in a closed pig breeding herd using ELISA].

PubMed

Pannwitz, Gunter; Haas, Bernd; Hoffmann, Bernd; Fischer, Sebastian

2009-01-01

In a closed pig establishment housing about 18,000 pigs, 2895 gilts were tested pre-export for SVD (swine vesicular disease) antibodies using Ceditest/PrioCHECK SVDV-AB ELISA. 130 gilts (4.5%) tested positive. In addition, 561 animals of this farm were sampled per random for SVD serology. One in 241 weaners (0.4%), eight in 150 gilts (5.3%) and 18 in 170 (10.6%) pregnant sows tested ELISA SVD-antibody positive. Of the ELISA positive samples, 23 tested positive in VNT (virus neutralization test). Of these, 20 VNT-positive animals were re-sampled two weeks later and re-tested via ELISA and VNT in different laboratories, displaying falling titres with one to two animals remaining VNT-positive. Epidemiological investigations and clinical examinations on site did not yield any evidence for SVD. 745 faecal samples taken from individual pigs and collected from pens tested negative in SVDV-RNA-PCR. 40 of these samples tested negative in virus isolation on cell culture. Pathological examinations on fallen pigs did not reveal any evidence for SVD either. After comparing our ELISA results with data recorded in the ELISA validation by Chenard et al. (1998), we propose that the published test performance is perhaps not currently applicable for the commercial test. Provided that SVD-antibody negative pigs were tested, a specificity of 99.6% in weaners, 95.5% in gilts and 89.4% in pregnant sows would appear to be more appropriate for the Ceditest/PrioCHECK SVDV-AB ELISA. Details are provided for all examined pigs regarding husbandry, breed, age, weeks pregnant and previous vaccinations. The results of other serological tests on the same sera are given. Possible clusterings of false-positive SVD-ELISA results are discussed.

[Management of cerebral small vessel disease for the diagnosis and treatment of dementia].

PubMed

Ihara, Masafumi

2013-07-01

With the demographic shift in life expectancy inexorably increasing in developed countries, dementia is set to become one of the most important health problems worldwide. In recent years, cerebral small vessel disease (SVD) has received much attention as an important cause of dementia. The reason for this is twofold: firstly, arteriosclerosis (type 1 SVD) is the leading cause of vascular cognitive impairment, and secondly, cerebral amyloid angiopathy (CAA; type 2 SVD) is an almost invariable accompaniment of Alzheimer's disease. SVD is known to induce a variety of pathological changes; for example, type 1 SVD results in lacunar infarction, deep microbleeds, and white matter damage, while type 2 SVD leads to cortical microinfarcts, lobar microbleeds, and white matter damage. SVD is considered a spectrum of abnormalities, with the majority of patients experiencing symptoms from both type 1 and type 2 SVD as the disease progresses. The discouraging results of immunotherapy clinical trials for Alzheimer's disease have shifted the scientific attention from the classical neuron-centric approach towards a novel neurovascular approach. As arteries stiffen with age or with other co-morbid factors such as life-related diseases, amyloid β (Aβ) synthesis becomes upregulated, resulting in the deposition of insoluble Aβ not only in the parenchyma as senile plaques but also in the perivascular drainage pathways as CAA. Therefore, therapeutic strategies such as vasoactive drugs that enhance the patency of this Aβ drainage pathway may facilitate Aβ removal and help prevent cognitive decline in the elderly. Based on this emerging paradigm, clinical trials are warranted to investigate whether a neurovascular therapeutic approach can effectively halt cognitive decline and act as a preemptive medicine for patients at risk of dementia.

Belle II SVD ladder assembly procedure and electrical qualification

NASA Astrophysics Data System (ADS)

Adamczyk, K.; Aihara, H.; Angelini, C.; Aziz, T.; Babu, Varghese; Bacher, S.; Bahinipati, S.; Barberio, E.; Baroncelli, T.; Basith, A. K.; Batignani, G.; Bauer, A.; Behera, P. K.; Bergauer, T.; Bettarini, S.; Bhuyan, B.; Bilka, T.; Bosi, F.; Bosisio, L.; Bozek, A.; Buchsteiner, F.; Casarosa, G.; Ceccanti, M.; Červenkov, D.; Chendvankar, S. R.; Dash, N.; Divekar, S. T.; Doležal, Z.; Dutta, D.; Forti, F.; Friedl, M.; Hara, K.; Higuchi, T.; Horiguchi, T.; Irmler, C.; Ishikawa, A.; Jeon, H. B.; Joo, C.; Kandra, J.; Kang, K. H.; Kato, E.; Kawasaki, T.; Kodyš, P.; Kohriki, T.; Koike, S.; Kolwalkar, M. M.; Kvasnička, P.; Lanceri, L.; Lettenbicher, J.; Mammini, P.; Mayekar, S. N.; Mohanty, G. B.; Mohanty, S.; Morii, T.; Nakamura, K. R.; Natkaniec, Z.; Negishi, K.; Nisar, N. K.; Onuki, Y.; Ostrowicz, W.; Paladino, A.; Paoloni, E.; Park, H.; Pilo, F.; Profeti, A.; Rao, K. K.; Rashevskaya, I.; Rizzo, G.; Rozanska, M.; Sandilya, S.; Sasaki, J.; Sato, N.; Schultschik, S.; Schwanda, C.; Seino, Y.; Shimizu, N.; Stypula, J.; Tanaka, S.; Tanida, K.; Taylor, G. N.; Thalmeier, R.; Thomas, R.; Tsuboyama, T.; Uozumi, S.; Urquijo, P.; Vitale, L.; Volpi, M.; Watanuki, S.; Watson, I. J.; Webb, J.; Wiechczynski, J.; Williams, S.; Würkner, B.; Yamamoto, H.; Yin, H.; Yoshinobu, T.; Belle II SVD Collaboration

2016-07-01

The Belle II experiment at the SuperKEKB asymmetric e+e- collider in Japan will operate at a luminosity approximately 50 times larger than its predecessor (Belle). At its heart lies a six-layer vertex detector comprising two layers of pixelated silicon detectors (PXD) and four layers of double-sided silicon microstrip detectors (SVD). One of the key measurements for Belle II is time-dependent CP violation asymmetry, which hinges on a precise charged-track vertex determination. Towards this goal, a proper assembly of the SVD components with precise alignment ought to be performed and the geometrical tolerances should be checked to fall within the design limits. We present an overview of the assembly procedure that is being followed, which includes the precision gluing of the SVD module components, wire-bonding of the various electrical components, and precision three dimensional coordinate measurements of the jigs used in assembly as well as of the final SVD modules.

Bioprosthetic mitral valve replacement in patients aged 65 years or younger: long-term outcomes with the Carpentier-Edwards PERIMOUNT pericardial valve.

PubMed

Bourguignon, Thierry; Espitalier, Fabien; Pantaleon, Clémence; Vermes, Emmanuelle; El-Arid, Jean Marc; Loardi, Claudia; Karam, Elias; Candolfi, Pascal; Ivanes, Fabrice; Aupart, Michel

2018-02-12

Mitral valve replacement using a bioprosthesis remains controversial in young patients because data on long-term outcomes are missing. This study evaluated the long-term results of the PERIMOUNT pericardial mitral bioprosthesis in patients aged 65 years or younger. From 1984 to 2010, 148 Carpentier-Edwards PERIMOUNT mitral bioprostheses were implanted in 148 patients aged 65 years or younger. Baseline clinical, perioperative and follow-up data were recorded prospectively. Structural valve deterioration (SVD) was defined by strict echocardiographic assessment. The mean follow-up period was 8.6 ± 5.5 years, for a total of 1269 valve-years. Operative mortality rate was 2.0%. Fifty-one late deaths occurred (linearized rate 4.0% per valve-year). Actuarial survival rates averaged 70 ± 4%, 53 ± 6% and 31 ± 7% after 10, 15 and 20 years of follow-up, respectively. Actuarial freedom from SVD at 10, 15 and 20 years was 78 ± 5%, 47 ± 7% and 19 ± 7%, respectively. Reoperation was associated with no operative mortality. Actuarial freedom from reoperation due to SVD at 10, 15 and 20 years was 82 ± 4%, 50 ± 6% and 25 ± 8%, respectively. Competing risk analysis demonstrated an actual risk of explantation secondary to SVD at 20 years of 44 ± 5%. Expected valve durability was 14.2 years for this age group. In the selected patients aged 65 years or younger undergoing mitral valve replacement with a pericardial bioprosthesis, the expected valve durability was 14.2 years. Reoperation for SVD was associated with a low risk of mortality. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Apathy, but not depression, is associated with executive dysfunction in cerebral small vessel disease

PubMed Central

Hollocks, Matthew J.; Morris, Robin G.; Markus, Hugh S.

2017-01-01

Objective To determine the prevalence of apathy and depression in cerebral small vessel disease (SVD), and the relationships between both apathy and depression with cognition. To examine whether apathy is specifically related to impairment in executive functioning and processing speed. Methods 196 patients with a clinical lacunar stroke and an anatomically corresponding lacunar infarct on MRI were compared to 300 stroke-free controls. Apathy and depression were measured using the Geriatric Depression Scale, and cognitive functioning was assessed using an SVD cognitive screening tool, the Brief Memory and Executive Test, which measures executive functioning/processing speed and memory/orientation. Path analysis and binary logistic regression were used to assess the relation between apathy, depression and cognitive impairment. Results 31 participants with SVD (15.8%) met criteria for apathy only, 23 (11.8%) for both apathy and depression, and 2 (1.0%) for depression only. In the SVD group the presence of apathy was related to global cognition, and specifically to impaired executive functioning/processing speed, but not memory/orientation. The presence of depression was not related to global cognition, impaired executive functioning/processing speed or memory/orientation. Conclusions Apathy is a common feature of SVD and is associated with impaired executive functioning/processing speed suggesting the two may share biological mechanisms. Screening for apathy should be considered in SVD, and further work is required to develop and evaluate effective apathy treatment or management in SVD. PMID:28493898

High amount of dietary fiber not harmful but favorable for Crohn disease.

PubMed

Chiba, Mitsuro; Tsuji, Tsuyotoshi; Nakane, Kunio; Komatsu, Masafumi

2015-01-01

Current chronic diseases are a reflection of the westernized diet that features a decreased consumption of dietary fiber. Indigestible dietary fiber is metabolized by gut bacteria, including Faecalibacterium prausnitzii, to butyrate, which has a critical role in colonic homeostasis owing to a variety of functions. Dietary fiber intake has been significantly inversely associated with the risk of chronic diseases. Crohn disease (CD) is not an exception. However, even authors who reported the inverse association between dietary fiber and a risk of CD made no recommendation of dietary fiber intake to CD patients. Some correspondence was against advocating high fiber intake in CD. We initiated a semivegetarian diet (SVD), namely a lacto-ovo-vegetarian diet, for patients with inflammatory bowel disease. Our SVD contains 32.4 g of dietary fiber in 2000 kcal. There was no untoward effect of the SVD. The remission rate with combined infliximab and SVD for newly diagnosed CD patients was 100%. Maintenance of remission on SVD without scheduled maintenance therapy with biologic drugs was 92% at 2 years. These excellent short- and long-term results can be explained partly by SVD. The fecal bacterial count of F prausnitzii in patients with CD is significantly lower than in healthy controls. Diet reviews recommend plant-based diets to treat and to prevent a variety of chronic diseases. SVD belongs to plant-based diets that inevitably contain considerable amounts of dietary fiber. Our clinical experience and available data provide a rationale to recommend a high fiber intake to treat CD.

Blood-brain barrier dysfunction and cerebral small vessel disease (arteriolosclerosis) in brains of older people.

PubMed

Bridges, Leslie R; Andoh, Joycelyn; Lawrence, Andrew J; Khoong, Cheryl H L; Poon, Wayne; Esiri, Margaret M; Markus, Hugh S; Hainsworth, Atticus H

2014-11-01

The blood-brain barrier protects brain tissue from potentially harmful plasma components. Small vessel disease (SVD; also termed arteriolosclerosis) is common in the brains of older people and is associated with lacunar infarcts, leukoaraiosis, and vascular dementia. To determine whether plasma extravasation is associated with SVD, we immunolabeled the plasma proteins fibrinogen and immunoglobulin G, which are assumed to reflect blood-brain barrier dysfunction, in deep gray matter (DGM; anterior caudate-putamen) and deep subcortical white matter (DWM) in the brains of a well-characterized cohort of donated brains with minimal Alzheimer disease pathology (Braak Stages 0-II) (n = 84; aged 65 years or older). Morphometric measures of fibrinogen labeling were compared between people with neuropathologically defined SVD and aged control subjects. Parenchymal cellular labeling with fibrinogen and immunoglobulin G was detectable in DGM and DWM in many subjects (>70%). Quantitative measures of fibrinogen were not associated with SVD in DGM or DWM; SVD severity was correlated between DGM and DWM (p < 0.0001). Fibrinogen in DGM showed a modest association with a history of hypertension; DWM fibrinogen was associated with dementia and cerebral amyloid angiopathy (all p < 0.05). In DWM, SVD was associated with leukoaraiosis identified in life (p < 0.05), but fibrinogen was not. Our data suggest that, in aged brains, plasma extravasation and hence local blood-brain barrier dysfunction are common but do not support an association with SVD.

Age-Specific Associations of Renal Impairment With Magnetic Resonance Imaging Markers of Cerebral Small Vessel Disease in Transient Ischemic Attack and Stroke

PubMed Central

Liu, Bian; Lau, Kui Kai; Li, Linxin; Lovelock, Caroline; Liu, Ming; Kuker, Wilhelm

2018-01-01

Background and Purpose— It has been hypothesized that cerebral small vessel disease (SVD) and chronic renal impairment may be part of a multisystem small-vessel disorder, but their association may simply be as a result of shared risk factors (eg, hypertension) rather than to a systemic susceptibility to premature SVD. However, most previous studies were hospital based, most had inadequate adjustment for hypertension, many were confined to patients with lacunar stroke, and none stratified by age. Methods— In a population-based study of transient ischemic attack and ischemic stroke (OXVASC [Oxford Vascular Study]), we evaluated the magnetic resonance imaging markers of cerebral SVD, including lacunes, white matter hyperintensities, cerebral microbleeds, and enlarged perivascular space. We studied the age-specific associations of renal impairment (estimated glomerular filtration rate <60 mL/min per 1.73 m2) and total SVD burden (total SVD score) adjusting for age, sex, vascular risk factors, and premorbid blood pressure (mean blood pressure during 15 years preevent). Results— Of 1080 consecutive patients, 1028 (95.2%) had complete magnetic resonance imaging protocol and creatinine measured at baseline. Renal impairment was associated with total SVD score (odds ratio [OR], 2.16; 95% confidence interval [CI], 1.69–2.75; P<0.001), but only at age <60 years (<60 years: OR, 3.97; 95% CI, 1.69–9.32; P=0.002; 60–79 years: OR, 1.01; 95% CI, 0.72–1.41; P=0.963; ≥80 years: OR, 0.95; 95% CI, 0.59–1.54; P=0.832). The overall association of renal impairment and total SVD score was also attenuated after adjustment for age, sex, history of hypertension, diabetes mellitus, and premorbid average systolic blood pressure (adjusted OR, 0.76; 95% CI, 0.56–1.02; P=0.067), but the independent association of renal impairment and total SVD score at age <60 years was maintained (adjusted OR, 3.11; 95% CI, 1.21–7.98; P=0.018). Associations of renal impairment and SVD were consistent for each SVD marker at age <60 years but were strongest for cerebral microbleeds (OR, 5.84; 95% CI, 1.45–23.53; P=0.013) and moderate–severe periventricular white matter hyperintensities (OR, 6.28; 95% CI, 1.54–25.63; P=0.010). Conclusions— The association of renal impairment and cerebral SVD was attenuated with adjustment for shared risk factors at older ages, but remained at younger ages, consistent with a shared susceptibility to premature disease. PMID:29523652

Drug-coated balloons for de novo lesions in small coronary arteries: rationale and design of BASKET-SMALL 2.

PubMed

Gilgen, Nicole; Farah, Ahmed; Scheller, Bruno; Ohlow, Marc-Alexander; Mangner, Norman; Weilenmann, Daniel; Wöhrle, Jochen; Jamshidi, Peiman; Leibundgut, Gregor; Möbius-Winkler, Sven; Zweiker, Robert; Krackhardt, Florian; Butter, Christian; Bruch, Leonhard; Kaiser, Christoph; Hoffmann, Andreas; Rickenbacher, Peter; Mueller, Christian; Stephan, Frank-Peter; Coslovsky, Michael; Jeger, Raban

2018-05-01

The treatment of coronary small vessel disease (SVD) remains an unresolved issue. Drug-eluting stents (DES) have limited efficacy due to increased rates of instent-restenosis, mainly caused by late lumen loss. Drug-coated balloons (DCB) are a promising technique because native vessels remain structurally unchanged. Basel Stent Kosten-Effektivitäts Trial: Drug-Coated Balloons vs. Drug-Eluting Stents in Small Vessel Interventions (BASKET-SMALL 2) is a multicenter, randomized, controlled, noninferiority trial of DCB vs DES in native SVD for clinical endpoints. Seven hundred fifty-eight patients with de novo lesions in vessels <3 mm in diameter and an indication for percutaneous coronary intervention such as stable angina pectoris, silent ischemia, or acute coronary syndromes are randomized 1:1 to angioplasty with DCB vs implantation of a DES after successful initial balloon angioplasty. The primary endpoint is the combination of cardiac death, nonfatal myocardial infarction, and target-vessel revascularization up to 1 year. Secondary endpoints include stent thrombosis, Bleeding Academic Research Consortium (BARC) type 3 to 5 bleeding, and long-term outcome up to 3 years. Based on clinical endpoints after 1 year, we plan to assess the noninferiority of DCB compared to DES in patients undergoing primary percutaneous coronary intervention for SVD. Results will be available in the second half of 2018. This study will compare DCB and DES regarding long-term safety and efficacy for the treatment of SVD in a large all-comer population. © 2018 The Authors. Clinical Cardiology published by Wiley Periodicals, Inc.

Gene expression suggests spontaneously hypertensive rats may have altered metabolism and reduced hypoxic tolerance.

PubMed

Ritz, Marie-Françoise; Grond-Ginsbach, Caspar; Engelter, Stefan; Lyrer, Philippe

2012-02-01

Cerebral small vessel disease (SVD) is an important cause of stroke, cognitive decline and vascular dementia (VaD). It is associated with diffuse white matter abnormalities and small deep cerebral ischemic infarcts. The molecular mechanisms involved in the development and progression of SVD are unclear. As hypertension is a major risk factor for developing SVD, Spontaneously Hypertensive Rats (SHR) are considered an appropriate experimental model for SVD. Prior work suggested an imbalance between the number of blood microvessels and astrocytes at the level of the neurovascular unit in 2-month-old SHR, leading to neuronal hypoxia in the brain of 9-month-old animals. To identify genes and pathways involved in the development of SVD, we compared the gene expression profile in the cortex of 2 and 9-month-old of SHR with age-matched normotensive Wistar Kyoto (WKY) rats using microarray-based technology. The results revealed significant differences in expression of genes involved in energy and lipid metabolisms, mitochondrial functions, oxidative stress and ischemic responses between both groups. These results strongly suggest that SHR suffer from chronic hypoxia, and therefore are unable to tolerate ischemia-like conditions, and are more vulnerable to high-energy needs than WKY. This molecular analysis gives new insights about pathways accounting for the development of SVD.

Pistachio (Pistacia vera L.) is a new natural host of Hop stunt viroid.

PubMed

Elleuch, Amine; Hamdi, Imen; Ellouze, Olfa; Ghrab, Mohamed; Fkahfakh, Hatem; Drira, Noureddine

2013-10-01

Besides hop, Hop stunt viroid (HpSVd) infects many woody species including grapevine, citrus, peach, plum, apricot, almond, pomegranate, mulberry and jujube. Here, we report the first detection of HpSVd in pistachio (Pistacia vera L.). Samples corresponding to 16 pistachio cultivars were obtained from a nearby almond collection. From these samples, low molecular weight RNAs were extracted for double polyacrylamide gel electrophoresis, northern-blot analysis and reverse transcription polymerase chain reaction assays. HpSVd was detected in 4 of the 16 pistachio cultivars in the first year and in 6 in the second, being also detected in the almond collection. Examination of the nucleotide sequences of pistachio and almond isolates revealed 13 new sequence variants. Sequences from pistachio shared 92-96 % similarity with the first reported HpSVd sequence (GenBank X00009), and multiple alignment and phylogenetic analyses showed that one pistachio isolate (HpSVdPis67Jabari) clustered with the plum group, whereas all the others clustered with the hop, and the recombinants plum-citrus and plum-Hop/cit3 groups. By identifying pistachio as a new natural host, we confirm that HpSVd is an ubiquitous and genetically variable viroid that infects many different fruit trees cultivated worldwide.

STEADFAST: Psychotherapeutic Intervention Improves Postural Strategy of Somatoform Vertigo and Dizziness

PubMed Central

Best, Christoph; Tschan, Regine; Stieber, Nikola; Beutel, Manfred E.; Eckhardt-Henn, Annegret; Dieterich, Marianne

2015-01-01

Patients with somatoform vertigo and dizziness (SVD) disorders often report instability of stance or gait and fear of falling. Posturographic measurements indeed indicated a pathological postural strategy. Our goal was to evaluate the effectiveness of a psychotherapeutic and psychoeducational short-term intervention (PTI) using static posturography and psychometric examination. Seventeen SVD patients took part in the study. The effects of PTI on SVD were evaluated with quantitative static posturography. As primary endpoint a quotient characterizing the relation between horizontal and vertical sway was calculated (Q H/V), reflecting the individual postural strategy. Results of static posturography were compared to those of age- and gender-matched healthy volunteers (n = 28); baseline measurements were compared to results after PTI. The secondary endpoint was the participation-limiting consequences of SVD as measured by the Vertigo Handicap Questionnaire (VHQ). Compared to the healthy volunteers, the patients with SVD showed a postural strategy characterized by stiffening-up that resulted in a significantly reduced body sway quotient before PTI (patients: Q H/V = 0.31 versus controls: Q H/V = 0.38; p = 0.022). After PTI the postural behavior normalized, and psychological distress was reduced. PTI therefore appears to modify pathological balance behaviour. The postural strategy of patients with SVD possibly results from anxious anticipatory cocontraction of the antigravity muscles. PMID:26843786

STEADFAST: Psychotherapeutic Intervention Improves Postural Strategy of Somatoform Vertigo and Dizziness.

PubMed

Best, Christoph; Tschan, Regine; Stieber, Nikola; Beutel, Manfred E; Eckhardt-Henn, Annegret; Dieterich, Marianne

2015-01-01

Patients with somatoform vertigo and dizziness (SVD) disorders often report instability of stance or gait and fear of falling. Posturographic measurements indeed indicated a pathological postural strategy. Our goal was to evaluate the effectiveness of a psychotherapeutic and psychoeducational short-term intervention (PTI) using static posturography and psychometric examination. Seventeen SVD patients took part in the study. The effects of PTI on SVD were evaluated with quantitative static posturography. As primary endpoint a quotient characterizing the relation between horizontal and vertical sway was calculated (Q H/V ), reflecting the individual postural strategy. Results of static posturography were compared to those of age- and gender-matched healthy volunteers (n = 28); baseline measurements were compared to results after PTI. The secondary endpoint was the participation-limiting consequences of SVD as measured by the Vertigo Handicap Questionnaire (VHQ). Compared to the healthy volunteers, the patients with SVD showed a postural strategy characterized by stiffening-up that resulted in a significantly reduced body sway quotient before PTI (patients: Q H/V = 0.31 versus controls: Q H/V = 0.38; p = 0.022). After PTI the postural behavior normalized, and psychological distress was reduced. PTI therefore appears to modify pathological balance behaviour. The postural strategy of patients with SVD possibly results from anxious anticipatory cocontraction of the antigravity muscles.

High Amount of Dietary Fiber Not Harmful But Favorable for Crohn Disease

PubMed Central

Chiba, Mitsuro; Tsuji, Tsuyotoshi; Nakane, Kunio; Komatsu, Masafumi

2015-01-01

Current chronic diseases are a reflection of the westernized diet that features a decreased consumption of dietary fiber. Indigestible dietary fiber is metabolized by gut bacteria, including Faecalibacterium prausnitzii, to butyrate, which has a critical role in colonic homeostasis owing to a variety of functions. Dietary fiber intake has been significantly inversely associated with the risk of chronic diseases. Crohn disease (CD) is not an exception. However, even authors who reported the inverse association between dietary fiber and a risk of CD made no recommendation of dietary fiber intake to CD patients. Some correspondence was against advocating high fiber intake in CD. We initiated a semivegetarian diet (SVD), namely a lacto-ovo-vegetarian diet, for patients with inflammatory bowel disease. Our SVD contains 32.4 g of dietary fiber in 2000 kcal. There was no untoward effect of the SVD. The remission rate with combined infliximab and SVD for newly diagnosed CD patients was 100%. Maintenance of remission on SVD without scheduled maintenance therapy with biologic drugs was 92% at 2 years. These excellent short- and long-term results can be explained partly by SVD. The fecal bacterial count of F prausnitzii in patients with CD is significantly lower than in healthy controls. Diet reviews recommend plant-based diets to treat and to prevent a variety of chronic diseases. SVD belongs to plant-based diets that inevitably contain considerable amounts of dietary fiber. Our clinical experience and available data provide a rationale to recommend a high fiber intake to treat CD. PMID:25663207

Learning overcomplete representations from distributed data: a brief review

NASA Astrophysics Data System (ADS)

Raja, Haroon; Bajwa, Waheed U.

2016-05-01

Most of the research on dictionary learning has focused on developing algorithms under the assumption that data is available at a centralized location. But often the data is not available at a centralized location due to practical constraints like data aggregation costs, privacy concerns, etc. Using centralized dictionary learning algorithms may not be the optimal choice in such settings. This motivates the design of dictionary learning algorithms that consider distributed nature of data as one of the problem variables. Just like centralized settings, distributed dictionary learning problem can be posed in more than one way depending on the problem setup. Most notable distinguishing features are the online versus batch nature of data and the representative versus discriminative nature of the dictionaries. In this paper, several distributed dictionary learning algorithms that are designed to tackle different problem setups are reviewed. One of these algorithms is cloud K-SVD, which solves the dictionary learning problem for batch data in distributed settings. One distinguishing feature of cloud K-SVD is that it has been shown to converge to its centralized counterpart, namely, the K-SVD solution. On the other hand, no such guarantees are provided for other distributed dictionary learning algorithms. Convergence of cloud K-SVD to the centralized K-SVD solution means problems that are solvable by K-SVD in centralized settings can now be solved in distributed settings with similar performance. Finally, cloud K-SVD is used as an example to show the advantages that are attainable by deploying distributed dictionary algorithms for real world distributed datasets.

Association of postural instability with asymptomatic cerebrovascular damage and cognitive decline: the Japan Shimanami health promoting program study.

PubMed

Tabara, Yasuharu; Okada, Yoko; Ohara, Maya; Uetani, Eri; Kido, Tomoko; Ochi, Namiko; Nagai, Tokihisa; Igase, Michiya; Miki, Tetsuro; Matsuda, Fumihiko; Kohara, Katsuhiko

2015-01-01

Asymptomatic cerebral small-vessel disease (cSVD) in elderly individuals are potent risk factors for stroke. In addition to common clinical risk factors, postural instability has been postulated to be associated with cSVD in older frail patients. Here, we conducted a cross-sectional study to understand the possible link between postural instability and asymptomatic cSVD further, namely periventricular hyperintensity, lacunar infarction, and microbleeds, as well as cognitive function, in a middle-aged to elderly general population (n=1387). Postural instability was assessed based on one-leg standing time (OLST) and posturography findings. cSVD was evaluated by brain MRI. Mild cognitive impairment was assessed using a computer-based questionnaire, and carotid intima-media thickness as an index of atherosclerosis was measured via ultrasonography. Frequency of short OLST, in particular <20 s, increased linearly with severity of cSVD (lacunar infarction lesion: none, 9.7%; 1, 16.0%; >2, 34.5%; microbleeds lesion: none, 10.1%; 1, 15.3%; >2, 30.0%; periventricular hyperintensity grade: 0, 5.7%; 1, 11.5%; >2, 23.7%). The association of short OLST with lacunar infarction and microbleeds but not periventricular hyperintensity remained significant even after adjustment for possible covariates (lacunar infarction, P=0.009; microbleeds, P=0.003; periventricular hyperintensity, P=0.601). In contrast, no significant association was found between posturographic parameters and cSVD, whereas these parameters were linearly associated with OLST. Short OLST was also significantly associated with reduced cognitive function independent of covariates, including cSVD (P=0.002). Postural instability was found to be associated with early pathological changes in the brain and functional decline, even in apparently healthy subjects. © 2014 American Heart Association, Inc.

Characterization of Heterozygous HTRA1 Mutations in Taiwanese Patients With Cerebral Small Vessel Disease.

PubMed

Lee, Yi-Chung; Chung, Chih-Ping; Chao, Nai-Chen; Fuh, Jong-Ling; Chang, Feng-Chi; Soong, Bing-Wing; Liao, Yi-Chu

2018-07-01

Homozygous and compound heterozygous mutations in the high temperature requirement serine peptidase A1 gene ( HTRA1 ) cause cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy. However, heterozygous HTRA1 mutations were recently identified to be associated with autosomal dominant cerebral small vessel disease (SVD). The present study aims at investigating the clinical features, frequency, and spectrum of HTRA1 mutations in a Taiwanese cohort with SVD. Mutational analyses of HTRA1 were performed by Sanger sequencing in 222 subjects, selected from a cohort of 337 unrelated patients with SVD after excluding those harboring a NOTCH3 mutation. The influence of these mutations on HTRA1 protease activities was characterized. Seven novel heterozygous mutations in HTRA1 were identified, including p.Gly120Asp, p.Ile179Asn, p.Ala182Profs*33, p.Ile256Thr, p.Gly276Ala, p.Gln289Ter, and p.Asn324Thr, and each was identified in 1 single index patient. All mutations significantly compromise the HTRA1 protease activities. For the 7 index cases and another 2 affected siblings carrying a heterozygous HTRA1 mutation, the common clinical presentations include lacunar infarction, intracerebral hemorrhage, cognitive decline, and spondylosis at the fifth to sixth decade of life. Among the 9 patients, 4 have psychiatric symptoms as delusion, depression, and compulsive behavior, 3 have leukoencephalopathy in anterior temporal poles, and 2 patients have alopecia. Heterozygous HTRA1 mutations account for 2.08% (7 of 337) of SVD in Taiwan. The clinical and neuroradiological features of HTRA1 -related SVD and sporadic SVD are similar. These findings broaden the mutational spectrum of HTRA1 and highlight the pathogenic role of heterozygous HTRA1 mutations in SVD. © 2018 American Heart Association, Inc.

UTM TCL 2.0 Software Version Description (SVD) Document

NASA Technical Reports Server (NTRS)

Mcguirk, Patrick

2017-01-01

This is the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) Technical Capability Level(TCL) 2.0 Software Version Description (SVD) document. This UTM TCL 2.0 SVD describes the following four topics: 1. Software Release Contents: A listing of the files comprising this release 2. Installation Instructions: How to install the release and get it running 3. Changes Since Previous Release: General updates since the previous UTM release 4. Known Issues: Known issues and limitations in this release

A robust indicator based on singular value decomposition for flaw feature detection from noisy ultrasonic signals

NASA Astrophysics Data System (ADS)

Cui, Ximing; Wang, Zhe; Kang, Yihua; Pu, Haiming; Deng, Zhiyang

2018-05-01

Singular value decomposition (SVD) has been proven to be an effective de-noising tool for flaw echo signal feature detection in ultrasonic non-destructive evaluation (NDE). However, the uncertainty in the arbitrary manner of the selection of an effective singular value weakens the robustness of this technique. Improper selection of effective singular values will lead to bad performance of SVD de-noising. What is more, the computational complexity of SVD is too large for it to be applied in real-time applications. In this paper, to eliminate the uncertainty in SVD de-noising, a novel flaw indicator, named the maximum singular value indicator (MSI), based on short-time SVD (STSVD), is proposed for flaw feature detection from a measured signal in ultrasonic NDE. In this technique, the measured signal is first truncated into overlapping short-time data segments to put feature information of a transient flaw echo signal in local field, and then the MSI can be obtained from the SVD of each short-time data segment. Research shows that this indicator can clearly indicate the location of ultrasonic flaw signals, and the computational complexity of this STSVD-based indicator is significantly reduced with the algorithm proposed in this paper. Both simulation and experiments show that this technique is very efficient for real-time application in flaw detection from noisy data.

Image fusion via nonlocal sparse K-SVD dictionary learning.

PubMed

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

NASA Technical Reports Server (NTRS)

Johnson, Marty E.; Lalime, Aimee L.; Grosveld, Ferdinand W.; Rizzi, Stephen A.; Sullivan, Brenda M.

2003-01-01

Applying binaural simulation techniques to structural acoustic data can be very computationally intensive as the number of discrete noise sources can be very large. Typically, Head Related Transfer Functions (HRTFs) are used to individually filter the signals from each of the sources in the acoustic field. Therefore, creating a binaural simulation implies the use of potentially hundreds of real time filters. This paper details two methods of reducing the number of real-time computations required by: (i) using the singular value decomposition (SVD) to reduce the complexity of the HRTFs by breaking them into dominant singular values and vectors and (ii) by using equivalent source reduction (ESR) to reduce the number of sources to be analyzed in real-time by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. The ESR and SVD reduction methods can be combined to provide an estimated computation time reduction of 99.4% for the structural acoustic data tested. In addition, preliminary tests have shown that there is a 97% correlation between the results of the combined reduction methods and the results found with the current binaural simulation techniques

Variability common to global sea surface temperatures and runoff in the conterminous United States

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.

2014-01-01

Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.

Cerebral small vessel disease: Capillary pathways to stroke and cognitive decline

PubMed Central

Engedal, Thorbjørn S; Moreton, Fiona; Hansen, Mikkel B; Wardlaw, Joanna M; Dalkara, Turgay; Markus, Hugh S; Muir, Keith W

2015-01-01

Cerebral small vessel disease (SVD) gives rise to one in five strokes worldwide and constitutes a major source of cognitive decline in the elderly. SVD is known to occur in relation to hypertension, diabetes, smoking, radiation therapy and in a range of inherited and genetic disorders, autoimmune disorders, connective tissue disorders, and infections. Until recently, changes in capillary patency and blood viscosity have received little attention in the aetiopathogenesis of SVD and the high risk of subsequent stroke and cognitive decline. Capillary flow patterns were, however, recently shown to limit the extraction efficacy of oxygen in tissue and capillary dysfunction therefore proposed as a source of stroke-like symptoms and neurodegeneration, even in the absence of physical flow-limiting vascular pathology. In this review, we examine whether capillary flow disturbances may be a shared feature of conditions that represent risk factors for SVD. We then discuss aspects of capillary dysfunction that could be prevented or alleviated and therefore might be of general benefit to patients at risk of SVD, stroke or cognitive decline. PMID:26661176

Solar variability datalogger

DOE PAGES

Lave, Matthew; Stein, Joshua; Smith, Ryan

2016-07-28

To address the lack of knowledge of local solar variability, we have developed and deployed a low-cost solar variability datalogger (SVD). While most currently used solar irradiance sensors are expensive pyranometers with high accuracy (relevant for annual energy estimates), low-cost sensors display similar precision (relevant for solar variability) as high-cost pyranometers, even if they are not as accurate. In this work, we present evaluation of various low-cost irradiance sensor types, describe the SVD, and present validation and comparison of the SVD collected data. In conclusion, the low cost and ease of use of the SVD will enable a greater understandingmore » of local solar variability, which will reduce developer and utility uncertainty about the impact of solar photovoltaic (PV) installations and thus will encourage greater penetrations of solar energy.« less

Mnemonic function in small vessel disease and associations with white matter tract microstructure.

PubMed

Metoki, Athanasia; Brookes, Rebecca L; Zeestraten, Eva; Lawrence, Andrew J; Morris, Robin G; Barrick, Thomas R; Markus, Hugh S; Charlton, Rebecca A

2017-09-01

Cerebral small vessel disease (SVD) is associated with deficits in working memory, with a relative sparing of long-term memory; function may be influenced by white matter microstructure. Working and long-term memory were examined in 106 patients with SVD and 35 healthy controls. Microstructure was measured in the uncinate fasciculi and cingula. Working memory was more impaired than long-term memory in SVD, but both abilities were reduced compared to controls. Regression analyses found that having SVD explained the variance in memory functions, with additional variance explained by the cingula (working memory) and uncinate (long-term memory). Performance can be explained in terms of integrity loss in specific white matter tract associated with mnemonic functions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Simplified Radiographic Damage Index for Affected Joints in Chronic Gouty Arthritis

PubMed Central

2016-01-01

The aim of this study was to develop and validate a new radiographic damage scoring method (DAmagE index of GoUt; DAEGU) in chronic gout using plain radiography. Two independent observers scored foot x-rays from 15 patients with chronic gout according to the DAEGU method and the modified Sharp/van der Heijde (SvdH) method. The 10 metatarsophalangeal (MTP) and 2 interphalangeal (IP) joints of the first toes of both feet were scored to assess the degrees of erosion and joint space narrowing (JSN). The intraobserver and interobserver reliabilities were analyzed by calculating the intraclass correlation coefficient (ICC) and minimal detectable change (MDC). The correlation between the DAEGU and SvdH methods was analyzed by calculating the Spearman's rho correlation coefficients and Kappa coefficients. The DAEGU method was found to be highly reproducible (0.945–0.987 for the intraobserver and 0.993–0.996 for the interobserver ICC values). The erosion, JSN, and total scores exhibited strong positive correlations between the DAEGU and SvdH methods and also within each method (r = 0.860–0.969, P < 0.001 for all parameters). The DAEGU and SvdH methods were in very good agreement as determined by Kappa coefficient analysis [0.732 (0.387–1.000) for erosion and 1.000 (1.000–1.000) for JSN]. In conclusion, this study revealed that DAEGU method was a reliable and feasible tool in the assessment of radiographic damage in chronic gout. The DAEGU method may provide a more easy assessment of structural damage in chronic gout in the real clinical practice. PMID:26955246

SVD analysis of Aura TES spectral residuals

NASA Technical Reports Server (NTRS)

Beer, Reinhard; Kulawik, Susan S.; Rodgers, Clive D.; Bowman, Kevin W.

2005-01-01

Singular Value Decomposition (SVD) analysis is both a powerful diagnostic tool and an effective method of noise filtering. We present the results of an SVD analysis of an ensemble of spectral residuals acquired in September 2004 from a 16-orbit Aura Tropospheric Emission Spectrometer (TES) Global Survey and compare them to alternative methods such as zonal averages. In particular, the technique highlights issues such as the orbital variation of instrument response and incompletely modeled effects of surface emissivity and atmospheric composition.

Hemorrhage recurrence risk factors in cerebral amyloid angiopathy: Comparative analysis of the overall small vessel disease severity score versus individual neuroimaging markers.

PubMed

Boulouis, Gregoire; Charidimou, Andreas; Pasi, Marco; Roongpiboonsopit, Duangnapa; Xiong, Li; Auriel, Eitan; van Etten, Ellis S; Martinez-Ramirez, Sergi; Ayres, Alison; Vashkevich, Anastasia; Schwab, Kristin M; Rosand, Jonathan; Goldstein, Joshua N; Gurol, M Edip; Greenberg, Steven M; Viswanathan, Anand

2017-09-15

An MRI-based score of total small vessel disease burden (CAA-SVD-Score) in cerebral amyloid angiopathy (CAA) has been demonstrated to correlate with severity of pathologic changes. Evidence suggests that CAA-related intracerebral hemorrhage (ICH) recurrence risk is associated with specific disease imaging manifestations rather than overall severity. We compared the correlation between the CAA-SVD-Score with the risk of recurrent CAA-related lobar ICH versus the predictive role of each of its components. Consecutive patients with CAA-related ICH from a single-center prospective cohort were analyzed. Radiological markers of CAA related SVD damage were quantified and categorized according to the CAA-SVD-Score (0-6 points). Subjects were followed prospectively for recurrent symptomatic ICH. Adjusted Cox proportional hazards models were used to investigate associations between the CAA-SVD-Score as well as each of the individual MRI signatures of CAA and the risk of recurrent ICH. In 229 CAA patients with ICH, a total of 56 recurrent ICH events occurred during a median follow-up of 2.8years [IQR 0.9-5.4years, 781 person-years). Higher CAA-SVD-Score (HR=1.26 per additional point, 95%CI [1.04-1.52], p=0.015) and older age were independently associated with higher ICH recurrence risk. Analysis of individual markers of CAA showed that CAA-SVD-Score findings were due to the independent effect of disseminated superficial siderosis (HR for disseminated cSS vs none: 2.89, 95%CI [1.47-5.5], p=0.002) and high degree of perivascular spaces enlargement (RR=3.50-95%CI [1.04-21], p=0.042). In lobar CAA-ICH patients, higher CAA-SVD-Score does predict recurrent ICH. Amongst individual elements of the score, superficial siderosis and dilated perivascular spaces are the only markers independently associated with ICH recurrence, contributing to the evidence for distinct CAA phenotypes singled out by neuro-imaging manifestations. Copyright © 2017 Elsevier B.V. All rights reserved.

Subvalvular Pannus Overgrowth after Mosaic Bioprosthesis Implantation in the Aortic Position

PubMed Central

Isomura, Tadashi; Yoshida, Minoru; Katsumata, Chieko; Ito, Fusahiko; Watanabe, Masazumi

2015-01-01

Purpose: Although pannus overgrowth by itself was not the pathology of structural valve deterioration (SVD), it might be related to reoperation for SVD of the bioprostheses. Methods: We retrospectively reviewed patients undergoing reoperation for SVD after implantation of the third-generation Mosaic aortic bioprosthesis and macroscopic appearance of the explanted valves was examined to detect the presence of pannus. Results: There were 10 patients and the age for the initial aortic valve replacement was 72 ± 10 years old. The duration of durability was 9.9 ± 2.0 years. Deteriorated valve presented stenosis (valvular area of 0.96 ± 0.20 cm2; pressure gradient of 60 ± 23 mmHg). Coexisting regurgitant flow was detected in two cases. Macroscopically, subvalvular pannus overgrowth was detected in 8 cases (80%). The proportion of overgrowth from the annulus was almost even and pannus overgrowth created subvalvular membrane, which restricted the area especially for each commissure. In contrast, opening and mobility of each leaflet was not severely limited and pannus overgrowth would restrict the area, especially for each commissure. In other two cases with regurgitation, tear of the leaflet on the stent strut was detected and mild calcification of each leaflet restricted opening. Conclusion: In patients with the Mosaic aortic bioprosthesis, pannus overgrowth was the major cause for reoperation. PMID:26633541

Subvalvular Pannus Overgrowth after Mosaic Bioprosthesis Implantation in the Aortic Position.

PubMed

Hirota, Masanori; Isomura, Tadashi; Yoshida, Minoru; Katsumata, Chieko; Ito, Fusahiko; Watanabe, Masazumi

2016-01-01

Although pannus overgrowth by itself was not the pathology of structural valve deterioration (SVD), it might be related to reoperation for SVD of the bioprostheses. We retrospectively reviewed patients undergoing reoperation for SVD after implantation of the third-generation Mosaic aortic bioprosthesis and macroscopic appearance of the explanted valves was examined to detect the presence of pannus. There were 10 patients and the age for the initial aortic valve replacement was 72 ± 10 years old. The duration of durability was 9.9 ± 2.0 years. Deteriorated valve presented stenosis (valvular area of 0.96 ± 0.20 cm(2); pressure gradient of 60 ± 23 mmHg). Coexisting regurgitant flow was detected in two cases. Macroscopically, subvalvular pannus overgrowth was detected in 8 cases (80%). The proportion of overgrowth from the annulus was almost even and pannus overgrowth created subvalvular membrane, which restricted the area especially for each commissure. In contrast, opening and mobility of each leaflet was not severely limited and pannus overgrowth would restrict the area, especially for each commissure. In other two cases with regurgitation, tear of the leaflet on the stent strut was detected and mild calcification of each leaflet restricted opening. In patients with the Mosaic aortic bioprosthesis, pannus overgrowth was the major cause for reoperation.

Rapid surface defect detection based on singular value decomposition using steel strips as an example

NASA Astrophysics Data System (ADS)

Sun, Qianlai; Wang, Yin; Sun, Zhiyi

2018-05-01

For most surface defect detection methods based on image processing, image segmentation is a prerequisite for determining and locating the defect. In our previous work, a method based on singular value decomposition (SVD) was used to determine and approximately locate surface defects on steel strips without image segmentation. For the SVD-based method, the image to be inspected was projected onto its first left and right singular vectors respectively. If there were defects in the image, there would be sharp changes in the projections. Then the defects may be determined and located according sharp changes in the projections of each image to be inspected. This method was simple and practical but the SVD should be performed for each image to be inspected. Owing to the high time complexity of SVD itself, it did not have a significant advantage in terms of time consumption over image segmentation-based methods. Here, we present an improved SVD-based method. In the improved method, a defect-free image is considered as the reference image which is acquired under the same environment as the image to be inspected. The singular vectors of each image to be inspected are replaced by the singular vectors of the reference image, and SVD is performed only once for the reference image off-line before detecting of the defects, thus greatly reducing the time required. The improved method is more conducive to real-time defect detection. Experimental results confirm its validity.

The Study of Fault Lineament Pattern of the Lamongan Volcanic Field Using Gravity Data

NASA Astrophysics Data System (ADS)

Aziz, K. N.; Hartantyo, E.; Niasari, S. W.

2018-04-01

Lamongan Volcano located in Tiris, East Java, possesses geothermal potential energy. The geothermal potential was indicated by the presence of geothermal manifestations such as hot springs. We usedsecondary gravity data from GGMplus. The result of gravity anomaly map shows that there is the lowest gravity anomaly in the center of the study area coinciding with the hot spring location. Gravity data were analyzed using SVD method to identify fault structures. It controls the geothermal fluid pathways. The result of this research shows thatthe type of fault in hot springsisanormal fault with direction NW-SE. The fault lineament pattern along maaris NW-SE.Maar indicates anormal fault. As the result we know that gravity data from GGMplus which analyzed with SVD can be used to determine the type and trend of fault.

Texture Analysis of T1-Weighted and Fluid-Attenuated Inversion Recovery Images Detects Abnormalities That Correlate With Cognitive Decline in Small Vessel Disease.

PubMed

Tozer, Daniel J; Zeestraten, Eva; Lawrence, Andrew J; Barrick, Thomas R; Markus, Hugh S

2018-06-04

Magnetic resonance imaging may be useful to assess disease severity in cerebral small vessel disease (SVD), identify those individuals who are most likely to progress to dementia, monitor disease progression, and act as surrogate markers to test new therapies. Texture analysis extracts information on the relationship between signal intensities of neighboring voxels. A potential advantage over techniques, such as diffusion tensor imaging, is that it can be used on clinically obtained magnetic resonance sequences. We determined whether texture parameters (TP) were abnormal in SVD, correlated with cognitive impairment, predicted cognitive decline, or conversion to dementia. In the prospective SCANS study (St George's Cognition and Neuroimaging in Stroke), we assessed TP in 121 individuals with symptomatic SVD at baseline, 99 of whom attended annual cognitive testing for 5 years. Conversion to dementia was recorded for all subjects during the 5-year period. Texture analysis was performed on fluid-attenuated inversion recovery and T1-weighted images. The TP obtained from the SVD cohort were cross-sectionally compared with 54 age-matched controls scanned on the same magnetic resonance imaging system. There were highly significant differences in several TP between SVD cases and controls. Within the SVD population, TP were highly correlated to other magnetic resonance imaging parameters (brain volume, white matter lesion volume, lacune count). TP correlated with executive function and global function at baseline and predicted conversion to dementia, after controlling for age, sex, premorbid intelligence quotient, and magnetic resonance parameters. TP, which can be obtained from routine clinical images, are abnormal in SVD, and the degree of abnormality correlates with executive dysfunction and global cognition at baseline and decline during 5 years. TP may be useful to assess disease severity in clinically collected data. This needs testing in data clinically acquired across multiple sites. © 2018 The Authors.

Image compression using singular value decomposition

NASA Astrophysics Data System (ADS)

Swathi, H. R.; Sohini, Shah; Surbhi; Gopichand, G.

2017-11-01

We often need to transmit and store the images in many applications. Smaller the image, less is the cost associated with transmission and storage. So we often need to apply data compression techniques to reduce the storage space consumed by the image. One approach is to apply Singular Value Decomposition (SVD) on the image matrix. In this method, digital image is given to SVD. SVD refactors the given digital image into three matrices. Singular values are used to refactor the image and at the end of this process, image is represented with smaller set of values, hence reducing the storage space required by the image. Goal here is to achieve the image compression while preserving the important features which describe the original image. SVD can be adapted to any arbitrary, square, reversible and non-reversible matrix of m × n size. Compression ratio and Mean Square Error is used as performance metrics.

Hyperhomocysteinemia Associates with Small Vessel Disease More Closely Than Large Vessel Disease

PubMed Central

Feng, Chao; Bai, Xue; Xu, Yu; Hua, Ting; Huang, Jing; Liu, Xue-Yuan

2013-01-01

Background: Hyperhomocysteinemia was believed to be an independent risk factor for stroke and associate with small vessel disease (SVD) related stroke and large vessel disease (LVD) related stroke differently. However it's still unclear which type of stroke associated with homocysteine (HCY) more strongly because the conclusions of previous studies were contradictory. In this study we focused on the subclinical angiopathies of stroke, i.e., SVD and LVD instead of stroke subtypes and sought to compare the associations between HCY level and different angiopathies. Methods: 324 non-stroke patients were enrolled. Sex, age, HCY level and other vascular risk factors were collected. MRI and angiographies were used to determine the type of angiopathies and their severity, i.e., the scores of leukoaraiosis (LA), plaques and numbers of silent brain infarctions (SBI). LVD was defined as the presence of atherosclerotic plaques of cerebral arteries. SVD was defined as the presence of either LA or SBI. 230 patients were deemed to have LVD; 180 patients were deemed to have SVD. Spearman's correlation test and logistic regression were used to analyze the association between HCY level and different angiopathies. Results: The correlation between HCY level and scores of plaques was weaker than that of the scores of LA and numbers of SBI. Hyperhomocysteinemia was an independent risk factor for SVD (OR = 1.315, P <0.001), whereas the association between HCY level and LVD was not that significant (OR = 1.058, P = 0.075). Conclusion: HCY level associated with SVD more strongly than LVD. PMID:23471237

Application of Texture Analysis to Study Small Vessel Disease and Blood-Brain Barrier Integrity.

PubMed

Valdés Hernández, Maria Del C; González-Castro, Victor; Chappell, Francesca M; Sakka, Eleni; Makin, Stephen; Armitage, Paul A; Nailon, William H; Wardlaw, Joanna M

2017-01-01

We evaluate the alternative use of texture analysis for evaluating the role of blood-brain barrier (BBB) in small vessel disease (SVD). We used brain magnetic resonance imaging from 204 stroke patients, acquired before and 20 min after intravenous gadolinium administration. We segmented tissues, white matter hyperintensities (WMH) and applied validated visual scores. We measured textural features in all tissues pre- and post-contrast and used ANCOVA to evaluate the effect of SVD indicators on the pre-/post-contrast change, Kruskal-Wallis for significance between patient groups and linear mixed models for pre-/post-contrast variations in cerebrospinal fluid (CSF) with Fazekas scores. Textural "homogeneity" increase in normal tissues with higher presence of SVD indicators was consistently more overt than in abnormal tissues. Textural "homogeneity" increased with age, basal ganglia perivascular spaces scores ( p  < 0.01) and SVD scores ( p  < 0.05) and was significantly higher in hypertensive patients ( p  < 0.002) and lacunar stroke ( p  = 0.04). Hypertension (74% patients), WMH load (median = 1.5 ± 1.6% of intracranial volume), and age (mean = 65.6 years, SD = 11.3) predicted the pre/post-contrast change in normal white matter, WMH, and index stroke lesion. CSF signal increased with increasing SVD post-contrast. A consistent general pattern of increasing textural "homogeneity" with increasing SVD and post-contrast change in CSF with increasing WMH suggest that texture analysis may be useful for the study of BBB integrity.

Characterization of anticancer agents by their growth inhibitory activity and relationships to mechanism of action and structure.

PubMed

Keskin, O; Bahar, I; Jernigan, R L; Beutler, J A; Shoemaker, R H; Sausville, E A; Covell, D G

2000-04-01

An analysis of the growth inhibitory potency of 122 anticancer agents available from the National Cancer Institute anticancer drug screen is presented. Methods of singular value decomposition (SVD) were applied to determine the matrix of distances between all compounds. These SVD-derived dissimilarity distances were used to cluster compounds that exhibit similar tumor growth inhibitory activity patterns against 60 human cancer cell lines. Cluster analysis divides the 122 standard agents into 25 statistically distinct groups. The first eight groups include structurally diverse compounds with reactive functionalities that act as DNA-damaging agents while the remaining 17 groups include compounds that inhibit nucleic acid biosynthesis and mitosis. Examination of the average activity patterns across the 60 tumor cell lines reveals unique 'fingerprints' associated with each group. A diverse set of structural features are observed for compounds within these groups, with frequent occurrences of strong within-group structural similarities. Clustering of cell types by their response to the 122 anticancer agents divides the 60 cell types into 21 groups. The strongest within-panel groupings were found for the renal, leukemia and ovarian cell panels. These results contribute to the basis for comparisons between log(GI(50)) screening patterns of the 122 anticancer agents and additional tested compounds.

Characterising the grey matter correlates of leukoaraiosis in cerebral small vessel disease.

PubMed

Lambert, Christian; Sam Narean, Janakan; Benjamin, Philip; Zeestraten, Eva; Barrick, Thomas R; Markus, Hugh S

2015-01-01

Cerebral small vessel disease (SVD) is a heterogeneous group of pathological disorders that affect the small vessels of the brain and are an important cause of cognitive impairment. The ischaemic consequences of this disease can be detected using MRI, and include white matter hyperintensities (WMH), lacunar infarcts and microhaemorrhages. The relationship between SVD disease severity, as defined by WMH volume, in sporadic age-related SVD and cortical thickness has not been well defined. However, regional cortical thickness change would be expected due to associated phenomena such as underlying ischaemic white matter damage, and the observation that widespread cortical thinning is observed in the related genetic condition CADASIL (Righart et al., 2013). Using MRI data, we have developed a semi-automated processing pipeline for the anatomical analysis of individuals with cerebral small vessel disease and applied it cross-sectionally to 121 subjects diagnosed with this condition. Using a novel combined automated white matter lesion segmentation algorithm and lesion repair step, highly accurate warping to a group average template was achieved. The volume of white matter affected by WMH was calculated, and used as a covariate of interest in a voxel-based morphometry and voxel-based cortical thickness analysis. Additionally, Gaussian Process Regression (GPR) was used to assess if the severity of SVD, measured by WMH volume, could be predicted from the morphometry and cortical thickness measures. We found significant (Family Wise Error corrected p < 0.05) volumetric decline with increasing lesion load predominately in the parietal lobes, anterior insula and caudate nuclei bilaterally. Widespread significant cortical thinning was found bilaterally in the dorsolateral prefrontal, parietal and posterio-superior temporal cortices. These represent distinctive patterns of cortical thinning and volumetric reduction compared to ageing effects in the same cohort, which exhibited greater changes in the occipital and sensorimotor cortices. Using GPR, the absolute WMH volume could be significantly estimated from the grey matter density and cortical thickness maps (Pearson's coefficients 0.80 and 0.75 respectively). We demonstrate that SVD severity is associated with regional cortical thinning. Furthermore a quantitative measure of SVD severity (WMH volume) can be predicted from grey matter measures, supporting an association between white and grey matter damage. The pattern of cortical thinning and volumetric decline is distinctive for SVD severity compared to ageing. These results, taken together, suggest that there is a phenotypic pattern of atrophy associated with SVD severity.

A nonlinear quality-related fault detection approach based on modified kernel partial least squares.

PubMed

Jiao, Jianfang; Zhao, Ning; Wang, Guang; Yin, Shen

2017-01-01

In this paper, a new nonlinear quality-related fault detection method is proposed based on kernel partial least squares (KPLS) model. To deal with the nonlinear characteristics among process variables, the proposed method maps these original variables into feature space in which the linear relationship between kernel matrix and output matrix is realized by means of KPLS. Then the kernel matrix is decomposed into two orthogonal parts by singular value decomposition (SVD) and the statistics for each part are determined appropriately for the purpose of quality-related fault detection. Compared with relevant existing nonlinear approaches, the proposed method has the advantages of simple diagnosis logic and stable performance. A widely used literature example and an industrial process are used for the performance evaluation for the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Constraint elimination in dynamical systems

NASA Technical Reports Server (NTRS)

Singh, R. P.; Likins, P. W.

1989-01-01

Large space structures (LSSs) and other dynamical systems of current interest are often extremely complex assemblies of rigid and flexible bodies subjected to kinematical constraints. A formulation is presented for the governing equations of constrained multibody systems via the application of singular value decomposition (SVD). The resulting equations of motion are shown to be of minimum dimension.

Qualitatively Assessing Randomness in SVD Results

NASA Astrophysics Data System (ADS)

Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

2012-12-01

Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

Perivascular spaces on 7 Tesla brain MRI are related to markers of small vessel disease but not to age or cardiovascular risk factors

PubMed Central

Zwanenburg, Jaco JM; Reinink, Rik; Wisse, Laura EM; Luijten, Peter R; Kappelle, L Jaap; Geerlings, Mirjam I; Biessels, Geert Jan

2016-01-01

Cerebral perivascular spaces (PVS) are small physiological structures around blood vessels in the brain. MRI visible PVS are associated with ageing and cerebral small vessel disease (SVD). 7 Tesla (7T) MRI improves PVS detection. We investigated the association of age, vascular risk factors, and imaging markers of SVD with PVS counts on 7 T MRI, in 50 persons aged ≥ 40. The average PVS count ± SD in the right hemisphere was 17 ± 6 in the basal ganglia and 71 ± 28 in the semioval centre. We observed no relation between age or vascular risk factors and PVS counts. The presence of microbleeds was related to more PVS in the basal ganglia (standardized beta 0.32; p = 0.04) and semioval centre (standardized beta 0.39; p = 0.01), and white matter hyperintensity volume to more PVS in the basal ganglia (standardized beta 0.41; p = 0.02). We conclude that PVS counts on 7T MRI are high and are related SVD markers, but not to age and vascular risk factors. This latter finding may indicate that due to the high sensitivity of 7T MRI, the correlation of PVS counts with age or vascular risk factors may be attenuated by the detection of “normal”, non-pathological PVS. PMID:27154503

Understanding the role of the perivascular space in cerebral small vessel disease.

PubMed

Brown, Rosalind; Benveniste, Helene; Black, Sandra E; Charpak, Serge; Dichgans, Martin; Joutel, Anne; Nedergaard, Maiken; Smith, Kenneth J; Zlokovic, Berislav V; Wardlaw, Joanna M

2018-05-02

Small vessel diseases are a group of disorders that result from pathological alteration of the small blood vessels in the brain, including the small arteries, capillaries and veins. Of the 35-36 million people that are estimated to suffer from dementia worldwide, up to 65% have an SVD component. Furthermore, SVD causes 20-25% of strokes, worsens outcome after stroke and is a leading cause of disability, cognitive impairment and poor mobility. Yet the underlying cause(s) of SVD are not fully understood.Magnetic resonance imaging (MRI) has confirmed enlarged perivascular spaces (PVS) as a hallmark feature of SVD. In healthy tissue, these spaces are proposed to form part of a complex brain fluid drainage system which supports interstitial fluid exchange and may also facilitate clearance of waste products from the brain. The pathophysiological signature of PVS, and what this infers about their function and interaction with cerebral microcirculation, plus subsequent downstream effects on lesion development in the brain has not been established. Here we discuss the potential of enlarged PVS to be a unique biomarker for SVD and related brain disorders with a vascular component. We propose that widening of PVS suggests presence of peri-vascular cell debris and other waste products that forms part of a vicious cycle involving impaired cerebrovascular reactivity (CVR), blood-brain barrier (BBB) dysfunction, perivascular inflammation and ultimately impaired clearance of waste proteins from the interstitial fluid (ISF) space, leading to accumulation of toxins, hypoxia and tissue damage.Here, we outline current knowledge, questions and hypotheses regarding understanding the brain fluid dynamics underpinning dementia and stroke through the common denominator of SVD.

Increased Burden of Cerebral Small Vessel Disease in Patients With Type 2 Diabetes and Retinopathy.

PubMed

Sanahuja, Jordi; Alonso, Núria; Diez, Javier; Ortega, Emilio; Rubinat, Esther; Traveset, Alícia; Alcubierre, Núria; Betriu, Àngels; Castelblanco, Esmeralda; Hernández, Marta; Purroy, Francisco; Arcidiacono, Maria Vittoria; Jurjo, Carmen; Fernández, Elvira; Puig-Domingo, Manuel; Groop, Per-Henrik; Mauricio, Dídac

2016-09-01

We sought to examine the presence and severity of brain small vessel disease (SVD) in patients with type 2 diabetes and diabetic retinopathy (DR) compared with those without DR. We evaluated 312 patients with type 2 diabetes without previous cardiovascular disease (men 51%; mean age 57 years; age range 40-75 years); 153 patients (49%) had DR. MRI was performed to evaluate the presence and severity (age-related white matter changes scale) of white matter lesions (WMLs) and lacunes, and transcranial Doppler ultrasound was used to measure the Gosling pulsatility index (PI) of the middle cerebral artery (MCA). The prevalence of lesions of cerebral SVD (WML and/or lacunes) was higher in patients with DR (40.2% vs. 30.1% without DR, P = 0.04). Age (P < 0.01) and systolic blood pressure (P = 0.02) were associated with the presence of SVD. The severity of SVD was associated with age and the presence of DR (P < 0.01 and P = 0.01, respectively). Patients with DR showed a higher MCA PI compared with those without DR (P < 0.01). Age, systolic and diastolic blood pressure, and retinopathy and its severity were associated with an increased MCA PI (P < 0.01 for all variables). A positive correlation was found between MCA PI values and the presence and severity of SVD (P < 0.01 for both variables). Patients with type 2 diabetes who have DR have an increased burden of cerebral SVD compared with those without DR. Our findings suggest that the brain is a target organ for microangiopathy, similar to other classic target organs, like the retina. © 2016 by the American Diabetes Association.

Distinctive Resting State Network Disruptions Among Alzheimer's Disease, Subcortical Vascular Dementia, and Mixed Dementia Patients.

PubMed

Kim, Hee Jin; Cha, Jungho; Lee, Jong-Min; Shin, Ji Soo; Jung, Na-Yeon; Kim, Yeo Jin; Choe, Yearn Seong; Lee, Kyung Han; Kim, Sung Tae; Kim, Jae Seung; Lee, Jae Hong; Na, Duk L; Seo, Sang Won

2016-01-01

Recent advances in resting-state functional MRI have revealed altered functional networks in Alzheimer's disease (AD), especially those of the default mode network (DMN) and central executive network (CEN). However, few studies have evaluated whether small vessel disease (SVD) or combined amyloid and SVD burdens affect the DMN or CEN. The aim of this study was to evaluate whether SVD or combined amyloid and SVD burdens affect the DMN or CEN. In this cross-sectional study, we investigated the resting-state functional connectivity within DMN and CEN in 37 Pittsburgh compound-B (PiB)(+) AD, 37 PiB(-) subcortical vascular dementia (SVaD), 13 mixed dementia patients, and 65 normal controls. When the resting-state DMN of PiB(+) AD and PiB(-) SVaD patients were compared, the PiB(+) AD patients displayed lower functional connectivity in the inferior parietal lobule while the PiB(-) SVaD patients displayed lower functional connectivity in the medial frontal and superior frontal gyri. Compared to the PiB(-) SVaD or PiB(+) AD, the mixed dementia patients displayed lower functional connectivity within the DMN in the posterior cingulate gyrus. When the resting-state CEN connectivity of PiB(+) AD and PiB(-) SVaD patients were compared, the PiB(-) SVaD patients displayed lower functional connectivity in the anterior insular region. Compared to the PiB(-) SVaD or PiB(+) AD, the mixed dementia patients displayed lower functional connectivity within the CEN in the inferior frontal gyrus. Our findings suggest that in PiB(+) AD and PiB(-) SVaD, there is divergent disruptions in resting-state DMN and CEN. Furthermore, patients with combined amyloid and SVD burdens exhibited more disrupted resting-state DMN and CEN than patients with only amyloid or SVD burden.

