Infant Manipulative Actions upon Customary and Uncustomary Objects in Independent and Joint Activity.

ERIC Educational Resources Information Center

Aureli, Tiziana; De Tommasi, Emilia

1999-01-01

Observed 12-month olds, with their mothers and independently, acting on objects from home and objects brought by the experimenter as new exemplars of previous toys. Found that conventional actions were more frequent in joint than in independent activity. In independent activity, conventional actions were more frequent with customary than with…

Independent component analysis for automatic note extraction from musical trills

NASA Astrophysics Data System (ADS)

Brown, Judith C.; Smaragdis, Paris

2004-05-01

The method of principal component analysis, which is based on second-order statistics (or linear independence), has long been used for redundancy reduction of audio data. The more recent technique of independent component analysis, enforcing much stricter statistical criteria based on higher-order statistical independence, is introduced and shown to be far superior in separating independent musical sources. This theory has been applied to piano trills and a database of trill rates was assembled from experiments with a computer-driven piano, recordings of a professional pianist, and commercially available compact disks. The method of independent component analysis has thus been shown to be an outstanding, effective means of automatically extracting interesting musical information from a sea of redundant data.

Tribological performance of the biological components of synovial fluid in artificial joint implants

NASA Astrophysics Data System (ADS)

Ghosh, Subir; Choudhury, Dipankar; Roy, Taposh; Moradi, Ali; Masjuki, H. H.; Pingguan-Murphy, Belinda

2015-08-01

The concentration of biological components of synovial fluid (such as albumin, globulin, hyaluronic acid, and lubricin) varies between healthy persons and osteoarthritis (OA) patients. The aim of the present study is to compare the effects of such variation on tribological performance in a simulated hip joint model. The study was carried out experimentally by utilizing a pin-on-disk simulator on ceramic-on-ceramic (CoC) and ceramic-on-polyethylene (CoP) hip joint implants. The experimental results show that both friction and wear of artificial joints fluctuate with the concentration level of biological components. Moreover, the performance also varies between material combinations. Wear debris sizes and shapes produced by ceramic and polyethylene were diverse. We conclude that the biological components of synovial fluid and their concentrations should be considered in order to select an artificial hip joint to best suit that patient.

Is There a Need For a Joint Reserve Components Command?

DTIC Science & Technology

2013-03-01

Bravo Zulu ”. If these words were heard by a Soldier, it might be interpreted as poor performance. By having one organization as a single source for...Commander, Joint Reserve Components Command. Creation of the JRCC would, in time, strengthen partnerships between the reserve components of each

Independent component analysis decomposition of hospital emergency department throughput measures

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Henry

2016-05-01

We present a method adapted from medical sensor data analysis, viz. independent component analysis of electroencephalography data, to health system analysis. Timely and effective care in a hospital emergency department is measured by throughput measures such as median times patients spent before they were admitted as an inpatient, before they were sent home, before they were seen by a healthcare professional. We consider a set of five such measures collected at 3,086 hospitals distributed across the U.S. One model of the performance of an emergency department is that these correlated throughput measures are linear combinations of some underlying sources. The independent component analysis decomposition of the data set can thus be viewed as transforming a set of performance measures collected at a site to a collection of outputs of spatial filters applied to the whole multi-measure data. We compare the independent component sources with the output of the conventional principal component analysis to show that the independent components are more suitable for understanding the data sets through visualizations.

Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

2008-06-01

Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Copyright 2007 Wiley-Liss, Inc.

Recrystallization Behavior in Mixed Solder Joints of BGA Components during Thermal Shock

NASA Astrophysics Data System (ADS)

Tan, Shihai; Han, Jing; Guo, Fu

2018-03-01

Sn-37Pb and Sn-3.0Ag-0.5Cu solder pastes printed onto a board were attached to ball grid array (BGA) samples using Sn-3.0Ag-0.5Cu solder balls. Before thermal shock, the initial grain orientations on the cross-section were obtained by scanning electron microscopy equipped with an electron backscattered diffraction system. Three mixed solder joints (two from the corner and another from the middle of the BGA component) and three lead-free solder joints (at the same positions) were selected to investigate the recrystallization behavior under thermal shock (TS) cycling conditions. All of the mixed and lead-free solder joints were initially single crystal. The results showed that recrystallization occurred in both the mixed and lead-free solder joints after 200 TS. For the mixed solder joints, more recrystallization was observed and the location of samples had a significant influence on their recrystallization behavior, while location was not as important for the lead-free samples after 200 TS in this study. Both the mixed and lead-free solder joints at the corner of BGA components showed the poorest reliability. According to misorientation distribution maps and subgrain rotation behaviors, the reliability of mixed solder joints was much poorer than that of lead-free solder joints.

Determining the optimal number of independent components for reproducible transcriptomic data analysis.

PubMed

Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

2017-09-11

Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

Joint Integration Office Independent Review Committee annual report, 1985

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

Not Available

Comprised of seven persons with extensive experience in the issues of nuclear waste, the Independent Review Committee (IRC) provides independent and objective review of Defense Transuranic Waste Program (DTWP) activities managed by the Joint Integration Office (JIO), formerly the Defense Transuranic Waste Lead Organization (TLO). The Committee is ensured a broad, interdisciplinary perspective since its membership includes representatives from the fields of nuclear engineering, nuclear waste transportation, industrial quality control, systems and environmental engineering and state and local government. The scope of IRC activities includes overall review of specific TLO plans, projects and activities, and technical review of particular researchmore » and development projects. The Committee makes specific suggestions and recommendations based upon expertise in the field of TRU Waste Management. The IRC operates as a consulting group, under an independent charter providing objective review of program activities. This report summarizes the 12 major topics reviewed by the committee during 1985.« less

When 1+1=1: the unification of independent actors revealed through joint Simon effects in crossed and uncrossed effector conditions.

PubMed

Welsh, Timothy N

2009-12-01

The "Simon effect" describes a pattern of reaction times (RTs) where responses to symbolic information are shorter when the information is presented on the same side of space as the desired response than when it is on the opposite side of space. For example, if right hand responses are required for green targets and left hand responses for red targets, RTs with the right hand are shorter when the green target appears on the right side than on the left side. It has been reported that Simon effects also appear when two individuals perform independent components of a Simon effect task. It has been suggested that such joint Simon effects occur because participants represent the action of their partner. It is unclear, however, if the joint Simon effect emerges because: (1) each partner represents the other's action; (2) each partner is using the other person or their response as an environmental reference; or (3) an intra-hemispheric processing advantage due to the lateralized cerebral organization of perceptual and motor systems. The present study distinguished between these possibilities by asking pairs of participants to perform in conditions in which they crossed their arms into the other person's space. Consistent with within-person Simon effects, joint Simon effects were observed in uncrossed- and crossed limb conditions. These results support a response co-representation explanation of joint Simon effects. It is suggested that the processes underlying the evoked representations have developed to allow two independent agents to form temporary synergies to facilitate efficient task completion. 2009 Elsevier B.V. All rights reserved.

Analysis of singular interface stresses in dissimilar material joints for plasma facing components

NASA Astrophysics Data System (ADS)

You, J. H.; Bolt, H.

2001-10-01

Duplex joint structures are typical material combinations for the actively cooled plasma facing components of fusion devices. The structural integrity under the incident heat loads from the plasma is one of the most crucial issues in the technology of these components. The most critical domain in a duplex joint component is the free surface edge of the bond interface between heterogeneous materials. This is due to the fact that the thermal stress usually shows a singular intensification in this region. If the plasma facing armour tile consists of a brittle material, the existence of the stress singularity can be a direct cause of failure. The present work introduces a comprehensive analytical tool to estimate the impact of the stress singularity for duplex PFC design and quantifies the relative stress intensification in various materials joints by use of a model formulated by Munz and Yang. Several candidate material combinations of plasma facing armour and metallic heat sink are analysed and the results are compared with each other.

Partitioning diversity into independent alpha and beta components.

PubMed

Jost, Lou

2007-10-01

Existing general definitions of beta diversity often produce a beta with a hidden dependence on alpha. Such a beta cannot be used to compare regions that differ in alpha diversity. To avoid misinterpretation, existing definitions of alpha and beta must be replaced by a definition that partitions diversity into independent alpha and beta components. Such a unique definition is derived here. When these new alpha and beta components are transformed into their numbers equivalents (effective numbers of elements), Whittaker's multiplicative law (alpha x beta = gamma) is necessarily true for all indices. The new beta gives the effective number of distinct communities. The most popular similarity and overlap measures of ecology (Jaccard, Sorensen, Horn, and Morisita-Horn indices) are monotonic transformations of the new beta diversity. Shannon measures follow deductively from this formalism and do not need to be borrowed from information theory; they are shown to be the only standard diversity measures which can be decomposed into meaningful independent alpha and beta components when community weights are unequal.

A review of typical thermal fatigue failure models for solder joints of electronic components

NASA Astrophysics Data System (ADS)

Li, Xiaoyan; Sun, Ruifeng; Wang, Yongdong

2017-09-01

For electronic components, cyclic plastic strain makes it easier to accumulate fatigue damage than elastic strain. When the solder joints undertake thermal expansion or cold contraction, different thermal strain of the electronic component and its corresponding substrate is caused by the different coefficient of thermal expansion of the electronic component and its corresponding substrate, leading to the phenomenon of stress concentration. So repeatedly, cracks began to sprout and gradually extend [1]. In this paper, the typical thermal fatigue failure models of solder joints of electronic components are classified and the methods of obtaining the parameters in the model are summarized based on domestic and foreign literature research.

Conformational states and folding pathways of peptides revealed by principal-independent component analyses.

PubMed

Nguyen, Phuong H

2007-05-15

Principal component analysis is a powerful method for projecting multidimensional conformational space of peptides or proteins onto lower dimensional subspaces in which the main conformations are present, making it easier to reveal the structures of molecules from e.g. molecular dynamics simulation trajectories. However, the identification of all conformational states is still difficult if the subspaces consist of more than two dimensions. This is mainly due to the fact that the principal components are not independent with each other, and states in the subspaces cannot be visualized. In this work, we propose a simple and fast scheme that allows one to obtain all conformational states in the subspaces. The basic idea is that instead of directly identifying the states in the subspace spanned by principal components, we first transform this subspace into another subspace formed by components that are independent of one other. These independent components are obtained from the principal components by employing the independent component analysis method. Because of independence between components, all states in this new subspace are defined as all possible combinations of the states obtained from each single independent component. This makes the conformational analysis much simpler. We test the performance of the method by analyzing the conformations of the glycine tripeptide and the alanine hexapeptide. The analyses show that our method is simple and quickly reveal all conformational states in the subspaces. The folding pathways between the identified states of the alanine hexapeptide are analyzed and discussed in some detail. 2007 Wiley-Liss, Inc.

Joint Procrustes Analysis for Simultaneous Nonsingular Transformation of Component Score and Loading Matrices

ERIC Educational Resources Information Center

Adachi, Kohei

2009-01-01

In component analysis solutions, post-multiplying a component score matrix by a nonsingular matrix can be compensated by applying its inverse to the corresponding loading matrix. To eliminate this indeterminacy on nonsingular transformation, we propose Joint Procrustes Analysis (JPA) in which component score and loading matrices are simultaneously…

Nonlinear Extraction of Independent Components of Natural Images Using Radial Gaussianization

PubMed Central

Lyu, Siwei; Simoncelli, Eero P.

2011-01-01

We consider the problem of efficiently encoding a signal by transforming it to a new representation whose components are statistically independent. A widely studied linear solution, known as independent component analysis (ICA), exists for the case when the signal is generated as a linear transformation of independent nongaussian sources. Here, we examine a complementary case, in which the source is nongaussian and elliptically symmetric. In this case, no invertible linear transform suffices to decompose the signal into independent components, but we show that a simple nonlinear transformation, which we call radial gaussianization (RG), is able to remove all dependencies. We then examine this methodology in the context of natural image statistics. We first show that distributions of spatially proximal bandpass filter responses are better described as elliptical than as linearly transformed independent sources. Consistent with this, we demonstrate that the reduction in dependency achieved by applying RG to either nearby pairs or blocks of bandpass filter responses is significantly greater than that achieved by ICA. Finally, we show that the RG transformation may be closely approximated by divisive normalization, which has been used to model the nonlinear response properties of visual neurons. PMID:19191599

Classification of independent components of EEG into multiple artifact classes.

PubMed

Frølich, Laura; Andersen, Tobias S; Mørup, Morten

2015-01-01

In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification performances were obtained. Between studies, however, classification was more difficult. For neural versus nonneural classifications, performance was on par with previous results obtained by others. We found that automatic separation of multiple artifact classes is possible with a small feature set. Our method can reduce manual workload and allow for the selective removal of artifact classes. Identifying artifacts during EEG recording may be used to instruct subjects to refrain from activity causing them. Copyright © 2014 Society for Psychophysiological Research.

A comparison of independent component analysis algorithms and measures to discriminate between EEG and artifact components.

PubMed

Dharmaprani, Dhani; Nguyen, Hoang K; Lewis, Trent W; DeLosAngeles, Dylan; Willoughby, John O; Pope, Kenneth J

2016-08-01

Independent Component Analysis (ICA) is a powerful statistical tool capable of separating multivariate scalp electrical signals into their additive independent or source components, specifically EEG or electroencephalogram and artifacts. Although ICA is a widely accepted EEG signal processing technique, classification of the recovered independent components (ICs) is still flawed, as current practice still requires subjective human decisions. Here we build on the results from Fitzgibbon et al. [1] to compare three measures and three ICA algorithms. Using EEG data acquired during neuromuscular paralysis, we tested the ability of the measures (spectral slope, peripherality and spatial smoothness) and algorithms (FastICA, Infomax and JADE) to identify components containing EMG. Spatial smoothness showed differentiation between paralysis and pre-paralysis ICs comparable to spectral slope, whereas peripherality showed less differentiation. A combination of the measures showed better differentiation than any measure alone. Furthermore, FastICA provided the best discrimination between muscle-free and muscle-contaminated recordings in the shortest time, suggesting it may be the most suited to EEG applications of the considered algorithms. Spatial smoothness results suggest that a significant number of ICs are mixed, i.e. contain signals from more than one biological source, and so the development of an ICA algorithm that is optimised to produce ICs that are easily classifiable is warranted.

Selection of independent components based on cortical mapping of electromagnetic activity

NASA Astrophysics Data System (ADS)

Chan, Hui-Ling; Chen, Yong-Sheng; Chen, Li-Fen

2012-10-01

Independent component analysis (ICA) has been widely used to attenuate interference caused by noise components from the electromagnetic recordings of brain activity. However, the scalp topographies and associated temporal waveforms provided by ICA may be insufficient to distinguish functional components from artifactual ones. In this work, we proposed two component selection methods, both of which first estimate the cortical distribution of the brain activity for each component, and then determine the functional components based on the parcellation of brain activity mapped onto the cortical surface. Among all independent components, the first method can identify the dominant components, which have strong activity in the selected dominant brain regions, whereas the second method can identify those inter-regional associating components, which have similar component spectra between a pair of regions. For a targeted region, its component spectrum enumerates the amplitudes of its parceled brain activity across all components. The selected functional components can be remixed to reconstruct the focused electromagnetic signals for further analysis, such as source estimation. Moreover, the inter-regional associating components can be used to estimate the functional brain network. The accuracy of the cortical activation estimation was evaluated on the data from simulation studies, whereas the usefulness and feasibility of the component selection methods were demonstrated on the magnetoencephalography data recorded from a gender discrimination study.

21 CFR 888.3320 - Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Hip joint metal/metal semi-constrained, with a... Devices § 888.3320 Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis. (a) Identification. A hip joint metal/metal semi-constrained, with a cemented acetabular...

21 CFR 888.3320 - Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Hip joint metal/metal semi-constrained, with a... Devices § 888.3320 Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis. (a) Identification. A hip joint metal/metal semi-constrained, with a cemented acetabular...

Independent control of joint stiffness in the framework of the equilibrium-point hypothesis.

PubMed

Latash, M L

1992-01-01

In the framework of the equilibrium-point hypothesis, virtual trajectories and joint stiffness patterns have been reconstructed during two motor tasks practiced against a constant bias torque. One task required a voluntary increase in joint stiffness while preserving the original joint position. The other task involved fast elbow flexions over 36 degrees. Joint stiffness gradually subsided after the termination of fast movements. In both tasks, the external torque could slowly and unexpectedly change. The subjects were required not to change their motor commands if the torque changed, i.e. "to do the same no matter what the motor did". In both tasks, changes in joint stiffness were accompanied by unchanged virtual trajectories that were also independent of the absolute value of the bias torque. By contrast, the intercept of the joint compliant characteristic with the angle axis, r(t)-function, has demonstrated a clear dependence upon both the level of coactivation and external load. We assume that a template virtual trajectory is generated at a certain level of the motor hierarchy and is later scaled taking into account some commonly changing dynamic factors of the movement execution, for example, external load. The scaling leads to the generation of commands to the segmental structures that can be expressed, according to the equilibrium-point hypothesis, as changes in the thresholds of the tonic stretch reflex for corresponding muscles.

Joint Bayesian Component Separation and CMB Power Spectrum Estimation

NASA Technical Reports Server (NTRS)

Eriksen, H. K.; Jewell, J. B.; Dickinson, C.; Banday, A. J.; Gorski, K. M.; Lawrence, C. R.

2008-01-01

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are (1) conditional sampling of foreground spectral parameters and (2) joint sampling of all amplitude-type degrees of freedom (e.g., CMB, foreground pixel amplitudes, and global template amplitudes) given spectral parameters. Given a parametric model of the foreground signals, we estimate efficiently and accurately the exact joint foreground- CMB posterior distribution and, therefore, all marginal distributions such as the CMB power spectrum or foreground spectral index posteriors. The main limitation of the current implementation is the requirement of identical beam responses at all frequencies, which restricts the analysis to the lowest resolution of a given experiment. We outline a future generalization to multiresolution observations. To verify the method, we analyze simple models and compare the results to analytical predictions. We then analyze a realistic simulation with properties similar to the 3 yr WMAP data, downgraded to a common resolution of 3 deg FWHM. The results from the actual 3 yr WMAP temperature analysis are presented in a companion Letter.

Joint Spatio-Temporal Shared Component Model with an Application in Iran Cancer Data

PubMed

Mahaki, Behzad; Mehrabi, Yadollah; Kavousi, Amir; Schmid, Volker J

2018-06-25

Background: Among the proposals for joint disease mapping, the shared component model has become more popular. Another advance to strengthen inference of disease data is the extension of purely spatial models to include time aspect. We aim to combine the idea of multivariate shared components with spatio-temporal modelling in a joint disease mapping model and apply it for incidence rates of seven prevalent cancers in Iran which together account for approximately 50% of all cancers. Methods: In the proposed model, each component is shared by different subsets of diseases, spatial and temporal trends are considered for each component, and the relative weight of these trends for each component for each relevant disease can be estimated. Results: For esophagus and stomach cancers the Northern provinces was the area of high risk. For colorectal cancer Gilan, Semnan, Fars, Isfahan, Yazd and East-Azerbaijan were the highest risk provinces. For bladder and lung cancer, the northwest were the highest risk area. For prostate and breast cancers, Isfahan, Yazd, Fars, Tehran, Semnan, Mazandaran and Khorasane-Razavi were the highest risk part. The smoking component, shared by esophagus, stomach, bladder and lung, had more effect in Gilan, Mazandaran, Chaharmahal and Bakhtiari, Kohgilouyeh and Boyerahmad, Ardebil and Tehran provinces, in turn. For overweight and obesity component, shared by esophagus, colorectal, prostate and breast cancers the largest effect was found for Tehran, Khorasane-Razavi, Semnan, Yazd, Isfahan, Fars, Mazandaran and Gilan, in turn. For low physical activity component, shared by colorectal and breast cancers North-Khorasan, Ardebil, Golestan, Ilam, Khorasane-Razavi and South-Khorasan had the largest effects, in turn. The smoking component is significantly more important for stomach than for esophagus, bladder and lung. The overweight and obesity had significantly more effect for colorectal than of esophagus cancer. Conclusions: The presented model is a

Electroencephalographic dynamics of musical emotion perception revealed by independent spectral components.

PubMed

Lin, Yuan-Pin; Duann, Jeng-Ren; Chen, Jyh-Horng; Jung, Tzyy-Ping

2010-04-21

This study explores the electroencephalographic (EEG) correlates of emotional experience during music listening. Independent component analysis and analysis of variance were used to separate statistically independent spectral changes of the EEG in response to music-induced emotional processes. An independent brain process with equivalent dipole located in the fronto-central region exhibited distinct δ-band and θ-band power changes associated with self-reported emotional states. Specifically, the emotional valence was associated with δ-power decreases and θ-power increases in the frontal-central area, whereas the emotional arousal was accompanied by increases in both δ and θ powers. The resultant emotion-related component activations that were less interfered by the activities from other brain processes complement previous EEG studies of emotion perception to music.

Enhanced automatic artifact detection based on independent component analysis and Renyi's entropy.

PubMed

Mammone, Nadia; Morabito, Francesco Carlo

2008-09-01

Artifacts are disturbances that may occur during signal acquisition and may affect their processing. The aim of this paper is to propose a technique for automatically detecting artifacts from the electroencephalographic (EEG) recordings. In particular, a technique based on both Independent Component Analysis (ICA) to extract artifactual signals and on Renyi's entropy to automatically detect them is presented. This technique is compared to the widely known approach based on ICA and the joint use of kurtosis and Shannon's entropy. The novel processing technique is shown to detect on average 92.6% of the artifactual signals against the average 68.7% of the previous technique on the studied available database. Moreover, Renyi's entropy is shown to be able to detect muscle and very low frequency activity as well as to discriminate them from other kinds of artifacts. In order to achieve an efficient rejection of the artifacts while minimizing the information loss, future efforts will be devoted to the improvement of blind artifact separation from EEG in order to ensure a very efficient isolation of the artifactual activity from any signals deriving from other brain tasks.

Independent and joint associations of physical activity and fitness on stroke in men.

PubMed

Sieverdes, John C; Sui, Xuemei; Lee, Duck-chul; Lee, I-Min; Hooker, Steven P; Blair, Steven N

2011-05-01

Recent studies have demonstrated that physical activity (PA) and cardiorespiratory fitness (CRF) are independent predictors of stroke in men. The combined associations of these 2 factors are not well established. To investigate the independent and joint associations of PA and CRF with fatal, nonfatal, and total stroke in a group of men. The current analyses included 45 689 men aged 18 to 100 years who completed baseline sessions between 1970 and 2001. All participants had no known myocardial infarction, stroke, or cancer. Physical activity was measured by questionnaire, and CRF was assessed from a maximal treadmill exercise test. The National Death Index for fatal stroke and mail-back surveys for nonfatal stroke were used to ascertain cases. Cox regression analyses were used to estimate the risk of stroke outcomes. There were 619 cases over 800 582 person-years of observation. Significant inverse associations were observed between CRF and fatal, nonfatal, and total strokes after adjustment for age and examination year (P for trend < 0.05 for each). No associations were found between PA and any of the 3 outcomes after adjusting for other covariates and CRF. Joint associations of 9 PA fitness groups showed less risk for total stroke in the moderate and high fitness categories. These findings suggest that CRF is an independent predictor of incident stroke in asymptomatic men.

A Local Learning Rule for Independent Component Analysis

PubMed Central

Isomura, Takuya; Toyoizumi, Taro

2016-01-01

Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering. PMID:27323661

Spatial pattern separation of chemicals and frequency-independent components by terahertz spectroscopic imaging

NASA Astrophysics Data System (ADS)

Watanabe, Yuuki; Kawase, Kodo; Ikari, Tomofumi; Ito, Hiromasa; Ishikawa, Youichi; Minamide, Hiroaki

2003-10-01

We separated the component spatial patterns of frequency-dependent absorption in chemicals and frequency-independent components such as plastic, paper, and measurement noise in terahertz (THz) spectroscopic images, using known spectral curves. Our measurement system, which uses a widely tunable coherent THz-wave parametric oscillator source, can image at a specific frequency in the range 1-2 THz. The component patterns of chemicals can easily be extracted by use of the frequency-independent components. This method could be successfully used for nondestructive inspection for the detection of illegal drugs and devices of bioterrorism concealed, e.g., inside mail and packages.

Independent components of neural activity carry information on individual populations.

PubMed

Głąbska, Helena; Potworowski, Jan; Łęski, Szymon; Wójcik, Daniel K

2014-01-01

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges.

Independent Components of Neural Activity Carry Information on Individual Populations

PubMed Central

Głąbska, Helena; Potworowski, Jan; Łęski, Szymon; Wójcik, Daniel K.

2014-01-01

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges. PMID:25153730

Characterization of Strombolian events by using independent component analysis

NASA Astrophysics Data System (ADS)

Ciaramella, A.; de Lauro, E.; de Martino, S.; di Lieto, B.; Falanga, M.; Tagliaferri, R.

2004-10-01

We apply Independent Component Analysis (ICA) to seismic signals recorded at Stromboli volcano. Firstly, we show how ICA works considering synthetic signals, which are generated by dynamical systems. We prove that Strombolian signals, both tremor and explosions, in the high frequency band (>0.5 Hz), are similar in time domain. This seems to give some insights to the organ pipe model generation for the source of these events. Moreover, we are able to recognize in the tremor signals a low frequency component (<0.5 Hz), with a well defined peak corresponding to 30s.

Real-space analysis of radiation-induced specific changes with independent component analysis

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

Borek, Dominika; Bromberg, Raquel; Hattne, Johan

A method of analysis is presented that allows for the separation of specific radiation-induced changes into distinct components in real space. The method relies on independent component analysis (ICA) and can be effectively applied to electron density maps and other types of maps, provided that they can be represented as sets of numbers on a grid. Here, for glucose isomerase crystals, ICA was used in a proof-of-concept analysis to separate temperature-dependent and temperature-independent components of specific radiation-induced changes for data sets acquired from multiple crystals across multiple temperatures. ICA identified two components, with the temperature-independent component being responsible for themore » majority of specific radiation-induced changes at temperatures below 130 K. The patterns of specific temperature-independent radiation-induced changes suggest a contribution from the tunnelling of electron holes as a possible explanation. In the second case, where a group of 22 data sets was collected on a single thaumatin crystal, ICA was used in another type of analysis to separate specific radiation-induced effects happening on different exposure-level scales. Here, ICA identified two components of specific radiation-induced changes that likely result from radiation-induced chemical reactions progressing with different rates at different locations in the structure. In addition, ICA unexpectedly identified the radiation-damage state corresponding to reduced disulfide bridges rather than the zero-dose extrapolated state as the highest contrast structure. The application of ICA to the analysis of specific radiation-induced changes in real space and the data pre-processing for ICA that relies on singular value decomposition, which was used previously in data space to validate a two-component physical model of X-ray radiation-induced changes, are discussed in detail. This work lays a foundation for a better understanding of protein-specific radiation

Long-Acting Opioid Use Independently Predicts Perioperative Complication in Total Joint Arthroplasty.

PubMed

Sing, David C; Barry, Jeffrey J; Cheah, Jonathan W; Vail, Thomas P; Hansen, Erik N

2016-09-01

Opioid therapy is an increasingly used modality for treatment of musculoskeletal pain despite multiple associated risks. The purpose of this study was to evaluate how preoperative opioid use affects early outcomes after total joint arthroplasty. A total of 174 patients undergoing total joint arthroplasty were matched by age, gender, and procedure into 3 groups stratified by preoperative opioid use (nonuser, short acting [eg, Vicodin], long acting [eg, Oxycontin]). Compared to nonusers, preoperative long-acting use was associated with increased postoperative mean opioid consumption (46 mg vs 366 mg mean morphine equivalents, P < .001) and independently predicted complications within 90 days (odds ratio: 6.15, confidence interval: [1.46, 25.95], P = .013). Preoperative opioid use should be disclosed as a risk factor for complication to patients and taken into consideration by physicians before initiating opioid management. Copyright © 2016 Elsevier Inc. All rights reserved.

A first application of independent component analysis to extracting structure from stock returns.

PubMed

Back, A D; Weigend, A S

1997-08-01

This paper explores the application of a signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent large shocks (responsible for the major changes in the stock prices), and (ii) frequent smaller fluctuations (contributing little to the overall level of the stocks). We show that the overall stock price can be reconstructed surprisingly well by using a small number of thresholded weighted ICs. In contrast, when using shocks derived from principal components instead of independent components, the reconstructed price is less similar to the original one. ICA is shown to be a potentially powerful method of analyzing and understanding driving mechanisms in financial time series. The application to portfolio optimization is described in Chin and Weigend (1998).

Determination of the optimal number of components in independent components analysis.

PubMed

Kassouf, Amine; Jouan-Rimbaud Bouveresse, Delphine; Rutledge, Douglas N

2018-03-01

Independent components analysis (ICA) may be considered as one of the most established blind source separation techniques for the treatment of complex data sets in analytical chemistry. Like other similar methods, the determination of the optimal number of latent variables, in this case, independent components (ICs), is a crucial step before any modeling. Therefore, validation methods are required in order to decide about the optimal number of ICs to be used in the computation of the final model. In this paper, three new validation methods are formally presented. The first one, called Random_ICA, is a generalization of the ICA_by_blocks method. Its specificity resides in the random way of splitting the initial data matrix into two blocks, and then repeating this procedure several times, giving a broader perspective for the selection of the optimal number of ICs. The second method, called KMO_ICA_Residuals is based on the computation of the Kaiser-Meyer-Olkin (KMO) index of the transposed residual matrices obtained after progressive extraction of ICs. The third method, called ICA_corr_y, helps to select the optimal number of ICs by computing the correlations between calculated proportions and known physico-chemical information about samples, generally concentrations, or between a source signal known to be present in the mixture and the signals extracted by ICA. These three methods were tested using varied simulated and experimental data sets and compared, when necessary, to ICA_by_blocks. Results were relevant and in line with expected ones, proving the reliability of the three proposed methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of Knee Joint Contact Forces From External Measures Using Principal Component Prediction and Reconstruction.