Pathogenesis and neuroimaging of cerebral large and small vessel disease in type 2 diabetes: A possible link between cerebral and retinal microvascular abnormalities.

PubMed

Umemura, Toshitaka; Kawamura, Takahiko; Hotta, Nigishi

2017-03-01

Diabetes patients have more than double the risk of ischemic stroke compared with non-diabetic individuals, and its neuroimaging characteristics have important clinical implications. To understand the pathophysiology of ischemic stroke in diabetes, it is important to focus not only on the stroke subtype, but also on the size and location of the occlusive vessels. Specifically, ischemic stroke in diabetes patients might be attributed to both large and small vessels, and intracranial internal carotid artery disease and small infarcts of the posterior circulation often occur. An additional feature is that asymptomatic lacunar infarctions are often seen in the basal ganglia and brain stem on brain magnetic resonance imaging. In particular, cerebral small vessel disease (SVD), including lacunar infarctions, white matter lesions and cerebral microbleeds, has been shown to be associated not only with stroke incidence, but also with the development and progression of dementia and diabetic microangiopathy. However, the pathogenesis of cerebral SVD is not fully understood. In addition, data on the association between neuroimaging findings of the cerebral SVD and diabetes are limited. Recently, the clinical importance of the link between cerebral SVD and retinal microvascular abnormalities has been a topic of considerable interest. Several clinical studies have shown that retinal microvascular abnormalities are closely related to cerebral SVD, suggesting that retinal microvascular abnormalities might be pathophysiologically linked to ischemic cerebral SVD. We review the literature relating to the pathophysiology and neuroimaging of cerebrovascular disease in diabetes, and discuss the problems based on the concept of cerebral large and small vessel disease. © 2016 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

A Fast SVD-Hidden-nodes based Extreme Learning Machine for Large-Scale Data Analytics.

PubMed

Deng, Wan-Yu; Bai, Zuo; Huang, Guang-Bin; Zheng, Qing-Hua

2016-05-01

Big dimensional data is a growing trend that is emerging in many real world contexts, extending from web mining, gene expression analysis, protein-protein interaction to high-frequency financial data. Nowadays, there is a growing consensus that the increasing dimensionality poses impeding effects on the performances of classifiers, which is termed as the "peaking phenomenon" in the field of machine intelligence. To address the issue, dimensionality reduction is commonly employed as a preprocessing step on the Big dimensional data before building the classifiers. In this paper, we propose an Extreme Learning Machine (ELM) approach for large-scale data analytic. In contrast to existing approaches, we embed hidden nodes that are designed using singular value decomposition (SVD) into the classical ELM. These SVD nodes in the hidden layer are shown to capture the underlying characteristics of the Big dimensional data well, exhibiting excellent generalization performances. The drawback of using SVD on the entire dataset, however, is the high computational complexity involved. To address this, a fast divide and conquer approximation scheme is introduced to maintain computational tractability on high volume data. The resultant algorithm proposed is labeled here as Fast Singular Value Decomposition-Hidden-nodes based Extreme Learning Machine or FSVD-H-ELM in short. In FSVD-H-ELM, instead of identifying the SVD hidden nodes directly from the entire dataset, SVD hidden nodes are derived from multiple random subsets of data sampled from the original dataset. Comprehensive experiments and comparisons are conducted to assess the FSVD-H-ELM against other state-of-the-art algorithms. The results obtained demonstrated the superior generalization performance and efficiency of the FSVD-H-ELM. Copyright © 2016 Elsevier Ltd. All rights reserved.

Is Dynamic Cerebral Autoregulation Bilaterally Impaired after Unilateral Acute Ischemic Stroke?

PubMed

Xiong, Li; Tian, Ge; Lin, Wenhua; Wang, Wei; Wang, Lijuan; Leung, Thomas; Mok, Vincent; Liu, Jia; Chen, Xiangyan; Wong, Ka Sing

2017-05-01

Whether dynamic cerebral autoregulation (dCA) is impaired focally in the affected hemisphere or bilaterally in both the affected and nonaffected hemispheres after ischemic stroke remains controversial. We therefore investigated the pattern of dCA in acute ischemic stroke patients with different subtypes. Sixty acute ischemic stroke patients with unilateral anterior circulation infarct [30 with large artery atherosclerosis (LAA), 13 with small vessel disease (SVD), and 17 with coexisting LAA and SVD] and 16 healthy controls were enrolled. Spontaneous arterial blood pressure and cerebral blood flow velocity fluctuations in both bilateral middle cerebral arteries using transcranial Doppler were recorded over 10 minutes. Transfer function analysis was applied to obtain autoregulatory parameters, autoregulation index (ARI), phase difference (PD), and gain. PD was significantly lower on both the ipsilateral and contralateral sides in the LAA group (ipsilateral, 30.74 degrees; contralateral, 29.17 degrees) and the coexisting LAA and SVD group (20.23 degrees; 13.10 degrees) than that in healthy controls (left side, 51.66 degrees; right side, 58.48 degrees) (all P < .05), but there were no significant differences between the 2 sides when compared with each other in all groups. However, in the coexisting LAA and SVD group, phase on both sides was significantly lower when compared with that in the LAA and SVD groups, respectively. The results of ARI were consistent with the findings in PD. The results indicate that dCA is bilaterally impaired in acute ischemic patients with LAA, and the coexisting SVD may aggravate the bilateral impairment of dCA. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Reduced Order Model Basis Vector Generation: Generates Basis Vectors fro ROMs

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

Arrighi, Bill

2016-03-03

libROM is a library that implements order reduction via singular value decomposition (SVD) of sampled state vectors. It implements 2 parallel, incremental SVD algorithms and one serial, non-incremental algorithm. It also provides a mechanism for adaptive sampling of basis vectors.

Deconvolutions based on singular value decomposition and the pseudoinverse: a guide for beginners.

PubMed

Hendler, R W; Shrager, R I

1994-01-01

Singular value decomposition (SVD) is deeply rooted in the theory of linear algebra, and because of this is not readily understood by a large group of researchers who could profit from its application. In this paper, we discuss the subject on a level that should be understandable to scientists who are not well versed in linear algebra. However, because it is necessary that certain key concepts in linear algebra be appreciated in order to comprehend what is accomplished by SVD, we present the section, 'Bare basics of linear algebra'. This is followed by a discussion of the theory of SVD. Next we present step-by-step examples to illustrate how SVD is applied to deconvolute a titration involving a mixture of three pH indicators. One noiseless case is presented as well as two cases where either a fixed or varying noise level is present. Finally, we discuss additional deconvolutions of mixed spectra based on the use of the pseudoinverse.

Characterization of agricultural land using singular value decomposition

NASA Astrophysics Data System (ADS)

Herries, Graham M.; Danaher, Sean; Selige, Thomas

1995-11-01

A method is defined and tested for the characterization of agricultural land from multi-spectral imagery, based on singular value decomposition (SVD) and key vector analysis. The SVD technique, which bears a close resemblance to multivariate statistic techniques, has previously been successfully applied to problems of signal extraction for marine data and forestry species classification. In this study the SVD technique is used as a classifier for agricultural regions, using airborne Daedalus ATM data, with 1 m resolution. The specific region chosen is an experimental research farm in Bavaria, Germany. This farm has a large number of crops, within a very small region and hence is not amenable to existing techniques. There are a number of other significant factors which render existing techniques such as the maximum likelihood algorithm less suitable for this area. These include a very dynamic terrain and tessellated pattern soil differences, which together cause large variations in the growth characteristics of the crops. The SVD technique is applied to this data set using a multi-stage classification approach, removing unwanted land-cover classes one step at a time. Typical classification accuracy's for SVD are of the order of 85-100%. Preliminary results indicate that it is a fast and efficient classifier with the ability to differentiate between crop types such as wheat, rye, potatoes and clover. The results of characterizing 3 sub-classes of Winter Wheat are also shown.

Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease.

PubMed

Zeestraten, Eva Anna; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew John; Williams, Owen Alan; Morris, Robin Guy; Barrick, Thomas Richard; Markus, Hugh Stephen

2016-01-01

Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life. Cognitive tests have been shown to be insensitive to change in longitudinal studies and, therefore, sensitive surrogate markers are needed to monitor disease progression and assess treatment effects in clinical trials. Diffusion tensor imaging (DTI) is thought to offer great potential in this regard. Sensitivity of the various parameters that can be derived from DTI is however unknown. We aimed to evaluate the differential sensitivity of DTI markers to detect SVD progression, and to estimate sample sizes required to assess therapeutic interventions aimed at halting decline based on DTI data. We investigated 99 patients with symptomatic SVD, defined as clinical lacunar syndrome with MRI confirmation of a corresponding infarct as well as confluent white matter hyperintensities over a 3 year follow-up period. We evaluated change in DTI histogram parameters using linear mixed effect models and calculated sample size estimates. Over a three-year follow-up period we observed a decline in fractional anisotropy and increase in diffusivity in white matter tissue and most parameters changed significantly. Mean diffusivity peak height was the most sensitive marker for SVD progression as it had the smallest sample size estimate. This suggests disease progression can be monitored sensitively using DTI histogram analysis and confirms DTI's potential as surrogate marker for SVD.

Effect of background correction on peak detection and quantification in online comprehensive two-dimensional liquid chromatography using diode array detection.

PubMed

Allen, Robert C; John, Mallory G; Rutan, Sarah C; Filgueira, Marcelo R; Carr, Peter W

2012-09-07

A singular value decomposition-based background correction (SVD-BC) technique is proposed for the reduction of background contributions in online comprehensive two-dimensional liquid chromatography (LC×LC) data. The SVD-BC technique was compared to simply subtracting a blank chromatogram from a sample chromatogram and to a previously reported background correction technique for one dimensional chromatography, which uses an asymmetric weighted least squares (AWLS) approach. AWLS was the only background correction technique to completely remove the background artifacts from the samples as evaluated by visual inspection. However, the SVD-BC technique greatly reduced or eliminated the background artifacts as well and preserved the peak intensity better than AWLS. The loss in peak intensity by AWLS resulted in lower peak counts at the detection thresholds established using standards samples. However, the SVD-BC technique was found to introduce noise which led to detection of false peaks at the lower detection thresholds. As a result, the AWLS technique gave more precise peak counts than the SVD-BC technique, particularly at the lower detection thresholds. While the AWLS technique resulted in more consistent percent residual standard deviation values, a statistical improvement in peak quantification after background correction was not found regardless of the background correction technique used. Copyright © 2012 Elsevier B.V. All rights reserved.

PICKY: a novel SVD-based NMR spectra peak picking method.

PubMed

Alipanahi, Babak; Gao, Xin; Karakoc, Emre; Donaldson, Logan; Li, Ming

2009-06-15

Picking peaks from experimental NMR spectra is a key unsolved problem for automated NMR protein structure determination. Such a process is a prerequisite for resonance assignment, nuclear overhauser enhancement (NOE) distance restraint assignment, and structure calculation tasks. Manual or semi-automatic peak picking, which is currently the prominent way used in NMR labs, is tedious, time consuming and costly. We introduce new ideas, including noise-level estimation, component forming and sub-division, singular value decomposition (SVD)-based peak picking and peak pruning and refinement. PICKY is developed as an automated peak picking method. Different from the previous research on peak picking, we provide a systematic study of the proposed method. PICKY is tested on 32 real 2D and 3D spectra of eight target proteins, and achieves an average of 88% recall and 74% precision. PICKY is efficient. It takes PICKY on average 15.7 s to process an NMR spectrum. More important than these numbers, PICKY actually works in practice. We feed peak lists generated by PICKY to IPASS for resonance assignment, feed IPASS assignment to SPARTA for fragments generation, and feed SPARTA fragments to FALCON for structure calculation. This results in high-resolution structures of several proteins, for example, TM1112, at 1.25 A. PICKY is available upon request. The peak lists of PICKY can be easily loaded by SPARKY to enable a better interactive strategy for rapid peak picking.

The anticipation of death by violence: a psychological profile.

PubMed

Mahoney, J; Kyle, D; Katz, G

1975-01-01

College students (n = 172) completed Cattell's personality factor questionnaire, Rotter's locus of control scale, Speilberger's trait anxiety measure, and Sabatini and Kastenbaum's self-completed death certificate. Comparison of profiles for subjects anticipating sudden violent death (SVD, n = 59) with those anticipating natural death (ND, n = 113) disclosed that the SVD group was characteristically more anxious and socially isolated. A sex-by-type of death interaction occurred for locus of control, with SVD females being the most external, suggesting that this group was more likely to "give up" in response to stress. The data support Shneidman's concept of subintentioned death in disclosing that several personality factors may be associated with violent death.

A collaborative filtering-based approach to biomedical knowledge discovery.

PubMed

Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

2018-02-15

The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Sparse Representation with Spatio-Temporal Online Dictionary Learning for Efficient Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Tang, Xin; Zou, Junni; Xiong, Hongkai; Chen, Chang Wen

2016-07-27

Classical dictionary learning methods for video coding suer from high computational complexity and interfered coding eciency by disregarding its underlying distribution. This paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to speed up the convergence rate of dictionary learning with a guarantee of approximation error. The proposed algorithm incorporates stochastic gradient descents to form a dictionary of pairs of 3-D low-frequency and highfrequency spatio-temporal volumes. In each iteration of the learning process, it randomly selects one sample volume and updates the atoms of dictionary by minimizing the expected cost, rather than optimizes empirical cost over the complete training data like batch learning methods, e.g. K-SVD. Since the selected volumes are supposed to be i.i.d. samples from the underlying distribution, decomposition coecients attained from the trained dictionary are desirable for sparse representation. Theoretically, it is proved that the proposed STOL could achieve better approximation for sparse representation than K-SVD and maintain both structured sparsity and hierarchical sparsity. It is shown to outperform batch gradient descent methods (K-SVD) in the sense of convergence speed and computational complexity, and its upper bound for prediction error is asymptotically equal to the training error. With lower computational complexity, extensive experiments validate that the STOL based coding scheme achieves performance improvements than H.264/AVC or HEVC as well as existing super-resolution based methods in ratedistortion performance and visual quality.

Efficient subtle motion detection from high-speed video for sound recovery and vibration analysis using singular value decomposition-based approach

NASA Astrophysics Data System (ADS)

Zhang, Dashan; Guo, Jie; Jin, Yi; Zhu, Chang'an

2017-09-01

High-speed cameras provide full field measurement of structure motions and have been applied in nondestructive testing and noncontact structure monitoring. Recently, a phase-based method has been proposed to extract sound-induced vibrations from phase variations in videos, and this method provides insights into the study of remote sound surveillance and material analysis. An efficient singular value decomposition (SVD)-based approach is introduced to detect sound-induced subtle motions from pixel intensities in silent high-speed videos. A high-speed camera is initially applied to capture a video of the vibrating objects stimulated by sound fluctuations. Then, subimages collected from a small region on the captured video are reshaped into vectors and reconstructed to form a matrix. Orthonormal image bases (OIBs) are obtained from the SVD of the matrix; available vibration signal can then be obtained by projecting subsequent subimages onto specific OIBs. A simulation test is initiated to validate the effectiveness and efficiency of the proposed method. Two experiments are conducted to demonstrate the potential applications in sound recovery and material analysis. Results show that the proposed method efficiently detects subtle motions from the video.

Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease

PubMed Central

Zeestraten, Eva Anna; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew John; Williams, Owen Alan; Morris, Robin Guy; Barrick, Thomas Richard; Markus, Hugh Stephen

2016-01-01

Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life. Cognitive tests have been shown to be insensitive to change in longitudinal studies and, therefore, sensitive surrogate markers are needed to monitor disease progression and assess treatment effects in clinical trials. Diffusion tensor imaging (DTI) is thought to offer great potential in this regard. Sensitivity of the various parameters that can be derived from DTI is however unknown. We aimed to evaluate the differential sensitivity of DTI markers to detect SVD progression, and to estimate sample sizes required to assess therapeutic interventions aimed at halting decline based on DTI data. We investigated 99 patients with symptomatic SVD, defined as clinical lacunar syndrome with MRI confirmation of a corresponding infarct as well as confluent white matter hyperintensities over a 3 year follow-up period. We evaluated change in DTI histogram parameters using linear mixed effect models and calculated sample size estimates. Over a three-year follow-up period we observed a decline in fractional anisotropy and increase in diffusivity in white matter tissue and most parameters changed significantly. Mean diffusivity peak height was the most sensitive marker for SVD progression as it had the smallest sample size estimate. This suggests disease progression can be monitored sensitively using DTI histogram analysis and confirms DTI’s potential as surrogate marker for SVD. PMID:26808982

Lesion location and cognitive impact of cerebral small vessel disease.

PubMed

Biesbroek, J Matthijs; Weaver, Nick A; Biessels, Geert Jan

2017-04-25

Cerebral small vessel disease (SVD) is an important cause of cognitive impairment. Important MRI manifestations of SVD include white matter hyperintensities (WMH) and lacunes. This narrative review addresses the role of anatomical lesion location in the impact of SVD on cognition, integrating findings from early autopsy studies with emerging findings from recent studies with advanced image analysis techniques. Early autopsy and imaging studies of small case series indicate that single lacunar infarcts in, for example the thalamus, caudate nucleus or internal capsule can cause marked cognitive impairment. However, the findings of such case studies may not be generalizable. Emerging location-based image analysis approaches are now being applied to large cohorts. Recent studies show that WMH burden in strategic white matter tracts, such as the forceps minor or anterior thalamic radiation (ATR), is more relevant in explaining variance in cognitive functioning than global WMH volume. These findings suggest that the future diagnostic work-up of memory clinic patients could potentially be improved by shifting from a global assessment of WMH and lacune burden towards a quantitative assessment of lesion volumes within strategic brain regions. In this review, a summary of currently known strategic regions for SVD-related cognitive impairment is provided, highlighting recent technical developments in SVD research. The potential and challenges of location-based approaches for diagnostic purposes in clinical practice are discussed, along with their potential prognostic and therapeutic applications. © 2017 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Tmax Determined Using a Bayesian Estimation Deconvolution Algorithm Applied to Bolus Tracking Perfusion Imaging: A Digital Phantom Validation Study.

PubMed

Uwano, Ikuko; Sasaki, Makoto; Kudo, Kohsuke; Boutelier, Timothé; Kameda, Hiroyuki; Mori, Futoshi; Yamashita, Fumio

2017-01-10

The Bayesian estimation algorithm improves the precision of bolus tracking perfusion imaging. However, this algorithm cannot directly calculate Tmax, the time scale widely used to identify ischemic penumbra, because Tmax is a non-physiological, artificial index that reflects the tracer arrival delay (TD) and other parameters. We calculated Tmax from the TD and mean transit time (MTT) obtained by the Bayesian algorithm and determined its accuracy in comparison with Tmax obtained by singular value decomposition (SVD) algorithms. The TD and MTT maps were generated by the Bayesian algorithm applied to digital phantoms with time-concentration curves that reflected a range of values for various perfusion metrics using a global arterial input function. Tmax was calculated from the TD and MTT using constants obtained by a linear least-squares fit to Tmax obtained from the two SVD algorithms that showed the best benchmarks in a previous study. Correlations between the Tmax values obtained by the Bayesian and SVD methods were examined. The Bayesian algorithm yielded accurate TD and MTT values relative to the true values of the digital phantom. Tmax calculated from the TD and MTT values with the least-squares fit constants showed excellent correlation (Pearson's correlation coefficient = 0.99) and agreement (intraclass correlation coefficient = 0.99) with Tmax obtained from SVD algorithms. Quantitative analyses of Tmax values calculated from Bayesian-estimation algorithm-derived TD and MTT from a digital phantom correlated and agreed well with Tmax values determined using SVD algorithms.

Small vessel disease, but neither amyloid load nor metabolic deficit, is dependent on age at onset in Alzheimer's disease.

PubMed

Ortner, Marion; Kurz, Alexander; Alexopoulos, Panagiotis; Auer, Florian; Diehl-Schmid, Janine; Drzezga, Alexander; Förster, Stefan; Förstl, Hans; Perneczky, Robert; Sorg, Christian; Yousefi, Behrooz H; Grimmer, Timo

2015-04-15

There is controversy concerning whether Alzheimer's disease (AD) with early onset is distinct from AD with late onset with regard to amyloid pathology and neuronal metabolic deficit. We hypothesized that compared with patients with early-onset AD, patients with late-onset AD have more comorbid small vessel disease (SVD) contributing to clinical severity, whereas there are no differences in amyloid pathology and neuronal metabolic deficit. The study included two groups of patients with probable AD dementia with evidence of the AD pathophysiologic process: 24 patients with age at onset <60 years old and 36 patients with age at onset >70 years old. Amyloid deposition was assessed using carbon-11-labeled Pittsburgh compound B positron emission tomography, comorbid SVD was assessed using magnetic resonance imaging, and neuronal metabolic deficit was assessed using fluorodeoxyglucose positron emission tomography. Group differences of global and regional distribution of pathology were explored using region of interest and voxel-based analyses, respectively, carefully controlling for the influence of dementia severity, apolipoprotein E genotype, and in particular SVD. The pattern of cognitive impairment was determined using z scores of the subtests of the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Assessment Battery. Patients with late-onset AD showed a significantly greater amount of SVD. No statistically significant differences in global or regional amyloid deposition or neuronal metabolic deficit between the two groups were revealed. However, when not controlling for SVD, subtle differences in fluorodeoxyglucose uptake between early-onset AD and late-onset AD groups were detectable. There were no significant differences regarding cognitive functioning. Age at onset does not influence amyloid deposition or neuronal metabolic deficit in AD. The greater extent of SVD in late-onset AD influences the association between neuronal metabolic deficit and clinical symptoms. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Ten-year results of the Freedom Solo stentless heart valve: excellent haemodynamics but progressive valve dysfunction in the long term.

PubMed

Sponga, Sandro; Barbera, Mila Della; Pavoni, Daisy; Lechiancole, Andrea; Mazzaro, Enzo; Valente, Marialuisa; Nucifora, Gaetano; Thiene, Gaetano; Livi, Ugolino

2017-05-01

Freedom Solo (FS) is a pericardial stentless heart valve showing excellent haemodynamic performance at mid-term. The aim of this study was to evaluate the long-term performance of such bioprostheses. Between December 2004 and November 2009, 109 patients (31 men; mean age 76 ± 6 years) underwent aortic valve replacement with FS. Preoperatively, the mean NYHA class was 2.5 ± 0.7, the mean EuroSCORE II, 2.8 ± 2.5. Mean prosthesis size was 22.7 ± 1.9 mm; concomitant procedures were performed in 65 patients. Structural valve deterioration (SVD) was diagnosed according to the Valve Academic Research Consortium-2 definition. Two patients (1.8%) died within 30 days. Follow-up (72 ± 36 months) was 100% completed. The 1-, 5- and 10-year actuarial survival rates were 89, 73 and 42%, respectively, with 8 valve-related deaths; the actuarial freedom from SVD was 99, 93 and 76%. During 61 ± 39 months of follow-up, echocardiographic findings worsened progressively: At discharge, 3-5 and 7-9 years, the mean gradient was 8 ± 4, 12 ± 11 and 19 ± 19 mmHg ( P  < 0.01); the indexed effective orifice area was 1.0 ± 0.2, 0.9 ± 0.2 and 0.8 ± 0.3 cm 2 /m 2 ( P  < 0.01). Of the 13 patients who developed SVD, it was due to aortic stenosis in 11. SVD was a predictor of cardiovascular mortality at univariate analysis (HR 2.87, 1.12-7.29); 2 explanted prostheses showed massive calcium deposits with mean calcium and phosphorus contents of 234 ± 16 and 116 ± 7 mg/g dry weight, respectively. The FS bioprosthesis shows excellent mid-term clinical and haemodynamic results and offers an alternative to other valves, particularly in the case of a small aortic annulus. Worsening of FS performance was observed at late follow-up because of progressive SVD with stenosis, questioning whether it should be used in patients with a long life expectancy. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Tensor Factorization for Low-Rank Tensor Completion.

PubMed

Zhou, Pan; Lu, Canyi; Lin, Zhouchen; Zhang, Chao

2018-03-01

Recently, a tensor nuclear norm (TNN) based method was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the low-rank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method only needs to update two smaller tensors, which can be more efficiently conducted than computing t-SVD. Furthermore, we prove that the proposed alternating minimization algorithm can converge to a Karush-Kuhn-Tucker point. Experimental results on the synthetic data recovery, image and video inpainting tasks clearly demonstrate the superior performance and efficiency of our developed method over state-of-the-arts including the TNN and matricization methods.

A tripolar pattern as an internal mode of the East Asian summer monsoon

NASA Astrophysics Data System (ADS)

Hirota, Nagio; Takahashi, Masaaki

2012-11-01

A tripolar anomaly pattern with centers located around the Philippines, China/Japan, and East Siberia dominantly appears in climate variations of the East Asian summer monsoon. In this study, we extracted this pattern as the first mode of a singular value decomposition (SVD1) over East Asia. The squared covariance fraction of SVD1 was 59 %, indicating that this pattern can be considered a dominant pattern of climate variations. Moreover, the results of numerical experiments suggested that the structure is also a dominant pattern of linear responses, even if external forcing is distributed homogeneously over the Northern Hemisphere. Thus, the tripolar pattern can be considered an internal mode that is characterized by the internal atmospheric processes. In this pattern, the moist processes strengthen the circulation anomalies, the dynamical energy conversion supplies energy to the anomalies, and the Rossby waves propagate northward in the lower troposphere and southeastward in the upper troposphere. These processes are favorable for the pattern to have large amplitude and to influence a large area.

Prediction of monthly-seasonal precipitation using coupled SVD patterns between soil moisture and subsequent precipitation

Treesearch

Yongqiang Liu

2003-01-01

It was suggested in a recent statistical correlation analysis that predictability of monthly-seasonal precipitation could be improved by using coupled singular value decomposition (SVD) pattems between soil moisture and precipitation instead of their values at individual locations. This study provides predictive evidence for this suggestion by comparing skills of two...

Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region

Treesearch

Yongqiang Liu

2003-01-01

The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is...

Weak characteristic information extraction from early fault of wind turbine generator gearbox

NASA Astrophysics Data System (ADS)

Xu, Xiaoli; Liu, Xiuli

2017-09-01

Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition (SVD)-based denoising may result in loss of useful information. A weak characteristic information extraction based on μ-SVD and local mean decomposition (LMD) is developed to address this problem. The basic principle of the method is as follows: Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and μ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.

A non-linear regression method for CT brain perfusion analysis

NASA Astrophysics Data System (ADS)

Bennink, E.; Oosterbroek, J.; Viergever, M. A.; Velthuis, B. K.; de Jong, H. W. A. M.

2015-03-01

CT perfusion (CTP) imaging allows for rapid diagnosis of ischemic stroke. Generation of perfusion maps from CTP data usually involves deconvolution algorithms providing estimates for the impulse response function in the tissue. We propose the use of a fast non-linear regression (NLR) method that we postulate has similar performance to the current academic state-of-art method (bSVD), but that has some important advantages, including the estimation of vascular permeability, improved robustness to tracer-delay, and very few tuning parameters, that are all important in stroke assessment. The aim of this study is to evaluate the fast NLR method against bSVD and a commercial clinical state-of-art method. The three methods were tested against a published digital perfusion phantom earlier used to illustrate the superiority of bSVD. In addition, the NLR and clinical methods were also tested against bSVD on 20 clinical scans. Pearson correlation coefficients were calculated for each of the tested methods. All three methods showed high correlation coefficients (>0.9) with the ground truth in the phantom. With respect to the clinical scans, the NLR perfusion maps showed higher correlation with bSVD than the perfusion maps from the clinical method. Furthermore, the perfusion maps showed that the fast NLR estimates are robust to tracer-delay. In conclusion, the proposed fast NLR method provides a simple and flexible way of estimating perfusion parameters from CT perfusion scans, with high correlation coefficients. This suggests that it could be a better alternative to the current clinical and academic state-of-art methods.

Operational modal analysis using SVD of power spectral density transmissibility matrices

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Laier, Jose Elias

2014-05-01

This paper proposes the singular value decomposition of power spectrum density transmissibility matrices with different references, (PSDTM-SVD), as an identification method of natural frequencies and mode shapes of a dynamic system subjected to excitations under operational conditions. At the system poles, the rows of the proposed transmissibility matrix converge to the same ratio of amplitudes of vibration modes. As a result, the matrices are linearly dependent on the columns, and their singular values converge to zero. Singular values are used to determine the natural frequencies, and the first left singular vectors are used to estimate mode shapes. A numerical example of the finite element model of a beam subjected to colored noise excitation is analyzed to illustrate the accuracy of the proposed method. Results of the PSDTM-SVD method in the numerical example are compared with obtained using frequency domain decomposition (FDD) and power spectrum density transmissibility (PSDT). It is demonstrated that the proposed method does not depend on the excitation characteristics contrary to the FDD method that assumes white noise excitation, and further reduces the risk to identify extra non-physical poles in comparison to the PSDT method. Furthermore, a case study is performed using data from an operational vibration test of a bridge with a simply supported beam system. The real application of a full-sized bridge has shown that the proposed PSDTM-SVD method is able to identify the operational modal parameter. Operational modal parameters identified by the PSDTM-SVD in the real application agree well those identified by the FDD and PSDT methods.

Dual-tree complex wavelet transform and SVD based acoustic noise reduction and its application in leak detection for natural gas pipeline

NASA Astrophysics Data System (ADS)

Yu, Xuchao; Liang, Wei; Zhang, Laibin; Jin, Hao; Qiu, Jingwei

2016-05-01

During the last decades, leak detection for natural gas pipeline has become one of the paramount concerns of pipeline operators and researchers across the globe. However, acoustic wave method has been proved to be an effective way to identify and localize leakage for gas pipeline. Considering the fact that noises inevitably exist in the acoustic signals collected, noise reduction should be enforced on the signals for subsequent data mining and analysis. Thus, an integrated acoustic noise reduction method based on DTCWT and SVD is proposed in this study. The method is put forward based on the idea that noise reduction strategy should match the characteristics of the noisy signal. According to previous studies, it is known that the energy of acoustic signals collected under leaking condition is mainly concentrated in low-frequency portion (0-100 Hz). And ultralow-frequency component (0-5 Hz), which is taken as the characteristic frequency band in this study, can propagate a relatively longer distance and be captured by sensors. Therefore, in order to filter the noises and to reserve the characteristic frequency band, DTCWT is taken as the core to conduct multilevel decomposition and refining for acoustic signals and SVD is employed to eliminate noises in non-characteristic bands. Both simulation and field experiments show that DTCWT-SVD is an excellent method for acoustic noise reduction. At the end of this study, application in leakage localization shows that it becomes much easier and a little more accurate to estimate the location of leak hole after noise reduction by DTCWT-SVD.

Microvascular Pathology and Morphometrics of Sporadic and Hereditary Small Vessel Diseases of the Brain

PubMed Central

Craggs, Lucinda JL; Yamamoto, Yumi; Deramecourt, Vincent; Kalaria, Raj N

2014-01-01

Small vessel diseases (SVDs) of the brain are likely to become increasingly common in tandem with the rise in the aging population. In recent years, neuroimaging and pathological studies have informed on the pathogenesis of sporadic SVD and several single gene (monogenic) disorders predisposing to subcortical strokes and diffuse white matter disease. However, one of the limitations toward studying SVD lies in the lack of consistent assessment criteria and lesion burden for both clinical and pathological measures. Arteriolosclerosis and diffuse white matter changes are the hallmark features of both sporadic and hereditary SVDs. The pathogenesis of the arteriopathy is the key to understanding the differential progression of disease in various SVDs. Remarkably, quantification of microvascular abnormalities in sporadic and hereditary SVDs has shown that qualitatively the processes involved in arteriolar degeneration are largely similar in sporadic SVD compared with hereditary disorders such as cerebral autosomal arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Important significant regional differences in lesion location within the brain may enable one to distinguish SVDs, where frontal lobe involvement appears consistently with almost every SVD, but others bear specific pathologies in other lobes, such as the temporal pole in CADASIL and the pons in pontine autosomal dominant microangiopathy and leukoencephalopathy or PADMAL. Additionally, degenerative changes in the vascular smooth muscle cells, the cerebral endothelium and the basal lamina are often rapid and more aggressive in genetic disorders. Further quantification of other microvascular elements and even neuronal cells is needed to fully characterize SVD pathogenesis and to differentiate the usefulness of vascular interventions and treatments on the resulting pathology. PMID:25323665

PICKY: a novel SVD-based NMR spectra peak picking method

PubMed Central

Alipanahi, Babak; Gao, Xin; Karakoc, Emre; Donaldson, Logan; Li, Ming

2009-01-01

Motivation: Picking peaks from experimental NMR spectra is a key unsolved problem for automated NMR protein structure determination. Such a process is a prerequisite for resonance assignment, nuclear overhauser enhancement (NOE) distance restraint assignment, and structure calculation tasks. Manual or semi-automatic peak picking, which is currently the prominent way used in NMR labs, is tedious, time consuming and costly. Results: We introduce new ideas, including noise-level estimation, component forming and sub-division, singular value decomposition (SVD)-based peak picking and peak pruning and refinement. PICKY is developed as an automated peak picking method. Different from the previous research on peak picking, we provide a systematic study of the proposed method. PICKY is tested on 32 real 2D and 3D spectra of eight target proteins, and achieves an average of 88% recall and 74% precision. PICKY is efficient. It takes PICKY on average 15.7 s to process an NMR spectrum. More important than these numbers, PICKY actually works in practice. We feed peak lists generated by PICKY to IPASS for resonance assignment, feed IPASS assignment to SPARTA for fragments generation, and feed SPARTA fragments to FALCON for structure calculation. This results in high-resolution structures of several proteins, for example, TM1112, at 1.25 Å. Availability: PICKY is available upon request. The peak lists of PICKY can be easily loaded by SPARKY to enable a better interactive strategy for rapid peak picking. Contact: mli@uwaterloo.ca PMID:19477998

Note: Sound recovery from video using SVD-based information extraction

NASA Astrophysics Data System (ADS)

Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Chang'an

2016-08-01

This note reports an efficient singular value decomposition (SVD)-based vibration extraction approach that recovers sound information in silent high-speed video. A high-speed camera of which frame rates are in the range of 2 kHz-10 kHz is applied to film the vibrating objects. Sub-images cut from video frames are transformed into column vectors and then reconstructed to a new matrix. The SVD of the new matrix produces orthonormal image bases (OIBs) and image projections onto specific OIB can be recovered as understandable acoustical signals. Standard frequencies of 256 Hz and 512 Hz tuning forks are extracted offline from their vibrating surfaces and a 3.35 s speech signal is recovered online from a piece of paper that is stimulated by sound waves within 1 min.

Singular value decomposition for collaborative filtering on a GPU

NASA Astrophysics Data System (ADS)

Kato, Kimikazu; Hosino, Tikara

2010-06-01

A collaborative filtering predicts customers' unknown preferences from known preferences. In a computation of the collaborative filtering, a singular value decomposition (SVD) is needed to reduce the size of a large scale matrix so that the burden for the next phase computation will be decreased. In this application, SVD means a roughly approximated factorization of a given matrix into smaller sized matrices. Webb (a.k.a. Simon Funk) showed an effective algorithm to compute SVD toward a solution of an open competition called "Netflix Prize". The algorithm utilizes an iterative method so that the error of approximation improves in each step of the iteration. We give a GPU version of Webb's algorithm. Our algorithm is implemented in the CUDA and it is shown to be efficient by an experiment.

Image processing enhancement of high-resolution TEM micrographs of nanometer-size metal particles

NASA Technical Reports Server (NTRS)

Artal, P.; Avalos-Borja, M.; Soria, F.; Poppa, H.; Heinemann, K.

1989-01-01

The high-resolution TEM detectability of lattice fringes from metal particles supported on substrates is impeded by the substrate itself. Single value decomposition (SVD) and Fourier filtering (FFT) methods were applied to standard high resolution micrographs to enhance lattice resolution from particles as well as from crystalline substrates. SVD produced good results for one direction of fringes, and it can be implemented as a real-time process. Fourier methods are independent of azimuthal directions and allow separation of particle lattice planes from those pertaining to the substrate, which makes it feasible to detect possible substrate distortions produced by the supported particle. This method, on the other hand, is more elaborate, requires more computer time than SVD and is, therefore, less likely to be used in real-time image processing applications.

Perivascular Spaces, Glymphatic Dysfunction, and Small Vessel Disease

PubMed Central

Mestre, Humberto; Kostrikov, Serhii; Mehta, Rupal I.; Nedergaard, Maiken

2017-01-01

Cerebral small vessel diseases (SVD) range broadly in etiology but share a remarkably overlapping pathology. Features of SVD including enlarged perivascular spaces and formation of abluminal protein deposits cannot be completely explained by the putative pathophysiology. The recently discovered glymphatic system provides a new perspective to potentially address these gaps. This work provides a comprehensive review of the known factors that regulate glymphatic function and the disease mechanisms underlying glymphatic impairment emphasizing the role that aquaporin-4 (AQP4)-lined perivascular spaces, cerebrovascular pulsatility, and metabolite clearance play in normal CNS physiology. This review also discusses the implications that glymphatic impairment may have on SVD inception and progression with the aim of exploring novel therapeutic targets and highlighting the key questions that remain to be answered. PMID:28798076

Real-time Automatic Detectors of P and S Waves Using Singular Values Decomposition

NASA Astrophysics Data System (ADS)

Kurzon, I.; Vernon, F.; Rosenberger, A.; Ben-Zion, Y.

2013-12-01

We implement a new method for the automatic detection of the primary P and S phases using Singular Value Decomposition (SVD) analysis. The method is based on a real-time iteration algorithm of Rosenberger (2010) for the SVD of three component seismograms. Rosenberger's algorithm identifies the incidence angle by applying SVD and separates the waveforms into their P and S components. We have been using the same algorithm with the modification that we filter the waveforms prior to the SVD, and then apply SNR (Signal-to-Noise Ratio) detectors for picking the P and S arrivals, on the new filtered+SVD-separated channels. A recent deployment in San Jacinto Fault Zone area provides a very dense seismic network that allows us to test the detection algorithm in diverse setting, such as: events with different source mechanisms, stations with different site characteristics, and ray paths that diverge from the SVD approximation used in the algorithm, (e.g., rays propagating within the fault and recorded on linear arrays, crossing the fault). We have found that a Butterworth band-pass filter of 2-30Hz, with four poles at each of the corner frequencies, shows the best performance in a large variety of events and stations within the SJFZ. Using the SVD detectors we obtain a similar number of P and S picks, which is a rare thing to see in ordinary SNR detectors. Also for the actual real-time operation of the ANZA and SJFZ real-time seismic networks, the above filter (2-30Hz) shows a very impressive performance, tested on many events and several aftershock sequences in the region from the MW 5.2 of June 2005, through the MW 5.4 of July 2010, to MW 4.7 of March 2013. Here we show the results of testing the detectors on the most complex and intense aftershock sequence, the MW 5.2 of June 2005, in which in the very first hour there were ~4 events a minute. This aftershock sequence was thoroughly reviewed by several analysts, identifying 294 events in the first hour, located in a condensed cluster around the main shock. We used this hour of events to fine-tune the automatic SVD detection, association and location of the real-time system, reaching a 37% automatic identification and location of events, with a minimum of 10 stations per event, all events fall within the same condensed cluster and there are no false events or large offsets of their locations. An ordinary SNR detector did not exceed the 11% success with a minimum of 8 stations per event, 2 false events and a wider spread of events (not within the reviewed cluster). One of the main advantages of the SVD detectors for real-time operations is the actual separation between the P and S components, by that significantly reducing the noise of picks detected by ordinary SNR detectors. The new method has been applied for a significant amount of events within the SJFZ in the past 8 years, and is now in the final stage of real-time implementation in UCSD for the ANZA and SJFZ networks, tuned for automatic detection and location of local events.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP effects (SNP-BLUP model). When reducing marker density from WGS data to 30 K, SNP-BLUP tended to yield the highest accuracies, at least in the short term. Based on SVD of the genotype matrix, we developed a direct method for the calculation of BayesC estimates of marker effects. Although SVD- and MCMC-based marker effects differed slightly, their prediction accuracies were similar. Assuming that the SVD of the marker genotype matrix is already performed for other reasons (e.g. for SNP-BLUP), computation times for the BayesC predictions were comparable to those of SNP-BLUP.

svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification.

PubMed

Zhang, Wensheng; Edwards, Andrea; Fan, Wei; Zhu, Dongxiao; Zhang, Kun

2010-06-22

Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods. Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG) and malpighian tubule (MT) tissues of the line W118 of M. drosophila. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR < 0.1. One divergent module suggested the tissue-specific relationship between the expressions of mitochondrion-related genes and the aging process. This finding, together with others, may be of biological significance. The validity of the proposed SVD-based method was further verified by a simulation study, as well as the comparisons with regression analysis and cubic spline regression analysis plus PAM based clustering. svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time series data of related organisms or different tissues of the same organism under equivalent or similar experimental conditions. The general scheme can be directly extended to the comparisons of multiple data sets. It also can be applied to the integration of data sets from different platforms and of different sources.

Measuring Glial Metabolism in Repetitive Brain Trauma and Alzheimer’s Disease

DTIC Science & Technology

2016-09-01

Six methods: Single value decomposition (SVD), wavelet, sliding window, sliding window with Gaussian weighting, spline and spectral improvements...comparison of a range of different denoising methods for dynamic MRS. Six denoising methods were considered: Single value decomposition (SVD), wavelet...project by improving the software required for the data analysis by developing six different denoising methods. He also assisted with the testing

40 CFR Appendix 7 to Subpart A of... - Determination of the Amount of Non-Aqueous Drilling Fluid (NAF) Base Fluid From Drill Cuttings by...

Code of Federal Regulations, 2013 CFR

2013-07-01

... multiplying the density of the small volume NAF-cuttings discharges (ρsvd) times the volume of the small...-cuttings discharges (kg) ρsvd = density of the small volume NAF-cuttings discharges (kg/bbl) VSVD = volume of the small volume NAF-cuttings discharges (bbl) The density of the small volume NAF-cuttings...

40 CFR Appendix 7 to Subpart A of... - Determination of the Amount of Non-Aqueous Drilling Fluid (NAF) Base Fluid From Drill Cuttings by...

Code of Federal Regulations, 2014 CFR

2014-07-01

... multiplying the density of the small volume NAF-cuttings discharges (ρsvd) times the volume of the small...-cuttings discharges (kg) ρsvd = density of the small volume NAF-cuttings discharges (kg/bbl) VSVD = volume of the small volume NAF-cuttings discharges (bbl) The density of the small volume NAF-cuttings...

40 CFR Appendix 7 to Subpart A of... - Determination of the Amount of Non-Aqueous Drilling Fluid (NAF) Base Fluid From Drill Cuttings by...

Code of Federal Regulations, 2012 CFR

2012-07-01

... multiplying the density of the small volume NAF-cuttings discharges (ρsvd) times the volume of the small...-cuttings discharges (kg) ρsvd = density of the small volume NAF-cuttings discharges (kg/bbl) VSVD = volume of the small volume NAF-cuttings discharges (bbl) The density of the small volume NAF-cuttings...

Comparison of quantitative myocardial perfusion imaging CT to fluorescent microsphere-based flow from high-resolution cryo-images

NASA Astrophysics Data System (ADS)

Eck, Brendan L.; Fahmi, Rachid; Levi, Jacob; Fares, Anas; Wu, Hao; Li, Yuemeng; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2016-03-01

Myocardial perfusion imaging using CT (MPI-CT) has the potential to provide quantitative measures of myocardial blood flow (MBF) which can aid the diagnosis of coronary artery disease. We evaluated the quantitative accuracy of MPI-CT in a porcine model of balloon-induced LAD coronary artery ischemia guided by fractional flow reserve (FFR). We quantified MBF at baseline (FFR=1.0) and under moderate ischemia (FFR=0.7) using MPI-CT and compared to fluorescent microsphere-based MBF from high-resolution cryo-images. Dynamic, contrast-enhanced CT images were obtained using a spectral detector CT (Philips Healthcare). Projection-based mono-energetic images were reconstructed and processed to obtain MBF. Three MBF quantification approaches were evaluated: singular value decomposition (SVD) with fixed Tikhonov regularization (ThSVD), SVD with regularization determined by the L-Curve criterion (LSVD), and Johnson-Wilson parameter estimation (JW). The three approaches over-estimated MBF compared to cryo-images. JW produced the most accurate MBF, with average error 33.3+/-19.2mL/min/100g, whereas LSVD and ThSVD had greater over-estimation, 59.5+/-28.3mL/min/100g and 78.3+/-25.6 mL/min/100g, respectively. Relative blood flow as assessed by a flow ratio of LAD-to-remote myocardium was strongly correlated between JW and cryo-imaging, with R2=0.97, compared to R2=0.88 and 0.78 for LSVD and ThSVD, respectively. We assessed tissue impulse response functions (IRFs) from each approach for sources of error. While JW was constrained to physiologic solutions, both LSVD and ThSVD produced IRFs with non-physiologic properties due to noise. The L-curve provided noise-adaptive regularization but did not eliminate non-physiologic IRF properties or optimize for MBF accuracy. These findings suggest that model-based MPI-CT approaches may be more appropriate for quantitative MBF estimation and that cryo-imaging can support the development of MPI-CT by providing spatial distributions of MBF.

Spectral biclustering of microarray data: coclustering genes and conditions.

PubMed

Kluger, Yuval; Basri, Ronen; Chang, Joseph T; Gerstein, Mark

2003-04-01

Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find "marker genes" that are differentially expressed in particular sets of "conditions." We have developed a method that simultaneously clusters genes and conditions, finding distinctive "checkerboard" patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data).

An R-peak detection method that uses an SVD filter and a search back system.

PubMed

Jung, Woo-Hyuk; Lee, Sang-Goog

2012-12-01

In this paper, we present a method for detecting the R-peak of an ECG signal by using an singular value decomposition (SVD) filter and a search back system. The ECG signal was detected in two phases: the pre-processing phase and the decision phase. The pre-processing phase consisted of the stages for the SVD filter, Butterworth High Pass Filter (HPF), moving average (MA), and squaring, whereas the decision phase consisted of a single stage that detected the R-peak. In the pre-processing phase, the SVD filter removed noise while the Butterworth HPF eliminated baseline wander. The MA removed the remaining noise of the signal that had gone through the SVD filter to make the signal smooth, and squaring played a role in strengthening the signal. In the decision phase, the threshold was used to set the interval before detecting the R-peak. When the latest R-R interval (RRI), suggested by Hamilton et al., was greater than 150% of the previous RRI, the method of detecting the R-peak in such an interval was modified to be 150% or greater than the smallest interval of the two most latest RRIs. When the modified search back system was used, the error rate of the peak detection decreased to 0.29%, compared to 1.34% when the modified search back system was not used. Consequently, the sensitivity was 99.47%, the positive predictivity was 99.47%, and the detection error was 1.05%. Furthermore, the quality of the signal in data with a substantial amount of noise was improved, and thus, the R-peak was detected effectively. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Characteristics of stroke mechanisms in patients with medullary infarction.

PubMed

Lee, M J; Park, Y G; Kim, S J; Lee, J J; Bang, O Y; Kim, J S

2012-11-01

Few studies have focused on the mechanisms underlying medullary infarctions. Our aim in this study was to investigate stroke mechanisms in patients with medullary infarctions and to determine the clinical, radiological and laboratory characteristics of these patients with different underlying stroke etiologies. Consecutive patients with medullary infarction were analysed. Stroke mechanisms were classified as large artery disease (LAD), cardiogenic embolism (CE), small vessel disease (SVD), arterial dissection or undetermined etiology. Clinical, radiological and laboratory factors were analysed according to the location of the lesion and stroke mechanisms. A total of 77 patients were enrolled in this study. Amongst them, 53 (68.8%) patients had lateral medullary infarction (LMI), 22 (28.6%) had medial medullary infarction (MMI), and the remaining 2 (2.6%) had hemimedullary infarction. In both LMI and MMI patients, LAD was the most frequently encountered stroke mechanism. Arterial dissection was the second most common cause followed by SVD and CE in patients with LMI, whereas SVD was more frequently observed (P < 0.001) and dissection and CE were less prevalent (P < 0.001 and P = 0.024, respectively) in MMI than in LMI. Regarding differences amongst stroke etiologies, patients with dissection were younger and had a significantly lower incidence of metabolic syndrome (P = 0.002 and P = 0.009, respectively) than patients with LAD and SVD. Patients in the LAD (19/34, 60%) and dissection groups (12/14, 75%) had abnormal perfusion-weighted MRI (PWI) findings, whereas all patients with SVD (9/9) had normal PWI findings (P < 0.001). Stroke mechanisms in medullary infarction differ between LMI and MMI. Clinical and radiological characteristics, especially PWI features, are helpful in discriminating the etiologies of stroke in these patients. © 2012 The Author(s) European Journal of Neurology © 2012 EFNS.

Swine vesicular disease in northern Italy: diffusion through densely populated pig areas.

PubMed

Bellini, S; Alborali, L; Zanardi, G; Bonazza, V; Brocchi, E

2010-12-01

At the end of 2006, a recrudescence of swine vesicular disease (SVD) was recorded in Italy and the disease spread widely throughout the northern regions. Lombardy, a densely populated pig area, was most affected and the presence of the disease caused heavy economic losses to the entire pig industry. Although SVD is considered only moderately contagious, the epidemic in the north was characterised by a rapid spread of the condition. Numerous difficulties were encountered in eradicating it. Over the past decade, there has been a significant increase in the population of pigs in Lombardy, concentrated mainly in a few areas which were the most severely affected during the 2006 to 2007 SVD epidemic. Increases in both the pig population and animal movements, combined with weak biosecurity measures, increased the spread rate of the disease and hampered eradication activities.

Could Better Phenotyping Small Vessel Disease Provide New Insights into Alzheimer Disease and Improve Clinical Trial Outcomes?

PubMed

Marnane, Michael; Hsiung, Ging-Yuek R

2016-01-01

Alzheimer Disease (AD) is the most common primary cause of dementia with a burgeoning epidemic as life expectancy and general medical care improve worldwide. Recent data from pathologic studies has shown that the cooccurrence of other neurodegenerative and vascular pathologies is in fact the rule rather than the exception. In late onset AD, cerebral small vessel disease (SVD) is almost invariably co-existent to a greater or lesser extent and is known to promote cognitive deterioration. Previous observational studies and clinical trials have largely sought to divide dementia based on predominant neurodegenerative or vascular mechanisms. Given the high degree of overlap, findings from such studies may be difficult to interpret and apply to population cohorts. Additionally opportunities may be lost for uncovering novel interventions that target interactions between co-existent vascular and neurodegenerative pathologies. In the current review, we consider potential pathophysiologic mechanisms through which SVD may be associated with and promote AD pathology. In particular we explore shared environmental and genetic associations and how these may converge via neuroinflammatory pathways potentially providing novel therapeutic targets. SVD has heterogenous manifestations on cerebral imaging and at pathology. We discuss how studying SVD topography may enable us to better identify those at risk for more rapid cognitive decline and improve future clinical trial design.

Using DEDICOM for completely unsupervised part-of-speech tagging.

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

Chew, Peter A.; Bader, Brett William; Rozovskaya, Alla

A standard and widespread approach to part-of-speech tagging is based on Hidden Markov Models (HMMs). An alternative approach, pioneered by Schuetze (1993), induces parts of speech from scratch using singular value decomposition (SVD). We introduce DEDICOM as an alternative to SVD for part-of-speech induction. DEDICOM retains the advantages of SVD in that it is completely unsupervised: no prior knowledge is required to induce either the tagset or the associations of terms with tags. However, unlike SVD, it is also fully compatible with the HMM framework, in that it can be used to estimate emission- and transition-probability matrices which can thenmore » be used as the input for an HMM. We apply the DEDICOM method to the CONLL corpus (CONLL 2000) and compare the output of DEDICOM to the part-of-speech tags given in the corpus, and find that the correlation (almost 0.5) is quite high. Using DEDICOM, we also estimate part-of-speech ambiguity for each term, and find that these estimates correlate highly with part-of-speech ambiguity as measured in the original corpus (around 0.88). Finally, we show how the output of DEDICOM can be evaluated and compared against the more familiar output of supervised HMM-based tagging.« less

Phase unwinding for dictionary compression with multiple channel transmission in magnetic resonance fingerprinting.

PubMed

Lattanzi, Riccardo; Zhang, Bei; Knoll, Florian; Assländer, Jakob; Cloos, Martijn A

2018-06-01

Magnetic Resonance Fingerprinting reconstructions can become computationally intractable with multiple transmit channels, if the B 1 + phases are included in the dictionary. We describe a general method that allows to omit the transmit phases. We show that this enables straightforward implementation of dictionary compression to further reduce the problem dimensionality. We merged the raw data of each RF source into a single k-space dataset, extracted the transceiver phases from the corresponding reconstructed images and used them to unwind the phase in each time frame. All phase-unwound time frames were combined in a single set before performing SVD-based compression. We conducted synthetic, phantom and in-vivo experiments to demonstrate the feasibility of SVD-based compression in the case of two-channel transmission. Unwinding the phases before SVD-based compression yielded artifact-free parameter maps. For fully sampled acquisitions, parameters were accurate with as few as 6 compressed time frames. SVD-based compression performed well in-vivo with highly under-sampled acquisitions using 16 compressed time frames, which reduced reconstruction time from 750 to 25min. Our method reduces the dimensions of the dictionary atoms and enables to implement any fingerprint compression strategy in the case of multiple transmit channels. Copyright © 2018 Elsevier Inc. All rights reserved.

[Serum level of S100B as a marker of progression of vascular mild cognitive impairment into subcortical vascular dementia and therapy effectiveness].

PubMed

Levada, O A; Traïlin, A V

2012-01-01

We evaluated serum level of S100B in 11 patients with subcortical vascular dementia (SVD) and 19 patients with subcortical vascular mild cognitive impairment (SVMCI). Comparable groups were age-matched (79.18 +/- 7.76 in SVD group, 77.84 +/- 3.83 in SVMCI; P = 0.53). 22 patients were assessed after 1 month therapy. It was shown that the serum S100B level significantly increased--(0.065 +/- 0.020) micro/l (P = 0.0005) in SVD patients comparing to SVMCI ones - (0.043 +/- 0.010) microg/l. S100B level was significantly correlated with the clinical parameters: MMSE performance (r(s) = -0.61), CDR (r(s) = 0.58), attention task (r(s) = -0.46), pseudobulbar syndrome severity (r(s) = 0.37) and walking alteration (r(s)= 0.37). In patients with reduction of S100B level due to therapy (positive dynamics, n = 12) we registered significant improvement of some clinical parameters: MMSE, attention level, walking. In patients with increasing of S100B level (negative dynamics, n = 10) we didn't registered improvement of any clinical parameters. We made the conclusion that the serum level of S100B could be used as marker of progression SVMCI into SVD and therapy effectiveness.

Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

NASA Astrophysics Data System (ADS)

Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

2017-12-01

This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

PubMed Central

Maadooliat, Mehdi; Huang, Jianhua Z.

2013-01-01

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence–structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu.edu/∼madoliat/LagSVD) that can be used to produce informative animations. PMID:22926831

Robust image watermarking using DWT and SVD for copyright protection

NASA Astrophysics Data System (ADS)

Harjito, Bambang; Suryani, Esti

2017-02-01

The Objective of this paper is proposed a robust combined Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The RGB image is called a cover medium, and watermark image is converted into gray scale. Then, they are transformed using DWT so that they can be split into several subbands, namely sub-band LL2, LH2, HL2. The watermark image embeds into the cover medium on sub-band LL2. This scheme aims to obtain the higher robustness level than the previous method which performs of SVD matrix factorization image for copyright protection. The experiment results show that the proposed method has robustness against several image processing attacks such as Gaussian, Poisson and Salt and Pepper Noise. In these attacks, noise has average Normalized Correlation (NC) values of 0.574863 0.889784, 0.889782 respectively. The watermark image can be detected and extracted.

Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

NASA Astrophysics Data System (ADS)

Akhbardeh, Alireza; Junnila, Sakari; Koivuluoma, Mikko; Koivistoinen, Teemu; Värri, Alpo

2006-12-01

As we know, singular value decomposition (SVD) is designed for computing singular values (SVs) of a matrix. Then, if it is used for finding SVs of an [InlineEquation not available: see fulltext.]-by-1 or 1-by- [InlineEquation not available: see fulltext.] array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD).'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal). This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs) for ballistocardiogram (BCG) data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

Strict vegetarian diet improves the risk factors associated with metabolic diseases by modulating gut microbiota and reducing intestinal inflammation.

PubMed

Kim, Min-Soo; Hwang, Seong-Soo; Park, Eun-Jin; Bae, Jin-Woo

2013-10-01

Low-grade inflammation of the intestine results in metabolic dysfunction, in which dysbiosis of the gut microbiota is intimately involved. Dietary fibre induces prebiotic effects that may restore imbalances in the gut microbiota; however, no clinical trials have been reported in patients with metabolic diseases. Here, six obese subjects with type 2 diabetes and/or hypertension were assigned to a strict vegetarian diet (SVD) for 1 month, and blood biomarkers of glucose and lipid metabolisms, faecal microbiota using 454-pyrosequencing of 16S ribosomal RNA genes, faecal lipocalin-2 and short-chain fatty acids were monitored. An SVD reduced body weight and the concentrations of triglycerides, total cholesterol, low-density lipoprotein cholesterol and haemoglobin A1c, and improved fasting glucose and postprandial glucose levels. An SVD reduced the Firmicutes-to-Bacteroidetes ratio in the gut microbiota, but did not alter enterotypes. An SVD led to a decrease in the pathobionts such as the Enterobacteriaceae and an increase in commensal microbes such as Bacteroides fragilis and Clostridium species belonging to clusters XIVa and IV, resulting in reduced intestinal lipocalin-2 and short-chain fatty acids levels. This study underscores the benefits of dietary fibre for improving the risk factors of metabolic diseases and shows that increased fibre intake reduces gut inflammation by changing the gut microbiota. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Reduced-rank approximations to the far-field transform in the gridded fast multipole method

NASA Astrophysics Data System (ADS)

Hesford, Andrew J.; Waag, Robert C.

2011-05-01

The fast multipole method (FMM) has been shown to have a reduced computational dependence on the size of finest-level groups of elements when the elements are positioned on a regular grid and FFT convolution is used to represent neighboring interactions. However, transformations between plane-wave expansions used for FMM interactions and pressure distributions used for neighboring interactions remain significant contributors to the cost of FMM computations when finest-level groups are large. The transformation operators, which are forward and inverse Fourier transforms with the wave space confined to the unit sphere, are smooth and well approximated using reduced-rank decompositions that further reduce the computational dependence of the FMM on finest-level group size. The adaptive cross approximation (ACA) is selected to represent the forward and adjoint far-field transformation operators required by the FMM. However, the actual error of the ACA is found to be greater than that predicted using traditional estimates, and the ACA generally performs worse than the approximation resulting from a truncated singular-value decomposition (SVD). To overcome these issues while avoiding the cost of a full-scale SVD, the ACA is employed with more stringent accuracy demands and recompressed using a reduced, truncated SVD. The results show a greatly reduced approximation error that performs comparably to the full-scale truncated SVD without degrading the asymptotic computational efficiency associated with ACA matrix assembly.

Reduced-Rank Approximations to the Far-Field Transform in the Gridded Fast Multipole Method.

PubMed

Hesford, Andrew J; Waag, Robert C

2011-05-10

The fast multipole method (FMM) has been shown to have a reduced computational dependence on the size of finest-level groups of elements when the elements are positioned on a regular grid and FFT convolution is used to represent neighboring interactions. However, transformations between plane-wave expansions used for FMM interactions and pressure distributions used for neighboring interactions remain significant contributors to the cost of FMM computations when finest-level groups are large. The transformation operators, which are forward and inverse Fourier transforms with the wave space confined to the unit sphere, are smooth and well approximated using reduced-rank decompositions that further reduce the computational dependence of the FMM on finest-level group size. The adaptive cross approximation (ACA) is selected to represent the forward and adjoint far-field transformation operators required by the FMM. However, the actual error of the ACA is found to be greater than that predicted using traditional estimates, and the ACA generally performs worse than the approximation resulting from a truncated singular-value decomposition (SVD). To overcome these issues while avoiding the cost of a full-scale SVD, the ACA is employed with more stringent accuracy demands and recompressed using a reduced, truncated SVD. The results show a greatly reduced approximation error that performs comparably to the full-scale truncated SVD without degrading the asymptotic computational efficiency associated with ACA matrix assembly.

Reduced-Rank Approximations to the Far-Field Transform in the Gridded Fast Multipole Method

PubMed Central

Hesford, Andrew J.; Waag, Robert C.

2011-01-01

The fast multipole method (FMM) has been shown to have a reduced computational dependence on the size of finest-level groups of elements when the elements are positioned on a regular grid and FFT convolution is used to represent neighboring interactions. However, transformations between plane-wave expansions used for FMM interactions and pressure distributions used for neighboring interactions remain significant contributors to the cost of FMM computations when finest-level groups are large. The transformation operators, which are forward and inverse Fourier transforms with the wave space confined to the unit sphere, are smooth and well approximated using reduced-rank decompositions that further reduce the computational dependence of the FMM on finest-level group size. The adaptive cross approximation (ACA) is selected to represent the forward and adjoint far-field transformation operators required by the FMM. However, the actual error of the ACA is found to be greater than that predicted using traditional estimates, and the ACA generally performs worse than the approximation resulting from a truncated singular-value decomposition (SVD). To overcome these issues while avoiding the cost of a full-scale SVD, the ACA is employed with more stringent accuracy demands and recompressed using a reduced, truncated SVD. The results show a greatly reduced approximation error that performs comparably to the full-scale truncated SVD without degrading the asymptotic computational efficiency associated with ACA matrix assembly. PMID:21552350

Spectral Biclustering of Microarray Data: Coclustering Genes and Conditions

PubMed Central

Kluger, Yuval; Basri, Ronen; Chang, Joseph T.; Gerstein, Mark

2003-01-01

Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find “marker genes” that are differentially expressed in particular sets of “conditions.” We have developed a method that simultaneously clusters genes and conditions, finding distinctive “checkerboard” patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data). PMID:12671006

Linear signatures in nonlinear gyrokinetics: interpreting turbulence with pseudospectra

DOE PAGES

Hatch, D. R.; Jenko, F.; Navarro, A. Banon; ...

2016-07-26

A notable feature of plasma turbulence is its propensity to retain features of the underlying linear eigenmodes in a strongly turbulent state—a property that can be exploited to predict various aspects of the turbulence using only linear information. In this context, this work examines gradient-driven gyrokinetic plasma turbulence through three lenses—linear eigenvalue spectra, pseudospectra, and singular value decomposition (SVD). We study a reduced gyrokinetic model whose linear eigenvalue spectra include ion temperature gradient driven modes, stable drift waves, and kinetic modes representing Landau damping. The goal is to characterize in which ways, if any, these familiar ingredients are manifest inmore » the nonlinear turbulent state. This pursuit is aided by the use of pseudospectra, which provide a more nuanced view of the linear operator by characterizing its response to perturbations. We introduce a new technique whereby the nonlinearly evolved phase space structures extracted with SVD are linked to the linear operator using concepts motivated by pseudospectra. Using this technique, we identify nonlinear structures that have connections to not only the most unstable eigenmode but also subdominant modes that are nonlinearly excited. The general picture that emerges is a system in which signatures of the linear physics persist in the turbulence, albeit in ways that cannot be fully explained by the linear eigenvalue approach; a non-modal treatment is necessary to understand key features of the turbulence.« less

Association of Chronic Kidney Disease With Small Vessel Disease in Patients With Hypertensive Intracerebral Hemorrhage.

PubMed

Tsai, Yuan-Hsiung; Lee, Meng; Lin, Leng-Chieh; Chang, Sheng-Wei; Weng, Hsu-Huei; Yang, Jen-Tsung; Huang, Yen-Chu; Lee, Ming-Hsueh

2018-01-01

Chronic kidney disease (CKD) has been closely associated with hypertension and stroke. Although studies have reported the relationship between CKD and cerebral small vessel disease (SVD), the link between CKD, hypertension, and SVD is uncertain. The aim of this study was to investigate the association between CKD and SVD in patients with strictly hypertensive intracerebral hemorrhage (ICH). 142 patients with acute hypertensive ICH were enrolled in this study. Magnetic resonance imaging was performed to assess imaging markers for SVD. Patients were categorized into three CKD groups based on the degree of kidney dysfunction [glomerular filtration rate (GFR) in milliliters per minute per 1.73 m 2 ]: normal kidney function (GFR ≥ 90), mild kidney disease (60 ≤ GFR < 90), and moderate to severe kidney disease (GFR < 60). The prevalence rate of mild and moderate to severe CKD was 50 and 14.8%, respectively. The stage of CKD was associated with history of chronic hypertension ( p  = 0.046) as well as the prevalence rate of overall and deep cerebral microbleed (CMB) ( p  = 0.001 and p  = 0.002, respectively). The stage of CKD was a significant risk factor for deep white matter hyperintensity (WMH) (OR 1.848; 95% CI 1.022-3.343, p  = 0.042), overall CMB (OR 2.628; 95% CI 1.462-4.724, p  = 0.001), lobar CMB (OR 2.106; 95% CI 1.119-3.963, p  = 0.021), and deep CMB (OR 2.237; 95% CI 1.263-3.960, p  = 0.006), even after adjustment for confounders. In patients with hypertensive ICH, the prevalence of CKD is high even at the early stage of renal function impairment and is associated with the prevalence of CMB and deep WMH. These results reinforce the notion of a link between hypertensive vasculopathy, renal function impairment, and cerebral SVD.

Causality analysis of leading singular value decomposition modes identifies rotor as the dominant driving normal mode in fibrillation

NASA Astrophysics Data System (ADS)

Biton, Yaacov; Rabinovitch, Avinoam; Braunstein, Doron; Aviram, Ira; Campbell, Katherine; Mironov, Sergey; Herron, Todd; Jalife, José; Berenfeld, Omer

2018-01-01

Cardiac fibrillation is a major clinical and societal burden. Rotors may drive fibrillation in many cases, but their role and patterns are often masked by complex propagation. We used Singular Value Decomposition (SVD), which ranks patterns of activation hierarchically, together with Wiener-Granger causality analysis (WGCA), which analyses direction of information among observations, to investigate the role of rotors in cardiac fibrillation. We hypothesized that combining SVD analysis with WGCA should reveal whether rotor activity is the dominant driving force of fibrillation even in cases of high complexity. Optical mapping experiments were conducted in neonatal rat cardiomyocyte monolayers (diameter, 35 mm), which were genetically modified to overexpress the delayed rectifier K+ channel IKr only in one half of the monolayer. Such monolayers have been shown previously to sustain fast rotors confined to the IKr overexpressing half and driving fibrillatory-like activity in the other half. SVD analysis of the optical mapping movies revealed a hierarchical pattern in which the primary modes corresponded to rotor activity in the IKr overexpressing region and the secondary modes corresponded to fibrillatory activity elsewhere. We then applied WGCA to evaluate the directionality of influence between modes in the entire monolayer using clear and noisy movies of activity. We demonstrated that the rotor modes influence the secondary fibrillatory modes, but influence was detected also in the opposite direction. To more specifically delineate the role of the rotor in fibrillation, we decomposed separately the respective SVD modes of the rotor and fibrillatory domains. In this case, WGCA yielded more information from the rotor to the fibrillatory domains than in the opposite direction. In conclusion, SVD analysis reveals that rotors can be the dominant modes of an experimental model of fibrillation. Wiener-Granger causality on modes of the rotor domains confirms their preferential driving influence on fibrillatory modes.

Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD.

PubMed

Bullinaria, John A; Levy, Joseph P

2012-09-01

In a previous article, we presented a systematic computational study of the extraction of semantic representations from the word-word co-occurrence statistics of large text corpora. The conclusion was that semantic vectors of pointwise mutual information values from very small co-occurrence windows, together with a cosine distance measure, consistently resulted in the best representations across a range of psychologically relevant semantic tasks. This article extends that study by investigating the use of three further factors--namely, the application of stop-lists, word stemming, and dimensionality reduction using singular value decomposition (SVD)--that have been used to provide improved performance elsewhere. It also introduces an additional semantic task and explores the advantages of using a much larger corpus. This leads to the discovery and analysis of improved SVD-based methods for generating semantic representations (that provide new state-of-the-art performance on a standard TOEFL task) and the identification and discussion of problems and misleading results that can arise without a full systematic study.

Asymmetric color image encryption based on singular value decomposition

NASA Astrophysics Data System (ADS)

Yao, Lili; Yuan, Caojin; Qiang, Junjie; Feng, Shaotong; Nie, Shouping

2017-02-01

A novel asymmetric color image encryption approach by using singular value decomposition (SVD) is proposed. The original color image is encrypted into a ciphertext shown as an indexed image by using the proposed method. The red, green and blue components of the color image are subsequently encoded into a complex function which is then separated into U, S and V parts by SVD. The data matrix of the ciphertext is obtained by multiplying orthogonal matrices U and V while implementing phase-truncation. Diagonal entries of the three diagonal matrices of the SVD results are abstracted and scrambling combined to construct the colormap of the ciphertext. Thus, the encrypted indexed image covers less space than the original image. For decryption, the original color image cannot be recovered without private keys which are obtained from phase-truncation and the orthogonality of V. Computer simulations are presented to evaluate the performance of the proposed algorithm. We also analyze the security of the proposed system.

Label consistent K-SVD: learning a discriminative dictionary for recognition.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2013-11-01

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More specifically, we introduce a new label consistency constraint called "discriminative sparse-code error" and combine it with the reconstruction error and the classification error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. Our algorithm learns a single overcomplete dictionary and an optimal linear classifier jointly. The incremental dictionary learning algorithm is presented for the situation of limited memory resources. It yields dictionaries so that feature points with the same class labels have similar sparse codes. Experimental results demonstrate that our algorithm outperforms many recently proposed sparse-coding techniques for face, action, scene, and object category recognition under the same learning conditions.

A general approach to regularizing inverse problems with regional data using Slepian wavelets

NASA Astrophysics Data System (ADS)

Michel, Volker; Simons, Frederik J.

2017-12-01

Slepian functions are orthogonal function systems that live on subdomains (for example, geographical regions on the Earth’s surface, or bandlimited portions of the entire spectrum). They have been firmly established as a useful tool for the synthesis and analysis of localized (concentrated or confined) signals, and for the modeling and inversion of noise-contaminated data that are only regionally available or only of regional interest. In this paper, we consider a general abstract setup for inverse problems represented by a linear and compact operator between Hilbert spaces with a known singular-value decomposition (svd). In practice, such an svd is often only given for the case of a global expansion of the data (e.g. on the whole sphere) but not for regional data distributions. We show that, in either case, Slepian functions (associated to an arbitrarily prescribed region and the given compact operator) can be determined and applied to construct a regularization for the ill-posed regional inverse problem. Moreover, we describe an algorithm for constructing the Slepian basis via an algebraic eigenvalue problem. The obtained Slepian functions can be used to derive an svd for the combination of the regionalizing projection and the compact operator. As a result, standard regularization techniques relying on a known svd become applicable also to those inverse problems where the data are regionally given only. In particular, wavelet-based multiscale techniques can be used. An example for the latter case is elaborated theoretically and tested on two synthetic numerical examples.

Interactions and consequences of silicon, nitrogen, and Fusarium palustre on herbivory and DMSP levels of Spartina alterniflora

NASA Astrophysics Data System (ADS)

Bazzano, Magalí; Elmer, Wade

2017-11-01

Sudden Vegetation Dieback (SVD) has been associated with multiple factors affecting the health of Spartina alterniflora. These include altered nutrition (N, Si and various metals), herbivory from the purple marsh crab, and the association with a fungal pathogen (Fusarium palustre). A metabolite produced by Spartina alterniflora that has been associated with plant health is dimethylsulfoniopropionate (DMSP), but little information exist on how these biotic stressors and nutrition interact to affect DMSP levels. Understanding how these factors might be interrelated might provide insight into the etiology of SVD. Surveys of a marsh affected by SVD confirmed lower levels of DMSP and higher concentrations of Si and other metals were present in Sp. alterniflora when compared to plants from marsh that exhibited no signs of SVD. In repeated greenhouse experiments, the application of Si to Sp. alterniflora had no effect on DMSP concentrations. However, when plants were inoculated with the pathogenic fungus, Fusarium palustre, and then treated with Si, DMSP levels were elevated 27%. Inoculation alone had no effect on DMSP levels. Si application neither favor growth nor suppress the stunting effect of disease by F. palustre. Furthermore, grazing by Sesarma reticulatum, a herbivorous crab, was not affected by Si nutrition. Grazing was increased by nitrogen fertilization and inoculation with F. palustre. Deciphering the role of Si nutrition in Sp. alterniflora and dieback remains unresolved, but no evidence suggests enhancing Si nutrition would directly favor marsh health.

East Asian Summer Monsoon Rainfall: A Historical Perspective of the 1998 Flood over Yangtze River

NASA Technical Reports Server (NTRS)

Weng, H.-Y.; Lau, K.-M.

1999-01-01

One of the main factors that might have caused the disastrous flood in China during 1998 summer is long-term variations that include a trend indicating increasing monsoon rainfall over the Yangtze River Valley. China's 160-station monthly rainfall anomaly for the summers of 1955-98 is analyzed for exploring such long-term variations. Singular value decomposition (SVD) between the summer rainfall and the global sea surface temperature (SST) anomalies reveals that the rainfall over Yangtze River Valley is closely related to global and regional SST variabilities at both interannual and interdecadal timescales. SVD1 mode links the above normal rainfall condition in central China to an El Nino-like SSTA distribution, varying on interannual timescale modified by a trend during the period. SVD3 mode links positive rainfall anomaly in Yangtze River Valley to the warm SST anomaly in the subtropical western Pacific, varying on interannual timescales modified by interdecadal timescales. This link tends to be stronger when the Nino3 area becomes colder and the western subtropical Pacific becomes warmer. The 1998 summer is a transition season when the 1997/98 El Nino event was in its decaying phase, and the SST in the Nino3 area emerged below normal anomaly while the subtropical western Pacific SST above normal. Thus, the first and third SVD modes become dominant in 1998 summer, favoring more Asian summer monsoon rainfall over the Yangtze River Valley.

A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery

NASA Astrophysics Data System (ADS)

Zhao, Ming; Jia, Xiaodong

2017-09-01

Singular value decomposition (SVD), as an effective signal denoising tool, has been attracting considerable attention in recent years. The basic idea behind SVD denoising is to preserve the singular components (SCs) with significant singular values. However, it is shown that the singular values mainly reflect the energy of decomposed SCs, therefore traditional SVD denoising approaches are essentially energy-based, which tend to highlight the high-energy regular components in the measured signal, while ignoring the weak feature caused by early fault. To overcome this issue, a reweighted singular value decomposition (RSVD) strategy is proposed for signal denoising and weak feature enhancement. In this work, a novel information index called periodic modulation intensity is introduced to quantify the diagnostic information in a mechanical signal. With this index, the decomposed SCs can be evaluated and sorted according to their information levels, rather than energy. Based on that, a truncated linear weighting function is proposed to control the contribution of each SC in the reconstruction of the denoised signal. In this way, some weak but informative SCs could be highlighted effectively. The advantages of RSVD over traditional approaches are demonstrated by both simulated signals and real vibration/acoustic data from a two-stage gearbox as well as train bearings. The results demonstrate that the proposed method can successfully extract the weak fault feature even in the presence of heavy noise and ambient interferences.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices.

PubMed

Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert

2010-03-01

We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 10(6) × 10(6) incomplete matrix with 10(5) observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices

PubMed Central

Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert

2010-01-01

We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 106 × 106 incomplete matrix with 105 observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques. PMID:21552465

Evolution of gut microbiota composition from birth to 24 weeks in the INFANTMET Cohort.

PubMed

Hill, Cian J; Lynch, Denise B; Murphy, Kiera; Ulaszewska, Marynka; Jeffery, Ian B; O'Shea, Carol Anne; Watkins, Claire; Dempsey, Eugene; Mattivi, Fulvio; Tuohy, Kieran; Ross, R Paul; Ryan, C Anthony; O' Toole, Paul W; Stanton, Catherine

2017-01-17

The gut is the most extensively studied niche of the human microbiome. The aim of this study was to characterise the initial gut microbiota development of a cohort of breastfed infants (n = 192) from 1 to 24 weeks of age. V4-V5 region 16S rRNA amplicon Illumina sequencing and, in parallel, bacteriological culture. The metabolomic profile of infant urine at 4 weeks of age was also examined by LC-MS. Full-term (FT), spontaneous vaginally delivered (SVD) infants' microbiota remained stable at both phylum and genus levels during the 24-week period examined. FT Caesarean section (CS) infants displayed an increased faecal abundance of Firmicutes (p < 0.01) and lower abundance of Actinobacteria (p < 0.001) after the first week of life compared to FT-SVD infants. FT-CS infants gradually progressed to harbouring a microbiota closely resembling FT-SVD (which remained stable) by week 8 of life, which was maintained at week 24. The gut microbiota of preterm (PT) infants displayed a significantly greater abundance of Proteobacteria compared to FT infants (p < 0.001) at week 1. Metabolomic analysis of urine at week 4 indicated PT-CS infants have a functionally different metabolite profile than FT (both CS and SVD) infants. Co-inertia analysis showed co-variation between the urine metabolome and the faecal microbiota of the infants. Tryptophan and tyrosine metabolic pathways, as well as fatty acid and bile acid metabolism, were found to be affected by delivery mode and gestational age. These findings confirm that mode of delivery and gestational age both have significant effects on early neonatal microbiota composition. There is also a significant difference between the metabolite profile of FT and PT infants. Prolonged breastfeeding was shown to have a significant effect on the microbiota composition of FT-CS infants at 24 weeks of age, but interestingly not on that of FT-SVD infants. Twins had more similar microbiota to one another than between two random infants, reflecting the influence of similarities in both host genetics and the environment on the microbiota..

[Immediate fetal-maternal morbidity of first instrumental vaginal delivery using Thierry's spatulas. A prospective continuous study of 195 fetal extractions].

PubMed

Parant, O; Simon-Toulza, C; Capdet, J; Fuzier, V; Arnaud, C; Rème, J-M

2009-10-01

To investigate the immediate fetal-maternal morbidity related to Thierry's spatula for first instrumental vaginal delivery. We conducted a prospective observational study in Toulouse university hospital, including primiparas who vaginally delivered a live singleton cephalic infant>36 WG, between December 2005 and June 2006. Instrumental deliveries were performed using short spatulas in all cases. Outcome measures were: perineal complications (episiotomy, laceration and associated lesions, urinary retention, pain at H48), neonatal morbidity (cutaneous injuries, neonatal transfer, cord pH, Apgar score). Instrumental deliveries were compared with spontaneous vaginal deliveries (SVD). Six hundred and eight primiparas were included, distributed in 195 extractions (32%) and 413 SVD (68%). Spatulas allowed fetal extraction in all cases. Main differences between the two groups were: length of labour, occiput posterior position (12.8% for spatulas vs 1.7% for SVD; p<0.0001), episiotomy rate (97.9% vs 51.3%; p<0.0001), severe perineal lacerations (3.6% vs 0.2%; p=0.0007), post-partum morbidity (pain, hematoma, and urinary retention). No case of early severe neonatal complication was related to the use of the spatulas. Perineal complications (severe lacerations) associated with spatulas are increased with regard to SVD, but comparable to that reported with forceps. The main disadvantage is the high frequency of episiotomy, which should not be systematic. Neonatal morbidity is reduced. Comparative studies (spatulas vs. other procedures) are needed to confirm these data, but spatulas remain a multipurpose instrument which should continue to be taught.

Extracellular matrix inflammation in vascular cognitive impairment and dementia.

PubMed

Rosenberg, Gary A

2017-03-01

Vascular cognitive impairment and dementia (VCID) include a wide spectrum of chronic manifestations of vascular disease related to large vessel strokes and small vessel disease (SVD). Lacunar strokes and white matter (WM) injury are consequences of SVD. The main vascular risk factor for SVD is brain hypoperfusion from cerebral blood vessel narrowing due to chronic hypertension. The hypoperfusion leads to activation and degeneration of astrocytes with the resulting fibrosis of the extracellular matrix (ECM). Elasticity is lost in fibrotic cerebral vessels, reducing the response of stiffened blood vessels in times of increased metabolic need. Intermittent hypoxia/ischaemia activates a molecular injury cascade, producing an incomplete infarction that is most damaging to the deep WM, which is a watershed region for cerebral blood flow. Neuroinflammation caused by hypoxia activates microglia/macrophages to release proteases and free radicals that perpetuate the damage over time to molecules in the ECM and the neurovascular unit (NVU). Matrix metalloproteinases (MMPs) secreted in an attempt to remodel the blood vessel wall have the undesired consequences of opening the blood-brain barrier (BBB) and attacking myelinated fibres. This dual effect of the MMPs causes vasogenic oedema in WM and vascular demyelination, which are the hallmarks of the subcortical ischaemic vascular disease (SIVD), which is the SVD form of VCID also called Binswanger's disease (BD). Unravelling the complex pathophysiology of the WM injury-related inflammation in the small vessel form of VCID could lead to novel therapeutic strategies to reduce damage to the ECM, preventing the progressive damage to the WM. © 2017 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD).

PubMed

Bermúdez Ordoñez, Juan Carlos; Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-05-16

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ 1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain.

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD)

PubMed Central

Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-01-01

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain. PMID:29772731

Long-Term Outcome of the Sorin Freedom SOLO Stentless Aortic Valve.

PubMed

Christ, Torsten; Claus, Benjamin; Zielinski, Christina; Falk, Volkmar; Grubitzsch, Herko

2016-11-01

The Sorin Freedom SOLO valve is a third-generation stentless aortic valve which shows beneficial hemodynamic performance compared to stented bioprostheses. Long-term results regarding hemodynamics, the durability of the valve, and patient outcome are scarce, and their acquisition was the aim of this single-center study. Between 2005 and 2006, a total of 68 consecutive patients (30 males, 38 females; mean age at surgery 76.1 ± 6.3 years) underwent aortic valve replacement with a Sorin Freedom SOLO prosthesis. Indications were aortic stenosis (n = 50), aortic regurgitation (n = 1) and mixed lesions (n = 17). Associated procedures were performed in 31 patients (45.6%), most of which were coronary artery bypass grafting (68.8 %). The follow up was performed by telephone interviews, and clinical and echocardiographic examinations. Morbidity, mortality and echocardiographic data were analyzed. The total follow up was 501.1 patient-years, with a mean follow up of 7.4 ± 3.4 years (maximum 11.2 years). The follow up was 100% complete. Hospital mortality was 4.4% (n = 3). Actuarial survival at five and 10 years was 76.5 ± 5.1% and 41.5 ± 6.5%, respectively. Reinterventions were performed in eight patients; these included three reoperations due to endocarditis, four transcatheter aortic valve implantations, and one reoperation due to structural valve deterioration (SVD). The overall freedom from valve reintervention due to SVD at five and 10 years was 97.8 ± 2.2% and 82.9 ± 7.5%, respectively. After eight years, echocardiography demonstrated peak and mean transvalvular gradients of 18 ± 11 and 10 ± 7 mmHg, respectively. The overall effective and indexed aortic valve orifice areas were 1.73 ± 0.58 cm2 and 0.92 ± 0.33 cm2/m2, respectively. At long-term follow up the Sorin Freedom SOLO bioprosthesis was associated with favourable hemodynamic results and survival. Freedom from SVD was not superior to that occurring with stented bioprostheses.

A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation

NASA Astrophysics Data System (ADS)

Vijverberg, Koen; Ghafoorian, Mohsen; van Uden, Inge W. M.; de Leeuw, Frank-Erik; Platel, Bram; Heskes, Tom

2016-03-01

Cerebral small vessel disease (SVD) is a disorder frequently found among the old people and is associated with deterioration in cognitive performance, parkinsonism, motor and mood impairments. White matter hyperintensities (WMH) as well as lacunes, microbleeds and subcortical brain atrophy are part of the spectrum of image findings, related to SVD. Accurate segmentation of WMHs is important for prognosis and diagnosis of multiple neurological disorders such as MS and SVD. Almost all of the published (semi-)automated WMH detection models employ multiple complex hand-crafted features, which require in-depth domain knowledge. In this paper we propose to apply a single-layer network unsupervised feature learning (USFL) method to avoid hand-crafted features, but rather to automatically learn a more efficient set of features. Experimental results show that a computer aided detection system with a USFL system outperforms a hand-crafted approach. Moreover, since the two feature sets have complementary properties, a hybrid system that makes use of both hand-crafted and unsupervised learned features, shows a significant performance boost compared to each system separately, getting close to the performance of an independent human expert.

The effect of caesarean section on self-esteem amongst primiparous women in South-Western Nigeria: a case-control study.

PubMed

Loto, Olabisi M; Adewuya, Abiodun O; Ajenifuja, Olusegun K; Orji, Ernest O; Owolabi, Alexander T; Ogunniyi, Solomon O

2009-09-01

This study aims to assess the level of self-esteem of newly delivered mothers who had caesarean section (CS) and evaluate the sociodemographic and obstetrics correlates of low self-esteem in them. Newly delivered mothers who had CS (n = 109) and who had spontaneous vaginal delivery (SVD) (n = 97) completed questionnaires on sociodemographic and obstetrics variables within 1 week of delivery. They also completed the Rosenberg self-esteem scale. RESULTS. Women with CS had statistically significant lower scores on the self-esteem scale than women with SVD (p = 0.006). Thirty (27.5%) of the CS group were classified as having low self-esteem compared with 11 (11.3%) of the SVD group (p = 004). The correlates of low self-esteem in the CS group included polygamy (odd ratio (OR) 4.99, 95% confidence interval (95% CI) 1.62-15.33) and emergency CS (OR 4.66, 95% CI 1.55-16.75). CS in South-Western Nigerian women is associated with lowered self-esteem in the mothers.

An analysis dictionary learning algorithm under a noisy data model with orthogonality constraint.

PubMed

Zhang, Ye; Yu, Tenglong; Wang, Wenwu

2014-01-01

Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements. This, however, renders a computationally slow optimization process and potentially unreliable estimation (if the noise level is high), as represented by the Analysis K-SVD (AK-SVD) algorithm. The other problem is the trivial solution to the dictionary, for example, the null dictionary matrix that may be given by a dictionary learning algorithm, as discussed in the learning overcomplete sparsifying transform (LOST) algorithm. Here we propose a novel optimization model and an iterative algorithm to learn the analysis dictionary, where we directly employ the observed data to compute the approximate analysis sparse representation of the original signals (leading to a fast optimization procedure) and enforce an orthogonality constraint on the optimization criterion to avoid the trivial solutions. Experiments demonstrate the competitive performance of the proposed algorithm as compared with three baselines, namely, the AK-SVD, LOST, and NAAOLA algorithms.

Using linear algebra for protein structural comparison and classification

PubMed Central

2009-01-01

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in. PMID:21637532

Using linear algebra for protein structural comparison and classification.

PubMed

Gomide, Janaína; Melo-Minardi, Raquel; Dos Santos, Marcos Augusto; Neshich, Goran; Meira, Wagner; Lopes, Júlio César; Santoro, Marcelo

2009-07-01

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.

A novel key-frame extraction approach for both video summary and video index.

PubMed

Lei, Shaoshuai; Xie, Gang; Yan, Gaowei

2014-01-01

Existing key-frame extraction methods are basically video summary oriented; yet the index task of key-frames is ignored. This paper presents a novel key-frame extraction approach which can be available for both video summary and video index. First a dynamic distance separability algorithm is advanced to divide a shot into subshots based on semantic structure, and then appropriate key-frames are extracted in each subshot by SVD decomposition. Finally, three evaluation indicators are proposed to evaluate the performance of the new approach. Experimental results show that the proposed approach achieves good semantic structure for semantics-based video index and meanwhile produces video summary consistent with human perception.

Impact of Strategically Located White Matter Hyperintensities on Cognition in Memory Clinic Patients with Small Vessel Disease.

PubMed

Biesbroek, J Matthijs; Weaver, Nick A; Hilal, Saima; Kuijf, Hugo J; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Postma, Albert; Biessels, Geert Jan; Chen, Christopher P L H

2016-01-01

Studies on the impact of small vessel disease (SVD) on cognition generally focus on white matter hyperintensity (WMH) volume. The extent to which WMH location relates to cognitive performance has received less attention, but is likely to be functionally important. We examined the relation between WMH location and cognition in a memory clinic cohort of patients with sporadic SVD. A total of 167 patients with SVD were recruited from memory clinics. Assumption-free region of interest-based analyses based on major white matter tracts and voxel-wise analyses were used to determine the association between WMH location and executive functioning, visuomotor speed and memory. Region of interest-based analyses showed that WMHs located particularly within the anterior thalamic radiation and forceps minor were inversely associated with both executive functioning and visuomotor speed, independent of total WMH volume. Memory was significantly associated with WMH volume in the forceps minor, independent of total WMH volume. An independent assumption-free voxel-wise analysis identified strategic voxels in these same tracts. Region of interest-based analyses showed that WMH volume within the anterior thalamic radiation explained 6.8% of variance in executive functioning, compared to 3.9% for total WMH volume; WMH volume within the forceps minor explained 4.6% of variance in visuomotor speed and 4.2% of variance in memory, compared to 1.8% and 1.3% respectively for total WMH volume. Our findings identify the anterior thalamic radiation and forceps minor as strategic white matter tracts in which WMHs are most strongly associated with cognitive impairment in memory clinic patients with SVD. WMH volumes in individual tracts explained more variance in cognition than total WMH burden, emphasizing the importance of lesion location when addressing the functional consequences of WMHs.

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.

PubMed

Till, Kevin; Jones, Ben L; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification.

Prevalence of CADASIL and Fabry Disease in a Cohort of MRI Defined Younger Onset Lacunar Stroke

PubMed Central

Kilarski, Laura L.; Rutten-Jacobs, Loes C. A.; Bevan, Steve; Baker, Rob; Hassan, Ahamad; Hughes, Derralynn A.; Markus, Hugh S.

2015-01-01

Background and Purpose Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), caused by mutations in the NOTCH3 gene, is the most common monogenic disorder causing lacunar stroke and cerebral small vessel disease (SVD). Fabry disease (FD) due to mutations in the GLA gene has been suggested as an underdiagnosed cause of stroke, and one feature is SVD. Previous studies reported varying prevalence of CADASIL and FD in stroke, likely due to varying subtypes studied; no studies have looked at a large cohort of younger onset SVD. We determined the prevalence in a well-defined, MRI-verified cohort of apparently sporadic patients with lacunar infarct. Methods Caucasian patients with lacunar infarction, aged ≤70 years (mean age 56.7 (SD8.6)), were recruited from 72 specialist stroke centres throughout the UK as part of the Young Lacunar Stroke DNA Resource. Patients with a previously confirmed monogenic cause of stroke were excluded. All MRI’s and clinical histories were reviewed centrally. Screening was performed for NOTCH3 and GLA mutations. Results Of 994 subjects five had pathogenic NOTCH3 mutations (R169C, R207C, R587C, C1222G and C323S) all resulting in loss or gain of a cysteine in the NOTCH3 protein. All five patients had confluent leukoaraiosis (Fazekas grade ≥2). CADASIL prevalence overall was 0.5% (95% CI 0.2%-1.1%) and among cases with confluent leukoaraiosis 1.5% (95% CI 0.6%-3.3%). No classic pathogenic FD mutations were found; one patient had a missense mutation (R118C), associated with late-onset FD. Conclusion CADASIL cases are rare and only detected in SVD patients with confluent leukoaraiosis. No definite FD cases were detected. PMID:26305465

Evaluation of glioblastomas and lymphomas with whole-brain CT perfusion: Comparison between a delay-invariant singular-value decomposition algorithm and a Patlak plot.

PubMed

Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Kikuchi, Kazufumi; Yoshimoto, Koji; Mizoguchi, Masahiro; Suzuki, Satoshi O; Yoshiura, Takashi; Honda, Hiroshi

2016-07-01

Correction of contrast leakage is recommended when enhancing lesions during perfusion analysis. The purpose of this study was to assess the diagnostic performance of computed tomography perfusion (CTP) with a delay-invariant singular-value decomposition algorithm (SVD+) and a Patlak plot in differentiating glioblastomas from lymphomas. This prospective study included 17 adult patients (12 men and 5 women) with pathologically proven glioblastomas (n=10) and lymphomas (n=7). CTP data were analyzed using SVD+ and a Patlak plot. The relative tumor blood volume and flow compared to contralateral normal-appearing gray matter (rCBV and rCBF derived from SVD+, and rBV and rFlow derived from the Patlak plot) were used to differentiate between glioblastomas and lymphomas. The Mann-Whitney U test and receiver operating characteristic (ROC) analyses were used for statistical analysis. Glioblastomas showed significantly higher rFlow (3.05±0.49, mean±standard deviation) than lymphomas (1.56±0.53; P<0.05). There were no statistically significant differences between glioblastomas and lymphomas in rBV (2.52±1.57 vs. 1.03±0.51; P>0.05), rCBF (1.38±0.41 vs. 1.29±0.47; P>0.05), or rCBV (1.78±0.47 vs. 1.87±0.66; P>0.05). ROC analysis showed the best diagnostic performance with rFlow (Az=0.871), followed by rBV (Az=0.771), rCBF (Az=0.614), and rCBV (Az=0.529). CTP analysis with a Patlak plot was helpful in differentiating between glioblastomas and lymphomas, but CTP analysis with SVD+ was not. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Efficient 3D Watermarked Video Communication with Chaotic Interleaving, Convolution Coding, and LMMSE Equalization

NASA Astrophysics Data System (ADS)

El-Shafai, W.; El-Bakary, E. M.; El-Rabaie, S.; Zahran, O.; El-Halawany, M.; Abd El-Samie, F. E.

2017-06-01

Three-Dimensional Multi-View Video (3D-MVV) transmission over wireless networks suffers from Macro-Blocks losses due to either packet dropping or fading-motivated bit errors. Thus, the robust performance of 3D-MVV transmission schemes over wireless channels becomes a recent considerable hot research issue due to the restricted resources and the presence of severe channel errors. The 3D-MVV is composed of multiple video streams shot by several cameras around a single object, simultaneously. Therefore, it is an urgent task to achieve high compression ratios to meet future bandwidth constraints. Unfortunately, the highly-compressed 3D-MVV data becomes more sensitive and vulnerable to packet losses, especially in the case of heavy channel faults. Thus, in this paper, we suggest the application of a chaotic Baker interleaving approach with equalization and convolution coding for efficient Singular Value Decomposition (SVD) watermarked 3D-MVV transmission over an Orthogonal Frequency Division Multiplexing wireless system. Rayleigh fading and Additive White Gaussian Noise are considered in the real scenario of 3D-MVV transmission. The SVD watermarked 3D-MVV frames are primarily converted to their luminance and chrominance components, which are then converted to binary data format. After that, chaotic interleaving is applied prior to the modulation process. It is used to reduce the channel effects on the transmitted bit streams and it also adds a degree of encryption to the transmitted 3D-MVV frames. To test the performance of the proposed framework; several simulation experiments on different SVD watermarked 3D-MVV frames have been executed. The experimental results show that the received SVD watermarked 3D-MVV frames still have high Peak Signal-to-Noise Ratios and watermark extraction is possible in the proposed framework.

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis

PubMed Central

Till, Kevin; Jones, Ben L.; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B.

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; p<0.001), although it could not distinguish between future professional and academy players. The validation dataset model was able to distinguish future professionals from the rest with reasonable accuracy (sensitivity = 83.3%, specificity = 63.8%; p = 0.003). Through the use of SVD analysis it was possible to objectively identify criteria to distinguish future career attainment with a sensitivity over 80% using anthropometric and fitness data alone. As such, this suggests that SVD analysis may be a useful analysis tool for research and practice within talent identification. PMID:27224653

Two Dimensional Finite Element Based Magnetotelluric Inversion using Singular Value Decomposition Method on Transverse Electric Mode

NASA Astrophysics Data System (ADS)

Tjong, Tiffany; Yihaa’ Roodhiyah, Lisa; Nurhasan; Sutarno, Doddy

2018-04-01

In this work, an inversion scheme was performed using a vector finite element (VFE) based 2-D magnetotelluric (MT) forward modelling. We use an inversion scheme with Singular value decomposition (SVD) method toimprove the accuracy of MT inversion.The inversion scheme was applied to transverse electric (TE) mode of MT. SVD method was used in this inversion to decompose the Jacobian matrices. Singular values which obtained from the decomposition process were analyzed. This enabled us to determine the importance of data and therefore to define a threshold for truncation process. The truncation of singular value in inversion processcould improve the resulted model.

Fast analytical spectral filtering methods for magnetic resonance perfusion quantification.

PubMed

Reddy, Kasireddy V; Mitra, Abhishek; Yalavarthy, Phaneendra K

2016-08-01

The deconvolution in the perfusion weighted imaging (PWI) plays an important role in quantifying the MR perfusion parameters. The PWI application to stroke and brain tumor studies has become a standard clinical practice. The standard approach for this deconvolution is oscillatory-limited singular value decomposition (oSVD) and frequency domain deconvolution (FDD). The FDD is widely recognized as the fastest approach currently available for deconvolution of MR perfusion data. In this work, two fast deconvolution methods (namely analytical fourier filtering and analytical showalter spectral filtering) are proposed. Through systematic evaluation, the proposed methods are shown to be computationally efficient and quantitatively accurate compared to FDD and oSVD.

Are there still roles for exocrine bladder drainage and portal venous drainage for pancreatic allografts?

PubMed

Young, Carlton J

2009-02-01

Controversy remains regarding the best methodology of handling exocrine pancreatic fluid and pancreatic venous effluent. Bladder drainage has given way to enteric drainage. However, is there an instance in which bladder drainage is preferable? Also, hyperinsulinemia, as a result of systemic venous drainage (SVD), is claimed to be proatherosclerotic, whereas portal venous drainage (PVD) is more physiologic and less atherosclerotic. Bladder drainage remains a viable method of exocrine pancreas drainage, but evidence is sparse that measuring urinary amylase has a substantial benefit in the early detection of acute rejection in all types of pancreas transplants. Currently, there is no incontrovertible evidence that systemic hyperinsulinemia is proatherosclerotic, whereas recent metabolic studies on SVD and PVD showed that there was no benefit to PVD. Given the advent of newer immunosuppressive agents and overall lower acute rejection rates, the perceived benefit of bladder drainage as a means to measure urinary amylase as an early marker of rejection has not been substantiated. However, there may be a selective role for bladder drainage in 'high risk' pancreases. Also, without a clear-cut metabolic benefit to PVD over SVD, it remains the surgeon's choice as to which method to use.

Muscle and eye movement artifact removal prior to EEG source localization.

PubMed

Hallez, Hans; Vergult, Anneleen; Phlypo, Ronald; Van Hese, Peter; De Clercq, Wim; D'Asseler, Yves; Van de Walle, Rik; Vanrumste, Bart; Van Paesschen, Wim; Van Huffel, Sabine; Lemahieu, Ignace

2006-01-01

Muscle and eye movement artifacts are very prominent in the ictal EEG of patients suffering from epilepsy, thus making the dipole localization of ictal activity very unreliable. Recently, two techniques (BSS-CCA and pSVD) were developed to remove those artifacts. The purpose of this study is to assess whether the removal of muscle and eye movement artifacts improves the EEG dipole source localization. We used a total of 8 EEG fragments, each from another patient, first unfiltered, then filtered by the BSS-CCA and pSVD. In both the filtered and unfiltered EEG fragments we estimated multiple dipoles using RAP-MUSIC. The resulting dipoles were subjected to a K-means clustering algorithm, to extract the most prominent cluster. We found that the removal of muscle and eye artifact results to tighter and more clear dipole clusters. Furthermore, we found that localization of the filtered EEG corresponded with the localization derived from the ictal SPECT in 7 of the 8 patients. Therefore, we can conclude that the BSS-CCA and pSVD improve localization of ictal activity, thus making the localization more reliable for the presurgical evaluation of the patient.

Nonlinear QR code based optical image encryption using spiral phase transform, equal modulus decomposition and singular value decomposition

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Bhaduri, Basanta; Nishchal, Naveen K.

2018-01-01

In this study, we propose a quick response (QR) code based nonlinear optical image encryption technique using spiral phase transform (SPT), equal modulus decomposition (EMD) and singular value decomposition (SVD). First, the primary image is converted into a QR code and then multiplied with a spiral phase mask (SPM). Next, the product is spiral phase transformed with particular spiral phase function, and further, the EMD is performed on the output of SPT, which results into two complex images, Z 1 and Z 2. Among these, Z 1 is further Fresnel propagated with distance d, and Z 2 is reserved as a decryption key. Afterwards, SVD is performed on Fresnel propagated output to get three decomposed matrices i.e. one diagonal matrix and two unitary matrices. The two unitary matrices are modulated with two different SPMs and then, the inverse SVD is performed using the diagonal matrix and modulated unitary matrices to get the final encrypted image. Numerical simulation results confirm the validity and effectiveness of the proposed technique. The proposed technique is robust against noise attack, specific attack, and brutal force attack. Simulation results are presented in support of the proposed idea.

A novel image watermarking method based on singular value decomposition and digital holography

NASA Astrophysics Data System (ADS)

Cai, Zhishan

2016-10-01

According to the information optics theory, a novel watermarking method based on Fourier-transformed digital holography and singular value decomposition (SVD) is proposed in this paper. First of all, a watermark image is converted to a digital hologram using the Fourier transform. After that, the original image is divided into many non-overlapping blocks. All the blocks and the hologram are decomposed using SVD. The singular value components of the hologram are then embedded into the singular value components of each block using an addition principle. Finally, SVD inverse transformation is carried out on the blocks and hologram to generate the watermarked image. The watermark information embedded in each block is extracted at first when the watermark is extracted. After that, an averaging operation is carried out on the extracted information to generate the final watermark information. Finally, the algorithm is simulated. Furthermore, to test the encrypted image's resistance performance against attacks, various attack tests are carried out. The results show that the proposed algorithm has very good robustness against noise interference, image cut, compression, brightness stretching, etc. In particular, when the image is rotated by a large angle, the watermark information can still be extracted correctly.

Delayed-onset dementia after stroke or transient ischemic attack.

PubMed

Mok, Vincent C T; Lam, Bonnie Y K; Wang, Zhaolu; Liu, Wenyan; Au, Lisa; Leung, Eric Y L; Chen, Sirong; Yang, Jie; Chu, Winnie C W; Lau, Alexander Y L; Chan, Anne Y Y; Shi, Lin; Fan, Florence; Ma, Sze H; Ip, Vincent; Soo, Yannie O Y; Leung, Thomas W H; Kwok, Timothy C Y; Ho, Chi L; Wong, Lawrence K S; Wong, Adrian

2016-11-01

Patients surviving stroke without immediate dementia are at high risk of delayed-onset dementia. Mechanisms underlying delayed-onset dementia are complex and may involve vascular and/or neurodegenerative diseases. Dementia-free patients with stroke and/or transient ischemic attack (TIA; n = 919) were studied for 3 years prospectively, excluding those who developed dementia 3 to 6 months after stroke and/or TIA. Forty subjects (4.4%) developed dementia during the study period. Imaging markers of severe small vessel disease (SVD), namely presence of ≥3 lacunes and confluent white matter changes; history of hypertension and diabetes mellitus independently predicted delayed-onset dementia after adjustment for age, gender, and education. Only 6 of 31 (19.4%) subjects with delayed cognitive decline harbored Alzheimer's disease-like Pittsburg compound B (PiB) retention. Most PiB cases (16/25, 64%) had evidence of severe SVD. Severe SVD contributes importantly to delayed-onset dementia after stroke and/or TIA. Future clinical trials aiming to prevent delayed-onset dementia after stroke and/or TIA should target this high-risk group. Copyright © 2016 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Dynamic CT myocardial perfusion imaging: detection of ischemia in a porcine model with FFR verification

NASA Astrophysics Data System (ADS)

Fahmi, Rachid; Eck, Brendan L.; Vembar, Mani; Bezerra, Hiram G.; Wilson, David L.

2014-03-01

Dynamic cardiac CT perfusion (CTP) is a high resolution, non-invasive technique for assessing myocardial blood ow (MBF), which in concert with coronary CT angiography enable CT to provide a unique, comprehensive, fast analysis of both coronary anatomy and functional ow. We assessed perfusion in a porcine model with and without coronary occlusion. To induce occlusion, each animal underwent left anterior descending (LAD) stent implantation and angioplasty balloon insertion. Normal ow condition was obtained with balloon completely de ated. Partial occlusion was induced by balloon in ation against the stent with FFR used to assess the extent of occlusion. Prospective ECG-triggered partial scan images were acquired at end systole (45% R-R) using a multi-detector CT (MDCT) scanner. Images were reconstructed using FBP and a hybrid iterative reconstruction (iDose4, Philips Healthcare). Processing included: beam hardening (BH) correction, registration of image volumes using 3D cubic B-spline normalized mutual-information, and spatio-temporal bilateral ltering to reduce partial scan artifacts and noise variation. Absolute blood ow was calculated with a deconvolutionbased approach using singular value decomposition (SVD). Arterial input function was estimated from the left ventricle (LV) cavity. Regions of interest (ROIs) were identi ed in healthy and ischemic myocardium and compared in normal and occluded conditions. Under-perfusion was detected in the correct LAD territory and ow reduction agreed well with FFR measurements. Flow was reduced, on average, in LAD territories by 54%.

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

A Partial Least-Squares Analysis of Health-Related Quality-of-Life Outcomes After Aneurysmal Subarachnoid Hemorrhage.

PubMed

Young, Julia M; Morgan, Benjamin R; Mišić, Bratislav; Schweizer, Tom A; Ibrahim, George M; Macdonald, R Loch

2015-12-01

Individuals who have aneurysmal subarachnoid hemorrhages (SAHs) experience decreased health-related qualities of life (HRQoLs) that persist after the primary insult. To identify clinical variables that concurrently associate with HRQoL outcomes by using a partial least-squares approach, which has the distinct advantage of explaining multidimensional variance where predictor variables may be highly collinear. Data collected from the CONSCIOUS-1 trial was used to extract 29 clinical variables including SAH presentation, hospital procedures, and demographic information in addition to 5 HRQoL outcome variables for 256 individuals. A partial least-squares analysis was performed by calculating a heterogeneous correlation matrix and applying singular value decomposition to determine components that best represent the correlations between the 2 sets of variables. Bootstrapping was used to estimate statistical significance. The first 2 components accounting for 81.6% and 7.8% of the total variance revealed significant associations between clinical predictors and HRQoL outcomes. The first component identified associations between disability in self-care with longer durations of critical care stay, invasive intracranial monitoring, ventricular drain time, poorer clinical grade on presentation, greater amounts of cerebral spinal fluid drainage, and a history of hypertension. The second component identified associations between disability due to pain and discomfort as well as anxiety and depression with greater body mass index, abnormal heart rate, longer durations of deep sedation and critical care, and higher World Federation of Neurosurgical Societies and Hijdra scores. By applying a data-driven, multivariate approach, we identified robust associations between SAH clinical presentations and HRQoL outcomes. EQ-VAS, EuroQoL visual analog scaleHRQoL, health-related quality of lifeICU, intensive care unitIVH, intraventricular hemorrhagePLS, partial least squaresSAH, subarachnoid hemorrhageSVD, singular value decompositionWFNS, World Federation of Neurosurgical Societies.

Stentless vs. stented bioprosthesis for aortic valve replacement: A case matched comparison of long-term follow-up and subgroup analysis of patients with native valve endocarditis.

PubMed

Schaefer, Andreas; Dickow, Jannis; Schoen, Gerhard; Westhofen, Sumi; Kloss, Lisa; Al-Saydali, Tarik; Reichenspurner, Hermann; Philipp, Sebastian A; Detter, Christian

2018-01-01

Current retrospective evidence suggests similar clinical and superior hemodynamic outcomes of the Sorin Freedom Solo stentless aortic valve (SFS) (LivaNova PLC, London, UK) compared to the Carpentier Edwards Perimount stented aortic valve (CEP) (Edwards Lifesciences Inc., Irvine, California, USA). To date, no reports exist describing case-matched long-term outcomes and analysis for treatment of native valve endocarditis (NVE). From 2004 through 2014, 77 consecutive patients (study group, 59.7% male, 68.9 ± 12.5 years, logEuroSCORE II 7.6 ± 12.3%) received surgical aortic valve replacement (SAVR) with the SFS. A control group of patients after SAVR with the CEP was retrieved from our database and matched to the study group regarding 15 parameters including preoperative endocarditis. Acute perioperative outcomes and follow-up data (mean follow-up time 48.7±29.8 months, 95% complete) were retrospectively analyzed. No differences in early mortality occurred during 30-day follow up (3/77; 3.9% vs. 4/77; 5.2%; p = 0.699). Echocardiographic findings revealed lower postprocedural transvalvular pressure gradients (max. 17.0 ± 8.2 vs. 24.5 ± 9.2 mmHg, p< 0.001/ mean pressure of 8.4 ± 4.1 vs. 13.1 ± 5.9 mmHg, p< 0.001) in the SFS group. Structural valve degeneration (SVD) (5.2% vs. 0%; p = 0.04) and valve explantation due to SVD or prosthetic valve endocarditis (PVE) (9.1% vs. 1.3%; p = 0.04) was more frequent in the SFS group. All-cause mortality during follow-up was 20.8% vs. 14.3% (p = 0.397). When patients were divided into subgroups of NVE and respective utilized bioprosthesis, the SFS presented impaired outcomes regarding mortality in NVE cases (p = 0.031). The hemodynamic superiority of the SFS was confirmed in this comparison. However, clinical outcomes in terms of SVD and PVE rates, as well as survival after NVE, were inferior in this study. Therefore, we are reluctant to recommend utilization of the SFS for treatment of NVE.

The Freedom Solo pericardial stentless valve: Single-center experience, outcomes, and long-term durability.

PubMed

Stanger, Olaf; Bleuel, Irina; Gisler, Fabian; Göber, Volkhard; Reineke, Sylvia; Gahl, Brigitta; Aymard, Thierry; Englberger, Lars; Carrel, Thierry; Tevaearai, Hendrik

2015-07-01

To report our institutional experience and long-term results with the Freedom Solo bovine pericardial stentless bioprosthesis (Sorin Group, Saluggia, Italy). Between January 2005 and November 2009, 149 patients (mean age, 73.6 ± 8.7 years; 68 [45.6%] female) underwent isolated (n = 75) or combined (n = 74) aortic valve replacement (AVR) using the Solo in our institution. Follow-up was 100% complete with an average follow-up time of 5.9 ± 2.6 years (maximum, 9.6 years) and a total of 885.3 patient years. Operative (30-day) mortality was 2.7% (1.3% for isolated AVR [n = 1] and 4.0% for combined procedures [n = 3]). All causes of death were not valve-related. Preoperative peak (mean) gradients of 74.2 ± 23.0 mm Hg (48.6 ± 16.3 mm Hg) decreased to 15.6 ± 5.4 mm Hg (8.8 ± 3.0 mm Hg) after AVR, and remained low for up to 9 years. The postoperative effective orifice area was 1.6 ± 0.57 cm(2), 1.90 ± 0.45 cm(2), 2.12 ± 0.48 cm(2), and 2.20 ± 0.66 cm(2) for the valve sizes 21, 23, 25, and 27, respectively, with absence of severe prosthesis-patient mismatch and 0.7% (n = 1) experienced moderate prosthesis-patient mismatch. During follow-up, 26 patients experienced structural valve deterioration (SVD) and 14 patients underwent explantation. Kaplan-Meier estimates for freedom from death, explantation, and SVD at 9 years averaged 0.57 (range, 0.47-0.66), 0.82 (range, 0.69-0.90), and 0.70 (range, 0.57-0.79), respectively. The Freedom Solo stentless aortic valve is safe to implant and shows excellent early and midterm hemodynamic performance. However, SVD was observed in a substantial number of patients after only 5-6 years and the need for explantation increased markedly, suggesting low durability. Copyright © 2015 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Characterizing the 21-cm absorption trough with pattern recognition and a numerical sampler

NASA Astrophysics Data System (ADS)

Tauscher, Keith A.; Rapetti, David; Burns, Jack O.; Monsalve, Raul A.; Bowman, Judd D.

2018-06-01

The highly redshifted sky-averaged 21-cm spectrum from neutral hydrogen is a key probe to a period of the Universe never before studied. Recent experimental advances have led to increasingly tightened constraints and the Experiment to Detect the Global Eor Signal (EDGES) has presented evidence for a detection of this global signal. In order to glean scientifically valuable information from these new measurements in a consistent manner, sophisticated fitting procedures must be applied. Here, I present a pipeline known as pylinex which takes advantage of Singular Value Decomposition (SVD), a pattern recognition tool, to leverage structure in the data induced by the design of an experiment to fit for signals in the experiment's data in the presence of large systematics (such as the beam-weighted foregrounds), especially those without parametric forms. This method requires training sets for each component of the data. Once the desired signal is extracted in SVD eigenmode coefficient space, the posterior distribution must be consistently transformed into a physical parameter space. This is done with the combination of a numerical least squares fitter and a Markov Chain Monte Carlo (MCMC) distribution sampler. After describing the pipeline's procedures and techniques, I present preliminary results of applying it to the EDGES low-band data used for their detection. The results include estimates of the signal in frequency space with errors and relevant parameter distributions.

Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis

PubMed Central

Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

2016-01-01

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques. PMID:27589760

Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis.

PubMed

Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

2016-08-31

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

Portuguese version of Wechsler Memory Scale-3rd edition's utility with demented elderly adults.

PubMed

Gonçalves, Cátia; Pinho, Maria S; Cruz, Vítor; Gens, Helena; Oliveira, Fátima; Pais, Joana; Rente, José; Santana, Isabel; Santos, José M

2017-01-01

The purpose of this study is to analyze the utility of the Portuguese version of the Wechsler Memory Scale-3rd edition (WMS-III) with demented elderly people, namely its capacity to detect and discriminate between subcortical vascular dementia (SVD) and Alzheimer's disease (AD). We assessed early demented patients (SVD = 16; AD = 36) aged 65 or older who were compared to a control group (n = 40). Both clinical groups were adequately matched in terms of disease severity, overall cognitive functioning, depressive symptomatology, and pre-morbid intelligence. Between-group's differences were evaluated using the Quade's rank analysis of covariance. We also computed indexes and subtests optimal cut-off scores, and the corresponding sensitivity, specificity, and positive and negative predictive values, which were able to successfully discriminate between patients and healthy subjects. The SVD patients had a better overall memory performance than AD patients on the majority of the indexes and the delayed condition subtests of the WMS-III. The AD patients only showed a better performance on digit span subtest. Several measures discriminated patients from healthy subjects. This study suggests some recommendations for the diagnostic accuracy of the Portuguese version of WMS-III in dementia and about differential diagnosis between SVD and AD.

Precision PEP-II optics measurement with an SVD-enhanced Least-Square fitting

NASA Astrophysics Data System (ADS)

Yan, Y. T.; Cai, Y.

2006-03-01

A singular value decomposition (SVD)-enhanced Least-Square fitting technique is discussed. By automatic identifying, ordering, and selecting dominant SVD modes of the derivative matrix that responds to the variations of the variables, the converging process of the Least-Square fitting is significantly enhanced. Thus the fitting speed can be fast enough for a fairly large system. This technique has been successfully applied to precision PEP-II optics measurement in which we determine all quadrupole strengths (both normal and skew components) and sextupole feed-downs as well as all BPM gains and BPM cross-plane couplings through Least-Square fitting of the phase advances and the Local Green's functions as well as the coupling ellipses among BPMs. The local Green's functions are specified by 4 local transfer matrix components R12, R34, R32, R14. These measurable quantities (the Green's functions, the phase advances and the coupling ellipse tilt angles and axis ratios) are obtained by analyzing turn-by-turn Beam Position Monitor (BPM) data with a high-resolution model-independent analysis (MIA). Once all of the quadrupoles and sextupole feed-downs are determined, we obtain a computer virtual accelerator which matches the real accelerator in linear optics. Thus, beta functions, linear coupling parameters, and interaction point (IP) optics characteristics can be measured and displayed.

Forcing mechanism of the seasonally asymmetric quasi-biennial oscillation secondary circulation in ERA-40 and MAECHAM5

NASA Astrophysics Data System (ADS)

Peña-Ortiz, C.; Ribera, P.; García-Herrera, R.; Giorgetta, M. A.; García, R. R.

2008-08-01

The seasonality of the quasi-biennial oscillation (QBO) and its secondary circulation is analyzed in the European Reanalysis (ERA-40) and Middle Atmosphere European Centre Hamburg Model (MAECHAM5) general circulation model data sets through the multitaper method-singular value decomposition (MTM-SVD). In agreement with previous studies, the results reveal a strong seasonal dependence of the QBO secondary circulation. This is characterized by a two-cell structure symmetric about the equator during autumn and spring. However, anomalies strongly weaken in the summer hemisphere and strengthen in the winter hemisphere, leading to an asymmetric QBO secondary circulation characterized by a single-cell structure displaced into the winter hemisphere during the solstices. In ERA-40, this asymmetry is more pronounced during the northern than during the southern winter. These results provide the first observation of the QBO secondary circulation asymmetries in the ERA-40 reanalysis data set across the full stratosphere and the lower mesosphere, up to 0.1 hPa. The MTM-SVD reconstruction of the seasonal QBO signals in the residual circulation and the QBO signals in Eliassen Palm (EP) flux divergences suggest a particular mechanism for the seasonal asymmetries of the QBO secondary circulation and its extension across the midlatitudes. The analysis shows that the QBO modulates the EP flux in the winter hemispheric surf zone poleward of the QBO jets. The zonal wind forcing by EP flux divergence is transformed by the Coriolis effect into a meridional wind signal. The seasonality in the stratospheric EP flux and the hemispheric differences in planetary wave forcing cause the observed seasonality in the QBO secondary circulation and its hemispheric differences.

Impact of Strategically Located White Matter Hyperintensities on Cognition in Memory Clinic Patients with Small Vessel Disease

PubMed Central

Hilal, Saima; Kuijf, Hugo J.; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Postma, Albert; Biessels, Geert Jan; Chen, Christopher P. L. H.

2016-01-01

Background and Purpose Studies on the impact of small vessel disease (SVD) on cognition generally focus on white matter hyperintensity (WMH) volume. The extent to which WMH location relates to cognitive performance has received less attention, but is likely to be functionally important. We examined the relation between WMH location and cognition in a memory clinic cohort of patients with sporadic SVD. Methods A total of 167 patients with SVD were recruited from memory clinics. Assumption-free region of interest-based analyses based on major white matter tracts and voxel-wise analyses were used to determine the association between WMH location and executive functioning, visuomotor speed and memory. Results Region of interest-based analyses showed that WMHs located particularly within the anterior thalamic radiation and forceps minor were inversely associated with both executive functioning and visuomotor speed, independent of total WMH volume. Memory was significantly associated with WMH volume in the forceps minor, independent of total WMH volume. An independent assumption-free voxel-wise analysis identified strategic voxels in these same tracts. Region of interest-based analyses showed that WMH volume within the anterior thalamic radiation explained 6.8% of variance in executive functioning, compared to 3.9% for total WMH volume; WMH volume within the forceps minor explained 4.6% of variance in visuomotor speed and 4.2% of variance in memory, compared to 1.8% and 1.3% respectively for total WMH volume. Conclusions Our findings identify the anterior thalamic radiation and forceps minor as strategic white matter tracts in which WMHs are most strongly associated with cognitive impairment in memory clinic patients with SVD. WMH volumes in individual tracts explained more variance in cognition than total WMH burden, emphasizing the importance of lesion location when addressing the functional consequences of WMHs. PMID:27824925

The rehabilitation of attention in patients with mild cognitive impairment and brain subcortical vascular changes using the Attention Process Training-II. The RehAtt Study: rationale, design and methodology.

PubMed

Salvadori, Emilia; Poggesi, Anna; Valenti, Raffaella; Della Rocca, Eleonora; Diciotti, Stefano; Mascalchi, Mario; Inzitari, Domenico; Pantoni, Leonardo

2016-10-01

Cerebral small vessel disease (SVD) may cause attentional and executive cognitive deficits. No drug is currently available to improve cognitive performance or to prevent dementia in SVD patients, and cognitive rehabilitation could be a promising approach. We aimed to investigate: (1) the effectiveness of the Attention Process Training-II program in the rehabilitation of patients with mild cognitive impairment (MCI) and SVD; (2) the impact of the induced cognitive improvement on functionality and quality of life; (3) the effect of training on brain activity at rest and the possibility of a training-induced plasticity effect. The RehAtt study is designed as a 3-year prospective, single-blinded, randomized clinical trial. Inclusion criteria were: (1) MCI defined according to Winblad et al. criteria; (2) evidence of impairment across attention neuropsychological tests; (3) evidence on MRI of moderate/severe white matter hyperintensities. All enrolled patients are evaluated at baseline, and after 6 and 12 months, according to an extensive clinical, functional, MRI and neuropsychological protocol. The baseline RehAtt cohort includes 44 patients (66 % males, mean ± SD age and years of education 75.3 ± 6.8 and 8.3 ± 4.3, respectively). After baseline assessment, patients have been randomly assigned to 'attention training' or 'standard care'. Treatments and follow-up visits at 6 months are completed, while follow-up visits at 12 months are ongoing. This study is the first attempt to reduce attention deficits in patients affected by MCI with SVD. The results of this pilot experience will represent an essential background for designing larger multicenter, prospective, double-blinded, randomized and controlled clinical trials. NCT02033850 (ClinicalTrials.gov Identifier).

Sex differences in associations between blood lipids and cerebral small vessel disease.

PubMed

Yin, Z-G; Wang, Q-S; Yu, K; Wang, W-W; Lin, H; Yang, Z-H

2018-01-01

Dyslipidemia predicts higher risk of coronary events and stroke and might be associated with cerebral small vessel disease (SVD). Previous studies linking blood lipids and SVD have yielded inconsistent results, which may be attributable to sex differences in lipids metabolism. The aim of this study was to investigate the relationships between blood lipids and SVD in neurologically healthy men and women. Consecutive 817 people aged 50 years or more were enrolled and underwent magnetic resonance imaging scans to evaluate the periventricular white matter lesions (PVWMLs), deep white matter lesions (DWMLs) and silent brain infarction (SBI). Fasting total cholesterol, triglyceride, high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol, apolipoprotein A-1 (apoA-1) and apolipoprotein B were assessed. Multivariable logistic regression analyses were performed to determine the associations of blood lipids with PVWMLs, DWMLs and SBI. HDL-C (for PVWMLs: OR 0.36, 95% CI 0.19-0.71; for DWMLs: OR 0.35, 95% CI 0.20-0.63) and apoA-1 (for PVWMLs: OR 0.27, 95% CI 0.11-0.66; for DWMLs: OR 0.22, 95% CI 0.10-0.48) were inversely associated with the severity of PVWMLs and DWMLs in women but not in men after adjustment for age, hypertension, diabetes, current smoking, daily drinking, body mass index and uric acid. Additionally, no blood lipids were significantly associated with SBI. Our findings demonstrate that sex differences may exist in the associations between lipids and SVD. HDL-C and apoA-1 levels were inversely associated with the severity of PVWMLs and DWMLs in women. Copyright © 2017 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Baroclinic stabilization effect of the Atlantic-Arctic water exchange simulated by the eddy-permitting ocean model and global atmosphere-ocean model

NASA Astrophysics Data System (ADS)

Moshonkin, Sergey; Bagno, Alexey; Gritsun, Andrey; Gusev, Anatoly

2017-04-01

Numerical experiments were performed with the global atmosphere-ocean model INMCM5 (for version of the international project CMIP6, resolution for atmosphere is 2°x1.5°, 21 level) and with the three-dimensional, free surface, sigma coordinate eddy-permitting ocean circulation model for Atlantic (from 30°S) - Arctic and Bering sea domain (0.25 degrees resolution, Institute of Numerical Mathematics Ocean Model or INMOM). Spatial resolution of the INMCM5 oceanic component is 0.5°x0.25°. Both models have 40 s-levels in ocean. Previously, the simulations were carried out for INMCM5 to generate climatic system stable state. Then model was run for 180 years. In the experiment with INMOM, CORE-II data for 1948-2009 were used. As the goal for comparing results of two these numerical models, we selected evolution of the density and velocity anomalies in the 0-300m active ocean layer near Fram Strait in the Greenland Sea, where oceanic cyclonic circulation influences Atlantic-Arctic water exchange. Anomalies were count without climatic seasonal cycle for time scales smaller than 30 years. We use Singular Value Decomposition analysis (SVD) for density-velocity anomalies with time lag from minus one to six months. Both models perform identical stable physical result. They reveal that changes of heat and salt transports by West Spitsbergen and East Greenland currents, caused by atmospheric forcing, produce the baroclinic modes of velocity anomalies in 0-300m layer, thereby stabilizing ocean response on the atmospheric forcing, which stimulates keeping water exchange between the North Atlantic and Arctic Ocean at the certain climatological level. The first SVD-mode of density-velocity anomalies is responsible for the cyclonic circulation variability. The second and third SVD-modes stabilize existing ocean circulation by the anticyclonic vorticity generation. The second and third SVD-modes give 35% of the input to the total dispersion of density anomalies and 16-18% of the input to the total dispersion of velocity anomalies for numerical results as in INMCM5 so in INMOM models. Input to the total dispersion of velocity anomalies for the first SVD-mode is equal to 50% for INMCM5 and only 19% for INMOM. The research was done in the INM RAS. The model INMOM was supported by Russian Foundation for Basic Research (grant №16-05-00534), and the model INMCM was supported by the Russian Scientific Foundation (grant №14-27-00126).

Lorentz force electrical impedance tomography using magnetic field measurements.

PubMed

Zengin, Reyhan; Gençer, Nevzat Güneri

2016-08-21

In this study, magnetic field measurement technique is investigated to image the electrical conductivity properties of biological tissues using Lorentz forces. This technique is based on electrical current induction using ultrasound together with an applied static magnetic field. The magnetic field intensity generated due to induced currents is measured using two coil configurations, namely, a rectangular loop coil and a novel xy coil pair. A time-varying voltage is picked-up and recorded while the acoustic wave propagates along its path. The forward problem of this imaging modality is defined as calculation of the pick-up voltages due to a given acoustic excitation and known body properties. Firstly, the feasibility of the proposed technique is investigated analytically. The basic field equations governing the behaviour of time-varying electromagnetic fields are presented. Secondly, the general formulation of the partial differential equations for the scalar and magnetic vector potentials are derived. To investigate the feasibility of this technique, numerical studies are conducted using a finite element method based software. To sense the pick-up voltages a novel coil configuration (xy coil pairs) is proposed. Two-dimensional numerical geometry with a 16-element linear phased array (LPA) ultrasonic transducer (1 MHz) and a conductive body (breast fat) with five tumorous tissues is modeled. The static magnetic field is assumed to be 4 Tesla. To understand the performance of the imaging system, the sensitivity matrix is analyzed. The sensitivity matrix is obtained for two different locations of LPA transducer with eleven steering angles from [Formula: see text] to [Formula: see text] at intervals of [Formula: see text]. The characteristics of the imaging system are shown with the singular value decomposition (SVD) of the sensitivity matrix. The images are reconstructed with the truncated SVD algorithm. The signal-to-noise ratio in measurements is assumed 80 dB. Simulation studies based on the sensitivity matrix analysis reveal that perturbations with [Formula: see text] mm size can be detected up to a 3.5 cm depth.