PubMed

Saliba, Christopher M; Clouthier, Allison L; Brandon, Scott C E; Rainbow, Michael J; Deluzio, Kevin J

2018-05-29

Abnormal loading of the knee joint contributes to the pathogenesis of knee osteoarthritis. Gait retraining is a non-invasive intervention that aims to reduce knee loads by providing audible, visual, or haptic feedback of gait parameters. The computational expense of joint contact force prediction has limited real-time feedback to surrogate measures of the contact force, such as the knee adduction moment. We developed a method to predict knee joint contact forces using motion analysis and a statistical regression model that can be implemented in near real-time. Gait waveform variables were deconstructed using principal component analysis and a linear regression was used to predict the principal component scores of the contact force waveforms. Knee joint contact force waveforms were reconstructed using the predicted scores. We tested our method using a heterogenous population of asymptomatic controls and subjects with knee osteoarthritis. The reconstructed contact force waveforms had mean (SD) RMS differences of 0.17 (0.05) bodyweight compared to the contact forces predicted by a musculoskeletal model. Our method successfully predicted subject-specific shape features of contact force waveforms and is a potentially powerful tool in biofeedback and clinical gait analysis.

Independent component model for cognitive functions of multiple subjects using [15O]H2O PET images.

PubMed

Park, Hae-Jeong; Kim, Jae-Jin; Youn, Tak; Lee, Dong Soo; Lee, Myung Chul; Kwon, Jun Soo

2003-04-01

An independent component model of multiple subjects' positron emission tomography (PET) images is proposed to explore the overall functional components involved in a task and to explain subject specific variations of metabolic activities under altered experimental conditions utilizing the Independent component analysis (ICA) concept. As PET images represent time-compressed activities of several cognitive components, we derived a mathematical model to decompose functional components from cross-sectional images based on two fundamental hypotheses: (1) all subjects share basic functional components that are common to subjects and spatially independent of each other in relation to the given experimental task, and (2) all subjects share common functional components throughout tasks which are also spatially independent. The variations of hemodynamic activities according to subjects or tasks can be explained by the variations in the usage weight of the functional components. We investigated the plausibility of the model using serial cognitive experiments of simple object perception, object recognition, two-back working memory, and divided attention of a syntactic process. We found that the independent component model satisfactorily explained the functional components involved in the task and discuss here the application of ICA in multiple subjects' PET images to explore the functional association of brain activations. Copyright 2003 Wiley-Liss, Inc.

Definition of large components assembled on-orbit and robot compatible mechanical joints

NASA Technical Reports Server (NTRS)

Williamsen, J.; Thomas, F.; Finckenor, J.; Spiegel, B.

1990-01-01

One of four major areas of project Pathfinder is in-space assembly and construction. The task of in-space assembly and construction is to develop the requirements and the technology needed to build elements in space. A 120-ft diameter tetrahedral aerobrake truss is identified as the focus element. A heavily loaded mechanical joint is designed to robotically assemble the defined aerobrake element. Also, typical large components such as habitation modules, storage tanks, etc., are defined, and attachment concepts of these components to the tetrahedral truss are developed.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

NASA Astrophysics Data System (ADS)

Tsouri, Gill R.; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K.

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Artifacts and noise removal in electrocardiograms using independent component analysis.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-26

Independent component analysis (ICA) is a novel technique capable of separating independent components from electrocardiogram (ECG) complex signals. The purpose of this analysis is to evaluate the effectiveness of ICA in removing artifacts and noise from ECG recordings. ICA is applied to remove artifacts and noise in ECG segments of either an individual ECG CSE data base file or all files. The reconstructed ECGs are compared with the original ECG signal. For the four special cases discussed, the R-Peak magnitudes of the CSE data base ECG waveforms before and after applying ICA are also found. In the results, it is shown that in most of the cases, the percentage error in reconstruction is very small. The results show that there is a significant improvement in signal quality, i.e. SNR. All the ECG recording cases dealt showed an improved ECG appearance after the use of ICA. This establishes the efficacy of ICA in elimination of noise and artifacts in electrocardiograms.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

PubMed

Tsouri, Gill R; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Determination of Parachute Joint Factors using Seam and Joint Testing

NASA Technical Reports Server (NTRS)

Mollmann, Catherine

2015-01-01

This paper details the methodology for determining the joint factor for all parachute components. This method has been successfully implemented on the Capsule Parachute Assembly System (CPAS) for the NASA Orion crew module for use in determining the margin of safety for each component under peak loads. Also discussed are concepts behind the joint factor and what drives the loss of material strength at joints. The joint factor is defined as a "loss in joint strength...relative to the basic material strength" that occurs when "textiles are connected to each other or to metals." During the CPAS engineering development phase, a conservative joint factor of 0.80 was assumed for each parachute component. In order to refine this factor and eliminate excess conservatism, a seam and joint testing program was implemented as part of the structural validation. This method split each of the parachute structural joints into discrete tensile tests designed to duplicate the loading of each joint. Breaking strength data collected from destructive pull testing was then used to calculate the joint factor in the form of an efficiency. Joint efficiency is the percentage of the base material strength that remains after degradation due to sewing or interaction with other components; it is used interchangeably with joint factor in this paper. Parachute materials vary in type-mainly cord, tape, webbing, and cloth -which require different test fixtures and joint sample construction methods. This paper defines guidelines for designing and testing samples based on materials and test goals. Using the test methodology and analysis approach detailed in this paper, the minimum joint factor for each parachute component can be formulated. The joint factors can then be used to calculate the design factor and margin of safety for that component, a critical part of the design verification process.

Position of the prosthesis components in total ankle replacement and the effect on motion at the replaced joint.

PubMed

Cenni, Francesco; Leardini, Alberto; Cheli, Andrea; Catani, Fabio; Belvedere, Claudio; Romagnoli, Matteo; Giannini, Sandro

2012-03-01

In some cases of total ankle replacement, perfect alignment of the prosthetic components is not achieved. This study analyses the extent to which component positioning is critical for the final range of motion. Fourteen patients undergoing total ankle replacement were assessed preoperatively and postoperatively at seven and 13 months follow-up. X-ray pictures of the ankle were taken in static double leg stance, i.e. at neutral joint position, and in maximum plantarflexion and dorsiflexion. Measurements were obtained by a specially devised computer program based on anatomical reference points digitised on the radiograms. These allowed calculation of the position and orientation of the components in the sagittal and coronal planes, together with the joint range of motion. The mean range of motion was about 34 degrees at the first follow-up and maintained at the second. Tibial and talar components were more anterior than the mid-tibial shaft in 11 and nine patients, respectively. Mean inclination was about four degrees posterior for the tibial component and nearly one degree anterior for the talar component. A significantly larger range of motion was found in ankles both with the talar component located and inclined more anteriorly than the tibial. Correlation, though weak, was found between motion at the replaced ankle and possible residual subluxation and inclination of the components. However, a satisfactory range of motion was also achieved in those patients where recommended locations for the components could not be reached because of the size of the original joint deformity.

Predicting timing of foot strike during running, independent of striking technique, using principal component analysis of joint angles.

PubMed

Osis, Sean T; Hettinga, Blayne A; Leitch, Jessica; Ferber, Reed

2014-08-22

As 3-dimensional (3D) motion-capture for clinical gait analysis continues to evolve, new methods must be developed to improve the detection of gait cycle events based on kinematic data. Recently, the application of principal component analysis (PCA) to gait data has shown promise in detecting important biomechanical features. Therefore, the purpose of this study was to define a new foot strike detection method for a continuum of striking techniques, by applying PCA to joint angle waveforms. In accordance with Newtonian mechanics, it was hypothesized that transient features in the sagittal-plane accelerations of the lower extremity would be linked with the impulsive application of force to the foot at foot strike. Kinematic and kinetic data from treadmill running were selected for 154 subjects, from a database of gait biomechanics. Ankle, knee and hip sagittal plane angular acceleration kinematic curves were chained together to form a row input to a PCA matrix. A linear polynomial was calculated based on PCA scores, and a 10-fold cross-validation was performed to evaluate prediction accuracy against gold-standard foot strike as determined by a 10 N rise in the vertical ground reaction force. Results show 89-94% of all predicted foot strikes were within 4 frames (20 ms) of the gold standard with the largest error being 28 ms. It is concluded that this new foot strike detection is an improvement on existing methods and can be applied regardless of whether the runner exhibits a rearfoot, midfoot, or forefoot strike pattern. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying reliable independent components via split-half comparisons

PubMed Central

Groppe, David M.; Makeig, Scott; Kutas, Marta

2011-01-01

Independent component analysis (ICA) is a family of unsupervised learning algorithms that have proven useful for the analysis of the electroencephalogram (EEG) and magnetoencephalogram (MEG). ICA decomposes an EEG/MEG data set into a basis of maximally temporally independent components (ICs) that are learned from the data. As with any statistic, a concern with using ICA is the degree to which the estimated ICs are reliable. An IC may not be reliable if ICA was trained on insufficient data, if ICA training was stopped prematurely or at a local minimum (for some algorithms), or if multiple global minima were present. Consequently, evidence of ICA reliability is critical for the credibility of ICA results. In this paper, we present a new algorithm for assessing the reliability of ICs based on applying ICA separately to split-halves of a data set. This algorithm improves upon existing methods in that it considers both IC scalp topographies and activations, uses a probabilistically interpretable threshold for accepting ICs as reliable, and requires applying ICA only three times per data set. As evidence of the method’s validity, we show that the method can perform comparably to more time intensive bootstrap resampling and depends in a reasonable manner on the amount of training data. Finally, using the method we illustrate the importance of checking the reliability of ICs by demonstrating that IC reliability is dramatically increased by removing the mean EEG at each channel for each epoch of data rather than the mean EEG in a prestimulus baseline. PMID:19162199

A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

PubMed

Spadone, Sara; de Pasquale, Francesco; Mantini, Dante; Della Penna, Stefania

2012-09-01

Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are

Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis

NASA Astrophysics Data System (ADS)

Pu, Huangsheng; Zhang, Guanglei; He, Wei; Liu, Fei; Guang, Huizhi; Zhang, Yue; Bai, Jing; Luo, Jianwen

2014-09-01

It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.

Evaluating the contribution of a neural component of ankle joint resistive torque in patients with stroke using a manual device.

PubMed

Kobayashi, Toshiki; Leung, Aaron K L; Akazawa, Yasushi; Hutchins, Stephen W

2011-01-01

To investigate the methodology using a manual ankle joint resistive torque measurement device to evaluate the contribution of the neural component of ankle joint resistive torque in patients with stroke. Within-subject comparison to compare the ankle joint resistive torque between fast and slow stretching conditions. Ten patients with stroke participated in this study. The incremental ratio of ankle joint resistive torque at the ankle angular position of 5degrees dorsiflexion under the fast stretching condition in comparison to the slow one was calculated in each patient. A significant increase (p<0.01) in the ankle joint resistive torque was demonstrated under the fast stretching condition in comparison to the slow one in all patients and the mean ankle joint resistive torque was 4.6 (SD=1.7) Nm under the slow stretching condition, while it was 8.4 (SD=4.1) Nm under the fast stretching condition at the ankle angular position of 5 degrees dorsiflexion. The incremental ratio ranged from 9.4-139.3% among the patients. The results of this study demonstrated the potential advantage of the device to evaluate the contribution of the neural component of ankle joint resistive torque.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

NOTE: Entropy-based automated classification of independent components separated from fMCG

NASA Astrophysics Data System (ADS)

Comani, S.; Srinivasan, V.; Alleva, G.; Romani, G. L.

2007-03-01

Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p <0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system.

Ultrasonic detection technology based on joint robot on composite component with complex surface

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

Hao, Juan; Xu, Chunguang; Zhang, Lan

Some components have complex surface, such as the airplane wing and the shell of a pressure vessel etc. The quality of these components determines the reliability and safety of related equipment. Ultrasonic nondestructive detection is one of the main methods used for testing material defects at present. In order to improve the testing precision, the acoustic axis of the ultrasonic transducer should be consistent with the normal direction of the measured points. When we use joint robots, automatic ultrasonic scan along the component surface normal direction can be realized by motion trajectory planning and coordinate transformation etc. In order tomore » express the defects accurately and truly, the robot position and the signal of the ultrasonic transducer should be synchronized.« less

Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials

PubMed Central

Smolinski, Tomasz G; Buchanan, Roger; Boratyn, Grzegorz M; Milanova, Mariofanna; Prinz, Astrid A

2006-01-01

Background Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to "predict" the condition a given signal was registered under, solely based on the components. However, the ICA's assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with "classification-awareness." Results The preliminary results described here are very promising and further investigation of other MOEAs and/or RS-based classification accuracy measures should be pursued. Even a quick visual analysis of those results can provide an interesting insight into the problem of neural activity analysis. Conclusion We present a methodology of classificatory decomposition of signals. One of the main advantages of our approach is the fact that rather than solely relying on often unrealistic assumptions about statistical independence of sources, components are generated in the light of a underlying classification problem itself. PMID:17118151

Dual-energy x-ray image decomposition by independent component analysis

NASA Astrophysics Data System (ADS)

Jiang, Yifeng; Jiang, Dazong; Zhang, Feng; Zhang, Dengfu; Lin, Gang

2001-09-01

The spatial distributions of bone and soft tissue in human body are separated by independent component analysis (ICA) of dual-energy x-ray images. It is because of the dual energy imaging modelí-s conformity to the ICA model that we can apply this method: (1) the absorption in body is mainly caused by photoelectric absorption and Compton scattering; (2) they take place simultaneously but are mutually independent; and (3) for monochromatic x-ray sources the total attenuation is achieved by linear combination of these two absorption. Compared with the conventional method, the proposed one needs no priori information about the accurate x-ray energy magnitude for imaging, while the results of the separation agree well with the conventional one.

Towards Solving the Mixing Problem in the Decomposition of Geophysical Time Series by Independent Component Analysis

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)

2000-01-01

The use of the Principal Component Analysis technique for the analysis of geophysical time series has been questioned in particular for its tendency to extract components that mix several physical phenomena even when the signal is just their linear sum. We demonstrate with a data simulation experiment that the Independent Component Analysis, a recently developed technique, is able to solve this problem. This new technique requires the statistical independence of components, a stronger constraint, that uses higher-order statistics, instead of the classical decorrelation a weaker constraint, that uses only second-order statistics. Furthermore, ICA does not require additional a priori information such as the localization constraint used in Rotational Techniques.

Buying and Selling Prices of Investments: Configural Weight Model of Interactions Predicts Violations of Joint Independence.

PubMed

Birnbaum; Zimmermann

1998-05-01

Judges evaluated buying and selling prices of hypothetical investments, based on the previous price of each investment and estimates of the investment's future value given by advisors of varied expertise. Effect of a source's estimate varied in proportion to the source's expertise, and it varied inversely with the number and expertise of other sources. There was also a configural effect in which the effect of a source's estimate was affected by the rank order of that source's estimate, in relation to other estimates of the same investment. These interactions were fit with a configural weight averaging model in which buyers and sellers place different weights on estimates of different ranks. This model implies that one can design a new experiment in which there will be different violations of joint independence in different viewpoints. Experiment 2 confirmed patterns of violations of joint independence predicted from the model fit in Experiment 1. Experiment 2 also showed that preference reversals between viewpoints can be predicted by the model of Experiment 1. Configural weighting provides a better account of buying and selling prices than either of two models of loss aversion or the theory of anchoring and insufficient adjustment. Copyright 1998 Academic Press.

Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.

Strength Variation of Parachute Joints

NASA Technical Reports Server (NTRS)

Mollmann, Catherine

2017-01-01

A parachute joint is defined as a location where a component is sewn or connected to another component. During the design and developmental phase of a parachute system, the joints for each structural component are isolated and tested through a process called seam and joint testing. The objective of seam and joint testing is to determine the degradation on a single component due to interaction with other components; this data is then used when calculating the margin of safety for that component. During the engineering developmental phase of CPAS (Capsule Parachute Assembly System), the parachute system for the NASA Orion Crew Module, testing was completed for every joint of the six subsystems: the four parachutes (main, drogue, pilot, and FBCP [forward bay cover parachute]), the retention release bridle, and the retention panels. The number of joint tests for these subsystems totaled 92, which provides a plethora of data and results for further analysis. In this paper, the data and results of these seam and joint tests are examined to determine the effects, if any, of different operators and sewing machines on the strength of parachute joints. Other variables are also studied to determine their effect on joint strength, such as joint complexity, joint strength magnitude, material type, and material construction. Findings reveal that an optimally-run seam and joint test program could result in an increased understanding of the structure of the parachute; this should lead to a parachute built with optimal components, potentially saving system weight and volume.

Preserving transfer independence among individuals with spinal cord injury.

PubMed

Nyland, J; Quigley, P; Huang, C; Lloyd, J; Harrow, J; Nelson, A

2000-11-01

Literature review. Upper extremity (UE) joint degeneration, particularly at the shoulder, detrimentally influences functional independence, quality of life, cardiovascular disease risk, and life expectancy of individuals following spinal cord injury (SCI). This review (1) describes UE use for transfers among individuals with SCI; (2) describes contributing factors associated with UE joint degeneration and loss of transfer independence; (3) summarizes and identifies gaps in existing research; and (4) provides suggestions for future research. Investigations of wheelchair transfer related UE joint and function preservation among individuals with SCI should consider factors including age and length of time from SCI onset, interface between subject-wheelchair, pain, shoulder joint range of motion (ROM) and muscle strength deficiencies or imbalances, exercise capacity and tolerance for the physical strain of activities of daily living (ADL), body mass and composition, previous UE injury or disease history, and transfer techniques. Existing studies of transfers among individuals with SCI have relied on small groups of either asymptomatic or non-impaired subjects, with minimal integration of kinematic, kinetic and electromyographic data. Descriptions of UE joint ROM, forces, and moments produced during transfers are lacking. Biomechanical measurement and computer modeling have provided increasingly accurate tools for acquiring the data needed to guide intervention planning to prevent UE joint degeneration and preserve function among individuals with SCI. The identification of stressful sub-components during transfers will enable intervening clinicians and engineers who design and modify assistive and adaptive devices to better serve individuals with SCI.

ULNAR NERVE COMPONENT TO INNERVATION OF THUMB CARPOMETACARPAL JOINT

PubMed Central

Miki, Roberto Augusto; Kam, Check C; Gennis, Elisabeth R; Barkin, Jodie A; Riel, Ryan U; Robinson, Philip G; Owens, Patrick W

2011-01-01

Purpose Thumb carpometacarpal (CMC) joint arthritis is one of the most common problems addressed by hand surgeons. The gold standard of treatment for thumb CMC joint arthritis is trapeziectomy, ligament reconstruction and tendon interposition. Denervation of the thumb CMC joint is not currently used to treat arthritis in this joint due to the failure of the procedure to yield significant symptomatic relief. The failure of denervation is puzzling, given that past anatomic studies show the radial nerve is the major innervation of the thumb CMC joint with the lateral antebrachial nerve and the median nerve also innervating this joint. Although no anatomic study has ever shown that the ulnar nerve innervates the CMC joint, due to both the failure of denervation and the success of arthroscopic thermal ablation, we suspect that previous anatomic studies may have overlooked innervation of the thumb CMC joint via the ulnar nerve. Methods We dissected 19 formalin-preserved cadaveric hand-to-mid-forearm specimens. The radial, median and ulnar nerves were identified in the proximal forearm and then followed distally. Any branch heading toward the radial side of the hand were followed to see if they innervated the thumb CMC joint. Results Eleven specimens (58%) had superficial radial nerve innervation to the thumb CMC joint. Nine specimens (47%) had median nerve innervation from the motor branch. Nine specimens (47%) had ulnar nerve innervation from the motor branch. Conclusions We believe this is the first study to demonstrate that the ulnar nerve innervates the thumb CMC joint This finding may explain the poor results seen in earlier attempts at denervation of the thumb CMC, but the more favorable results with techniques such as arthroscopy with thermal ablation. PMID:22096446

Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density.

PubMed

Lęski, Szymon; Kublik, Ewa; Swiejkowski, Daniel A; Wróbel, Andrzej; Wójcik, Daniel K

2010-12-01

Local field potentials have good temporal resolution but are blurred due to the slow spatial decay of the electric field. For simultaneous recordings on regular grids one can reconstruct efficiently the current sources (CSD) using the inverse Current Source Density method (iCSD). It is possible to decompose the resultant spatiotemporal information about the current dynamics into functional components using Independent Component Analysis (ICA). We show on test data modeling recordings of evoked potentials on a grid of 4 × 5 × 7 points that meaningful results are obtained with spatial ICA decomposition of reconstructed CSD. The components obtained through decomposition of CSD are better defined and allow easier physiological interpretation than the results of similar analysis of corresponding evoked potentials in the thalamus. We show that spatiotemporal ICA decompositions can perform better for certain types of sources but it does not seem to be the case for the experimental data studied. Having found the appropriate approach to decomposing neural dynamics into functional components we use the technique to study the somatosensory evoked potentials recorded on a grid spanning a large part of the forebrain. We discuss two example components associated with the first waves of activation of the somatosensory thalamus. We show that the proposed method brings up new, more detailed information on the time and spatial location of specific activity conveyed through various parts of the somatosensory thalamus in the rat.

Damage prognosis of adhesively-bonded joints in laminated composite structural components of unmanned aerial vehicles

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

Farrar, Charles R; Gobbato, Maurizio; Conte, Joel

2009-01-01

The extensive use of lightweight advanced composite materials in unmanned aerial vehicles (UAVs) drastically increases the sensitivity to both fatigue- and impact-induced damage of their critical structural components (e.g., wings and tail stabilizers) during service life. The spar-to-skin adhesive joints are considered one of the most fatigue sensitive subcomponents of a lightweight UAV composite wing with damage progressively evolving from the wing root. This paper presents a comprehensive probabilistic methodology for predicting the remaining service life of adhesively-bonded joints in laminated composite structural components of UAVs. Non-destructive evaluation techniques and Bayesian inference are used to (i) assess the current statemore » of damage of the system and, (ii) update the probability distribution of the damage extent at various locations. A probabilistic model for future loads and a mechanics-based damage model are then used to stochastically propagate damage through the joint. Combined local (e.g., exceedance of a critical damage size) and global (e.g.. flutter instability) failure criteria are finally used to compute the probability of component failure at future times. The applicability and the partial validation of the proposed methodology are then briefly discussed by analyzing the debonding propagation, along a pre-defined adhesive interface, in a simply supported laminated composite beam with solid rectangular cross section, subjected to a concentrated load applied at mid-span. A specially developed Eliler-Bernoulli beam finite element with interlaminar slip along the damageable interface is used in combination with a cohesive zone model to study the fatigue-induced degradation in the adhesive material. The preliminary numerical results presented are promising for the future validation of the methodology.« less

Functionally independent components of the late positive event-related potential during visual spatial attention.

PubMed

Makeig, S; Westerfield, M; Jung, T P; Covington, J; Townsend, J; Sejnowski, T J; Courchesne, E

1999-04-01

Human event-related potentials (ERPs) were recorded from 10 subjects presented with visual target and nontarget stimuli at five screen locations and responding to targets presented at one of the locations. The late positive response complexes of 25-75 ERP average waveforms from the two task conditions were simultaneously analyzed with Independent Component Analysis, a new computational method for blindly separating linearly mixed signals. Three spatially fixed, temporally independent, behaviorally relevant, and physiologically plausible components were identified without reference to peaks in single-channel waveforms. A novel frontoparietal component (P3f) began at approximately 140 msec and peaked, in faster responders, at the onset of the motor command. The scalp distribution of P3f appeared consistent with brain regions activated during spatial orienting in functional imaging experiments. A longer-latency large component (P3b), positive over parietal cortex, was followed by a postmotor potential (Pmp) component that peaked 200 msec after the button press and reversed polarity near the central sulcus. A fourth component associated with a left frontocentral nontarget positivity (Pnt) was evoked primarily by target-like distractors presented in the attended location. When no distractors were presented, responses of five faster-responding subjects contained largest P3f and smallest Pmp components; when distractors were included, a Pmp component appeared only in responses of the five slower-responding subjects. Direct relationships between component amplitudes, latencies, and behavioral responses, plus similarities between component scalp distributions and regional activations reported in functional brain imaging experiments suggest that P3f, Pmp, and Pnt measure the time course and strength of functionally distinct brain processes.

A novel approach to analyzing fMRI and SNP data via parallel independent component analysis

NASA Astrophysics Data System (ADS)

Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas

2007-03-01

There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.

Equivalent water height extracted from GRACE gravity field model with robust independent component analysis

NASA Astrophysics Data System (ADS)

Guo, Jinyun; Mu, Dapeng; Liu, Xin; Yan, Haoming; Dai, Honglei

2014-08-01

The Level-2 monthly GRACE gravity field models issued by Center for Space Research (CSR), GeoForschungs Zentrum (GFZ), and Jet Propulsion Laboratory (JPL) are treated as observations used to extract the equivalent water height (EWH) with the robust independent component analysis (RICA). The smoothing radii of 300, 400, and 500 km are tested, respectively, in the Gaussian smoothing kernel function to reduce the observation Gaussianity. Three independent components are obtained by RICA in the spatial domain; the first component matches the geophysical signal, and the other two match the north-south strip and the other noises. The first mode is used to estimate EWHs of CSR, JPL, and GFZ, and compared with the classical empirical decorrelation method (EDM). The EWH STDs for 12 months in 2010 extracted by RICA and EDM show the obvious fluctuation. The results indicate that the sharp EWH changes in some areas have an important global effect, like in Amazon, Mekong, and Zambezi basins.

Independent and Joint Effect of Brachial-Ankle Pulse Wave Velocity and Blood Pressure Control on Incident Stroke in Hypertensive Adults.

PubMed

Song, Yun; Xu, Benjamin; Xu, Richard; Tung, Renee; Frank, Eric; Tromble, Wayne; Fu, Tong; Zhang, Weiyi; Yu, Tao; Zhang, Chunyan; Fan, Fangfang; Zhang, Yan; Li, Jianping; Bao, Huihui; Cheng, Xiaoshu; Qin, Xianhui; Tang, Genfu; Chen, Yundai; Yang, Tianlun; Sun, Ningling; Li, Xiaoying; Zhao, Lianyou; Hou, Fan Fan; Ge, Junbo; Dong, Qiang; Wang, Binyan; Xu, Xiping; Huo, Yong

2016-07-01

Pulse wave velocity (PWV) has been shown to influence the effects of antihypertensive drugs in the prevention of cardiovascular diseases. Data are limited on whether PWV is an independent predictor of stroke above and beyond hypertension control. This longitudinal analysis examined the independent and joint effect of brachial-ankle PWV (baPWV) with hypertension control on the risk of first stroke. This report included 3310 hypertensive adults, a subset of the China Stroke Primary Prevention Trial (CSPPT) with baseline measurements for baPWV. During a median follow-up of 4.5 years, 111 participants developed first stroke. The risk of stroke was higher among participants with baPWV in the highest quartile than among those in the lower quartiles (6.3% versus 2.4%; hazard ratio, 1.66; 95% confidence interval, 1.06-2.60). Similarly, the participants with inadequate hypertension control had a higher risk of stroke than those with adequate control (5.1% versus 1.8%; hazard ratio, 2.32; 95% confidence interval, 1.49-3.61). When baPWV and hypertension control were examined jointly, participants in the highest baPWV quartile and with inadequate hypertension control had the highest risk of stroke compared with their counterparts (7.5% versus 1.3%; hazard ratio, 3.57; 95% confidence interval, 1.88-6.77). There was a significant and independent effect of high baPWV on stroke as shown among participants with adequate hypertension control (4.2% versus 1.3%; hazard ratio, 2.29, 95% confidence interval, 1.09-4.81). In summary, among hypertensive patients, baPWV and hypertension control were found to independently and jointly affect the risk of first stroke. Participants with high baPWV and inadequate hypertension control had the highest risk of stroke compared with other groups. © 2016 American Heart Association, Inc.

Independent component analysis algorithm FPGA design to perform real-time blind source separation

NASA Astrophysics Data System (ADS)

Meyer-Baese, Uwe; Odom, Crispin; Botella, Guillermo; Meyer-Baese, Anke

2015-05-01

The conditions that arise in the Cocktail Party Problem prevail across many fields creating a need for of Blind Source Separation. The need for BSS has become prevalent in several fields of work. These fields include array processing, communications, medical signal processing, and speech processing, wireless communication, audio, acoustics and biomedical engineering. The concept of the cocktail party problem and BSS led to the development of Independent Component Analysis (ICA) algorithms. ICA proves useful for applications needing real time signal processing. The goal of this research was to perform an extensive study on ability and efficiency of Independent Component Analysis algorithms to perform blind source separation on mixed signals in software and implementation in hardware with a Field Programmable Gate Array (FPGA). The Algebraic ICA (A-ICA), Fast ICA, and Equivariant Adaptive Separation via Independence (EASI) ICA were examined and compared. The best algorithm required the least complexity and fewest resources while effectively separating mixed sources. The best algorithm was the EASI algorithm. The EASI ICA was implemented on hardware with Field Programmable Gate Arrays (FPGA) to perform and analyze its performance in real time.

Applications of independent component analysis in SAR images

NASA Astrophysics Data System (ADS)

Huang, Shiqi; Cai, Xinhua; Hui, Weihua; Xu, Ping

2009-07-01

The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of SAR image and increase the detection rate for the faint small targets.

Mutual coordination strengthens the sense of joint agency in cooperative joint action.

PubMed

Bolt, Nicole K; Poncelet, Evan M; Schultz, Benjamin G; Loehr, Janeen D

2016-11-01

Philosophers have proposed that when people coordinate their actions with others they may experience a sense of joint agency, or shared control over actions and their effects. However, little empirical work has investigated the sense of joint agency. In the current study, pairs coordinated their actions to produce tone sequences and then rated their sense of joint agency on a scale ranging from shared to independent control. People felt more shared than independent control overall, confirming that people experience joint agency during joint action. Furthermore, people felt stronger joint agency when they (a) produced sequences that required mutual coordination compared to sequences in which only one partner had to coordinate with the other, (b) held the role of follower compared to leader, and (c) were better coordinated with their partner. Thus, the strength of joint agency is influenced by the degree to which people mutually coordinate with each other's actions. Copyright © 2016 Elsevier Inc. All rights reserved.

Do the radial head prosthesis components fit with the anatomical structures of the proximal radioulnar joint?