Lorentz force electrical impedance tomography using magnetic field measurements

NASA Astrophysics Data System (ADS)

Zengin, Reyhan; Güneri Gençer, Nevzat

2016-08-01

In this study, magnetic field measurement technique is investigated to image the electrical conductivity properties of biological tissues using Lorentz forces. This technique is based on electrical current induction using ultrasound together with an applied static magnetic field. The magnetic field intensity generated due to induced currents is measured using two coil configurations, namely, a rectangular loop coil and a novel xy coil pair. A time-varying voltage is picked-up and recorded while the acoustic wave propagates along its path. The forward problem of this imaging modality is defined as calculation of the pick-up voltages due to a given acoustic excitation and known body properties. Firstly, the feasibility of the proposed technique is investigated analytically. The basic field equations governing the behaviour of time-varying electromagnetic fields are presented. Secondly, the general formulation of the partial differential equations for the scalar and magnetic vector potentials are derived. To investigate the feasibility of this technique, numerical studies are conducted using a finite element method based software. To sense the pick-up voltages a novel coil configuration (xy coil pairs) is proposed. Two-dimensional numerical geometry with a 16-element linear phased array (LPA) ultrasonic transducer (1 MHz) and a conductive body (breast fat) with five tumorous tissues is modeled. The static magnetic field is assumed to be 4 Tesla. To understand the performance of the imaging system, the sensitivity matrix is analyzed. The sensitivity matrix is obtained for two different locations of LPA transducer with eleven steering angles from -{{25}\\circ} to {{25}\\circ} at intervals of {{5}\\circ} . The characteristics of the imaging system are shown with the singular value decomposition (SVD) of the sensitivity matrix. The images are reconstructed with the truncated SVD algorithm. The signal-to-noise ratio in measurements is assumed 80 dB. Simulation studies based on the sensitivity matrix analysis reveal that perturbations with 5~\\text{mm}× 5 mm size can be detected up to a 3.5 cm depth.

Parallel Reconstruction Using Null Operations (PRUNO)

PubMed Central

Zhang, Jian; Liu, Chunlei; Moseley, Michael E.

2011-01-01

A novel iterative k-space data-driven technique, namely Parallel Reconstruction Using Null Operations (PRUNO), is presented for parallel imaging reconstruction. In PRUNO, both data calibration and image reconstruction are formulated into linear algebra problems based on a generalized system model. An optimal data calibration strategy is demonstrated by using Singular Value Decomposition (SVD). And an iterative conjugate- gradient approach is proposed to efficiently solve missing k-space samples during reconstruction. With its generalized formulation and precise mathematical model, PRUNO reconstruction yields good accuracy, flexibility, stability. Both computer simulation and in vivo studies have shown that PRUNO produces much better reconstruction quality than autocalibrating partially parallel acquisition (GRAPPA), especially under high accelerating rates. With the aid of PRUO reconstruction, ultra high accelerating parallel imaging can be performed with decent image quality. For example, we have done successful PRUNO reconstruction at a reduction factor of 6 (effective factor of 4.44) with 8 coils and only a few autocalibration signal (ACS) lines. PMID:21604290

ApoE and Sex Bias in Cerebrovascular Aging of Men and Mice

PubMed Central

Finch, Caleb E.; Shams, Sara

2016-01-01

Alzheimer disease (AD) research has mainly focused on neurodegenerative processes associated with the classic neuropathologic markers of senile plaques and neurofibrillary tangles. Additionally, cerebrovascular contributions to dementia are increasingly recognized, particularly from cerebral small vessel disease (SVD). Remarkably, in AD brains, the ApoE ε4 allele shows male excess for cerebral microbleeds (CMB), a marker of SVD, which is opposite to the female excess of plaques and tangles. Mouse transgenic models add further complexities to sex-ApoE ε4 allele interactions, with female excess of CMBs and brain amyloid. We conclude that brain aging and AD pathogenesis cannot be understood in humans without addressing major gaps in the extent of sex differences in cerebrovascular pathology. PMID:27546867

A robust watermarking scheme using lifting wavelet transform and singular value decomposition

NASA Astrophysics Data System (ADS)

Bhardwaj, Anuj; Verma, Deval; Verma, Vivek Singh

2017-01-01

The present paper proposes a robust image watermarking scheme using lifting wavelet transform (LWT) and singular value decomposition (SVD). Second level LWT is applied on host/cover image to decompose into different subbands. SVD is used to obtain singular values of watermark image and then these singular values are updated with the singular values of LH2 subband. The algorithm is tested on a number of benchmark images and it is found that the present algorithm is robust against different geometric and image processing operations. A comparison of the proposed scheme is performed with other existing schemes and observed that the present scheme is better not only in terms of robustness but also in terms of imperceptibility.

Obstructive Sleep Apnea is Linked to Depression and Cognitive Impairment: Evidence and Potential Mechanisms

PubMed Central

Kerner, Nancy A.; Roose, Steven P.

2017-01-01

Obstructive sleep apnea (OSA) is highly prevalent but very frequently undiagnosed. OSA is an independent risk factor for depression and cognitive impairment/dementia. Herein the authors review studies in the literature pertinent to the effects of OSA on the cerebral microvascular and neurovascular systems and present a model to describe the key pathophysiologic mechanisms that may underlie the associations, including hypoperfusion, endothelial dysfunction, and neuroinflammation. Intermittent hypoxia plays a critical role in initiating and amplifying these pathologic processes. Hypoperfusion and impaired cerebral vasomotor reactivity lead to the development or progression of cerebral small vessel disease (C-SVD). Hypoxemia exacerbates these processes, resulting in white matter lesions, white matter integrity abnormalities, and gray matter loss. Blood–brain barrier (BBB) hyperpermeability and neuroinflammation lead to altered synaptic plasticity, neuronal damage, and worsening C-SVD. Thus, OSA may initiate or amplify the pathologic processes of C-SVD and BBB dysfunction, resulting in the development or exacerbation of depressive symptoms and cognitive deficits. Given the evidence that adequate treatment of OSA with continuous positive airway pressure improves depression and neurocognitive functions, it is important to identify OSA when assessing patients with depression or cognitive impairment. Whether treatment of OSA changes the deteriorating trajectory of elderly patients with already-diagnosed vascular depression and cognitive impairment/dementia remains to be determined in randomized controlled trials. PMID:27139243

Passive forensics for copy-move image forgery using a method based on DCT and SVD.

PubMed

Zhao, Jie; Guo, Jichang

2013-12-10

As powerful image editing tools are widely used, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the tampering techniques which are frequently used. Most existing techniques to expose this forgery need to improve the robustness for common post-processing operations and fail to precisely locate the tampering region especially when there are large similar or flat regions in the image. In this paper, a robust method based on DCT and SVD is proposed to detect this specific artifact. Firstly, the suspicious image is divided into fixed-size overlapping blocks and 2D-DCT is applied to each block, then the DCT coefficients are quantized by a quantization matrix to obtain a more robust representation of each block. Secondly, each quantized block is divided non-overlapping sub-blocks and SVD is applied to each sub-block, then features are extracted to reduce the dimension of each block using its largest singular value. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by predefined shift frequency threshold. Experiment results demonstrate that our proposed method can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, AWGN, JPEG compression and their mixed operations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Risk and Determinants of Dementia in Patients with Mild Cognitive Impairment and Brain Subcortical Vascular Changes: A Study of Clinical, Neuroimaging, and Biological Markers—The VMCI-Tuscany Study: Rationale, Design, and Methodology

PubMed Central

Poggesi, Anna; Salvadori, Emilia; Pantoni, Leonardo; Pracucci, Giovanni; Cesari, Francesca; Chiti, Alberto; Ciolli, Laura; Cosottini, Mirco; Del Bene, Alessandra; De Stefano, Nicola; Diciotti, Stefano; Dotti, Maria Teresa; Ginestroni, Andrea; Giusti, Betti; Gori, Anna Maria; Nannucci, Serena; Orlandi, Giovanni; Pescini, Francesca; Valenti, Raffaella; Abbate, Rosanna; Federico, Antonio; Mascalchi, Mario; Murri, Luigi; Inzitari, Domenico

2012-01-01

Dementia is one of the most disabling conditions. Alzheimer's disease and vascular dementia (VaD) are the most frequent causes. Subcortical VaD is consequent to deep-brain small vessel disease (SVD) and is the most frequent form of VaD. Its pathological hallmarks are ischemic white matter changes and lacunar infarcts. Degenerative and vascular changes often coexist, but mechanisms of interaction are incompletely understood. The term mild cognitive impairment defines a transitional state between normal ageing and dementia. Pre-dementia stages of VaD are also acknowledged (vascular mild cognitive impairment, VMCI). Progression relates mostly to the subcortical VaD type, but determinants of such transition are unknown. Variability of phenotypic expression is not fully explained by severity grade of lesions, as depicted by conventional MRI that is not sensitive to microstructural and metabolic alterations. Advanced neuroimaging techniques seem able to achieve this. Beside hypoperfusion, blood-brain-barrier dysfunction has been also demonstrated in subcortical VaD. The aim of the Vascular Mild Cognitive Impairment Tuscany Study is to expand knowledge about determinants of transition from mild cognitive impairment to dementia in patients with cerebral SVD. This paper summarizes the main aims and methodological aspects of this multicenter, ongoing, observational study enrolling patients affected by VMCI with SVD. PMID:22550606

Neuroimaging Characteristics of Small-Vessel Disease in Older Adults with Normal Cognition, Mild Cognitive Impairment, and Alzheimer Disease.

PubMed

Mimenza-Alvarado, Alberto; Aguilar-Navarro, Sara G; Yeverino-Castro, Sara; Mendoza-Franco, César; Ávila-Funes, José Alberto; Román, Gustavo C

2018-01-01

Cerebral small-vessel disease (SVD) represents the most frequent type of vascular brain lesions, often coexisting with Alzheimer disease (AD). By quantifying white matter hyperintensities (WMH) and hippocampal and parietal atrophy, we aimed to describe the prevalence and severity of SVD among older adults with normal cognition (NC), mild cognitive impairment (MCI), and probable AD and to describe associated risk factors. This study included 105 older adults evaluated with magnetic resonance imaging and clinical and neuropsychological tests. We used the Fazekas scale (FS) for quantification of WMH, the Scheltens scale (SS) for hippocampal atrophy, and the Koedam scale (KS) for parietal atrophy. Logistic regression models were performed to determine the association between FS, SS, and KS scores and the presence of NC, MCI, or probable AD. Compared to NC subjects, SVD was more prevalent in MCI and probable AD subjects. After adjusting for confounding factors, logistic regression showed a positive association between higher scores on the FS and probable AD (OR = 7.6, 95% CI 2.7-20, p < 0.001). With the use of the SS and KS (OR = 4.5, 95% CI 3.5-58, p = 0.003 and OR = 8.9, 95% CI 1-72, p = 0.04, respectively), the risk also remained significant for probable AD. These results suggest an association between severity of vascular brain lesions and neurodegeneration.

Over 20 years experience with aortic homograft in aortic valve replacement during acute infective endocarditis.

PubMed

Solari, Silvia; Mastrobuoni, Stefano; De Kerchove, Laurent; Navarra, Emiliano; Astarci, Parla; Noirhomme, Philippe; Poncelet, Alain; Jashari, Ramadan; Rubay, Jean; El Khoury, Gebrine

2016-12-01

Despite the controversy, the aortic homograft is supposedly the best option in acute infective endocarditis (AIE), due to its resistance to reinfection. However, the technical complexity and the risk of structural deterioration over time have limited its utilization. The aim of this study was to evaluate the long-term results of aortic homograft for the treatment of infective endocarditis in our institution with particular attention to predictors of survival and homograft reoperation. The cohort includes 112 patients who underwent aortic valve replacement with an aortic homograft for AIE between January 1990 and December 2014. Fifteen patients (13.4%) died during the first 30 days after the operation. Two patients were lost to follow-up after discharge from the hospital; therefore, 95 patients were available for long-term analysis. The median duration of follow-up was 7.8 years (IQR 4.7-17.6). Five patients (5.3%) suffered a recurrence of infective endocarditis (1 relapse and 4 new episodes). Sixteen patients (16.8%) were reoperated for structural valve degeneration (SVD; n = 14, 87.5%) or for infection recurrence (n = 2, 12.5%). Freedom from homograft reoperation for infective endocarditis or structural homograft degeneration at 10 and 15 years postoperatively was 86.3 ± 5.5 and 47.3 ± 11.0%, respectively. For patients requiring homograft reoperation, the median interval to reintervention was 11.6 years (IQR 8.3-14.5). Long-term survival was 63.6% (95% CI 52.4-72.8%) and 53.8% (95% CI 40.6-65.3%) at 10 and 15 years, respectively. The use of aortic homograft in acute aortic valve endocarditis is associated with a remarkably low risk of relapsing infection and very acceptable long-term survival. The risk of reoperation due to SVD is significant after one decade especially in young patients. The aortic homograft seems to be ideally suited for reconstruction of the aortic valve and cardiac structures damaged by the infective process especially in early surgery. © The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Video quality assesment using M-SVD

NASA Astrophysics Data System (ADS)

Tao, Peining; Eskicioglu, Ahmet M.

2007-01-01

Objective video quality measurement is a challenging problem in a variety of video processing application ranging from lossy compression to printing. An ideal video quality measure should be able to mimic the human observer. We present a new video quality measure, M-SVD, to evaluate distorted video sequences based on singular value decomposition. A computationally efficient approach is developed for full-reference (FR) video quality assessment. This measure is tested on the Video Quality Experts Group (VQEG) phase I FR-TV test data set. Our experiments show the graphical measure displays the amount of distortion as well as the distribution of error in all frames of the video sequence while the numerical measure has a good correlation with perceived video quality outperforms PSNR and other objective measures by a clear margin.

Apolipoprotein E and Sex Bias in Cerebrovascular Aging of Men and Mice.

PubMed

Finch, Caleb E; Shams, Sara

2016-09-01

Alzheimer disease (AD) research has mainly focused on neurodegenerative processes associated with the classic neuropathologic markers of senile plaques and neurofibrillary tangles. Additionally, cerebrovascular contributions to dementia are increasingly recognized, particularly from cerebral small vessel disease (SVD). Remarkably, in AD brains, the apolipoprotein E (ApoE) ɛ4 allele shows male excess for cerebral microbleeds (CMBs), a marker of SVD, which is opposite to the female excess of plaques and tangles. Mouse transgenic models add further complexities to sex-ApoE ɛ4 allele interactions, with female excess of both CMBs and brain amyloid. We conclude that brain aging and AD pathogenesis cannot be understood in humans without addressing major gaps in the extent of sex differences in cerebrovascular pathology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Contribution of deletion in angiotensin-converting enzyme but not A1166C angiotensin II type-1 receptor gene polymorphisms to clinical outcomes in atherothrombotic disease.

PubMed

Le Hello, Claire; Fradin, Sabine; Morello, Rémy; Coffin, Olivier; Maïza, Dominique; Hamon, Martial

2011-04-01

Angiotensin-converting enzyme insertion/deletion (rs4340) and angiotensin II type 1 receptor A1166C (rs5186) gene polymorphisms may be involved in coronary heart disease (CHD). This study was designed to evaluate potential relationships between these polymorphisms and the risk of long-term all-cause mortality and major adverse cardiovascular events (MACE) in patients requiring revascularization for atherothrombotic disease (ATD) lesions. This prospective observational study concerned patients referred for supra-aortic vessel disease (SVD), CHD, peripheral artery occlusive disease (PAOD) or visceral artery disease (VAD). Collected data included ATD referral site, ATD symptoms, personal and familial medical histories, ATD extent, vascular risk factors, biological values, medication use and rs4340 and rs5186 polymorphisms. The primary end point was all-cause mortality. The secondary end point, MACE, included cardiovascular death, clinical ischemic event related to SVD, CHD, PAOD or VAD. The cohort comprised 956 patients of whom 872 (91.2%) were genotyped and followed for 21.1 ± 9.9 months. Patients were referred for SVD (25.9%), CHD (42.3%), PAOD (35.2%) or VAD (1.6%). All-cause mortality and MACE rates were 7.6 and 27.2%, respectively. When comparing I/D + D/D vs. I/I genotypes, rs4340 polymorphism was associated with higher all-cause mortality rates according to uni- and multivariate analyses (p=0.008 and 0.011, respectively). Other differences were not significant (rs4340 polymorphism and MACE, rs5186 polymorphism and all-cause mortality and MACE). No interaction was found between the polymorphisms. Other independent predictors of all-cause mortality included PAOD history, SVD history, body mass index <25 kg/m(2), HbA(1c) ≥6.5%, absence of dyslipidemia and no use of aspirin. rs4340 polymorphism is associated with long-term all-cause mortality in advanced ATD patients requiring revascularization, whereas rs5186 polymorphism does not. Copyright © 2011 IMSS. Published by Elsevier Inc. All rights reserved.

Spatial-frequency variability of the eddy kinetic energy in the South Atlantic Ocean

NASA Astrophysics Data System (ADS)

Cecilio, C. M.; Gherardi, D. F.; Souza, R.; Correa-Ramirez, M.

2013-05-01

In the South Atlantic Ocean (SAO) part of the inter-oceanic flow is accomplished through the issuance of anticyclonic eddies by the Agulhas Retroflection. This region, known as Agulhas Leakage (AL), is responsible by the intermittent shedding of eddies in the SAO. The propagation of these eddies into the SAO induces wave processes that allows the interaction between modes of variability of different basins, ranging from high to low frequency. Modelling studies suggests that the Indian-Atlantic inter-ocean exchange is strongly related to the structure of the wind field, in particular with the position of the maximum Southern Hemisphere westerly winds. This study aims to investigate the variations of the large-scale and regional mesoscale eddy field over the SAO using a frequency domain technique, Multiple Taper Method with Singular Value Decomposition (MTM-SVD). The MTM-SVD approach is applied to examine the individual and joint spatiotemporal variability modes of eddy kinetic energy (EKE) and winds stress. The EKE is estimated from geostrophic velocity anomalies data distributed by Aviso and winds stress from winds dataset of Cross-Calibrated Multi-Platform (CCMP) project from PO.DAAC. The impact of the AL in the SAO, was assessed first for the entire region and subsequently applied in the regions of higher mesoscale activity, which are the Brazil-Malvinas Confluence (BMC), the AL, and the Brazilian Current (BC) region. The results of local fractional variance (LFV) of EKE obtained by the MTM-SVD method show a strong significant annual variability in SAO and BC region while in BMC and in AL this frequency is weaker. In the most energetic mesoscale activity regions (BMC and AL) the pattern of variability is distinct. In the BMC region the interannual variability is dominated while in the AL region the most part of variability is associated by high frequency. The joint LFV spectrum of wind and EKE show an out-of-phase relationship between the AL region and BMC region in the interannual frequencies (3 to 5 years). The dominant frequencies can be seen in 1,5 to 3 years period band and in the intrasazonal frequencies, 0,3 to 0,5 years. The results suggests that the EKE variability patterns are different in the SAO wich might be related to the influence of eddies from AL.

A hybrid linear/nonlinear training algorithm for feedforward neural networks.

PubMed

McLoone, S; Brown, M D; Irwin, G; Lightbody, A

1998-01-01

This paper presents a new hybrid optimization strategy for training feedforward neural networks. The algorithm combines gradient-based optimization of nonlinear weights with singular value decomposition (SVD) computation of linear weights in one integrated routine. It is described for the multilayer perceptron (MLP) and radial basis function (RBF) networks and then extended to the local model network (LMN), a new feedforward structure in which a global nonlinear model is constructed from a set of locally valid submodels. Simulation results are presented demonstrating the superiority of the new hybrid training scheme compared to second-order gradient methods. It is particularly effective for the LMN architecture where the linear to nonlinear parameter ratio is large.

Singular value decomposition approach to the yttrium occurrence in mineral maps of rare earth element ores using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Romppanen, Sari; Häkkänen, Heikki; Kaski, Saara

2017-08-01

Laser-induced breakdown spectroscopy (LIBS) has been used in analysis of rare earth element (REE) ores from the geological formation of Norra Kärr Alkaline Complex in southern Sweden. Yttrium has been detected in eudialyte (Na15 Ca6(Fe,Mn)3 Zr3Si(Si25O73)(O,OH,H2O)3 (OH,Cl)2) and catapleiite (Ca/Na2ZrSi3O9·2H2O). Singular value decomposition (SVD) has been employed in classification of the minerals in the rock samples and maps representing the mineralogy in the sampled area have been constructed. Based on the SVD classification the percentage of the yttrium-bearing ore minerals can be calculated even in fine-grained rock samples.

Rapid determination of particle velocity from space-time images using the Radon transform

PubMed Central

Drew, Patrick J.; Blinder, Pablo; Cauwenberghs, Gert; Shih, Andy Y.; Kleinfeld, David

2016-01-01

Laser-scanning methods are a means to observe streaming particles, such as the flow of red blood cells in a blood vessel. Typically, particle velocity is extracted from images formed from cyclically repeated line-scan data that is obtained along the center-line of the vessel; motion leads to streaks whose angle is a function of the velocity. Past methods made use of shearing or rotation of the images and a Singular Value Decomposition (SVD) to automatically estimate the average velocity in a temporal window of data. Here we present an alternative method that makes use of the Radon transform to calculate the velocity of streaming particles. We show that this method is over an order of magnitude faster than the SVD-based algorithm and is more robust to noise. PMID:19459038

Perivascular spaces, glymphatic dysfunction, and small vessel disease.

PubMed

Mestre, Humberto; Kostrikov, Serhii; Mehta, Rupal I; Nedergaard, Maiken

2017-09-01

Cerebral small vessel diseases (SVDs) range broadly in etiology but share remarkably overlapping pathology. Features of SVD including enlarged perivascular spaces (EPVS) and formation of abluminal protein deposits cannot be completely explained by the putative pathophysiology. The recently discovered glymphatic system provides a new perspective to potentially address these gaps. This work provides a comprehensive review of the known factors that regulate glymphatic function and the disease mechanisms underlying glymphatic impairment emphasizing the role that aquaporin-4 (AQP4)-lined perivascular spaces (PVSs), cerebrovascular pulsatility, and metabolite clearance play in normal CNS physiology. This review also discusses the implications that glymphatic impairment may have on SVD inception and progression with the aim of exploring novel therapeutic targets and highlighting the key questions that remain to be answered. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Does vacuum delivery carry a higher risk of shoulder dystocia? Review and meta-analysis of the literature.

PubMed

Dall'Asta, Andrea; Ghi, Tullio; Pedrazzi, Giuseppe; Frusca, Tiziana

2016-09-01

Vacuum extractor has been increasingly used over the last decades and is acknowledged as a risk factor for shoulder dystocia (SD). In this meta-analysis we assess the actual risk of SD following a vacuum delivery compared to spontaneous vaginal delivery (SVD) and forceps. Systematic literature search (English literature only) on MEDLINE, EMBASE, ScienceDirect, the Cochrane library and ClinicalTrials.gov conducted up to May 2015. Key search terms included: Operative/Vacuum/Forceps delivery [Mesh] and shoulder dystocia and subheadings. 2 stage-process study selection. We included only studies where data concerning the occurrence of SD following operative vaginal delivery were reported as adjusted odds ratio (AOR) and no significant difference in confounding factors for SD was recorded. Included trials clustered according to the delivery mode (1) vacuum vs. SVD, (2) forceps vs. vacuum. Methodological quality of each study evaluated with the Newcastle-Ottawa System (NOS). 87 potentially relevant papers. After applying inclusion and exclusion criteria only 7 were selected for the meta-analysis. Vacuum delivery appeared associated with a higher risk of SD than SVD in both fixed and random model (OR 2.87 and 2.98 respectively). No difference in the rate of SD was found between vacuum and forceps (p>0.05). Vacuum extractor carries an increased risk of SD compared with spontaneous vaginal delivery whereas the occurrence of SD does not seem to vary following vacuum or forceps. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Slavic Village: incorporating active living into community development through partnerships.

PubMed

Miller, Emily K; Scofield, Jennifer L

2009-12-01

The Slavic Village neighborhood in Cleveland, Ohio, is a diverse community of 30,524 residents that is struggling economically yet strong in tradition. The neighborhood is located just south of downtown and adjacent to the city's industrial valley. Slavic Village Development (SVD) works with local and state partners to improve the quality of life for its residents, including low-income and market-rate housing developments, economic development, community organizing, and greenspace planning. Using the Active Living by Design framework (ALbD), SVD developed strong partnerships to address preparation, promotions, programs, policy, and physical projects. Efforts were focused on Safe Routes to School, neighborhood activities, asset mapping, worksite wellness, and social marketing. The ALbD project changed both the physical environment of Slavic Village and its marketed image. The initiative built cross-disciplinary partnerships that leveraged individual strengths to implement strategies to make Slavic Village a vibrant, healthy, family-friendly neighborhood that promotes active living. There is a strong connection between health and community development. When partners from multiple disciplines work together on a common goal, it is easier to leverage resources and create change. Resource development will always be a challenge. Through the leadership of SVD and its strong ties in the community, the ALbD initiative has re-engaged residents and businesses in efforts to restore the vitality of the community. The partnership in Cleveland has successfully incorporated health into community development, a model of collaboration that can be replicated in other communities.

Understanding Singular Vectors

ERIC Educational Resources Information Center

James, David; Botteron, Cynthia

2013-01-01

matrix yields a surprisingly simple, heuristical approximation to its singular vectors. There are correspondingly good approximations to the singular values. Such rules of thumb provide an intuitive interpretation of the singular vectors that helps explain why the SVD is so…

SVD-aided pseudo principal-component analysis: A new method to speed up and improve determination of the optimum kinetic model from time-resolved data

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

Oang, Key Young; Yang, Cheolhee; Muniyappan, Srinivasan

Determination of the optimum kinetic model is an essential prerequisite for characterizing dynamics and mechanism of a reaction. Here, we propose a simple method, termed as singular value decomposition-aided pseudo principal-component analysis (SAPPA), to facilitate determination of the optimum kinetic model from time-resolved data by bypassing any need to examine candidate kinetic models. We demonstrate the wide applicability of SAPPA by examining three different sets of experimental time-resolved data and show that SAPPA can efficiently determine the optimum kinetic model. In addition, the results of SAPPA for both time-resolved X-ray solution scattering (TRXSS) and transient absorption (TA) data of themore » same protein reveal that global structural changes of protein, which is probed by TRXSS, may occur more slowly than local structural changes around the chromophore, which is probed by TA spectroscopy.« less

Association of Key Magnetic Resonance Imaging Markers of Cerebral Small Vessel Disease With Hematoma Volume and Expansion in Patients With Lobar and Deep Intracerebral Hemorrhage

PubMed Central

Boulouis, Gregoire; van Etten, Ellis S.; Charidimou, Andreas; Auriel, Eitan; Morotti, Andrea; Pasi, Marco; Haley, Kellen E.; Brouwers, H. Bart; Ayres, Alison M.; Vashkevich, Anastasia; Jessel, Michael J.; Schwab, Kristin M.; Viswanathan, Anand; Greenberg, Steven M.; Rosand, Jonathan; Goldstein, Joshua N.; Gurol, M. Edip

2017-01-01

IMPORTANCE Hematoma expansion is an important determinant of outcome in spontaneous intracerebral hemorrhage (ICH) due to small vessel disease (SVD), but the association between the severity of the underlying SVD and the extent of bleeding at the acute phase is unknown to date. OBJECTIVE To investigate the association between key magnetic resonance imaging (MRI) markers of SVD (as per the Standards for Reporting Vascular Changes on Neuroimaging [STRIVE] guidelines) and hematoma volume and expansion in patients with lobar or deep ICH. DESIGN, SETTING, AND PARTICIPANTS Analysis of data collected from 418 consecutive patients admitted with primary lobar or deep ICH to a single tertiary care medical center between January 1, 2000, and October 1, 2012. Data were analyzed on March 4, 2016. Participants were consecutive patients with computed tomographic images allowing ICH volume calculation and MRI allowing imaging markers of SVD assessment. MAIN OUTCOMES AND MEASURES The ICH volumes at baseline and within 48 hours after symptom onset were measured in 418 patients with spontaneous ICH without anticoagulant therapy, and hematoma expansion was calculated. Cerebral microbleeds, cortical superficial siderosis, and white matter hyperintensity volume were assessed on MRI. The associations between these SVD markers and ICH volume, as well as hematoma expansion, were investigated using multivariable models. RESULTS This study analyzed 254 patients with lobar ICH (mean [SD] age, 75 [11] years and 140 [55.1%] female) and 164 patients with deep ICH (mean [SD] age 67 [14] years and 71 [43.3%] female). The presence of cortical superficial siderosis was an independent variable associated with larger ICH volume in the lobar ICH group (odds ratio per quintile increase in final ICH volume, 1.49; 95% CI, 1.14–1.94; P = .004). In multivariable models, the absence of cerebral microbleeds was associated with larger ICH volume for both the lobar and deep ICH groups (odds ratios per quintile increase in final ICH volume, 1.41; 95% CI, 1.11–1.81; P = .006 and 1.43; 95% CI, 1.04–1.99; P = .03; respectively) and with hematoma expansion in the lobar ICH group (odds ratio, 1.70; 95% CI, 1.07–2.92; P = .04). The white matter hyperintensity volumes were not associated with either hematoma volume or expansion. CONCLUSIONS AND RELEVANCE In patients admitted with primary lobar or deep ICH to a single tertiary care medical center, the presence of cortical superficial siderosis was an independent variable associated with larger lobar ICH volume, and the absence of cerebral microbleeds was associated with larger lobar and deep ICHs. The absence of cerebral microbleeds was independently associated with more frequent hematoma expansion in patients with lobar ICH. We provide an analytical framework for future studies aimed at limiting hematoma expansion. PMID:27723863

The Belle II Silicon Vertex Detector

NASA Astrophysics Data System (ADS)

Friedl, M.; Ackermann, K.; Aihara, H.; Aziz, T.; Bergauer, T.; Bozek, A.; Campbell, A.; Dingfelder, J.; Drasal, Z.; Frankenberger, A.; Gadow, K.; Gfall, I.; Haba, J.; Hara, K.; Hara, T.; Higuchi, T.; Himori, S.; Irmler, C.; Ishikawa, A.; Joo, C.; Kah, D. H.; Kang, K. H.; Kato, E.; Kiesling, C.; Kodys, P.; Kohriki, T.; Koike, S.; Kvasnicka, P.; Marinas, C.; Mayekar, S. N.; Mibe, T.; Mohanty, G. B.; Moll, A.; Negishi, K.; Nakayama, H.; Natkaniec, Z.; Niebuhr, C.; Onuki, Y.; Ostrowicz, W.; Park, H.; Rao, K. K.; Ritter, M.; Rozanska, M.; Saito, T.; Sakai, K.; Sato, N.; Schmid, S.; Schnell, M.; Shimizu, N.; Steininger, H.; Tanaka, S.; Tanida, K.; Taylor, G.; Tsuboyama, T.; Ueno, K.; Uozumi, S.; Ushiroda, Y.; Valentan, M.; Yamamoto, H.

2013-12-01

The KEKB machine and the Belle experiment in Tsukuba (Japan) are now undergoing an upgrade, leading to an ultimate luminosity of 8×1035 cm-2 s-1 in order to measure rare decays in the B system with high statistics. The previous vertex detector cannot cope with this 40-fold increase of luminosity and thus needs to be replaced. Belle II will be equipped with a two-layer Pixel Detector surrounding the beam pipe, and four layers of double-sided silicon strip sensors at higher radii than the old detector. The Silicon Vertex Detector (SVD) will have a total sensitive area of 1.13 m2 and 223,744 channels-twice as many as its predecessor. All silicon sensors will be made from 150 mm wafers in order to maximize their size and thus to reduce the relative contribution of the support structure. The forward part has slanted sensors of trapezoidal shape to improve the measurement precision and to minimize the amount of material as seen by particles from the vertex. Fast-shaping front-end amplifiers will be used in conjunction with an online hit time reconstruction algorithm in order to reduce the occupancy to the level of a few percent at most. A novel “Origami” chip-on-sensor scheme is used to minimize both the distance between strips and amplifier (thus reducing the electronic noise) as well as the overall material budget. This report gives an overview on the status of the Belle II SVD and its components, including sensors, front-end detector ladders, mechanics, cooling and the readout electronics.

Complex numbers in chemometrics: examples from multivariate impedance measurements on lipid monolayers.

PubMed

Geladi, Paul; Nelson, Andrew; Lindholm-Sethson, Britta

2007-07-09

Electrical impedance gives multivariate complex number data as results. Two examples of multivariate electrical impedance data measured on lipid monolayers in different solutions give rise to matrices (16x50 and 38x50) of complex numbers. Multivariate data analysis by principal component analysis (PCA) or singular value decomposition (SVD) can be used for complex data and the necessary equations are given. The scores and loadings obtained are vectors of complex numbers. It is shown that the complex number PCA and SVD are better at concentrating information in a few components than the naïve juxtaposition method and that Argand diagrams can replace score and loading plots. Different concentrations of Magainin and Gramicidin A give different responses and also the role of the electrolyte medium can be studied. An interaction of Gramicidin A in the solution with the monolayer over time can be observed.

RF tomography of metallic objects in free space: preliminary results

NASA Astrophysics Data System (ADS)

Li, Jia; Ewing, Robert L.; Berdanier, Charles; Baker, Christopher

2015-05-01

RF tomography has great potential in defense and homeland security applications. A distributed sensing research facility is under development at Air Force Research Lab. To develop a RF tomographic imaging system for the facility, preliminary experiments have been performed in an indoor range with 12 radar sensors distributed on a circle of 3m radius. Ultra-wideband pulses are used to illuminate single and multiple metallic targets. The echoes received by distributed sensors were processed and combined for tomography reconstruction. Traditional matched filter algorithm and truncated singular value decomposition (SVD) algorithm are compared in terms of their complexity, accuracy, and suitability for distributed processing. A new algorithm is proposed for shape reconstruction, which jointly estimates the object boundary and scatter points on the waveform's propagation path. The results show that the new algorithm allows accurate reconstruction of object shape, which is not available through the matched filter and truncated SVD algorithms.

a Unified Matrix Polynomial Approach to Modal Identification

NASA Astrophysics Data System (ADS)

Allemang, R. J.; Brown, D. L.

1998-04-01

One important current focus of modal identification is a reformulation of modal parameter estimation algorithms into a single, consistent mathematical formulation with a corresponding set of definitions and unifying concepts. Particularly, a matrix polynomial approach is used to unify the presentation with respect to current algorithms such as the least-squares complex exponential (LSCE), the polyreference time domain (PTD), Ibrahim time domain (ITD), eigensystem realization algorithm (ERA), rational fraction polynomial (RFP), polyreference frequency domain (PFD) and the complex mode indication function (CMIF) methods. Using this unified matrix polynomial approach (UMPA) allows a discussion of the similarities and differences of the commonly used methods. the use of least squares (LS), total least squares (TLS), double least squares (DLS) and singular value decomposition (SVD) methods is discussed in order to take advantage of redundant measurement data. Eigenvalue and SVD transformation methods are utilized to reduce the effective size of the resulting eigenvalue-eigenvector problem as well.

Incorporation of perceptually adaptive QIM with singular value decomposition for blind audio watermarking

NASA Astrophysics Data System (ADS)

Hu, Hwai-Tsu; Chou, Hsien-Hsin; Yu, Chu; Hsu, Ling-Yuan

2014-12-01

This paper presents a novel approach for blind audio watermarking. The proposed scheme utilizes the flexibility of discrete wavelet packet transformation (DWPT) to approximate the critical bands and adaptively determines suitable embedding strengths for carrying out quantization index modulation (QIM). The singular value decomposition (SVD) is employed to analyze the matrix formed by the DWPT coefficients and embed watermark bits by manipulating singular values subject to perceptual criteria. To achieve even better performance, two auxiliary enhancement measures are attached to the developed scheme. Performance evaluation and comparison are demonstrated with the presence of common digital signal processing attacks. Experimental results confirm that the combination of the DWPT, SVD, and adaptive QIM achieves imperceptible data hiding with satisfying robustness and payload capacity. Moreover, the inclusion of self-synchronization capability allows the developed watermarking system to withstand time-shifting and cropping attacks.

Time evolution of two holes in t - J chains with anisotropic couplings

NASA Astrophysics Data System (ADS)

Manmana, Salvatore R.; Thyen, Holger; Köhler, Thomas; Kramer, Stephan C.

Using time-dependent Matrix Product State (MPS) methods we study the real-time evolution of hole-excitations in t-J chains close to filling n = 1 . The dynamics in 'standard' t - J chains with SU(2) invariant spin couplings is compared to the one when introducing anisotropic, XXZ-type spin interactions as realizable, e.g., by ultracold polar molecules on optical lattices. The simulations are performed with MPS implementations based on the usual singular value decompositions (SVD) as well as ones using the adaptive cross approximation (ACA) instead. The ACA can be seen as an iterative approach to SVD which is often used, e.g., in the context of finite-element-methods, leading to a substantial speedup. A comparison of the performance of both algorithms in the MPS context is discussed. Financial support via DFG through CRC 1073 (''Atomic scale control of energy conversion''), project B03 is gratefully acknowledged.

Parallel transformation of K-SVD solar image denoising algorithm

NASA Astrophysics Data System (ADS)

Liang, Youwen; Tian, Yu; Li, Mei

2017-02-01

The images obtained by observing the sun through a large telescope always suffered with noise due to the low SNR. K-SVD denoising algorithm can effectively remove Gauss white noise. Training dictionaries for sparse representations is a time consuming task, due to the large size of the data involved and to the complexity of the training algorithms. In this paper, an OpenMP parallel programming language is proposed to transform the serial algorithm to the parallel version. Data parallelism model is used to transform the algorithm. Not one atom but multiple atoms updated simultaneously is the biggest change. The denoising effect and acceleration performance are tested after completion of the parallel algorithm. Speedup of the program is 13.563 in condition of using 16 cores. This parallel version can fully utilize the multi-core CPU hardware resources, greatly reduce running time and easily to transplant in multi-core platform.

Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD.

PubMed

Bhandari, A K; Soni, V; Kumar, A; Singh, G K

2014-07-01

This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A Feasibility Study on a Parallel Mechanism for Examining the Space Shuttle Orbiter Payload Bay Radiators

NASA Technical Reports Server (NTRS)

Roberts, Rodney G.; LopezdelCastillo, Eduardo

1996-01-01

The goal of the project was to develop the necessary analysis tools for a feasibility study of a cable suspended robot system for examining the space shuttle orbiter payload bay radiators These tools were developed to address design issues such as workspace size, tension requirements on the cable, the necessary accuracy and resolution requirements and the stiffness and movement requirements of the system. This report describes the mathematical models for studying the inverse kinematics, statics, and stiffness of the robot. Each model is described by a matrix. The manipulator Jacobian was also related to the stiffness matrix, which characterized the stiffness of the system. Analysis tools were then developed based on the singular value decomposition (SVD) of the corresponding matrices. It was demonstrated how the SVD can be used to quantify the robot's performance and to provide insight into different design issues.

Channel Training for Analog FDD Repeaters: Optimal Estimators and Cramér-Rao Bounds

NASA Astrophysics Data System (ADS)

Wesemann, Stefan; Marzetta, Thomas L.

2017-12-01

For frequency division duplex channels, a simple pilot loop-back procedure has been proposed that allows the estimation of the UL & DL channels at an antenna array without relying on any digital signal processing at the terminal side. For this scheme, we derive the maximum likelihood (ML) estimators for the UL & DL channel subspaces, formulate the corresponding Cram\\'er-Rao bounds and show the asymptotic efficiency of both (SVD-based) estimators by means of Monte Carlo simulations. In addition, we illustrate how to compute the underlying (rank-1) SVD with quadratic time complexity by employing the power iteration method. To enable power control for the data transmission, knowledge of the channel gains is needed. Assuming that the UL & DL channels have on average the same gain, we formulate the ML estimator for the channel norm, and illustrate its robustness against strong noise by means of simulations.

Singular Value Decomposition Method to Determine Distance Distributions in Pulsed Dipolar Electron Spin Resonance.

PubMed

Srivastava, Madhur; Freed, Jack H

2017-11-16

Regularization is often utilized to elicit the desired physical results from experimental data. The recent development of a denoising procedure yielding about 2 orders of magnitude in improvement in SNR obviates the need for regularization, which achieves a compromise between canceling effects of noise and obtaining an estimate of the desired physical results. We show how singular value decomposition (SVD) can be employed directly on the denoised data, using pulse dipolar electron spin resonance experiments as an example. Such experiments are useful in measuring distances and their distributions, P(r) between spin labels on proteins. In noise-free model cases exact results are obtained, but even a small amount of noise (e.g., SNR = 850 after denoising) corrupts the solution. We develop criteria that precisely determine an optimum approximate solution, which can readily be automated. This method is applicable to any signal that is currently processed with regularization of its SVD analysis.

Glove-based approach to online signature verification.

PubMed

Kamel, Nidal S; Sayeed, Shohel; Ellis, Grant A

2008-06-01

Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.

Reaction Time is a Marker of Early Cognitive and Behavioral Alterations in Pure Cerebral Small Vessel Disease.

PubMed

Jouvent, Eric; Reyes, Sonia; De Guio, François; Chabriat, Hugues

2015-01-01

The assessment of early and subtle cognitive and behavioral effects of cerebral small vessel disease (SVD) requires specific and long-lasting evaluations performed by experienced neuropsychologists. Simpler tools would be helpful for daily clinical practice. To determine whether a simple reaction time task that lasts 5 minutes and can be performed without external supervision on any tablet or laptop can be used as a proxy of early cognitive and behavioral alterations in CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), a monogenic form of pure SVD related to NOTCH3 mutations. Twenty-two genetically confirmed patients with CADASIL having preserved global cognitive abilities and without disability (MMSE >24 and modified Rankin's scale ≤1) were compared to 29 age-and-gender matched controls to determine group differences according to: 1) conventional neuropsychological and behavioral testing; 2) a computerized battery evaluating reaction time, processing speed, and executive functions. In a second step, correlations between reaction time and cognitive and behavioral alterations detected using both conventional and computerized testing were tested in patients. Reaction time was significantly higher in patients than in controls (mean in patients: 283 ms - in controls: 254 ms, p = 0.03). In patients, reaction time was significantly associated with conventional and chronometric tests of executive functions, working memory, and apathy. Reaction time obtained using a very simple task may serve as a proxy of early cognitive and behavioral alterations in SVD and could be easily used in daily clinical practice.

The pathology and pathophysiology of vascular dementia.

PubMed

Kalaria, Raj N

2017-12-19

Vascular dementia (VaD) is widely recognised as the second most common type of dementia. Consensus and accurate diagnosis of clinically suspected VaD relies on wide-ranging clinical, neuropsychological and neuroimaging measures in life but more importantly pathological confirmation. Factors defining subtypes of VaD include the nature and extent of vascular pathologies, degree of involvement of extra and intracranial vessels and the anatomical location of tissue changes as well as time after the initial vascular event. Atherosclerotic and cardioembolic diseases combined appear the most common subtypes of vascular brain injury. In recent years, cerebral small vessel disease (SVD) has gained prominence worldwide as an important substrate of cognitive impairment. SVD is characterised by arteriolosclerosis, lacunar infarcts and cortical and subcortical microinfarcts and diffuse white matter changes, which involve myelin loss and axonal abnormalities. Global brain atrophy and focal degeneration of the cerebrum including medial temporal lobe atrophy are also features of VaD similar to Alzheimer's disease. Hereditary arteriopathies have provided insights into the mechanisms of dementia particularly how arteriolosclerosis, a major contributor of SVD promotes cognitive impairment. Recently developed and validated neuropathology guidelines indicated that the best predictors of vascular cognitive impairment were small or lacunar infarcts, microinfarcts, perivascular space dilation, myelin loss, arteriolosclerosis and leptomeningeal cerebral amyloid angiopathy. While these substrates do not suggest high specificity, VaD is likely defined by key neuronal and dendro-synaptic changes resulting in executive dysfunction and related cognitive deficits. Greater understanding of the molecular pathology is needed to clearly define microvascular disease and vascular substrates of dementia. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Framework for Propagation of Uncertainties in the Kepler Data Analysis Pipeline

NASA Technical Reports Server (NTRS)

Clarke, Bruce D.; Allen, Christopher; Bryson, Stephen T.; Caldwell, Douglas A.; Chandrasekaran, Hema; Cote, Miles T.; Girouard, Forrest; Jenkins, Jon M.; Klaus, Todd C.; Li, Jie;

Medial medullary infarction: clinical, imaging, and outcome study in 86 consecutive patients.

PubMed

Kim, Jong S; Han, Young S

2009-10-01

Clinical-imaging correlation and long-term clinical outcomes remain to be investigated in medial medullary infarction (MMI). We studied clinical, MRI, and angiographic data of 86 consecutive MMI patients. The lesions were correlated with clinical findings, and long-term outcomes, divided into mild and severe (modified Rankin scale >3), were assessed by telephone interview. Central poststroke pain (CPSP) was defined as persistent pain with visual numeric scale > or = 4. The lesions were located mostly in the rostral medulla (rostral 76%, rostral+middle 16%), while ventro-dorsal lesion patterns include ventral (V, 20%), ventral+middle (VM, 33%), and ventral+middle+dorsal (VMD, 41%). Clinical manifestations included motor dysfunction in 78 patients (91%), sensory dysfunction in 59 (73%), and vertigo/dizziness in 51 (59%), each closely related to involvement of ventral, middle, and dorsal portions, respectively (P<0.001, each). Vertebral artery (VA) atherosclerotic disease relevant to the infarction occurred in 53 (62%) patients, mostly producing atheromatous branch occlusion (ABO). Small vessel disease (SVD) occurred in 24 (28%) patients. ABO was more closely related to VMD (versus V+VM) than was SVD (P=0.035). During follow-up (mean 71 months), 11 patients died, and recurrent strokes occurred in 11. Old age (P=0.001) and severe motor dysfunction at admission (P=0.001) were factors predicting poor prognosis. CPSP, occurring in 21 patients, was closely (P=0.013) related to poor clinical outcome. MMI usually presents with a rostral medullary lesion, with a good clinical ventro-dorsal imaging correlation, caused most frequently by ABO followed by SVD. A significant proportion of patients remain dependent or have CPSP.

Vitamin D status and vascular dementia due to cerebral small vessel disease in the elderly Asian Indian population.

PubMed

Prabhakar, Puttachandra; Chandra, Sadanandavalli Retnaswami; Supriya, Manjunath; Issac, Thomas Gregor; Prasad, Chandrajit; Christopher, Rita

2015-12-15

Vitamin D plays vital roles in human health and recent studies have shown its beneficial effect on brain functioning. The present study was designed to evaluate the association of vitamin D with vascular dementia (VaD) due to cerebral small vessel disease (SVD) in Asian Indian population. 140 VaD patients aged ≥ 60 years with neuroimaging evidence of SVD, and 132 age and gender-matched controls, were investigated. Vitamin D status was estimated by measuring serum 25-hydroxy vitamin D. Logistic regression model revealed that deficient levels of vitamin D (<12 ng/ml) were associated with 2.2-fold increase in odds of VaD after adjustment with covariates. Hypertension was independently associated with 11.3-fold increased odds of VaD. In hypertensives with vitamin D deficiency and insufficiency (12-20 ng/ml), the odds were increased to 31.6-fold and 14.4-fold, respectively. However, in hypertensives with vitamin D sufficiency (>20 ng/ml), the odds of VaD were increased by 3.8-fold only. Pearson correlation showed that serum vitamin D was inversely associated with systolic and diastolic blood pressure (r=-0.401 and -0.411, p<0.01, respectively) in vitamin D-deficient subjects. Since the combined presence of hypertension and vitamin D deficiency increases the probability of developing VaD, screening for vitamin D status in addition to regular monitoring of blood pressure, could reduce the risk of VaD associated with cerebral SVD in the elderly Asian Indian subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

Structural brain changes and all-cause mortality in the elderly population-the mediating role of inflammation.

PubMed

Hanning, Uta; Roesler, Andreas; Peters, Annette; Berger, Klaus; Baune, Bernhard T

2016-12-01

While MRI brain changes have been related to mortality during ageing, the role of inflammation in this relationship remains poorly understood. Hence, this study aimed to investigate the impact of MRI changes on all-cause mortality and the mediating role of cytokines. All-cause mortality was evaluated in 268 community dwelling elderly (age 65-83 years) in the MEMO study (Memory and Morbidity in Augsburg elderly). MRI markers of brain atrophy and cerebral small vessel disease (SVD), C-reactive protein (CRP) and a panel of cytokines in serum were assessed. Cox proportional hazard models were used to estimate the association of MRI changes with survival over 9 years. Regression models were used to assess the hypothesis that inflammation is mediating the relationship between MRI-brain changes and mortality. In total, 77 (29 %) deaths occurred during a mean follow up of 9 years. After adjusting for confounders, the degree of global cortical atrophy and the level of the cytokines CRP, TNF-α and IL-8 were of higher significance in study participants who had died at follow-up in comparison to survivors. In Cox proportional hazard models, higher degrees of global cortical atrophy (HR 1.56, p = 0.003) and regional atrophy of the temporal lobe (HR 1.38, p = 0.011) were associated with a significantly increased risk of mortality. Mediation analyses revealed a partial mediation by IL-6 and IL-8 of the effects of global cortical atrophy on mortality. Global cortical brain atrophy is a significant indicator of survival in the elderly. Our study supports a possible role for inflammation in the atrophy pathogenesis. If replicated in other samples, IL-6 and IL-8 level assessment may improve risk prognosis for mortality.

Comparison of Different Measurement Technologies for the In-Flight Assessment of Radiated Acoustic Intensity

NASA Technical Reports Server (NTRS)

Klos, Jacob; Palumbo, Daniel L.; Buehrle, Ralph D.; Williams, Earl G.; Valdivia, Nicolas; Herdic, Peter C.; Sklanka, Bernard

2005-01-01

A series of tests was planned and conducted in the Interior Noise Test Facility at Boeing Field, on the NASA Aries 757 flight research aircraft, and in the Structural Acoustic Loads and Transmission Facility at NASA Langley Research Center. These tests were designed to answer several questions concerning the use of array methods in flight. One focus of the tests was determining whether and to what extent array methods could be used to identify the effects of an acoustical treatment applied to a limited portion of an aircraft fuselage. Another focus of the tests was to verify that the arrays could be used to localize and quantify a known source purposely placed in front of the arrays. Thus the issues related to backside sources and flanking paths present in the complicated sound field were addressed during these tests. These issues were addressed through the use of reference transducers, both accelerometers mounted to the fuselage and microphones in the cabin, that were used to correlate the pressure holograms. measured by the microphone arrays using either SVD methods or partial coherence methods. This correlation analysis accepts only energy that is coherent with the sources sensed by the reference transducers, allowing a noise control engineer to only identify and study those vibratory sources of interest. The remainder of this paper will present a detailed description of the test setups that were used in this test sequence and typical results of the NAH/IBEM analysis used to reconstruct the sound fields. Also, a comparison of data obtained in the laboratory environments and during flights of the 757 aircraft will be made.

Investigating the Differences in the Total and Active Microbial Community of Mid-Atlantic Ridge Sediments

NASA Astrophysics Data System (ADS)

Sobol, M. S.; Zinke, L. A.; Orcutt, B.; Mills, H. J.; Edwards, K. J.; Girguis, P. R.; Reese, B. K.

2016-02-01

Microbes in the marine deep subsurface are key mediators of many geochemical cycles. It is important to understand how microbial communities and the diversity of those communities impacts geochemical cycling. Sediment cores were collected from IODP (Integrated Ocean Drilling Program) Expedition 336 to the western flank of the mid-Atlantic ridge also referred to as North Pond. The dissolved oxygen concentration decreased with depth for 60-70 mbsf, followed by a sharp increase in oxygen until it terminated at the basement. The 16S rRNA genes (DNA) and transcripts (RNA) were extracted simultaneously using a method designed by Reese et al. (2013) to differentiate between the total and active microbial community structures, respectively, as well as correlate the putative metabolism with the geochemistry. We observed many differences between the active and total communities. Sequences most closely related to Cyanobacteria were found to dominate the total community at both sites, but were found in small numbers in the active community. The most abundant phyla in the active community were Alphaproteobacteria, which suggests that they may have high activity even though the abundance was not as great in the total community. This suggests that, even in small numbers, bacteria are capable of contributing greatly to their environment. Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) showed that iron-reducing bacteria in the active (RNA) community correlated strongly with solid phase iron oxides. SVD also showed that the putative nitrate reducers in the active community were found in greater abundance where porewater NO3- and NO2- total concentrations were elevated. Overall, the active (RNA) community correlated significantly with the geochemistry whereas the total (DNA) community did not. Therefore, RNA analysis yields a more accurate representation of how microbial communities impact geochemical cycling.

Objective Assessment and Design Improvement of a Staring, Sparse Transducer Array by the Spatial Crosstalk Matrix for 3D Photoacoustic Tomography

PubMed Central

Kosik, Ivan; Raess, Avery

2015-01-01

Accurate reconstruction of 3D photoacoustic (PA) images requires detection of photoacoustic signals from many angles. Several groups have adopted staring ultrasound arrays, but assessment of array performance has been limited. We previously reported on a method to calibrate a 3D PA tomography (PAT) staring array system and analyze system performance using singular value decomposition (SVD). The developed SVD metric, however, was impractical for large system matrices, which are typical of 3D PAT problems. The present study consisted of two main objectives. The first objective aimed to introduce the crosstalk matrix concept to the field of PAT for system design. Figures-of-merit utilized in this study were root mean square error, peak signal-to-noise ratio, mean absolute error, and a three dimensional structural similarity index, which were derived between the normalized spatial crosstalk matrix and the identity matrix. The applicability of this approach for 3D PAT was validated by observing the response of the figures-of-merit in relation to well-understood PAT sampling characteristics (i.e. spatial and temporal sampling rate). The second objective aimed to utilize the figures-of-merit to characterize and improve the performance of a near-spherical staring array design. Transducer arrangement, array radius, and array angular coverage were the design parameters examined. We observed that the performance of a 129-element staring transducer array for 3D PAT could be improved by selection of optimal values of the design parameters. The results suggested that this formulation could be used to objectively characterize 3D PAT system performance and would enable the development of efficient strategies for system design optimization. PMID:25875177

Mode of delivery and risk of intracranial haemorrhage in newborns with severe haemophilia A: a multicentre study in Gulf region.

PubMed

Nazir, H F; Al Lawati, T; Beshlawi, I; AlSharidah, S; Elshinawy, M; Alkasim, F; Khanani, M F; Tarawa, A; Al Subhi, T; Alrawas, A; Al Riyami, W; Al Kindi, S; Al Saadi, K; Al-Lamki, S; Wali, Y

2016-05-01

The optimum mode of delivery in a known carrier of a haemophilia A is still an issue of debate. This study was conducted to report a multicentre experience in Gulf Cooperation Council (GCC) on the incidence of intracranial haemorrhage (ICH) in newborns with severe haemophilia A delivered by different modalities. We have conducted a retrospective/prospective multicentre cohort study including a total of seven hospitals distributed in four GCC countries between 1998 and Jan 2015. A total of 163 patient with severe haemophilia A (factor VIII <1%) were enrolled in this study, age ranged between 2 weeks to 18 years. Most of the patients were born by spontaneous vaginal delivery (SVD) (131, 80.4%), whereas 26 patients (16%) were born by CS and only six patients were born by instrumental delivery (3.7%), five of them by vacuum and one was delivered using forceps. Five out of 163 patients developed ICH during the first 2 weeks of life (3.1%). Two of them were born by SVD (2/131; 1.5%) and two were born by instrumental delivery (2/6; 33.3%). Only one patient among those who were born by caesarean section developed ICH (1/26; 3.8%). Assisted vaginal delivery was associated with a significant risk of ICH, in comparison to SVD and CS (P = 0.0093). Normal vaginal delivery is still considered a safe journey through the birth canal for haemophilic newborns particularly in this area of the world. Larger prospective studies might be needed to define an evidence-based optimal mode of delivery for the haemophilia carrier expecting an affected child. © 2015 John Wiley & Sons Ltd.

Covariability of Central America/Mexico winter precipitation and tropical sea surface temperatures

NASA Astrophysics Data System (ADS)

Pan, Yutong; Zeng, Ning; Mariotti, Annarita; Wang, Hui; Kumar, Arun; Sánchez, René Lobato; Jha, Bhaskar

2018-06-01

In this study, the relationships between Central America/Mexico (CAM) winter precipitation and tropical Pacific/Atlantic sea surface temperatures (SSTs) are examined based on 68-year (1948-2015) observations and 59-year (1957-2015) atmospheric model simulations forced by observed SSTs. The covariability of the winter precipitation and SSTs is quantified using the singular value decomposition (SVD) method with observational data. The first SVD mode relates out-of-phase precipitation anomalies in northern Mexico and Central America to the tropical Pacific El Niño/La Niña SST variation. The second mode links a decreasing trend in the precipitation over Central America to the warming of SSTs in the tropical Atlantic, as well as in the tropical western Pacific and the tropical Indian Ocean. The first mode represents 67% of the covariance between the two fields, indicating a strong association between CAM winter precipitation and El Niño/La Niña, whereas the second mode represents 20% of the covariance. The two modes account for 32% of CAM winter precipitation variance, of which, 17% is related to the El Niño/La Niña SST and 15% is related to the SST warming trend. The atmospheric circulation patterns, including 500-hPa height and low-level winds obtained by linear regressions against the SVD SST time series, are dynamically consistent with the precipitation anomaly patterns. The model simulations driven by the observed SSTs suggest that these precipitation anomalies are likely a response to tropical SST forcing. It is also shown that there is significant potential predictability of CAM winter precipitation given tropical SST information.

Plasma Amyloid-β Levels, Cerebral Small Vessel Disease, and Cognition: The Rotterdam Study.

PubMed

Hilal, Saima; Akoudad, Saloua; van Duijn, Cornelia M; Niessen, Wiro J; Verbeek, Marcel M; Vanderstichele, Hugo; Stoops, Erik; Ikram, M Arfan; Vernooij, Meike W

2017-01-01

Plasma amyloid-β (Aβ) levels are increasingly studied as a potential, accessible marker of cognitive impairment and dementia. The most common plasma Aβ isoforms, i.e., Aβ1-40 and Aβ1-42 have been linked with risk of Alzheimer's disease. However, it remains under-explored whether plasma Aβ levels including novel Aβ1-38 relate to vascular brain disease and cognition in a preclinical-phase of dementiaObjective:To examine the association of plasma Aβ levels (i.e., Aβ1-38, Aβ1-40, and Aβ1-42) with markers of cerebral small vessel disease (SVD) and cognition in a large population-based setting. We analyzed plasma Aβ1 levels in 1201 subjects from two independent cohorts of the Rotterdam Study. Markers of SVD [lacunes, white matter hyperintensity (WMH) volume] were assessed on brain MRI (1.5T). Cognition was assessed by a detailed neuropsychological battery. In each cohort, the association of Aβ levels with SVD and cognition was performed using regression models. Estimates were then pooled across cohorts using inverse variance meta-analysis with fixed effects. Higher levels of plasma Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-40/ Aβ1-42 ratio were associated with increasing lacunar and microbleeds counts. Moreover, higher levels of Aβ1-40 and Aβ1-40/ Aβ1-42 were significantly associated with larger WMH volumes. With regard to cognition, a higher level of Aβ1-38 Aβ1-40 and Aβ1-40/ Aβ1-42 was related to worse performance on cognitive test specifically in memory domain. Higher plasma levels of Aβ levels are associated with subclinical markers of vascular disease and poorer memory. Plasma Aβ levels thus mark the presence of vascular brain pathology.

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations.

PubMed

Mandke, Kanad; Meier, Jil; Brookes, Matthew J; O'Dea, Reuben D; Van Mieghem, Piet; Stam, Cornelis J; Hillebrand, Arjan; Tewarie, Prejaas

2018-02-01

There is an increasing awareness of the advantages of multi-modal neuroimaging. Networks obtained from different modalities are usually treated in isolation, which is however contradictory to accumulating evidence that these networks show non-trivial interdependencies. Even networks obtained from a single modality, such as frequency-band specific functional networks measured from magnetoencephalography (MEG) are often treated independently. Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation for group comparison. We analyse how well-known biases for single layer networks, such as effects of group differences in link density and/or average connectivity, influence multilayer networks, and we compare four schemes that aim to correct for such biases: the minimum spanning tree (MST), effective graph resistance cost minimisation, efficiency cost optimisation (ECO) and a normalisation scheme based on singular value decomposition (SVD). These schemes can be applied to the layers independently or to the multilayer network as a whole. For correction applied to whole multilayer networks, only the SVD showed sufficient bias correction. For correction applied to individual layers, three schemes (ECO, MST, SVD) could correct for biases. By using generative models as well as empirical MEG and functional magnetic resonance imaging (fMRI) data, we further demonstrated that all schemes were sensitive to identify network topology when the original networks were perturbed. In conclusion, uncorrected multilayer network analysis leads to biases. These biases may differ between centres and studies and could consequently lead to unreproducible results in a similar manner as for single layer networks. We therefore recommend using correction schemes prior to multilayer network analysis for group comparisons. Copyright © 2017 Elsevier Inc. All rights reserved.

A multi-subunit Chlamydia vaccine inducing neutralizing antibodies and strong IFN-γ⁺ CMI responses protects against a genital infection in minipigs.

PubMed

Bøje, Sarah; Olsen, Anja Weinreich; Erneholm, Karin; Agerholm, Jørgen Steen; Jungersen, Gregers; Andersen, Peter; Follmann, Frank

2016-02-01

Chlamydia is the most widespread sexually transmitted bacterial disease and a prophylactic vaccine is highly needed. Ideally, this vaccine is required to induce a combined response of Th1 cell-mediated immune (CMI) response in concert with neutralizing antibodies. Using a novel Göttingen minipig animal model, we evaluated the immunogenicity and efficacy of a multi-subunit vaccine formulated in the strong Th1-inducing adjuvant CAF01. We evaluated a mixture of two fusion proteins (Hirep1 and CTH93) designed to promote either neutralizing antibodies or cell-mediated immunity, respectively. Hirep1 is a novel immunogen based on the variant domain (VD) 4 region from major outer membrane protein (MOMP) serovar (Sv) D, SvE and SvF, and CTH93 is a fusion molecule of three antigens (CT043, CT414 and MOMP). Pigs were immunized twice intramuscularly with either Hirep1+CTH93/CAF01, UV-inactivated Chlamydia trachomatis SvD bacteria (UV-SvD/CAF01) or CAF01. The Hirep1+CTH93/CAF01 vaccine induced a strong CMI response against the vaccine antigens and high titers of antibodies, particularly against the VD4 region of MOMP. Sera from Hirep1+CTH93/CAF01 immunized pigs neutralized C. trachomatis SvD and SvF infectivity in vitro. Both Hirep1+CTH93/CAF01 and UV-SvD/CAF01 vaccination protected pigs against a vaginal C. trachomatis SvD infection. In conclusion, the Hirep1+CTH93/CAF01 vaccine proved highly immunogenic and equally protective as UV-SvD/CAF01 showing promise for the development of a subunit vaccine against Chlamydia.

A multi-subunit Chlamydia vaccine inducing neutralizing antibodies and strong IFN-γ+ CMI responses protects against a genital infection in minipigs

PubMed Central

Bøje, Sarah; Olsen, Anja Weinreich; Erneholm, Karin; Agerholm, Jørgen Steen; Jungersen, Gregers; Andersen, Peter; Follmann, Frank

2016-01-01

Chlamydia is the most widespread sexually transmitted bacterial disease and a prophylactic vaccine is highly needed. Ideally, this vaccine is required to induce a combined response of Th1 cell-mediated immune (CMI) response in concert with neutralizing antibodies. Using a novel Göttingen minipig animal model, we evaluated the immunogenicity and efficacy of a multi-subunit vaccine formulated in the strong Th1-inducing adjuvant CAF01. We evaluated a mixture of two fusion proteins (Hirep1 and CTH93) designed to promote either neutralizing antibodies or cell-mediated immunity, respectively. Hirep1 is a novel immunogen based on the variant domain (VD) 4 region from major outer membrane protein (MOMP) serovar (Sv) D, SvE and SvF, and CTH93 is a fusion molecule of three antigens (CT043, CT414 and MOMP). Pigs were immunized twice intramuscularly with either Hirep1+CTH93/CAF01, UV-inactivated Chlamydia trachomatis SvD bacteria (UV-SvD/CAF01) or CAF01. The Hirep1+CTH93/CAF01 vaccine induced a strong CMI response against the vaccine antigens and high titers of antibodies, particularly against the VD4 region of MOMP. Sera from Hirep1+CTH93/CAF01 immunized pigs neutralized C. trachomatis SvD and SvF infectivity in vitro. Both Hirep1+CTH93/CAF01 and UV-SvD/CAF01 vaccination protected pigs against a vaginal C. trachomatis SvD infection. In conclusion, the Hirep1+CTH93/CAF01 vaccine proved highly immunogenic and equally protective as UV-SvD/CAF01 showing promise for the development of a subunit vaccine against Chlamydia. PMID:26268662

Inverse electrocardiographic transformations: dependence on the number of epicardial regions and body surface data points.

PubMed

Johnston, P R; Walker, S J; Hyttinen, J A; Kilpatrick, D

1994-04-01

The inverse problem of electrocardiography, the computation of epicardial potentials from body surface potentials, is influenced by the desired resolution on the epicardium, the number of recording points on the body surface, and the method of limiting the inversion process. To examine the role of these variables in the computation of the inverse transform, Tikhonov's zero-order regularization and singular value decomposition (SVD) have been used to invert the forward transfer matrix. The inverses have been compared in a data-independent manner using the resolution and the noise amplification as endpoints. Sets of 32, 50, 192, and 384 leads were chosen as sets of body surface data, and 26, 50, 74, and 98 regions were chosen to represent the epicardium. The resolution and noise were both improved by using a greater number of electrodes on the body surface. When 60% of the singular values are retained, the results show a trade-off between noise and resolution, with typical maximal epicardial noise levels of less than 0.5% of maximum epicardial potentials for 26 epicardial regions, 2.5% for 50 epicardial regions, 7.5% for 74 epicardial regions, and 50% for 98 epicardial regions. As the number of epicardial regions is increased, the regularization technique effectively fixes the noise amplification but markedly decreases the resolution, whereas SVD results in an increase in noise and a moderate decrease in resolution. Overall the regularization technique performs slightly better than SVD in the noise-resolution relationship. There is a region at the posterior of the heart that was poorly resolved regardless of the number of regions chosen. The variance of the resolution was such as to suggest the use of variable-size epicardial regions based on the resolution.

Using metabolic flux data to further constrain the metabolic solution space and predict internal flux patterns: the Escherichia coli spectrum.

PubMed

Wiback, Sharon J; Mahadevan, Radhakrishnan; Palsson, Bernhard Ø

2004-05-05

Constraint-based metabolic modeling has been used to capture the genome-scale, systems properties of an organism's metabolism. The first generation of these models has been built on annotated gene sequence. To further this field, we now need to develop methods to incorporate additional "omic" data types including transcriptomics, metabolomics, and fluxomics to further facilitate the construction, validation, and predictive capabilities of these models. The work herein combines metabolic flux data with an in silico model of central metabolism of Escherichia coli for model centric integration of the flux data. The extreme pathways for this network, which define the allowable solution space for all possible flux distributions, are analyzed using the alpha-spectrum. The alpha-spectrum determines which extreme pathways can and cannot contribute to the metabolic flux distribution for a given condition and gives the allowable range of weightings on each extreme pathway that can contribute. Since many extreme pathways cannot be used under certain conditions, the result is a "condition-specific" solution space that is a subset of the original solution space. The alpha-spectrum results are used to create a "condition-specific" extreme pathway matrix that can be analyzed using singular value decomposition (SVD). The first mode of the SVD analysis characterizes the solution space for a given condition. We show that SVD analysis of the alpha-spectrum extreme pathway matrix that incorporates measured uptake and byproduct secretion rates, can predict internal flux trends for different experimental conditions. These predicted internal flux trends are, in general, consistent with the flux trends measured using experimental metabolic flux analysis techniques. Copyright 2004 Wiley Periodicals, Inc.

Unitary Operators on the Document Space.

ERIC Educational Resources Information Center

Hoenkamp, Eduard

2003-01-01

Discusses latent semantic indexing (LSI) that would allow search engines to reduce the dimension of the document space by mapping it into a space spanned by conceptual indices. Topics include vector space models; singular value decomposition (SVD); unitary operators; the Haar transform; and new algorithms. (Author/LRW)

Face recognition using tridiagonal matrix enhanced multivariance products representation

NASA Astrophysics Data System (ADS)

Ã-zay, Evrim Korkmaz

2017-01-01

This study aims to retrieve face images from a database according to a target face image. For this purpose, Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is taken into consideration. TMEMPR is a recursive algorithm based on Enhanced Multivariance Products Representation (EMPR). TMEMPR decomposes a matrix into three components which are a matrix of left support terms, a tridiagonal matrix of weight parameters for each recursion, and a matrix of right support terms, respectively. In this sense, there is an analogy between Singular Value Decomposition (SVD) and TMEMPR. However TMEMPR is a more flexible algorithm since its initial support terms (or vectors) can be chosen as desired. Low computational complexity is another advantage of TMEMPR because the algorithm has been constructed with recursions of certain arithmetic operations without requiring any iteration. The algorithm has been trained and tested with ORL face image database with 400 different grayscale images of 40 different people. TMEMPR's performance has been compared with SVD's performance as a result.

Flexitarian Diets and Health: A Review of the Evidence-Based Literature

PubMed Central

Derbyshire, Emma J.

2017-01-01

A flexitarian or semi-vegetarian diet (SVD) is one that is primarily vegetarian with the occasional inclusion of meat or fish. Of late, there appears to be an increasing movement toward this practice. There has not been a recent update on these diets from a health perspective. Using the National Centre for Biotechnology Information PubMed database, a search was made for all studies published between 2000 and 2016 that met defined inclusion criteria. A total of 25 studies were located with 12 focusing on body weight and diet quality. There was emerging evidence suggestive of benefits for body weight, improved markers of metabolic health, blood pressure, and reduced risk of type 2 diabetes. SVD may also have a role to play in the treatment of inflammatory bowel diseases, such as Crohn’s disease. Given that there is a higher tendency for females to be flexitarian yet males are more likely to overconsume meat, there is a clear need to communicate the potential health benefits of these diets to males. PMID:28111625

Feedback process responsible for intermodel diversity of ENSO variability

NASA Astrophysics Data System (ADS)

An, Soon-Il; Heo, Eun Sook; Kim, Seon Tae

2017-05-01

The origin of the intermodel diversity of the El Niño-Southern Oscillation (ENSO) variability is investigated by applying a singular value decomposition (SVD) analysis between the intermodel tropical Pacific sea surface temperature anomalies (SSTA) variance and the intermodel ENSO stability index (BJ index). The first SVD mode features an ENSO-like pattern for the intermodel SSTA variance (74% of total variance) and the dominant thermocline feedback (TH) for the BJ index (51%). Intermodel TH is mainly modified by the intermodel sensitivity of the zonal thermocline gradient response to zonal winds over the equatorial Pacific (βh), and the intermodel βh is correlated higher with the intermodel off-equatorial wind stress curl anomalies than the equatorial zonal wind stress anomalies. Finally, the intermodel off-equatorial wind stress curl is associated with the meridional shape and intensity of ENSO-related wind patterns, which may cause a model-to-model difference in ENSO variability by influencing the off-equatorial oceanic Rossby wave response.

Singular value decomposition based feature extraction technique for physiological signal analysis.

PubMed

Chang, Cheng-Ding; Wang, Chien-Chih; Jiang, Bernard C

2012-06-01

Multiscale entropy (MSE) is one of the popular techniques to calculate and describe the complexity of the physiological signal. Many studies use this approach to detect changes in the physiological conditions in the human body. However, MSE results are easily affected by noise and trends, leading to incorrect estimation of MSE values. In this paper, singular value decomposition (SVD) is adopted to replace MSE to extract the features of physiological signals, and adopt the support vector machine (SVM) to classify the different physiological states. A test data set based on the PhysioNet website was used, and the classification results showed that using SVD to extract features of the physiological signal could attain a classification accuracy rate of 89.157%, which is higher than that using the MSE value (71.084%). The results show the proposed analysis procedure is effective and appropriate for distinguishing different physiological states. This promising result could be used as a reference for doctors in diagnosis of congestive heart failure (CHF) disease.

SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults

NASA Astrophysics Data System (ADS)

Golafshan, Reza; Yuce Sanliturk, Kenan

2016-03-01

Ball bearings remain one of the most crucial components in industrial machines and due to their critical role, it is of great importance to monitor their conditions under operation. However, due to the background noise in acquired signals, it is not always possible to identify probable faults. This incapability in identifying the faults makes the de-noising process one of the most essential steps in the field of Condition Monitoring (CM) and fault detection. In the present study, Singular Value Decomposition (SVD) and Hankel matrix based de-noising process is successfully applied to the ball bearing time domain vibration signals as well as to their spectrums for the elimination of the background noise and the improvement the reliability of the fault detection process. The test cases conducted using experimental as well as the simulated vibration signals demonstrate the effectiveness of the proposed de-noising approach for the ball bearing fault detection.

Sliding window denoising K-Singular Value Decomposition and its application on rolling bearing impact fault diagnosis

NASA Astrophysics Data System (ADS)

Yang, Honggang; Lin, Huibin; Ding, Kang

2018-05-01

The performance of sparse features extraction by commonly used K-Singular Value Decomposition (K-SVD) method depends largely on the signal segment selected in rolling bearing diagnosis, furthermore, the calculating speed is relatively slow and the dictionary becomes so redundant when the fault signal is relatively long. A new sliding window denoising K-SVD (SWD-KSVD) method is proposed, which uses only one small segment of time domain signal containing impacts to perform sliding window dictionary learning and select an optimal pattern with oscillating information of the rolling bearing fault according to a maximum variance principle. An inner product operation between the optimal pattern and the whole fault signal is performed to enhance the characteristic of the impacts' occurrence moments. Lastly, the signal is reconstructed at peak points of the inner product to realize the extraction of the rolling bearing fault features. Both simulation and experiments verify that the method could extract the fault features effectively.

SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain

PubMed Central

McGivney, Debra F.; Pierre, Eric; Ma, Dan; Jiang, Yun; Saybasili, Haris; Gulani, Vikas; Griswold, Mark A.

2016-01-01

Magnetic resonance fingerprinting is a technique for acquiring and processing MR data that simultaneously provides quantitative maps of different tissue parameters through a pattern recognition algorithm. A predefined dictionary models the possible signal evolutions simulated using the Bloch equations with different combinations of various MR parameters and pattern recognition is completed by computing the inner product between the observed signal and each of the predicted signals within the dictionary. Though this matching algorithm has been shown to accurately predict the MR parameters of interest, one desires a more efficient method to obtain the quantitative images. We propose to compress the dictionary using the singular value decomposition (SVD), which will provide a low-rank approximation. By compressing the size of the dictionary in the time domain, we are able to speed up the pattern recognition algorithm, by a factor of between 3.4-4.8, without sacrificing the high signal-to-noise ratio of the original scheme presented previously. PMID:25029380

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.

PubMed

Wei, Runmin; Wang, Jingye; Su, Mingming; Jia, Erik; Chen, Shaoqiu; Chen, Tianlu; Ni, Yan

2018-01-12

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).

Intelligent Classification in Huge Heterogeneous Data Sets

DTIC Science & Technology

2015-06-01

Competencies DoD Department of Defense GMTI Ground Moving Target Indicator ISR Intelligence, Surveillance and Reconnaissance NCD Noncoherent Change...Detection OCR Optical Character Recognition PCA Principal Component Analysis SAR Synthetic Aperture Radar SVD Singular Value Decomponsition USPS United States Postal Service 8 Approved for Public Release; Distribution Unlimited.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Singular value decomposition utilizing parallel algorithms on graphical processors

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

Kotas, Charlotte W; Barhen, Jacob

2011-01-01

One of the current challenges in underwater acoustic array signal processing is the detection of quiet targets in the presence of noise. In order to enable robust detection, one of the key processing steps requires data and replica whitening. This, in turn, involves the eigen-decomposition of the sample spectral matrix, Cx = 1/K xKX(k)XH(k) where X(k) denotes a single frequency snapshot with an element for each element of the array. By employing the singular value decomposition (SVD) method, the eigenvectors and eigenvalues can be determined directly from the data without computing the sample covariance matrix, reducing the computational requirements formore » a given level of accuracy (van Trees, Optimum Array Processing). (Recall that the SVD of a complex matrix A involves determining V, , and U such that A = U VH where U and V are orthonormal and is a positive, real, diagonal matrix containing the singular values of A. U and V are the eigenvectors of AAH and AHA, respectively, while the singular values are the square roots of the eigenvalues of AAH.) Because it is desirable to be able to compute these quantities in real time, an efficient technique for computing the SVD is vital. In addition, emerging multicore processors like graphical processing units (GPUs) are bringing parallel processing capabilities to an ever increasing number of users. Since the computational tasks involved in array signal processing are well suited for parallelization, it is expected that these computations will be implemented using GPUs as soon as users have the necessary computational tools available to them. Thus, it is important to have an SVD algorithm that is suitable for these processors. This work explores the effectiveness of two different parallel SVD implementations on an NVIDIA Tesla C2050 GPU (14 multiprocessors, 32 cores per multiprocessor, 1.15 GHz clock - peed). The first algorithm is based on a two-step algorithm which bidiagonalizes the matrix using Householder transformations, and then diagonalizes the intermediate bidiagonal matrix through implicit QR shifts. This is similar to that implemented for real matrices by Lahabar and Narayanan ("Singular Value Decomposition on GPU using CUDA", IEEE International Parallel Distributed Processing Symposium 2009). The implementation is done in a hybrid manner, with the bidiagonalization stage done using the GPU while the diagonalization stage is done using the CPU, with the GPU used to update the U and V matrices. The second algorithm is based on a one-sided Jacobi scheme utilizing a sequence of pair-wise column orthogonalizations such that A is replaced by AV until the resulting matrix is sufficiently orthogonal (that is, equal to U ). V is obtained from the sequence of orthogonalizations, while can be found from the square root of the diagonal elements of AH A and, once is known, U can be found from column scaling the resulting matrix. These implementations utilize CUDA Fortran and NVIDIA's CUB LAS library. The primary goal of this study is to quantify the comparative performance of these two techniques against themselves and other standard implementations (for example, MATLAB). Considering that there is significant overhead associated with transferring data to the GPU and with synchronization between the GPU and the host CPU, it is also important to understand when it is worthwhile to use the GPU in terms of the matrix size and number of concurrent SVDs to be calculated.« less

Implicit Multibody Penalty-BasedDistributed Contact.

PubMed

Xu, Hongyi; Zhao, Yili; Barbic, Jernej

2014-09-01

The penalty method is a simple and popular approach to resolving contact in computer graphics and robotics. Penalty-based contact, however, suffers from stability problems due to the highly variable and unpredictable net stiffness, and this is particularly pronounced in simulations with time-varying distributed geometrically complex contact. We employ semi-implicit integration, exact analytical contact gradients, symbolic Gaussian elimination and a SVD solver to simulate stable penalty-based frictional contact with large, time-varying contact areas, involving many rigid objects and articulated rigid objects in complex conforming contact and self-contact. We also derive implicit proportional-derivative control forces for real-time control of articulated structures with loops. We present challenging contact scenarios such as screwing a hexbolt into a hole, bowls stacked in perfectly conforming configurations, and manipulating many objects using actively controlled articulated mechanisms in real time.

Structure Calculation and Reconstruction of Discrete-State Dynamics from Residual Dipolar Couplings.

PubMed

Cole, Casey A; Mukhopadhyay, Rishi; Omar, Hanin; Hennig, Mirko; Valafar, Homayoun

2016-04-12

Residual dipolar couplings (RDCs) acquired by nuclear magnetic resonance (NMR) spectroscopy are an indispensable source of information in investigation of molecular structures and dynamics. Here, we present a comprehensive strategy for structure calculation and reconstruction of discrete-state dynamics from RDC data that is based on the singular value decomposition (SVD) method of order tensor estimation. In addition to structure determination, we provide a mechanism of producing an ensemble of conformations for the dynamical regions of a protein from RDC data. The developed methodology has been tested on simulated RDC data with ±1 Hz of error from an 83 residue α protein (PDB ID 1A1Z ) and a 213 residue α/β protein DGCR8 (PDB ID 2YT4 ). In nearly all instances, our method reproduced the structure of the protein including the conformational ensemble to within less than 2 Å. On the basis of our investigations, arc motions with more than 30° of rotation are identified as internal dynamics and are reconstructed with sufficient accuracy. Furthermore, states with relative occupancies above 20% are consistently recognized and reconstructed successfully. Arc motions with a magnitude of 15° or relative occupancy of less than 10% are consistently unrecognizable as dynamical regions within the context of ±1 Hz of error.

Structure-seeking multilinear methods for the analysis of fMRI data.

PubMed

Andersen, Anders H; Rayens, William S

2004-06-01

In comprehensive fMRI studies of brain function, the data structures often contain higher-order ways such as trial, task condition, subject, and group in addition to the intrinsic dimensions of time and space. While multivariate bilinear methods such as principal component analysis (PCA) have been used successfully for extracting information about spatial and temporal features in data from a single fMRI run, the need to unfold higher-order data sets into bilinear arrays has led to decompositions that are nonunique and to the loss of multiway linkages and interactions present in the data. These additional dimensions or ways can be retained in multilinear models to produce structures that are unique and which admit interpretations that are neurophysiologically meaningful. Multiway analysis of fMRI data from multiple runs of a bilateral finger-tapping paradigm was performed using the parallel factor (PARAFAC) model. A trilinear model was fitted to a data cube of dimensions voxels by time by run. Similarly, a quadrilinear model was fitted to a higher-way structure of dimensions voxels by time by trial by run. The spatial and temporal response components were extracted and validated by comparison to results from traditional SVD/PCA analyses based on scenarios of unfolding into lower-order bilinear structures.

Remarkable link between projected uncertainties of Arctic sea-ice decline and winter Eurasian climate

NASA Astrophysics Data System (ADS)

Cheung, Hoffman H. N.; Keenlyside, Noel; Omrani, Nour-Eddine; Zhou, Wen

2018-01-01

We identify that the projected uncertainty of the pan-Arctic sea-ice concentration (SIC) is strongly coupled with the Eurasian circulation in the boreal winter (December-March; DJFM), based on a singular value decomposition (SVD) analysis of the forced response of 11 CMIP5 models. In the models showing a stronger sea-ice decline, the Polar cell becomes weaker and there is an anomalous increase in the sea level pressure (SLP) along 60°N, including the Urals-Siberia region and the Iceland low region. There is an accompanying weakening of both the midlatitude westerly winds and the Ferrell cell, where the SVD signals are also related to anomalous sea surface temperature warming in the midlatitude North Atlantic. In the Mediterranean region, the anomalous circulation response shows a decreasing SLP and increasing precipitation. The anomalous SLP responses over the Euro-Atlantic region project on to the negative North Atlantic Oscillation-like pattern. Altogether, pan-Arctic SIC decline could strongly impact the winter Eurasian climate, but we should be cautious about the causality of their linkage.

Viromes of one year old infants reveal the impact of birth mode on microbiome diversity.

PubMed

McCann, Angela; Ryan, Feargal J; Stockdale, Stephen R; Dalmasso, Marion; Blake, Tony; Ryan, C Anthony; Stanton, Catherine; Mills, Susan; Ross, Paul R; Hill, Colin

2018-01-01

Establishing a diverse gut microbiota after birth is being increasingly recognised as important for preventing illnesses later in life. It is well established that bacterial diversity rapidly increases post-partum; however, few studies have examined the infant gut virome/phageome during this developmental period. We performed a metagenomic analysis of 20 infant faecal viromes at one year of age to determine whether spontaneous vaginal delivery (SVD) or caesarean section (CS) influenced viral composition. We find that birth mode results in distinctly different viral communities, with SVD infants having greater viral and bacteriophage diversity. We demonstrate that CrAssphage is acquired early in life, both in this cohort and two others, although no difference in birth mode is detected. A previous study has shown that bacterial OTU's (operational taxonomic units) identified in the same infants could not discriminate between birth mode at 12 months of age. Therefore, our results indicate that vertical transmission of viral communities from mother to child may play a role in shaping the early life microbiome, and that birth mode should be considered when studying the early life gut virome.

Detection of the secondary meridional circulation associated with the quasi-biennial oscillation

NASA Astrophysics Data System (ADS)

Ribera, P.; PeñA-Ortiz, C.; Garcia-Herrera, R.; Gallego, D.; Gimeno, L.; HernáNdez, E.

2004-09-01

The quasi-biennial oscillation (QBO) signal in stratospheric zonal and meridional wind, temperature, and geopotential height fields is analyzed based on the use of the National Centers for Environmental Prediction (NCEP) reanalysis (1958-2001). The multitaper method-singular value decomposition (MTM-SVD), a multivariate frequency domain analysis method, is used to detect significant and spatially coherent narrowband oscillations. The QBO is found as the most intense signal in the stratospheric zonal wind. Then, the MTM-SVD method is used to determine the patterns induced by the QBO at every stratospheric level and data field. The secondary meridional circulation associated with the QBO is identified in the obtained patterns. This circulation can be characterized by negative (positive) temperature anomalies associated with adiabatic rising (sinking) motions over zones of easterly (westerly) wind shear and over the subtropics and midlatitudes, while meridional convergence and divergence levels are found separated by a level of maximum zonal wind shear. These vertical and meridional motions form quasi-symmetric circulation cells over both hemispheres, though less intense in the Southern Hemisphere.

Inverse Relationship between Coffee Consumption and Cerebral Microbleeds in Men, but Not Women.

PubMed

Shinoda, Masaki; Fujii, Motoharu; Takahashi, Osamu; Kawatsu, Akiko; Uemura, Akihiro; Niimi, Yasunari

2015-10-01

Studies evaluating the association between coffee consumption and neurovascular diseases have frequently yielded contradictory results. The aim of this study was to investigate the association of coffee consumption with small-vessel disease (SVD) incidence in a healthy urban population while accounting for multiple demographic and lifestyle risk factors. This prospective study conducted from May 2013 through March 2014 included 455 participants (314 men and 141 women) aged 25 to 92 years. All subjects completed a questionnaire on coffee consumption and received a comprehensive neurologic examination, including magnetic resonance imaging, at St. Luke's International Hospital (Tokyo, Japan). Incidence of SVD was lower in male daily coffee drinkers than male nondrinkers and occasional drinkers, whereas incidence of white matter lesions was lower in female daily coffee drinkers than female nondrinkers or occasional drinkers. In multivariate analyses including age, sex, smoking status, and BMI, as well as coffee consumption, incidence of microbleeds was significantly lower in male daily coffee drinkers compared to nondrinkers. Daily coffee consumption is associated with reduced risk of cerebral microbleeds in men. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Rong, Shenghui; Wang, Bingjian; Cheng, Kuanhong

2017-05-01

Infrared small target tracking plays an important role in applications including military reconnaissance, early warning and terminal guidance. In this paper, an effective algorithm based on the Singular Value Decomposition (SVD) and the improved Kernelized Correlation Filter (KCF) is presented for infrared small target tracking. Firstly, the super performance of the SVD-based algorithm is that it takes advantage of the target's global information and obtains a background estimation of an infrared image. A dim target is enhanced by subtracting the corresponding estimated background with update from the original image. Secondly, the KCF algorithm is combined with Gaussian Curvature Filter (GCF) to eliminate the excursion problem. The GCF technology is adopted to preserve the edge and eliminate the noise of the base sample in the KCF algorithm, helping to calculate the classifier parameter for a small target. At last, the target position is estimated with a response map, which is obtained via the kernelized classifier. Experimental results demonstrate that the presented algorithm performs favorably in terms of efficiency and accuracy, compared with several state-of-the-art algorithms.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958

Matched field localization based on CS-MUSIC algorithm

NASA Astrophysics Data System (ADS)

Guo, Shuangle; Tang, Ruichun; Peng, Linhui; Ji, Xiaopeng

2016-04-01

The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered. A matched field localization algorithm based on CS-MUSIC (Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning. The signal matrix is calculated through the SVD (Singular Value Decomposition) of the observation matrix. The observation matrix in the sparse mathematical model is replaced by the signal matrix, and a new concise sparse mathematical model is obtained, which means not only the scale of the localization problem but also the noise level is reduced; then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS (Compressive Sensing) method and MUSIC (Multiple Signal Classification) method. The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots, and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large, which will be proved in this paper.

Distinguishing autofluorescence of normal, benign, and cancerous breast tissues through wavelet domain correlation studies.

PubMed

Gharekhan, Anita H; Arora, Siddharth; Oza, Ashok N; Sureshkumar, Mundan B; Pradhan, Asima; Panigrahi, Prasanta K

2011-08-01

Using the multiresolution ability of wavelets and effectiveness of singular value decomposition (SVD) to identify statistically robust parameters, we find a number of local and global features, capturing spectral correlations in the co- and cross-polarized channels, at different scales (of human breast tissues). The copolarized component, being sensitive to intrinsic fluorescence, shows different behavior for normal, benign, and cancerous tissues, in the emission domain of known fluorophores, whereas the perpendicular component, being more prone to the diffusive effect of scattering, points out differences in the Kernel-Smoother density estimate employed to the principal components, between malignant, normal, and benign tissues. The eigenvectors, corresponding to the dominant eigenvalues of the correlation matrix in SVD, also exhibit significant differences between the three tissue types, which clearly reflects the differences in the spectral correlation behavior. Interestingly, the most significant distinguishing feature manifests in the perpendicular component, corresponding to porphyrin emission range in the cancerous tissue. The fact that perpendicular component is strongly influenced by depolarization, and porphyrin emissions in cancerous tissue has been found to be strongly depolarized, may be the possible cause of the above observation.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

White matter hyperintensity patterns in cerebral amyloid angiopathy and hypertensive arteriopathy.

PubMed

Charidimou, Andreas; Boulouis, Gregoire; Haley, Kellen; Auriel, Eitan; van Etten, Ellis S; Fotiadis, Panagiotis; Reijmer, Yael; Ayres, Alison; Vashkevich, Anastasia; Dipucchio, Zora Y; Schwab, Kristin M; Martinez-Ramirez, Sergi; Rosand, Jonathan; Viswanathan, Anand; Greenberg, Steven M; Gurol, M Edip

2016-02-09

To identify different white matter hyperintensity (WMH) patterns between 2 hemorrhage-prone cerebral small vessel diseases (SVD): cerebral amyloid angiopathy (CAA) and hypertensive arteriopathy (HA). Consecutive patients with SVD-related intracerebral hemorrhage (ICH) from a single-center prospective cohort were analyzed. Four predefined subcortical WMH patterns were compared between the CAA and HA groups. These WMH patterns were (1) multiple subcortical spots; (2) peri-basal ganglia (BG); (3) large posterior subcortical patches; and (4) anterior subcortical patches. Their associations with other imaging (cerebral microbleeds [CMBs], enlarged perivascular spaces [EPVS]) and clinical markers of SVD were investigated using multivariable logistic regression. The cohort included 319 patients with CAA and 137 patients with HA. Multiple subcortical spots prevalence was higher in the CAA compared to the HA group (29.8% vs 16.8%; p = 0.004). Peri-BG WMH pattern was more common in the HA- vs the CAA-ICH group (19% vs 7.8%; p = 0.001). In multivariable logistic regression, presence of multiple subcortical spots was associated with lobar CMBs (odds ratio [OR] 1.23; 95% confidence interval [CI] 1.01-1.50, p = 0.039) and high degree of centrum semiovale EPVS (OR 2.43; 95% CI 1.56-3.80, p < 0.0001). By contrast, age (OR 1.05; 95% CI 1.02-1.09, p = 0.002), deep CMBs (OR 2.46; 95% CI 1.44-4.20, p = 0.001), total WMH volume (OR 1.02; 95% CI 1.01-1.04, p = 0.002), and high BG EPVS degree (OR 8.81; 95% CI 3.37-23.02, p < 0.0001) were predictors of peri-BG WMH pattern. Different patterns of subcortical leukoaraiosis visually identified on MRI might provide insights into the dominant underlying microangiopathy type as well as mechanisms of tissue injury in patients with ICH. © 2016 American Academy of Neurology.

Coronary Angiography Findings and Its Determinants in Patients Presenting With Acute Coronary Syndrome: A Descriptive Analysis from Asian Population.

PubMed

Chourasiya, M; Satheesh, S; Selvaraj, R; Jayaraman, B; Pillai, A A

2017-10-01

The aim was to study the angiographic profile in patients presented as acute coronary syndrome and its relation with risk factors and comparison between genders. This prospective observational study was performed on total 352 patients of acute coronary syndrome were analyzed for various risk factors, angiographic pattern in Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, South India from January 2015 to July 2016. Mean age of presentation was 52.62±11.63 years. Male were 271(77.0%) and female were 81(23.0%). Majority of patients were STEMI (67.6%) followed by UA (24.4%) and NSTEMI (8%). Smoker was 117(33.3%) patients. Hypertensive were 124(35.2%) of patients and 149(42.3%) were diabetics. Family history of CAD was positive in 45(12.8%). On angiographic evaluation left main reference diameter was lower in females (4.02±0.72) than males (4.07±0.82). LAD was most commonly involved followed by RCA and LCX among all three group of acute coronary syndrome. Left main was least involved (8.3%). In STEMI SVD (40.3%) was most common presentation, after that DVD was seen in 22.3%, TVD in 10.5%, non-obstructive coronary was seen in 16% of patients and normal coronary was seen in 11% of patients. In UA 28%, 22.8%, 13.2%, 15.8%, 20.2% was seen in SVD, DVD, TVD, non-obstructive and normal coronary respectively. Long length coronary lesions (>20mm) were seen in majority in all type of acute coronary syndrome. Coronary lesion length was not associated with presentation acute coronary syndrome and genders. Male were most commonly presented as acute coronary syndrome. STEMI was most common presentation. Diabetic was most prevalent risk factor. SVD was most common angiographic pattern and LAD was most common involved arteries.

Susceptibility-weighted imaging using inter-echo-variance channel combination for improved contrast at 7 tesla.

PubMed

Hosseini, Zahra; Liu, Junmin; Solovey, Igor; Menon, Ravi S; Drangova, Maria

2017-04-01

To implement and optimize a new approach for susceptibility-weighted image (SWI) generation from multi-echo multi-channel image data and compare its performance against optimized traditional SWI pipelines. Five healthy volunteers were imaged at 7 Tesla. The inter-echo-variance (IEV) channel combination, which uses the variance of the local frequency shift at multiple echo times as a weighting factor during channel combination, was used to calculate multi-echo local phase shift maps. Linear phase masks were combined with the magnitude to generate IEV-SWI. The performance of the IEV-SWI pipeline was compared with that of two accepted SWI pipelines-channel combination followed by (i) Homodyne filtering (HPH-SWI) and (ii) unwrapping and high-pass filtering (SVD-SWI). The filtering steps of each pipeline were optimized. Contrast-to-noise ratio was used as the comparison metric. Qualitative assessment of artifact and vessel conspicuity was performed and processing time of pipelines was evaluated. The optimized IEV-SWI pipeline (σ = 7 mm) resulted in continuous vessel visibility throughout the brain. IEV-SWI had significantly higher contrast compared with HPH-SWI and SVD-SWI (P < 0.001, Friedman nonparametric test). Residual background fields and phase wraps in HPH-SWI and SVD-SWI corrupted the vessel signal and/or generated vessel-mimicking artifact. Optimized implementation of the IEV-SWI pipeline processed a six-echo 16-channel dataset in under 10 min. IEV-SWI benefits from channel-by-channel processing of phase data and results in high contrast images with an optimal balance between contrast and background noise removal, thereby presenting evidence of importance of the order in which postprocessing techniques are applied for multi-channel SWI generation. 2 J. Magn. Reson. Imaging 2017;45:1113-1124. © 2016 International Society for Magnetic Resonance in Medicine.

Extracting time-frequency feature of single-channel vastus medialis EMG signals for knee exercise pattern recognition.

PubMed

Zhang, Yi; Li, Peiyang; Zhu, Xuyang; Su, Steven W; Guo, Qing; Xu, Peng; Yao, Dezhong

2017-01-01

The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exercises, i.e., flexion of the leg up (standing), hip extension from a sitting position (sitting) and gait (walking) are investigated from 14 healthy untrained subjects, while EMG signals from the muscle group of vastus medialis and the goniometer on the knee joint of the detected leg are synchronously monitored and recorded. Four types of lower-limb motions including standing, sitting, stance phase of walking, and swing phase of walking, are segmented. The Wavelet Transform (WT) based Singular Value Decomposition (SVD) approach is proposed for the classification of four lower-limb motions using a single-channel EMG signal from the muscle group of vastus medialis. Based on lower-limb motions from all subjects, the combination of five-level wavelet decomposition and SVD is used to comprise the feature vector. The Support Vector Machine (SVM) is then configured to build a multiple-subject classifier for which the subject independent accuracy will be given across all subjects for the classification of four types of lower-limb motions. In order to effectively indicate the classification performance, EMG features from time-domain (e.g., Mean Absolute Value (MAV), Root-Mean-Square (RMS), integrated EMG (iEMG), Zero Crossing (ZC)) and frequency-domain (e.g., Mean Frequency (MNF) and Median Frequency (MDF)) are also used to classify lower-limb motions. The five-fold cross validation is performed and it repeats fifty times in order to acquire the robust subject independent accuracy. Results show that the proposed WT-based SVD approach has the classification accuracy of 91.85%±0.88% which outperforms other feature models.

The Mosaic bioprosthesis in the aortic position: 17 years' results.

PubMed

Gansera, Brigitte; Hapfelmeier, Alexander; Brandl, Kristina; Spiliopoulos, Kyriakos; Gundling, Felix; Eichinger, Walter

2014-02-01

The Mosaic bioprosthesis (Medtronic Inc., Minneapolis, Minnesota, United States), a stented porcine aortic valve, combines glutaraldehyde fixation with zero-pressure, root-pressure techniques and antimineralization treatment with amino-oleic acid for improved hemodynamics and tissue durability. The first device has been implanted worldwide at the authors' institution in September 1993. The aim of the present study was to collect mid- to long-term data of the prosthesis. A total of 272 patients (124 males and 148 females) underwent isolated aortic valve replacement with the Mosaic bioprosthesis between September 1993 and August 2007. Median age at implant was 76.8 years (range, 31.3 to 90.7). Median follow-up was 12.0 years (range, 0 to 17.2 years); follow-up was complete for 223 (82%) patients. Early mortality (30 days) was 4% (12 patients). Overall survival at 5, 10, 15, and 17 years was 68.6% ± 3.1%, 36.4% ± 3.3%, 17.1% ± 3.6%, and 10.7% ± 4.3%, respectively. Eleven late deaths (5%) were cardiac related. There were 24 thromboembolic events, 1 hemorrhagic, and 6 reoperations/explants. At a median follow-up of 12 years, freedom from any cause of death was 27.0% ± 3.2% acting as a competing risk for the incidence of thromboembolic events (16.4% ± 3.5%), hemorrhage (0.5% ± 0.5%), and reoperation/explant (4.1% ± 1.8%). Two redos were due to structural valve deterioration (SVD), two for nonstructural dysfunction (paravalvular leakage), one for thrombosed prosthesis, and one for endocarditis. Performance and late outcome of the Mosaic bioprosthesis was satisfactory during 17 years after clinical introduction. The Mosaic bioprosthesis showed low incidence of SVD or need for reoperation in the long term. Georg Thieme Verlag KG Stuttgart · New York.

A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-01-01

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method. PMID:24573313

A tensor-based subspace approach for bistatic MIMO radar in spatial colored noise.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Wang, Junxiang

2014-02-25

In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method.

Sampling considerations for modal analysis with damping

NASA Astrophysics Data System (ADS)

Park, Jae Young; Wakin, Michael B.; Gilbert, Anna C.

2015-03-01

Structural health monitoring (SHM) systems are critical for monitoring aging infrastructure (such as buildings or bridges) in a cost-effective manner. Wireless sensor networks that sample vibration data over time are particularly appealing for SHM applications due to their flexibility and low cost. However, in order to extend the battery life of wireless sensor nodes, it is essential to minimize the amount of vibration data these sensors must collect and transmit. In recent work, we have studied the performance of the Singular Value Decomposition (SVD) applied to the collection of data and provided new finite sample analysis characterizing conditions under which this simple technique{also known as the Proper Orthogonal Decomposition (POD){can correctly estimate the mode shapes of the structure. Specifically, we provided theoretical guarantees on the number and duration of samples required in order to estimate a structure's mode shapes to a desired level of accuracy. In that previous work, however, we considered simplified Multiple-Degree-Of-Freedom (MDOF) systems with no damping. In this paper we consider MDOF systems with proportional damping and show that, with sufficiently light damping, the POD can continue to provide accurate estimates of a structure's mode shapes. We support our discussion with new analytical insight and experimental demonstrations. In particular, we study the tradeoffs between the level of damping, the sampling rate and duration, and the accuracy to which the structure's mode shapes can be estimated.

Readout, first- and second-level triggers of the new Belle silicon vertex detector

NASA Astrophysics Data System (ADS)

Friedl, M.; Abe, R.; Abe, T.; Aihara, H.; Asano, Y.; Aso, T.; Bakich, A.; Browder, T.; Chang, M. C.; Chao, Y.; Chen, K. F.; Chidzik, S.; Dalseno, J.; Dowd, R.; Dragic, J.; Everton, C. W.; Fernholz, R.; Fujii, H.; Gao, Z. W.; Gordon, A.; Guo, Y. N.; Haba, J.; Hara, K.; Hara, T.; Harada, Y.; Haruyama, T.; Hasuko, K.; Hayashi, K.; Hazumi, M.; Heenan, E. M.; Higuchi, T.; Hirai, H.; Hitomi, N.; Igarashi, A.; Igarashi, Y.; Ikeda, H.; Ishino, H.; Itoh, K.; Iwaida, S.; Kaneko, J.; Kapusta, P.; Karawatzki, R.; Kasami, K.; Kawai, H.; Kawasaki, T.; Kibayashi, A.; Koike, S.; Korpar, S.; Križan, P.; Kurashiro, H.; Kusaka, A.; Lesiak, T.; Limosani, A.; Lin, W. C.; Marlow, D.; Matsumoto, H.; Mikami, Y.; Miyake, H.; Moloney, G. R.; Mori, T.; Nakadaira, T.; Nakano, Y.; Natkaniec, Z.; Nozaki, S.; Ohkubo, R.; Ohno, F.; Okuno, S.; Onuki, Y.; Ostrowicz, W.; Ozaki, H.; Peak, L.; Pernicka, M.; Rosen, M.; Rozanska, M.; Sato, N.; Schmid, S.; Shibata, T.; Stamen, R.; Stanič, S.; Steininger, H.; Sumisawa, K.; Suzuki, J.; Tajima, H.; Tajima, O.; Takahashi, K.; Takasaki, F.; Tamura, N.; Tanaka, M.; Taylor, G. N.; Terazaki, H.; Tomura, T.; Trabelsi, K.; Trischuk, W.; Tsuboyama, T.; Uchida, K.; Ueno, K.; Ueno, K.; Uozaki, N.; Ushiroda, Y.; Vahsen, S.; Varner, G.; Varvell, K.; Velikzhanin, Y. S.; Wang, C. C.; Wang, M. Z.; Watanabe, M.; Watanabe, Y.; Yamada, Y.; Yamamoto, H.; Yamashita, Y.; Yamashita, Y.; Yamauchi, M.; Yanai, H.; Yang, R.; Yasu, Y.; Yokoyama, M.; Ziegler, T.; Žontar, D.

2004-12-01

A major upgrade of the Silicon Vertex Detector (SVD 2.0) of the Belle experiment at the KEKB factory was installed along with new front-end and back-end electronics systems during the summer shutdown period in 2003 to cope with higher particle rates, improve the track resolution and meet the increasing requirements of radiation tolerance. The SVD 2.0 detector modules are read out by VA1TA chips which provide "fast or" (hit) signals that are combined by the back-end FADCTF modules to coarse, but immediate level 0 track trigger signals at rates of several tens of a kHz. Moreover, the digitized detector signals are compared to threshold lookup tables in the FADCTFs to pass on hit information on a single strip basis to the subsequent level 1.5 trigger system, which reduces the rate below the kHz range. Both FADCTF and level 1.5 electronics make use of parallel real-time processing in Field Programmable Gate Arrays (FPGAs), while further data acquisition and event building is done by PC farms running Linux. The new readout system hardware is described and the first results obtained with cosmics are shown.

Spherical Harmonic Analysis of Particle Velocity Distribution Function: Comparison of Moments and Anisotropies using Cluster Data

NASA Technical Reports Server (NTRS)

Gurgiolo, Chris; Vinas, Adolfo F.

2009-01-01

This paper presents a spherical harmonic analysis of the plasma velocity distribution function using high-angular, energy, and time resolution Cluster data obtained from the PEACE spectrometer instrument to demonstrate how this analysis models the particle distribution function and its moments and anisotropies. The results show that spherical harmonic analysis produced a robust physical representation model of the velocity distribution function, resolving the main features of the measured distributions. From the spherical harmonic analysis, a minimum set of nine spectral coefficients was obtained from which the moment (up to the heat flux), anisotropy, and asymmetry calculations of the velocity distribution function were obtained. The spherical harmonic method provides a potentially effective "compression" technique that can be easily carried out onboard a spacecraft to determine the moments and anisotropies of the particle velocity distribution function for any species. These calculations were implemented using three different approaches, namely, the standard traditional integration, the spherical harmonic (SPH) spectral coefficients integration, and the singular value decomposition (SVD) on the spherical harmonic methods. A comparison among the various methods shows that both SPH and SVD approaches provide remarkable agreement with the standard moment integration method.

A Modified Sparse Representation Method for Facial Expression Recognition.

PubMed

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result.

Crystal Identification in Dual-Layer-Offset DOI-PET Detectors Using Stratified Peak Tracking Based on SVD and Mean-Shift Algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Dai, Tiantian; Ma, Tianyu; Liu, Yaqiang; Gu, Yu

2016-10-01

An Anger-logic based pixelated PET detector block requires a crystal position map (CPM) to assign the position of each detected event to a most probable crystal index. Accurate assignments are crucial to PET imaging performance. In this paper, we present a novel automatic approach to generate the CPMs for dual-layer offset (DLO) PET detectors using a stratified peak tracking method. In which, the top and bottom layers are distinguished by their intensity difference and the peaks of the top and bottom layers are tracked based on a singular value decomposition (SVD) and mean-shift algorithm in succession. The CPM is created by classifying each pixel to its nearest peak and assigning the pixel with the crystal index of that peak. A Matlab-based graphical user interface program was developed including the automatic algorithm and a manual interaction procedure. The algorithm was tested for three DLO PET detector blocks. Results show that the proposed method exhibits good performance as well as robustness for all the three blocks. Compared to the existing methods, our approach can directly distinguish the layer and crystal indices using the information of intensity and offset grid pattern.

HGVS Recommendations for the Description of Sequence Variants: 2016 Update.

PubMed

den Dunnen, Johan T; Dalgleish, Raymond; Maglott, Donna R; Hart, Reece K; Greenblatt, Marc S; McGowan-Jordan, Jean; Roux, Anne-Francoise; Smith, Timothy; Antonarakis, Stylianos E; Taschner, Peter E M

2016-06-01

The consistent and unambiguous description of sequence variants is essential to report and exchange information on the analysis of a genome. In particular, DNA diagnostics critically depends on accurate and standardized description and sharing of the variants detected. The sequence variant nomenclature system proposed in 2000 by the Human Genome Variation Society has been widely adopted and has developed into an internationally accepted standard. The recommendations are currently commissioned through a Sequence Variant Description Working Group (SVD-WG) operating under the auspices of three international organizations: the Human Genome Variation Society (HGVS), the Human Variome Project (HVP), and the Human Genome Organization (HUGO). Requests for modifications and extensions go through the SVD-WG following a standard procedure including a community consultation step. Version numbers are assigned to the nomenclature system to allow users to specify the version used in their variant descriptions. Here, we present the current recommendations, HGVS version 15.11, and briefly summarize the changes that were made since the 2000 publication. Most focus has been on removing inconsistencies and tightening definitions allowing automatic data processing. An extensive version of the recommendations is available online, at http://www.HGVS.org/varnomen. © 2016 WILEY PERIODICALS, INC.

Speckle Noise Reduction in Optical Coherence Tomography Using Two-dimensional Curvelet-based Dictionary Learning.

PubMed

Esmaeili, Mahdad; Dehnavi, Alireza Mehri; Rabbani, Hossein; Hajizadeh, Fedra

2017-01-01

The process of interpretation of high-speed optical coherence tomography (OCT) images is restricted due to the large speckle noise. To address this problem, this paper proposes a new method using two-dimensional (2D) curvelet-based K-SVD algorithm for speckle noise reduction and contrast enhancement of intra-retinal layers of 2D spectral-domain OCT images. For this purpose, we take curvelet transform of the noisy image. In the next step, noisy sub-bands of different scales and rotations are separately thresholded with an adaptive data-driven thresholding method, then, each thresholded sub-band is denoised based on K-SVD dictionary learning with a variable size initial dictionary dependent on the size of curvelet coefficients' matrix in each sub-band. We also modify each coefficient matrix to enhance intra-retinal layers, with noise suppression at the same time. We demonstrate the ability of the proposed algorithm in speckle noise reduction of 100 publically available OCT B-scans with and without non-neovascular age-related macular degeneration (AMD), and improvement of contrast-to-noise ratio from 1.27 to 5.12 and mean-to-standard deviation ratio from 3.20 to 14.41 are obtained.

The comparison between SVD-DCT and SVD-DWT digital image watermarking

NASA Astrophysics Data System (ADS)

Wira Handito, Kurniawan; Fauzi, Zulfikar; Aminy Ma’ruf, Firda; Widyaningrum, Tanti; Muslim Lhaksmana, Kemas

2018-03-01

With internet, anyone can publish their creation into digital data simply, inexpensively, and absolutely easy to be accessed by everyone. However, the problem appears when anyone else claims that the creation is their property or modifies some part of that creation. It causes necessary protection of copyrights; one of the examples is with watermarking method in digital image. The application of watermarking technique on digital data, especially on image, enables total invisibility if inserted in carrier image. Carrier image will not undergo any decrease of quality and also the inserted image will not be affected by attack. In this paper, watermarking will be implemented on digital image using Singular Value Decomposition based on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) by expectation in good performance of watermarking result. In this case, trade-off happen between invisibility and robustness of image watermarking. In embedding process, image watermarking has a good quality for scaling factor < 0.1. The quality of image watermarking in decomposition level 3 is better than level 2 and level 1. Embedding watermark in low-frequency is robust to Gaussian blur attack, rescale, and JPEG compression, but in high-frequency is robust to Gaussian noise.

Background recovery via motion-based robust principal component analysis with matrix factorization

NASA Astrophysics Data System (ADS)

Pan, Peng; Wang, Yongli; Zhou, Mingyuan; Sun, Zhipeng; He, Guoping

2018-03-01

Background recovery is a key technique in video analysis, but it still suffers from many challenges, such as camouflage, lighting changes, and diverse types of image noise. Robust principal component analysis (RPCA), which aims to recover a low-rank matrix and a sparse matrix, is a general framework for background recovery. The nuclear norm is widely used as a convex surrogate for the rank function in RPCA, which requires computing the singular value decomposition (SVD), a task that is increasingly costly as matrix sizes and ranks increase. However, matrix factorization greatly reduces the dimension of the matrix for which the SVD must be computed. Motion information has been shown to improve low-rank matrix recovery in RPCA, but this method still finds it difficult to handle original video data sets because of its batch-mode formulation and implementation. Hence, in this paper, we propose a motion-assisted RPCA model with matrix factorization (FM-RPCA) for background recovery. Moreover, an efficient linear alternating direction method of multipliers with a matrix factorization (FL-ADM) algorithm is designed for solving the proposed FM-RPCA model. Experimental results illustrate that the method provides stable results and is more efficient than the current state-of-the-art algorithms.

Rapid perfusion quantification using Welch-Satterthwaite approximation and analytical spectral filtering

NASA Astrophysics Data System (ADS)

Krishnan, Karthik; Reddy, Kasireddy V.; Ajani, Bhavya; Yalavarthy, Phaneendra K.

2017-02-01

CT and MR perfusion weighted imaging (PWI) enable quantification of perfusion parameters in stroke studies. These parameters are calculated from the residual impulse response function (IRF) based on a physiological model for tissue perfusion. The standard approach for estimating the IRF is deconvolution using oscillatory-limited singular value decomposition (oSVD) or Frequency Domain Deconvolution (FDD). FDD is widely recognized as the fastest approach currently available for deconvolution of CT Perfusion/MR PWI. In this work, three faster methods are proposed. The first is a direct (model based) crude approximation to the final perfusion quantities (Blood flow, Blood volume, Mean Transit Time and Delay) using the Welch-Satterthwaite approximation for gamma fitted concentration time curves (CTC). The second method is a fast accurate deconvolution method, we call Analytical Fourier Filtering (AFF). The third is another fast accurate deconvolution technique using Showalter's method, we call Analytical Showalter's Spectral Filtering (ASSF). Through systematic evaluation on phantom and clinical data, the proposed methods are shown to be computationally more than twice as fast as FDD. The two deconvolution based methods, AFF and ASSF, are also shown to be quantitatively accurate compared to FDD and oSVD.

Joint Smoothed l₀-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar.

PubMed

Liu, Jing; Zhou, Weidong; Juwono, Filbert H

2017-05-08

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l 0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l 0 -norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l 1 -norm minimization based methods, such as l 1 -SVD (singular value decomposition), RV (real-valued) l 1 -SVD and RV l 1 -SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.

A Modified Sparse Representation Method for Facial Expression Recognition

PubMed Central

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result. PMID:26880878

Intelligibility Evaluation of Pathological Speech through Multigranularity Feature Extraction and Optimization.

PubMed

Fang, Chunying; Li, Haifeng; Ma, Lin; Zhang, Mancai

2017-01-01

Pathological speech usually refers to speech distortion resulting from illness or other biological insults. The assessment of pathological speech plays an important role in assisting the experts, while automatic evaluation of speech intelligibility is difficult because it is usually nonstationary and mutational. In this paper, we carry out an independent innovation of feature extraction and reduction, and we describe a multigranularity combined feature scheme which is optimized by the hierarchical visual method. A novel method of generating feature set based on S -transform and chaotic analysis is proposed. There are BAFS (430, basic acoustics feature), local spectral characteristics MSCC (84, Mel S -transform cepstrum coefficients), and chaotic features (12). Finally, radar chart and F -score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96 dimensions based on NKI-CCRT corpus and 104 dimensions based on SVD corpus. The experimental results denote that new features by support vector machine (SVM) have the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus and 78.7% on SVD corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.

Sparse representations via learned dictionaries for x-ray angiogram image denoising

NASA Astrophysics Data System (ADS)

Shang, Jingfan; Huang, Zhenghua; Li, Qian; Zhang, Tianxu

2018-03-01

X-ray angiogram image denoising is always an active research topic in the field of computer vision. In particular, the denoising performance of many existing methods had been greatly improved by the widely use of nonlocal similar patches. However, the only nonlocal self-similar (NSS) patch-based methods can be still be improved and extended. In this paper, we propose an image denoising model based on the sparsity of the NSS patches to obtain high denoising performance and high-quality image. In order to represent the sparsely NSS patches in every location of the image well and solve the image denoising model more efficiently, we obtain dictionaries as a global image prior by the K-SVD algorithm over the processing image; Then the single and effectively alternating directions method of multipliers (ADMM) method is used to solve the image denoising model. The results of widely synthetic experiments demonstrate that, owing to learned dictionaries by K-SVD algorithm, a sparsely augmented lagrangian image denoising (SALID) model, which perform effectively, obtains a state-of-the-art denoising performance and better high-quality images. Moreover, we also give some denoising results of clinical X-ray angiogram images.

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.

The spectrum of aphasia subtypes and etiology in subacute stroke.

PubMed

Hoffmann, Michael; Chen, Ren

2013-11-01

Aphasia is one of the most common stroke syndrome presentations, yet little is known about the spectrum of different subtypes or their stroke mechanisms. Yet, subtypes and etiology are known to influence the prognosis and recovery. Our aim is to analyze aphasia subtypes and etiology in a large subacute stroke population. Consecutive patients from a dedicated cognitive stroke registry were accrued. A validated cognitive screening examination was administered during the first month of stroke presentation, which enabled a diagnosis of 14 different aphasic subtypes. The evolution from one subtype to another in the acute and subacute period, at times, resulted in more than 1 subtype being diagnosed. Etiology of stroke was determined by the modified Trial of Org 10172 in Acute Stroke Treatment criteria that included intracerebral hemorrhage. Exclusions included dementia, chronic medical illness, substance abuse, and severe depression. Of 2389 stroke patients, after exclusions (n=593), aphasias numbered 625 (625 of 1796; 34.8%), and the subtype frequencies included Broca aphasia (n=170; 27.2%), anomic aphasia (n=165; 26.4%), global aphasia (n=119; 19.04%), and subcortical aphasia (n=57; 9.12%). Less frequent subtypes (total n=40; 6.7%) included transcortical aphasia (n=11), Wernicke aphasia (n=10), conduction aphasia (n=7), aphemia (n=3), semantic aphasia (n=3), crossed aphasia (n=3), pure word deafness (n=2), and foreign accent syndrome (n=1). Aphasia subtypes and etiologies had some significant associations (chi-square: 855.8, P value<.0001). Bonferroni-adjusted P values revealed that anomic aphasia had a significant association with small-vessel disease (SVD) (odds ratio [OR]=2.0254, 95% confidence interval [CI]: 1.3820-2.9681), and global aphasia patients mostly had cardioembolic (CE) causes (OR=2.3589, 95% CI: 1.5506-3.5885) and less likely SVD (OR=.2583, 95% CI: .1444-.4654). Other notable inferences were included. Wernicke aphasia was caused by either CE (6 of 12; 50%) or hemorrhage (4 of 12; 33.3%) in a combined 83% of cases. Subcortical aphasia was because of SVD in 36% (31 of 85) or because of hemorrhage in 32% (27 of 85) yielding a combined 68% of cases. Sixty percent of transcortical aphasias as a group were because of either large-vessel disease (7 of 20; 35%) or hemorrhage (5 of 20; 25%). Alternatively, a diagnosis of Broca aphasia could be because of any of the etiological categories. (1) Aphasias are a heterogeneous entity in subtype and etiology; (2) Broca, global, anomic, and subcortical aphasias accounted for the vast majority of aphasia subtypes; (3) SVD, cardioembolism, and hemorrhage are significantly associated with certain signature aphasic syndromes; and (4) determination of aphasia subtype can assist with etiology, prognosis, influence aphasia therapy, and provide the basis for future randomized controlled trials with pharmacological therapy or behavioral therapy. Copyright © 2013 National Stroke Association. Published by Elsevier Inc. All rights reserved.

76 FR 15211 - Changes in Disease Status of the Brazilian State of Santa Catarina With Regard to Certain...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-21

..., introductory text, and Sec. 94.25, paragraph (a), to add Santa Catarina to those lists. USDA's Food Safety and... import restrictions on pork and pork products because of their proximity to or trading relationships with... regions. Because we have not declared the rest of Brazil to be free of SVD or CSF, the importation of pork...

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.

Implementation of the RCOG guidelines for prevention of obstetric anal sphincter injuries (OASIS) at two London Hospitals: A time series analysis.

PubMed

Mohiudin, Henna; Ali, Sajjad; Pisal, Pradyna N; Villar, Rose

2018-05-01

To audit the impact of implementation of the RCOG guidelines for prevention of Obstetric anal sphincter injuries (OASIS) by introducing antenatal perineal massage, manual perineal protection, and cutting episiotomies at 60° to the midline at the time of crowning. Time series analysis; Setting - Two London teaching hospitals; Royal Free London (RFL) and Barnet; Population or Sample - All nulliparous women undergoing vaginal birth; Methods - Training was provided for above techniques. EPISCISSORS-60 were introduced to perform 60° episiotomies. Data were extracted from maternity databases and dashboards; Main Outcome Measures - OASIS rates before and after implementation. Data from 2566 births were analysed. In operative vaginal deliveries (OVD), OASIS declined from 9.6% to 2% (p = 0.001) at Barnet and from 5.6% to 4.2% (p = 0.4) at RFL. OASIS reduced in nulliparous OVD's given episiotomies from 6.3% in the 'before' period to 0.6% in the 'after' period [p = 0.01] at Barnet. Before introduction of the EPISCISSORS-60, OASIS rate was 6.3% with episiotomies and 30% without episiotomies (p = 0.000). After introduction of the EPISCISSORS-60, OASIS rate was 0.63% with episiotomies v 16% without episiotomies (p = 0.000) at Barnet. At RFL, OASIS rate was 2.6% with episiotomies, and 42% without episiotomy (p = 0.000). In SVD's at Barnet, OASIS declined from 6.6% before to 0% after (p = 0.000) in women given episiotomies while it declined from 5.4% to 3% (p = 0.12) in those not given episiotomies. After introduction of the EPISCISSORS-60, OASIS was 0% in women with episiotomies and 3% in those without episiotomies (p = 0.04). In SVD's at RFL, OASIS was 0% in women given episiotomy v 4.7% without episiotomy (p = 0.03). Deliveries with EPISCISSORS-60 episiotomies had lesser OASIS than those without episiotomies in both nulliparous OVD's and SVD's. OASIS was lower with EPISCISSORS-60 episiotomies than those with eyeballed episiotomies. Copyright © 2018 Elsevier B.V. All rights reserved.

Cross-language information retrieval using PARAFAC2.

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

Bader, Brett William; Chew, Peter; Abdelali, Ahmed

A standard approach to cross-language information retrieval (CLIR) uses Latent Semantic Analysis (LSA) in conjunction with a multilingual parallel aligned corpus. This approach has been shown to be successful in identifying similar documents across languages - or more precisely, retrieving the most similar document in one language to a query in another language. However, the approach has severe drawbacks when applied to a related task, that of clustering documents 'language-independently', so that documents about similar topics end up closest to one another in the semantic space regardless of their language. The problem is that documents are generally more similar tomore » other documents in the same language than they are to documents in a different language, but on the same topic. As a result, when using multilingual LSA, documents will in practice cluster by language, not by topic. We propose a novel application of PARAFAC2 (which is a variant of PARAFAC, a multi-way generalization of the singular value decomposition [SVD]) to overcome this problem. Instead of forming a single multilingual term-by-document matrix which, under LSA, is subjected to SVD, we form an irregular three-way array, each slice of which is a separate term-by-document matrix for a single language in the parallel corpus. The goal is to compute an SVD for each language such that V (the matrix of right singular vectors) is the same across all languages. Effectively, PARAFAC2 imposes the constraint, not present in standard LSA, that the 'concepts' in all documents in the parallel corpus are the same regardless of language. Intuitively, this constraint makes sense, since the whole purpose of using a parallel corpus is that exactly the same concepts are expressed in the translations. We tested this approach by comparing the performance of PARAFAC2 with standard LSA in solving a particular CLIR problem. From our results, we conclude that PARAFAC2 offers a very promising alternative to LSA not only for multilingual document clustering, but also for solving other problems in cross-language information retrieval.« less

Correlation analysis between the LDL-C in serum and the onset of transient ischemic attack caused by CSVD.

PubMed

Chen, Yaqi; Hu, Mei; Gong, Hongying

2017-08-01

The aim of this study was to investigate the correlation between the low-density lipoprotein cholesterol (LDL-C) in serum and the onset of transient ischemic attack caused by cerebral small vascular disease (CSVD). Between September 2012 and September 2015, 249 patients who were diagnosed as CSVD were randomly enrolled in this study. According to MRI results, patients were divided into the patient and control groups. In the patient group, the patients were further subdivided into the white matter lesion (WML) group (n=86) and lacunar infarction (LI) group (n=53). Head MRI and/or CT were conducted on all the patients. This included T1 and T2 phases, diffusion weighted imaging (DWI) and fluid attenuated inversion recovery (FLAIR). Additionally, mini-mental status examination (MMSE) test and Montreal cognitive assessment (MoCA) test were carried out on all the patients. As a result, the age, total cholesterol (TC) level and low-density lipoprotein (LDL) levels in the patient group were higher than those in the control group (p<0.05). The MMSE and MoCA scores in the patient group were significantly lower than those in the control group (p<0.05). With all the risk factors being set as independent variables and small vessel disease (SVD) as the dependent variable, we performed the logistic regression analysis and correlation analysis for paired data, and found that the increase in LDL was correlated to the onset of SVD, OR=1,321. After adjustment of other risk factors, we enrolled the level of triglyceride (TG) into the multivariable analysis and obtained a statistically significant difference (p<0.05). In conclusion, LDL is a major risk factor affecting the onset of transient ischemic attack (TIA) induced by CSVD. Patients with hyperlipidemia should receive head MRI or CT examination to eliminate the probability of the existence of CSVD. To reduce the occurrence of adverse events in clinical practice, we can perform early intervention in SVD by decreasing the level of LDL, improving the endothelial function of small vessels and applying the anti-inflammation and nerve-protection methods.

Optimal Tikhonov Regularization in Finite-Frequency Tomography

NASA Astrophysics Data System (ADS)

Fang, Y.; Yao, Z.; Zhou, Y.

2017-12-01

The last decade has witnessed a progressive transition in seismic tomography from ray theory to finite-frequency theory which overcomes the resolution limit of the high-frequency approximation in ray theory. In addition to approximations in wave propagation physics, a main difference between ray-theoretical tomography and finite-frequency tomography is the sparseness of the associated sensitivity matrix. It is well known that seismic tomographic problems are ill-posed and regularizations such as damping and smoothing are often applied to analyze the tradeoff between data misfit and model uncertainty. The regularizations depend on the structure of the matrix as well as noise level of the data. Cross-validation has been used to constrain data uncertainties in body-wave finite-frequency inversions when measurements at multiple frequencies are available to invert for a common structure. In this study, we explore an optimal Tikhonov regularization in surface-wave phase-velocity tomography based on minimization of an empirical Bayes risk function using theoretical training datasets. We exploit the structure of the sensitivity matrix in the framework of singular value decomposition (SVD) which also allows for the calculation of complete resolution matrix. We compare the optimal Tikhonov regularization in finite-frequency tomography with traditional tradeo-off analysis using surface wave dispersion measurements from global as well as regional studies.

A panel of clinical and neuropathological features of cerebrovascular disease through the novel neuroimaging methods

PubMed Central

Alves, Gilberto Sousa; de Carvalho, Luiza de Amorim; Sudo, Felipe Kenji; Briand, Lucas; Laks, Jerson; Engelhardt, Eliasz

2017-01-01

ABSTRACT. The last decade has witnessed substantial progress in acquiring diagnostic biomarkers for the diagnostic workup of cerebrovascular disease (CVD). Advanced neuroimaging methods not only provide a strategic contribution for the differential diagnosis of vascular dementia (VaD) and vascular cognitive impairment (VCI), but also help elucidate the pathophysiological mechanisms ultimately leading to small vessel disease (SVD) throughout its course. Objective: In this review, the novel imaging methods, both structural and metabolic, were summarized and their impact on the diagnostic workup of age-related CVD was analysed. Methods: An electronic search between January 2010 and 2017 was carried out on PubMed/MEDLINE, Institute for Scientific Information Web of Knowledge and EMBASE. Results: The use of full functional multimodality in simultaneous Magnetic Resonance (MR)/Positron emission tomography (PET) may potentially improve the clinical characterization of VCI-VaD; for structural imaging, MRI at 3.0 T enables higher-resolution scanning with greater imaging matrices, thinner slices and more detail on the anatomical structure of vascular lesions. Conclusion: Although the importance of most of these techniques in the clinical setting has yet to be recognized, there is great expectancy in achieving earlier and more refined therapeutic interventions for the effective management of VCI-VaD. PMID:29354214

Simplex volume analysis for finding endmembers in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Li, Hsiao-Chi; Song, Meiping; Chang, Chein-I.