PubMed

Wegmann, Kilian; Hain, Moritz K; Ries, Christian; Neiss, Wolfram F; Müller, Lars P; Burkhart, Klaus J

2015-09-01

The fitting accuracy of radial head components has been investigated in the capitulo-radial joint, and reduced contact after prosthetic replacement of the radial head has been observed. The kinematics of the proximal radioulnar joint (PRUJ) are affected by radial head arthroplasty as well, but have not yet been investigated in this regard. The elbow joints of 60 upper extremities of formalin-fixed body donors were disarticulated to obtain a good view of the PRUJ. Each specimen was mounted on the examining table and radial head position in the native PRUJ was assessed in neutral position, full pronation, and full supination. Measurements were repeated after implantation of mono- and bi-polar prostheses. Analysis of the distribution of the joint contacts in the compartments showed significant differences after radial head replacement. In comparison to the native joint, after bipolar and monopolar radial head replacement, the physiological shift of the proximal radius was altered. The physiological shift of the joint contact of the radial head from anterior to posterior during forearm rotation that was found in the native joint in our cadaver model was not observed after prosthetic replacement. With higher conformity and physiological kinematic of radial head prostheses, possibly lower shear forces and lower contact pressures would be generated. The tested radial head prostheses do not replicate the physiological kinematics of the radial head. Further development in the prosthesis design has to be made. The meticulous reconstruction of the annular ligament seems to be of importance to increase joint contact.

The impact of maternal obesity and race/ethnicity on perinatal outcomes: independent and joint effects

PubMed Central

Snowden, Jonathan M; Mission, John F; Marshall, Nicole E; Quigley, Brian; Main, Elliott; Gilbert, William M; Chung, Judith H; Caughey, Aaron B

2016-01-01

Objective We characterized independent and joint impacts of maternal race/ethnicity and obesity on adverse birth outcomes, including preeclampsia, low birthweight (LBW), and macrosomia. Methods Retrospective cohort study of all 2007 California births using vital records and claims data. Maternal race/ethnicity and maternal BMI were the key exposures; we analyzed their independent and joint impact on outcomes using regression models. Results Racial/ethnic minority women of normal weight generally had higher risk as compared to white women of normal weight (e.g., African-American women, preeclampsia aOR, 1.60, 95% CI: 1.48 – 1.74, versus white women). However, elevated BMI did not usually confer additional risk (e.g., preeclampsia aOR comparing African-American women with morbid obesity to white women with morbid obesity; 1.17, 95% CI: 0.89 – 1.54). Obesity was a risk factor for LBW only among white women (morbid obesity aOR, 95% CI: 1.24, 1.04 – 1.49, versus white women of normal weight), and not among racial/ethnic minority women (e.g., African-American women, 0.95, 0.83 – 1.08). Conclusions These findings add nuance to our understanding of the interplay between maternal race/ethnicity, BMI, and perinatal outcomes. While the BMI/adverse outcome gradient appears weaker in racial/ethnic minority women, this reflects the overall risk increase in racial/ethnic minority women of all body sizes. PMID:27222008

The Impact of maternal obesity and race/ethnicity on perinatal outcomes: Independent and joint effects.

PubMed

Snowden, Jonathan M; Mission, John F; Marshall, Nicole E; Quigley, Brian; Main, Elliott; Gilbert, William M; Chung, Judith H; Caughey, Aaron B

2016-07-01

Independent and joint impacts of maternal race/ethnicity and obesity on adverse birth outcomes, including pre-eclampsia, low birth weight, and macrosomia, were characterized. Retrospective cohort study of all 2007 California births was conducted using vital records and claims data. Maternal race/ethnicity and maternal body mass index (BMI) were the key exposures; their independent and joint impact on outcomes using regression models was analyzed. Racial/ethnic minority women of normal weight generally had higher risk as compared with white women of normal weight (e.g., African-American women, pre-eclampsia adjusted odds ratio [aOR] 1.60, 95% confidence interval [CI]: 1.48-1.74 vs. white women). However, elevated BMI did not usually confer additional risk (e.g., pre-eclampsia aOR comparing African-American women with excess weight with white women with excess weight, 1.17, 95% CI: 0.89-1.54). Obesity was a risk factor for low birth weight only among white women (excess weight aOR, 1.24, 95% CI: 1.04-1.49 vs. white women of normal weight) and not among racial/ethnic minority women (e.g., African-American women, 0.95, 95% CI: 0.83-1.08). These findings add nuance to our understanding of the interplay between maternal race/ethnicity, BMI, and perinatal outcomes. While the BMI/adverse outcome gradient appears weaker in racial/ethnic minority women, this reflects the overall risk increase in racial/ethnic minority women of all body sizes. © 2016 The Obesity Society.

Analysis of independent components of cognitive event related potentials in a group of ADHD adults.

PubMed

Markovska-Simoska, Silvana; Pop-Jordanova, Nada; Pop-Jordanov, Jordan

In the last decade, many studies have tried to define the neural correlates of attention deficit hyperactivity disorder (ADHD). The main aim of this study is the comparison of the ERPs independent components in the four QEEG subtypes in a group of ADHD adults as a basis for defining the corresponding endophenotypes among ADHD population. Sixty-seven adults diagnosed as ADHD according to the DSM-IV criteria and 50 age-matched control subjects participated in the study. The brain activity of the subjects was recorded by 19 channel quantitative electroencephalography (QEEG) system in two neuropsychological tasks (visual and emotional continuous performance tests). The ICA method was applied for separation of the independent ERPs components. The components were associated with distinct psychological operations, such as engagement operations (P3bP component), comparison (vcomTL and vcom TR), motor inhibition (P3supF) and monitoring (P4monCC) operations. The ERPs results point out that there is disturbance in executive functioning in investigated ADHD group obtained by the significantly lower amplitude and longer latency for the engagement (P3bP), motor inhibition (P3supF) and monitoring (P4monCC) components. Particularly, the QEEG subtype IV was with the most significant ERPs differences comparing to the other subtypes. In particular, the most prominent difference in the ERPs independent components for the QEEG subtype IV in comparison to other three subtypes, rise many questions and becomes the subject for future research. This study aims to advance and facilitate the use of neurophysiological procedures (QEEG and ERPs) in clinical practice as objective measures of ADHD for better assessment, subtyping and treatment of ADHD.

Independent component analysis for onset detection in piano trills

NASA Astrophysics Data System (ADS)

Brown, Judith C.; Todd, Jeremy G.; Smaragdis, Paris

2002-05-01

The detection of onsets in piano music is difficult due to the presence of many notes simultaneously and their long decay times from pedaling. This is even more difficult for trills where the rapid note changes make it difficult to observe a decrease in amplitude for individual notes in either the temporal wave form or the time dependent Fourier components. Occasionally one note of the trill has a much lower amplitude than the other making an unambiguous determination of its onset virtually impossible. We have analyzed a number of trills from CD's of performances by Horowitz, Ashkenazy, and Goode, choosing the same trill and different performances where possible. The Fourier transform was calculated as a function of time, and the magnitude coefficients served as input for a calculation using the method of independent component analysis. In most cases this gave a more definitive determination of the onset times, as can be demonstrated graphically. For comparison identical calculations have been carried out on recordings of midi generated performances on a Yamaha Disclavier piano.

Independent Component Analysis applied to Ground-based observations

NASA Astrophysics Data System (ADS)

Martins-Filho, Walter; Griffith, Caitlin; Pearson, Kyle; Waldmann, Ingo; Alvarez-Candal, Alvaro; Zellem, Robert Thomas

2018-01-01

Transit measurements of Jovian-sized exoplanetary atmospheres allow one to study the composition of exoplanets, largely independent of the planet’s temperature profile. However, measurements of hot-Jupiter transits must archive a level of accuracy in the flux to determine the spectral modulation of the exoplanetary atmosphere. To accomplish this level of precision, we need to extract systematic errors, and, for ground-based measurements, the effects of Earth’s atmosphere, from signal due to the exoplanet, which is several orders of magnitude smaller. The effects of the terrestrial atmosphere and some of the time-dependent systematic errors of ground-based transit measurements are treated mainly by dividing the host star by a reference star at each wavelength and time step of the transit. Recently, Independent Component Analysis (ICA) have been used to remove systematics effects from the raw data of space-based observations (Waldmann, 2014, 2012; Morello et al., 2016, 2015). ICA is a statistical method born from the ideas of the blind-source separations studies, which can be used to de-trend several independent source signals of a data set (Hyvarinen and Oja, 2000). This technique requires no additional prior knowledge of the data set. In addition, this technique has the advantage of requiring no reference star. Here we apply the ICA to ground-based photometry of the exoplanet XO-2b recorded by the 61” Kuiper Telescope and compare the results of the ICA to those of a previous analysis from Zellem et al. (2015), which does not use ICA. We also simulate the effects of various conditions (concerning the systematic errors, noise and the stability of object on the detector) to determine the conditions under which an ICA can be used with high precision to extract the light curve of exoplanetary photometry measurements

Independent Component Analysis applied to Ground-based observations

NASA Astrophysics Data System (ADS)

Martins-Filho, Walter; Griffith, Caitlin Ann; Pearson, Kyle; Waldmann, Ingo; Alvarez-Candal, Alvaro; Zellem, Robert

2017-10-01

Transit measurements of Jovian-sized exoplanetary atmospheres allow one to study the composition of exoplanets, largely independent of the planet’s temperature profile. However, measurements of hot-Jupiter transits must archive a level of accuracy in the flux to determine the spectral modulations of the exoplanetary atmosphere. To accomplish this level of precision, we need to extract systematic errors, and, for ground-based measurements, the effects of Earth’s atmosphere, from signal due to the exoplanet, which is several orders of magnitudes smaller.The effects of the terrestrial atmosphere and some of the time dependent systematic errors of ground-based transit measurements are treated mainly by dividing the host star by a reference star at each wavelength and time step of the transit. Recently, Independent Component Analyses (ICA) have been used to remove systematics effects from the raw data of space-based observations (Waldmann, 2014, 2012; Morello et al., 2016, 2015). ICA is a statistical method born from the ideas of the blind-source separations studies, which can be used to de-trend several independent source signals of a data set (Hyvarinen and Oja, 2000). This technique requires no additional prior knowledge of the data set. In addition this technique has the advantage of requiring no reference star.Here we apply the ICA to ground-based photometry of the exoplanet XO-2b recorded by the 61” Kuiper Telescope and compare the results of the ICA to those of a previous analysis from Zellem et al. (2015), which does not use ICA. We also simulate the effects of various conditions (concerning the systematic errors, noise and the stability of object on the detector) to determine the conditions under which an ICA can be used with high precision to extract the light curve of exoplanetary photometry measurements.

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

NASA Astrophysics Data System (ADS)

E, Jianwei; Bao, Yanling; Ye, Jimin

2017-10-01

As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

21 CFR 888.3320 - Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis. 888.3320 Section 888.3320 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES ORTHOPEDIC DEVICES Prosthetic...

21 CFR 888.3320 - Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis. 888.3320 Section 888.3320 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES ORTHOPEDIC DEVICES Prosthetic...

21 CFR 888.3320 - Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Hip joint metal/metal semi-constrained, with a cemented acetabular component, prosthesis. 888.3320 Section 888.3320 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES ORTHOPEDIC DEVICES Prosthetic...

Comparing Independent Component Analysis with Principle Component Analysis in Detecting Alterations of Porphyry Copper Deposit (case Study: Ardestan Area, Central Iran)

NASA Astrophysics Data System (ADS)

Mahmoudishadi, S.; Malian, A.; Hosseinali, F.

2017-09-01

The image processing techniques in transform domain are employed as analysis tools for enhancing the detection of mineral deposits. The process of decomposing the image into important components increases the probability of mineral extraction. In this study, the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) has been evaluated for the visible and near-infrared (VNIR) and Shortwave infrared (SWIR) subsystems of ASTER data. Ardestan is located in part of Central Iranian Volcanic Belt that hosts many well-known porphyry copper deposits. This research investigated the propylitic and argillic alteration zones and outer mineralogy zone in part of Ardestan region. The two mentioned approaches were applied to discriminate alteration zones from igneous bedrock using the major absorption of indicator minerals from alteration and mineralogy zones in spectral rang of ASTER bands. Specialized PC components (PC2, PC3 and PC6) were used to identify pyrite and argillic and propylitic zones that distinguish from igneous bedrock in RGB color composite image. Due to the eigenvalues, the components 2, 3 and 6 account for 4.26% ,0.9% and 0.09% of the total variance of the data for Ardestan scene, respectively. For the purpose of discriminating the alteration and mineralogy zones of porphyry copper deposit from bedrocks, those mentioned percentages of data in ICA independent components of IC2, IC3 and IC6 are more accurately separated than noisy bands of PCA. The results of ICA method conform to location of lithological units of Ardestan region, as well.

Appliance of Independent Component Analysis to System Intrusion Analysis

NASA Astrophysics Data System (ADS)

Ishii, Yoshikazu; Takagi, Tarou; Nakai, Kouji

In order to analyze the output of the intrusion detection system and the firewall, we evaluated the applicability of ICA(independent component analysis). We developed a simulator for evaluation of intrusion analysis method. The simulator consists of the network model of an information system, the service model and the vulnerability model of each server, and the action model performed on client and intruder. We applied the ICA for analyzing the audit trail of simulated information system. We report the evaluation result of the ICA on intrusion analysis. In the simulated case, ICA separated two attacks correctly, and related an attack and the abnormalities of the normal application produced under the influence of the attach.

Robust artifactual independent component classification for BCI practitioners.

PubMed

Winkler, Irene; Brandl, Stephanie; Horn, Franziska; Waldburger, Eric; Allefeld, Carsten; Tangermann, Michael

2014-06-01

EEG artifacts of non-neural origin can be separated from neural signals by independent component analysis (ICA). It is unclear (1) how robustly recently proposed artifact classifiers transfer to novel users, novel paradigms or changed electrode setups, and (2) how artifact cleaning by a machine learning classifier impacts the performance of brain-computer interfaces (BCIs). Addressing (1), the robustness of different strategies with respect to the transfer between paradigms and electrode setups of a recently proposed classifier is investigated on offline data from 35 users and 3 EEG paradigms, which contain 6303 expert-labeled components from two ICA and preprocessing variants. Addressing (2), the effect of artifact removal on single-trial BCI classification is estimated on BCI trials from 101 users and 3 paradigms. We show that (1) the proposed artifact classifier generalizes to completely different EEG paradigms. To obtain similar results under massively reduced electrode setups, a proposed novel strategy improves artifact classification. Addressing (2), ICA artifact cleaning has little influence on average BCI performance when analyzed by state-of-the-art BCI methods. When slow motor-related features are exploited, performance varies strongly between individuals, as artifacts may obstruct relevant neural activity or are inadvertently used for BCI control. Robustness of the proposed strategies can be reproduced by EEG practitioners as the method is made available as an EEGLAB plug-in.

Technical Note: Independent component analysis for quality assurance in functional MRI.

PubMed

Astrakas, Loukas G; Kallistis, Nikolaos S; Kalef-Ezra, John A

2016-02-01

Independent component analysis (ICA) is an established method of analyzing human functional MRI (fMRI) data. Here, an ICA-based fMRI quality control (QC) tool was developed and used. ICA-based fMRI QC tool to be used with a commercial phantom was developed. In an attempt to assess the performance of the tool relative to preexisting alternative tools, it was used seven weeks before and eight weeks after repair of a faulty gradient amplifier of a non-state-of-the-art MRI unit. More specifically, its performance was compared with the AAPM 100 acceptance testing and quality assurance protocol and two fMRI QC protocols, proposed by Freidman et al. ["Report on a multicenter fMRI quality assurance protocol," J. Magn. Reson. Imaging 23, 827-839 (2006)] and Stocker et al. ["Automated quality assurance routines for fMRI data applied to a multicenter study," Hum. Brain Mapp. 25, 237-246 (2005)], respectively. The easily developed and applied ICA-based QC protocol provided fMRI QC indices and maps equally sensitive to fMRI instabilities with the indices and maps of other established protocols. The ICA fMRI QC indices were highly correlated with indices of other fMRI QC protocols and in some cases theoretically related to them. Three or four independent components with slow varying time series are detected under normal conditions. ICA applied on phantom measurements is an easy and efficient tool for fMRI QC. Additionally, it can protect against misinterpretations of artifact components as human brain activations. Evaluating fMRI QC indices in the central region of a phantom is not always the optimal choice.

Quantification method for the appearance of melanin pigmentation using independent component analysis

NASA Astrophysics Data System (ADS)

Ojima, Nobutoshi; Okiyama, Natsuko; Okaguchi, Saya; Tsumura, Norimichi; Nakaguchi, Toshiya; Hori, Kimihiko; Miyake, Yoichi

2005-04-01

In the cosmetics industry, skin color is very important because skin color gives a direct impression of the face. In particular, many people suffer from melanin pigmentation such as liver spots and freckles. However, it is very difficult to evaluate melanin pigmentation using conventional colorimetric values because these values contain information on various skin chromophores simultaneously. Therefore, it is necessary to extract information of the chromophore of individual skins independently as density information. The isolation of the melanin component image based on independent component analysis (ICA) from a single skin image was reported in 2003. However, this technique has not developed a quantification method for melanin pigmentation. This paper introduces a quantification method based on the ICA of a skin color image to isolate melanin pigmentation. The image acquisition system we used consists of commercially available equipment such as digital cameras and lighting sources with polarized light. The images taken were analyzed using ICA to extract the melanin component images, and Laplacian of Gaussian (LOG) filter was applied to extract the pigmented area. As a result, for skin images including those showing melanin pigmentation and acne, the method worked well. Finally, the total amount of extracted area had a strong correspondence to the subjective rating values for the appearance of pigmentation. Further analysis is needed to recognize the appearance of pigmentation concerning the size of the pigmented area and its spatial gradation.

Independent and combined influence of the components of physical fitness on academic performance in youth.

PubMed

Esteban-Cornejo, Irene; Tejero-González, Carlos Ma; Martinez-Gomez, David; del-Campo, Juan; González-Galo, Ana; Padilla-Moledo, Carmen; Sallis, James F; Veiga, Oscar L

2014-08-01

To examine the independent and combined associations of the components of physical fitness with academic performance among youths. This cross-sectional study included a total of 2038 youths (989 girls) aged 6-18 years. Cardiorespiratory capacity was measured using the 20-m shuttle run test. Motor ability was assessed with the 4×10-m shuttle run test of speed of movement, agility, and coordination. A muscular strength z-score was computed based on handgrip strength and standing long jump distance. Academic performance was assessed through school records using 4 indicators: Mathematics, Language, an average of Mathematics and Language, and grade point average score. Cardiorespiratory capacity and motor ability were independently associated with all academic variables in youth, even after adjustment for fitness and fatness indicators (all P≤.001), whereas muscular strength was not associated with academic performance independent of the other 2 physical fitness components. In addition, the combined adverse effects of low cardiorespiratory capacity and motor ability on academic performance were observed across the risk groups (P for trend<.001). Cardiorespiratory capacity and motor ability, both independently and combined, may have a beneficial influence on academic performance in youth. Copyright © 2014 Elsevier Inc. All rights reserved.

Time Independent Functional task Training: a case study on the effect of inter-joint coordination driven haptic guidance in stroke therapy.

PubMed

Brokaw, Elizabeth B; Murray, Theresa M; Nef, Tobias; Lum, Peter S; Brokaw, Elizabeth B; Nichols, Diane; Holley, Rahsaan J

2011-01-01

After a stroke abnormal joint coordination of the arm may limit functional movement and recovery. To aid in training inter-joint movement coordination a haptic guidance method for functional driven rehabilitation after stroke called Time Independent Functional Training (TIFT) has been developed for the ARMin III robot. The mode helps retraining inter-joint coordination during functional movements, such as putting an object on a shelf, pouring from a pitcher, and sorting objects into bins. A single chronic stroke subject was tested for validation of the modality. The subject was given 1.5 hrs of robotic therapy twice a week for 4 weeks. The therapy and the results of training the single stroke subject are discussed. The subject showed a decrease in training joint error for the sorting task across training sessions and increased self-selected movement time in training. In kinematic reaching analysis the subject showed improvements in range of motion and joint coordination in a reaching task, as well as improvements in supination-pronation range of motion at the wrist. © 2011 IEEE

Noise reduction in functional near-infrared spectroscopy signals by independent component analysis

NASA Astrophysics Data System (ADS)

Santosa, Hendrik; Jiyoun Hong, Melissa; Kim, Sung-Phil; Hong, Keum-Shik

2013-07-01

Functional near-infrared spectroscopy (fNIRS) is used to detect concentration changes of oxy-hemoglobin and deoxy-hemoglobin in the human brain. The main difficulty entailed in the analysis of fNIRS signals is the fact that the hemodynamic response to a specific neuronal activation is contaminated by physiological and instrument noises, motion artifacts, and other interferences. This paper proposes independent component analysis (ICA) as a means of identifying the original hemodynamic response in the presence of noises. The original hemodynamic response was reconstructed using the primary independent component (IC) and other, less-weighting-coefficient ICs. In order to generate experimental brain stimuli, arithmetic tasks were administered to eight volunteer subjects. The t-value of the reconstructed hemodynamic response was improved by using the ICs found in the measured data. The best t-value out of 16 low-pass-filtered signals was 37, and that of the reconstructed one was 51. Also, the average t-value of the eight subjects' reconstructed signals was 40, whereas that of all of their low-pass-filtered signals was only 20. Overall, the results showed the applicability of the ICA-based method to noise-contamination reduction in brain mapping.

First metatarsophalangeal joint replacement with modular three-component press-fit implant. Preliminary report.

PubMed

Kolodziej, L; Bohatyrewicz, A; Zietek, P

2013-01-01

The aim of this retrospective study was to assess functional and radiographic results of the first metatarsophalangeal joint replacement with use of unconstrained, modular, three components, porous titanium and hydroxyapatite coated, press-fit METIS® prosthesis. According to author's knowledge, results of that type of prosthesis have never been published before. 25 prosthesis were implanted in 24 patients between February 2009 and May 2011. American Orthopaedic Foot and Ankle Society Hallux Metatarsophalangeal Interphalangeal scoring system (AOFAS-HMI) was used to assess functional results. Patients were also asked if they would undergo procedure again or recommend it to other people. Weight bearing radiographs ware made at final follow up and analyzed for presence of osteolysis and radiolucencies. In 8 patients total joint replacement was introduced as a salvage after failure of previous surgery like Keller resection arthroplasty, failed arthrodesis, avascular necrosis and postoperative arthritis. In 11 patients the reason for prosthetic replacement were hallux rigidus, in 4 cases rheumatoid arthritis and gout in one patient. In two patients additional procedures like Akin phalangeal osteotomy and in one case fifth metatarsal osteotomy, was performed. There were 20 females and 4 males in presented group. The mean age at the operation was 56 years. The average follow up period was 18 months (from 12 to 36 months). The median postoperative value of AOFAS-HMI scores was 88 points (from 75 to 95 points). First metatarsophalangeal joint motion (dorsiflexion plus plantarflexion) was classified according to AOFAS-HMI ranges as: moderately restricted (between 30 to 70 degrees) in 19 patients 80% (20 prosthesis) and severely restricted (less then 30 degrees) in 5 patients (20%). 15 (64%) patients were completely satisfied, 5 (20%) reported moderate satisfaction and (16%) 4 were totally disappointed and would not undergo this procedure again. A limited hallux dorsiflexion

Separation of GRACE geoid time-variations using Independent Component Analysis

NASA Astrophysics Data System (ADS)

Frappart, F.; Ramillien, G.; Maisongrande, P.; Bonnet, M.

2009-12-01

Independent Component Analysis (ICA) is a blind separation method based on the simple assumptions of the independence of the sources and the non-Gaussianity of the observations. An approach based on this numerical method is used here to extract hydrological signals over land and oceans from the polluting striping noise due to orbit repetitiveness and present in the GRACE global mass anomalies. We took advantage of the availability of monthly Level-2 solutions from three official providers (i.e., CSR, JPL and GFZ) that can be considered as different observations of the same phenomenon. The efficiency of the methodology is first demonstrated on a synthetic case. Applied to one month of GRACE solutions, it allows to clearly separate the total water storage change from the meridional-oriented spurious gravity signals on the continents but not on the oceans. This technique gives results equivalent as the destriping method for continental water storage for the hydrological patterns with less smoothing. This methodology is then used to filter the complete series of the 2002-2009 GRACE solutions.

BLIND EXTRACTION OF AN EXOPLANETARY SPECTRUM THROUGH INDEPENDENT COMPONENT ANALYSIS

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

Waldmann, I. P.; Tinetti, G.; Hollis, M. D. J.

2013-03-20

Blind-source separation techniques are used to extract the transmission spectrum of the hot-Jupiter HD189733b recorded by the Hubble/NICMOS instrument. Such a 'blind' analysis of the data is based on the concept of independent component analysis. The detrending of Hubble/NICMOS data using the sole assumption that nongaussian systematic noise is statistically independent from the desired light-curve signals is presented. By not assuming any prior or auxiliary information but the data themselves, it is shown that spectroscopic errors only about 10%-30% larger than parametric methods can be obtained for 11 spectral bins with bin sizes of {approx}0.09 {mu}m. This represents a reasonablemore » trade-off between a higher degree of objectivity for the non-parametric methods and smaller standard errors for the parametric de-trending. Results are discussed in light of previous analyses published in the literature. The fact that three very different analysis techniques yield comparable spectra is a strong indication of the stability of these results.« less

Development of W-composites/EUROFER brazed joints for the first wall component of future fusion reactors

NASA Astrophysics Data System (ADS)

de Prado, J.; Sánchez, M.; Antusch, S.; Ureña, A.

2017-12-01

The present work describes a joining procedure between two different tungsten composite materials (W-2Y2O3 and W-1TiC) with reduced activation ferritic-martensitic steel (Eurofer). The results indicated the achievement, in both cases, of high quality W-composites/Eurofer joints using 80Cu-20Ti as filler material. The braze is constituted by several ternary Cu-Ti-Fe phases distributed along a Cu-matrix, which acts as ductile phase capable of relieving the residual stresses, which could be produced during the service life of the component. Some cracks growing from W-braze interface into the base material have been detected. They are originated by the stresses produced during the cooling stage of the brazing cycle. Regarding the strength of the joints, similar shear strengths of both joints were obtained (˜105 MPa). These values were slightly lower than the ones obtained when pure tungsten was used as the base metal.

High pressure ceramic joint

DOEpatents

Ward, Michael E.; Harkins, Bruce D.

1993-01-01

Many recuperators have components which react to corrosive gases and are used in applications where the donor fluid includes highly corrosive gases. These recuperators have suffered reduced life, increased service or maintenance, and resulted in increased cost. The present joint when used with recuperators increases the use of ceramic components which do not react to highly corrosive gases. Thus, the present joint used with the present recuperator increases the life, reduces the service and maintenance, and reduces the increased cost associated with corrosive action of components used to manufacture recuperators. The present joint is comprised of a first ceramic member, a second ceramic member, a mechanical locking device having a groove defined in one of the first ceramic member and the second ceramic member. The joint and the mechanical locking device is further comprised of a refractory material disposed in the groove and contacting the first ceramic member and the second ceramic member. The present joint mechanically provides a high strength load bearing joint having good thermal cycling characteristics, good resistance to a corrosive environment and good steady state strength at elevated temperatures.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

PubMed

Calhoun, V D; Adali, T; Giuliani, N R; Pekar, J J; Kiehl, K A; Pearlson, G D

2006-01-01

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task. Hum Brain Mapp, 2005. (c) 2005 Wiley-Liss, Inc.

Principal Component Analysis in Construction of 3D Human Knee Joint Models Using a Statistical Shape Model Method

PubMed Central

Tsai, Tsung-Yuan; Li, Jing-Sheng; Wang, Shaobai; Li, Pingyue; Kwon, Young-Min; Li, Guoan

2013-01-01

The statistical shape model (SSM) method that uses 2D images of the knee joint to predict the 3D joint surface model has been reported in literature. In this study, we constructed a SSM database using 152 human CT knee joint models, including the femur, tibia and patella and analyzed the characteristics of each principal component of the SSM. The surface models of two in vivo knees were predicted using the SSM and their 2D bi-plane fluoroscopic images. The predicted models were compared to their CT joint models. The differences between the predicted 3D knee joint surfaces and the CT image-based surfaces were 0.30 ± 0.81 mm, 0.34 ± 0.79 mm and 0.36 ± 0.59 mm for the femur, tibia and patella, respectively (average ± standard deviation). The computational time for each bone of the knee joint was within 30 seconds using a personal computer. The analysis of this study indicated that the SSM method could be a useful tool to construct 3D surface models of the knee with sub-millimeter accuracy in real time. Thus it may have a broad application in computer assisted knee surgeries that require 3D surface models of the knee. PMID:24156375

Simplified Phased-Mission System Analysis for Systems with Independent Component Repairs

NASA Technical Reports Server (NTRS)

Somani, Arun K.

1996-01-01

Accurate analysis of reliability of system requires that it accounts for all major variations in system's operation. Most reliability analyses assume that the system configuration, success criteria, and component behavior remain the same. However, multiple phases are natural. We present a new computationally efficient technique for analysis of phased-mission systems where the operational states of a system can be described by combinations of components states (such as fault trees or assertions). Moreover, individual components may be repaired, if failed, as part of system operation but repairs are independent of the system state. For repairable systems Markov analysis techniques are used but they suffer from state space explosion. That limits the size of system that can be analyzed and it is expensive in computation. We avoid the state space explosion. The phase algebra is used to account for the effects of variable configurations, repairs, and success criteria from phase to phase. Our technique yields exact (as opposed to approximate) results. We demonstrate our technique by means of several examples and present numerical results to show the effects of phases and repairs on the system reliability/availability.

Linked independent component analysis for multimodal data fusion.

PubMed

Groves, Adrian R; Beckmann, Christian F; Smith, Steve M; Woolrich, Mark W

2011-02-01

In recent years, neuroimaging studies have increasingly been acquiring multiple modalities of data and searching for task- or disease-related changes in each modality separately. A major challenge in analysis is to find systematic approaches for fusing these differing data types together to automatically find patterns of related changes across multiple modalities, when they exist. Independent Component Analysis (ICA) is a popular unsupervised learning method that can be used to find the modes of variation in neuroimaging data across a group of subjects. When multimodal data is acquired for the subjects, ICA is typically performed separately on each modality, leading to incompatible decompositions across modalities. Using a modular Bayesian framework, we develop a novel "Linked ICA" model for simultaneously modelling and discovering common features across multiple modalities, which can potentially have completely different units, signal- and contrast-to-noise ratios, voxel counts, spatial smoothnesses and intensity distributions. Furthermore, this general model can be configured to allow tensor ICA or spatially-concatenated ICA decompositions, or a combination of both at the same time. Linked ICA automatically determines the optimal weighting of each modality, and also can detect single-modality structured components when present. This is a fully probabilistic approach, implemented using Variational Bayes. We evaluate the method on simulated multimodal data sets, as well as on a real data set of Alzheimer's patients and age-matched controls that combines two very different types of structural MRI data: morphological data (grey matter density) and diffusion data (fractional anisotropy, mean diffusivity, and tensor mode). Copyright © 2010 Elsevier Inc. All rights reserved.

Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2016-04-01

Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i

High pressure ceramic joint

DOEpatents

Ward, M.E.; Harkins, B.D.

1993-11-30

Many recuperators have components which react to corrosive gases and are used in applications where the donor fluid includes highly corrosive gases. These recuperators have suffered reduced life, increased service or maintenance, and resulted in increased cost. The present joint when used with recuperators increases the use of ceramic components which do not react to highly corrosive gases. Thus, the present joint used with the present recuperator increases the life, reduces the service and maintenance, and reduces the increased cost associated with corrosive action of components used to manufacture recuperators. The present joint is comprised of a first ceramic member, a second ceramic member, a mechanical locking device having a groove defined in one of the first ceramic member and the second ceramic member. The joint and the mechanical locking device is further comprised of a refractory material disposed in the groove and contacting the first ceramic member and the second ceramic member. The present joint mechanically provides a high strength load bearing joint having good thermal cycling characteristics, good resistance to a corrosive environment and good steady state strength at elevated temperatures. 4 figures.

Rotation of EOFs by the Independent Component Analysis: Towards A Solution of the Mixing Problem in the Decomposition of Geophysical Time Series

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)

2001-01-01

The Independent Component Analysis is a recently developed technique for component extraction. This new method requires the statistical independence of the extracted components, a stronger constraint that uses higher-order statistics, instead of the classical decorrelation, a weaker constraint that uses only second-order statistics. This technique has been used recently for the analysis of geophysical time series with the goal of investigating the causes of variability in observed data (i.e. exploratory approach). We demonstrate with a data simulation experiment that, if initialized with a Principal Component Analysis, the Independent Component Analysis performs a rotation of the classical PCA (or EOF) solution. This rotation uses no localization criterion like other Rotation Techniques (RT), only the global generalization of decorrelation by statistical independence is used. This rotation of the PCA solution seems to be able to solve the tendency of PCA to mix several physical phenomena, even when the signal is just their linear sum.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Fetal ECG Extraction From Maternal Body Surface Measurement Using Independent Component Analysis

DTIC Science & Technology

2001-10-25

Ibaraki 305-0901, Japan Abstract – A method applying independent component analysis (ICA) to detect the electrocardiogram of a prenatal cattle foetus is...monitoring the health status of an unborn cattle foetus is indispensable in preventing natural abortion and premature birth [3]. One of the applicable...and Y. Honda, “ECG and Heart Rate Detection of Prenatal Cattle Foetus Using Adaptive Digital Filtering,” World Congress on Med. Phys.& Biomed. Eng., Chicago TU-CXH-75, pp. 1-4, 2000.

Principal component analysis in construction of 3D human knee joint models using a statistical shape model method.

PubMed

Tsai, Tsung-Yuan; Li, Jing-Sheng; Wang, Shaobai; Li, Pingyue; Kwon, Young-Min; Li, Guoan

2015-01-01

The statistical shape model (SSM) method that uses 2D images of the knee joint to predict the three-dimensional (3D) joint surface model has been reported in the literature. In this study, we constructed a SSM database using 152 human computed tomography (CT) knee joint models, including the femur, tibia and patella and analysed the characteristics of each principal component of the SSM. The surface models of two in vivo knees were predicted using the SSM and their 2D bi-plane fluoroscopic images. The predicted models were compared to their CT joint models. The differences between the predicted 3D knee joint surfaces and the CT image-based surfaces were 0.30 ± 0.81 mm, 0.34 ± 0.79 mm and 0.36 ± 0.59 mm for the femur, tibia and patella, respectively (average ± standard deviation). The computational time for each bone of the knee joint was within 30 s using a personal computer. The analysis of this study indicated that the SSM method could be a useful tool to construct 3D surface models of the knee with sub-millimeter accuracy in real time. Thus, it may have a broad application in computer-assisted knee surgeries that require 3D surface models of the knee.

Keys and seats: Spatial response coding underlying the joint spatial compatibility effect.

PubMed

Dittrich, Kerstin; Dolk, Thomas; Rothe-Wulf, Annelie; Klauer, Karl Christoph; Prinz, Wolfgang

2013-11-01

Spatial compatibility effects (SCEs) are typically observed when participants have to execute spatially defined responses to nonspatial stimulus features (e.g., the color red or green) that randomly appear to the left and the right. Whereas a spatial correspondence of stimulus and response features facilitates response execution, a noncorrespondence impairs task performance. Interestingly, the SCE is drastically reduced when a single participant responds to one stimulus feature (e.g., green) by operating only one response key (individual go/no-go task), whereas a full-blown SCE is observed when the task is distributed between two participants (joint go/no-go task). This joint SCE (a.k.a. the social Simon effect) has previously been explained by action/task co-representation, whereas alternative accounts ascribe joint SCEs to spatial components inherent in joint go/no-go tasks that allow participants to code their responses spatially. Although increasing evidence supports the idea that spatial rather than social aspects are responsible for joint SCEs emerging, it is still unclear to which component(s) the spatial coding refers to: the spatial orientation of response keys, the spatial orientation of responding agents, or both. By varying the spatial orientation of the responding agents (Exp. 1) and of the response keys (Exp. 2), independent of the spatial orientation of the stimuli, in the present study we found joint SCEs only when both the seating and the response key alignment matched the stimulus alignment. These results provide evidence that spatial response coding refers not only to the response key arrangement, but also to the-often neglected-spatial orientation of the responding agents.

Inflammation is more distinct in temporomandibular joint osteoarthritis compared to the knee joint.

PubMed

Vos, Lukas M; Kuijer, Roel; Huddleston Slater, James J R; Bulstra, Sjoerd K; Stegenga, Boudewijn

2014-01-01

Most of the current understanding of articular cartilage maintenance and degradation is derived from large load-bearing synovial joints, in particular the knee joint. The aim of this study was to identify valuable degradation markers for cartilage degradation in the temporomandibular joint (TMJ) by comparing the relative concentrations of carboxyterminal telopeptides of collagen types I and II (CTX-I and CTX-II), cartilage oligomeric matrix protein (COMP), and prostaglandin E2 (PGE2) in synovial fluid (SF) of TMJ and knee joints with cartilage degradation. In this cross-sectional comparative study, participants were recruited from the University Medical Center Groningen, The Netherlands. Patients with TMJ osteoarthritis were compared with patients with knee osteoarthritis. The outcome variables were the relative SF concentrations of CTX-I, CTX-II, COMP, and PGE2. An independent samples Mann-Whitney U test was used to compare the relative concentrations. Thirty consecutive patients (9 male, 21 female; mean age, 40.1 yr; standard deviation, 15.3 yr) with TMJ osteoarthritis and 31 consecutive patients (20 male, 11 female; mean age, 37.4 yr; standard deviation, 13.7 yr) who were scheduled for arthroscopy of the knee joint participated in this study. Significant differences were found between relative concentrations of COMP (P = .000) and PGE2 (P = .005), and no significant differences were found between relative concentrations of CTX-I (P = .720) and CTX-II (P = .242). Relative SF concentrations of COMP and PGE2 showed significant differences between the TMJ and the knee joint, suggesting that there are differences in pathophysiology and that the inflammatory component may be more distinct in the TMJ. Copyright © 2014 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Mechanics of Suture Joints

NASA Astrophysics Data System (ADS)

Li, Yaning; Song, Juha; Ortiz, Christine; Boyce, Mary; Ortiz Group/DMSE/MIT Team; Boyce Group/ME/MIT Team

2011-03-01

Biological sutures are joints which connect two stiff skeletal or skeletal-like components. These joints possess a wavy geometry with a thin organic layer providing adhesion. Examples of biological sutures include mammalian skulls, the pelvic assembly of the armored fish Gasterosteus aculeatus (the three-spined stickleback), and the suture joints in the shell of the red-eared slider turtle. Biological sutures allow for movement and compliance, control stress concentrations, transmit loads, reduce fatigue stress and absorb energy. In this investigation, the mechanics of the role of suture geometry in providing a naturally optimized joint is explored. In particular, analytical and numerical micromechanical models of the suture joint are constructed. The anisotropic mechanical stiffness and strength are studied as a function of suture wavelength, amplitude and the material properties of the skeletal and organic components, revealing key insights into the optimized nature of these ubiquitous natural joints.

Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data.

PubMed

Pagani, Marco; Giuliani, Alessandro; Öberg, Johanna; De Carli, Fabrizio; Morbelli, Silvia; Girtler, Nicola; Arnaldi, Dario; Accardo, Jennifer; Bauckneht, Matteo; Bongioanni, Francesca; Chincarini, Andrea; Sambuceti, Gianmario; Jonsson, Cathrine; Nobili, Flavio

2017-07-01

Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18 F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD-including mild cognitive impairment (MCI) not converting or converting to AD-to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18 F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Concurrent white matter bundles and grey matter networks using independent component analysis.

PubMed

O'Muircheartaigh, Jonathan; Jbabdi, Saad

2018-04-15

Developments in non-invasive diffusion MRI tractography techniques have permitted the investigation of both the anatomy of white matter pathways connecting grey matter regions and their structural integrity. In parallel, there has been an expansion in automated techniques aimed at parcellating grey matter into distinct regions based on functional imaging. Here we apply independent component analysis to whole-brain tractography data to automatically extract brain networks based on their associated white matter pathways. This method decomposes the tractography data into components that consist of paired grey matter 'nodes' and white matter 'edges', and automatically separates major white matter bundles, including known cortico-cortical and cortico-subcortical tracts. We show how this framework can be used to investigate individual variations in brain networks (in terms of both nodes and edges) as well as their associations with individual differences in behaviour and anatomy. Finally, we investigate correspondences between tractography-based brain components and several canonical resting-state networks derived from functional MRI. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Development of non-destructive examination techniques for CFC-metal joints in annular geometry and their application to the manufacturing of plasma-facing components

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

Di Pietro, E.; Visca, E.; Orsini, A.

1995-12-31

The design of plasma-facing components for ITER, as for any of the envisaged next-step machines, relies heavily on the use of brazed junctions to couple armour materials to the heat sink and cooling tubes. Moreover, the typical number of brazed components and the envisaged effects of local overheating due to failure in a single brazed junction stress the importance of having a set of NDE techniques developed that can ensure the flawless quality of the joint. The qualification and application of two NDE techniques (ultrasonic and thermographic analysis) for inspection of CFC-to-metal joints is described with particular regard to themore » annular geometry typical of macroblock/monoblock solutions for divertor high-heat-flux components. The results of the eddy current inspection are not reported. The development has been focused specifically on the joint between carbon-fiber composite and TZM molybdenum alloy; techniques for the production of reference defect samples have been devised and a set of reference defect samples produced. The comparative results of the NDE inspections are reported and discussed, also on the basis of the destructive examination of the samples. The nature and size of relevant and detectable defects are discussed together with hints for a possible NDE strategy for divertor high-heat-flux components.« less

Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

PubMed

Leibig, Christian; Wachtler, Thomas; Zeck, Günther

2016-09-15

Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (ICA) achieves rapid unsupervised sorting, it ignores the convolutive structure of extracellular data, thus limiting the unmixing to a subset of neurons. Here we present a spike sorting algorithm based on convolutive ICA (cICA) to retrieve a larger number of accurately sorted neurons than with instantaneous ICA while accounting for signal overlaps. Spike sorting was applied to datasets with varying signal-to-noise ratios (SNR: 3-12) and 27% spike overlaps, sampled at either 11.5 or 23kHz on 4365 electrodes. We demonstrate how the instantaneity assumption in ICA-based algorithms has to be relaxed in order to improve the spike sorting performance for high-density microelectrode array recordings. Reformulating the convolutive mixture as an instantaneous mixture by modeling several delayed samples jointly is necessary to increase signal-to-noise ratio. Our results emphasize that different cICA algorithms are not equivalent. Spike sorting performance was assessed with ground-truth data generated from experimentally derived templates. The presented spike sorter was able to extract ≈90% of the true spike trains with an error rate below 2%. It was superior to two alternative (c)ICA methods (≈80% accurately sorted neurons) and comparable to a supervised sorting. Our new algorithm represents a fast solution to overcome the current bottleneck in spike sorting of large datasets generated by simultaneous recording with thousands of electrodes. Copyright © 2016 Elsevier B.V. All rights reserved.

A method for independent component graph analysis of resting-state fMRI.

PubMed

Ribeiro de Paula, Demetrius; Ziegler, Erik; Abeyasinghe, Pubuditha M; Das, Tushar K; Cavaliere, Carlo; Aiello, Marco; Heine, Lizette; di Perri, Carol; Demertzi, Athena; Noirhomme, Quentin; Charland-Verville, Vanessa; Vanhaudenhuyse, Audrey; Stender, Johan; Gomez, Francisco; Tshibanda, Jean-Flory L; Laureys, Steven; Owen, Adrian M; Soddu, Andrea

2017-03-01

Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. First, ICA was performed at the single-subject level in 15 healthy volunteers using a 3T MRI scanner. The identification of nine networks was performed by a multiple-template matching procedure and a subsequent component classification based on the network "neuronal" properties. Second, for each of the identified networks, the nodes were defined as 1,015 anatomically parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Network graph comparison between the classically constructed network and the nine networks showed significant differences in the auditory and visual medial networks with regard to the average degree and the number of edges, while the visual lateral network showed a significant difference in the small-worldness. This novel approach permits us to take advantage of the well-recognized power of ICA in BOLD signal decomposition and, at the same time, to make use of well-established graph measures to evaluate connectivity differences. Moreover, by providing a graph for each separate network, it can offer the possibility to extract graph measures in a specific way for each network. This increased specificity could be relevant for studying pathological brain activity or altered states of consciousness as induced by anesthesia or sleep, where specific networks are known to be altered in

An early underwater artificial vision model in ocean investigations via independent component analysis.

PubMed

Nian, Rui; Liu, Fang; He, Bo

2013-07-16

Underwater vision is one of the dominant senses and has shown great prospects in ocean investigations. In this paper, a hierarchical Independent Component Analysis (ICA) framework has been established to explore and understand the functional roles of the higher order statistical structures towards the visual stimulus in the underwater artificial vision system. The model is inspired by characteristics such as the modality, the redundancy reduction, the sparseness and the independence in the early human vision system, which seems to respectively capture the Gabor-like basis functions, the shape contours or the complicated textures in the multiple layer implementations. The simulation results have shown good performance in the effectiveness and the consistence of the approach proposed for the underwater images collected by autonomous underwater vehicles (AUVs).

An Early Underwater Artificial Vision Model in Ocean Investigations via Independent Component Analysis

PubMed Central

Nian, Rui; Liu, Fang; He, Bo

2013-01-01

Underwater vision is one of the dominant senses and has shown great prospects in ocean investigations. In this paper, a hierarchical Independent Component Analysis (ICA) framework has been established to explore and understand the functional roles of the higher order statistical structures towards the visual stimulus in the underwater artificial vision system. The model is inspired by characteristics such as the modality, the redundancy reduction, the sparseness and the independence in the early human vision system, which seems to respectively capture the Gabor-like basis functions, the shape contours or the complicated textures in the multiple layer implementations. The simulation results have shown good performance in the effectiveness and the consistence of the approach proposed for the underwater images collected by autonomous underwater vehicles (AUVs). PMID:23863855

Extraction of a Weak Co-Channel Interfering Communication Signal Using Complex Independent Component Analysis

DTIC Science & Technology

2013-06-01

zarzoso/ biblio /tnn10.pdf"> % "Robust independent component analysis by iterative maximization</a> % <a href = "http://www.i3s.unice.fr/~zarzoso... biblio /tnn10.pdf"> % of the kurtosis contrast with algebraic optimal step size"</a>, % IEEE Transactions on Neural Networks, vol. 21, no. 2, % pp

Independent component analysis based digital signal processing in coherent optical fiber communication systems

NASA Astrophysics Data System (ADS)

Li, Xiang; Luo, Ming; Qiu, Ying; Alphones, Arokiaswami; Zhong, Wen-De; Yu, Changyuan; Yang, Qi

2018-02-01

In this paper, channel equalization techniques for coherent optical fiber transmission systems based on independent component analysis (ICA) are reviewed. The principle of ICA for blind source separation is introduced. The ICA based channel equalization after both single-mode fiber and few-mode fiber transmission for single-carrier and orthogonal frequency division multiplexing (OFDM) modulation formats are investigated, respectively. The performance comparisons with conventional channel equalization techniques are discussed.

Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Ouyang, Xin; Sun, Xiaoyu; Guo, Ting; Sun, Qiaoyue; Chen, Kewei; Yao, Li; Wu, Xia; Guo, Xiaojuan

2014-03-01

Alzheimer's disease (AD) is a progressive neurodegenerative disease with the clinical symptom of the continuous deterioration of cognitive and memory functions. Multiple diffusion tensor imaging (DTI) indices such as fractional anisotropy (FA) and mean diffusivity (MD) can successfully explain the white matter damages in AD patients. However, most studies focused on the univariate measures (voxel-based analysis) to examine the differences between AD patients and normal controls (NCs). In this investigation, we applied a multivariate independent component analysis (ICA) to investigate the white matter covariances based on FA measurement from DTI data in 35 AD patients and 45 NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We found that six independent components (ICs) showed significant FA reductions in white matter covariances in AD compared with NC, including the genu and splenium of corpus callosum (IC-1 and IC-2), middle temporal gyral of temporal lobe (IC-3), sub-gyral of frontal lobe (IC-4 and IC-5) and sub-gyral of parietal lobe (IC-6). Our findings revealed covariant white matter loss in AD patients and suggest that the unsupervised data-driven ICA method is effective to explore the changes of FA in AD. This study assists us in understanding the mechanism of white matter covariant reductions in the development of AD.

Face recognition using an enhanced independent component analysis approach.

PubMed

Kwak, Keun-Chang; Pedrycz, Witold

2007-03-01

This paper is concerned with an enhanced independent component analysis (ICA) and its application to face recognition. Typically, face representations obtained by ICA involve unsupervised learning and high-order statistics. In this paper, we develop an enhancement of the generic ICA by augmenting this method by the Fisher linear discriminant analysis (LDA); hence, its abbreviation, FICA. The FICA is systematically developed and presented along with its underlying architecture. A comparative analysis explores four distance metrics, as well as classification with support vector machines (SVMs). We demonstrate that the FICA approach leads to the formation of well-separated classes in low-dimension subspace and is endowed with a great deal of insensitivity to large variation in illumination and facial expression. The comprehensive experiments are completed for the facial-recognition technology (FERET) face database; a comparative analysis demonstrates that FICA comes with improved classification rates when compared with some other conventional approaches such as eigenface, fisherface, and the ICA itself.

Variational Bayesian Learning for Wavelet Independent Component Analysis

NASA Astrophysics Data System (ADS)

Roussos, E.; Roberts, S.; Daubechies, I.

2005-11-01

In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.

Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2018-02-01

Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.

Order-crossing removal in Gabor order tracking by independent component analysis

NASA Astrophysics Data System (ADS)

Guo, Yu; Tan, Kok Kiong

2009-08-01

Order-crossing problems in Gabor order tracking (GOT) of rotating machinery often occur when noise due to power-frequency interference, local structure resonance, etc., is prominent in applications. They can render the analysis results and the waveform-reconstruction tasks in GOT inaccurate or even meaningless. An approach is proposed in this paper to address the order-crossing problem by independent component analysis (ICA). With the approach, accurate order analysis results can be obtained and the waveforms of the order components of interest can be reconstructed or extracted from the recorded noisy data series. In addition, the ambiguities (permutation and scaling) of ICA results are also solved with the approach. The approach is amenable to applications in condition monitoring and fault diagnosis of rotating machinery. The evaluation of the approach is presented in detail based on simulations and an experiment on a rotor test rig. The results obtained using the proposed approach are compared with those obtained using the standard GOT. The comparison shows that the presented approach is more effective to solve order-crossing problems in GOT.

Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers.

PubMed

De Martino, Federico; Gentile, Francesco; Esposito, Fabrizio; Balsi, Marco; Di Salle, Francesco; Goebel, Rainer; Formisano, Elia

2007-01-01

We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets. The method consists of two steps. In the first step, each fMRI-IC is associated with an IC-fingerprint, i.e., a representation of the component in a multidimensional space of parameters. These parameters are post hoc estimates of global properties of the ICs and are largely independent of a specific experimental design and stimulus timing. In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components. We illustrate this approach in a multisubject fMRI study employing visual structure-from-motion stimuli encoding faces and control random shapes. We show that: (1) IC-fingerprints are a valuable tool for the inspection, characterization and selection of fMRI-ICs and (2) automatic classifications of fMRI-ICs in new subjects present a high correspondence with those obtained by expert visual inspection of the components. Importantly, our classification procedure highlights several neurophysiologically interesting processes. The most intriguing of which is reflected, with high intra- and inter-subject reproducibility, in one IC exhibiting a transiently task-related activation in the 'face' region of the primary sensorimotor cortex. This suggests that in addition to or as part of the mirror system, somatotopic regions of the sensorimotor cortex are involved in disambiguating the perception of a moving body part. Finally, we show that the same classification algorithm can be successfully applied, without re-training, to fMRI collected using acquisition parameters, stimulation modality and timing considerably different from those used for training.

QM-8 field joint protection system, volume 7

NASA Technical Reports Server (NTRS)

Hale, Elgie

1989-01-01

The pre-launch functioning data of the Field Joint Protection System (JPS) used on QM-8 are presented. Also included is the post fire condition of the JPS components following the test firing of the motor. The JPS components are: field joint heaters; field joint sensors; field joint moisture seal; moisture seal kevlar retaining straps; field joint external extruded cork insulation; vent valve; power cables; and igniter heater.

The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

PubMed

Wang, Gang; Teng, Chaolin; Li, Kuo; Zhang, Zhonglin; Yan, Xiangguo

2016-09-01

The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.

[Extraction of evoked related potentials by using the combination of independent component analysis and wavelet analysis].

PubMed

Zou, Ling; Chen, Shuyue; Sun, Yuqiang; Ma, Zhenghua

2010-08-01

In this paper we present a new method of combining Independent Component Analysis (ICA) and Wavelet de-noising algorithm to extract Evoked Related Potentials (ERPs). First, the extended Infomax-ICA algorithm is used to analyze EEG signals and obtain the independent components (Ics); Then, the Wave Shrink (WS) method is applied to the demixed Ics as an intermediate step; the EEG data were rebuilt by using the inverse ICA based on the new Ics; the ERPs were extracted by using de-noised EEG data after being averaged several trials. The experimental results showed that the combined method and ICA method could remove eye artifacts and muscle artifacts mixed in the ERPs, while the combined method could retain the brain neural activity mixed in the noise Ics and could extract the weak ERPs efficiently from strong background artifacts.

Classification of high-resolution multispectral satellite remote sensing images using extended morphological attribute profiles and independent component analysis

NASA Astrophysics Data System (ADS)

Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei

2017-07-01

In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.

Functional anatomy of the temporomandibular joint (I).

PubMed

Sava, Anca; Scutariu, Mihaela Monica

2012-01-01

Jaw movement is analyzed as the action between two rigid components jointed together in a particular way, the movable mandible against the stabilized cranium. Jaw articulation distinguishes form most other synovial joints of the body by the coincidence of certain characteristic features. Its articular surfaces are not covered by hyaline cartilage as elsewhere. The two jointed components carry teeth the shape, position and occlusion of which having a unique influence on specific positions and movements within the joint. A fibrocartilaginous disc is interposed between upper and lower articular surfaces; this disc compensates for the incongruities in opposing parts and allows sliding, pivoting, and rotating movements between the bony components. These are the reasons for our review of the functional anatomy of the temporomandibular joint.

Immediate Biomechanical Implications of Transfer Component Skills Training on Independent Wheelchair Transfers.

PubMed

Tsai, Chung-Ying; Boninger, Michael L; Hastings, Jennifer; Cooper, Rory A; Rice, Laura; Koontz, Alicia M

2016-10-01

To evaluate the immediate effects of transfer training based on the Transfer Assessment Instrument (TAI) on the upper limb biomechanics during transfers. Pre-post intervention. Biomechanics laboratory. Full-time manual wheelchair users (N=24) performed 5 transfers to a level height bench, while their natural transfer skills were scored using the TAI, and their biomechanical data were recorded. Participants with 2 or more component skill deficits were invited to return to receive personalized transfer training. TAI part 1 summary scores and biomechanical variables calculated at the shoulder, elbow, and wrist joints were compared before and immediately after transfer training. Sixteen of the 24 manual wheelchair users met the criteria for training, and 11 manual wheelchair users came back for the revisit. Their TAI part 1 summary scores improved from 6.31±.98 to 9.92±.25. They had significantly smaller elbow range of motion, shoulder resultant moment, and rates of rise of elbow and wrist resultant forces on their trailing side during transfers after training (P<.05). On the leading side, shoulder maximum internal rotation and elevation angles, and shoulder resultant moments and rates of rise of shoulder resultant force and moment decreased after training (P<.04). The TAI-based training showed short-term beneficial biomechanical effects on wheelchair users' upper limbs, such as better shoulder positioning and lower joint loadings. If the skills are practiced longer-term, they may help protect the upper limbs from developing pain and injuries. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Independent component analysis separates spikes of different origin in the EEG.

PubMed

Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

2006-02-01

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

Component separation of a isotropic Gravitational Wave Background

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

Parida, Abhishek; Jhingan, Sanjay; Mitra, Sanjit, E-mail: abhishek@jmi.ac.in, E-mail: sanjit@iucaa.in, E-mail: sjhingan@jmi.ac.in

2016-04-01

A Gravitational Wave Background (GWB) is expected in the universe from the superposition of a large number of unresolved astrophysical sources and phenomena in the early universe. Each component of the background (e.g., from primordial metric perturbations, binary neutron stars, milli-second pulsars etc.) has its own spectral shape. Many ongoing experiments aim to probe GWB at a variety of frequency bands. In the last two decades, using data from ground-based laser interferometric gravitational wave (GW) observatories, upper limits on GWB were placed in the frequency range of 0∼ 50−100 Hz, considering one spectral shape at a time. However, one strong componentmore » can significantly enhance the estimated strength of another component. Hence, estimation of the amplitudes of the components with different spectral shapes should be done jointly. Here we propose a method for 'component separation' of a statistically isotropic background, that can, for the first time, jointly estimate the amplitudes of many components and place upper limits. The method is rather straightforward and needs negligible amount of computation. It utilises the linear relationship between the measurements and the amplitudes of the actual components, alleviating the need for a sampling based method, e.g., Markov Chain Monte Carlo (MCMC) or matched filtering, which are computationally intensive and cumbersome in a multi-dimensional parameter space. Using this formalism we could also study how many independent components can be separated using a given dataset from a network of current and upcoming ground based interferometric detectors.« less

Validation of Shared and Specific Independent Component Analysis (SSICA) for Between-Group Comparisons in fMRI

PubMed Central

Maneshi, Mona; Vahdat, Shahabeddin; Gotman, Jean; Grova, Christophe

2016-01-01

Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named “shared and specific independent component analysis” (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i.e., components that could be considered “specific” for a group or condition. Here, we investigated the performance of SSICA on realistic simulations, and task fMRI data and compared the results with one of the state-of-the-art group ICA approaches to infer between-group differences. We examined SSICA robustness with respect to the number of allowable extracted specific components and between-group orthogonality assumptions. Furthermore, we proposed a modified formulation of the back-reconstruction method to generate group-level t-statistics maps based on SSICA results. We also evaluated the consistency and specificity of the extracted specific components by SSICA. The results on realistic simulated and real fMRI data showed that SSICA outperforms the regular group ICA approach in terms of reconstruction and classification performance. We demonstrated that SSICA is a powerful data-driven approach to detect patterns of differences in functional connectivity across groups/conditions, particularly in model-free designs such as resting-state fMRI. Our findings in task fMRI show that SSICA confirms results of the general linear model (GLM) analysis and when combined with clustering analysis, it complements GLM findings by providing additional information regarding the reliability and specificity of networks. PMID:27729843

Joint diseases: from connexins to gap junctions.

PubMed

Donahue, Henry J; Qu, Roy W; Genetos, Damian C

2017-12-19

Connexons form the basis of hemichannels and gap junctions. They are composed of six tetraspan proteins called connexins. Connexons can function as individual hemichannels, releasing cytosolic factors (such as ATP) into the pericellular environment. Alternatively, two hemichannel connexons from neighbouring cells can come together to form gap junctions, membrane-spanning channels that facilitate cell-cell communication by enabling signalling molecules of approximately 1 kDa to pass from one cell to an adjacent cell. Connexins are expressed in joint tissues including bone, cartilage, skeletal muscle and the synovium. Indicative of their importance as gap junction components, connexins are also known as gap junction proteins, but individual connexin proteins are gaining recognition for their channel-independent roles, which include scaffolding and signalling functions. Considerable evidence indicates that connexons contribute to the function of bone and muscle, but less is known about the function of connexons in other joint tissues. However, the implication that connexins and gap junctional channels might be involved in joint disease, including age-related bone loss, osteoarthritis and rheumatoid arthritis, emphasizes the need for further research into these areas and highlights the therapeutic potential of connexins.