2015-05-01

Using maximal simplex volume as an optimal criterion for finding endmembers is a common approach and has been widely studied in the literature. Interestingly, very little work has been reported on how simplex volume is calculated. It turns out that the issue of calculating simplex volume is much more complicated and involved than what we may think. This paper investigates this issue from two different aspects, geometric structure and eigen-analysis. The geometric structure is derived from its simplex structure whose volume can be calculated by multiplying its base with its height. On the other hand, eigen-analysis takes advantage of the Cayley-Menger determinant to calculate the simplex volume. The major issue of this approach is that when the matrix is ill-rank where determinant is desired. To deal with this problem two methods are generally considered. One is to perform data dimensionality reduction to make the matrix to be of full rank. The drawback of this method is that the original volume has been shrunk and the found volume of a dimensionality-reduced simplex is not the real original simplex volume. Another is to use singular value decomposition (SVD) to find singular values for calculating simplex volume. The dilemma of this method is its instability in numerical calculations. This paper explores all of these three methods in simplex volume calculation. Experimental results show that geometric structure-based method yields the most reliable simplex volume.

Use of Oral Fluids for Detection of Virus and Antibodies in Pigs Infected with Swine Vesicular Disease Virus.

PubMed

Senthilkumaran, C; Bittner, H; Ambagala, A; Lung, O; Babiuk, S; Yang, M; Zimmerman, J; Giménez-Lirola, L G; Nfon, C

2017-12-01

The use of swine oral fluid (OF) for the detection of nucleic acids and antibodies is gaining significant popularity. Assays have been developed for this purpose for endemic and foreign animal diseases of swine. Here, we report the use of OF for the detection of virus and antibodies in pigs experimentally infected with swine vesicular disease virus (SVDV), a virus that causes a disease clinically indistinguishable from the economically devastating foot-and-mouth disease. Viral genome was detected in OF by real-time reverse transcription polymerase chain reaction (RRT-PCR) from 1 day post-infection (DPI) to 21 DPI. Virus isolation from OF was also successful at 1-5 DPI. An adapted competitive ELISA based on the monoclonal antibodies 5B7 detected antibodies to SVDV in OF starting at DPI 6. Additionally, using isotype-specific indirect ELISAs, SVDV-specific IgM and IgA were evaluated in OF. IgM response started at DPI 6, peaking at DPI 7 or 14 and declining sharply at DPI 21, while IgA response started at DPI 7, peaked at DPI 14 and remained high until the end of the experiment. These results confirm the potential use of OF for SVD surveillance using both established and partially validated assays in this study. © 2016 Her Majesty the Queen in Right of Canada.

Masterless Distributed Computing Over Mobile Devices

DTIC Science & Technology

2012-09-01

Matrix Computations,” Handbooks in OR & MS, vol. 3, pp. 247–321, 1990. [18] R. Barrett et al ., Templates for the Solution of Linear Systems: Building...the truncated SVD of a matrix. The algorithm used in this thesis was developed by Halko , Martinsson, and Tropp in their journal article, Finding...experiments,” dodbuzz.com, 2011 . [Online]. Available: http://www.dodbuzz.com/ 2011 /06/06/army-begins-mobile- phone-experiments/. [Accessed: 15-Feb

The International Conference on Vector and Parallel Computing (2nd)

DTIC Science & Technology

1989-01-17

Computation of the SVD of Bidiagonal Matrices" ...................................... 11 " Lattice QCD -As a Large Scale Scientific Computation...vectorizcd for the IBM 3090 Vector Facility. In addition, elapsed times " Lattice QCD -As a Large Scale Scientific have been reduced by using 3090...benchmarked Lattice QCD on a large number ofcompu- come from the wavefront solver routine. This was exten- ters: CrayX-MP and Cray 2 (vector

Studies on Radar Sensor Networks

DTIC Science & Technology

2007-08-08

scheme in which 2-D image was created via adding voltages with the appropriate time offset. Simulation results show that our DCT-based scheme works...using RSNs in terms of the probability of miss detection PMD and the root mean square error (RMSE). Simulation results showed that multi-target detection... Simulation results are presented to evaluate the feasibility and effectiveness of the proposed JMIC algorithm in a query surveillance region. 5 SVD-QR and

Context as the Building Blocks of Meaning: A Retrieval Model for the Semantic Representation of Words

DTIC Science & Technology

2003-04-01

8 Deconstructing the model’s output................................................................................ 9 Implications of the ideas...identified characters of a word are used as a probe to retrieve a word’s identity (its spelling and phonology ) from memory. In addition to the...document matrix has been reduced by the SVD. Deconstructing the model’s output Why do semantic relationships between words emerge from the model? Is the

Optimal Robust Matching of Engine Models to Test Data

DTIC Science & Technology

2009-02-28

Monte Carlo process 19 Figure 7: Flowchart of SVD Calculations 22 Figure 8: Schematic Diagram of NPSS Engine Model Components 24 Figure 9: PW2037...System Simulation ( NPSS ). NPSS is an object-oriented modeling environment widely used throughout industry and the USAF. With NPSS , the engine is...34 modifiers are available for adjusting the component representations. The scripting language in NPSS allowed for easy implementation of each solution

Eigen Spreading

DTIC Science & Technology

2008-02-27

between the PHY layer and for example a host PC computer . The PC wants to generate and receive a sequence of data packets. The PC may also want to send...the testbed is quite similar. Given the intense computational requirements of SVD and other matrix mode operations needed to support eigen spreading a...platform for real time operation. This task is probably the major challenge in the development of the testbed. All compute intensive tasks will be

Statistical Feature Extraction for Artifact Removal from Concurrent fMRI-EEG Recordings

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H.

2011-01-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphases are directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use a channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable by the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. PMID:22036675

Drought assessment using multi-sattelite remote sensing in Brazil

NASA Astrophysics Data System (ADS)

Rebello, V.; Getirana, A.; Rotunno Filho, O. C.; Lakshmi, V.

2016-12-01

In this study, we investigated long-term Terra-MODIS Normalized Difference Vegetation Index (NDVI) response to a recent drought period in Brazil's Southeast (SE) and Northeast (NE) regions between 2012 and 2015. An analysis of precipitation anomaly from 1979 to 2015 suggests a dry period over NE in 2012-2013 and SE in 2014-2015. Through EOF analysis it was possible to note that the first two modes account for 76% of variability and depict the vegetation seasonal cycle. Moreover, the time series of the respective modes show a deviation of NDVI in 2012 when both regions had negative precipitation anomaly. The other EOF modes show a negative trend from 2012 until 2015 mainly in northeastern Brazil in the semiarid region named Caatinga. In order to examine the influence of hydro-meterological variables on vegetation changes, the SVD technique was used to identify coupled patterns between NDVI and precipitation, soil moisture and evapotranspiration. SVD results showed that the highest correlations are achieved between NDVI and precipitation, 0.81 and 0.83, respectively in the first two modes. Although less correlated than precipitation, significant coupling between NDVI and evapotranspiration was found for the second and third modes, the correlation between their expanded coefficients was respectively 0.82 and 0.90.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN.

PubMed

Liu, Chang; Cheng, Gang; Chen, Xihui; Pang, Yusong

2018-05-11

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears.

Comment on “Two statistics for evaluating parameter identifiability and error reduction” by John Doherty and Randall J. Hunt

USGS Publications Warehouse

Hill, Mary C.

2010-01-01

Doherty and Hunt (2009) present important ideas for first-order-second moment sensitivity analysis, but five issues are discussed in this comment. First, considering the composite-scaled sensitivity (CSS) jointly with parameter correlation coefficients (PCC) in a CSS/PCC analysis addresses the difficulties with CSS mentioned in the introduction. Second, their new parameter identifiability statistic actually is likely to do a poor job of parameter identifiability in common situations. The statistic instead performs the very useful role of showing how model parameters are included in the estimated singular value decomposition (SVD) parameters. Its close relation to CSS is shown. Third, the idea from p. 125 that a suitable truncation point for SVD parameters can be identified using the prediction variance is challenged using results from Moore and Doherty (2005). Fourth, the relative error reduction statistic of Doherty and Hunt is shown to belong to an emerging set of statistics here named perturbed calculated variance statistics. Finally, the perturbed calculated variance statistics OPR and PPR mentioned on p. 121 are shown to explicitly include the parameter null-space component of uncertainty. Indeed, OPR and PPR results that account for null-space uncertainty have appeared in the literature since 2000.

Spectral and entropic characterizations of Wigner functions: applications to model vibrational systems.

PubMed

Luzanov, A V

2008-09-07

The Wigner function for the pure quantum states is used as an integral kernel of the non-Hermitian operator K, to which the standard singular value decomposition (SVD) is applied. It provides a set of the squared singular values treated as probabilities of the individual phase-space processes, the latter being described by eigenfunctions of KK(+) (for coordinate variables) and K(+)K (for momentum variables). Such a SVD representation is employed to obviate the well-known difficulties in the definition of the phase-space entropy measures in terms of the Wigner function that usually allows negative values. In particular, the new measures of nonclassicality are constructed in the form that automatically satisfies additivity for systems composed of noninteracting parts. Furthermore, the emphasis is given on the geometrical interpretation of the full entropy measure as the effective phase-space volume in the Wigner picture of quantum mechanics. The approach is exemplified by considering some generic vibrational systems. Specifically, for eigenstates of the harmonic oscillator and a superposition of coherent states, the singular value spectrum is evaluated analytically. Numerical computations are given for the nonlinear problems (the Morse and double well oscillators, and the Henon-Heiles system). We also discuss the difficulties in implementation of a similar technique for electronic problems.

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

PubMed Central

Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

PubMed

Liu, Zhongming; de Zwart, Jacco A; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H

2012-02-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphasis is directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac timing markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable with the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. Published by Elsevier Inc.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN

PubMed Central

Cheng, Gang; Chen, Xihui

2018-01-01

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears. PMID:29751671

Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine.

PubMed

Dey, Nilanjan; Bose, Soumyo; Das, Achintya; Chaudhuri, Sheli Sinha; Saba, Luca; Shafique, Shoaib; Nicolaides, Andrew; Suri, Jasjit S

2016-04-01

Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DPsystem) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application.

Deciphering life history transcriptomes in different environments

PubMed Central

Etges, William J.; Trotter, Meredith V.; de Oliveira, Cássia C.; Rajpurohit, Subhash; Gibbs, Allen G.; Tuljapurkar, Shripad

2014-01-01

We compared whole transcriptome variation in six preadult stages and seven adult female ages in two populations of cactophilic Drosophila mojavensis reared on two host plants in order to understand how differences in gene expression influence standing life history variation. We used Singular Value Decomposition (SVD) to identify dominant trajectories of life cycle gene expression variation, performed pair-wise comparisons of stage and age differences in gene expression across the life cycle, identified when genes exhibited maximum levels of life cycle gene expression, and assessed population and host cactus effects on gene expression. Life cycle SVD analysis returned four significant components of transcriptional variation, revealing functional enrichment of genes responsible for growth, metabolic function, sensory perception, neural function, translation and aging. Host cactus effects on female gene expression revealed population and stage specific differences, including significant host plant effects on larval metabolism and development, as well as adult neurotransmitter binding and courtship behavior gene expression levels. In 3 - 6 day old virgin females, significant up-regulation of genes associated with meiosis and oogenesis was accompanied by down-regulation of genes associated with somatic maintenance, evidence for a life history tradeoff. The transcriptome of D. mojavensis reared in natural environments throughout its life cycle revealed core developmental transitions and genome wide influences on life history variation in natural populations. PMID:25442828

Delineation of The Sumatra Fault in The Central Part of West Sumatra based on Gravity Method

NASA Astrophysics Data System (ADS)

Saragih, R. D.; Brotopuspito, K. S.

2018-04-01

The Sumatra Fault System is elongated across the Sumatra Island, Indonesia, Southeast Asia including the central part of West Sumatra, Indonesia, Southeast Asia. The Sumatra Fault and subsurface structure on the Central Part of West Sumatra had been analyzed using gravity method. Bouguer anomaly data were obtained from GRDC (Geological Research and Development Centre) maps, Bandung, Indonesia (i.e. without terrain correction). In this study, terrain correction had been applied to these Bouguer data. Bouguer anomaly in a horizontal plane at 3000 meters high and equivalent depth of mass point 7000 meters were obtained using Dampney Method. Residual and regional anomalies were separated using upward continuation method at 8000 meters high. The result of the SVD on residual anomaly shows two negative anomalies on northwest – southeast. The zero miligal per meter square quantity coincides remarkably well with trace faults which is a part of the Sumatra Fault System. Two negative anomalies are located around the Sianok Segment and Sumani Segment.

Watermarking scheme based on singular value decomposition and homomorphic transform

NASA Astrophysics Data System (ADS)

Verma, Deval; Aggarwal, A. K.; Agarwal, Himanshu

2017-10-01

A semi-blind watermarking scheme based on singular-value-decomposition (SVD) and homomorphic transform is pro-posed. This scheme ensures the digital security of an eight bit gray scale image by inserting an invisible eight bit gray scale wa-termark into it. The key approach of the scheme is to apply the homomorphic transform on the host image to obtain its reflectance component. The watermark is embedded into the singular values that are obtained by applying the singular value decomposition on the reflectance component. Peak-signal-to-noise-ratio (PSNR), normalized-correlation-coefficient (NCC) and mean-structural-similarity-index-measure (MSSIM) are used to evaluate the performance of the scheme. Invisibility of watermark is ensured by visual inspection and high value of PSNR of watermarked images. Presence of watermark is ensured by visual inspection and high values of NCC and MSSIM of extracted watermarks. Robustness of the scheme is verified by high values of NCC and MSSIM for attacked watermarked images.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values.

PubMed

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-05

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD=0.12], 0.67-23.19 [LOD=0.13] and 0.73-25.12 [LOD=0.15] μgmL(-1) for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values

NASA Astrophysics Data System (ADS)

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-01

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD = 0.12], 0.67-23.19 [LOD = 0.13] and 0.73-25.12 [LOD = 0.15] μg mL- 1 for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples.

Left ventricular mass regression after aortic valve replacement with the new Mitroflow 12A pericardial bioprosthesis.

PubMed

García-Bengochea, José; Sierra, Juan; González-Juanatey, José R; Rubio, José; Vega, Marino; Fernández, Angel L; Sánchez, Daniel

2006-05-01

The study aim was to evaluate the durability of the new Mitroflow 12A pericardial bioprosthesis and to assess ventricular mass regression after aortic valve replacement (AVR) in patients with small valves. A total of 326 Mitroflow 12A pericardial bioprostheses was implanted without any other associated valve procedure. The mean patient age was 73.5 +/- 6.1 years; 252 patients (78.0%) were in NYHA class III/IV. Small valves (19 and 21 mm) were implanted in 212 patients (65.6%). The total follow up period was 837.1 patient-years (pt-yr). A subset of 61 patients with preoperative stenosis was selected and submitted to conventional echo-Doppler assessment at a mean period of 11.1 months after surgery. Hospital mortality was 8.6%. At eight years of follow up, survival was 57.1%. Freedom from structural valve deterioration (SVD) was 86.5% per pt-yr. Mean gradients were significantly reduced postoperatively for each valve size (to 18 +/- 8 mmHg for 19-mm valves and 12 +/- 4 mmHg for 25-mm valves). The effective orifice area (EOA) was also increased significantly for all valve sizes (to 1.1 +/- 0.1 cm2 for 19-mm valves and 1.8 +/- 0.2 cm2 for 25-mm valves). The left ventricular mass index (LVMI) decreased significantly, from 177 +/- 29 to 136 +/- 22 g/m2 for the 19-mm valve, and from 200 +/- 42 to 132 +/- 22 g/m2 for the 25-mm valve. The EOA index (EOAI) showed mismatch for the 19- and 21-mm valves (0.74 and 0.82 cm2/m2, respectively). The diagrammatic calculation between LVMI and relative wall thickness after surgery showed that 29.7% of patients achieved a normal pattern of remodeling (including 19- and 21-mm valves), despite various degrees of mismatch. The new Mitroflow 12A pericardial bioprosthesis showed an absence of mechanical failure after an eight-year follow up, with a satisfactory rate of SVD. Significant reductions in LVMI and improved ventricular geometry were observed, despite the small valve sizes implanted.

On the Comparison of the Global Surface Soil Moisture product and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Delorme, B., Jr.; Ottlé, C.; Peylin, P.; Polcher, J.

2016-12-01

Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to assess and improve land surface models parametrization. In this study, the ESA CCI surface soil moisture (SSM) combined product (v2.2) has been compared to the simulated top first layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to evaluate its potential of improvements with data assimilation techniques. The ambition of the work was to develop a comprehensive comparison methodology by analyzing simultaneously the temporal and spatial structures of both datasets. We analyzed the SSM synoptic, seasonal, and inter-annual variations by decomposing the signals into fast and slow components. ORCHIDEE was shown to adequately reproduce the observed SSM dynamics in terms of temporal correlation. However, these correlation scores are supposed to be strongly influenced by SSM seasonal variability and the quality of the model input forcing. Autocorrelation and spectral analyses brought out disagreements in the temporal inertia of the upper soil moisture reservoirs. By linking our results to land cover maps, we found that ORCHIDEE is more dependent on rainfall events compared to the observations in regions with sparse vegetation cover. These diflerences might be due to a wrong partition of rainfall between soil evaporation, transpiration, runofl and drainage in ORCHIDEE. To refine this analysis, a single value decomposition (SVD) of the co-variability between rainfall provided by WFDEI and soil moisture was pursued over Central Europe and South Africa. It showed that spatio-temporal co-varying patterns between ORCHIDEE and rainfall and the ESA-CCI product and rainfall are in relatively good agreement. However, the leading SVD pattern, which exhibits a strong annual cycle and explains the same portion of covariance for both datasets, explains a much larger fraction of variance for ORCHIDEE than for the ESA-CCI product. These results highlight that the role of other surface variables presenting a strong seasonal variability (like vegetation cover, possibly irrigation) is not accounted for similarly in both the model and the product, and that further work is needed to explore these discrepancies.

The Accuracy of Parameter Estimation in System Identification of Noisy Aircraft Load Measurement. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Kong, Jeffrey

1994-01-01

This thesis focuses on the subject of the accuracy of parameter estimation and system identification techniques. Motivated by a complicated load measurement from NASA Dryden Flight Research Center, advanced system identification techniques are needed. The objective of this problem is to accurately predict the load experienced by the aircraft wing structure during flight determined from a set of calibrated load and gage response relationship. We can then model the problem as a black box input-output system identification from which the system parameter has to be estimated. Traditional LS (Least Square) techniques and the issues of noisy data and model accuracy are addressed. A statistical bound reflecting the change in residual is derived in order to understand the effects of the perturbations on the data. Due to the intrinsic nature of the LS problem, LS solution faces the dilemma of the trade off between model accuracy and noise sensitivity. A method of conflicting performance indices is presented, thus allowing us to improve the noise sensitivity while at the same time configuring the degredation of the model accuracy. SVD techniques for data reduction are studied and the equivalence of the Correspondence Analysis (CA) and Total Least Squares Criteria are proved. We also looked at nonlinear LS problems with NASA F-111 data set as an example. Conventional methods are neither easily applicable nor suitable for the specific load problem since the exact model of the system is unknown. Neural Network (NN) does not require prior information on the model of the system. This robustness motivated us to apply the NN techniques on our load problem. Simulation results for the NN methods used in both the single load and the 'warning signal' problems are both useful and encouraging. The performance of the NN (for single load estimate) is better than the LS approach, whereas no conventional approach was tried for the 'warning signals' problems. The NN design methodology is also presented. The use of SVD, CA and Collinearity Index methods are used to reduce the number of neurons in a layer.

Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value Decomposition (SVD)

DTIC Science & Technology

2017-09-27

ARL-TR-8161•SEP 2017 US Army Research Laboratory Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value...originator. ARL-TR-8161•SEP 2017 US Army Research Laboratory Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value...unlimited. October 2015–January 2016 US Army Research Laboratory ATTN: RDRL-CIH-C Aberdeen Proving Ground, MD 21005-5066 primary author’s email

Sparse Representations for Limited Data Tomography (PREPRINT)

DTIC Science & Technology

2007-11-01

predefined (such as wavelets ) or learned (e.g., by the K-SVD algorithm [8]), as in this work. Due to its highly effectiveness for tasks such as image...from den- tal data produced by the Focus intraoral X-ray source and the Sigma intraoral sensor (Instrumentarium Dental ; courtesy of Maaria Rantala...proposed method (right column). a functional, encouraging a sparse representation of the im- age patches while keeping the data constraints provided by

The Shock and Vibration Digest. Volume 13, Number 12

DTIC Science & Technology

1981-12-01

Resulting Unsteady Forces and Flow Phenomenon. Part III 26 BOOK REVIEWS STATISTICAL ENERGY ANALYSIS Chapter IV considers the problems of estimating J OF...stress, acceleration, modes. Statistical energy analysis (SEA), which is and pressure; estimations of the average system expressed in terms of random...by F.C. Nelson, SVD, 13 (8), pp 30-31 (Aug 1981) Lyons, R.H., Statistical Energy Analysis of Dynamic Systems, MIT Press, Cambridge, MA; Revieed by H

Geo-Coding for the Mapping of Documents and Social Media Messages

DTIC Science & Technology

2013-08-22

O.L. (2007). UBC-ALM: Combining KNN with SVD for WSD. Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval-2007), Prague...and Yarowsky, D. (1992). One sense per discourse. In Proceedings of the 4th DARPA Speech and Natural Language Workshop. pp. 233-237, 1992. Retrieved...Part-of- Speech Tagging for Twitter: Annotation, Features, and Experiments. Proceedings of the Annual Meeting of the Association for Computational

Trend and Variability of China Precipitation in Spring and Summer: Linkage to Sea Surface Temperatures

NASA Technical Reports Server (NTRS)

Yang, Fanglin; Lau, K.-M.

2004-01-01

Observational records in the past 50 years show an upward trend of boreal-summer precipitation over central eastern China and a downward trend over northern China. During boreal spring, the trend is upward over southeastern China and downward over central eastern China. This study explores the forcing mechanism of these trends in association with the global sea-surface temperature (SST) variations on the interannual and inter-decadal timescales. Results based on Singular Value Decomposition analyses (SVD) show that the interannual variability of China precipitation in boreal spring and summer can be well defined by two centers of actions for each season, which are co-varying with two interannual modes of SSTs. The first SVD modes of precipitation in spring and summer, which are centered in southeastern China and northern China, respectively, are linked to an ENSO-like mode of SSTs. The second SVD modes of precipitation in both seasons are confined to central eastern China, and are primarily linked to SST variations over the warm pool and Indian Ocean. Features of the anomalous 850-hPa winds and 700-Wa geopotential height corresponding to these modes support a physical mechanism that explains the causal links between the modal variations of precipitation and SSTs. On the decadal and longer timescale, similar causal links are found between the same modes of precipitation and SSTs, except for the case of springtime precipitation over central eastern China. For this case, while the interannual mode of precipitation is positively correlated with the interannual variations of SSTs over the warm pool and Indian Ocean; the inter-decadal mode is negatively correlated with a different SST mode, the North Pacific mode. The later is responsible for the observed downward trend of springtime precipitation over central eastern China. For all other cases, both the interannual and inter-decadal variations of precipitation can be explained by the same mode of SSTs. The upward trend of springtime precipitation over southeastern China and downward trend of summertime precipitation over northern China are attributable to the warming trend of the ENSO-like mode. The recent frequent summertime floods over central eastern China are linked to the warming trend of SSTs over the warm pool and Indian Ocean.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions.

PubMed

Jha, Abhinav K; Barrett, Harrison H; Frey, Eric C; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A

2015-09-21

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions

NASA Astrophysics Data System (ADS)

Jha, Abhinav K.; Barrett, Harrison H.; Frey, Eric C.; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A.

2015-09-01

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

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.

Genomic Signal Processing: Predicting Basic Molecular Biological Principles

NASA Astrophysics Data System (ADS)

Alter, Orly

2005-03-01

Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of these two sets of states. Mapping genome-scale protein binding data using pseudoinverse projection onto patterns of RNA expression data that had been extracted by SVD and GSVD, a novel correlation between DNA replication initiation and RNA transcription during the cell cycle in yeast, that might be due to a previously unknown mechanism of regulation, is predicted. (1) Alter & Golub, Proc. Natl. Acad. Sci. USA 101, 16577 (2004). (2) Alter, Golub, Brown & Botstein, Miami Nat. Biotechnol. Winter Symp. 2004 (www.med.miami.edu/mnbws/alter-.pdf)

Mid-Level Planning and Control for Articulated Locomoting Systems

DTIC Science & Technology

2017-02-12

accelerometers and gyros into each module of our snake robots. Prior work from our group has already used an extended Kalman filter (EKF) to fuse these distributed...body frame is performed as part of the measurement model at every iteration of the filter , using an SVD to identify the principle components of the...addi- tion the conventional EKF, although we found that all three methods worked equally well. All three filters used the same process and measurement

Multiplex detection of agricultural pathogens

DOEpatents

McBride, Mary Teresa; Slezak, Thomas Richard; Messenger, Sharon Lee

2010-09-14

Described are kits and methods useful for detection of seven agricultural pathogens (BPSV; BHV; BVD; FMDV; BTV; SVD; and VESV) in a sample. Genomic sequence information from 7 agricultural pathogens was analyzed to identify signature sequences, e.g., polynucleotide sequences useful for confirming the presence or absence of a pathogen in a sample. Primer and probe sets were designed and optimized for use in a PCR based, multiplexed Luminex assay to successfully identify the presence or absence of pathogens in a sample.

Invariant object recognition based on the generalized discrete radon transform

NASA Astrophysics Data System (ADS)

Easley, Glenn R.; Colonna, Flavia

2004-04-01

We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.

Methods, Software and Tools for Three Numerical Applications. Final report

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

E. R. Jessup

2000-03-01

This is a report of the results of the authors work supported by DOE contract DE-FG03-97ER25325. They proposed to study three numerical problems. They are: (1) the extension of the PMESC parallel programming library; (2) the development of algorithms and software for certain generalized eigenvalue and singular value (SVD) problems, and (3) the application of techniques of linear algebra to an information retrieval technique known as latent semantic indexing (LSI).

Convergence analysis of the alternating RGLS algorithm for the identification of the reduced complexity Volterra model.

PubMed

Laamiri, Imen; Khouaja, Anis; Messaoud, Hassani

2015-03-01

In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS). Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Enhancement of snow cover change detection with sparse representation and dictionary learning

NASA Astrophysics Data System (ADS)

Varade, D.; Dikshit, O.

2014-11-01

Sparse representation and decoding is often used for denoising images and compression of images with respect to inherent features. In this paper, we adopt a methodology incorporating sparse representation of a snow cover change map using the K-SVD trained dictionary and sparse decoding to enhance the change map. The pixels often falsely characterized as "changes" are eliminated using this approach. The preliminary change map was generated using differenced NDSI or S3 maps in case of Resourcesat-2 and Landsat 8 OLI imagery respectively. These maps are extracted into patches for compressed sensing using Discrete Cosine Transform (DCT) to generate an initial dictionary which is trained by the K-SVD approach. The trained dictionary is used for sparse coding of the change map using the Orthogonal Matching Pursuit (OMP) algorithm. The reconstructed change map incorporates a greater degree of smoothing and represents the features (snow cover changes) with better accuracy. The enhanced change map is segmented using kmeans to discriminate between the changed and non-changed pixels. The segmented enhanced change map is compared, firstly with the difference of Support Vector Machine (SVM) classified NDSI maps and secondly with a reference data generated as a mask by visual interpretation of the two input images. The methodology is evaluated using multi-spectral datasets from Resourcesat-2 and Landsat-8. The k-hat statistic is computed to determine the accuracy of the proposed approach.

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health

PubMed Central

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S. Stanley

2016-01-01

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability. PMID:27213413

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health.

PubMed

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S Stanley

2016-05-18

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability.

Alternative methods of phylogenetic inference for the Patagonian lizard group Liolaemus elongatus-kriegi (Iguania: Liolaemini) based on mitochondrial and nuclear markers.

PubMed

Medina, Cintia Débora; Avila, Luciano Javier; Sites, Jack Walter; Santos, Juan; Morando, Mariana

2018-03-01

We present different approaches to a multi-locus phylogeny for the Liolaemus elongatus-kriegi group, including almost all species and recognized lineages. We sequenced two mitochondrial and five nuclear gene regions for 123 individuals from 35 taxa, and compared relationships resolved from concatenated and species tree methods. The L. elongatus-kriegi group was inferred as monophyletic in three of the five analyses (concatenated mitochondrial, concatenated mitochondrial + nuclear gene trees, and SVD quartet species tree). The mitochondrial gene tree resolved four haploclades, three corresponding to the previously recognized complexes: L. elongatus, L. kriegi and L. petrophilus complexes, and the L. punmahuida group. The BEAST species tree approach included the L. punmahuida group within the L. kriegi complex, but the SVD quartet method placed it as sister to the L. elongatus-kriegi group. BEAST inferred species of the L. elongatus and L. petrophilus complexes as one clade, while SVDquartet inferred these two complexes as monophyletic (although with no statistical support for the L. petrophilus complex). The species tree approach also included the L. punmahuida group as part of the L. elongatus-kriegi group. Our study provides detailed multilocus phylogenetic hypotheses for the L. elongatus-kriegi group, and we discuss possible reasons for differences in the concatenation and species tree methods. Copyright © 2017 Elsevier Inc. All rights reserved.

SAMHD1 Gene Mutations Are Associated with Cerebral Large-Artery Atherosclerosis

PubMed Central

Xin, Baozhong; Yan, Junpeng; Wu, Ying; Hu, Bo; Liu, Liping; Wang, Yilong; Ahn, Jinwoo; Skowronski, Jacek; Zhang, Zaiqiang; Wang, Yongjun; Wang, Heng

2015-01-01

Background. To investigate whether one or more SAMHD1 gene mutations are associated with cerebrovascular disease in the general population using a Chinese stroke cohort. Methods. Patients with a Chinese Han background (N = 300) diagnosed with either cerebral large-artery atherosclerosis (LAA, n = 100), cerebral small vessel disease (SVD, n = 100), or other stroke-free neurological disorders (control, n = 100) were recruited. Genomic DNA from the whole blood of each patient was isolated, and direct sequencing of the SAMHD1 gene was performed. Both wild type and mutant SAMHD1 proteins identified from the patients were expressed in E. coli and purified; then their dNTPase activities and ability to form stable tetramers were analysed in vitro. Results. Three heterozygous mutations, including two missense mutations c.64C>T (P22S) and c.841G>A (p.E281K) and one splice site mutation c.696+2T>A, were identified in the LAA group with a prevalence of 3%. No mutations were found in the patients with SVD or the controls (p = 0.05). The mutant SAMHD1 proteins were functionally impaired in terms of their catalytic activity as a dNTPase and ability to assemble stable tetramers. Conclusions. Heterozygous SAMHD1 gene mutations might cause genetic predispositions that interact with other risk factors, resulting in increased vulnerability to stroke. PMID:26504826

Geometry of the 1954 Fairview Peak-Dixie Valley earthquake sequence from a joint inversion of leveling and triangulation data

USGS Publications Warehouse

Hodgkinson, K.M.; Stein, R.S.; Marshall, G.

1996-01-01

In 1954, four earthquakes greater than Ms=6.0 occurred within a 30-km radius and in a period of 6 months. Elevation and angle changes calculated from repeated leveling and triangulation surveys which span the coseismic period provide constraints on the fault geometries and coseismic slip of the faults which were activated. The quality of the coseismic geodetic data is assessed. Corrections are applied to the leveling data for subsidence due to groundwater withdrawal in the Fallon area, and a rod miscalibration error of 150??30 ppm is isolated in leveling surveys made in 1967. The leveling and triangulation observations are then simultaneously inverted using the single value decomposition (SVD) inversion method to determine fault geometries and coseismic slip. Using SVD, it is possible to determine on which faults slip is resolvable given the data distribution. The faults are found to dip between 50?? and 80?? and extend to depths of 5 to 14 km. The geodetically derived slip values are generally equal to, or greater than, the maximum observed displacement along the surface scarps. Where slip is resolvable the geodetic data indicates the 1954 sequence contained a significant component of right-lateral slip. This is consistent with the N15??W trending shear zone which geodetic surveys have detected in western Nevada. Copyright 1996 by the American Geophysical Union.

Dispersion characteristics of the flexural wave assessed using low frequency (50-150kHz) point-contact transducers: A feasibility study on bone-mimicking phantoms.

PubMed

Kassou, Koussila; Remram, Youcef; Laugier, Pascal; Minonzio, Jean-Gabriel

2017-11-01

Guided waves-based techniques are currently under development for quantitative cortical bone assessment. However, the signal interpretation is challenging due to multiple mode overlapping. To overcome this limitation, dry point-contact transducers have been used at low frequencies for a selective excitation of the zeroth order anti-symmetric Lamb A0 mode, a mode whose dispersion characteristics can be used to infer the thickness of the waveguide. In this paper, our purpose was to extend the technique by combining a dry point-contact transducers approach to the SVD-enhanced 2-D Fourier transform in order to measure the dispersion characteristics of the flexural mode. The robustness of our approach is assessed on bone-mimicking phantoms covered or not with soft tissue-mimicking layer. Experiments were also performed on a bovine bone. Dispersion characteristics of measured modes were extracted using a SVD-based signal processing technique. The thickness was obtained by fitting a free plate model to experimental data. The results show that, in all studied cases, the estimated thickness values are in good agreement with the actual thickness values. From the results, we speculate that in vivo cortical thickness assessment by measuring the flexural wave using point-contact transducers is feasible. However, this assumption has to be confirmed by further in vivo studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Plasma homocysteine and cerebral small vessel disease as possible mediators between kidney and cognitive functions in patients with diabetes mellitus.

PubMed

Sonoda, Mika; Shoji, Tetsuo; Kuwamura, Yukinobu; Okute, Yujiro; Naganuma, Toshihide; Shima, Hideaki; Motoyama, Koka; Morioka, Tomoaki; Mori, Katsuhito; Fukumoto, Shinya; Shioi, Atsushi; Shimono, Taro; Fujii, Hisako; Kabata, Daijiro; Shintani, Ayumi; Emoto, Masanori; Inaba, Masaaki

2017-06-29

Cognitive impairment is more prevalent in those with decreased kidney function. We tested a hypothesis that an increased homocysteine and/or cerebral small vessel diseases (SVDs) mediate the link between kidney and cognitive functions in a cross-sectional study in 143 type 2 diabetes patients without diagnosis of dementia or prior stroke. The exposure and outcome variables were estimated glomerular filtration rate (eGFR) and cognitive performance evaluated with Modified Mini-Mental State (3 MS) examination, respectively. The candidate mediators were plasma homocysteine concentration, and SVDs including silent cerebral infarction, cerebral microbleed, periventricular hyperintensity, and deep and subcortical white matter hyperintensity by magnetic resonance imaging. In multiple regression models adjusted for 12 potential confounders, eGFR was positively associated with 3 MS score, inversely with homocysteine, but not significantly with the presence of any type of SVD. The association of eGFR with 3 MS remained significant when each of the SVDs was added to the model, whereas it disappeared when homocysteine was included in place of SVD. Mediation analysis indicated nearly significant mediation of homocysteine (P = 0.062) but no meaningful mediations of SVDs (P = 0.842-0.930). Thus, homocysteine, not SVDs, was shown to be the possible mediator between kidney and cognitive functions in patients with type 2 diabetes mellitus.

Sparse coded image super-resolution using K-SVD trained dictionary based on regularized orthogonal matching pursuit.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2015-01-01

Image super-resolution (SR) plays a vital role in medical imaging that allows a more efficient and effective diagnosis process. Usually, diagnosing is difficult and inaccurate from low-resolution (LR) and noisy images. Resolution enhancement through conventional interpolation methods strongly affects the precision of consequent processing steps, such as segmentation and registration. Therefore, we propose an efficient sparse coded image SR reconstruction technique using a trained dictionary. We apply a simple and efficient regularized version of orthogonal matching pursuit (ROMP) to seek the coefficients of sparse representation. ROMP has the transparency and greediness of OMP and the robustness of the L1-minization that enhance the dictionary learning process to capture feature descriptors such as oriented edges and contours from complex images like brain MRIs. The sparse coding part of the K-SVD dictionary training procedure is modified by substituting OMP with ROMP. The dictionary update stage allows simultaneously updating an arbitrary number of atoms and vectors of sparse coefficients. In SR reconstruction, ROMP is used to determine the vector of sparse coefficients for the underlying patch. The recovered representations are then applied to the trained dictionary, and finally, an optimization leads to high-resolution output of high-quality. Experimental results demonstrate that the super-resolution reconstruction quality of the proposed scheme is comparatively better than other state-of-the-art schemes.

Relating ocean-atmospheric climate indices with Australian river streamflow

NASA Astrophysics Data System (ADS)

Shams, Md Shamim; Faisal Anwar, A. H. M.; Lamb, Kenneth W.; Bari, Mohammed

2018-01-01

The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971-2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF.

The Manifest Association Structure of the Single-Factor Model: Insights from Partial Correlations

ERIC Educational Resources Information Center

Salgueiro, Maria de Fatima; Smith, Peter W. F.; McDonald, John W.

2008-01-01

The association structure between manifest variables arising from the single-factor model is investigated using partial correlations. The additional insights to the practitioner provided by partial correlations for detecting a single-factor model are discussed. The parameter space for the partial correlations is presented, as are the patterns of…

Impacts of El Niño and El Niño Modoki on the precipitation in Colombia

NASA Astrophysics Data System (ADS)

Córdoba Machado, Samir; Palomino Lemus, Reiner; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda; Jesús Esteban Parra, María

2015-04-01

The influence of the tropical Pacific SST on precipitation in Colombia is examined using 341 stations covering the period 1979-2009. Through a Singular Value Decomposition (SVD) the two main coupled variability modes show SST patterns clearly associated with El Niño (EN) and El Niño Modoki (ENM), respectively, presenting great coupling strength with the corresponding seasonal precipitation modes in Colombia. The results reveal that, mainly in winter and summer, EN and ENM events are associated with a significant rainfall decrease over northern, central, and western Colombia. The opposite effect occurs in some localities during spring, summer, and autumn. The southwestern region of Colombia exhibits an opposite behaviour connected to EN and ENM events during years when both events do not coexist, showing that the seasonal precipitation response is not linear. The Partial Regression Analysis used to quantify separately the influence of the two types of ENSO on seasonal precipitation shows the importance of both types in the reconstruction process. The results obtained in this study establish the base for modeling and forecasting the seasonal precipitation in Colombia using the tropical Pacific SST associated with El Niño and El Niño Modoki. Keywords: Seasonal precipitation, Tropical Pacific SST, El Niño, El Niño Modoki, Singular Value Decomposition, Colombia. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

[Surface electromyography signal classification using gray system theory].

PubMed

Xie, Hongbo; Ma, Congbin; Wang, Zhizhong; Huang, Hai

2004-12-01

A new method based on gray correlation was introduced to improve the identification rate in artificial limb. The electromyography (EMG) signal was first transformed into time-frequency domain by wavelet transform. Singular value decomposition (SVD) was then used to extract feature vector from the wavelet coefficient for pattern recognition. The decision was made according to the maximum gray correlation coefficient. Compared with neural network recognition, this robust method has an almost equivalent recognition rate but much lower computation costs and less training samples.

The Mesoscale Eddies and Kuroshio Transport in the Western North Pacific East of Taiwan from 8-year (2003-2010) Model Reanalysis

DTIC Science & Technology

2013-07-25

EOF . SVD 1 Introduction Mesoscale eddies are abundant in the ocean. Chelton et al. ( 2007 ), based on 10 years of altimetry sea surface height anomaly...transport. The dynamic height has a strong annual signal due to steric variations (Wang and Koblinsky 1996; Stammer 1997). Since our study is...JOE.2004.838334 Chelton DB, Schlax MG, Samelson RM, deSzoeke RA ( 2007 ) Global observations of large oceanic eddies. Geophys Res Lett 34, L15606. doi

A Note on the Factor Analysis of Partial Covariance Matrices

ERIC Educational Resources Information Center

McDonald, Roderick P.

1978-01-01

The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)

Comparative study of inversion methods of three-dimensional NMR and sensitivity to fluids

NASA Astrophysics Data System (ADS)

Tan, Maojin; Wang, Peng; Mao, Keyu

2014-04-01

Three-dimensional nuclear magnetic resonance (3D NMR) logging can simultaneously measure transverse relaxation time (T2), longitudinal relaxation time (T1), and diffusion coefficient (D). These parameters can be used to distinguish fluids in the porous reservoirs. For 3D NMR logging, the relaxation mechanism and mathematical model, Fredholm equation, are introduced, and the inversion methods including Singular Value Decomposition (SVD), Butler-Reeds-Dawson (BRD), and Global Inversion (GI) methods are studied in detail, respectively. During one simulation test, multi-echo CPMG sequence activation is designed firstly, echo trains of the ideal fluid models are synthesized, then an inversion algorithm is carried on these synthetic echo trains, and finally T2-T1-D map is built. Futhermore, SVD, BRD, and GI methods are respectively applied into a same fluid model, and the computing speed and inversion accuracy are compared and analyzed. When the optimal inversion method and matrix dimention are applied, the inversion results are in good aggreement with the supposed fluid model, which indicates that the inversion method of 3D NMR is applieable for fluid typing of oil and gas reservoirs. Additionally, the forward modeling and inversion tests are made in oil-water and gas-water models, respectively, the sensitivity to the fluids in different magnetic field gradients is also examined in detail. The effect of magnetic gradient on fluid typing in 3D NMR logging is stuied and the optimal manetic gradient is choosen.

Multidecadal climate variability of global lands and oceans

USGS Publications Warehouse

McCabe, G.J.; Palecki, M.A.

2006-01-01

Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperature (SSTs). The PDSI and SST data for 1925-2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Published in 2006 by John Wiley & Sons, Ltd.

Dementia incidence and predictors in cerebral amyloid angiopathy patients without intracerebral hemorrhage.

PubMed

Xiong, Li; Boulouis, Gregoire; Charidimou, Andreas; Roongpiboonsopit, Duangnapa; Jessel, Michael J; Pasi, Marco; Reijmer, Yael D; Fotiadis, Panagiotis; Ayres, Alison; Merrill, Emily; Schwab, Kristin; Blacker, Deborah; Gurol, M Edip; Greenberg, Steven M; Viswanathan, Anand

2018-02-01

Cerebral amyloid angiopathy (CAA) is a common cause of cognitive impairment in older individuals. This study aimed to investigate predictors of dementia in CAA patients without intracerebral hemorrhage (ICH). A total of 158 non-demented patients from the Stroke Service or the Memory Clinic who met the modified Boston Criteria for probable CAA were included. At baseline, neuroimaging markers, including lobar microbleeds (cerebral microbleeds (CMBs)), white matter hyperintensities (WMH), cortical superficial siderosis (cSS), magnetic resonance imaging (MRI)-visible centrum semiovale perivascular spaces (CSO-PVS), lacunes, and medial temporal atrophy (MTA) were assessed. The overall burden of small vessel disease (SVD) for CAA was calculated by a cumulative score based on CMB number, WMH severity, cSS presence and extent and CSO-PVS severity. The estimated cumulative dementia incidence at 1 year was 14% (95% confidence interval (CI): 5%-23%), and 5 years 73% (95% CI: 55%, 84%). Age (hazard ratio (HR) 1.05 per year, 95% CI: 1.01-1.08, p = 0.007), presence of MCI status (HR 3.40, 95% CI: 1.97-6.92, p < 0.001), MTA (HR 1.71 per point, 95% CI: 1.26-2.32, p = 0.001), and SVD score (HR 1.23 per point, 95% CI: 1.20-1.48, p = 0.030) at baseline were independent predictors for dementia conversion in these patients. Cognitive deterioration of CAA patients appears attributable to cumulative changes, from both vasculopathic and neurodegenerative lesions.

Erasing the Milky Way: new cleaning technique applied to GBT intensity mapping data

NASA Astrophysics Data System (ADS)

Wolz, L.; Blake, C.; Abdalla, F. B.; Anderson, C. J.; Chang, T.-C.; Li, Y.-C.; Masui, K. W.; Switzer, E.; Pen, U.-L.; Voytek, T. C.; Yadav, J.

2017-02-01

We present the first application of a new foreground removal pipeline to the current leading H I intensity mapping data set, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h-field data of the GBT observations previously presented in Mausui et al. and Switzer et al., covering about 41 deg2 at 0.6 < z < 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point-source contamination using an independent component analysis technique (FASTICA), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that FASTICA is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps are dominated by instrumental noise on small scales which FASTICA, as a conservative subtraction technique of non-Gaussian signals, cannot mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the singular value decomposition (SVD) method, and confirm that foreground subtraction with FASTICA is robust against 21 cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and FASTICA are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping data sets.

Small white matter lesion detection in cerebral small vessel disease

NASA Astrophysics Data System (ADS)

Ghafoorian, Mohsen; Karssemeijer, Nico; van Uden, Inge; de Leeuw, Frank E.; Heskes, Tom; Marchiori, Elena; Platel, Bram

2015-03-01

Cerebral small vessel disease (SVD) is a common finding on magnetic resonance images of elderly people. White matter lesions (WML) are important markers for not only the small vessel disease, but also neuro-degenerative diseases including multiple sclerosis, Alzheimer's disease and vascular dementia. Volumetric measurements such as the "total lesion load", have been studied and related to these diseases. With respect to SVD we conjecture that small lesions are important, as they have been observed to grow over time and they form the majority of lesions in number. To study these small lesions they need to be annotated, which is a complex and time-consuming task. Existing (semi) automatic methods have been aimed at volumetric measurements and large lesions, and are not suitable for the detection of small lesions. In this research we established a supervised voxel classification CAD system, optimized and trained to exclusively detect small WMLs. To achieve this, several preprocessing steps were taken, which included a robust standardization of subject intensities to reduce inter-subject intensity variability as much as possible. A number of features that were found to be well identifying small lesions were calculated including multimodal intensities, tissue probabilities, several features for accurate location description, a number of second order derivative features as well as multi-scale annular filter for blobness detection. Only small lesions were used to learn the target concept via Adaboost using random forests as its basic classifiers. Finally the results were evaluated using Free-response receiver operating characteristic.

Can sun-induced chlorophyll fluorescence track diurnal variations of GPP in an evergreen needle leaf forest?

NASA Astrophysics Data System (ADS)

Kim, J.; Ryu, Y.; Dechant, B.; Cho, S.; Kim, H. S.; Yang, K.

2017-12-01

The emerging technique of remotely sensed sun-induced fluorescence (SIF) has advanced our ability to estimate plant photosynthetic activity at regional and global scales. Continuous observations of SIF and gross primary productivity (GPP) at the canopy scale in evergreen needleleaf forests, however, have not yet been presented in the literature so far. Here, we report a time series of near-surface measurements of canopy-scale SIF, hyperspectral reflectance and GPP during the senescence period in an evergreen needleleaf forest in South Korea. Mean canopy height was 30 m and a hyperspectrometer connected with a single fiber and rotating prism, which measures bi-hemispheric irradiance, was installed 20 m above the canopy. SIF was retrieved in the spectral range 740-790 nm at a temporal resolution of 1 min. We tested different SIF retrieval methods, such as Fraunhofer line depth (FLD), spectral fitting method (SFM) and singular vector decomposition (SVD) against GPP estimated by eddy covariance and absorbed photosynthetically active radiation (APAR). We found that the SVD-retrieved SIF signal shows linear relationships with GPP (R2 = 0.63) and APAR (R2 = 0.52) while SFM- and FLD-retrieved SIF performed poorly. We suspect the larger influence of atmospheric oxygen absorption between the sensor and canopy might explain why SFM and FLD methods showed poor results. Data collection will continue and the relationships between SIF, GPP and APAR will be studied during the senescence period.

Magnetic design and method of a superconducting magnet for muon g - 2/EDM precise measurements in a cylindrical volume with homogeneous magnetic field

NASA Astrophysics Data System (ADS)

Abe, M.; Murata, Y.; Iinuma, H.; Ogitsu, T.; Saito, N.; Sasaki, K.; Mibe, T.; Nakayama, H.

2018-05-01

A magnetic field design method of magneto-motive force (coil block (CB) and iron yoke) placements for g - 2/EDM measurements has been developed and a candidate placements were designed under superconducting limitations of current density 125 A/mm2 and maximum magnetic field on CBs less than 5.5 T. Placements of CBs and an iron yoke with poles were determined by tuning SVD (singular value decomposition) eigenmode strengths. The SVD was applied on a response matrix from magneto-motive forces to the magnetic fields in the muon storage region and two-dimensional (2D) placements of magneto-motive forces were designed by tuning the magnetic field eigenmode strengths obtained by the magnetic field. The tuning was performed iteratively. Magnetic field ripples in the azimuthal direction were minimized for the design. The candidate magnetic design had five CBs and an iron yoke with center iron poles. The magnet satisfied specifications of homogeneity (0.2 ppm peak-to-peak in 2D placements (the cylindrical coordinate of the radial position R and axial position Z) and less than 1.0 ppm ripples in the ring muon storage volume (0.318 m < R < 0 . 348 m and -0.05 < Z < 0.05 m) with 3.0 T strength and a slightly negative BR (magnetic field radial component) at Z > 0.0 m) for the spiral muon injection from the iron yoke at top.

The effects of partial cutting on stand structure and growth of western hemlock—Sitka spruce stands in southeast Alaska.

Treesearch

Robert L. Deal; John C. Tappeiner

2002-01-01

The effects of partial cutting on species composition, new and residual-tree cohorts, tree size distribution, and tree growth was evaluate on 73 plots in 18 stands throughout southeast Alaska. These partially cut stands were harvested 12-96 years ago, when 16-96% if the former stand basal area was removed.Partial cutting maintained stand structures similar to...

Can Chinese Herbal Medicine Adjunctive Therapy Improve Outcomes of Senile Vascular Dementia? Systematic Review with Meta-analysis of Clinical Trials.

PubMed

Zeng, Lingfeng; Zou, Yuanping; Kong, Lingshuo; Wang, Ningsheng; Wang, Qi; Wang, Lu; Cao, Ye; Wang, Kezhu; Chen, Yunbo; Mi, Suiqing; Zhao, Wei; Wu, Haitao; Cheng, Shuyi; Xu, Weihua; Liang, Weixiong

2015-12-01

Many publications have reported the growing application of complementary and alternative medicine, particularly the use of Chinese herbal medicine (CHM) in combination with routine pharmacotherapy (RP) for senile vascular dementia (SVD), but its efficacy remains largely unexplored. The purpose of this study is to evaluate the efficacy of CHM adjunctive therapy (CHMAT), which is CHM combined with RP, in the treatment of SVD. Publications in seven electronic databases were searched extensively, and 27 trials with a total of 1961 patients were included for analysis. Compared with RP alone, CHMAT significantly increased the effective rate [odds ratio (OR) 2.98, 95% confidence interval (CI) 2.30, 3.86]. In addition, CHMAT showed benefits in detailed subgroups of the Mini-Mental State Exam (MMSE) score from time of onset to 4 weeks (WMD 3.01, 95% CI 2.15, 3.87), 8 weeks (weighted mean difference (WMD) 2.30, 95% CI 1.28, 3.32), 12 weeks (WMD 2.93, 95% CI 2.17, 3.69), and 24 weeks (WMD 3.25, 95% CI 2.61, 3.88), and in the activity of daily living scale score from time of onset to 4 weeks (WMD -4.64, 95% CI -6.12, -3.17), 8 weeks (WMD -4.30, 95% CI -6.04, -2.56), 12 weeks (WMD -3.89, 95% CI -4.68, -3.09), and 24 weeks (WMD -4.04, 95% CI -6.51, -1.57). Moreover, CHMAT had positive effects on changes in the Hasegawa dementia scale, National Institutes of Health Stroke Scale, Clinical Dementia Rating, and Montreal Cognitive Assessment scores, as well as blood fat levels (total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and apolipoprotein E), platelet aggregation rate (1-min platelet aggregation rate, 5-min platelet aggregation rate, and maximal platelet aggregation rate), and blood rheology (whole-blood viscosity and hematocrit). No serious or frequently occurring adverse effects were reported. Weaknesses of methodological quality in most trials were assessed using the Cochrane risk of bias tool, while the quality level of Grades of Recommendations Assessment Development and Evaluation (GRADE) evidence classification indicated 'very low'. This systematic review suggests that CHM as an adjunctive therapy can improve cognitive impairment and enhance immediate response and quality of life in SVD patients. However, because of limitations of methodological quality in the included studies, further research of rigorous design is needed. Copyright © 2015 John Wiley & Sons, Ltd.

A geochemical approach for assessing the possible uses of the geothermal resource in the eastern sector of the Sabatini Volcanic District (Central Italy)

NASA Astrophysics Data System (ADS)

Cinti, Daniele; Tassi, Franco; Procesi, Monia; Brusca, Lorenzo; Cabassi, Jacopo; Capecchiacci, Francesco; Delgado Huertas, Antonio; Galli, Gianfranco; Grassa, Fausto; Vaselli, Orlando; Voltattorni, Nunzia

2017-04-01

The Sabatini Volcanic District (SVD) hosts a hydrothermal reservoir heated by the post-magmatic activity that affected the peri-Tyrrhenian sector of central Italy, giving rise to a number of thermal and mineral discharges. In this study, a complete geochemical and isotopic dataset based on the composition of 215 water and 9 bubbling gases, collected from the eastern sector of this huge hydrothermal system, is reported. The main aims are to (i) investigate the fluid sources and the main chemical-physical processes controlling the fluid chemistry and (ii) construct a conceptual fluid circulation model to provide insights into the possible use(s) of the geothermal resource. The fluid discharges are fed by two main aquifers, characterized by: (1) a Ca-HCO3 to Ca(Na)-HCO3 composition, typical of a shallow hydrological circuit within volcanic and sedimentary formations, and (2) a Ca-HCO3(SO4) to Na(Ca)-HCO3(Cl) composition, produced by the interaction of CO2-rich fluids with Mesozoic and Triassic carbonate-evaporite rocks. A thick sequence of low-permeability volcanic products represents a physical barrier between the two fluid reservoirs. As commonly occurring in central-southern Italy, CO2 is mainly produced by thermo-metamorphic decarbonation within the carbonate-evaporite reservoir, with minor contribution of mantle CO2. A dominant crustal source is also indicated by the relatively low R/Ra values (0.07-1.04). Methane and light hydrocarbons are mostly thermogenic, whereas H2S derives from thermogenic reduction of the Triassic anhydrites. Slightly positive 15N/14N values suggest minor N2 contribution from deep sedimentary sources. On the whole, a comparison of these geochemical features with those of the thermal fluids from the western portion of SVD highlights an eastward increasing influence of the shallow aquifer on the deep-originated fluids, likely caused by the proximity of the Apennine range from where the meteoric water, recharging the hydrothermal system, permeate. Accordingly, gas geothermometry in the CH4-CO2-H2 and H2S-CO2-H2 systems suggests equilibrium temperatures <200 °C, i.e. significantly lower than those measured in fluids from deep geothermal wells (300 °C). Although mitigated by the short distance from the Apennine range, the thermal anomaly recognized by fluid geochemistry in the eastern SVD makes this area suitable for direct exploitation of the geothermal resource.

Species trees from consensus single nucleotide polymorphism (SNP) data: Testing phylogenetic approaches with simulated and empirical data.

PubMed

Schmidt-Lebuhn, Alexander N; Aitken, Nicola C; Chuah, Aaron

2017-11-01

Datasets of hundreds or thousands of SNPs (Single Nucleotide Polymorphisms) from multiple individuals per species are increasingly used to study population structure, species delimitation and shallow phylogenetics. The principal software tool to infer species or population trees from SNP data is currently the BEAST template SNAPP which uses a Bayesian coalescent analysis. However, it is computationally extremely demanding and tolerates only small amounts of missing data. We used simulated and empirical SNPs from plants (Australian Craspedia, Asteraceae, and Pelargonium, Geraniaceae) to compare species trees produced (1) by SNAPP, (2) using SVD quartets, and (3) using Bayesian and parsimony analysis with several different approaches to summarising data from multiple samples into one set of traits per species. Our aims were to explore the impact of tree topology and missing data on the results, and to test which data summarising and analyses approaches would best approximate the results obtained from SNAPP for empirical data. SVD quartets retrieved the correct topology from simulated data, as did SNAPP except in the case of a very unbalanced phylogeny. Both methods failed to retrieve the correct topology when large amounts of data were missing. Bayesian analysis of species level summary data scoring the two alleles of each SNP as independent characters and parsimony analysis of data scoring each SNP as one character produced trees with branch length distributions closest to the true trees on which SNPs were simulated. For empirical data, Bayesian inference and Dollo parsimony analysis of data scored allele-wise produced phylogenies most congruent with the results of SNAPP. In the case of study groups divergent enough for missing data to be phylogenetically informative (because of additional mutations preventing amplification of genomic fragments or bioinformatic establishment of homology), scoring of SNP data as a presence/absence matrix irrespective of allele content might be an additional option. As this depends on sampling across species being reasonably even and a random distribution of non-informative instances of missing data, however, further exploration of this approach is needed. Properly chosen data summary approaches to inferring species trees from SNP data may represent a potential alternative to currently available individual-level coalescent analyses especially for quick data exploration and when dealing with computationally demanding or patchy datasets. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

No-go for partially massless spin-2 Yang-Mills

DOE PAGES

Garcia-Saenz, Sebastian; Hinterbichler, Kurt; Joyce, Austin; ...

2016-02-05

There are various no-go results forbidding self-interactions for a single partially massless spin-2 field. Given the photon-like structure of the linear partially massless field, it is natural to ask whether a multiplet of such fields can interact under an internal Yang-Mills like extension of the partially massless symmetry. In this paper, we give two arguments that such a partially massless Yang-Mills theory does not exist. The first is that there is no Yang-Mills like non-abelian deformation of the partially massless symmetry, and the second is that cubic vertices with the appropriate structure constants do not exist.

Hitting America’s Soft Underbelly. The Potential Threat of Deliberate Biological Attacks Against the U.S. Agricultural and Food Industry

DTIC Science & Technology

2004-01-01

virus) RVF Rift Valley fever SGP sheep and goat pox (viruses) SVD Swine vesicular disease UK United Kingdom USDA U.S. Department of Agriculture VS...and dairy farm- ers alone earn between $50 billion and $54 billion a year through meat and milk sales,7 while roughly $50 billion in revenues are gener...especially true of outlying fields and feedlots and may also be the case with centralized facilities such as milking stands. Security at animal auctions

Comparison of tree size structure and growth for partially harvested and even-aged hemlock-spruce stands in southeast Alaska

Treesearch

Robert L. Deal; Troy Heithecker; Eric K. Zenner

2010-01-01

The effects of partial cutting on tree size structure and stand growth were evaluated in 52 plots in 13 stands in southeast Alaska that were partially harvested 53 to 96 years ago and compared with 50-year-old even-aged stands that developed after clearcutting. The net basal-area growth was greater in the partially cut plots than in the uncut plots, and basal-area...

Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Shangbin; Lu, Siliang; He, Qingbo; Kong, Fanrang

2016-09-01

For rotating machines, the defective faults of bearings generally are represented as periodic transient impulses in acquired signals. The extraction of transient features from signals has been a key issue for fault diagnosis. However, the background noise reduces identification performance of periodic faults in practice. This paper proposes a time-varying singular value decomposition (TSVD) method to enhance the identification of periodic faults. The proposed method is inspired by the sliding window method. By applying singular value decomposition (SVD) to the signal under a sliding window, we can obtain a time-varying singular value matrix (TSVM). Each column in the TSVM is occupied by the singular values of the corresponding sliding window, and each row represents the intrinsic structure of the raw signal, namely time-singular-value-sequence (TSVS). Theoretical and experimental analyses show that the frequency of TSVS is exactly twice that of the corresponding intrinsic structure. Moreover, the signal-to-noise ratio (SNR) of TSVS is improved significantly in comparison with the raw signal. The proposed method takes advantages of the TSVS in noise suppression and feature extraction to enhance fault frequency for diagnosis. The effectiveness of the TSVD is verified by means of simulation studies and applications to diagnosis of bearing faults. Results indicate that the proposed method is superior to traditional methods for bearing fault diagnosis.

Three-dimensional dictionary-learning reconstruction of (23)Na MRI data.

PubMed

Behl, Nicolas G R; Gnahm, Christine; Bachert, Peter; Ladd, Mark E; Nagel, Armin M

2016-04-01

To reduce noise and artifacts in (23)Na MRI with a Compressed Sensing reconstruction and a learned dictionary as sparsifying transform. A three-dimensional dictionary-learning compressed sensing reconstruction algorithm (3D-DLCS) for the reconstruction of undersampled 3D radial (23)Na data is presented. The dictionary used as the sparsifying transform is learned with a K-singular-value-decomposition (K-SVD) algorithm. The reconstruction parameters are optimized on simulated data, and the quality of the reconstructions is assessed with peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The performance of the algorithm is evaluated in phantom and in vivo (23)Na MRI data of seven volunteers and compared with nonuniform fast Fourier transform (NUFFT) and other Compressed Sensing reconstructions. The reconstructions of simulated data have maximal PSNR and SSIM for an undersampling factor (USF) of 10 with numbers of averages equal to the USF. For 10-fold undersampling, the PSNR is increased by 5.1 dB compared with the NUFFT reconstruction, and the SSIM by 24%. These results are confirmed by phantom and in vivo (23)Na measurements in the volunteers that show markedly reduced noise and undersampling artifacts in the case of 3D-DLCS reconstructions. The 3D-DLCS algorithm enables precise reconstruction of undersampled (23)Na MRI data with markedly reduced noise and artifact levels compared with NUFFT reconstruction. Small structures are well preserved. © 2015 Wiley Periodicals, Inc.

The Artificial Hamiltonian, First Integrals, and Closed-Form Solutions of Dynamical Systems for Epidemics

NASA Astrophysics Data System (ADS)

Naz, Rehana; Naeem, Imran

2018-03-01

The non-standard Hamiltonian system, also referred to as a partial Hamiltonian system in the literature, of the form {\\dot q^i} = {partial H}/{partial {p_i}},\\dot p^i = - {partial H}/{partial {q_i}} + {Γ ^i}(t,{q^i},{p_i}) appears widely in economics, physics, mechanics, and other fields. The non-standard (partial) Hamiltonian systems arise from physical Hamiltonian structures as well as from artificial Hamiltonian structures. We introduce the term `artificial Hamiltonian' for the Hamiltonian of a model having no physical structure. We provide here explicitly the notion of an artificial Hamiltonian for dynamical systems of ordinary differential equations (ODEs). Also, we show that every system of second-order ODEs can be expressed as a non-standard (partial) Hamiltonian system of first-order ODEs by introducing an artificial Hamiltonian. This notion of an artificial Hamiltonian gives a new way to solve dynamical systems of first-order ODEs and systems of second-order ODEs that can be expressed as a non-standard (partial) Hamiltonian system by using the known techniques applicable to the non-standard Hamiltonian systems. We employ the proposed notion to solve dynamical systems of first-order ODEs arising in epidemics.

User's guide to computer program CIVM-JET 4B to calculate the transient structural responses of partial and/or complete structural rings to engine-rotor-fragment impact

NASA Technical Reports Server (NTRS)

Stagliano, T. R.; Spilker, R. L.; Witmer, E. A.

1976-01-01

A user-oriented computer program CIVM-JET 4B is described to predict the large-deflection elastic-plastic structural responses of fragment impacted single-layer: (a) partial-ring fragment containment or deflector structure or (b) complete-ring fragment containment structure. These two types of structures may be either free or supported in various ways. Supports accommodated include: (1) point supports such as pinned-fixed, ideally-clamped, or supported by a structural branch simulating mounting-bracket structure and (2) elastic foundation support distributed over selected regions of the structure. The initial geometry of each partial or complete ring may be circular or arbitrarily curved; uniform or variable thicknesses of the structure are accommodated. The structural material is assumed to be initially isotropic; strain hardening and strain rate effects are taken into account.

Modified truncated randomized singular value decomposition (MTRSVD) algorithms for large scale discrete ill-posed problems with general-form regularization

NASA Astrophysics Data System (ADS)

Jia, Zhongxiao; Yang, Yanfei

2018-05-01

In this paper, we propose new randomization based algorithms for large scale linear discrete ill-posed problems with general-form regularization: subject to , where L is a regularization matrix. Our algorithms are inspired by the modified truncated singular value decomposition (MTSVD) method, which suits only for small to medium scale problems, and randomized SVD (RSVD) algorithms that generate good low rank approximations to A. We use rank-k truncated randomized SVD (TRSVD) approximations to A by truncating the rank- RSVD approximations to A, where q is an oversampling parameter. The resulting algorithms are called modified TRSVD (MTRSVD) methods. At every step, we use the LSQR algorithm to solve the resulting inner least squares problem, which is proved to become better conditioned as k increases so that LSQR converges faster. We present sharp bounds for the approximation accuracy of the RSVDs and TRSVDs for severely, moderately and mildly ill-posed problems, and substantially improve a known basic bound for TRSVD approximations. We prove how to choose the stopping tolerance for LSQR in order to guarantee that the computed and exact best regularized solutions have the same accuracy. Numerical experiments illustrate that the best regularized solutions by MTRSVD are as accurate as the ones by the truncated generalized singular value decomposition (TGSVD) algorithm, and at least as accurate as those by some existing truncated randomized generalized singular value decomposition (TRGSVD) algorithms. This work was supported in part by the National Science Foundation of China (Nos. 11771249 and 11371219).

Screening by imaging: scaling up single-DNA-molecule analysis with a novel parabolic VA-TIRF reflector and noise-reduction techniques.

PubMed

van 't Hoff, Marcel; Reuter, Marcel; Dryden, David T F; Oheim, Martin

2009-09-21

Bacteriophage lambda-DNA molecules are frequently used as a scaffold to characterize the action of single proteins unwinding, translocating, digesting or repairing DNA. However, scaling up such single-DNA-molecule experiments under identical conditions to attain statistically relevant sample sizes remains challenging. Additionally the movies obtained are frequently noisy and difficult to analyse with any precision. We address these two problems here using, firstly, a novel variable-angle total internal reflection fluorescence (VA-TIRF) reflector composed of a minimal set of optical reflective elements, and secondly, using single value decomposition (SVD) to improve the signal-to-noise ratio prior to analysing time-lapse image stacks. As an example, we visualize under identical optical conditions hundreds of surface-tethered single lambda-DNA molecules, stained with the intercalating dye YOYO-1 iodide, and stretched out in a microcapillary flow. Another novelty of our approach is that we arrange on a mechanically driven stage several capillaries containing saline, calibration buffer and lambda-DNA, respectively, thus extending the approach to high-content, high-throughput screening of single molecules. Our length measurements of individual DNA molecules from noise-reduced kymograph images using SVD display a 6-fold enhanced precision compared to raw-data analysis, reaching approximately 1 kbp resolution. Combining these two methods, our approach provides a straightforward yet powerful way of collecting statistically relevant amounts of data in a semi-automated manner. We believe that our conceptually simple technique should be of interest for a broader range of single-molecule studies, well beyond the specific example of lambda-DNA shown here.

A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

PubMed Central

Khorshidtalab, Aida; Mesbah, Mostefa; Salami, Momoh J. E.

2015-01-01

In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extraction. The transform defines the mapping as the left singular vectors of the LP coefficient filter impulse response matrix. Using a logistic tree-based model classifier; the extracted features are classified into one of four motor imagery movements. The proposed approach was first benchmarked against two related state-of-the-art feature extraction approaches, namely, discrete cosine transform (DCT) and adaptive autoregressive (AAR)-based methods. By achieving an accuracy of 67.35%, the LP-SVD approach outperformed the other approaches by large margins (25% compared with DCT and 6 % compared with AAR-based methods). To further improve the discriminatory capability of the extracted features and reduce the computational complexity, we enlarged the extracted feature subset by incorporating two extra features, namely, Q- and the Hotelling’s \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$T^{2}$ \\end{document} statistics of the transformed EEG and introduced a new EEG channel selection method. The performance of the EEG classification based on the expanded feature set and channel selection method was compared with that of a number of the state-of-the-art classification methods previously reported with the BCI IIIa competition data set. Our method came second with an average accuracy of 81.38%. PMID:27170898

Progressive deficit in isolated pontine infarction: the association with etiological subtype, lesion topography and outcome.

PubMed

Gökçal, Elif; Niftaliyev, Elvin; Baran, Gözde; Deniz, Çiğdem; Asil, Talip

2017-09-01

It is important to predict progressive deficit (PD) in isolated pontine infarction, a relatively common problem of clinical stroke practice. Traditionally, lacunar infarctions are known with their progressive course. However, few studies have analyzed the branch atheromatous disease subtype as a subtype of lacunar infarction, separately. There are also conflicting results regarding the relationship with the topography of lesion and PD. In this study, we classified etiological subtypes and lesion topography in isolated pontine infarction and aimed to investigate the association of etiological subtypes, lesion topography and clinical outcome with PD. We analyzed demographics, laboratory parameters, and risk factors of 120 patients having isolated pontine infarction and admitted within 24 h retrospectively. PD was defined as an increase in the National Institutes of Health Stroke scale ≥2 units in 5 days after onset. Patients were classified as following: large artery disease (LAA), basilar artery branch disease (BABD) and small vessel disease (SVD). Upper, middle and lower pontine infarcts were identified longitudinally. Functional outcome at 3 months was determined according to modified Rankin scores. Of 120 patients, 41.7% of the patients were classified as BABD, 30.8% as SVD and 27.5% as LAA. 23 patients (19.2%) exhibited PD. PD was significantly more frequent in patient with BABD (p 0.006). PD was numerically higher in patients with lower pontine infarction. PD was associated with BABD and poor functional outcome. It is important to discriminate the BABD neuroradiologically from other stroke subtypes to predict PD which is associated with poor functional outcome in patients with isolated pontine infarctions.

Erasing the Milky Way: New Cleaning Technique Applied to GBT Intensity Mapping Data

NASA Technical Reports Server (NTRS)

Wolz, L.; Blake, C.; Abdalla, F. B.; Anderson, C. J.; Chang, T.-C.; Li, Y.-C.; Masi, K.W.; Switzer, E.; Pen, U.-L.; Voytek, T. C.;

Biomechanics and Biotensegrity: Study Method and Frequency Response of the Simplex and 3-bar-SVD Tensegrity Configurations

NASA Astrophysics Data System (ADS)

Castro Arenas, C.; Ghersi, I.; Miralles, M. T.

2016-04-01

The purpose of this work is to study the frequency response of 3D tensegrity structures. These are structures that have been used, since the 80’s, to model biological systems of different scales. This fact led to the origin of the field of biotensegrity, which includes biomechanics as a natural field of application. In this work: a) A simple method for the analysis of frequency response of different nodes in 3D tensegrity structures was set up and tuned. This method is based on a video-analysis algorithm, which was applied to the structures, as they were vibrated along their axis of symmetry, at frequencies from 1 Hz to 60 Hz. b) Frequency-response analyses were performed, for the simplest 3D structure, the Simplex module, as well as for two towers, formed by stacking two and three Simplex modules, respectively. Resonant frequencies were detected for the Simplex module at (19.2±0.1) Hz and (50.2±0.1) Hz (the latter being an average of frequencies between homologous nodes). For the towers with two and three modules, each selected node presented a characteristic frequency response, modulated by their spatial placement in each model. Resonances for the two-stage tower were found at: (12±0.1) Hz; (16.2±0.1) Hz; (29.4±0.1) Hz and (37.2±0.1) Hz. For the tower with three Simplex modules, the main resonant frequencies were found at (12.0±0.1) Hz and (21.0±0.1) Hz. Results show that the proposed method is adequate for the study (2D) of any 3D tensegrity structure, with the potential of being generalized to the study of oscillations in three dimensions. A growing complexity and variability in the frequency response of the nodes was observed, as modules were added to the structures. These findings were compared to those found in the available literature.

Deriving semantic structure from category fluency: clustering techniques and their pitfalls

PubMed Central

Voorspoels, Wouter; Storms, Gert; Longenecker, Julia; Verheyen, Steven; Weinberger, Daniel R.; Elvevåg, Brita

2013-01-01

Assessing verbal output in category fluency tasks provides a sensitive indicator of cortical dysfunction. The most common metrics are the overall number of words produced and the number of errors. Two main observations have been made about the structure of the output, first that there is a temporal component to it with words being generated in spurts, and second that the clustering pattern may reflect a search for meanings such that the ‘clustering’ is attributable to the activation of a specific semantic field in memory. A number of sophisticated approaches to examining the structure of this clustering have been developed, and a core theme is that the similarity relations between category members will reveal the mental semantic structure of the category underlying an individual’s responses, which can then be visualized by a number of algorithms, such as MDS, hierarchical clustering, ADDTREE, ADCLUS or SVD. Such approaches have been applied to a variety of neurological and psychiatric populations, and the general conclusion has been that the clinical condition systematically distorts the semantic structure in the patients, as compared to the healthy controls. In the present paper we explore this approach to understanding semantic structure using category fluency data. On the basis of a large pool of patients with schizophrenia (n=204) and healthy control participants (n=204), we find that the methods are problematic and unreliable to the extent that it is not possible to conclude that any putative difference reflects a systematic difference between the semantic representations in patients and controls. Moreover, taking into account the unreliability of the methods, we find that the most probable conclusion to be made is that no difference in underlying semantic representation exists. The consequences of these findings to understanding semantic structure, and the use of category fluency data, in cortical dysfunction are discussed. PMID:24275165

hypoDD-A Program to Compute Double-Difference Hypocenter Locations

USGS Publications Warehouse

Waldhauser, Felix

2001-01-01

HypoDD is a Fortran computer program package for relocating earthquakes with the double-difference algorithm of Waldhauser and Ellsworth (2000). This document provides a brief introduction into how to run and use the programs ph2dt and hypoDD to compute double-difference (DD) hypocenter locations. It gives a short overview of the DD technique, discusses the data preprocessing using ph2dt, and leads through the earthquake relocation process using hypoDD. The appendices include the reference manuals for the two programs and a short description of auxiliary programs and example data. Some minor subroutines are presently in the c language, and future releases will be in c. Earthquake location algorithms are usually based on some form of Geiger’s method, the linearization of the travel time equation in a first order Taylor series that relates the difference between the observed and predicted travel time to unknown adjustments in the hypocentral coordinates through the partial derivatives of travel time with respect to the unknowns. Earthquakes can be located individually with this algorithm, or jointly when other unknowns link together the solutions to indivdual earthquakes, such as station corrections in the joint hypocenter determination (JHD) method, or the earth model in seismic tomography. The DD technique (described in detail in Waldhauser and Ellsworth, 2000) takes advantage of the fact that if the hypocentral separation between two earthquakes is small compared to the event-station distance and the scale length of velocity heterogeneity, then the ray paths between the source region and a common station are similar along almost the entire ray path (Fréchet, 1985; Got et al., 1994). In this case, the difference in travel times for two events observed at one station can be attributed to the spatial offset between the events with high accuracy. DD equations are built by differencing Geiger’s equation for earthquake location. In this way, the residual between observed and calculated travel-time difference (or double-difference) between two events at a common station are a related to adjustments in the relative position of the hypocenters and origin times through the partial derivatives of the travel times for each event with respect to the unknown. HypoDD calculates travel times in a layered velocity model (where velocity depends only on depth) for the current hypocenters at the station where the phase was recorded. The double-difference residuals for pairs of earthquakes at each station are minimized by weighted least squares using the method of singular value decomposition (SVD) or the conjugate gradients method (LSQR, Paige and Saunders, 1982). Solutions are found by iteratively adjusting the vector difference between nearby hypocentral pairs, with the locations and partial derivatives being updated after each iteration. Details about the algorithm can be found in Waldhauser and Ellsworth (2000). When the earthquake location problem is linearized using the double-difference equations, the common mode errors cancel, principally those related to the receiver-side structure. Thus we avoid the need for station corrections or high-accuracy of predicted travel times for the portion of the raypath that lies outside the focal volume. This approach is especially useful in regions with a dense distribution of seismicity, i.e. where distances between neighboring events are only a few hundred meters. The improvement of double-difference locations over ordinary JHD locations is shown in Figure 1 for about 10,000 earthquakes that occurred during the 1997 seismic crisis in the Long Valley caldera, California. While the JHD locations (left panel) show a diffuse picture of the seismicity, double-difference locations (right panel) bring structural details such as the location of active fault planes into sharp focus.

Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery

NASA Astrophysics Data System (ADS)

Vishnukumar, S.; Wilscy, M.

2017-12-01

In this paper, we propose a single image Super-Resolution (SR) method based on Compressive Sensing (CS) and Improved Total Variation (TV) Minimization Sparse Recovery. In the CS framework, low-resolution (LR) image is treated as the compressed version of high-resolution (HR) image. Dictionary Training and Sparse Recovery are the two phases of the method. K-Singular Value Decomposition (K-SVD) method is used for dictionary training and the dictionary represents HR image patches in a sparse manner. Here, only the interpolated version of the LR image is used for training purpose and thereby the structural self similarity inherent in the LR image is exploited. In the sparse recovery phase the sparse representation coefficients with respect to the trained dictionary for LR image patches are derived using Improved TV Minimization method. HR image can be reconstructed by the linear combination of the dictionary and the sparse coefficients. The experimental results show that the proposed method gives better results quantitatively as well as qualitatively on both natural and remote sensing images. The reconstructed images have better visual quality since edges and other sharp details are preserved.

The natural oscillation of two types of ENSO events based on analyses of CMIP5 model control runs

NASA Astrophysics Data System (ADS)

Xu, Kang; Su, Jingzhi; Zhu, Congwen

2014-07-01

The eastern- and central-Pacific El Niño-Southern Oscillation (EP- and CP-ENSO) have been found to be dominant in the tropical Pacific Ocean, and are characterized by interannual and decadal oscillation, respectively. In the present study, we defined the EP- and CP-ENSO modes by singular value decomposition (SVD) between SST and sea level pressure (SLP) anomalous fields. We evaluated the natural features of these two types of ENSO modes as simulated by the pre-industrial control runs of 20 models involved in phase five of the Coupled Model Intercomparison Project (CMIP5). The results suggested that all the models show good skill in simulating the SST and SLP anomaly dipolar structures for the EP-ENSO mode, but only 12 exhibit good performance in simulating the tripolar CP-ENSO modes. Wavelet analysis suggested that the ensemble principal components in these 12 models exhibit an interannual and multi-decadal oscillation related to the EP- and CP-ENSO, respectively. Since there are no changes in external forcing in the pre-industrial control runs, such a result implies that the decadal oscillation of CP-ENSO is possibly a result of natural climate variability rather than external forcing.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition.

PubMed

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-03-27

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K -nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction.

Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis.

PubMed

Seghouane, Abd-Krim; Iqbal, Asif

2017-09-01

Sequential dictionary learning algorithms have been successfully applied to functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are, however, structured data matrices with the notions of temporal smoothness in the column direction. This prior information, which can be converted into a constraint of smoothness on the learned dictionary atoms, has seldomly been included in classical dictionary learning algorithms when applied to fMRI data analysis. In this paper, we tackle this problem by proposing two new sequential dictionary learning algorithms dedicated to fMRI data analysis by accounting for this prior information. These algorithms differ from the existing ones in their dictionary update stage. The steps of this stage are derived as a variant of the power method for computing the SVD. The proposed algorithms generate regularized dictionary atoms via the solution of a left regularized rank-one matrix approximation problem where temporal smoothness is enforced via regularization through basis expansion and sparse basis expansion in the dictionary update stage. Applications on synthetic data experiments and real fMRI data sets illustrating the performance of the proposed algorithms are provided.

Amyloidogenesis of Natively Unfolded Proteins

PubMed Central

Uversky, Vladimir N.

2009-01-01

Aggregation and subsequent development of protein deposition diseases originate from conformational changes in corresponding amyloidogenic proteins. The accumulated data support the model where protein fibrillogenesis proceeds via the formation of a relatively unfolded amyloidogenic conformation, which shares many structural properties with the pre-molten globule state, a partially folded intermediate first found during the equilibrium and kinetic (un)folding studies of several globular proteins and later described as one of the structural forms of natively unfolded proteins. The flexibility of this structural form is essential for the conformational rearrangements driving the formation of the core cross-beta structure of the amyloid fibril. Obviously, molecular mechanisms describing amyloidogenesis of ordered and natively unfolded proteins are different. For ordered protein to fibrillate, its unique and rigid structure has to be destabilized and partially unfolded. On the other hand, fibrillogenesis of a natively unfolded protein involves the formation of partially folded conformation; i.e., partial folding rather than unfolding. In this review recent findings are surveyed to illustrate some unique features of the natively unfolded proteins amyloidogenesis. PMID:18537543

Evaluation of the 2-(1-Hexyloxyethyl)-2-devinyl pyropheophorbide (HPPH) mediated photodynamic therapy by macroscopic singlet oxygen modeling [J. Biophotonics 9, No. 11-12, 1344-1354 (2016)].

PubMed

Penjweini, Rozhin; Kim, Michele M; Liu, Baochang; Zhu, Timothy C

2017-03-01

In the article by R. Penjweini, M. M. Kim et al. (doi: 10.1002/jbio.201600121), published in J. Biophotonics 9, 1344-1354 (2016), the constants C 01 , C 02 , b 1 , and b 2 determined from fitting the fluorescence single value decomposition (SVD) for phantoms with different optical properties and the corresponding Figure 2(a) are not correct. This erratum is published to correct the Section 2.3 and Figure 2(a). © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

ENSO related variability in the Southern Hemisphere, 1948-2000

NASA Astrophysics Data System (ADS)

Ribera, Pedro; Mann, Michael E.

2003-01-01

The spatiotemporal evolution of Southern Hemisphere climate variability is diagnosed based on the use of the NCEP reanalysis (1948-2000) dataset. Using the MTM-SVD analysis method, significant narrowband variability is isolated from the multi-variate dataset. It is found that the ENSO signal exhibits statistically significant behavior at quasiquadrennial (3-6 yr) timescales for the full time-period. A significant quasibiennial (2-3 yr) timescales emerges only for the latter half of period. Analyses of the spatial evolution of the two reconstructed signals shed additional light on linkages between low and high-latitude Southern Hemisphere climate anomalies.

Linear optics measurements and corrections using an AC dipole in RHIC

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

Wang, G.; Bai, M.; Yang, L.

2010-05-23

We report recent experimental results on linear optics measurements and corrections using ac dipole. In RHIC 2009 run, the concept of the SVD correction algorithm is tested at injection energy for both identifying the artificial gradient errors and correcting it using the trim quadrupoles. The measured phase beatings were reduced by 30% and 40% respectively for two dedicated experiments. In RHIC 2010 run, ac dipole is used to measure {beta}* and chromatic {beta} function. For the 0.65m {beta}* lattice, we observed a factor of 3 discrepancy between model and measured chromatic {beta} function in the yellow ring.

Using dynamic mode decomposition for real-time background/foreground separation in video

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

Kutz, Jose Nathan; Grosek, Jacob; Brunton, Steven

The technique of dynamic mode decomposition (DMD) is disclosed herein for the purpose of robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. Foreground/background separation is achieved at the computational cost of just one singular value decomposition (SVD) and one linear equation solve, thus producing results orders of magnitude faster than robust principal component analysis (RPCA). Additional techniques, including techniques for analyzing the video for multi-resolution time-scale components, and techniques for reusing computations to allow processing of streaming video in real time, are also described herein.

Developing silvicultural systems based on partial cutting in western hemlock–Sitka spruce stands of southeast Alaska.

Treesearch

Robert L. Deal; J.C. Tappeiner; Paul E. Hennon

2002-01-01

The effects of partial cutting on species composition, stand structure and growth, tree size distribution, and tree disease and mortality were evaluated on 73 plots in 18 stands that were harvested 12–96 years ago in southeast Alaska. Partially-cut stands had diverse and highly complex stand structures similar to uncut stands. Sitka spruce was maintained in mixed...

11. DETAIL VIEW OF DAM 87, SHOWING STOPLOG STRUCTURE (PARTIALLY ...

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

11. DETAIL VIEW OF DAM 87, SHOWING STOPLOG STRUCTURE (PARTIALLY HIDDEN BY MARSH GRASSES IN LOWER PART OF PHOTO) AT RIGHT (WEST) END OF SPILLWAY - Upper Souris National Wildlife Refuge, Dam 87, Souris River Basin, Foxholm, Surrey (England), ND

Salt bridge as a gatekeeper against partial unfolding.

PubMed

Hinzman, Mark W; Essex, Morgan E; Park, Chiwook

2016-05-01

Salt bridges are frequently observed in protein structures. Because the energetic contribution of salt bridges is strongly dependent on the environmental context, salt bridges are believed to contribute to the structural specificity rather than the stability. To test the role of salt bridges in enhancing structural specificity, we investigated the contribution of a salt bridge to the energetics of native-state partial unfolding in a cysteine-free version of Escherichia coli ribonuclease H (RNase H*). Thermolysin cleaves a protruding loop of RNase H(*) through transient partial unfolding under native conditions. Lys86 and Asp108 in RNase H(*) form a partially buried salt bridge that tethers the protruding loop. Investigation of the global stability of K86Q/D108N RNase H(*) showed that the salt bridge does not significantly contribute to the global stability. However, K86Q/D108N RNase H(*) is greatly more susceptible to proteolysis by thermolysin than wild-type RNase H(*) is. The free energy for partial unfolding determined by native-state proteolysis indicates that the salt bridge significantly increases the energy for partial unfolding by destabilizing the partially unfolded form. Double mutant cycles with single and double mutations of the salt bridge suggest that the partially unfolded form is destabilized due to a significant decrease in the interaction energy between Lys86 and Asp108 upon partial unfolding. This study demonstrates that, even in the case that a salt bridge does not contribute to the global stability, the salt bridge may function as a gatekeeper against partial unfolding that disturbs the optimal geometry of the salt bridge. © 2016 The Protein Society.

Structure and energetics of extended defects in ice Ih

NASA Astrophysics Data System (ADS)

Silva Junior, Domingos L.; de Koning, Maurice

2012-01-01

We consider the molecular structure and energetics of extended defects in proton-disordered hexagonal ice Ih. Using plane-wave density functional theory (DFT) calculations, we compute the energetics of stacking faults and determine the structure of the 30∘ and 90∘ partial dislocations on the basal plane. Consistent with experimental data, the formation energies of all fully reconstructed stacking faults are found to be very low. This is consistent with the idea that basal-plane glide dislocations in ice Ih are dissociated into partial dislocations separated by an area of stacking fault. For both types of partial dislocation we find a strong tendency toward core reconstruction through pairwise hydrogen-bond reformation. In the case of the 30∘ dislocation, the pairwise hydrogen-bond formation leads to a period-doubling core structure equivalent to that seen in zinc-blende semiconductor crystals. For the 90∘ partial we consider two possible core reconstructions, one in which the periodicity of the structure along the core remains unaltered and another in which it is doubled. The latter is preferred, although the energy difference between both is rather small, so that a coexistence of both reconstructions appears plausible. Our results imply that a mobility theory for dislocations on the basal plane in ice Ih should be based on the idea of reconstructed partial dislocations.

Kinetics of proton uptake and dye binding by photoactive yellow protein in wild type and in the E46Q and E46A mutants.

PubMed

Borucki, Berthold; Devanathan, Savitha; Otto, Harald; Cusanovich, Michael A; Tollin, Gordon; Heyn, Maarten P

2002-08-06

We studied the kinetics of proton uptake and release by photoactive yellow protein (PYP) from Ectothiorhodospira halophila in wild type and the E46Q and E46A mutants by transient absorption spectroscopy with the pH-indicator dyes bromocresol purple or cresol red in unbuffered solution. In parallel, we investigated the kinetics of chromophore protonation as monitored by the rise and decay of the blue-shifted state I(2) (lambda(max) = 355 nm). For wild type the proton uptake kinetics is synchronized with the fast phase of I(2) formation (tau = 500 micros at pH 6.2). The transient absorption signal from the dye also contains a slower component which is not due to dye deprotonation but is caused by dye binding to a hydrophobic patch that is transiently exposed in the structurally changed and partially unfolded I(2) intermediate. This conclusion is based on the wavelength, pH, and concentration dependence of the dye signal and on dye measurements in the presence of buffer. SVD analysis, moreover, indicates the presence of two components in the dye signal: protonation and dye binding. The dye binding has a rise time of about 4 ms and is coupled kinetically with a transition between two I(2) intermediates. In the mutant E46Q, which lacks the putative internal proton donor E46, the formation of I(2) is accelerated, but the proton uptake kinetics remains kinetically coupled to the fast phase of I(2) formation (tau = 100 micros at pH 6.3). For this mutant the protein conformational change, as monitored by the dye binding, occurs with about the same time constant as in wild type but with reduced amplitude. In the alkaline form of the mutant E46A the formation of the I(2)-like intermediate is even faster as is the proton uptake (tau = 20 micros at pH 8.3). No dye binding occurred in E46A, suggesting the absence of a conformational change. In all of the systems proton release is synchronized with the decay of I(2). Our results support mechanisms in which the chromophore of PYP is protonated directly from the external medium rather than by the internal donor E46.

Dose reduction assessment in dynamic CT myocardial perfusion imaging in a porcine balloon-induced-ischemia model

NASA Astrophysics Data System (ADS)

Fahmi, Rachid; Eck, Brendan L.; Vembar, Mani; Bezerra, Hiram G.; Wilson, David L.

2014-03-01

We investigated the use of an advanced hybrid iterative reconstruction (IR) technique (iDose4, Philips Health- care) for low dose dynamic myocardial CT perfusion (CTP) imaging. A porcine model was created to mimic coronary stenosis through partial occlusion of the left anterior descending (LAD) artery with a balloon catheter. The severity of LAD occlusion was adjusted with FFR measurements. Dynamic CT images were acquired at end-systole (45% R-R) using a multi-detector CT (MDCT) scanner. Various corrections were applied to the acquired scans to reduce motion and imaging artifacts. Absolute myocardial blood flow (MBF) was computed with a deconvolution-based approach using singular value decomposition (SVD). We compared a high and a low dose radiation protocol corresponding to two different tube-voltage/tube-current combinations (80kV p/100mAs and 120kV p/150mAs). The corresponding radiation doses for these protocols are 7.8mSv and 34.3mSV , respectively. The images were reconstructed using conventional FBP and three noise-reduction strengths of the IR method, iDose. Flow contrast-to-noise ratio, CNRf, as obtained from MBF maps, was used to quantitatively evaluate the effect of reconstruction on contrast between normal and ischemic myocardial tissue. Preliminary results showed that the use of iDose to reconstruct low dose images provide better or comparable CNRf to that of high dose images reconstructed with FBP, suggesting significant dose savings. CNRf was improved with the three used levels of iDose compared to FBP for both protocols. When using the entire 4D dynamic sequence for MBF computation, a 77% dose reduction was achieved, while considering only half the scans (i.e., every other heart cycle) allowed even further dose reduction while maintaining relatively higher CNRf.

Exploring cartilage damage in gout using 3-T MRI: distribution and associations with joint inflammation and tophus deposition.

PubMed

Popovich, I; Dalbeth, N; Doyle, A; Reeves, Q; McQueen, F M

2014-07-01

Few imaging studies have investigated cartilage in gout. Magnetic resonance imaging (MRI) can image cartilage damage and also reveals other features of gouty arthropathy. The objective was to develop and validate a system for quantifying cartilage damage in gout. 3-T MRI scans of the wrist were obtained in 40 gout patients. MRI cartilage damage was quantified using an adaptation of the radiographic Sharp van der Heijde score. Two readers scored cartilage loss at 7 wrist joints: 0 (normal), 1 (partial narrowing), 2 (complete narrowing) and concomitant osteoarthritis was recorded. Bone erosion, bone oedema and synovitis were scored (RAMRIS) and tophi were assessed. Correlations between radiographic and MRI cartilage scores were investigated, as was the reliability of the MRI cartilage score and its associations. The GOut MRI Cartilage Score (GOMRICS) was highly correlated with the total Sharp van der Heijde (SvdH) score and the joint space narrowing component (R = 0.8 and 0.71 respectively, p < 0.001). Reliability was high (intraobserver, interobserver ICCs = 0.87 [0.57-0.97], 0.64 [0.41-0.79] respectively), and improved on unenhanced scans; interobserver ICC = 0.82 [0.49-0.95]. Cartilage damage was predominantly focal (82% of lesions) and identified in 40 out of 280 (14%) of joints. Cartilage scores correlated with bone erosion (R = 0.57), tophus size (R = 0.52), and synovitis (R = 0.55), but not bone oedema scores. Magnetic resonance imaging can be used to investigate cartilage in gout. Cartilage damage was relatively uncommon, focal, and associated with bone erosions, tophi and synovitis, but not bone oedema. This emphasises the unique pathophysiology of gout.

Contribution for new genetic markers of rheumatoid arthritis activity and severity: sequencing of the tumor necrosis factor-alpha gene promoter.

PubMed

Fonseca, João Eurico; Cavaleiro, João; Teles, José; Sousa, Elsa; Andreozzi, Valeska L; Antunes, Marília; Amaral-Turkman, Maria A; Canhão, Helena; Mourão, Ana F; Lopes, Joana; Caetano-Lopes, Joana; Weinmann, Pamela; Sobral, Marta; Nero, Patrícia; Saavedra, Maria J; Malcata, Armando; Cruz, Margarida; Melo, Rui; Braña, Araceli; Miranda, Luis; Patto, José V; Barcelos, Anabela; da Silva, José Canas; Santos, Luís M; Figueiredo, Guilherme; Rodrigues, Mário; Jesus, Herberto; Quintal, Alberto; Carvalho, Teresa; da Silva, José A Pereira; Branco, Jaime; Queiroz, Mário Viana

2007-01-01

The objective of this study was to assess whether clinical measures of rheumatoid arthritis activity and severity were influenced by tumor necrosis factor-alpha (TNF-alpha) promoter genotype/haplotype markers. Each patient's disease activity was assessed by the disease activity score using 28 joint counts (DAS28) and functional capacity by the Health Assessment Questionnaire (HAQ) score. Systemic manifestations, radiological damage evaluated by the Sharp/van der Heijde (SvdH) score, disease-modifying anti-rheumatic drug use, joint surgeries, and work disability were also assessed. The promoter region of the TNF-alpha gene, between nucleotides -1,318 and +49, was sequenced using an automated platform. Five hundred fifty-four patients were evaluated and genotyped for 10 single-nucleotide polymorphism (SNP) markers, but 5 of these markers were excluded due to failure to fall within Hardy-Weinberg equilibrium or to monomorphism. Patients with more than 10 years of disease duration (DD) presented significant associations between the -857 SNP and systemic manifestations, as well as joint surgeries. Associations were also found between the -308 SNP and work disability in patients with more than 2 years of DD and radiological damage in patients with less than 10 years of DD. A borderline effect was found between the -238 SNP and HAQ score and radiological damage in patients with 2 to 10 years of DD. An association was also found between haplotypes and the SvdH score for those with more than 10 years of DD. An association was found between some TNF-alpha promoter SNPs and systemic manifestations, radiological progression, HAQ score, work disability, and joint surgeries, particularly in some classes of DD and between haplotypes and radiological progression for those with more than 10 years of DD.

Contribution for new genetic markers of rheumatoid arthritis activity and severity: sequencing of the tumor necrosis factor-alpha gene promoter

PubMed Central

Fonseca, João Eurico; Cavaleiro, João; Teles, José; Sousa, Elsa; Andreozzi, Valeska L; Antunes, Marília; Amaral-Turkman, Maria A; Canhão, Helena; Mourão, Ana F; Lopes, Joana; Caetano-Lopes, Joana; Weinmann, Pamela; Sobral, Marta; Nero, Patrícia; Saavedra, Maria J; Malcata, Armando; Cruz, Margarida; Melo, Rui; Braña, Araceli; Miranda, Luis; Patto, José V; Barcelos, Anabela; da Silva, José Canas; Santos, Luís M; Figueiredo, Guilherme; Rodrigues, Mário; Jesus, Herberto; Quintal, Alberto; Carvalho, Teresa; da Silva, José A Pereira; Branco, Jaime; Queiroz, Mário Viana

2007-01-01

The objective of this study was to assess whether clinical measures of rheumatoid arthritis activity and severity were influenced by tumor necrosis factor-alpha (TNF-α) promoter genotype/haplotype markers. Each patient's disease activity was assessed by the disease activity score using 28 joint counts (DAS28) and functional capacity by the Health Assessment Questionnaire (HAQ) score. Systemic manifestations, radiological damage evaluated by the Sharp/van der Heijde (SvdH) score, disease-modifying anti-rheumatic drug use, joint surgeries, and work disability were also assessed. The promoter region of the TNF-α gene, between nucleotides -1,318 and +49, was sequenced using an automated platform. Five hundred fifty-four patients were evaluated and genotyped for 10 single-nucleotide polymorphism (SNP) markers, but 5 of these markers were excluded due to failure to fall within Hardy-Weinberg equilibrium or to monomorphism. Patients with more than 10 years of disease duration (DD) presented significant associations between the -857 SNP and systemic manifestations, as well as joint surgeries. Associations were also found between the -308 SNP and work disability in patients with more than 2 years of DD and radiological damage in patients with less than 10 years of DD. A borderline effect was found between the -238 SNP and HAQ score and radiological damage in patients with 2 to 10 years of DD. An association was also found between haplotypes and the SvdH score for those with more than 10 years of DD. An association was found between some TNF-α promoter SNPs and systemic manifestations, radiological progression, HAQ score, work disability, and joint surgeries, particularly in some classes of DD and between haplotypes and radiological progression for those with more than 10 years of DD. PMID:17408492

Polygenic overlap between kidney function and large artery atherosclerotic stroke

PubMed Central

Holliday, Elizabeth G.; Traylor, Matthew; Malik, Rainer; Bevan, Stephen; Maguire, Jane; Koblar, Simon A.; Sturm, Jonathan; Hankey, Graeme J.; Oldmeadow, Christopher; McEvoy, Mark; Sudlow, Cathie; Rothwell, Peter M.; Coresh, Josef; Hamet, Pavel; Tremblay, Johanne; Turner, Stephen T.; de Andrade, Mariza; Rao, Madhumathi; Schmidt, Reinhold; Crick, Peter A.; Robino, Antonietta; Peralta, Carmen A.; Jukema, J. Wouter; Mitchell, Paul; Rosas, Sylvia E.; Wang, Jie Jin; Scott, Rodney J.; Dichgans, Martin; Mitchell, Braxton D.; Linda Kao, W. H.; Fox, Caroline S.; Levi, Christopher; Attia, John; Markus, Hugh S

2014-01-01

Background and Purpose Epidemiological studies show strong associations between kidney dysfunction and risk of ischaemic stroke, the mechanisms of which are incompletely understood. We investigated whether these associations may reflect shared heritability due to a common polygenic basis and whether this differed for ischaemic stroke subtypes. Methods Polygenic models were derived using GWAS meta-analysis results for three kidney traits: estimated glomerular filtration rate using serum creatinine (eGFRcrea: N=73,998), eGFR using cystatin C (eGFRcys: N=22,937) and urinary albumin to creatinine ratio (UACR: N=31,580). For each, SNPs passing ten P-value thresholds were used to form profile scores in 4,561 ischaemic stroke cases and 7,094 controls from the UK, Germany and Australia. Scores were tested for association with ischaemic stroke and its three aetiological subtypes: large artery atherosclerosis (LAA), cardioembolism (CE) and small vessel disease (SVD). Results Polygenic scores correlating with higher eGFRcrea were associated with reduced risk of LAA, with five scores reaching P<0.05 (peak P=0.004) and all showing the epidemiologically expected direction of effect. A similar pattern was observed for polygenic scores reflecting higher UACR, of which three associated with LAA (peak P=0.01) and all showed the expected directional association. One UACR-based score also associated with SVD (P=0.03). The global pattern of results was unlikely to have occurred by chance (P=0.02). Conclusions This study suggests possible polygenic correlation between renal dysfunction and ischaemic stroke. The shared genetic components may be specific to stroke subtypes, particularly large artery atherosclerotic stroke. Further study of the genetic relationships between these disorders appears merited. PMID:25352485

Assessment of the Performance of a Scanning Wind Doppler Lidar at an Urban-Mountain Site in Seoul

NASA Astrophysics Data System (ADS)

Park, S.; Kim, S. W.

2017-12-01

Winds in the planetary boundary layer (PBL) are important factors for accurate modelling of air quality, numerical weather prediction and conversion of satellite measurements to near-surface air quality information (Seibert et al., AE, 2000; Emeis et al., Meteorol. Z., 2008). In this study, we (1) evaluate wind speed (WS) and direction (WD) retrieved from Wind Doppler Lidar (WDL) measurements by two methods [so called, `sine-fitting (SF) method' and `singular value decomposition (SVD) method'] and (2) analyze the WDL data at Seoul National University (SNU), Seoul, to investigate the diurnal evolution of winds and aerosol characteristics in PBL. Evaluation of the two methods used in retrieving wind from radial velocity was done through comparison with radiosonde soundings from the same site. Winds retrieved using the SVD method from mean radial velocity of 15 minutes showed good agreement with radiosonde profiles (i.e., bias of 0.03 m s-1 and root mean square of 1.70 m s-1 in WS). However, the WDL was found to have difficulty retrieving signals under clean conditions (i.e., too small signal to noise ratio) or under the presence of near-surface optically-thick aerosol/cloud layer (i.e., strong signal attenuation). Despite this shortcoming, the WDL was able to successfully capture the diurnal variation of PBL wind. Two major wind patterns were observed at SNU; first of all, when convective boundary layer was strongly developed, thermally induced winds with large variation of vertical WS in the afternoon and a diurnal variation in WD showing characteristics of mountain and valley winds were observed. Secondly, small variation in WS and WD throughout the day was a major characteristic of cases when wind was largely influenced by the synoptic weather pattern.

Using DTI to assess white matter microstructure in cerebral small vessel disease (SVD) in multicentre studies

PubMed Central

Croall, Iain D.; Lohner, Valerie; Moynihan, Barry; Khan, Usman; Hassan, Ahamad; O’Brien, John T.; Morris, Robin G.; Tozer, Daniel J.; Cambridge, Victoria C.; Harkness, Kirsty; Werring, David J.; Blamire, Andrew M.; Ford, Gary A.; Barrick, Thomas R.

2017-01-01

Diffusion tensor imaging (DTI) metrics such as fractional anisotropy (FA) and mean diffusivity (MD) have been proposed as clinical trial markers of cerebral small vessel disease (SVD) due to their associations with outcomes such as cognition. However, studies investigating this have been predominantly single-centre. As clinical trials are likely to be multisite, further studies are required to determine whether associations with cognition of similar strengths can be detected in a multicentre setting. One hundred and nine patients (mean age =68 years) with symptomatic lacunar infarction and confluent white matter hyperintensities (WMH) on MRI was recruited across six sites as part of the PRESERVE DTI substudy. After handling missing data, 3T-MRI scanning was available from five sites on five scanner models (Siemens and Philips), alongside neuropsychological and quality of life (QoL) assessments. FA median and MD peak height were extracted from DTI histogram analysis. Multiple linear regressions were performed, including normalized brain volume, WMH lesion load, and n° lacunes as covariates, to investigate the association of FA and MD with cognition and QoL. DTI metrics from all white matter were significantly associated with global cognition (standardized β =0.268), mental flexibility (β =0.306), verbal fluency (β =0.376), and Montreal Cognitive Assessment (MoCA) (β =0.273). The magnitudes of these associations were comparable with those previously reported from single-centre studies found in a systematic literature review. In this multicentre study, we confirmed associations between DTI parameters and cognition, which were similar in strength to those found in previous single-centre studies. The present study supports the use of DTI metrics as biomarkers of disease progression in multicentre studies. PMID:28487471

GRACE RL03-v2 monthly time series of solutions from CNES/GRGS

NASA Astrophysics Data System (ADS)

Lemoine, Jean-Michel; Bourgogne, Stéphane; Bruinsma, Sean; Gégout, Pascal; Reinquin, Franck; Biancale, Richard

2015-04-01

Based on GRACE GPS and KBR Level-1B.v2 data, as well as on LAGEOS-1/2 SLR data, CNES/GRGS has published in 2014 the third full re-iteration of its GRACE gravity field solutions. This monthly time series of solutions, named RL03-v1, complete to spherical harmonics degree/order 80, has displayed interesting performances in terms of spatial resolution and signal amplitude compared to JPL/GFZ/CSR RL05. This is due to a careful selection of the background models (FES2014 ocean tides, ECMWF ERA-interim (atmosphere) and TUGO (non IB-ocean) "dealiasing" models every 3 hours) and to the choice of an original method for gravity field inversion : truncated SVD. Identically to the previous CNES/GRGS releases, no additional filtering of the solutions is necessary before using them. Some problems have however been identified in CNES/GRGS RL03-v1: - an erroneous mass signal located in two small circular rings close to the Earth's poles, leading to the recommendation not to use RL03-v1 above 82° latitudes North and South; - a weakness in the sectorials due to an excessive downweighting of the GRACE GPS observations. These two problems have been understood and addressed, leading to the computation of a corrected time series of solutions, RL03-v2. The corrective steps have been: - to strengthen the determination of the very low degrees by adding Starlette and Stella SLR data to the normal equations; - to increase the weight of the GRACE GPS observations; - to adopt a two steps approach for the computation of the solutions: first a Choleski inversion for the low degrees, followed by a truncated SVD solution. The identification of these problems will be discussed and the performance of the new time series evaluated.

A population neuroscience approach to the study of cerebral small vessel disease in mid- and late-life: an Invited Review.

PubMed

Jorgensen, Dana R; Shaaban, C Elizabeth; Wiley, Clayton A; Gianaros, Peter J; Mettenburg, Joseph; Rosano, Caterina

2018-02-02

Aging in later life engenders numerous changes to the cerebral microvasculature. Such changes can remain clinically silent, but are associated with greater risk for negative health outcomes over time. Knowledge is limited about the pathogenesis, prevention, and treatment of potentially detrimental changes in the cerebral microvasculature that occur with advancing age. In this review, we summarize literature on aging of the cerebral microvasculature, and we propose a conceptual framework to fill existing research gaps and advance future work on this heterogeneous phenomenon. We propose that the major gaps in this area are attributable to an incomplete characterization of cerebrovascular pathology, the populations being studied, and the temporality of exposure to risk factors. Specifically, currently available measures of age-related cerebral microvasculature changes are indirect, primarily related to parenchymal damage rather than direct quantification of small vessel damage-limiting the understanding of cerebral small vessel disease (cSVD) itself. Moreover, studies seldom account for variability in the health-related conditions or interactions with risk factors, which are likely determinants of cSVD pathogenesis. Lastly, study designs are predominantly cross-sectional, and/or have relied on single time point measures, leaving no clear evidence of time trajectories of risk factors or of change in cerebral microvasculature. We argue that more resources should be invested in (1) developing methodological approaches and basic science models to better understand the pathogenic and etiological nature of age-related brain microvascular diseases, and (2) implementing state-of-the-science population study designs that account for the temporal evolution of cerebral microvascular changes in diverse populations across the life-span.

Grouping Parturients by Parity, Previous-Cesarean, and Mode of Delivery (P-C-MoD Classification) Better Identifies Groups at Risk for Postpartum Hemorrhage.

PubMed

Reichman, Orna; Gal, Micahel; Sela, Hen Y; Khayyat, Izzat; Emanuel, Michael; Samueloff, Arnon

2016-10-01

Objective We aimed to create a clinical classification to better identify parturients at risk for postpartum hemorrhage (PPH). Method A retrospective cohort, including all women who delivered at a single tertiary care medical center, between 2006 and 2014. Parturients were grouped by parity and history of cesarean delivery (CD): primiparas, multipara, and multipara with previous CD. Each were further subgrouped by mode of delivery (spontaneous vaginal delivery [SVD], operative vaginal delivery [OVD], emergency or elective CD). In all, 12 subgroups, based on parity, previous cesarean, and mode of delivery, formed the P-C-MoD classification. PPH was defined as a decrease of ≥3 gram% hemoglobin from admission and/or transfusion of blood products. Univariate analysis followed by multivariate analysis was performed to assess risk for PPH, controlling for confounders. Results The crude rate of PPH among 126,693 parturients was 7%. The prevalence differed significantly among independent risk factors: primiparity, 14%; multiparity, 4%; OVD, 22%; and CD, 15%. The P-C-MoD classification, segregated better between parturients at risk for PPH. The prevalence of PPH was highest for primiparous undergoing OVD (27%) compared with multiparous with SVD (3%), odds ratio [OR] = 12.8 (95% confidence interval [CI],11.9-13.9). These finding were consistent in the multivariate analysis OR = 13.1 (95% CI,12.1-14.3). Conclusion Employing the P-C-MoD classification more readily identifies parturients at risk for PPH and is superior to estimations based on single risk factors. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Systematic Constraint Selection Strategy for Rate-Controlled Constrained-Equilibrium Modeling of Complex Nonequilibrium Chemical Kinetics

NASA Astrophysics Data System (ADS)

Beretta, Gian Paolo; Rivadossi, Luca; Janbozorgi, Mohammad

2018-04-01

Rate-Controlled Constrained-Equilibrium (RCCE) modeling of complex chemical kinetics provides acceptable accuracies with much fewer differential equations than for the fully Detailed Kinetic Model (DKM). Since its introduction by James C. Keck, a drawback of the RCCE scheme has been the absence of an automatable, systematic procedure to identify the constraints that most effectively warrant a desired level of approximation for a given range of initial, boundary, and thermodynamic conditions. An optimal constraint identification has been recently proposed. Given a DKM with S species, E elements, and R reactions, the procedure starts by running a probe DKM simulation to compute an S-vector that we call overall degree of disequilibrium (ODoD) because its scalar product with the S-vector formed by the stoichiometric coefficients of any reaction yields its degree of disequilibrium (DoD). The ODoD vector evolves in the same (S-E)-dimensional stoichiometric subspace spanned by the R stoichiometric S-vectors. Next we construct the rank-(S-E) matrix of ODoD traces obtained from the probe DKM numerical simulation and compute its singular value decomposition (SVD). By retaining only the first C largest singular values of the SVD and setting to zero all the others we obtain the best rank-C approximation of the matrix of ODoD traces whereby its columns span a C-dimensional subspace of the stoichiometric subspace. This in turn yields the best approximation of the evolution of the ODoD vector in terms of only C parameters that we call the constraint potentials. The resulting order-C RCCE approximate model reduces the number of independent differential equations related to species, mass, and energy balances from S+2 to C+E+2, with substantial computational savings when C ≪ S-E.

Absorption spectrum analysis based on singular value decomposition for photoisomerization and photodegradation in organic dyes

NASA Astrophysics Data System (ADS)

Kawabe, Yutaka; Yoshikawa, Toshio; Chida, Toshifumi; Tada, Kazuhiro; Kawamoto, Masuki; Fujihara, Takashi; Sassa, Takafumi; Tsutsumi, Naoto

2015-10-01

In order to analyze the spectra of inseparable chemical mixtures, many mathematical methods have been developed to decompose them into the components relevant to species from series of spectral data obtained under different conditions. We formulated a method based on singular value decomposition (SVD) of linear algebra, and applied it to two example systems of organic dyes, being successful in reproducing absorption spectra assignable to cis/trans azocarbazole dyes from the spectral data after photoisomerization and to monomer/dimer of cyanine dyes from those during photodegaradation process. For the example of photoisomerization, polymer films containing the azocarbazole dyes were prepared, which have showed updatable holographic stereogram for real images with high performance. We made continuous monitoring of absorption spectrum after optical excitation and found that their spectral shapes varied slightly after the excitation and during recovery process, of which fact suggested the contribution from a generated photoisomer. Application of the method was successful to identify two spectral components due to trans and cis forms of azocarbazoles. Temporal evolution of their weight factors suggested important roles of long lifetimed cis states in azocarbazole derivatives. We also applied the method to the photodegradation of cyanine dyes doped in DNA-lipid complexes which have shown efficient and durable optical amplification and/or lasing under optical pumping. The same SVD method was successful in the extraction of two spectral components presumably due to monomer and H-type dimer. During the photodegradation process, absorption magnitude gradually decreased due to decomposition of molecules and their decaying rates strongly depended on the spectral components, suggesting that the long persistency of the dyes in DNA-complex related to weak tendency of aggregate formation.

Baseline serum level of matrix metalloproteinase-3 as a biomarker of progressive joint damage in rheumatoid arthritis patients.

PubMed

Galil, Sahar Mahfouz Abdel; El-Shafey, Abeer Mohamed; Hagrass, Hoda A; Fawzy, Faten; Sammak, Ahmed El

2016-04-01

Matrix metalloproteinase-3 (MMP-3) plays a pivotal role in the destruction of bone and degradation of cartilage components in rheumatoid arthritis (RA). We aimed in this study to analyze the relation between baseline levels of MMP-3 and the progression of joint damage in RA. Eighty-one untreated RA patients with joint symptoms for <1 year were evaluated at baseline and after 12 months as regards erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), rheumatoid factor (RF), anti-cyclic citrullinated peptide (anti-CCP) and plain X-ray of both hands and wrists. Baseline levels of MMP-3 were measured by enzyme-linked immunosorbent assay and magnetic resonance imaging (MRI) of hands/wrists was performed. Disease Activity Score (DAS28) and Health Assessment Questionnaire (HAQ) were performed at baseline evaluation and after 12 months. The baseline MMP-3 levels were significantly higher in the high-progression group compared with the low-progression one (95.75 ± 42.84 vs. 50.45 ± 12.83, P < 0.001). There was a positive correlation between baseline levels of MMP-3 and MRI erosion score and other baseline clinical parameters, except for HAQ and the van der Heijde modification of the Sharp scoring system (SvdH) scores, while after 12 months, there were high positive correlations between MMP-3 and SvdH score, as well as all parameters except for ESR. Serum baseline levels of MMP-3 are strong prognostic markers of disease activity, and act well as an early predictor of progressive joint damage in recent-onset RA disease. © 2014 Asia Pacific League of Associations for Rheumatology and Wiley Publishing Asia Pty Ltd.

Application of global sensitivity analysis methods to Takagi-Sugeno-Kang rainfall-runoff fuzzy models

NASA Astrophysics Data System (ADS)

Jacquin, A. P.; Shamseldin, A. Y.

2009-04-01

This study analyses the sensitivity of the parameters of Takagi-Sugeno-Kang rainfall-runoff fuzzy models previously developed by the authors. These models can be classified in two types, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity in the rainfall-runoff relationship. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis (RSA) and Sobol's Variance Decomposition (SVD). In general, the RSA method has the disadvantage of not being able to detect sensitivities arising from parameter interactions. By contrast, the SVD method is suitable for analysing models where the model response surface is expected to be affected by interactions at a local scale and/or local optima, such as the case of the rainfall-runoff fuzzy models analysed in this study. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of two measures of goodness of fit, assessing the model performance from different points of view. These measures are the Nash-Sutcliffe criterion and the index of volumetric fit. The results of the study show that the sensitivity of the model parameters depends on both the type of non-linear effects (i.e. changes in catchment wetness or seasonality) that dominates the catchment's rainfall-runoff relationship and the measure used to assess the model performance. Acknowledgements: This research was supported by FONDECYT, Research Grant 11070130. We would also like to express our gratitude to Prof. Kieran M. O'Connor from the National University of Ireland, Galway, for providing the data used in this study.

Partially coherent axiconic surface plasmon polariton fields

NASA Astrophysics Data System (ADS)

Chen, Yahong; Norrman, Andreas; Ponomarenko, Sergey A.; Friberg, Ari T.

2018-04-01

We introduce a class of structured polychromatic surface electromagnetic fields, reminiscent of conventional optical axicon fields, through a judicious superposition of partially correlated surface plasmon polaritons. We show that such partially coherent axiconic surface plasmon polariton fields are structurally stable and statistically highly versatile with regard to spectral density, polarization state, energy flow, and degree of coherence. These fields can be created by plasmon coherence engineering and may prove instrumental broadly in surface physics and in various nanophotonics applications.

Effect of O 2 gas partial pressure on structures and dielectric characteristics of rf sputtered ZrO 2 thin films

NASA Astrophysics Data System (ADS)

Ma, C. Y.; Lapostolle, F.; Briois, P.; Zhang, Q. Y.

2007-08-01

Amorphous and polycrystalline zirconium oxide thin films have been deposited by reactive rf magnetron sputtering in a mixed argon/oxygen or pure oxygen atmosphere with no intentional heating of the substrate. The films were characterized by high-resolution transmission electron microscopy (HR-TEM), atomic force microscopy (AFM), spectroscopic ellipsometry (SE), and capacitance versus voltage ( C- V) measurements to investigate the variation of structure, surface morphology, thickness of SiO 2-like interfacial layer as well as dielectric characteristics with different oxygen partial pressures. The films deposited at low oxygen partial pressures (less than 15%) are amorphous and dense with a smooth surface. In contrast, the films prepared at an oxygen partial pressure higher than 73% are crystallized with the microstructure changing from the mixture of monoclinic and tetragonal phases to a single monoclinic structure. The film structural transition is believed to be consequences of decrease in the oxygen vacancy concentration in the film and of increase of the energetically neutral particles in the plasma due to an increased oxygen partial pressure. SE measurements showed that significant interfacial SiO 2 growth has taken place above approximately 51%. The best C- V results in terms of relative dielectric constant values are obtained for thin films prepared at an oxygen partial pressure of 15%.

Direct-method SAD phasing with partial-structure iteration: towards automation.

PubMed

Wang, J W; Chen, J R; Gu, Y X; Zheng, C D; Fan, H F

2004-11-01

The probability formula of direct-method SAD (single-wavelength anomalous diffraction) phasing proposed by Fan & Gu (1985, Acta Cryst. A41, 280-284) contains partial-structure information in the form of a Sim-weighting term. Previously, only the substructure of anomalous scatterers has been included in this term. In the case that the subsequent density modification and model building yields only structure fragments, which do not straightforwardly lead to the complete solution, the partial structure can be fed back into the Sim-weighting term of the probability formula in order to strengthen its phasing power and to benefit the subsequent automatic model building. The procedure has been tested with experimental SAD data from two known proteins with copper and sulfur as the anomalous scatterers.

Model-based approach to partial tracking for musical transcription

NASA Astrophysics Data System (ADS)

Sterian, Andrew; Wakefield, Gregory H.

1998-10-01

We present a new method for musical partial tracking in the context of musical transcription using a time-frequency Kalman filter structure. The filter is based upon a model for the evolution of a partial behavior across a wide range of pitch from four brass instruments. Statistics are computed independently for the partial attributes of frequency and log-power first differences. We present observed power spectral density shapes, total powers, and histograms, as well as least-squares approximations to these. We demonstrate that a Kalman filter tracker using this partial model is capable of tracking partials in music. We discuss how the filter structure naturally provides quality-of-fit information about the data for use in further processing and how this information can be used to perform partial track initiation and termination within a common framework. We propose that a model-based approach to partial tracking is preferable to existing approaches which generally use heuristic rules or birth/death notions over a small time neighborhood. The advantages include better performance in the presence of cluttered data and simplified tracking over missed observations.

Technical brief: Pump-probe paradigm in an integrating cavity to study photodecomposition processes

PubMed Central

Betts-Obregon, Brandi; Tsin, Andrew T.; DeSa, Richard J.

2016-01-01

Purpose Assaying photodecomposition is challenging because light must be used to initiate the photodamage and light must be used to monitor the photodecomposition. The experimental requirements are as follows: 1) During exposure of the actinic beam, continuously monitor the spectral characteristics of the sample, 2) uniformly expose the reactants to the actinic source, 3) obtain informative spectra in the presence of light scatter, and 4) achieve sufficient sensitivity for dilute reactants. Traditional spectrophotometers cannot address these issues due to sample turbidity, the inability to uniformly expose the cuvette contents to the incident beam, the inability to simultaneously perform spectral scans, and inherent low sensitivity. Here, we describe a system that meets these challenges in a practical way. Methods Light access to a 8.6 ml quartz integrating sphere containing 10 µM all-trans retinol in PBS was provided by three ports at right angles allowing for the following: 1) actinic light delivery from light-emitting diodes (LEDs) firing at 100 pulses/sec, 2) entry of a separate scanning beam at 100 scans/sec (10,000 µsec scan time) via an OLIS RSM 1000 ultraviolet/visual (UV/Vis) rapid-scanning spectrophotometer (RSM), and 3) light exit to the detector photomultiplier. The RSM spectral intermediate slit was partially covered to allow for a “dark” period of 2,000 µsec when no scanning light was admitted to the cuvette. During that interval, the LED was flashed, and the photomultiplier was temporarily blocked by a perforated spinning shutter disk. The absorbance per centimeter, which is increased due to the internal reflectance of the integrating sphere compared to a standard 1 cm rectangular cuvette, was calculated according to Fry et al. (2010) Applied Optics 49:575. Retinoid photodecomposition was confirmed with high-performance liquid chromatography (HPLC). Results Using the RSM to trigger the LED flash and photomultiplier shutter closure during the “dark” period allowed actinic flashes to be placed between scans. Exposure of the all-trans retinol to 366 nm flashes resulted in marked reduction in absorbance and a blue shift of the λmax. A white LED, despite its higher photon output, did not support all-trans retinol photolysis. Singular value decomposition (SVD) analysis revealed three spectral intermediates with mechanism, I -> II -> III. HPLC analysis of the reactants at the beginning and the conclusion of the light exposure confirmed the retinol photodecomposition. Conclusions The highly reflecting cavity acts as a multipass cuvette that markedly increased the light path length and, thus, sensitivity. Triggering the LED during a dark period within the scan time allowed the actinic flashes to be interleafed between scans in a pump-probe paradigm. Furthermore, the entire sample was exposed to scan beam and actinic flashes, which is not possible in traditional spectrophotometers. Finally, the integrating cavity cuvette allowed use of turbid samples. SVD was useful for resolving spectral intermediates. Although the identity of the intermediates was not determined here, the ability to define molecular intermediates during photodecomposition reactions will allow future studies to isolate and identify the degradation products and determine the mechanism of light-induced retinoid degradation and that of retinoid-binding protein-mediated photoprotection. PMID:27559291

Experimental Studies on Wave Interactions of Partially Perforated Wall under Obliquely Incident Waves

PubMed Central

Lee, Jong-In; Kim, Young-Taek; Shin, Sungwon

2014-01-01

This study presents wave height distribution in terms of stem wave evolution phenomena on partially perforated wall structures through three-dimensional laboratory experiments. The plain and partially perforated walls were tested to understand their effects on the stem wave evolution under the monochromatic and random wave cases with the various wave conditions, incident angle (from 10 to 40 degrees), and configurations of front and side walls. The partially perforated wall reduced the relative wave heights more effectively compared to the plain wall structure. Partially perforated walls with side walls showed a better performance in terms of wave height reduction compared to the structure without the side wall. Moreover, the relative wave heights along the wall were relatively small when the relative chamber width is large, within the range of the chamber width in this study. The wave spectra showed a frequency dependency of the wave energy dissipation. In most cases, the existence of side wall is a more important factor than the porosity of the front wall in terms of the wave height reduction even if the partially perforated wall was still effective compared to the plain wall. PMID:25254260

Experimental studies on wave interactions of partially perforated wall under obliquely incident waves.

PubMed

Lee, Jong-In; Kim, Young-Taek; Shin, Sungwon

2014-01-01

This study presents wave height distribution in terms of stem wave evolution phenomena on partially perforated wall structures through three-dimensional laboratory experiments. The plain and partially perforated walls were tested to understand their effects on the stem wave evolution under the monochromatic and random wave cases with the various wave conditions, incident angle (from 10 to 40 degrees), and configurations of front and side walls. The partially perforated wall reduced the relative wave heights more effectively compared to the plain wall structure. Partially perforated walls with side walls showed a better performance in terms of wave height reduction compared to the structure without the side wall. Moreover, the relative wave heights along the wall were relatively small when the relative chamber width is large, within the range of the chamber width in this study. The wave spectra showed a frequency dependency of the wave energy dissipation. In most cases, the existence of side wall is a more important factor than the porosity of the front wall in terms of the wave height reduction even if the partially perforated wall was still effective compared to the plain wall.

Independent saturation of three TrpRS subsites generates a partially assembled state similar to those observed in molecular simulations

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

Laowanapiban, Poramaet; Kapustina, Maryna; Vonrhein, Clemens

2009-03-05

Two new crystal structures of Bacillus stearothermophilus tryptophanyl-tRNA synthetase (TrpRS) afford evidence that a closed interdomain hinge angle requires a covalent bond between AMP and an occupant of either pyrophosphate or tryptophan subsite. They also are within experimental error of a cluster of structures observed in a nonequilibrium molecular dynamics simulation showing partial active-site assembly. Further, the highest energy structure in a minimum action pathway computed by using elastic network models for Open and Pretransition state (PreTS) conformations for the fully liganded TrpRS monomer is intermediate between that simulated structure and a partially disassembled structure from a nonequilibrium molecular dynamicsmore » trajectory for the unliganded PreTS. These mutual consistencies provide unexpected validation of inferences drawn from molecular simulations.« less

76 FR 9820 - Notice of Intent To Grant a Partially Exclusive License

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-22

... NATIONAL AERONAUTICS AND SPACE ADMINISTRATION [Notice (11-018)] Notice of Intent To Grant a Partially Exclusive License AGENCY: National Aeronautics and Space Administration. ACTION: Notice of intent... Integrating A Rigid Structure Into A Flexible Wall Of An Inflatable Structure'' to Bigelow Aerospace, having...

Application of partial differential equation modeling of the control/structural dynamics of flexible spacecraft

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr.; Rajiyah, H.

1991-01-01

Partial differential equations for modeling the structural dynamics and control systems of flexible spacecraft are applied here in order to facilitate systems analysis and optimization of these spacecraft. Example applications are given, including the structural dynamics of SCOLE, the Solar Array Flight Experiment, the Mini-MAST truss, and the LACE satellite. The development of related software is briefly addressed.

Lithospheric structure of the southern French Alps inferred from broadband analysis

NASA Astrophysics Data System (ADS)

Bertrand, E.; Deschamps, A.

2000-11-01

Broadband receiver functions analysis is commonly used to evaluate the fine-scale S-velocity structure of the lithosphere. We analyse teleseismic P-waves and their coda from 30 selected teleseismic events recorded at three seismological stations of to the French TGRS network in the Alpes Maritimes. Receiver functions are computed in the time domain using an SVD matrix inversion method. Dipping Moho and lateral heterogeneities beneath the array are inferred from the amplitude, arrival time and polarity of locally-generated PS phases. We propose that the Moho dips 11° towards 25°±10°N below station CALF, in the outer part of the Alpine belt. At this station, we determine a Moho depth of about 20±2 km; the same depth is suggested below SAOF station also located in the fold-trust belt. Beneath station STET located in the inner part of the Alpine belt, the Moho depth increases to 30 km and dips towards the N-NW. Moreover, 1D-modelling of summed receiver function from STET station constrains a crustal structure significantly different from that observed at stations located in the outer part of the Alps. Indeed, beneath CALF and SAOF stations we need a 2 km thick shallow low velocity layer to fit best the observed receiver functions whereas this layer seems not to be present beneath STET station. Because recent P-coda studies have shown that near-receiver scattering can dominate teleseismic P-wave recordings in tectonically complicated areas, we account for effect of scattering energy in our records from array measurements. As the array aperture is wide relative to the heterogeneity scale length in the area, the array analysis produces only smooth imaging of scatterers beneath the stations.