Using Independent Components Analysis to diminish the response of groundwater in borehole strainmeter

NASA Astrophysics Data System (ADS)

Chen, Chih-Yen; Hu, Jyr-Ching

2017-04-01

With designed feather, borehole strainmeter can not only record minor signals of tectonic movements, but also broad environmental signs such as barometry, rainfall and groundwater. Among these external factor, groundwater will influence the observation of borehole strainmeter mostly. According to essential observation, groundwater will cause much bigger response than the target tectonic strain change. We use co-sited piezometer to record pore pressure of groundwater in the rock formation in order to obtain the relationship of stain change and pore pressure. But there still exist some puzzle that can not be solved. First, due to instrument limitation, we could not set the pore pressure transducer in the same aquifer as strainmeter did. In this case, the response due to pore pressure change might be not fully correct. Furthermore, through pore-pressure transducers were set in most observatory, problem of electricity and connectivity will cause the record lack and lost. Therefore, it is necessary to find out a better and more stable method to diminish the groundwater response of strainmeter data.Strain transducer with different orientation can observe the groundwater response in different scale. If we can extract out groundwater signal from each independent strain transducer and estimate its original source. That will significantly rise signal strength and lower noise level. The case belongs some kind of blind-signal-separation (BSS) problem. The procedure of BSS extract or rebuild signal that can't be observed directly in many mixed sources and Independent-Component-Analysis (ICA) is one method adopted broadly. ICA is an analysis to find out parts which have statistics independence and non-Gaussian factor in complex signals. We use FastICA developed by to figure out the groundwater response strain in original strain data, and try to diminish it to rise the signal strength. We preceded strain data previously, then using ICA to separate data into serval independent

Data analysis using a combination of independent component analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lin, Shih-Lin; Tung, Pi-Cheng; Huang, Norden E.

2009-06-01

A combination of independent component analysis and empirical mode decomposition (ICA-EMD) is proposed in this paper to analyze low signal-to-noise ratio data. The advantages of ICA-EMD combination are these: ICA needs few sensory clues to separate the original source from unwanted noise and EMD can effectively separate the data into its constituting parts. The case studies reported here involve original sources contaminated by white Gaussian noise. The simulation results show that the ICA-EMD combination is an effective data analysis tool.

Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures.

PubMed

Bouhlel, Jihéne; Jouan-Rimbaud Bouveresse, Delphine; Abouelkaram, Said; Baéza, Elisabeth; Jondreville, Catherine; Travel, Angélique; Ratel, Jérémy; Engel, Erwan; Rutledge, Douglas N

2018-02-01

The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not

Influence factors of multicomponent mixtures containing reactive chemicals and their joint effects.

PubMed

Tian, Dayong; Lin, Zhifen; Yu, Jianqiao; Yin, Daqiang

2012-08-01

Organic chemicals usually coexist as a mixture in the environment, and the mixture toxicity of organic chemicals has received increased attention. However, research regarding the joint effects of reactive chemicals is lacking. In this study, we examined two kinds of reactive chemicals, cyanogenic toxicants and aldehydes and determined their joint effects on Photobacterium phosphoreum. Three factors were found to influence the joint effects of multicomponent mixtures containing reactive chemicals, including the number of components, the dominating components and the toxic ratios. With an increased number of components, the synergistic or antagonistic effects (interactions) will weaken to the additive effects (non-interactions) if the added component cannot yield a much stronger joint effect with an existing component. Contrarily, the joint effect of the mixture may become stronger instead of weaker if the added components can yield a much stronger joint effect than the existing joint effect of the multicomponent mixture. The components that yield the strongest interactions in their binary mixture can be considered the dominating components. These components contribute more to the interactions of multicomponent mixtures than other components. Moreover, the toxic ratios also influence the joint effects of the mixtures. This study provides an insight into what are the main factors and how they influence the joint effects of multicomponent mixtures containing reactive chemicals, and thus, the findings are beneficial to the study of mixture toxicology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers

PubMed Central

Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

2014-01-01

Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject “at rest”). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing “signal” (brain activity) can be distinguished form the “noise” components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX (“FMRIB’s ICA-based X-noiseifier”), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different Classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of

Rotational joint assembly and method for constructing the same

NASA Technical Reports Server (NTRS)

Bandera, Pablo (Inventor); Buchele, Paul (Inventor)

2012-01-01

A rotational joint assembly and a method for constructing a rotational joint assembly are provided. The rotational joint assembly includes a first rotational component, a second rotational component coupled to the first rotational component such that the second rotational component is rotatable relative to the first rotational component in first and second rotational directions about an axis, and a flexure member, being deflectable in first and second deflection directions, coupled to at least one of the first and second rotational components such that when the second rotational component is rotated relative to the first rotational component in each of the first and second rotational directions about the axis, the flexure member is deflected in the first deflection direction and exerts a force on the second rotational component opposing the rotation.

Speed invariance of independent control of finger movements in pianists

PubMed Central

Soechting, John F.

2012-01-01

Independent control of finger movements characterizes skilled motor behaviors such as tool use and musical performance. The purpose of the present study was to identify the effect of movement frequency (tempo) on individuated finger movements in piano playing. Joint motion at the digits was recorded while 5 expert pianists were playing 30 excerpts from musical pieces with different fingering and key locations either at a predetermined normal tempo or as fast as possible. Principal component analysis and cluster analysis using an expectation-maximization algorithm determined three distinct patterns of finger movement coordination for a keypress with each of the index, middle, ring, and little fingers at each of the two tempi. The finger kinematics of each coordination pattern was overall similar across the tempi. Tone sequences assigned into each cluster were also similar for both tempi. A linear regression analysis determined no apparent difference in the amount of movement covariation between the striking and nonstriking fingers at both metacarpo-phalangeal and proximal-interphalangeal joints across the two tempi, which indicated no effect of tempo on independent finger movements in piano playing. In addition, the standard deviation of interkeystroke interval across strokes did not differ between the two tempi, indicating maintenance of rhythmic accuracy of keystrokes. Strong temporal constraints on finger movements during piano playing may underlie the maintained independent control of fingers over a wider range of tempi, a feature being likely to be specific to skilled pianists. PMID:22815403

Reliability Study of Solder Paste Alloy for the Improvement of Solder Joint at Surface Mount Fine-Pitch Components.

PubMed

Rahman, Mohd Nizam Ab; Zubir, Noor Suhana Mohd; Leuveano, Raden Achmad Chairdino; Ghani, Jaharah A; Mahmood, Wan Mohd Faizal Wan

2014-12-02

The significant increase in metal costs has forced the electronics industry to provide new materials and methods to reduce costs, while maintaining customers' high-quality expectations. This paper considers the problem of most electronic industries in reducing costly materials, by introducing a solder paste with alloy composition tin 98.3%, silver 0.3%, and copper 0.7%, used for the construction of the surface mount fine-pitch component on a Printing Wiring Board (PWB). The reliability of the solder joint between electronic components and PWB is evaluated through the dynamic characteristic test, thermal shock test, and Taguchi method after the printing process. After experimenting with the dynamic characteristic test and thermal shock test with 20 boards, the solder paste was still able to provide a high-quality solder joint. In particular, the Taguchi method is used to determine the optimal control parameters and noise factors of the Solder Printer (SP) machine, that affects solder volume and solder height. The control parameters include table separation distance, squeegee speed, squeegee pressure, and table speed of the SP machine. The result shows that the most significant parameter for the solder volume is squeegee pressure (2.0 mm), and the solder height is the table speed of the SP machine (2.5 mm/s).

Reliability Study of Solder Paste Alloy for the Improvement of Solder Joint at Surface Mount Fine-Pitch Components

PubMed Central

Rahman, Mohd Nizam Ab.; Zubir, Noor Suhana Mohd; Leuveano, Raden Achmad Chairdino; Ghani, Jaharah A.; Mahmood, Wan Mohd Faizal Wan

2014-01-01

The significant increase in metal costs has forced the electronics industry to provide new materials and methods to reduce costs, while maintaining customers’ high-quality expectations. This paper considers the problem of most electronic industries in reducing costly materials, by introducing a solder paste with alloy composition tin 98.3%, silver 0.3%, and copper 0.7%, used for the construction of the surface mount fine-pitch component on a Printing Wiring Board (PWB). The reliability of the solder joint between electronic components and PWB is evaluated through the dynamic characteristic test, thermal shock test, and Taguchi method after the printing process. After experimenting with the dynamic characteristic test and thermal shock test with 20 boards, the solder paste was still able to provide a high-quality solder joint. In particular, the Taguchi method is used to determine the optimal control parameters and noise factors of the Solder Printer (SP) machine, that affects solder volume and solder height. The control parameters include table separation distance, squeegee speed, squeegee pressure, and table speed of the SP machine. The result shows that the most significant parameter for the solder volume is squeegee pressure (2.0 mm), and the solder height is the table speed of the SP machine (2.5 mm/s). PMID:28788270

An automated method for identifying artifact in independent component analysis of resting-state FMRI.

PubMed

Bhaganagarapu, Kaushik; Jackson, Graeme D; Abbott, David F

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.

Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

NASA Astrophysics Data System (ADS)

Schelkanova, Irina; Toronov, Vladislav

2011-07-01

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

Flight set 360L007 (STS-33R) field joint protection system, thermal protection system, and systems tunnel components, volume 7

NASA Technical Reports Server (NTRS)

1990-01-01

The performance of the thermal protection system, field joint protection system, and systems tunnel components of flight set 360L007 is presented as evaluated by postflight hardware inspection. The condition of both motors was similar to previous flights. Four aft edge strikes were noted on the ground environment instrumentation thermal protection system. The hits all left a clean substrate, indicating that the damage was caused by nozzle severance debris and/or water impact. No National Space Transportation System debris criteria for missing thermal protection system were violated. Two problem reports were written against the field joint protection system. The first concerned two cracks in the K5NA closeout over the trunnion/vent valve location on the left-hand aft field joint. A similar condition was observed on Flight 5 (360H005). The second problem report referred to a number of small surface cracks between two impact marks on the left-hand forward field joint. Neither area exhibited loose material or any abnormal heat effects, and they have no impact on flight safety.

Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals

NASA Astrophysics Data System (ADS)

Tian, Siyuan; Tregoning, Paul; Renzullo, Luigi J.; van Dijk, Albert I. J. M.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.; Allgeyer, Sébastien

2017-03-01

The accuracy of global water balance estimates is limited by the lack of observations at large scale and the uncertainties of model simulations. Global retrievals of terrestrial water storage (TWS) change and soil moisture (SM) from satellites provide an opportunity to improve model estimates through data assimilation. However, combining these two data sets is challenging due to the disparity in temporal and spatial resolution at both vertical and horizontal scale. For the first time, TWS observations from the Gravity Recovery and Climate Experiment (GRACE) and near-surface SM observations from the Soil Moisture and Ocean Salinity (SMOS) were jointly assimilated into a water balance model using the Ensemble Kalman Smoother from January 2010 to December 2013 for the Australian continent. The performance of joint assimilation was assessed against open-loop model simulations and the assimilation of either GRACE TWS anomalies or SMOS SM alone. The SMOS-only assimilation improved SM estimates but reduced the accuracy of groundwater and TWS estimates. The GRACE-only assimilation improved groundwater estimates but did not always produce accurate estimates of SM. The joint assimilation typically led to more accurate water storage profile estimates with improved surface SM, root-zone SM, and groundwater estimates against in situ observations. The assimilation successfully downscaled GRACE-derived integrated water storage horizontally and vertically into individual water stores at the same spatial scale as the model and SMOS, and partitioned monthly averaged TWS into daily estimates. These results demonstrate that satellite TWS and SM measurements can be jointly assimilated to produce improved water balance component estimates.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

PubMed

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2016-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

Automatic Identification of Artifact-related Independent Components for Artifact Removal in EEG Recordings

PubMed Central

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2017-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from Independent Component Analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event related potential (ERP)-related independent components (ICs). However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g. identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by non-biological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature based clustering algorithm used to identify artifacts which have physiological origins and 2) the electrode-scalp impedance information employed for identifying non-biological artifacts. The results on EEG data collected from 10 subjects show that our algorithm can effectively detect, separate, and remove both physiological and non-biological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods. PMID:25415992

RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Gholian, Armen; Bradley, Damon C.; Wong, Mark; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.

2016-01-01

Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Independent events in elementary probability theory

NASA Astrophysics Data System (ADS)

Csenki, Attila

2011-07-01

In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): If the n events E 1, E 2, … , E n are jointly independent then any two events A and B built in finitely many steps from two disjoint subsets of E 1, E 2, … , E n are also independent. The operations 'union', 'intersection' and 'complementation' are permitted only when forming the events A and B. Here we examine this statement from the point of view of elementary probability theory. The approach described here is accessible also to users of probability theory and is believed to be novel.

Joint Command and Control of Cyber Operations: The Joint Force Cyber Component Command (JFCCC)

DTIC Science & Technology

2012-05-04

relies so heavily on complex command and control systems and interconnectivity in general, cyber warfare has become a serious topic of interest at the...defensive cyber warfare into current and future operations and plans. In particular, Joint Task Force (JTF) Commanders must develop an optimum method to

Comparison of soft tissue balancing, femoral component rotation, and joint line change between the gap balancing and measured resection techniques in primary total knee arthroplasty

PubMed Central

Moon, Young-Wan; Kim, Hyun-Jung; Ahn, Hyeong-Sik; Park, Chan-Deok; Lee, Dae-Hee

2016-01-01

Abstract Background: This meta-analysis was designed to compare the accuracy of soft tissue balancing and femoral component rotation as well as change in joint line positions, between the measured resection and gap balancing techniques in primary total knee arthroplasty. Methods: Studies were included in the meta-analysis if they compared soft tissue balancing and/or radiologic outcomes in patients who underwent total knee arthroplasty with the gap balancing and measured resection techniques. Comparisons included differences in flexion/extension, medial/lateral flexion, and medial/lateral extension gaps (LEGs), femoral component rotation, and change in joint line positions. Finally, 8 studies identified via electronic (MEDLINE, EMBASE, and the Cochrane Library) and manual searches were included. All 8 studies showed a low risk of selection bias and provided detailed demographic data. There was some inherent heterogeneity due to uncontrolled bias, because all included studies were observational comparison studies. Results: The pooled mean difference in gap differences between the gap balancing and measured resection techniques did not differ significantly (−0.09 mm, 95% confidence interval [CI]: −0.40 to +0.21 mm; P = 0.55), except that the medial/LEG difference was 0.58 mm greater for measured resection than gap balancing (95% CI: −1.01 to −0.15 mm; P = 0.008). Conversely, the pooled mean difference in femoral component external rotation (0.77°, 95% CI: 0.18° to 1.35°; P = 0.01) and joint line change (1.17 mm, 95% CI: 0.82 to 1.52 mm; P < 0.001) were significantly greater for the gap balancing than the measured resection technique. Conclusion: The gap balancing and measured resection techniques showed similar soft tissue balancing, except for medial/LEG difference. However, the femoral component was more externally rotated and the joint line was more elevated with gap balancing than measured resection. These differences were minimal

Independent component processes underlying emotions during natural music listening

PubMed Central

Zollinger, Nina; Elmer, Stefan; Jäncke, Lutz

2016-01-01

The aim of this study was to investigate the brain processes underlying emotions during natural music listening. To address this, we recorded high-density electroencephalography (EEG) from 22 subjects while presenting a set of individually matched whole musical excerpts varying in valence and arousal. Independent component analysis was applied to decompose the EEG data into functionally distinct brain processes. A k-means cluster analysis calculated on the basis of a combination of spatial (scalp topography and dipole location mapped onto the Montreal Neurological Institute brain template) and functional (spectra) characteristics revealed 10 clusters referring to brain areas typically involved in music and emotion processing, namely in the proximity of thalamic-limbic and orbitofrontal regions as well as at frontal, fronto-parietal, parietal, parieto-occipital, temporo-occipital and occipital areas. This analysis revealed that arousal was associated with a suppression of power in the alpha frequency range. On the other hand, valence was associated with an increase in theta frequency power in response to excerpts inducing happiness compared to sadness. These findings are partly compatible with the model proposed by Heller, arguing that the frontal lobe is involved in modulating valenced experiences (the left frontal hemisphere for positive emotions) whereas the right parieto-temporal region contributes to the emotional arousal. PMID:27217116

Metabolic syndrome: An independent risk factor for erectile dysfunction.

PubMed

Sanjay, Saran; Bharti, Gupta Sona; Manish, Gutch; Rajeev, Philip; Pankaj, Agrawal; Puspalata, Agroiya; Keshavkumar, Gupta

2015-01-01

The objective was to determine the role of various components of metabolic syndrome (MetS) as independent risk factor for erectile dysfunction (ED). A total of 113 subjects of MetS, as recommended by recent IDF and AHA/NHLBI joint interim statement were selected for study who presented for ED. After doing Anthropometric examination, fasting laboratory assay for fasting plasma glucose (FPG), fasting insulin, hemoglobin A1c, triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and 2 h oral glucose tolerance test (OGTT) was done. Erectile function was assessed by completing questions one through five of the International Index of Erectile Function (IIEF-5). A multiple linear regression analysis was carried out on 66 subjects with IIEF-5 score as dependent variable and components of MetS FPG, 2 h OGTT, TG, HDL, and waist circumference as independent variables. Using a multiple linear regression analysis, we observed that presence of the various components of MetS was associated with ED and a decrease IIEF-5 score and this effect was greater than the effect associated with any of the individual components. Of the individual components of the MetS, HDL (B = 0.136; P = 0.004) and FPG (B = -0.069; P = 0.007) conferred the strongest effect on IIEF-5 score. However, overall age had most significant effect on IIEF-5 score. It is crucial to formulate strategies and implement them to prevent or control the epidemic of the MetS and its consequences. The early identification and treatment of risk factors might be helpful to prevent ED and secondary cardiovascular disease, including diet and lifestyle interventions.

Structural analysis of Aircraft fuselage splice joint

NASA Astrophysics Data System (ADS)

Udaya Prakash, R.; Kumar, G. Raj; Vijayanandh, R.; Senthil Kumar, M.; Ramganesh, T.

2016-09-01

In Aviation sector, composite materials and its application to each component are one of the prime factors of consideration due to the high strength to weight ratio, design flexibility and non-corrosive so that the composite materials are widely used in the low weight constructions and also it can be treated as a suitable alternative to metals. The objective of this paper is to estimate and compare the suitability of a composite skin joint in an aircraft fuselage with different joints by simulating the displacement, normal stress, vonmises stress and shear stress with the help of numerical solution methods. The reference Z-stringer component of this paper is modeled by CATIA and numerical simulation is carried out by ANSYS has been used for splice joint presents in the aircraft fuselage with three combinations of joints such as riveted joint, bonded joint and hybrid joint. Nowadays the stringers are using to avoid buckling of fuselage skin, it has joined together by rivets and they are connected end to end by splice joint. Design and static analysis of three-dimensional models of joints such as bonded, riveted and hybrid are carried out and results are compared.

Label-free observation of tissues by high-speed stimulated Raman spectral microscopy and independent component analysis

NASA Astrophysics Data System (ADS)

Ozeki, Yasuyuki; Otsuka, Yoichi; Sato, Shuya; Hashimoto, Hiroyuki; Umemura, Wataru; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi

2013-02-01

We have developed a video-rate stimulated Raman scattering (SRS) microscope with frame-by-frame wavenumber tunability. The system uses a 76-MHz picosecond Ti:sapphire laser and a subharmonically synchronized, 38-MHz Yb fiber laser. The Yb fiber laser pulses are spectrally sliced by a fast wavelength-tunable filter, which consists of a galvanometer scanner, a 4-f optical system and a reflective grating. The spectral resolution of the filter is ~ 3 cm-1. The wavenumber was scanned from 2800 to 3100 cm-1 with an arbitrary waveform synchronized to the frame trigger. For imaging, we introduced a 8-kHz resonant scanner and a galvanometer scanner. We were able to acquire SRS images of 500 x 480 pixels at a frame rate of 30.8 frames/s. Then these images were processed by principal component analysis followed by a modified algorithm of independent component analysis. This algorithm allows blind separation of constituents with overlapping Raman bands from SRS spectral images. The independent component (IC) spectra give spectroscopic information, and IC images can be used to produce pseudo-color images. We demonstrate various label-free imaging modalities such as 2D spectral imaging of the rat liver, two-color 3D imaging of a vessel in the rat liver, and spectral imaging of several sections of intestinal villi in the mouse. Various structures in the tissues such as lipid droplets, cytoplasm, fibrous texture, nucleus, and water-rich region were successfully visualized.

Joint source based morphometry identifies linked gray and white matter group differences.

PubMed

Xu, Lai; Pearlson, Godfrey; Calhoun, Vince D

2009-02-01

We present a multivariate approach called joint source based morphometry (jSBM), to identify linked gray and white matter regions which differ between groups. In jSBM, joint independent component analysis (jICA) is used to decompose preprocessed gray and white matter images into joint sources and statistical analysis is used to determine the significant joint sources showing group differences and their relationship to other variables of interest (e.g. age or sex). The identified joint sources are groupings of linked gray and white matter regions with common covariation among subjects. In this study, we first provide a simulation to validate the jSBM approach. To illustrate our method on real data, jSBM is then applied to structural magnetic resonance imaging (sMRI) data obtained from 120 chronic schizophrenia patients and 120 healthy controls to identify group differences. JSBM identified four joint sources as significantly associated with schizophrenia. Linked gray-white matter regions identified in each of the joint sources included: 1) temporal--corpus callosum, 2) occipital/frontal--inferior fronto-occipital fasciculus, 3) frontal/parietal/occipital/temporal--superior longitudinal fasciculus and 4) parietal/frontal--thalamus. Age effects on all four joint sources were significant, but sex effects were significant only for the third joint source. Our findings demonstrate that jSBM can exploit the natural linkage between gray and white matter by incorporating them into a unified framework. This approach is applicable to a wide variety of problems to study linked gray and white matter group differences.

Joint source based morphometry identifies linked gray and white matter group differences

PubMed Central

Xu, Lai; Pearlson, Godfrey; Calhoun, Vince D.

2009-01-01

We present a multivariate approach called joint source based morphometry (jSBM), to identify linked gray and white matter regions which differ between groups. In jSBM, joint independent component analysis (jICA) is used to decompose preprocessed gray and white matter images into joint sources and statistical analysis is used to determine the significant joint sources showing group differences and their relationship to other variables of interest (e.g. age or sex). The identified joint sources are groupings of linked gray and white matter regions with common covariation among subjects. In this study, we first provide a simulation to validate the jSBM approach. To illustrate our method on real data, jSBM is then applied to structural magnetic resonance imaging (sMRI) data obtained from 120 chronic schizophrenia patients and 120 healthy controls to identify group differences. JSBM identified four joint sources as significantly associated with schizophrenia. Linked gray–white matter regions identified in each of the joint sources included: 1) temporal — corpus callosum, 2) occipital/frontal — inferior fronto-occipital fasciculus, 3) frontal/parietal/occipital/temporal —superior longitudinal fasciculus and 4) parietal/frontal — thalamus. Age effects on all four joint sources were significant, but sex effects were significant only for the third joint source. Our findings demonstrate that jSBM can exploit the natural linkage between gray and white matter by incorporating them into a unified framework. This approach is applicable to a wide variety of problems to study linked gray and white matter group differences. PMID:18992825

Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

NASA Technical Reports Server (NTRS)

Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

2016-01-01

Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Gravity Tides Extracted from Relative Gravimeter Data by Combining Empirical Mode Decomposition and Independent Component Analysis

NASA Astrophysics Data System (ADS)

Yu, Hongjuan; Guo, Jinyun; Kong, Qiaoli; Chen, Xiaodong

2018-04-01

The static observation data from a relative gravimeter contain noise and signals such as gravity tides. This paper focuses on the extraction of the gravity tides from the static relative gravimeter data for the first time applying the combined method of empirical mode decomposition (EMD) and independent component analysis (ICA), called the EMD-ICA method. The experimental results from the CG-5 gravimeter (SCINTREX Limited Ontario Canada) data show that the gravity tides time series derived by EMD-ICA are consistent with the theoretical reference (Longman formula) and the RMS of their differences only reaches 4.4 μGal. The time series of the gravity tides derived by EMD-ICA have a strong correlation with the theoretical time series and the correlation coefficient is greater than 0.997. The accuracy of the gravity tides estimated by EMD-ICA is comparable to the theoretical model and is slightly higher than that of independent component analysis (ICA). EMD-ICA could overcome the limitation of ICA having to process multiple observations and slightly improve the extraction accuracy and reliability of gravity tides from relative gravimeter data compared to that estimated with ICA.

Detection of explosives on the surface of banknotes by Raman hyperspectral imaging and independent component analysis.

PubMed

Almeida, Mariana R; Correa, Deleon N; Zacca, Jorge J; Logrado, Lucio Paulo Lima; Poppi, Ronei J

2015-02-20

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50 μg cm(-2). Copyright © 2014 Elsevier B.V. All rights reserved.

Histological fate of abdominal dermis-fat grafts implanted in the temporomandibular joint of the rabbit following condylectomy.

PubMed

Dimitroulis, G; Slavin, J; Morrison, W

2011-02-01

The histological fate of abdominal dermis-fat grafts implanted into the temporomandibular joint (TMJ) following condylectomy was studied. 21 rabbits underwent left TMJ discectomies and condylectomies; 6 were controls (Group A; no graft used); 15 (Group B) had autogenous abdominal grafts transplanted into the left TMJ. Animals were killed after 4, 12 and 20 weeks. Specimens of the TMJ were histologically and histomorphometrically evaluated. At 4 weeks, fat necrosis was clear in all specimens. The dermis component survived and formed cysts with no necrosis. By 12 weeks, viable fat deposits appeared with no evidence of necrotic fat. At 20 weeks, large amounts of viable fat were present in Group B specimens. Group A had no fat, although the missing condyles regenerated. In the presence of viable fat, Group B showed little condyle regeneration 20 weeks after condylectomy. Non-vascularised fat grafts do not survive transplantation, but stimulate neoadipogenesis. The fate of the dermis component of the graft is independent of the fat component. Fat in the joint space disrupts the regeneration of a new condylar head. Neoadipogensis inhibits growth of new bone and cartilage. This has clinical implications for TMJ ankylosis management and preventing heterotopic bone formation around prosthetic joints. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Modeling Progressive Failure of Bonded Joints Using a Single Joint Finite Element

NASA Technical Reports Server (NTRS)

Stapleton, Scott E.; Waas, Anthony M.; Bednarcyk, Brett A.

2010-01-01

Enhanced finite elements are elements with an embedded analytical solution which can capture detailed local fields, enabling more efficient, mesh-independent finite element analysis. In the present study, an enhanced finite element is applied to generate a general framework capable of modeling an array of joint types. The joint field equations are derived using the principle of minimum potential energy, and the resulting solutions for the displacement fields are used to generate shape functions and a stiffness matrix for a single joint finite element. This single finite element thus captures the detailed stress and strain fields within the bonded joint, but it can function within a broader structural finite element model. The costs associated with a fine mesh of the joint can thus be avoided while still obtaining a detailed solution for the joint. Additionally, the capability to model non-linear adhesive constitutive behavior has been included within the method, and progressive failure of the adhesive can be modeled by using a strain-based failure criteria and re-sizing the joint as the adhesive fails. Results of the model compare favorably with experimental and finite element results.

The independent effects of speed and propulsive force on joint power generation in walking

PubMed Central

Browne, Michael G.; Franz, Jason R.

2017-01-01

Walking speed is modulated using propulsive forces (FP) during push-off and both preferred speed and FP decrease with aging. However, even prior to walking slower, reduced FP may be accompanied by potentially unfavorable changes in joint power generation. For example, compared to young adults, older adults exhibit a redistribution of mechanical power generation from the propulsive plantarflexor muscles to more proximal muscles acting across the knee and hip. Here, we used visual biofeedback based on real-time FP measurements to decouple and investigate the interaction between joint-level coordination, whole-body FP, and walking speed. 12 healthy young subjects walked on a dual-belt instrumented treadmill at a range of speeds (0.9 – 1.3 m/s). We immediately calculated the average FP from each speed. Subjects then walked at 1.3 m/s while completing a series of biofeedback trials with instructions to match their instantaneous FP to their averaged FP from slower speeds. Walking slower decreased FP and total positive joint work with little effect on relative joint-level contributions. Conversely, subjects walked at a constant speed with reduced FP, not by reducing total positive joint work, but by redistributing the mechanical demands of each step from the plantarflexor muscles during push-off to more proximal leg muscles during single support. Interestingly, these naturally emergent joint- and limb-level biomechanical changes, in the absence of neuromuscular constraints, resemble those due to aging. Our findings provide important reference data to understand the presumably complex interactions between joint power generation, whole-body FP, and walking speed in our aging population. PMID:28262285

21 CFR 888.3510 - Knee joint femorotibial metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2012 CFR

2012-04-01

...-and-socket joint located between a stemmed femoral and a stemmed tibial component and a runner and track joint between each pair of femoral and tibial condyles. The ball-and-socket joint is composed of a...-molybdenum. The ball of the tibial component is held within the socket of the femoral component by the...

21 CFR 888.3510 - Knee joint femorotibial metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2011 CFR

2011-04-01

...-and-socket joint located between a stemmed femoral and a stemmed tibial component and a runner and track joint between each pair of femoral and tibial condyles. The ball-and-socket joint is composed of a...-molybdenum. The ball of the tibial component is held within the socket of the femoral component by the...

21 CFR 888.3510 - Knee joint femorotibial metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2013 CFR

2013-04-01

...-and-socket joint located between a stemmed femoral and a stemmed tibial component and a runner and track joint between each pair of femoral and tibial condyles. The ball-and-socket joint is composed of a...-molybdenum. The ball of the tibial component is held within the socket of the femoral component by the...

21 CFR 888.3510 - Knee joint femorotibial metal/polymer constrained cemented prosthesis.

Code of Federal Regulations, 2014 CFR

2014-04-01

...-and-socket joint located between a stemmed femoral and a stemmed tibial component and a runner and track joint between each pair of femoral and tibial condyles. The ball-and-socket joint is composed of a...-molybdenum. The ball of the tibial component is held within the socket of the femoral component by the...

Independent and joint associations of physical activity and fitness with fibromyalgia symptoms and severity: The al-Ándalus project.

PubMed

Segura-Jiménez, Víctor; Soriano-Maldonado, Alberto; Estévez-López, Fernando; Álvarez-Gallardo, Inmaculada C; Delgado-Fernández, Manuel; Ruiz, Jonatan R; Aparicio, Virginia A

2017-08-01

We examined independent and joint associations of objectively measured physical activity (PA) and physical fitness (PF) with pain, fatigue and the overall impact of fibromyalgia in 386 fibromyalgia women aged 51.2 ± 7.6 years. Levels of PA (light, moderate and vigorous) and PF were measured with triaxial accelerometry and the Senior Fitness Test, respectively. We used the Short-Form health survey-36 pain sub-scale and the Multidimensional Fatigue Inventory to assess pain and multiple dimensions of fatigue, respectively. The impact of fibromyalgia was studied with the Revised Fibromyalgia Impact Questionnaire (FIQR). Both, total PA and global PF were independently associated with pain pressure threshold, SF-36 pain, reduced activity, reduced motivation and FIQR total score (all, P ≤ 0.027). The associations between total PA and symptoms were weaker than those observed between global PF and symptoms. Overall, unfit patients with low PA showed a worse profile that fit patients with high PA (all, P ≤ 0.001). In summary, PA and PF are independently associated with pain, fatigue and the overall impact of fibromyalgia in women. Although PF presented greater associations with symptoms, the results suggest that both being physically active and keep adequate fitness levels might be convenient for fibromyalgia women.

Time course based artifact identification for independent components of resting-state FMRI.

PubMed

Rummel, Christian; Verma, Rajeev Kumar; Schöpf, Veronika; Abela, Eugenio; Hauf, Martinus; Berruecos, José Fernando Zapata; Wiest, Roland

2013-01-01

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Strategies for reducing large fMRI data sets for independent component analysis.

PubMed

Wang, Ze; Wang, Jiongjiong; Calhoun, Vince; Rao, Hengyi; Detre, John A; Childress, Anna R

2006-06-01

In independent component analysis (ICA), principal component analysis (PCA) is generally used to reduce the raw data to a few principal components (PCs) through eigenvector decomposition (EVD) on the data covariance matrix. Although this works for spatial ICA (sICA) on moderately sized fMRI data, it is intractable for temporal ICA (tICA), since typical fMRI data have a high spatial dimension, resulting in an unmanageable data covariance matrix. To solve this problem, two practical data reduction methods are presented in this paper. The first solution is to calculate the PCs of tICA from the PCs of sICA. This approach works well for moderately sized fMRI data; however, it is highly computationally intensive, even intractable, when the number of scans increases. The second solution proposed is to perform PCA decomposition via a cascade recursive least squared (CRLS) network, which provides a uniform data reduction solution for both sICA and tICA. Without the need to calculate the covariance matrix, CRLS extracts PCs directly from the raw data, and the PC extraction can be terminated after computing an arbitrary number of PCs without the need to estimate the whole set of PCs. Moreover, when the whole data set becomes too large to be loaded into the machine memory, CRLS-PCA can save data retrieval time by reading the data once, while the conventional PCA requires numerous data retrieval steps for both covariance matrix calculation and PC extractions. Real fMRI data were used to evaluate the PC extraction precision, computational expense, and memory usage of the presented methods.

Joint Laxity in Preschool Children Born Preterm.

PubMed

Romeo, Domenico M; Velli, Chiara; Lucibello, Simona; Ferrantini, Gloria; Leo, Giuseppina; Brogna, Claudia; Cota, Francesco; Ricci, Daniela; Gallini, Francesca; Romagnoli, Costantino; Vento, Giovanni; Mercuri, Eugenio

2018-06-01

To evaluate the prevalence of joint laxity in children born preterm assessed in the first 2 years, the relationship between joint laxity and motor performance at preschool age, and possible changes over time in a subgroup of children followed longitudinally. The revised scale of Beighton Score was used to evaluate joint laxity in a population of 132 preschool children born preterm between 24 and 32 weeks of gestational age. All were assessed for joint laxity between 12 and 24 months of age. Children also performed the Movement Assessment Battery for Children-Second Edition between the age of 3 years and 6 months and 4 years; the age at onset of independent walking also was recorded. The total Beighton Score ranged between 0 and 8. Twenty percent of the cohort showed joint laxity. No differences related to sex or gestational age were observed. Children born preterm with joint laxity achieved later independent walking and achieved lower scores on Movement Assessment Battery for Children-Second Edition than those without joint laxity. In 76 children born preterm, an assessment for joint laxity was repeated once between 25 and 36 months and again after >36 months. No statistically significant difference was observed between the 3 assessments. The Beighton Score can be used to assess generalized joint laxity in children born preterm. As the presence of joint laxity influenced motor competences, the possibility to early identify these infants in the first 2 years is of interest to benefit from early intervention and potentially improve gross motor skills and coordination. Copyright © 2018 Elsevier Inc. All rights reserved.

Autoantibodies to citrullinated proteins induce joint pain independent of inflammation via a chemokine-dependent mechanism

PubMed Central

Wigerblad, Gustaf; Bas, Duygu B; Fernades-Cerqueira, Cátia; Krishnamurthy, Akilan; Rogoz, Katarzyna; Kato, Jungo; Sandor, Katalin; Su, Jie; Jimenez–Andrade, Juan Miguel; Finn, Anja; Bersellini Farinotti, Alex; Amara, Khaled; Lundberg, Karin; Holmdahl, Rikard; Jakobsson, Per-Johan; Malmström, Vivianne; Catrina, Anca I; Klareskog, Lars; Svensson, Camilla I

2016-01-01

Objective An interesting and so far unexplained feature of chronic pain in autoimmune disease is the frequent disconnect between pain and inflammation. This is illustrated well in rheumatoid arthritis (RA) where pain in joints (arthralgia) may precede joint inflammation and persist even after successful anti-inflammatory treatment. In the present study, we have addressed the possibility that autoantibodies against citrullinated proteins (ACPA), present in RA, may be directly responsible for the induction of pain, independent of inflammation. Methods Antibodies purified from human patients with RA, healthy donors and murinised monoclonal ACPA were injected into mice. Pain-like behaviour was monitored for up to 28 days, and tissues were analysed for signs of pathology. Mouse osteoclasts were cultured and stimulated with antibodies, and supernatants analysed for release of factors. Mice were treated with CXCR1/2 (interleukin (IL) 8 receptor) antagonist reparixin. Results Mice injected with either human or murinised ACPA developed long-lasting pronounced pain-like behaviour in the absence of inflammation, while non-ACPA IgG from patients with RA or control monoclonal IgG were without pronociceptive effect. This effect was coupled to ACPA-mediated activation of osteoclasts and release of the nociceptive chemokine CXCL1 (analogue to human IL-8). ACPA-induced pain-like behaviour was reversed with reparixin. Conclusions The data suggest that CXCL1/IL-8, released from osteoclasts in an autoantibody-dependent manner, produces pain by activating sensory neurons. The identification of this new pain pathway may open new avenues for pain treatment in RA and also in other painful diseases associated with autoantibody production and/or osteoclast activation. PMID:26613766

Spatiotemporal analysis of single-trial EEG of emotional pictures based on independent component analysis and source location

NASA Astrophysics Data System (ADS)

Liu, Jiangang; Tian, Jie

2007-03-01

The present study combined the Independent Component Analysis (ICA) and low-resolution brain electromagnetic tomography (LORETA) algorithms to identify the spatial distribution and time course of single-trial EEG record differences between neural responses to emotional stimuli vs. the neutral. Single-trial multichannel (129-sensor) EEG records were collected from 21 healthy, right-handed subjects viewing the emotion emotional (pleasant/unpleasant) and neutral pictures selected from International Affective Picture System (IAPS). For each subject, the single-trial EEG records of each emotional pictures were concatenated with the neutral, and a three-step analysis was applied to each of them in the same way. First, the ICA was performed to decompose each concatenated single-trial EEG records into temporally independent and spatially fixed components, namely independent components (ICs). The IC associated with artifacts were isolated. Second, the clustering analysis classified, across subjects, the temporally and spatially similar ICs into the same clusters, in which nonparametric permutation test for Global Field Power (GFP) of IC projection scalp maps identified significantly different temporal segments of each emotional condition vs. neutral. Third, the brain regions accounted for those significant segments were localized spatially with LORETA analysis. In each cluster, a voxel-by-voxel randomization test identified significantly different brain regions between each emotional condition vs. the neutral. Compared to the neutral, both emotional pictures elicited activation in the visual, temporal, ventromedial and dorsomedial prefrontal cortex and anterior cingulated gyrus. In addition, the pleasant pictures activated the left middle prefrontal cortex and the posterior precuneus, while the unpleasant pictures activated the right orbitofrontal cortex, posterior cingulated gyrus and somatosensory region. Our results were well consistent with other functional imaging

An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

PubMed Central

Bhaganagarapu, Kaushik; Jackson, Graeme D.; Abbott, David F.

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available. PMID:23847511

Three-dimensional localization and optical imaging of objects in turbid media with independent component analysis.

PubMed

Xu, M; Alrubaiee, M; Gayen, S K; Alfano, R R

2005-04-01

A new approach for optical imaging and localization of objects in turbid media that makes use of the independent component analysis (ICA) from information theory is demonstrated. Experimental arrangement realizes a multisource illumination of a turbid medium with embedded objects and a multidetector acquisition of transmitted light on the medium boundary. The resulting spatial diversity and multiple angular observations provide robust data for three-dimensional localization and characterization of absorbing and scattering inhomogeneities embedded in a turbid medium. ICA of the perturbations in the spatial intensity distribution on the medium boundary sorts out the embedded objects, and their locations are obtained from Green's function analysis based on any appropriate light propagation model. Imaging experiments were carried out on two highly scattering samples of thickness approximately 50 times the transport mean-free path of the respective medium. One turbid medium had two embedded absorptive objects, and the other had four scattering objects. An independent component separation of the signal, in conjunction with diffusive photon migration theory, was used to locate the embedded inhomogeneities. In both cases, improved lateral and axial localizations of the objects over the result obtained by use of common photon migration reconstruction algorithms were achieved. The approach is applicable to different medium geometries, can be used with any suitable photon propagation model, and is amenable to near-real-time imaging applications.

Identification of faulty sensor using relative partial decomposition via independent component analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Quek, S. T.

2015-07-01

Performance of any structural health monitoring algorithm relies heavily on good measurement data. Hence, it is necessary to employ robust faulty sensor detection approaches to isolate sensors with abnormal behaviour and exclude the highly inaccurate data in the subsequent analysis. The independent component analysis (ICA) is implemented to detect the presence of sensors showing abnormal behaviour. A normalized form of the relative partial decomposition contribution (rPDC) is proposed to identify the faulty sensor. Both additive and multiplicative types of faults are addressed and the detectability illustrated using a numerical and an experimental example. An empirical method to establish control limits for detecting and identifying the type of fault is also proposed. The results show the effectiveness of the ICA and rPDC method in identifying faulty sensor assuming that baseline cases are available.

The independent effects of speed and propulsive force on joint power generation in walking.

PubMed

Browne, Michael G; Franz, Jason R

2017-04-11

Walking speed is modulated using propulsive forces (F P ) during push-off and both preferred speed and F P decrease with aging. However, even prior to walking slower, reduced F P may be accompanied by potentially unfavorable changes in joint power generation. For example, compared to young adults, older adults exhibit a redistribution of mechanical power generation from the propulsive plantarflexor muscles to more proximal muscles acting across the knee and hip. Here, we used visual biofeedback based on real-time F P measurements to decouple and investigate the interaction between joint-level coordination, whole-body F P , and walking speed. 12 healthy young subjects walked on a dual-belt instrumented treadmill at a range of speeds (0.9-1.3m/s). We immediately calculated the average F P from each speed. Subjects then walked at 1.3m/s while completing a series of biofeedback trials with instructions to match their instantaneous F P to their averaged F P from slower speeds. Walking slower decreased F P and total positive joint work with little effect on relative joint-level contributions. Conversely, subjects walked at a constant speed with reduced F P , not by reducing total positive joint work, but by redistributing the mechanical demands of each step from the plantarflexor muscles during push-off to more proximal leg muscles during single support. Interestingly, these naturally emergent joint- and limb-level biomechanical changes, in the absence of neuromuscular constraints, resemble those due to aging. Our findings provide important reference data to understand the presumably complex interactions between joint power generation, whole-body F P , and walking speed in our aging population. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlation of the Features of the Lumbar Multifidus Muscle With Facet Joint Osteoarthritis.

PubMed

Yu, Bo; Jiang, Kaibiao; Li, Xinfeng; Zhang, Jidong; Liu, Zude

2017-09-01

Facet joint osteoarthritis is considered a consequence of the aging process; however, there is evidence that it may be associated with degenerative changes of other structures. The goal of this study was to investigate the correlation between lumbar multifidus muscle features and facet joint osteoarthritis. This retrospective study included 160 patients who had acute or chronic low back pain and were diagnosed with facet joint osteoarthritis on computed tomography scan. Morphometric parameters, including cross-sectional area, muscle-fat index, and percentage of bilateral multifidus asymmetry at L3-L4, L4-L5, and L5-S1, were evaluated with T2-weighted magnetic resonance imaging. Patients with facet joint osteoarthritis had a smaller cross-sectional area and a higher muscle-fat index than those without facet joint osteoarthritis (P<.001). In multivariate regression analysis, older age and higher muscle-fat index were independently associated with facet joint osteoarthritis at all 3 spinal levels (P<.001). Smaller cross-sectional area was independently associated with facet joint osteoarthritis only at L4-L5 (P=.005). Asymmetry of the bilateral multifidus cross-sectional area was independently associated with facet joint osteoarthritis at L5-S1 (P=.009), but did not seem to be responsible for asymmetric degeneration of the bilateral facet joints. A higher multifidus muscle-fat index was independently associated with facet joint osteoarthritis, and bilateral multifidus size asymmetry was associated with the development of facet joint osteoarthritis at L5-S1. It seems more accurate to consider facet joint osteoarthritis a failure of the whole joint structure, including the paraspinal musculature, rather than simply a failure of the facet joint cartilage. [Orthopedics. 2017; 40(5):e793-e800.]. Copyright 2017, SLACK Incorporated.

Flight Set 360L006 STS-34 field joint protection system, thermal protection system, and systems tunnel components, volume 4

NASA Technical Reports Server (NTRS)

Wilkinson, J. P.

1990-01-01

The performance of the thermal protection system, field joint protection system, and systems tunnel components of Flight Set 360L006, are documented, as evaluated by postflight hardware inspection. The condition of both motors was similar to previous flights. Sixteen aft edge hits were noted on the ground environment instrumentation thermal protection system. Each hit left a clean substrate, indicating that the damage was caused by nozzle severance debris and/or water impact. No National Space and Transporation System debris criteria for missing thermal protection system were violated. One 5.0 by 1.0 in. unbond was observed on the left hand center field joint K5NA closeout and was elevated to an in-flight anomaly (STS-34-M-4) by the NASA Ice/Debris team. Aft edge damage to the K5NA and an associated black streak indicate that burning debris from the nozzle severance system was the likely cause of the damage. Minor divots caused by debris were seen on previous flights, but this is the first occurrence of a K5NA unbond. Since the unbond occurred after booster separation there is no impact on flight safety and no corrective actions was taken. The right hand center field joint primary heater failed the dielectric withstanding voltage test after joint closeout. The heater was then disabled by opening the circuit breaker, and the redundant heater was used. The redundant heater performed nominally during the launch countdown. A similar condition occurred on Flight 4 when a secondary joint heater failed the dielectric withstanding voltage test.

Independent component processes underlying emotions during natural music listening.

PubMed

Rogenmoser, Lars; Zollinger, Nina; Elmer, Stefan; Jäncke, Lutz

2016-09-01

The aim of this study was to investigate the brain processes underlying emotions during natural music listening. To address this, we recorded high-density electroencephalography (EEG) from 22 subjects while presenting a set of individually matched whole musical excerpts varying in valence and arousal. Independent component analysis was applied to decompose the EEG data into functionally distinct brain processes. A k-means cluster analysis calculated on the basis of a combination of spatial (scalp topography and dipole location mapped onto the Montreal Neurological Institute brain template) and functional (spectra) characteristics revealed 10 clusters referring to brain areas typically involved in music and emotion processing, namely in the proximity of thalamic-limbic and orbitofrontal regions as well as at frontal, fronto-parietal, parietal, parieto-occipital, temporo-occipital and occipital areas. This analysis revealed that arousal was associated with a suppression of power in the alpha frequency range. On the other hand, valence was associated with an increase in theta frequency power in response to excerpts inducing happiness compared to sadness. These findings are partly compatible with the model proposed by Heller, arguing that the frontal lobe is involved in modulating valenced experiences (the left frontal hemisphere for positive emotions) whereas the right parieto-temporal region contributes to the emotional arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Adaptive Postural Control for Joint Immobilization during Multitask Performance

PubMed Central

Hsu, Wei-Li

2014-01-01

Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21–29 yr) without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM) stability were examined using uncontrolled manifold (UCM) analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM); the second leads to COM position variability (VORT). The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM) was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT) tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements. PMID:25329477

Detection and Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of GPS Time Series

NASA Astrophysics Data System (ADS)

Gualandi, A.; Serpelloni, E.; Belardinelli, M. E.

2014-12-01

A critical point in the analysis of ground displacements time series is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies. Indeed, PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem, i.e. in recovering and separating the original sources that generated the observed data. This is mainly due to the assumptions on which PCA relies: it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here we present the application of the vbICA technique to GPS position time series. First, we use vbICA on synthetic data that simulate a seismic cycle

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

Aggregate blood pressure responses to serial dietary sodium and potassium intervention: defining responses using independent component analysis.

PubMed

Chen, Gengsheng; de las Fuentes, Lisa; Gu, Chi C; He, Jiang; Gu, Dongfeng; Kelly, Tanika; Hixson, James; Jacquish, Cashell; Rao, D C; Rice, Treva K

2015-06-20

Hypertension is a complex trait that often co-occurs with other conditions such as obesity and is affected by genetic and environmental factors. Aggregate indices such as principal components among these variables and their responses to environmental interventions may represent novel information that is potentially useful for genetic studies. In this study of families participating in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) Study, blood pressure (BP) responses to dietary sodium interventions are explored. Independent component analysis (ICA) was applied to 20 variables indexing obesity and BP measured at baseline and during low sodium, high sodium and high sodium plus potassium dietary intervention periods. A "heat map" protocol that classifies subjects based on risk for hypertension is used to interpret the extracted components. ICA and heat map suggest four components best describe the data: (1) systolic hypertension, (2) general hypertension, (3) response to sodium intervention and (4) obesity. The largest heritabilities are for the systolic (64%) and general hypertension (56%) components. There is a pattern of higher heritability for the component response to intervention (40-42%) as compared to those for the traditional intervention responses computed as delta scores (24%-40%). In summary, the present study provides intermediate phenotypes that are heritable. Using these derived components may prove useful in gene discovery applications.

Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

NASA Astrophysics Data System (ADS)

Cohen-Waeber, J.; Bürgmann, R.; Chaussard, E.; Giannico, C.; Ferretti, A.

2018-02-01

Long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. High-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

Metabolic syndrome: An independent risk factor for erectile dysfunction

PubMed Central

Sanjay, Saran; Bharti, Gupta Sona; Manish, Gutch; Rajeev, Philip; Pankaj, Agrawal; Puspalata, Agroiya; Keshavkumar, Gupta

2015-01-01

Objective: The objective was to determine the role of various components of metabolic syndrome (MetS) as independent risk factor for erectile dysfunction (ED). Materials and Methods: A total of 113 subjects of MetS, as recommended by recent IDF and AHA/NHLBI joint interim statement were selected for study who presented for ED. After doing Anthropometric examination, fasting laboratory assay for fasting plasma glucose (FPG), fasting insulin, hemoglobin A1c, triglyceride (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and 2 h oral glucose tolerance test (OGTT) was done. Erectile function was assessed by completing questions one through five of the International Index of Erectile Function (IIEF-5). A multiple linear regression analysis was carried out on 66 subjects with IIEF-5 score as dependent variable and components of MetS FPG, 2 h OGTT, TG, HDL, and waist circumference as independent variables. Results: Using a multiple linear regression analysis, we observed that presence of the various components of MetS was associated with ED and a decrease IIEF-5 score and this effect was greater than the effect associated with any of the individual components. Of the individual components of the MetS, HDL (B = 0.136; P = 0.004) and FPG (B = −0.069; P = 0.007) conferred the strongest effect on IIEF-5 score. However, overall age had most significant effect on IIEF-5 score. Conclusion: It is crucial to formulate strategies and implement them to prevent or control the epidemic of the MetS and its consequences. The early identification and treatment of risk factors might be helpful to prevent ED and secondary cardiovascular disease, including diet and lifestyle interventions. PMID:25729692

Gauge-origin independent formalism of two-component relativistic framework based on unitary transformation in nuclear magnetic shielding constant

NASA Astrophysics Data System (ADS)

Hayami, Masao; Seino, Junji; Nakai, Hiromi

2018-03-01

This article proposes a gauge-origin independent formalism of the nuclear magnetic shielding constant in the two-component relativistic framework based on the unitary transformation. The proposed scheme introduces the gauge factor and the unitary transformation into the atomic orbitals. The two-component relativistic equation is formulated by block-diagonalizing the Dirac Hamiltonian together with gauge factors. This formulation is available for arbitrary relativistic unitary transformations. Then, the infinite-order Douglas-Kroll-Hess (IODKH) transformation is applied to the present formulation. Next, the analytical derivatives of the IODKH Hamiltonian for the evaluation of the nuclear magnetic shielding constant are derived. Results obtained from the numerical assessments demonstrate that the present formulation removes the gauge-origin dependence completely. Furthermore, the formulation with the IODKH transformation gives results that are close to those in four-component and other two-component relativistic schemes.

Increasing Information Sharing Among Independent Police Departments

DTIC Science & Technology

2009-03-01

the operational level . 50 Robert Fox (Lieutenant, Los Angeles Police Department – Assigned to the Joint Regional... Angeles Police Department ( LAPD ) is the largest independent police department in Los Angeles County. The department is responsible for patrolling...agencies operating in metropolitan areas based on a quantitative analysis of the 46 independent police

[Temporo-mandibular joint. Morpho-functional considerations].

PubMed

Scutariu, M D; Indrei, Anca

2004-01-01

The temporo-mandibular joint is distinguished from most other synovial joints of the body by two features: 1. the two jointed components carry teeth whose position and occlusion introduce a very strong influence on the movements of the temporo-mandibular joint and 2. its articular surfaces are not covered by hyaline cartilage, but by a dense, fibrous tissue. This paper describes the parts of the temporo-mandibular joint: the articular surfaces (the condylar process of the mandible and the glenoid part of the temporal bone), the fibrocartilaginous disc which is interposed between the mandibular and the temporal surface, the fibrous capsule of the temporo-mandibular joint and the ligaments of this joint. All these parts present a very strong adaptation at the important functions of the temporo-mandibular joint.

Autoantibodies to citrullinated proteins induce joint pain independent of inflammation via a chemokine-dependent mechanism.

PubMed

Wigerblad, Gustaf; Bas, Duygu B; Fernades-Cerqueira, Cátia; Krishnamurthy, Akilan; Nandakumar, Kutty Selva; Rogoz, Katarzyna; Kato, Jungo; Sandor, Katalin; Su, Jie; Jimenez-Andrade, Juan Miguel; Finn, Anja; Bersellini Farinotti, Alex; Amara, Khaled; Lundberg, Karin; Holmdahl, Rikard; Jakobsson, Per-Johan; Malmström, Vivianne; Catrina, Anca I; Klareskog, Lars; Svensson, Camilla I

2016-04-01

An interesting and so far unexplained feature of chronic pain in autoimmune disease is the frequent disconnect between pain and inflammation. This is illustrated well in rheumatoid arthritis (RA) where pain in joints (arthralgia) may precede joint inflammation and persist even after successful anti-inflammatory treatment. In the present study, we have addressed the possibility that autoantibodies against citrullinated proteins (ACPA), present in RA, may be directly responsible for the induction of pain, independent of inflammation. Antibodies purified from human patients with RA, healthy donors and murinised monoclonal ACPA were injected into mice. Pain-like behaviour was monitored for up to 28 days, and tissues were analysed for signs of pathology. Mouse osteoclasts were cultured and stimulated with antibodies, and supernatants analysed for release of factors. Mice were treated with CXCR1/2 (interleukin (IL) 8 receptor) antagonist reparixin. Mice injected with either human or murinised ACPA developed long-lasting pronounced pain-like behaviour in the absence of inflammation, while non-ACPA IgG from patients with RA or control monoclonal IgG were without pronociceptive effect. This effect was coupled to ACPA-mediated activation of osteoclasts and release of the nociceptive chemokine CXCL1 (analogue to human IL-8). ACPA-induced pain-like behaviour was reversed with reparixin. The data suggest that CXCL1/IL-8, released from osteoclasts in an autoantibody-dependent manner, produces pain by activating sensory neurons. The identification of this new pain pathway may open new avenues for pain treatment in RA and also in other painful diseases associated with autoantibody production and/or osteoclast activation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Origins of mass-dependent and mass-independent Ca isotope variations in meteoritic components and meteorites

NASA Astrophysics Data System (ADS)

Bermingham, K. R.; Gussone, N.; Mezger, K.; Krause, J.

2018-04-01

The Ca isotope composition of meteorites and their components may vary due to mass-dependent and/or -independent isotope effects. In order to evaluate the origin of these effects, five amoeboid olivine aggregates (AOAs), three calcium aluminum inclusions (CAIs), five chondrules (C), a dark inclusion from Allende (CV3), two dark fragments from North West Africa 753 (NWA 753; R3.9), and a whole rock sample of Orgueil (CI1) were analyzed. This is the first coupled mass-dependent and -independent Ca isotope dataset to include AOAs, a dark inclusion, and dark fragments. Where sample masses permit, Ca isotope data are reported with corresponding petrographic analyses and rare earth element (REE) relative abundance patterns. The CAIs and AOAs are enriched in light Ca isotopes (δ44/40Ca -5.32 to +0.72, where δ44/40Ca is reported relative to SRM 915a). Samples CAI 5 and AOA 1 have anomalous Group II REE patterns. These REE and δ44/40Ca data suggest that the CAI 5 and AOA 1 compositions were set via kinetic isotope fractionation during condensation and evaporation. The remaining samples show mass-dependent Ca isotope variations which cluster between δ44/40Ca +0.53 and +1.59, some of which are coupled with unfractionated REE abundance patterns. These meteoritic components likely formed through the coaccretion of the evaporative residue and condensate following Group II CAI formation or their chemical and isotopic signatures were decoupled (e.g., via nebular or parent-body alteration). The whole rock sample of Orgueil has a δ44/40Ca +0.67 ± 0.18 which is in agreement with most published data. Parent-body alteration, terrestrial alteration, and variable sampling of Ca-rich meteoritic components can have an effect on δ44/40Ca compositions in whole rock meteorites. Samples AOA 1, CAI 5, C 2, and C 4 display mass-independent 48/44Ca anomalies (ε48/44Ca +6 to +12) which are resolved from the standard composition. Other samples measured for these effects (AOA 5, CAI 1, CAI 2

Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

NASA Astrophysics Data System (ADS)

Wen-Bo, Wang; Xiao-Dong, Zhang; Yuchan, Chang; Xiang-Li, Wang; Zhao, Wang; Xi, Chen; Lei, Zheng

2016-01-01

In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. Project supported by the National Science and Technology, China (Grant No. 2012BAJ15B04), the National Natural Science Foundation of China (Grant Nos. 41071270 and 61473213), the Natural Science Foundation of Hubei Province, China (Grant No. 2015CFB424), the State Key Laboratory Foundation of Satellite Ocean Environment Dynamics, China (Grant No. SOED1405), the Hubei Provincial Key Laboratory Foundation of Metallurgical Industry Process System Science, China (Grant No. Z201303), and the Hubei Key Laboratory Foundation of Transportation Internet of Things, Wuhan University of Technology, China (Grant No.2015III015-B02).

High Bone Mass is associated with bone-forming features of osteoarthritis in non-weight bearing joints independent of body mass index.

PubMed

Gregson, C L; Hardcastle, S A; Murphy, A; Faber, B; Fraser, W D; Williams, M; Davey Smith, G; Tobias, J H

2017-04-01

High Bone Mass (HBM) is associated with (a) radiographic knee osteoarthritis (OA), partly mediated by increased BMI, and (b) pelvic enthesophytes and hip osteophytes, suggestive of a bone-forming phenotype. We aimed to establish whether HBM is associated with radiographic features of OA in non-weight-bearing (hand) joints, and whether such OA demonstrates a bone-forming phenotype. HBM cases (BMD Z-scores≥+3.2) were compared with family controls. A blinded assessor graded all PA hand radiographs for: osteophytes (0-3), joint space narrowing (JSN) (0-3), subchondral sclerosis (0-1), at the index Distal Interphalangeal Joint (DIPJ) and 1st Carpometacarpal Joint (CMCJ), using an established atlas. Analyses used a random effects logistic regression model, adjusting a priori for age and gender. Mediating roles of BMI and bone turnover markers (BTMs) were explored by further adjustment. 314 HBM cases (mean age 61.1years, 74% female) and 183 controls (54.3years, 46% female) were included. Osteophytes (grade≥1) were more common in HBM (DIPJ: 67% vs. 45%, CMCJ: 69% vs. 50%), with adjusted OR [95% CI] 1.82 [1.11, 2.97], p=0.017 and 1.89 [1.19, 3.01], p=0.007 respectively; no differences were seen in JSN. Further adjustment for BMI failed to attenuate ORs for osteophytes in HBM cases vs. controls; DIPJ 1.72 [1.05, 2.83], p=0.032, CMCJ 1.76 [1.00, 3.06], p=0.049. Adjustment for BTMs (concentrations lower amongst HBM cases) did not attenuate ORs. HBM is positively associated with OA in non-weight-bearing joints, independent of BMI. HBM-associated OA is characterised by osteophytes, consistent with a bone-forming phenotype, rather than JSN reflecting cartilage loss. Systemic factors (e.g. genetic architecture) which govern HBM may also increase bone-forming OA risk. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

An evaluation of independent component analyses with an application to resting-state fMRI

PubMed Central

Matteson, David S.; Ruppert, David; Eloyan, Ani; Caffo, Brian S.