Generic construction of efficient matrix product operators

NASA Astrophysics Data System (ADS)

Hubig, C.; McCulloch, I. P.; Schollwöck, U.

2017-01-01

Matrix product operators (MPOs) are at the heart of the second-generation density matrix renormalization group (DMRG) algorithm formulated in matrix product state language. We first summarize the widely known facts on MPO arithmetic and representations of single-site operators. Second, we introduce three compression methods (rescaled SVD, deparallelization, and delinearization) for MPOs and show that it is possible to construct efficient representations of arbitrary operators using MPO arithmetic and compression. As examples, we construct powers of a short-ranged spin-chain Hamiltonian, a complicated Hamiltonian of a two-dimensional system and, as proof of principle, the long-range four-body Hamiltonian from quantum chemistry.

Genetic algorithm and graph theory based matrix factorization method for online friend recommendation.

PubMed

Li, Qu; Yao, Min; Yang, Jianhua; Xu, Ning

2014-01-01

Online friend recommendation is a fast developing topic in web mining. In this paper, we used SVD matrix factorization to model user and item feature vector and used stochastic gradient descent to amend parameter and improve accuracy. To tackle cold start problem and data sparsity, we used KNN model to influence user feature vector. At the same time, we used graph theory to partition communities with fairly low time and space complexity. What is more, matrix factorization can combine online and offline recommendation. Experiments showed that the hybrid recommendation algorithm is able to recommend online friends with good accuracy.

Dislocation Structure and Mobility in hcp He 4

DOE PAGES

Landinez Borda, Edgar Josue; Cai, Wei; de Koning, Maurice

2016-07-20

We assess the core structure and mobility of the screw and edge basal-plane dislocations in hcp 4He using path-integral Monte Carlo simulations. Our findings provide key insights into recent interpretations of giant plasticity and mass flow junction experiments. First, both dislocations are dissociated into nonsuperfluid Shockley partial dislocations separated by ribbons of stacking fault, suggesting that they are unlikely to act as one-dimensional channels that may display Lüttinger-liquid-like behavior. Second, the centroid positions of the partial cores are found to fluctuate substantially, even in the absence of applied shear stresses. This implies that the lattice resistance to motion of themore » partial dislocations is negligible, consistent with the recent experimental observations of giant plasticity. Our results indicate that both the structure of the partial cores and the zero-point fluctuations play a role in this extreme mobility.« less

Theoretical study of the partial molar volume change associated with the pressure-induced structural transition of ubiquitin

PubMed Central

Imai, Takashi; Ohyama, Shusaku; Kovalenko, Andriy; Hirata, Fumio

2007-01-01

The partial molar volume (PMV) change associated with the pressure-induced structural transition of ubiquitin is analyzed by the three-dimensional reference interaction site model (3D-RISM) theory of molecular solvation. The theory predicts that the PMV decreases upon the structural transition, which is consistent with the experimental observation. The volume decomposition analysis demonstrates that the PMV reduction is primarily caused by the decrease in the volume of structural voids in the protein, which is partially canceled by the volume expansion due to the hydration effects. It is found from further analysis that the PMV reduction is ascribed substantially to the penetration of water molecules into a specific part of the protein. Based on the thermodynamic relation, this result implies that the water penetration causes the pressure-induced structural transition. It supports the water penetration model of pressure denaturation of proteins proposed earlier. PMID:17660257

Theoretical study of the partial molar volume change associated with the pressure-induced structural transition of ubiquitin.

PubMed

Imai, Takashi; Ohyama, Shusaku; Kovalenko, Andriy; Hirata, Fumio

2007-09-01

The partial molar volume (PMV) change associated with the pressure-induced structural transition of ubiquitin is analyzed by the three-dimensional reference interaction site model (3D-RISM) theory of molecular solvation. The theory predicts that the PMV decreases upon the structural transition, which is consistent with the experimental observation. The volume decomposition analysis demonstrates that the PMV reduction is primarily caused by the decrease in the volume of structural voids in the protein, which is partially canceled by the volume expansion due to the hydration effects. It is found from further analysis that the PMV reduction is ascribed substantially to the penetration of water molecules into a specific part of the protein. Based on the thermodynamic relation, this result implies that the water penetration causes the pressure-induced structural transition. It supports the water penetration model of pressure denaturation of proteins proposed earlier.

Characterization of two distinct beta2-microglobulin unfolding intermediates that may lead to amyloid fibrils of different morphology.

PubMed

Armen, Roger S; Daggett, Valerie

2005-12-13

The self-assembly of beta(2)-microglobulin into fibrils leads to dialysis-related amyloidosis. pH-mediated partial unfolding is required for the formation of the amyloidogenic intermediate that then self-assembles into amyloid fibrils. Two partially folded intermediates of beta(2)-microglobulin have been identified experimentally and linked to the formation of fibrils of distinct morphology, yet it remains difficult to characterize these partially unfolded states at high resolution using experimental approaches. Consequently, we have performed molecular dynamics simulations at neutral and low pH to determine the structures of these partially unfolded amyloidogenic intermediates. In the low-pH simulations, we observed the formation of alpha-sheet structure, which was first proposed by Pauling and Corey. Multiple simulations were performed, and two distinct intermediate state ensembles were identified that may account for the different fibril morphologies. The predominant early unfolding intermediate was nativelike in structure, in agreement with previous NMR studies. The late unfolding intermediate was significantly disordered, but it maintained an extended elongated structure, with hydrophobic clusters and residual alpha-extended chain strands in specific regions of the sequence that map to amyloidogenic peptides. We propose that the formation of alpha-sheet facilitates self-assembly into partially unfolded prefibrillar amyloidogenic intermediates.

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies.

PubMed

Dukart, Juergen; Bertolino, Alessandro

2014-01-01

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality--an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

Impacts from Partial Removal of Decommissioned Oil and Gas Platforms on Fish Biomass and Production on the Remaining Platform Structure and Surrounding Shell Mounds.

PubMed

Claisse, Jeremy T; Pondella, Daniel J; Love, Milton; Zahn, Laurel A; Williams, Chelsea M; Bull, Ann S

2015-01-01

When oil and gas platforms become obsolete they go through a decommissioning process. This may include partial removal (from the surface to 26 m depth) or complete removal of the platform structure. While complete removal would likely eliminate most of the existing fish biomass and associated secondary production, we find that the potential impacts of partial removal would likely be limited on all but one platform off the coast of California. On average 80% of fish biomass and 86% of secondary fish production would be retained after partial removal, with above 90% retention expected for both metrics on many platforms. Partial removal would likely result in the loss of fish biomass and production for species typically found residing in the shallow portions of the platform structure. However, these fishes generally represent a small proportion of the fishes associated with these platforms. More characteristic of platform fauna are the primarily deeper-dwelling rockfishes (genus Sebastes). "Shell mounds" are biogenic reefs that surround some of these platforms resulting from an accumulation of mollusk shells that have fallen from the shallow areas of the platforms mostly above the depth of partial removal. We found that shell mounds are moderately productive fish habitats, similar to or greater than natural rocky reefs in the region at comparable depths. The complexity and areal extent of these biogenic habitats, and the associated fish biomass and production, will likely be reduced after either partial or complete platform removal. Habitat augmentation by placing the partially removed platform superstructure or some other additional habitat enrichment material (e.g., rock boulders) on the seafloor adjacent to the base of partially removed platforms provides additional options to enhance fish production, potentially mitigating reductions in shell mound habitat.

Densities of L-Glutamic Acid HCl Drug in Aqueous NaCl and KCl Solutions at Different Temperatures

NASA Astrophysics Data System (ADS)

Ryshetti, Suresh; Raghuram, Noothi; Rani, Emmadi Jayanthi; Tangeda, Savitha Jyostna

2016-04-01

Densities (ρ ) of (0.01 to 0.07) {mol}{\\cdot } {kg}^{-1} L-Glutamic acid HCl (L-HCl) drug in water, and in aqueous NaCl and KCl (0.5 and 1.0) {mol}{\\cdot } {kg}^{-1} solutions have been reported as a function of temperature at T = (298.15, 303.15, 308.15, and 313.15) K and atmospheric pressure. The accurate density (ρ ) values are used to estimate the various parameters such as the apparent molar volume (V_{2,{\\upphi }}), the partial molar volume (V2^{∞}), the isobaric thermal expansion coefficient (α 2), the partial molar expansion (E2^{∞}), and Hepler's constant (partial 2V2^{∞}/partial T2)P. The Cosphere overlap model is used to understand the solute-solvent interactions in a ternary mixture (L-HCl drug + NaCl or KCl + water). Hepler's constant (partial 2V2^{∞}/partial T2)_P is utilized to interpret the structure-making or -breaking ability of L-HCl drug in aqueous NaCl and KCl solutions, and the results are inferred that L-HCl drug acts as a structure maker, i.e., kosmotrope in aqueous NaCl solutions and performs as a structure breaker, i.e., chaotrope in aqueous KCl solutions.

Pressure effects on the structure, kinetic, and thermodynamic properties of heat-induced aggregation of protein studied by FT-IR spectroscopy

NASA Astrophysics Data System (ADS)

Taniguchi, Y.; Okuno, A.; Kato, M.

2010-03-01

Pressure can retrain the heat-induced aggregation and dissociate the heat-induced aggregates. We observed the aggregation-preventing pressure effect and the aggregates-dissociating pressure effect to characterize the heat-induced aggregation of equine serum albumin (ESA) by FT-IR spectroscopy. The results suggest the α-helical structure collapses at the beginning of heat-induced aggregation through the swollen structure, and then the rearrangement of structure to the intermolecular β-sheet takes place through partially unfolded structure. We determined the activation volume for the heat-induced aggregation (ΔV# = +93 ml/mol) and the partial molar volume difference between native state and heat-induced aggregates (ΔV=+32 ml/mol). This positive partial molar volume difference suggests that the heat-induced aggregates have larger internal voids than the native structure. Moreover, the positive volume change implies that the formation of the intermolecular β-sheet is unfavorable under high pressure.

COMPUTER SIMULATION STUDY OF AMYLOID FIBRIL FORMATION BY PALINDROMIC SEQUENCES IN PRION PEPTIDES

PubMed Central

Wagoner, Victoria; Cheon, Mookyung; Chang, Iksoo; Hall, Carol

2011-01-01

We simulate the aggregation of large systems containing palindromic peptides from the Syrian hamster prion protein SHaPrP 113–120 (AGAAAAGA) and the mouse prion protein MoPrP 111–120 (VAGAAAAGAV) and eight sequence variations: GAAAAAAG, (AG)4, A8, GAAAGAAA, A10, V10, GAVAAAAVAG, and VAVAAAAVAV The first two peptides are thought to act as the Velcro that holds the parent prion proteins together in amyloid structures and can form fibrils themselves. Kinetic events along the fibrillization pathway influence the types of structures that occur and variations in the sequence affect aggregation kinetics and fibrillar structure. Discontinuous molecular dynamics simulations using the PRIME20 force field are performed on systems containing 48 peptides starting from a random coil configuration. Depending on the sequence, fibrillar structures form spontaneously over a range of temperatures, below which amorphous aggregates form and above which no aggregation occurs. AGAAAAGA forms well organized fibrillar structures whereas VAGAAAAGAV forms less well organized structures that are partially fibrillar and partially amorphous. The degree of order in the fibrillar structure stems in part from the types of kinetic events leading up to its formation, with AGAAAAGA forming less amorphous structures early in the simulation than VAGAAAAGAV. The ability to form fibrils increases as the chain length and the length of the stretch of hydrophobic residues increase. However as the hydrophobicity of the sequence increases, the ability to form well-ordered structures decreases. Thus, longer hydrophobic sequences form slightly disordered aggregates that are partially fibrillar and partially amorphous. Subtle changes in sequence result in slightly different fibril structures. PMID:21557317

Domain atrophy creates rare cases of functional partial protein domains.

PubMed

Prakash, Ananth; Bateman, Alex

2015-04-30

Protein domains display a range of structural diversity, with numerous additions and deletions of secondary structural elements between related domains. We have observed a small number of cases of surprising large-scale deletions of core elements of structural domains. We propose a new concept called domain atrophy, where protein domains lose a significant number of core structural elements. Here, we implement a new pipeline to systematically identify new cases of domain atrophy across all known protein sequences. The output of this pipeline was carefully checked by hand, which filtered out partial domain instances that were unlikely to represent true domain atrophy due to misannotations or un-annotated sequence fragments. We identify 75 cases of domain atrophy, of which eight cases are found in a three-dimensional protein structure and 67 cases have been inferred based on mapping to a known homologous structure. Domains with structural variations include ancient folds such as the TIM-barrel and Rossmann folds. Most of these domains are observed to show structural loss that does not affect their functional sites. Our analysis has significantly increased the known cases of domain atrophy. We discuss specific instances of domain atrophy and see that there has often been a compensatory mechanism that helps to maintain the stability of the partial domain. Our study indicates that although domain atrophy is an extremely rare phenomenon, protein domains under certain circumstances can tolerate extreme mutations giving rise to partial, but functional, domains.

Inversion of gravity gradient tensor data: does it provide better resolution?

NASA Astrophysics Data System (ADS)

Paoletti, V.; Fedi, M.; Italiano, F.; Florio, G.; Ialongo, S.

2016-04-01

The gravity gradient tensor (GGT) has been increasingly used in practical applications, but the advantages and the disadvantages of the analysis of GGT components versus the analysis of the vertical component of the gravity field are still debated. We analyse the performance of joint inversion of GGT components versus separate inversion of the gravity field alone, or of one tensor component. We perform our analysis by inspection of the Picard Plot, a Singular Value Decomposition tool, and analyse both synthetic data and gradiometer measurements carried out at the Vredefort structure, South Africa. We show that the main factors controlling the reliability of the inversion are algebraic ambiguity (the difference between the number of unknowns and the number of available data points) and signal-to-noise ratio. Provided that algebraic ambiguity is kept low and the noise level is small enough so that a sufficient number of SVD components can be included in the regularized solution, we find that: (i) the choice of tensor components involved in the inversion is not crucial to the overall reliability of the reconstructions; (ii) GGT inversion can yield the same resolution as inversion with a denser distribution of gravity data points, but with the advantage of using fewer measurement stations.

Automated detection of microaneurysms using robust blob descriptors

NASA Astrophysics Data System (ADS)

Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

2013-03-01

Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition

PubMed Central

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-01-01

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K-nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction. PMID:28346385

Propagation of partially coherent Lorentz and Lorentz-Gauss beams through a paraxial ABCD optical system in a turbulent atmosphere

NASA Astrophysics Data System (ADS)

Zhao, Chengliang; Cai, Yangjian

2011-05-01

Based on the generalized Huygens-Fresnel integral, propagation of partially coherent Lorentz and Lorentz-Gauss beams through a paraxial ABCD optical system in a turbulent atmosphere was investigated. Analytical propagation formulae were derived for the cross-spectral densities of partially coherent Lorentz and Lorentz-Gauss beams. As an application example, the focusing properties of partially coherent Gaussian, Lorentz and Lorentz-Gauss beams in a turbulent atmosphere and in free space were studied numerically and comparatively. It is found that the focusing properties of such beams are closely related to the initial coherence length and the structure constant of turbulence. By choosing a suitable initial coherence length, a partially coherent Lorentz beam can be focused more tightly than a Gaussian or Lorentz-Gauss beam in free space or in a turbulent atmosphere with small structure constant at the geometrical focal plane.

Effect of visual experience on structural organization of the human brain: a voxel based morphometric study using DARTEL.

PubMed

Modi, Shilpi; Bhattacharya, Manisha; Singh, Namita; Tripathi, Rajendra Prasad; Khushu, Subash

2012-10-01

To investigate structural reorganization in the brain with differential visual experience using Voxel-Based Morphometry with Diffeomorphic Anatomic Registration Through Exponentiated Lie algebra algorithm (DARTEL) approach. High resolution structural MR images were taken in fifteen normal sighted healthy controls, thirteen totally blind subjects and six partial blind subjects. The analysis was carried out using SPM8 software on MATLAB 7.6.0 platform. VBM study revealed gray matter volume atrophy in the cerebellum and left inferior parietal cortex in total blind subjects and in left inferior parietal cortex, right caudate nucleus, and left primary visual cortex in partial blind subjects as compared to controls. White matter volume loss was found in calcarine gyrus in total blind subjects and Thlamus-somatosensory region in partially blind subjects as compared to controls. Besides, an increase in Gray Matter volume was also found in left middle occipital and middle frontal gyrus and right entorhinal cortex, and an increase in White Matter volume was found in superior frontal gyrus, left middle temporal gyrus and right Heschl's gyrus in totally blind subjects as compared to controls. Comparison between total and partial blind subjects revealed a greater Gray Matter volume in left cerebellum of partial blinds and left Brodmann area 18 of total blind subjects. Results suggest that, loss of vision at an early age can induce significant structural reorganization on account of the loss of visual input. These plastic changes are different in early onset of total blindness as compared to partial blindness. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Improved toughness of silicon carbide

NASA Technical Reports Server (NTRS)

Palm, J. A.

1976-01-01

Impact energy absorbing layers (EALs) comprised of partially densified silicon carbide were formed in situ on fully sinterable silicon carbide substrates. After final sintering, duplex silicon carbide structures resulted which were comprised of a fully sintered, high density silicon carbide substrate or core, overlayed with an EAL of partially sintered silicon carbide integrally bonded to its core member. Thermal cycling tests proved such structures to be moderately resistant to oxidation and highly resistant to thermal shock stresses. The strength of the developed structures in some cases exceeded but essentially it remained the same as the fully sintered silicon carbide without the EAL. Ballistic impact tests indicated that substantial improvements in the toughness of sintered silicon carbide were achieved by the use of the partially densified silicon carbide EALs.

Prolongation structures of nonlinear evolution equations

NASA Technical Reports Server (NTRS)

Wahlquist, H. D.; Estabrook, F. B.

1975-01-01

A technique is developed for systematically deriving a 'prolongation structure' - a set of interrelated potentials and pseudopotentials - for nonlinear partial differential equations in two independent variables. When this is applied to the Korteweg-de Vries equation, a new infinite set of conserved quantities is obtained. Known solution techniques are shown to result from the discovery of such a structure: related partial differential equations for the potential functions, linear 'inverse scattering' equations for auxiliary functions, Backlund transformations. Generalizations of these techniques will result from the use of irreducible matrix representations of the prolongation structure.

Dislocation core structures of tungsten with dilute solute hydrogen

NASA Astrophysics Data System (ADS)

Wang, Yinan; Li, Qiulin; Li, Chengliang; Shu, Guogang; Xu, Ben; Liu, Wei

2017-12-01

In this paper, a combination of quantum mechanical and interatomic potential-based atomistic calculations are used to predict the core structures of screw and edge dislocations in tungsten in the presence of a particular concentration of hydrogen atoms. These configurations of the core structures are the results of two competing energies: the interaction between the partial dislocations and the corresponding generalized stacking fault energy in between the two partial dislocations, which are presented in this work. With this, we can precisely predict the configurations of the hydrogen-doped dislocation core structures.

Thermal control structure and garment

DOEpatents

Klett, James W [Knoxville, TN; Cameron, Christopher Stan [Sanford, NC

2012-03-13

A flexible thermally conductive structure. The structure generally includes a plurality of thermally conductive yarns, at least some of which are at least partially disposed adjacent to an elastomeric material. Typically, at least a portion of the plurality of thermally conductive yarns is configured as a sheet. The yarns may be constructed from graphite, metal, or similar materials. The elastomeric material may be formed from urethane or silicone foam that is at least partially collapsed, or from a similar material. A thermal management garment is provided, the garment incorporating a flexible thermally conductive structure.

Integrated control/structure optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Gilbert, Michael G.

1990-01-01

A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Resolving structural uncertainty in natural resources management using POMDP approaches

USGS Publications Warehouse

Williams, B.K.

2011-01-01

In recent years there has been a growing focus on the uncertainties of natural resources management, and the importance of accounting for uncertainty in assessing management effectiveness. This paper focuses on uncertainty in resource management in terms of discrete-state Markov decision processes (MDP) under structural uncertainty and partial observability. It describes the treatment of structural uncertainty with approaches developed for partially observable resource systems. In particular, I show how value iteration for partially observable MDPs (POMDP) can be extended to structurally uncertain MDPs. A key difference between these process classes is that structurally uncertain MDPs require the tracking of system state as well as a probability structure for the structure uncertainty, whereas with POMDPs require only a probability structure for the observation uncertainty. The added complexity of the optimization problem under structural uncertainty is compensated by reduced dimensionality in the search for optimal strategy. A solution algorithm for structurally uncertain processes is outlined for a simple example in conservation biology. By building on the conceptual framework developed for POMDPs, natural resource analysts and decision makers who confront structural uncertainties in natural resources can take advantage of the rapid growth in POMDP methods and approaches, and thereby produce better conservation strategies over a larger class of resource problems. ?? 2011.

Focus on Kir7.1: physiology and channelopathy

PubMed Central

Kumar, Mohit; Pattnaik, Bikash R

2014-01-01

Genetic studies have linked alterations in Kir7.1 channel to diverse pathologies. We summarize functional relevance of Kir7.1 channel in retinal pigment epithelium (RPE), regulation of channel function by various cytoplasmic metabolites, and mutations that cause channelopathies. At the apical membrane of RPE, K+ channels contribute to subretinal K+ homeostasis and support Na+/K+ pump and Na+-K+-2Cl− cotransporter function by providing a pathway for K+ secretion. Electrophysiological studies have established that barium- and cesium-sensitive inwardly rectifying K+ (Kir) channels make up a major component of the RPE apical membrane K+ conductance. Native human RPE expresses transcripts for Kir1.1, Kir2.1, Kir2.2, Kir3.1, Kir3.4, Kir4.2, and Kir6.1, albeit at levels at least 50-fold lower than Kir7.1. Kir7.1 is structurally similar to other Kir channels, consisting of 2 trans-membrane domains, a pore-forming loop that contains the selectivity filter, and 2 cytoplasmic polar tails. Within the cytoplasmic structure, clusters of amino acid sequences form regulatory domains that interact with cellular metabolites and control the opening and closing of the channel. Recent evidence indicated that intrinsic sequence motifs present in Kir7.1 control surface expression. Mutant Kir7.1 channels are associated with inherited eye pathologies such as Snowflake Vitreoretinal Degeneration (SVD) and Lebers Congenital Amaurosis (LCA16). Based on the current evidence, mutations implicated in channelopathies have the potential to be used for genetic testing to diagnose blindness due to Kir7.1. PMID:25558901

Predicting responses from Rasch measures.

PubMed

Linacre, John M

2010-01-01

There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

Robust Control of Multivariable and Large Scale Systems.

DTIC Science & Technology

1988-03-23

D, and let A E [0, 1]. We need to show that h ((1 - A)D1 + AD2 ) < (1 - A)h(D 1 ) + Ah(D 2) Define f:R-+R by f(t) := h((1 - t)D 1 + tD 2 ) = ebt...SVD -S M = 3UV * + U2E2 V2 *. (13.11) In this setting, / is any singular value of M, not necessarily &(M), but none of the singular values in E 2 should...a)f (x) -afr(y)] and let A be the largest value in [0, 1] that achieves #3. Obviously, since /3 > 0, A E (0, 1). Define tD := (1 - A)x + Ay. Hence f

Letters: Noise Equalization for Ultrafast Plane Wave Microvessel Imaging

PubMed Central

Song, Pengfei; Manduca, Armando; Trzasko, Joshua D.

2017-01-01

Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity by increasing the number of Doppler ensembles that can be collected within a short period of time. The rich spatiotemporal plane wave data also enables more robust clutter filtering based on singular value decomposition (SVD). However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. This study was designed to: 1) study the relationship between ultrasound system noise (primarily time gain compensation-induced) and microvessel blood flow signal; 2) propose an adaptive and computationally cost-effective noise equalization method that is independent of hardware or software imaging settings to improve microvessel image quality. PMID:28880169

Spreading Sequence System for Full Connectivity Relay Network

NASA Technical Reports Server (NTRS)

Kwon, Hyuck M. (Inventor); Pham, Khanh D. (Inventor); Yang, Jie (Inventor)

2018-01-01

Fully connected uplink and downlink fully connected relay network systems using pseudo-noise spreading and despreading sequences subjected to maximizing the signal-to-interference-plus-noise ratio. The relay network systems comprise one or more transmitting units, relays, and receiving units connected via a communication network. The transmitting units, relays, and receiving units each may include a computer for performing the methods and steps described herein and transceivers for transmitting and/or receiving signals. The computer encodes and/or decodes communication signals via optimum adaptive PN sequences found by employing Cholesky decompositions and singular value decompositions (SVD). The PN sequences employ channel state information (CSI) to more effectively and more securely computing the optimal sequences.

Properties of L-ascorbic acid in water and binary aqueous mixtures of D-glucose and D-fructose at different temperatures

NASA Astrophysics Data System (ADS)

Sharma, Ravi; Thakur, R. C.; Sani, Balwinder; Kumar, Harsh

2017-12-01

Using density and sound velocity partial molar volumes, partial molar adiabatic compressibilities, partial molar expansibilities and structure of L-ascorbic acid have been determined in water and aqueous mixtures of D-glucose and D-fructose at different concentrations and temperatures. Masson's equation was used to analyze the measured data. The obtained parameters have been interpreted in terms of solute-solute and solute-solvent interactions. It is found that the L-ascorbic acid acts as structure breaker in water as well in binary studied mixtures.

[The structure and antimicrobial activity of the partial degradation products of the antibiotic eremomycin].

PubMed

Berdnikova, T F; Lomakina, N N; Olsuf'eva, E N; Aleksandrova, L G; Potapova, N P; Rozynov, B V; Malkova, I V; Orlova, G I

1991-06-01

Antimicrobial activity of partial degradation products of eremomycin, a new glycopeptide antibiotic, was studied. The products formed by eremomycin deglycosylation (deseremosaminyl eremomycin, eremosaminyl aglycone and aglycone) and elimination of the chlorine atom from the molecule aglycone moiety (dechloroeremomycin). The spectral data in favour of the compounds structure are presented. It was found that partial degradation led to a decrease in the antimicrobial activity of the antibiotic. Dechloreremomycin had the highest activity among the products. Its MIC for the methicillin-resistant strains of Staphylococcus aureus was only twice as low as that of the initial antibiotic.

Structural investigation of porcine stomach mucin by X-ray fiber diffraction and homology modeling

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

Veluraja, K., E-mail: veluraja@msuniv.ac.in; Vennila, K.N.; Umamakeshvari, K.

Research highlights: {yields} Techniques to get oriented mucin fibre. {yields} X-ray fibre diffraction pattern for mucin. {yields} Molecular modeling of mucin based on X-ray fibre diffraction pattern. -- Abstract: The basic understanding of the three dimensional structure of mucin is essential to understand its physiological function. Technology has been developed to achieve orientated porcine stomach mucin molecules. X-ray fiber diffraction of partially orientated porcine stomach mucin molecules show d-spacing signals at 2.99, 4.06, 4.22, 4.7, 5.37 and 6.5 A. The high intense d-spacing signal at 4.22 A is attributed to the antiparallel {beta}-sheet structure identified in the fraction of themore » homology modeled mucin molecule (amino acid residues 800-980) using Nidogen-Laminin complex structure as a template. The X-ray fiber diffraction signal at 6.5 A reveals partial organization of oligosaccharides in porcine stomach mucin. This partial structure of mucin will be helpful in establishing a three dimensional structure for the whole mucin molecule.« less

Integrated control/structure optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Gilbert, Michael G.

1990-01-01

A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.

Electronic structure and partial charge distribution of doxorubicin under different molecular environments

NASA Astrophysics Data System (ADS)

Poudel, Lokendra

Doxorubicin (trade name Adriamycin, abbreviated DOX) is a well-known an- thracyclic chemotherapeutic used in treating a variety of cancers including acute leukemia, lymphoma, multiple myeloma, and a range of stomach, lung, bladder, bone, breast, and ovarian cancers. The purpose of the present work is to study electronic structure, partial charge distribution and interaction energy of DOX under different environments. It provides a framework for better understanding of bioactivity of DOX with DNA. While in this work, we focus on DOX -- DNA interactions; the obtained knowledge could be translated to other drug -- target interactions or biomolecular interactions. The electronic structure and partial charge distribution of DOX in three dierent molecular environments: isolated, solvated, and intercalated into a DNA complex,were studied by rst principles density functional methods. It is shown that the addition of solvating water molecules to DOX and the proximity and interaction with DNA has a signicant impact on the electronic structure as well as the partial charge distribution. The calculated total partial charges for DOX in the three models are 0.0, +0.123 and -0.06 electrons for the isolated, solvated, and intercalated state, respectively. Furthermore, by using the more accurate ab initio partial charge values on every atom in the models, signicant improvement in estimating the DOX-DNA interaction energy is obtained in conjunction with the NAnoscale Molecular Dynamics (NAMD) code. The electronic structure of the DOX-DNA is further elucidated by resolving the total density of states (TDOS) into dierent functional groups of DOX, DNA, water, co-crystallized Spermine molecule, and Na ions. The surface partial charge distribution in the DOX-DNA is calculated and displayed graphically. We conclude that the presence of the solvent as well as the details of the interaction geometry matter greatly in the determination of the stability of the DOX complexion. Ab initio calculations on realistic models are an important step towards a more accurate description of biomolecular interaction and in the eventual understanding of long-range interactions in biomolecular systems.

Impacts from Partial Removal of Decommissioned Oil and Gas Platforms on Fish Biomass and Production on the Remaining Platform Structure and Surrounding Shell Mounds

PubMed Central

Claisse, Jeremy T.; Pondella, Daniel J.; Love, Milton; Zahn, Laurel A.; Williams, Chelsea M.; Bull, Ann S.

2015-01-01

When oil and gas platforms become obsolete they go through a decommissioning process. This may include partial removal (from the surface to 26 m depth) or complete removal of the platform structure. While complete removal would likely eliminate most of the existing fish biomass and associated secondary production, we find that the potential impacts of partial removal would likely be limited on all but one platform off the coast of California. On average 80% of fish biomass and 86% of secondary fish production would be retained after partial removal, with above 90% retention expected for both metrics on many platforms. Partial removal would likely result in the loss of fish biomass and production for species typically found residing in the shallow portions of the platform structure. However, these fishes generally represent a small proportion of the fishes associated with these platforms. More characteristic of platform fauna are the primarily deeper-dwelling rockfishes (genus Sebastes). “Shell mounds” are biogenic reefs that surround some of these platforms resulting from an accumulation of mollusk shells that have fallen from the shallow areas of the platforms mostly above the depth of partial removal. We found that shell mounds are moderately productive fish habitats, similar to or greater than natural rocky reefs in the region at comparable depths. The complexity and areal extent of these biogenic habitats, and the associated fish biomass and production, will likely be reduced after either partial or complete platform removal. Habitat augmentation by placing the partially removed platform superstructure or some other additional habitat enrichment material (e.g., rock boulders) on the seafloor adjacent to the base of partially removed platforms provides additional options to enhance fish production, potentially mitigating reductions in shell mound habitat. PMID:26332384

First-principles study of atomic and electronic structures of 60° perfect and 30°/90° partial glide dislocations in CdTe

DOE PAGES

Kweon, Kyoung E.; Aberg, Daniel; Lordi, Vincenzo

2016-05-16

The atomic and electronic structures of 60° glide perfect and 30°/90° glide partial dislocations in CdTe are studied using combined semi-empirical and density functional theory calculations. The calculations predict that the dislocation cores tend to undergo significant reconstructions along the dislocation lines from the singly-periodic (SP) structures, yielding either doubly-periodic (DP) ordering by forming a dimer or quadruply-periodic (QP) ordering by alternating a dimer and a missing dimer. Charge modulation along the dislocation line, accompanied by the QP reconstruction for the Cd-/Te-core 60° perfect and 30° partials or the DP reconstruction for the Cd-core 90° partial, results in semiconducting character,more » as opposed to the metallic character of the SP dislocation cores. Dislocation-induced defect states for the 60° Cd-/Te-core are located relatively close to the band edges, whereas the defect states lie in the middle of the band gap for the 30° Cd-/Te-core partial dislocations. In addition to the intracore charge modulation within each QP core, the possibility of intercore charge transfer between two different dislocation cores when they are paired together in the same system is discussed. As a result, the analysis of the electronic structures reveals the potential role of the dislocations on charge transport in CdTe, particularly in terms of charge trapping and recombination.« less

Mechanism of partial agonism in AMPA-type glutamate receptors

PubMed Central

Salazar, Hector; Eibl, Clarissa; Chebli, Miriam; Plested, Andrew

2017-01-01

Neurotransmitters trigger synaptic currents by activating ligand-gated ion channel receptors. Whereas most neurotransmitters are efficacious agonists, molecules that activate receptors more weakly—partial agonists—also exist. Whether these partial agonists have weak activity because they stabilize less active forms, sustain active states for a lesser fraction of the time or both, remains an open question. Here we describe the crystal structure of an α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptor (AMPAR) ligand binding domain (LBD) tetramer in complex with the partial agonist 5-fluorowillardiine (FW). We validate this structure, and others of different geometry, using engineered intersubunit bridges. We establish an inverse relation between the efficacy of an agonist and its promiscuity to drive the LBD layer into different conformations. These results suggest that partial agonists of the AMPAR are weak activators of the receptor because they stabilize multiple non-conducting conformations, indicating that agonism is a function of both the space and time domains. PMID:28211453

Uniscale multi-view registration using double dog-leg method

NASA Astrophysics Data System (ADS)

Chen, Chao-I.; Sargent, Dusty; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Dan

2009-02-01

3D computer models of body anatomy can have many uses in medical research and clinical practices. This paper describes a robust method that uses videos of body anatomy to construct multiple, partial 3D structures and then fuse them to form a larger, more complete computer model using the structure-from-motion framework. We employ the Double Dog-Leg (DDL) method, a trust-region based nonlinear optimization method, to jointly optimize the camera motion parameters (rotation and translation) and determine a global scale that all partial 3D structures should agree upon. These optimized motion parameters are used for constructing local structures, and the global scale is essential for multi-view registration after all these partial structures are built. In order to provide a good initial guess of the camera movement parameters and outlier free 2D point correspondences for DDL, we also propose a two-stage scheme where multi-RANSAC with a normalized eight-point algorithm is first performed and then a few iterations of an over-determined five-point algorithm is used to polish the results. Our experimental results using colonoscopy video show that the proposed scheme always produces more accurate outputs than the standard RANSAC scheme. Furthermore, since we have obtained many reliable point correspondences, time-consuming and error-prone registration methods like the iterative closest points (ICP) based algorithms can be replaced by a simple rigid-body transformation solver when merging partial structures into a larger model.

Intraseasonal variability of winter precipitation over central asia and the western tibetan plateau from 1979 to 2013 and its relationship with the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Liu, Heng; Liu, Xiaodong; Dong, Buwen

2017-09-01

Winter precipitation over Central Asia and the western Tibetan Plateau (CAWTP) is mainly a result of the interaction between the westerly circulation and the high mountains around the plateau. Empirical Orthogonal Functions (EOFs), Singular Value Decomposition (SVD), linear regression and composite analysis were used to analyze winter daily precipitation and other meteorological elements in this region from 1979 to 2013, in order to understand how interactions between the regional circulation and topography affect the intraseasonal variability in precipitation. The SVD analysis shows that the winter daily precipitation variability distribution is characterized by a dipole pattern with opposite signs over the northern Pamir Plateau and over the Karakoram Himalaya, similar to the second mode of EOF analysis. This dipole pattern of precipitation anomaly is associated with local anomalies in both the 700 hPa moisture transport and the 500 hPa geopotential height and is probably caused by oscillations in the regional and large-scale circulations, which can influence the westerly disturbance tracks and water vapor transport. The linear regression shows that the anomalous mid-tropospheric circulation over CAWTP corresponds to an anti-phase variation of the 500 hPa geopotential height anomalies over the southern and northern North Atlantic 10 days earlier (at 95% significance level), that bears a similarity to the North Atlantic Oscillation (NAO). The composite analysis reveals that the NAO impacts the downstream regions including CAWTP by controlling south-north two branches of the middle latitude westerly circulation around the Eurasian border. During the positive phases of the NAO, the northern branch of the westerly circulation goes around the northwest Tibetan Plateau, whereas the southern branch encounters the southwest Tibetan Plateau, which leads to reduced precipitation over the northern Pamir Plateau and increased precipitation over the Karakoram Himalaya, and vice versa.

Impact of the origin of the collateral feeding donor artery on short-term mortality in ST-elevation myocardial infarction with comorbid chronic total occlusion.

PubMed

Fujii, Toshiharu; Sakai, Katsuaki; Nakano, Masataka; Ohno, Yohei; Nakazawa, Gaku; Shinozaki, Norihiko; Matsukage, Takashi; Yoshimachi, Fuminobu; Ikari, Yuji

2016-09-01

Patients with ST-elevation myocardial infarction (STEMI) and multi-vessel disease (MVD) have higher mortality, especially with comorbid chronic total occlusion (CTO). The origin of collateral flow to the CTO segment has not been studied in regard to short-term mortality. This study examined the impact of collateral feeding donor arteries from an infarct-related artery (IRA) or non-IRA to the comorbid CTO segment in regard to STEMI short-term mortality. Data from 760 consecutive STEMI patients who underwent primary percutaneous coronary intervention were obtained retrospectively from medical records. The number of vessels involved and origin of the collateral feeding donor artery were evaluated using angiograms from the primary percutaneous coronary intervention. The study population was divided into patients with: single-vessel disease (SVD) (n=483), MVD without CTO (n=208), and MVD with CTO (n=64). All CTO segments had collateral flow from an IRA (n=23) or non-IRA (n=46). All-cause mortality (30-day) was analyzed. Compared to SVD and MVD without CTO, MVD with comorbid CTO had a higher mortality (5.4% vs. 15.9% vs. 24.6%, P<0.0001, respectively). Of patients with CTO, those with collateral flow from the IRA had significantly higher mortality than the non-IRA group (52.2% vs. 10.9%, P<0.0001). Collateral flow from the IRA was extracted as an independent predictor associated with 30-day all-cause mortality using a multivariate Cox proportional hazards model (hazard ratio 4.71, 95% confidence interval 1.60-14.2, P=0.0005). The origin of the collateral donor artery from the IRA had an impact on short-term mortality in STEMI patients with comorbid CTO lesions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rare variants of the 3’-5’ DNA exonuclease TREX1 in early onset small vessel stroke

PubMed Central

McGlasson, Sarah; Rannikmäe, Kristiina; Bevan, Steven; Logan, Clare; Bicknell, Louise S.; Jury, Alexa; Jackson, Andrew P.

2017-01-01

Background: Monoallelic and biallelic mutations in the exonuclease TREX1 cause monogenic small vessel diseases (SVD). Given recent evidence for genetic and pathophysiological overlap between monogenic and polygenic forms of SVD, evaluation of TREX1 in small vessel stroke is warranted. Methods: We sequenced the TREX1 gene in an exploratory cohort of patients with lacunar stroke (Edinburgh Stroke Study, n=290 lacunar stroke cases). We subsequently performed a fully blinded case-control study of early onset MRI-confirmed small vessel stroke within the UK Young Lacunar Stroke Resource (990 cases, 939 controls). Results: No patients with canonical disease-causing mutations of TREX1 were identified in cases or controls. Analysis of an exploratory cohort identified a potential association between rare variants of TREX1 and patients with lacunar stroke. However, subsequent controlled and blinded evaluation of TREX1 in a larger and MRI-confirmed patient cohort, the UK Young Lacunar Stroke Resource, identified heterozygous rare variants in 2.1% of cases and 2.3% of controls. No association was observed with stroke risk (odds ratio = 0.90; 95% confidence interval, 0.49-1.65 p=0.74). Similarly no association was seen with rare TREX1 variants with predicted deleterious effects on enzyme function (odds ratio = 1.05; 95% confidence interval, 0.43-2.61 p=0.91). Conclusions: No patients with early-onset lacunar stroke had genetic evidence of a TREX1-associated monogenic microangiopathy. These results show no evidence of association between rare variants of TREX1 and early onset lacunar stroke. This includes rare variants that significantly affect protein and enzyme function. Routine sequencing of the TREX1 gene in patients with early onset lacunar stroke is therefore unlikely to be of diagnostic utility, in the absence of syndromic features or family history. PMID:29387804

Mixed-location cerebral hemorrhage/microbleeds: Underlying microangiopathy and recurrence risk.

PubMed

Pasi, Marco; Charidimou, Andreas; Boulouis, Gregoire; Auriel, Eitan; Ayres, Alison; Schwab, Kristin M; Goldstein, Joshua N; Rosand, Jonathan; Viswanathan, Anand; Pantoni, Leonardo; Greenberg, Steven M; Gurol, M Edip

2018-01-09

To assess the predominant type of cerebral small vessel disease (SVD) and recurrence risk in patients who present with a combination of lobar and deep intracerebral hemorrhage (ICH)/microbleed locations (mixed ICH). Of 391 consecutive patients with primary ICH enrolled in a prospective registry, 75 (19%) had mixed ICH. Their demographics, clinical/laboratory features, and SVD neuroimaging markers were compared to those of 191 patients with probable cerebral amyloid angiopathy (CAA-ICH) and 125 with hypertensive strictly deep microbleeds and ICH (HTN-ICH). ICH recurrence and case fatality were also analyzed. Patients with mixed ICH showed a higher burden of vascular risk factors reflected by a higher rate of left ventricular hypertrophy, higher creatinine values, and more lacunes and severe basal ganglia (BG) enlarged perivascular spaces (EPVS) than patients with CAA-ICH (all p < 0.05). In multivariable models mixed ICH diagnosis was associated with higher creatinine levels (odds ratio [OR] 2.5, 95% confidence interval [CI] 1.2-5.0, p = 0.010), more lacunes (OR 3.4, 95% CI 1.7-6.8), and more severe BG EPVS (OR 5.8, 95% CI 1.7-19.7) than patients with CAA-ICH. Conversely, when patients with mixed ICH were compared to patients with HTN-ICH, they were independently associated with older age (OR 1.03, 95% CI 1.02-1.1), more lacunes (OR 2.4, 95% CI 1.1-5.3), and higher microbleed count (OR 1.6, 95% CI 1.3-2.0). Among 90-day survivors, adjusted case fatality rates were similar for all 3 categories. Annual risk of ICH recurrence was 5.1% for mixed ICH, higher than for HTN-ICH but lower than for CAA-ICH (1.6% and 10.4%, respectively). Mixed ICH, commonly seen on MRI obtained during etiologic workup, appears to be driven mostly by vascular risk factors similar to HTN-ICH but demonstrates more severe parenchymal damage and higher ICH recurrence risk. Copyright © 2017 American Academy of Neurology.

Explosion Source Similarity Analysis via SVD

NASA Astrophysics Data System (ADS)

Yedlin, Matthew; Ben Horin, Yochai; Margrave, Gary

2016-04-01

An important seismological ingredient for establishing a regional seismic nuclear discriminant is the similarity analysis of a sequence of explosion sources. To investigate source similarity, we are fortunate to have access to a sequence of 1805 three-component recordings of quarry blasts, shot from March 2002 to January 2015. The centroid of these blasts has an estimated location 36.3E and 29.9N. All blasts were detonated by JPMC (Jordan Phosphate Mines Co.) All data were recorded at the Israeli NDC, HFRI, located at 30.03N and 35.03E. Data were first winnowed based on the distribution of maximum amplitudes in the neighborhood of the P-wave arrival. The winnowed data were then detrended using the algorithm of Cleveland et al (1990). The detrended data were bandpass filtered between .1 to 12 Hz using an eighth order Butterworth filter. Finally, data were sorted based on maximum trace amplitude. Two similarity analysis approaches were used. First, for each component, the entire suite of traces was decomposed into its eigenvector representation, by employing singular-valued decomposition (SVD). The data were then reconstructed using 10 percent of the singular values, with the resulting enhancement of the S-wave and surface wave arrivals. The results of this first method are then compared to the second analysis method based on the eigenface decomposition analysis of Turk and Pentland (1991). While both methods yield similar results in enhancement of data arrivals and reduction of data redundancy, more analysis is required to calibrate the recorded data to charge size, a quantity that was not available for the current study. References Cleveland, R. B., Cleveland, W. S., McRae, J. E., and Terpenning, I., Stl: A seasonal-trend decomposition procedure based on loess, Journal of Official Statistics, 6, No. 1, 3-73, 1990. Turk, M. and Pentland, A., Eigenfaces for recognition. Journal of cognitive neuroscience, 3(1), 71-86, 1991.

The primary vascular dysregulation syndrome: implications for eye diseases

PubMed Central

2013-01-01

Vascular dysregulation refers to the regulation of blood flow that is not adapted to the needs of the respective tissue. We distinguish primary vascular dysregulation (PVD, formerly called vasospastic syndrome) and secondary vascular dysregulation (SVD). Subjects with PVD tend to have cold extremities, low blood pressure, reduced feeling of thirst, altered drug sensitivity, increased pain sensitivity, prolonged sleep onset time, altered gene expression in the lymphocytes, signs of oxidative stress, slightly increased endothelin-1 plasma level, low body mass index and often diffuse and fluctuating visual field defects. Coldness, emotional or mechanical stress and starving can provoke symptoms. Virtually all organs, particularly the eye, can be involved. In subjects with PVD, retinal vessels are stiffer and more irregular, and both neurovascular coupling and autoregulation capacity are reduced while retinal venous pressure is often increased. Subjects with PVD have increased risk for normal-tension glaucoma, optic nerve compartment syndrome, central serous choroidopathy, Susac syndrome, retinal artery and vein occlusions and anterior ischaemic neuropathy without atherosclerosis. Further characteristics are their weaker blood–brain and blood-retinal barriers and the higher prevalence of optic disc haemorrhages and activated astrocytes. Subjects with PVD tend to suffer more often from tinnitus, muscle cramps, migraine with aura and silent myocardial ischaemic and are at greater risk for altitude sickness. While the main cause of vascular dysregulation is vascular endotheliopathy, dysfunction of the autonomic nervous system is also involved. In contrast, SVD occurs in the context of other diseases such as multiple sclerosis, retrobulbar neuritis, rheumatoid arthritis, fibromyalgia and giant cell arteritis. Taking into consideration the high prevalence of PVD in the population and potentially linked pathologies, in the current article, the authors provide recommendations on how to effectively promote the field in order to create innovative diagnostic tools to predict the pathology and develop more efficient treatment approaches tailored to the person. PMID:23742177

Inferior sinus venosus defects: anatomic features and echocardiographic correlates.

PubMed

Plymale, Jennifer; Kolinski, Kellen; Frommelt, Peter; Bartz, Peter; Tweddell, James; Earing, Michael G

2013-02-01

Inferior sinus venosus defects (SVDs) are rare imperfections located in the inferior portion of the atrial septum, leading to an overriding inferior vena cava (IVC) and an interatrial connection. These defects have increased risk of anomalous pulmonary venous return (PAPVR) and often are confused with secundum atrial septal defects (ASDs) with inferior extension. The authors sought to review their experience with inferior SVDs and to establish at their institution an echocardiographic definition that differentiates inferior SVDs from secundum ASDs with inferior extension. The study identified 161 patients 1.5 to 32 years of age who had undergone repair of a secundum ASD with inferior extension or inferior SVD over the preceding 10 years. All surgical notes, preoperative transthoracic echocardiograms (TTEs), and preoperative transesophageal echocardiograms (TEEs) were reviewed. Based on the surgical notes, 147 patients were classified as having a secundum ASD (147/161, 91 %) and 14 patients (9 %) as having an inferior SVD. The study identified PAPVR in 7 % (1/14) of the patients with inferior SVDs and 3.5 % (5/14) of the patients with secundum ASDs. Surgical diagnosis and preoperative TTE correlated for 143 (89 %) of the 161 patients. Using a strict anatomic and echocardiographic definition with a blinded observer, the majority of the defects (14/18, 78 %) were reclassified correctly after review of their TTE images, and 100 % of the defects were correctly reclassified after TEE image review. Accurate diagnosis of inferior SVDs remains challenging. The data from this study demonstrate that use of a strict anatomic and echocardiographic definition (a defect that originates in the mouth of the IVC and continues into the inferoposterior border of the left atrium, leaving no residual atrial septal tissue at the inferior margin) allows for accurate differentiation between secundum ASDs with inferior extension and inferior SVDs. This differentiation is extremely important in planning for surgical versus device closure of these rare defects.

SVD/MCMC Data Analysis Pipeline for Global Redshifted 21-cm Spectrum Observations of the Cosmic Dawn and Dark Ages

NASA Astrophysics Data System (ADS)

Burns, Jack O.; Tauscher, Keith; Rapetti, David; Mirocha, Jordan; Switzer, Eric

2018-01-01

We have designed a complete data analysis pipeline for constraining Cosmic Dawn physics using sky-averaged spectra in the VHF range (40-200 MHz) obtained either from the ground (e.g., the Experiment to Detect Global Epoch of Reionization Signal, EDGES; and the Cosmic Twilight Polarimeter, CTP) or from orbit above the lunar farside (e.g., the Dark Ages Radio Explorer, DARE). In the case of DARE, we avoid Earth-based RFI, ionospheric effects, and radio solar emissions (when observing at night). To extract the 21-cm spectrum, we parametrize the cosmological signal and systematics with two separate sets of modes defined through Singular Value Decomposition (SVD) of training set curves. The training set for the 21-cm spin-flip brightness temperatures is composed of theoretical models of the first stars, galaxies and black holes created by varying physical parameters within the ares code. The systematics training set is created using sky and beam data to model the beam-weighted foregrounds (which are about four orders of magnitude larger than the signal) as well as expected lab data to model receiver systematics. To constrain physical parameters determining the 21-cm spectrum, we apply to the extracted signal a series of consecutive fitting techniques including two usages of a Markov Chain Monte Carlo (MCMC) algorithm. Importantly, our pipeline efficiently utilizes the significant differences between the foreground and the 21-cm signal in spatial and spectral variations. In addition, it incorporates for the first time polarization data, dramatically improving the constraining power. We are currently validating this end-to-end pipeline using detailed simulations of the signal, foregrounds and instruments. This work was directly supported by the NASA Solar System Exploration Research Virtual Institute cooperative agreement number 80ARC017M0006 and funding from the NASA Ames Research Center cooperative agreement NNX16AF59G.

Hybrid method based on singular value decomposition and embedded zero tree wavelet technique for ECG signal compression.

PubMed

Kumar, Ranjeet; Kumar, A; Singh, G K

2016-06-01

In the field of biomedical, it becomes necessary to reduce data quantity due to the limitation of storage in real-time ambulatory system and telemedicine system. Research has been underway since very beginning for the development of an efficient and simple technique for longer term benefits. This paper, presents an algorithm based on singular value decomposition (SVD), and embedded zero tree wavelet (EZW) techniques for ECG signal compression which deals with the huge data of ambulatory system. The proposed method utilizes the low rank matrix for initial compression on two dimensional (2-D) ECG data array using SVD, and then EZW is initiated for final compression. Initially, 2-D array construction has key issue for the proposed technique in pre-processing. Here, three different beat segmentation approaches have been exploited for 2-D array construction using segmented beat alignment with exploitation of beat correlation. The proposed algorithm has been tested on MIT-BIH arrhythmia record, and it was found that it is very efficient in compression of different types of ECG signal with lower signal distortion based on different fidelity assessments. The evaluation results illustrate that the proposed algorithm has achieved the compression ratio of 24.25:1 with excellent quality of signal reconstruction in terms of percentage-root-mean square difference (PRD) as 1.89% for ECG signal Rec. 100 and consumes only 162bps data instead of 3960bps uncompressed data. The proposed method is efficient and flexible with different types of ECG signal for compression, and controls quality of reconstruction. Simulated results are clearly illustrate the proposed method can play a big role to save the memory space of health data centres as well as save the bandwidth in telemedicine based healthcare systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Predict subcellular locations of singleplex and multiplex proteins by semi-supervised learning and dimension-reducing general mode of Chou's PseAAC.

PubMed

Pacharawongsakda, Eakasit; Theeramunkong, Thanaruk

2013-12-01

Predicting protein subcellular location is one of major challenges in Bioinformatics area since such knowledge helps us understand protein functions and enables us to select the targeted proteins during drug discovery process. While many computational techniques have been proposed to improve predictive performance for protein subcellular location, they have several shortcomings. In this work, we propose a method to solve three main issues in such techniques; i) manipulation of multiplex proteins which may exist or move between multiple cellular compartments, ii) handling of high dimensionality in input and output spaces and iii) requirement of sufficient labeled data for model training. Towards these issues, this work presents a new computational method for predicting proteins which have either single or multiple locations. The proposed technique, namely iFLAST-CORE, incorporates the dimensionality reduction in the feature and label spaces with co-training paradigm for semi-supervised multi-label classification. For this purpose, the Singular Value Decomposition (SVD) is applied to transform the high-dimensional feature space and label space into the lower-dimensional spaces. After that, due to limitation of labeled data, the co-training regression makes use of unlabeled data by predicting the target values in the lower-dimensional spaces of unlabeled data. In the last step, the component of SVD is used to project labels in the lower-dimensional space back to those in the original space and an adaptive threshold is used to map a numeric value to a binary value for label determination. A set of experiments on viral proteins and gram-negative bacterial proteins evidence that our proposed method improve the classification performance in terms of various evaluation metrics such as Aiming (or Precision), Coverage (or Recall) and macro F-measure, compared to the traditional method that uses only labeled data.

Influence of the Cyclooxygenase-2 Gene -765G/C and -1195G/A Polymorphisms on Development of Ischemic Stroke.

PubMed

Wu, Guangliang; Cai, Haiyan; Cai, Haobin; Chen, Zhao; Tan, Lei; Qin, Xiurong; Cai, Yefeng

2016-09-01

Many studies have investigated the association between the cyclooxygenase-2 (COX-2) gene polymorphism and ischemic stroke. However, results of these studies still remain controversial. To better explain the association between COX-2 polymorphisms (-765G/C and -1195G/A) and ischemic stroke risk, a meta-analysis was performed. Relevant studies were identified from 4 Chinese databases (Chinese Biological Medical Literature database, Chinese National Knowledge Infrastructure database, Chongqing VIP database, and Chinese WANFANG database), PUBMED and EMBASE prior to December 2015. The strength of association between COX-2 polymorphism and ischemic stroke was evaluated by the odds ratio (OR) with 95% confidence interval (CI). Inconsistency index (I(2)) and the Cochran's Q statistic were used to check heterogeneity. Publication bias was evaluated by funnel plots and Egger's regression test. A total of 4086 ischemic stroke cases and 4747 controls were identified. Significant association between COX-2 -765G/C polymorphism and the risk of ischemic stroke was found in Brazilians and the African-Americans. The OR of (CC+GC versus GG) for the Brazilians and African-Americans were (6.328, 95% CI = 2.295-17.448) and (1.644, 95% CI = 1.060-2.551). In addition, the recessive model of the Brazilians gave an OR of 3.621 (95% CI: 1.519-8.630). Furthermore, the (GC versus GG) and the allele model of the African-Americans were (OR: 1.615, 95% CI = 1.015-2.572) and (OR: 1.422, 95% CI = 1.033-1.957). Significant association was also observed for COX-2 -1195G/A polymorphism in the subtypes of small vessel disease (SVD) of ischemic stroke. Our study suggests that COX-2 -765G/C and -1195G/A polymorphisms may contribute to susceptibility of ischemic stroke, specifically in Brazilians and the African-Americans, and those of SVD. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Detection of white matter lesions in cerebral small vessel disease

NASA Astrophysics Data System (ADS)

Riad, Medhat M.; Platel, Bram; de Leeuw, Frank-Erik; Karssemeijer, Nico

2013-02-01

White matter lesions (WML) are diffuse white matter abnormalities commonly found in older subjects and are important indicators of stroke, multiple sclerosis, dementia and other disorders. We present an automated WML detection method and evaluate it on a dataset of small vessel disease (SVD) patients. In early SVD, small WMLs are expected to be of importance for the prediction of disease progression. Commonly used WML segmentation methods tend to ignore small WMLs and are mostly validated on the basis of total lesion load or a Dice coefficient for all detected WMLs. Therefore, in this paper, we present a method that is designed to detect individual lesions, large or small, and we validate the detection performance of our system with FROC (free-response ROC) analysis. For the automated detection, we use supervised classification making use of multimodal voxel based features from different magnetic resonance imaging (MRI) sequences, including intensities, tissue probabilities, voxel locations and distances, neighborhood textures and others. After preprocessing, including co-registration, brain extraction, bias correction, intensity normalization, and nonlinear registration, ventricle segmentation is performed and features are calculated for each brain voxel. A gentle-boost classifier is trained using these features from 50 manually annotated subjects to give each voxel a probability of being a lesion voxel. We perform ROC analysis to illustrate the benefits of using additional features to the commonly used voxel intensities; significantly increasing the area under the curve (Az) from 0.81 to 0.96 (p<0.05). We perform the FROC analysis by testing our classifier on 50 previously unseen subjects and compare the results with manual annotations performed by two experts. Using the first annotator results as our reference, the second annotator performs at a sensitivity of 0.90 with an average of 41 false positives per subject while our automated method reached the same level of sensitivity at approximately 180 false positives per subject.

Rational design of orally-active, pyrrolidine-based progesterone receptor partial agonists

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

Thompson, Scott K.; Washburn, David G.; Frazee, James S.

2010-09-03

Using the X-ray crystal structure of an amide-based progesterone receptor (PR) partial agonist bound to the PR ligand binding domain, a novel PR partial agonist class containing a pyrrolidine ring was designed. Members of this class of N-alkylpyrrolidines demonstrate potent and highly selective partial agonism of the progesterone receptor, and one of these analogs was shown to be efficacious upon oral dosing in the OVX rat model of estrogen opposition.

Structural physical approximation for the realization of the optimal singlet fraction with two measurements

NASA Astrophysics Data System (ADS)

Adhikari, Satyabrata

2018-04-01

Structural physical approximation (SPA) has been exploited to approximate nonphysical operation such as partial transpose. It has already been studied in the context of detection of entanglement and found that if the minimum eigenvalue of SPA to partial transpose is less than 2/9 then the two-qubit state is entangled. We find application of SPA to partial transpose in the estimation of the optimal singlet fraction. We show that the optimal singlet fraction can be expressed in terms of the minimum eigenvalue of SPA to partial transpose. We also show that the optimal singlet fraction can be realized using Hong-Ou-Mandel interferometry with only two detectors. Further we have shown that the generated hybrid entangled state between a qubit and a binary coherent state can be used as a resource state in quantum teleportation.

Mapping of the Resistance of a Superconducting Transition Edge Sensor as a Function of Temperature, Current, and Applied Magnetic Field

NASA Technical Reports Server (NTRS)

Zhang, Shou; Eckart, Megan E.; Jaeckel, Felix; Kripps, Kari L.; McCammon, Dan; Zhou, Yu; Morgan, Kelsey M.

2017-01-01

We have measured the resistance R (T, I, B(sub ext) of a superconducting transition edge sensor over the entire transition region on a fine scale, producing a four-dimensional map of the resistance surface. The dimensionless temperature and current sensitivities (alpha equivalence partial derivative log R/partial derivative log T|(sub I) and beta equivalence partial derivative log R/partial derivative log I|(sub T) of the TES resistance have been determined at each point. alpha and beta are closely related to the sensor performance, but show a great deal of complex, large amplitude fine structure over large portions of the surface that is sensitive to the applied magnetic field. We discuss the relation of this structure to the presence of Josephson weak link fringes.

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

Smith, S; Danganan, L; Tammero, L

Lawrence Livermore National Laboratory (LLNL), in collaboration with the Department of Homeland Security (DHS) and the United States Department of Agriculture (USDA), Animal and Plant Health Inspection Services (APHIS) has developed advanced rapid diagnostics that may be used within the National Animal Health Laboratory Network (NAHLN), the National Veterinary Services Laboratory (Ames, Iowa) and the Plum Island Animal Disease Center (PIADC). This effort has the potential to improve our nation's ability to discriminate between foreign animal diseases and those that are endemic using a single assay, thereby increasing our ability to protect animal populations of high economic importance in themore » United States. Under 2005 DHS funding we have developed multiplexed (MUX) nucleic-acid-based PCR assays that combine foot-and-mouth disease virus (FMDV) detection with rule-out tests for two other foreign animal diseases Vesicular Exanthema of Swine (VESV) and Swine Vesicular Disease (SVD) and four other domestic viral diseases Bovine Viral Diarrhea Virus (BVDV), Bovine Herpes Virus 1 (BHV-1 or Infectious Bovine Rhinotracheitus IBR), Bluetongue virus (BTV) and Parapox virus complex (which includes Bovine Papular Stomatitis Virus BPSV, Orf of sheep, and Pseudocowpox). Under 2006 funding we have developed a Multiplexed PCR [MUX] porcine assay for detection of FMDV with rule out tests for VESV and SVD foreign animal diseases in addition to one other domestic vesicular animal disease vesicular stomatitis virus (VSV) and one domestic animal disease of swine porcine reproductive and respiratory syndrome (PRRS). We have also developed a MUX bovine assay for detection of FMDV with rule out tests for the two bovine foreign animal diseases malignant catarrhal fever (MCF), rinderpest virus (RPV) and the domestic diseases vesicular stomatitis virus (VSV), bovine viral diarrhea virus (BVDV), infectious bovine rhinotracheitus virus (BHV-1), bluetongue virus (BTV), and the Parapox viruses which are of two bovine types bovine papular stomatitis virus (BPSV) and psuedocowpox (PCP). This document provides details of signature generation, evaluation, and testing, as well as the specific methods and materials used. A condensed summary of the development, testing and performance of the multiplexed assay panel was presented in a 126 page separate document, entitled 'Development and Characterization of A Multiplexed RT-PCR Species Specific Assay for Bovine and one for Porcine Foot-and-Mouth Disease Virus Rule-Out'. This supplemental document provides additional details of large amount of data collected for signature generation, evaluation, and testing, as well as the specific methods and materials used for all steps in the assay development and utilization processes. In contrast to last years effort, the development of the bovine and porcine panels is pending additional work to complete analytical characterization of FMDV, VESV, VSV, SVD, RPV and MCF. The signature screening process and final panel composition impacts this effort. The unique challenge presented this year was having strict predecessor limitations in completing characterization, where efforts at LLNL must preceed efforts at PIADC, such challenges were alleviated in the 2006 reporting by having characterization data from the interlaboratory comparison and at Plum Island under AgDDAP project. We will present an addendum at a later date with additional data on the characterization of the porcine and bovine multiplex assays when that data is available.« less

Shock-wave structure in a partially ionized gas

NASA Technical Reports Server (NTRS)

Lu, C. S.; Huang, A. B.

1974-01-01

The structure of a steady plane shock in a partially ionized gas has been investigated using the Boltzmann equation with a kinetic model as the governing equation and the discrete ordinate method as a tool. The effects of the electric field induced by the charge separation on the shock structure have also been studied. Although the three species of an ionized gas travel with approximately the same macroscopic velocity, the individual distribution functions are found to be very different. In a strong shock the atom distribution function may have double peaks, while the ion distribution function has only one peak. Electrons are heated up much earlier than ions and atoms in a partially ionized gas. Because the interactions of electrons with atoms and with ions are different, the ion temperature can be different from the atom temperature.

The Role of a Novel Myosin Isoform in Prostate Cancer Metastasis

DTIC Science & Technology

2013-10-01

of unconventional myosin function and targeting, Annu. Rev. Cell Dev. Biol. 27 (2011) 133–155. [42] W. Kliche, S. Fujita- Becker , M. Kollmar, D.J...tissue-specific diseases (laminopathies), including Emery–Dreifuss muscular dystrophy , Dunnigan-type familial partial lipodystrophy (FPLD), and...structure of the C-terminal domain of lamin A/C, mutated in muscular dystrophies , cardiomyopathy, and partial lipodystrophy. Structure 10, 811–823