2013-01-01

Summary We examine differences between independent component analyses (ICAs) arising from different as-sumptions, measures of dependence, and starting points of the algorithms. ICA is a popular method with diverse applications including artifact removal in electrophysiology data, feature extraction in microarray data, and identifying brain networks in functional magnetic resonance imaging (fMRI). ICA can be viewed as a generalization of principal component analysis (PCA) that takes into account higher-order cross-correlations. Whereas the PCA solution is unique, there are many ICA methods–whose solutions may differ. Infomax, FastICA, and JADE are commonly applied to fMRI studies, with FastICA being arguably the most popular. Hastie and Tibshirani (2003) demonstrated that ProDenICA outperformed FastICA in simulations with two components. We introduce the application of ProDenICA to simulations with more components and to fMRI data. ProDenICA was more accurate in simulations, and we identified differences between biologically meaningful ICs from ProDenICA versus other methods in the fMRI analysis. ICA methods require nonconvex optimization, yet current practices do not recognize the importance of, nor adequately address sensitivity to, initial values. We found that local optima led to dramatically different estimates in both simulations and group ICA of fMRI, and we provide evidence that the global optimum from ProDenICA is the best estimate. We applied a modification of the Hungarian (Kuhn-Munkres) algorithm to match ICs from multiple estimates, thereby gaining novel insights into how brain networks vary in their sensitivity to initial values and ICA method. PMID:24350655

Sea level reconstructions from altimetry and tide gauges using independent component analysis

NASA Astrophysics Data System (ADS)

Brunnabend, Sandra-Esther; Kusche, Jürgen; Forootan, Ehsan

2017-04-01

Many reconstructions of global and regional sea level rise derived from tide gauges and satellite altimetry used the method of empirical orthogonal functions (EOF) to reduce noise, improving the spatial resolution of the reconstructed outputs and investigate the different signals in climate time series. However, the second order EOF method has some limitations, e.g. in the separation of individual physical signals into different modes of sea level variations and in the capability to physically interpret the different modes as they are assumed to be orthogonal. Therefore, we investigate the use of the more advanced statistical signal decomposition technique called independent component analysis (ICA) to reconstruct global and regional sea level change from satellite altimetry and tide gauge records. Our results indicate that the used method has almost no influence on the reconstruction of global mean sea level change (1.6 mm/yr from 1960-2010 and 2.9 mm/yr from 1993-2013). Only different numbers of modes are needed for the reconstruction. Using the ICA method is advantageous for separating independent climate variability signals from regional sea level variations as the mixing problem of the EOF method is strongly reduced. As an example, the modes most dominated by the El Niño-Southern Oscillation (ENSO) signal are compared. Regional sea level changes near Tianjin, China, Los Angeles, USA, and Majuro, Marshall Islands are reconstructed and the contributions from ENSO are identified.

Developing a Complex Independent Component Analysis (CICA) Technique to Extract Non-stationary Patterns from Geophysical Time Series

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen; Talpe, Matthieu; Shum, C. K.; Schmidt, Michael

2017-12-01

In recent decades, decomposition techniques have enabled increasingly more applications for dimension reduction, as well as extraction of additional information from geophysical time series. Traditionally, the principal component analysis (PCA)/empirical orthogonal function (EOF) method and more recently the independent component analysis (ICA) have been applied to extract, statistical orthogonal (uncorrelated), and independent modes that represent the maximum variance of time series, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the autocovariance matrix and diagonalizing higher (than two) order statistical tensors from centered time series, respectively. However, the stationarity assumption in these techniques is not justified for many geophysical and climate variables even after removing cyclic components, e.g., the commonly removed dominant seasonal cycles. In this paper, we present a novel decomposition method, the complex independent component analysis (CICA), which can be applied to extract non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA, where (a) we first define a new complex dataset that contains the observed time series in its real part, and their Hilbert transformed series as its imaginary part, (b) an ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex dataset in (a), and finally, (c) the dominant independent complex modes are extracted and used to represent the dominant space and time amplitudes and associated phase propagation patterns. The performance of CICA is examined by analyzing synthetic data constructed from multiple physically meaningful modes in a simulation framework, with known truth. Next, global terrestrial water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) gravimetry mission

Metadata Mapper: a web service for mapping data between independent visual analysis components, guided by perceptual rules

NASA Astrophysics Data System (ADS)

Rogowitz, Bernice E.; Matasci, Naim

2011-03-01

The explosion of online scientific data from experiments, simulations, and observations has given rise to an avalanche of algorithmic, visualization and imaging methods. There has also been enormous growth in the introduction of tools that provide interactive interfaces for exploring these data dynamically. Most systems, however, do not support the realtime exploration of patterns and relationships across tools and do not provide guidance on which colors, colormaps or visual metaphors will be most effective. In this paper, we introduce a general architecture for sharing metadata between applications and a "Metadata Mapper" component that allows the analyst to decide how metadata from one component should be represented in another, guided by perceptual rules. This system is designed to support "brushing [1]," in which highlighting a region of interest in one application automatically highlights corresponding values in another, allowing the scientist to develop insights from multiple sources. Our work builds on the component-based iPlant Cyberinfrastructure [2] and provides a general approach to supporting interactive, exploration across independent visualization and visual analysis components.

Method of forming a ceramic to ceramic joint

DOEpatents

Cutler, Raymond Ashton; Hutchings, Kent Neal; Kleinlein, Brian Paul; Carolan, Michael Francis

2010-04-13

A method of joining at least two sintered bodies to form a composite structure, includes: providing a joint material between joining surfaces of first and second sintered bodies; applying pressure from 1 kP to less than 5 MPa to provide an assembly; heating the assembly to a conforming temperature sufficient to allow the joint material to conform to the joining surfaces; and further heating the assembly to a joining temperature below a minimum sintering temperature of the first and second sintered bodies. The joint material includes organic component(s) and ceramic particles. The ceramic particles constitute 40-75 vol. % of the joint material, and include at least one element of the first and/or second sintered bodies. Composite structures produced by the method are also disclosed.

Patterns of glaucomatous visual field loss in sita fields automatically identified using independent component analysis.

PubMed

Goldbaum, Michael H; Jang, Gil-Jin; Bowd, Chris; Hao, Jiucang; Zangwill, Linda M; Liebmann, Jeffrey; Girkin, Christopher; Jung, Tzyy-Ping; Weinreb, Robert N; Sample, Pamela A

2009-12-01

To determine if the patterns uncovered with variational Bayesian-independent component analysis-mixture model (VIM) applied to a large set of normal and glaucomatous fields obtained with the Swedish Interactive Thresholding Algorithm (SITA) are distinct, recognizable, and useful for modeling the severity of the field loss. SITA fields were obtained with the Humphrey Visual Field Analyzer (Carl Zeiss Meditec, Inc, Dublin, California) on 1,146 normal eyes and 939 glaucoma eyes from subjects followed by the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. VIM modifies independent component analysis (ICA) to develop separate sets of ICA axes in the cluster of normal fields and the 2 clusters of abnormal fields. Of 360 models, the model with the best separation of normal and glaucomatous fields was chosen for creating the maximally independent axes. Grayscale displays of fields generated by VIM on each axis were compared. SITA fields most closely associated with each axis and displayed in grayscale were evaluated for consistency of pattern at all severities. The best VIM model had 3 clusters. Cluster 1 (1,193) was mostly normal (1,089, 95% specificity) and had 2 axes. Cluster 2 (596) contained mildly abnormal fields (513) and 2 axes; cluster 3 (323) held mostly moderately to severely abnormal fields (322) and 5 axes. Sensitivity for clusters 2 and 3 combined was 88.9%. The VIM-generated field patterns differed from each other and resembled glaucomatous defects (eg, nasal step, arcuate, temporal wedge). SITA fields assigned to an axis resembled each other and the VIM-generated patterns for that axis. Pattern severity increased in the positive direction of each axis by expansion or deepening of the axis pattern. VIM worked well on SITA fields, separating them into distinctly different yet recognizable patterns of glaucomatous field defects. The axis and pattern properties make VIM a good candidate as a preliminary process for

Application of Independent Component Analysis to Legacy UV Quasar Spectra

NASA Astrophysics Data System (ADS)

Richards, Gordon

2017-08-01

We propose to apply a novel analysis technique to UV spectroscopy ofquasars in the HST archive. We endeavor to analyze all of thearchival quasar spectra, but will first focus on those quasars thatalso have optical spectroscopy from SDSS. An archival investigationby Sulentic et al. (2007) revealed 130 known quasars with UV coverageof CIV complementing optical emission line coverage. Today, thesample has grown considerably and now includes COS spectroscopy. Ourproposal includes a proof-of-concept demonstration of the power of atechnique called Independent Component Analysis (ICA). ICA allows usto reduce complexity of of quasar spectra to just a handful ofnumbers. In addition to providing a uniform set of traditional linemeasurements (and carefully calibrated redshifts), we will provide ICAweights to the community with examples of how they can be used to doscience that previously would have been quite difficult. The time isripe for such an investigation because 1) it has been a decade sincethe last significant archival investigation of UV emission lines fromHST quasars, 2) the future is uncertain for obtaining new UV quasarspectroscopy, and 3) the rise of machine learning has provided us withpowerful new tools. Thus our proposed work will provide a true UVlegacy database for quasar-based investigations.

BAYESIAN SEMI-BLIND COMPONENT SEPARATION FOR FOREGROUND REMOVAL IN INTERFEROMETRIC 21 cm OBSERVATIONS

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

Zhang, Le; Timbie, Peter T.; Bunn, Emory F.

In this paper, we present a new Bayesian semi-blind approach for foreground removal in observations of the 21 cm signal measured by interferometers. The technique, which we call H i Expectation–Maximization Independent Component Analysis (HIEMICA), is an extension of the Independent Component Analysis technique developed for two-dimensional (2D) cosmic microwave background maps to three-dimensional (3D) 21 cm cosmological signals measured by interferometers. This technique provides a fully Bayesian inference of power spectra and maps and separates the foregrounds from the signal based on the diversity of their power spectra. Relying only on the statistical independence of the components, this approachmore » can jointly estimate the 3D power spectrum of the 21 cm signal, as well as the 2D angular power spectrum and the frequency dependence of each foreground component, without any prior assumptions about the foregrounds. This approach has been tested extensively by applying it to mock data from interferometric 21 cm intensity mapping observations under idealized assumptions of instrumental effects. We also discuss the impact when the noise properties are not known completely. As a first step toward solving the 21 cm power spectrum analysis problem, we compare the semi-blind HIEMICA technique to the commonly used Principal Component Analysis. Under the same idealized circumstances, the proposed technique provides significantly improved recovery of the power spectrum. This technique can be applied in a straightforward manner to all 21 cm interferometric observations, including epoch of reionization measurements, and can be extended to single-dish observations as well.« less

Localization of spontaneous magnetoencephalographic activity of neonates and fetuses using independent component and Hilbert phase analysis.

PubMed

Vairavan, Srinivasan; Eswaran, Hari; Preissl, Hubert; Wilson, James D; Haddad, Naim; Lowery, Curtis L; Govindan, Rathinaswamy B

2010-01-01

The fetal magnetoencephalogram (fMEG) is measured in the presence of large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). These cardiac interferences can be attenuated by orthogonal projection (OP) technique of the corresponding spatial vectors. However, the OP technique redistributes the fMEG signal among the channels and also leaves some cardiac residuals (partially attenuated mMCG and fMCG) due to loss of stationarity in the signal. In this paper, we propose a novel way to extract and localize the neonatal and fetal spontaneous brain activity by using independent component analysis (ICA) technique. In this approach, we perform ICA on a small subset of sensors for 1-min duration. The independent components obtained are further investigated for the presence of discontinuous patterns as identified by the Hilbert phase analysis and are used as decision criteria for localizing the spontaneous brain activity. In order to locate the region of highest spontaneous brain activity content, this analysis is performed on the sensor subsets, which are traversed across the entire sensor space. The region of the spontaneous brain activity as identified by the proposed approach correlated well with the neonatal and fetal head location. In addition, the burst duration and the inter-burst interval computed for the identified discontinuous brain patterns are in agreement with the reported values.

Robotic joint experiments under ultravacuum

NASA Technical Reports Server (NTRS)

Borrien, A.; Petitjean, L.

1988-01-01

First, various aspects of a robotic joint development program, including gearbox technology, electromechanical components, lubrication, and test results, are discussed. Secondly, a test prototype of the joint allowing simulation of robotic arm dynamic effects is presented. This prototype is tested under vacuum with different types of motors and sensors to characterize the functional parameters: angular position error, mechanical backlash, gearbox efficiency, and lifetime.

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterization of CuCrZr and CuCrZr/SS joint strength for different blanket components manufacturing conditions

NASA Astrophysics Data System (ADS)

Gillia, Olivier; Briottet, Laurent; Chu, Isabelle; Lemoine, Patrick; Rigal, Emmanuel; Peacock, Alan

2009-04-01

This work describes studies on the strength of CuCrZr/SS joints for different manufacturing conditions foreseen for the fabrication of blanket components. In the meantime, as junction strength is expected to be strongly related to CuCrZr properties, investigation on the properties of the CuCrZr itself after the different manufacturing conditions is also presented. The initial manufacturing conditions retained were made of a HIP treatment combined with a fast cooling plus a subsequent ageing treatment. For security reasons, the HIP-quenching operation was not possible. A supplementary solutionning cycle with fast cooling has thus been inserted in the heat treatment process just after the HIP bonding treatment. The influence of solutionning temperature (1040 °C or 980 °C), the cooling rate after solutionning (70 °C/min to water quench), the ageing temperature (480 °C or 560 °C) and the HIP temperature (1040 °C or 980 °C) have been addressed. Test results show that the ageing temperature is very important for keeping high strength of material whereas elongation properties are not very sensible to the manufacturing conditions. 1040 °C HIP or solutionning temperature gives better strength properties, as well as a higher cooling rate after solutionning. Concerning samples with joints, it appears that CT test is more selective than other tests since tensile test does not give rupture at joint and KCU test eliminates a route without classifying other routes.

Estimation of Time-Varying, Intrinsic and Reflex Dynamic Joint Stiffness during Movement. Application to the Ankle Joint

PubMed Central

Guarín, Diego L.; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness determines the relation between joint position and torque, and plays a vital role in the control of posture and movement. Dynamic joint stiffness can be quantified during quasi-stationary conditions using disturbance experiments, where small position perturbations are applied to the joint and the torque response is recorded. Dynamic joint stiffness is composed of intrinsic and reflex mechanisms that act and change together, so that nonlinear, mathematical models and specialized system identification techniques are necessary to estimate their relative contributions to overall joint stiffness. Quasi-stationary experiments have demonstrated that dynamic joint stiffness is heavily modulated by joint position and voluntary torque. Consequently, during movement, when joint position and torque change rapidly, dynamic joint stiffness will be Time-Varying (TV). This paper introduces a new method to quantify the TV intrinsic and reflex components of dynamic joint stiffness during movement. The algorithm combines ensemble and deterministic approaches for estimation of TV systems; and uses a TV, parallel-cascade, nonlinear system identification technique to separate overall dynamic joint stiffness into intrinsic and reflex components from position and torque records. Simulation studies of a stiffness model, whose parameters varied with time as is expected during walking, demonstrated that the new algorithm accurately tracked the changes in dynamic joint stiffness using as little as 40 gait cycles. The method was also used to estimate the intrinsic and reflex dynamic ankle stiffness from an experiment with a healthy subject during which ankle movements were imposed while the subject maintained a constant muscle contraction. The method identified TV stiffness model parameters that predicted the measured torque very well, accounting for more than 95% of its variance. Moreover, both intrinsic and reflex dynamic stiffness were heavily modulated through the

Comparison of soft tissue balancing, femoral component rotation, and joint line change between the gap balancing and measured resection techniques in primary total knee arthroplasty: A meta-analysis.

PubMed

Moon, Young-Wan; Kim, Hyun-Jung; Ahn, Hyeong-Sik; Park, Chan-Deok; Lee, Dae-Hee

2016-09-01

This meta-analysis was designed to compare the accuracy of soft tissue balancing and femoral component rotation as well as change in joint line positions, between the measured resection and gap balancing techniques in primary total knee arthroplasty. Studies were included in the meta-analysis if they compared soft tissue balancing and/or radiologic outcomes in patients who underwent total knee arthroplasty with the gap balancing and measured resection techniques. Comparisons included differences in flexion/extension, medial/lateral flexion, and medial/lateral extension gaps (LEGs), femoral component rotation, and change in joint line positions. Finally, 8 studies identified via electronic (MEDLINE, EMBASE, and the Cochrane Library) and manual searches were included. All 8 studies showed a low risk of selection bias and provided detailed demographic data. There was some inherent heterogeneity due to uncontrolled bias, because all included studies were observational comparison studies. The pooled mean difference in gap differences between the gap balancing and measured resection techniques did not differ significantly (-0.09 mm, 95% confidence interval [CI]: -0.40 to +0.21 mm; P = 0.55), except that the medial/LEG difference was 0.58 mm greater for measured resection than gap balancing (95% CI: -1.01 to -0.15 mm; P = 0.008). Conversely, the pooled mean difference in femoral component external rotation (0.77°, 95% CI: 0.18° to 1.35°; P = 0.01) and joint line change (1.17 mm, 95% CI: 0.82 to 1.52 mm; P < 0.001) were significantly greater for the gap balancing than the measured resection technique. The gap balancing and measured resection techniques showed similar soft tissue balancing, except for medial/LEG difference. However, the femoral component was more externally rotated and the joint line was more elevated with gap balancing than measured resection. These differences were minimal (around 1 mm or 1°) and therefore may have little effect on

Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

PubMed

Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

2018-01-01

Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

Shoulder joint impairment among Finns aged 30 years or over: prevalence, risk factors and co-morbidity.

PubMed

Mäkelä, M; Heliövaara, M; Sainio, P; Knekt, P; Impivaara, O; Aromaa, A

1999-07-01

To describe the prevalence, risk factors and consequences of shoulder joint impairment in the population. A representative sample (n = 7217) of the Finnish population aged > or = 30 yr participated in a health examination survey (the Mini-Finland Health Survey). The design of the survey allowed an independent assessment of disability, reported shoulder pain, shoulder joint impairment and major chronic co-morbidity. Shoulder impairment was observed in 8.8%, while pain was reported by 30%. The prevalence of shoulder pain decreased among the elderly, whereas impairments increased up to 20% of those aged 75-80 yr. In addition to age, sex, previous injury to the shoulder joint and a history of physically heavy work, diabetes was associated with shoulder impairment (OR 1.6, 95% CI 1.2-2.1). Shoulder impairment was associated with disability (adjusted OR 2.0, CI 1.6-2.5). Shoulder impairment is an important component of ill health among the elderly, and cannot be reduced to reported pain alone.

Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

NASA Astrophysics Data System (ADS)

Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

2012-04-01

In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

Independent and joint effects of tea and milk consumption on oral cancer among non-smokers and non-drinkers: a case-control study in China.

PubMed

Chen, Fa; Yan, Lingjun; Lin, Lisong; Liu, Fengqiong; Qiu, Yu; Liu, Fangping; Huang, Jiangfeng; Wu, Junfeng; Cai, Lin; Cai, Guoxi; Aoyagi, Kiyoshi; He, Baochang

2017-07-25

This study aims to evaluate the independent and joint effects of tea and milk consumption on oral cancer risk among non-smokers and non-drinkers (NS/ND). A hospital-based case-control study was performed in Fujian, China. 421 cases and frequency-matched 1398 controls were included without tobacco smoking and alcohol drinking habits. Unconditional logistic regression model was used to assess the relationship of tea and milk consumption with oral cancer risk. Tea and milk consumption were significantly associated with decreased risk of oral cancer, the adjusted odds ratios (aORs) were 0.73 (95% CI: 0.54-0.97) and 0.69 (95% CI: 0.55-0.88), respectively. According to subgroup analysis, the inverse associations between tea consumption and oral cancer risk were only observed among the elders (>60 years) and urban residents. While the protect effect of milk drinking was more obvious in males, normal body mass index population (18.5-23.9), urban residents and those age ≤ 60 years. Additionally, a significantly multiplicative interaction between tea and milk consumption was observed for oral cancer risk (P = 0.001). The present study is the first to simultaneously assess the association of tea consumption and milk drinking with oral cancer risk. The results suggest that tea and milk consumption are independent protective factors for oral cancer among NS/ND, with a joint effect between them.

A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification.

PubMed

LeVan, P; Urrestarazu, E; Gotman, J

2006-04-01

To devise an automated system to remove artifacts from ictal scalp EEG, using independent component analysis (ICA). A Bayesian classifier was used to determine the probability that 2s epochs of seizure segments decomposed by ICA represented EEG activity, as opposed to artifact. The classifier was trained using numerous statistical, spectral, and spatial features. The system's performance was then assessed using separate validation data. The classifier identified epochs representing EEG activity in the validation dataset with a sensitivity of 82.4% and a specificity of 83.3%. An ICA component was considered to represent EEG activity if the sum of the probabilities that its epochs represented EEG exceeded a threshold predetermined using the training data. Otherwise, the component represented artifact. Using this threshold on the validation set, the identification of EEG components was performed with a sensitivity of 87.6% and a specificity of 70.2%. Most misclassified components were a mixture of EEG and artifactual activity. The automated system successfully rejected a good proportion of artifactual components extracted by ICA, while preserving almost all EEG components. The misclassification rate was comparable to the variability observed in human classification. Current ICA methods of artifact removal require a tedious visual classification of the components. The proposed system automates this process and removes simultaneously multiple types of artifacts.

Flight Set 360L002 (STS-27) field joint protection system, volume 7

NASA Technical Reports Server (NTRS)

Hale, Elgie

1989-01-01

This report contains the pre-launch functioning data of the Field Joint Protection System (JPS) used on STS-27. Also included is the post flight condition of the JPS components following the launch and recovery of the two redesigned solid rocket motors (RSRM) boosters. The JPS components are: (1) field joint heaters; (2) field joint sensors; (3) field joint moisture seal; (4) moisture seal Kevlar retaining straps; (5) field joint external insulation; (6) vent valve; (7) power cables; and (8) igniter heater.

Independent component analysis of EEG dipole source localization in resting and action state of brain

NASA Astrophysics Data System (ADS)

Almurshedi, Ahmed; Ismail, Abd Khamim

2015-04-01

EEG source localization was studied in order to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes using EEGLAB with Independent Component Analysis (ICA) algorithm. Neuron source locations are responsible in generating current dipoles in different states of brain through the measured potentials. The current dipole sources localization are measured by fitting an equivalent current dipole model using a non-linear optimization technique with the implementation of standardized boundary element head model. To fit dipole models to ICA components in an EEGLAB dataset, ICA decomposition is performed and appropriate components to be fitted are selected. The topographical scalp distributions of delta, theta, alpha, and beta power spectrum and cross coherence of EEG signals are observed. In close eyes condition it shows that during resting and action states of brain, alpha band was activated from occipital (O1, O2) and partial (P3, P4) area. Therefore, parieto-occipital area of brain are active in both resting and action state of brain. However cross coherence tells that there is more coherence between right and left hemisphere in action state of brain than that in the resting state. The preliminary result indicates that these potentials arise from the same generators in the brain.

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

PubMed

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2008-02-15

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

A Method for Functional Network Connectivity Among Spatially Independent Resting-State Components in Schizophrenia

PubMed Central

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2011-01-01

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in patients versus controls. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject’s ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients. PMID:18082428

Systematic Quantification of Stabilizing Effects of Subtalar Joint Soft-Tissue Constraints in a Novel Cadaveric Model.

PubMed

Pellegrini, Manuel J; Glisson, Richard R; Wurm, Markus; Ousema, Paul H; Romash, Michael M; Nunley, James A; Easley, Mark E

2016-05-18

Distinguishing between ankle instability and subtalar joint instability is challenging because the contributions of the subtalar joint's soft-tissue constraints are poorly understood. This study quantified the effects on joint stability of systematic sectioning of these constraints followed by application of torsional and drawer loads simulating a manual clinical examination. Subtalar joint motion in response to carefully controlled inversion, eversion, internal rotation, and external rotation moments and multidirectional drawer forces was quantified in fresh-frozen cadaver limbs. Sequential measurements were obtained under axial load approximating a non-weight-bearing clinical setting with the foot in neutral, 10° of dorsiflexion, and 10° and 20° of plantar flexion. The contributions of the components of the inferior extensor retinaculum were documented after incremental sectioning. The calcaneofibular, cervical, and interosseous talocalcaneal ligaments were then sectioned sequentially, in two different orders, to produce five different ligament-insufficiency scenarios. Incremental detachment of the components of the inferior extensor retinaculum had no effect on subtalar motion independent of foot position. Regardless of the subsequent ligament-sectioning order, significant motion increases relative to the intact condition occurred only after transection of the calcaneofibular ligament. Sectioning of this ligament produced increased inversion and external rotation, which was most evident with the foot dorsiflexed. Calcaneofibular ligament disruption results in increases in subtalar inversion and external rotation that might be detectable during a manual examination. Insufficiency of other subtalar joint constraints may result in motion increases that are too subtle to be perceptible. If calcaneofibular ligament insufficiency is established, its reconstruction or repair should receive priority over that of other ankle or subtalar periarticular soft

Virtual trajectories of single-joint movements performed under two basic strategies.

PubMed

Latash, M L; Gottlieb, G L

1992-01-01

The framework of the equilibrium point hypothesis has been used to analyse motor control processes for single-joint movements. Virtual trajectories and joint stiffness were reconstructed for different movement speeds and distances when subjects were instructed either to move "as fast as possible" or to intentionally vary movement speed. These instructions are assumed to be associated with similar or different rates of change of hypothetical central control variables (corresponding to the speed-sensitive and speed-insensitive strategies). The subjects were trained to perform relatively slow, moderately fast and very fast (nominal movement times 800, 400 and 250 ms) single-joint elbow flexion movements against a constant extending torque bias. They were instructed to reproduce the motor command for a series of movements while ignoring possible changes in the external torque which could slowly and unpredictably increase, decrease, or remain constant. The total muscle torque was calculated as a sum of external and inertial components. Fast movements over different distances were made with the speed-insensitive strategy. They were characterized by an increase in joint stiffness near the midpoint of the movements which was relatively independent of movement amplitude. Their virtual trajectories had a non-monotonic N-shape. All three arms of the N-shape scaled with movement amplitude. Movements over one distance at different speeds were made with a speed-sensitive strategy. They demonstrated different patterns of virtual trajectories and joint stiffness that depended on movement speed. The N-shape became less apparent for moderately fast movements and virtually disappeared for the slow movements. Slow movements showed no visible increase in joint stiffness.(ABSTRACT TRUNCATED AT 250 WORDS)

Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of Space Geodetic Time Series

NASA Astrophysics Data System (ADS)

Gualandi, Adriano; Serpelloni, Enrico; Elina Belardinelli, Maria; Bonafede, Maurizio; Pezzo, Giuseppe; Tolomei, Cristiano

2015-04-01

A critical point in the analysis of ground displacement time series, as those measured by modern space geodetic techniques (primarly continuous GPS/GNSS and InSAR) is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies, since PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem. The recovering and separation of the different sources that generate the observed ground deformation is a fundamental task in order to provide a physical meaning to the possible different sources. PCA fails in the BSS problem since it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the displacement time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient deformation signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources

Self-sustained vibrations in volcanic areas extracted by Independent Component Analysis: a review and new results

NASA Astrophysics Data System (ADS)

de Lauro, E.; de Martino, S.; Falanga, M.; Palo, M.

2011-12-01

We investigate the physical processes associated with volcanic tremor and explosions. A volcano is a complex system where a fluid source interacts with the solid edifice so generating seismic waves in a regime of low turbulence. Although the complex behavior escapes a simple universal description, the phases of activity generate stable (self-sustained) oscillations that can be described as a non-linear dynamical system of low dimensionality. So, the system requires to be investigated with non-linear methods able to individuate, decompose, and extract the main characteristics of the phenomenon. Independent Component Analysis (ICA), an entropy-based technique is a good candidate for this purpose. Here, we review the results of ICA applied to seismic signals acquired in some volcanic areas. We emphasize analogies and differences among the self-oscillations individuated in three cases: Stromboli (Italy), Erebus (Antarctica) and Volcán de Colima (Mexico). The waveforms of the extracted independent components are specific for each volcano, whereas the similarity can be ascribed to a very general common source mechanism involving the interaction between gas/magma flow and solid structures (the volcanic edifice). Indeed, chocking phenomena or inhomogeneities in the volcanic cavity can play the same role in generating self-oscillations as the languid and the reed do in musical instruments. The understanding of these background oscillations is relevant not only for explaining the volcanic source process and to make a forecast into the future, but sheds light on the physics of complex systems developing low turbulence.

On the microstructure analysis of FSW joints of aluminium components made via direct metal laser sintering

NASA Astrophysics Data System (ADS)

Scherillo, Fabio; Astarita, Antonello; di Martino, Daniela; Contaldi, Vincenzo; di Matteo, Luca; di Petta, Paolo; Casarin, Renzo; Squillace, Antonino; Langella, Antonio

2017-10-01

Additive Manufacturing (AM), applied to metal industry, is a family of processes that allow complex shape components to be realized from raw materials in the form of powders. The compaction of the powders can be achieved by local melting of the powder bed or by solid state sintering. Direct Metal Laser Sintering (DMLS) is an additive manufacturing process in which a focalized laser beam is the heat source that allows the powders to be compacted. By DMLS it is possible to realize complex shape components. One of the limits of DMLS, as for every additive layer manufacturing techniques, is the unfeasibility to realize large dimension parts. Due to this limit the study of joining process of parts made via ALM is of great interest. One of the most promising options is the Friction Stir Welding (FSW), a solid state welding technique that has been proven to be very effective in the welding of metals difficult to weld, above all aluminium alloys. Since FSW is a solid-state technique, the microstructure of the various zone of the weld bead depends not only by the process itself but also by the parent microstruct ure of the parts to be welded. Furthermore, parts made of aluminium alloy via DMLS have a particular microstructure that is the result of repeated severe thermal cycles. In the present work the authors, starting from the description of the parent microstructure of parts made of AlSi10Mg aluminium alloy, study the microstructure evolution occurred within the joint made by Friction Stir Welding, analysing in details the microstructure of the main well recognized zone of the weld bead. The structure of the parent material is characterized by the presence of melting pools with a very fine microstructure. In the joint the recrystallization, the grain refinement and, above all, the redistribution of intermetallic phases occurs, resulting in an homogenization of the microstructure and in an increase of micro hardness.

Adaptive kernel independent component analysis and UV spectrometry applied to characterize the procedure for processing prepared rhubarb roots.

PubMed

Wang, Guoqing; Hou, Zhenyu; Peng, Yang; Wang, Yanjun; Sun, Xiaoli; Sun, Yu-an

2011-11-07

By determination of the number of absorptive chemical components (ACCs) in mixtures using median absolute deviation (MAD) analysis and extraction of spectral profiles of ACCs using kernel independent component analysis (KICA), an adaptive KICA (AKICA) algorithm was proposed. The proposed AKICA algorithm was used to characterize the procedure for processing prepared rhubarb roots by resolution of the measured mixed raw UV spectra of the rhubarb samples that were collected at different steaming intervals. The results show that the spectral features of ACCs in the mixtures can be directly estimated without chemical and physical pre-separation and other prior information. The estimated three independent components (ICs) represent different chemical components in the mixtures, which are mainly polysaccharides (IC1), tannin (IC2), and anthraquinone glycosides (IC3). The variations of the relative concentrations of the ICs can account for the chemical and physical changes during the processing procedure: IC1 increases significantly before the first 5 h, and is nearly invariant after 6 h; IC2 has no significant changes or is slightly decreased during the processing procedure; IC3 decreases significantly before the first 5 h and decreases slightly after 6 h. The changes of IC1 can explain why the colour became black and darkened during the processing procedure, and the changes of IC3 can explain why the processing procedure can reduce the bitter and dry taste of the rhubarb roots. The endpoint of the processing procedure can be determined as 5-6 h, when the increasing or decreasing trends of the estimated ICs are insignificant. The AKICA-UV method provides an alternative approach for the characterization of the processing procedure of rhubarb roots preparation, and provides a novel way for determination of the endpoint of the traditional Chinese medicine (TCM) processing procedure by inspection of the change trends of the ICs.

Dynamic analysis of clamp band joint system subjected to axial vibration

NASA Astrophysics Data System (ADS)

Qin, Z. Y.; Yan, S. Z.; Chu, F. L.

2010-10-01

Clamp band joints are commonly used for connecting circular components together in industry. Some of the systems jointed by clamp band are subjected to dynamic load. However, very little research on the dynamic characteristics for this kind of joint can be found in the literature. In this paper, a dynamic model for clamp band joint system is developed. Contact and frictional slip between the components are accommodated in this model. Nonlinear finite element analysis is conducted to identify the model parameters. Then static experiments are carried out on a scaled model of the clamp band joint to validate the joint model. Finally, the model is adopted to study the dynamic characteristics of the clamp band joint system subjected to axial harmonic excitation and the effects of the wedge angle of the clamp band joint and the preload on the response. The model proposed in this paper can represent the nonlinearity of the clamp band joint and be used conveniently to investigate the effects of the structural and loading parameters on the dynamic characteristics of this type of joint system.

Analysis on unevenness of skin color using the melanin and hemoglobin components separated by independent component analysis of skin color image

NASA Astrophysics Data System (ADS)

Ojima, Nobutoshi; Fujiwara, Izumi; Inoue, Yayoi; Tsumura, Norimichi; Nakaguchi, Toshiya; Iwata, Kayoko

2011-03-01

Uneven distribution of skin color is one of the biggest concerns about facial skin appearance. Recently several techniques to analyze skin color have been introduced by separating skin color information into chromophore components, such as melanin and hemoglobin. However, there are not many reports on quantitative analysis of unevenness of skin color by considering type of chromophore, clusters of different sizes and concentration of the each chromophore. We propose a new image analysis and simulation method based on chromophore analysis and spatial frequency analysis. This method is mainly composed of three techniques: independent component analysis (ICA) to extract hemoglobin and melanin chromophores from a single skin color image, an image pyramid technique which decomposes each chromophore into multi-resolution images, which can be used for identifying different sizes of clusters or spatial frequencies, and analysis of the histogram obtained from each multi-resolution image to extract unevenness parameters. As the application of the method, we also introduce an image processing technique to change unevenness of melanin component. As the result, the method showed high capabilities to analyze unevenness of each skin chromophore: 1) Vague unevenness on skin could be discriminated from noticeable pigmentation such as freckles or acne. 2) By analyzing the unevenness parameters obtained from each multi-resolution image for Japanese ladies, agerelated changes were observed in the parameters of middle spatial frequency. 3) An image processing system modulating the parameters was proposed to change unevenness of skin images along the axis of the obtained age-related change in real time.

Design, Fabrication and Characterization of High Temperature Joints in Ceramic Composites

NASA Technical Reports Server (NTRS)

Singh, M.

1999-01-01

Ceramic joining has been recognized as one of the enabling technologies for the successful utilization of ceramic components in a number of demanding, high temperature applications. Various joint design philosophies and design issues have been discussed along with an affordable, robust ceramic joining technology (ARCJoinT). A wide variety of silicon carbide-based composite materials, in different shapes and sizes, have been joined using this technology. This technique is capable of producing joints with tailorable thickness and composition. The room and high temperature mechanical properties and fractography of ceramic joints have been reported. These joints maintain their mechanical strength up to 1200 C in air. This technology is suitable for the joining of large and complex shaped ceramic composite components and with certain modifications, can be applied to repair of ceramic components damaged in service.

Design, Fabrication, and Characterization of High Temperature Joints in Ceramic Composites

NASA Technical Reports Server (NTRS)

Singh, M.

1999-01-01

Ceramic joining has been recognized as one of the enabling technologies for the successful utilization of ceramic components in a number of demanding, high temperature applications. Various joint design philosophies and design issues have been discussed along with an affordable, robust ceramic joining technology (ARCJoinT). A wide variety of silicon carbide-based composite materials, in different shapes and sizes, have been joined using this technology. This technique is capable of producing joints with tailorable thickness and composition. The room and high temperature mechanical properties and fractography of ceramic joints have been reported. These joints maintain their mechanical strength up to 1200C in air. This technology is suitable for the joining of large and complex shaped ceramic composite components and with certain modifications, can be applied to repair of ceramic components damaged in service.

Acoustic emissions (AE) monitoring of large-scale composite bridge components

NASA Astrophysics Data System (ADS)

Velazquez, E.; Klein, D. J.; Robinson, M. J.; Kosmatka, J. B.

2008-03-01

Acoustic Emissions (AE) has been successfully used with composite structures to both locate and give a measure of damage accumulation. The current experimental study uses AE to monitor large-scale composite modular bridge components. The components consist of a carbon/epoxy beam structure as well as a composite to metallic bonded/bolted joint. The bonded joints consist of double lap aluminum splice plates bonded and bolted to carbon/epoxy laminates representing the tension rail of a beam. The AE system is used to monitor the bridge component during failure loading to assess the failure progression and using time of arrival to give insight into the origins of the failures. Also, a feature in the AE data called Cumulative Acoustic Emission counts (CAE) is used to give an estimate of the severity and rate of damage accumulation. For the bolted/bonded joints, the AE data is used to interpret the source and location of damage that induced failure in the joint. These results are used to investigate the use of bolts in conjunction with the bonded joint. A description of each of the components (beam and joint) is given with AE results. A summary of lessons learned for AE testing of large composite structures as well as insight into failure progression and location is presented.

21 CFR 888.3480 - Knee joint femorotibial metallic constrained cemented prosthesis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Knee joint femorotibial metallic constrained... Knee joint femorotibial metallic constrained cemented prosthesis. (a) Identification. A knee joint... knee joint. The device prevents dislocation in more than one anatomic plane and has components that are...

Proximal Versus Distal Control of Two-Joint Planar Reaching Movements in the Presence of Neuromuscular Noise

PubMed Central

Nguyen, Hung P.; Dingwell, Jonathan B.

2012-01-01

Determining how the human nervous system contends with neuro-motor noise is vital to understanding how humans achieve accurate goal-directed movements. Experimentally, people learning skilled tasks tend to reduce variability in distal joint movements more than in proximal joint movements. This suggests that they might be imposing greater control over distal joints than proximal joints. However, the reasons for this remain unclear, largely because it is not experimentally possible to directly manipulate either the noise or the control at each joint independently. Therefore, this study used a 2 degree-of-freedom torque driven arm model to determine how different combinations of noise and/or control independently applied at each joint affected the reaching accuracy and the total work required to make the movement. Signal-dependent noise was simultaneously and independently added to the shoulder and elbow torques to induce endpoint errors during planar reaching. Feedback control was then applied, independently and jointly, at each joint to reduce endpoint error due to the added neuromuscular noise. Movement direction and the inertia distribution along the arm were varied to quantify how these biomechanical variations affected the system performance. Endpoint error and total net work were computed as dependent measures. When each joint was independently subjected to noise in the absence of control, endpoint errors were more sensitive to distal (elbow) noise than to proximal (shoulder) noise for nearly all combinations of reaching direction and inertia ratio. The effects of distal noise on endpoint errors were more pronounced when inertia was distributed more toward the forearm. In contrast, the total net work decreased as mass was shifted to the upper arm for reaching movements in all directions. When noise was present at both joints and joint control was implemented, controlling the distal joint alone reduced endpoint errors more than controlling the proximal joint

Proximal versus distal control of two-joint planar reaching movements in the presence of neuromuscular noise.

PubMed

Nguyen, Hung P; Dingwell, Jonathan B

2012-06-01

Determining how the human nervous system contends with neuro-motor noise is vital to understanding how humans achieve accurate goal-directed movements. Experimentally, people learning skilled tasks tend to reduce variability in distal joint movements more than in proximal joint movements. This suggests that they might be imposing greater control over distal joints than proximal joints. However, the reasons for this remain unclear, largely because it is not experimentally possible to directly manipulate either the noise or the control at each joint independently. Therefore, this study used a 2 degree-of-freedom torque driven arm model to determine how different combinations of noise and/or control independently applied at each joint affected the reaching accuracy and the total work required to make the movement. Signal-dependent noise was simultaneously and independently added to the shoulder and elbow torques to induce endpoint errors during planar reaching. Feedback control was then applied, independently and jointly, at each joint to reduce endpoint error due to the added neuromuscular noise. Movement direction and the inertia distribution along the arm were varied to quantify how these biomechanical variations affected the system performance. Endpoint error and total net work were computed as dependent measures. When each joint was independently subjected to noise in the absence of control, endpoint errors were more sensitive to distal (elbow) noise than to proximal (shoulder) noise for nearly all combinations of reaching direction and inertia ratio. The effects of distal noise on endpoint errors were more pronounced when inertia was distributed more toward the forearm. In contrast, the total net work decreased as mass was shifted to the upper arm for reaching movements in all directions. When noise was present at both joints and joint control was implemented, controlling the distal joint alone reduced endpoint errors more than controlling the proximal joint

Augmented Reality-Guided Lumbar Facet Joint Injections.

PubMed

Agten, Christoph A; Dennler, Cyrill; Rosskopf, Andrea B; Jaberg, Laurenz; Pfirrmann, Christian W A; Farshad, Mazda

2018-05-08

The aim of this study was to assess feasibility and accuracy of augmented reality-guided lumbar facet joint injections. A spine phantom completely embedded in hardened opaque agar with 3 ring markers was built. A 3-dimensional model of the phantom was uploaded to an augmented reality headset (Microsoft HoloLens). Two radiologists independently performed 20 augmented reality-guided and 20 computed tomography (CT)-guided facet joint injections each: for each augmented reality-guided injection, the hologram was manually aligned with the phantom container using the ring markers. The radiologists targeted the virtual facet joint and tried to place the needle tip in the holographic joint space. Computed tomography was performed after each needle placement to document final needle tip position. Time needed from grabbing the needle to final needle placement was measured for each simulated injection. An independent radiologist rated images of all needle placements in a randomized order blinded to modality (augmented reality vs CT) and performer as perfect, acceptable, incorrect, or unsafe. Accuracy and time to place needles were compared between augmented reality-guided and CT-guided facet joint injections. In total, 39/40 (97.5%) of augmented reality-guided needle placements were either perfect or acceptable compared with 40/40 (100%) CT-guided needle placements (P = 0.5). One augmented reality-guided injection missed the facet joint space by 2 mm. No unsafe needle placements occurred. Time to final needle placement was substantially faster with augmented reality guidance (mean 14 ± 6 seconds vs 39 ± 15 seconds, P < 0.001 for both readers). Augmented reality-guided facet joint injections are feasible and accurate without potentially harmful needle placement in an experimental setting.

Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

NASA Astrophysics Data System (ADS)

Kolski, Jeffrey S.; Macek, Robert J.; McCrady, Rodney C.; Pang, Xiaoying

2012-11-01

Independent component analysis (ICA) is a powerful blind source separation (BSS) method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs) yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor) for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

Predicting the Functional Roles of Knee Joint Muscles from Internal Joint Moments.

PubMed

Flaxman, Teresa E; Alkjær, Tine; Simonsen, Erik B; Krogsgaard, Michael R; Benoit, Daniel L

2017-03-01

Knee muscles are commonly labeled as flexors or extensors and aptly stabilize the knee against sagittal plane loads. However, how these muscles stabilize the knee against adduction-abduction and rotational loads remains unclear. Our study sought 1) to classify muscle roles as they relate to joint stability by quantifying the relationship between individual muscle activation patterns and internal net joint moments in all three loading planes and 2) to determine whether these roles change with increasing force levels. A standing isometric force matching protocol required subjects to modulate ground reaction forces to elicit various combinations and magnitudes of sagittal, frontal, and transverse internal joint moments. Surface EMG measured activities of 10 lower limb muscles. Partial least squares regressions determined which internal moment(s) were significantly related to the activation of individual muscles. Rectus femoris and tensor fasciae latae were classified as moment actuators for knee extension and hip flexion. Hamstrings were classified as moment actuators for hip extension and knee flexion. Gastrocnemius and hamstring muscles were classified as specific joint stabilizers for knee rotation. Vastii were classified as general joint stabilizers because activation was independent of moment generation. Muscle roles did not change with increasing effort levels. Our findings indicate muscle activation is not dependent on anatomical orientation but perhaps on its role in maintaining knee joint stability in the frontal and transverse loading planes. This is useful for delineating the roles of biarticular knee joint muscles and could have implications in robotics, musculoskeletal modeling, sports sciences, and rehabilitation.

Outcome measures in older persons with acquired joint contractures: a systematic review and content analysis using the ICF (International Classification of Functioning, Disability and Health) as a reference.

PubMed

Bartoszek, Gabriele; Fischer, Uli; Müller, Martin; Strobl, Ralf; Grill, Eva; Nadolny, Stephan; Meyer, Gabriele

2016-02-09

Joint contractures are a common health problem in older persons with significant impact on activities of daily living. We aimed to retrieve outcome measures applied in studies on older persons with joint contractures and to identify and categorise the concepts contained in these outcome measures using the ICF (International Classification of Functioning, Disability and Health) as a reference. Electronic searches of Medline, EMBASE, CINAHL, Pedro and the Cochrane Library were conducted (1/2002-8/2012). We included studies in the geriatric rehabilitation and nursing home settings with participants aged ≥ 65 years and with acquired joint contractures. Two independent reviewers extracted the outcome measures and transferred them to concepts using predefined conceptual frameworks. Concepts were subsequently linked to the ICF categories. From the 1057 abstracts retrieved, 60 studies met the inclusion criteria. We identified 52 single outcome measures and 24 standardised assessment instruments. A total of 1353 concepts were revealed from the outcome measures; 96.2% could be linked to 50 ICF categories in the 2nd level; 3.8% were not categorised. Fourteen of the 50 categories (28%) belonged to the component Body Functions, 4 (8%) to the component Body Structures, 26 (52%) to the component Activities and Participation, and 6 (12%) to the component Environmental Factors. The ICF is a valuable reference for identifying and quantifying the concepts of outcome measures on joint contractures in older people. The revealed ICF categories remain to be validated in populations with joint contractures in terms of clinical relevance and personal impact.

Nonlinear analysis of heart rate variability within independent frequency components during the sleep-wake cycle.

PubMed

Vigo, Daniel E; Dominguez, Javier; Guinjoan, Salvador M; Scaramal, Mariano; Ruffa, Eduardo; Solernó, Juan; Siri, Leonardo Nicola; Cardinali, Daniel P

2010-04-19

Heart rate variability (HRV) is a complex signal that results from the contribution of different sources of oscillation related to the autonomic nervous system activity. Although linear analysis of HRV has been applied to sleep studies, the nonlinear dynamics of HRV underlying frequency components during sleep is less known. We conducted a study to evaluate nonlinear HRV within independent frequency components in wake status, slow-wave sleep (SWS, stages III or IV of non-rapid eye movement sleep), and rapid-eye-movement sleep (REM). The sample included 10 healthy adults. Polysomnography was performed to detect sleep stages. HRV was studied globally during each phase and then very low frequency (VLF), low frequency (LF) and high frequency (HF) components were separated by means of the wavelet transform algorithm. HRV nonlinear dynamics was estimated with sample entropy (SampEn). A higher SampEn was found when analyzing global variability (Wake: 1.53+/-0.28, SWS: 1.76+/-0.32, REM: 1.45+/-0.19, p=0.005) and VLF variability (Wake: 0.13+/-0.03, SWS: 0.19+/-0.03, REM: 0.14+/-0.03, p<0.001) at SWS. REM was similar to wake status regarding nonlinear HRV. We propose nonlinear HRV is a useful index of the autonomic activity that characterizes the different sleep-wake cycle stages. 2009 Elsevier B.V. All rights reserved.

Dimension reduction: additional benefit of an optimal filter for independent component analysis to extract event-related potentials.

PubMed

Cong, Fengyu; Leppänen, Paavo H T; Astikainen, Piia; Hämäläinen, Jarmo; Hietanen, Jari K; Ristaniemi, Tapani

2011-09-30

The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the number of sources) simultaneously. We demonstrated these effects using two datasets, one containing visual and the other auditory ERPs. The results showed that the method including OF and ICA extracted much more reliable components than the sole ICA without OF did, and that OF removed some non-targeted sources and made the underdetermined model of EEG recordings approach to the determined one. Thus, we suggest designing an OF based on the properties of an ERP to filter recordings before using ICA decomposition to extract the targeted ERP component. Copyright © 2011 Elsevier B.V. All rights reserved.

Fabrication and Assembly of High-Precision Hinge and Latch Joints for Deployable Optical Instruments

NASA Technical Reports Server (NTRS)

Phelps, James E.

1999-01-01

Descriptions are presented of high-precision hinge and latch joints that have been co-developed, for application to deployable optical instruments, by NASA Langley Research Center and Nyma/ADF. Page-sized versions of engineering drawings are included in two appendices to describe all mechanical components of both joints. Procedures for assembling the mechanical components of both joints are also presented. The information herein is intended to facilitate the fabrication and assembly of the high-precision hinge and latch joints, and enable the incorporation of these joints into the design of deployable optical instrument systems.

46 CFR 56.30-20 - Threaded joints.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., inches Maximum pressure, p.s.i.g. Above 2″ (Not permitted in Class I piping service.) Above 1″ up to 2... joints appear in the low temperature piping section. 2 Threaded joints in hydraulic systems are permitted above the pressures indicated for the nominal sizes shown when commercially available components such as...

46 CFR 56.30-20 - Threaded joints.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., inches Maximum pressure, p.s.i.g. Above 2″ (Not permitted in Class I piping service.) Above 1″ up to 2... joints appear in the low temperature piping section. 2 Threaded joints in hydraulic systems are permitted above the pressures indicated for the nominal sizes shown when commercially available components such as...

46 CFR 56.30-20 - Threaded joints.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., inches Maximum pressure, p.s.i.g. Above 2″ (Not permitted in Class I piping service.) Above 1″ up to 2... joints appear in the low temperature piping section. 2 Threaded joints in hydraulic systems are permitted above the pressures indicated for the nominal sizes shown when commercially available components such as...

46 CFR 56.30-20 - Threaded joints.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., inches Maximum pressure, p.s.i.g. Above 2″ (Not permitted in Class I piping service.) Above 1″ up to 2... joints appear in the low temperature piping section. 2 Threaded joints in hydraulic systems are permitted above the pressures indicated for the nominal sizes shown when commercially available components such as...

46 CFR 56.30-20 - Threaded joints.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., inches Maximum pressure, p.s.i.g. Above 2″ (Not permitted in Class I piping service.) Above 1″ up to 2... joints appear in the low temperature piping section. 2 Threaded joints in hydraulic systems are permitted above the pressures indicated for the nominal sizes shown when commercially available components such as...

Joint multifractal analysis based on wavelet leaders

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing

2017-12-01

Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

Localized cervical facet joint kinematics under physiological and whiplash loading.

PubMed

Stemper, Brian D; Yoganandan, Narayan; Gennarelli, Thomas A; Pintar, Frank A

2005-12-01

Although facet joints have been implicated in the whiplash injury mechanism, no investigators have determined the degree to which joint motions in whiplash are nonphysiological. The purpose of this investigation was to quantify the correlation between facet joint and segmental motions under physiological and whiplash loading. Human cadaveric cervical spine specimens were exercise tested under physiological extension loading, and intact human head-neck complexes were exercise tested under whiplash loading to correlate the localized component motions of the C4-5 facet joint with segmental extension. Facet joint shear and distraction kinematics demonstrated a linear correlation with segmental extension under both loading modes. Facet joints responded differently to whiplash and physiological loading, with significantly increased kinematics for the same-segmental angulation. The limitations of this study include removal of superficial musculature and the limited sample size for physiological testing. The presence of increased facet joint motions indicated that synovial joint soft-tissue components (that is, synovial membrane and capsular ligament) sustain increased distortion that may subject these tissues to a greater likelihood of injury. This finding is supported by clinical investigations in which lower cervical facet joint injury resulted in similar pain patterns due to the most commonly reported whiplash symptoms.

Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra.

PubMed

Mantini, Dante; Petrucci, Francesca; Del Boccio, Piero; Pieragostino, Damiana; Di Nicola, Marta; Lugaresi, Alessandra; Federici, Giorgio; Sacchetta, Paolo; Di Ilio, Carmine; Urbani, Andrea

2008-01-01

Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.

Static and Fatigue Strength Evaluations for Bolted Composite/Steel Joints for Heavy Vehicle Chassis Components

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

Sun, Xin; Stephens, Elizabeth V.; Herling, Darrell R.

2004-09-14

In May 2003, ORNL and PNNL began collaboration on a four year research effort focused on developing joining techniques to overcome the technical issues associated with joining lightweight materials in heavy vehicles. The initial focus of research is the development and validation of joint designs for a composite structural member attached to a metal member that satisfy the structural requirements both economically and reliably. Huck-bolting is a common joining method currently used in heavy truck chassis structures. The initial round of testing was conducted to establish a performance benchmark by evaluating the static and fatigue behavior of an existing steel/steelmore » chassis joint at the single huck-bolt level. Both tension and shear loading conditions were considered, and the resulting static and fatigue strengths will be used to guide the joint design for a replacement composite/steel joint. A commercially available, pultruded composite material was chosen to study the generic issues related to composite/steel joints. Extren is produced by STRONGWELL, and it is a combination of fiberglass reinforcement and thermosetting polyester or vinyl ester resin systems. Extren sheets of 3.2 mm thick were joined to 1.4 mm SAE1008 steel sheets with a standard grade 5 bolt with 6.35 mm diameter. Both tension and shear loading modes were considered for the single hybrid joint under static and fatigue loading conditions. Since fiberglass reinforced thermoset polymer composites are a non-homogenous material, their strengths and behavior are dependent upon the design of the composite and reinforcement. The Extren sheet stock was cut along the longitudinal direction to achieve maximum net-section strength. The effects of various manufacturing factors and operational conditions on the static and fatigue strength of the hybrid joint were modeled and experimentally verified. It was found that loading mode and washer size have significant influence on the static and fatigue

A two-step super-Gaussian independent component analysis approach for fMRI data.

PubMed

Ge, Ruiyang; Yao, Li; Zhang, Hang; Long, Zhiying

2015-09-01

Independent component analysis (ICA) has been widely applied to functional magnetic resonance imaging (fMRI) data analysis. Although ICA assumes that the sources underlying data are statistically independent, it usually ignores sources' additional properties, such as sparsity. In this study, we propose a two-step super-GaussianICA (2SGICA) method that incorporates the sparse prior of the sources into the ICA model. 2SGICA uses the super-Gaussian ICA (SGICA) algorithm that is based on a simplified Lewicki-Sejnowski's model to obtain the initial source estimate in the first step. Using a kernel estimator technique, the source density is acquired and fitted to the Laplacian function based on the initial source estimates. The fitted Laplacian prior is used for each source at the second SGICA step. Moreover, the automatic target generation process for initial value generation is used in 2SGICA to guarantee the stability of the algorithm. An adaptive step size selection criterion is also implemented in the proposed algorithm. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of 2SGICA and made a performance comparison between InfomaxICA, FastICA, mean field ICA (MFICA) with Laplacian prior, sparse online dictionary learning (ODL), SGICA and 2SGICA. Both simulated and real fMRI experiments showed that the 2SGICA was most robust to noises, and had the best spatial detection power and the time course estimation among the six methods. Copyright © 2015. Published by Elsevier Inc.

Independent and joint associations between multiple measures of the built and social environment and physical activity in a multi-ethnic urban community.

PubMed

Schulz, Amy; Mentz, Graciela; Johnson-Lawrence, Vicki; Israel, Barbara A; Max, Paul; Zenk, Shannon N; Wineman, Jean; Marans, Robert W

2013-10-01

Physical activity is associated with reduced risk of a number of health outcomes, yet fewer than half of adults in the United States report recommended levels of physical activity. Analyses of structural characteristics of the built environment as correlates of physical activity have yielded mixed results. We examine associations between multiple aspects of urban neighborhood environments and physical activity in order to understand their independent and joint effects, with a focus on the extent to which the condition of the built environment and indicators of the social environment modify associations between structural characteristics and physical activity. We use data from a stratified, multi-stage proportional probability sample of 919 non-Hispanic Black, non-Hispanic White, and Hispanic adults in an urban community, observational data from their residential neighborhoods, and census data to examine independent and joint associations of structural characteristics (e.g., street network connectivity), their condition (e.g., sidewalk condition), and social environments (e.g., territoriality) with physical activity. Our findings suggest that sidewalk condition is associated with physical activity, above and beyond structural characteristics of the built environment. Associations between some structural characteristics of the built environment and physical activity were conditional upon street condition, physical deterioration, and the proportion of parks and playgrounds in good condition. We found modest support for the hypothesis that associations between structural characteristics and physical activity are modified by aspects of the social environment. Results presented here point to the value of and need for understanding and addressing the complexity of factors that contribute to the relationships between the built and social environments and physical activity, and in turn, obesity and co-morbidities. Bringing together urban planners, public health

Independent component analysis based channel equalization for 6 × 6 MIMO-OFDM transmission over few-mode fiber.

PubMed

He, Zhixue; Li, Xiang; Luo, Ming; Hu, Rong; Li, Cai; Qiu, Ying; Fu, Songnian; Yang, Qi; Yu, Shaohua

2016-05-02

We propose and experimentally demonstrate two independent component analysis (ICA) based channel equalizers (CEs) for 6 × 6 MIMO-OFDM transmission over few-mode fiber. Compared with the conventional channel equalizer based on training symbols (TSs-CE), the proposed two ICA-based channel equalizers (ICA-CE-I and ICA-CE-II) can achieve comparable performances, while requiring much less training symbols. Consequently, the overheads for channel equalization can be substantially reduced from 13.7% to 0.4% and 2.6%, respectively. Meanwhile, we also experimentally investigate the convergence speed of the proposed ICA-based CEs.

Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

NASA Astrophysics Data System (ADS)

Yue, Y.; Jiang, T.; Zhou, Q.

2017-12-01

In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in

Hyaline cartilage calcification of the first metatarsophalangeal joint is associated with osteoarthritis but independent of age and BMI.

PubMed

Hubert, Jan; Hawellek, Thelonius; Hischke, Sandra; Bertrand, Jessica; Krause, Matthias; Püschel, Klaus; Rüther, Wolfgang; Niemeier, Andreas

2016-11-15

Hyaline cartilage calcification (CC) is associated with osteoarthritis (OA) in hip and knee joints. The first metatarsophalangeal joint (1 st MTPJ) is frequently affected by OA, but it is unclear if CC occurs in the 1 st MTPJ. The aim of the present study was to analyze the prevalence of CC of the 1 st MTPJ in the general population by high-resolution digital contact radiography (DCR) and to determine its association with histological OA severity, age and body mass index (BMI). 168 metatarsal heads of 84 donors (n = 47 male, n = 37 female; mean age 62.73 years, SD ±18.8, range 20-93) were analyzed by DCR for the presence of CC. Histological OA grade (hOA) by OARSI was analyzed in the central load-bearing zone of the first metatarsal head (1 st MH). Structural equation modeling (SEM) was performed to analyze the interrelationship between CC, hOA, age and BMI. The prevalence of CC of 1 st MH was 48.8 % (41/84) (95 %-CI [37.7 %, 60.0 %]), independent of the affected side (p = 0.42), gender (p = 0.41) and BMI (p = 0.51). The mean amount of CC of one MH correlated significantly with that of the contralateral side (r s  = 0.4, 95 %-CI [0.26, 0.52], p < 0.001). The mean amount of CC (in % of total cartilage area) of the MH correlated significantly with the severity of hOA (r s  = 0.51, 95 %-CI [0.32, 0.65], p < 0.001). SEM revealed significant associations between CC and hOA (r = 0.74, p < 0.001) and between hOA and age (β = 0.62, p = 0.001), but not between CC and age (p = 0.15). There was no significant influence of BMI on either CC (p = 0.37) or hOA (p = 0.16). The observation that CC of the 1 st MH is significantly associated with the severity of OA but independent of age and BMI, suggests an intimate relationship between CC and the pathogenesis of OA, the exact nature of which will have to be explored by future studies.

Stabilizing bidirectional associative memory with Principles in Independent Component Analysis and Null Space (PICANS)

NASA Astrophysics Data System (ADS)

LaRue, James P.; Luzanov, Yuriy

2013-05-01

A new extension to the way in which the Bidirectional Associative Memory (BAM) algorithms are implemented is presented here. We will show that by utilizing the singular value decomposition (SVD) and integrating principles of independent component analysis (ICA) into the nullspace (NS) we have created a novel approach to mitigating spurious attractors. We demonstrate this with two applications. The first application utilizes a one-layer association while the second application is modeled after the several hierarchal associations of ventral pathways. The first application will detail the way in which we manage the associations in terms of matrices. The second application will take what we have learned from the first example and apply it to a cascade of a convolutional neural network (CNN) and perceptron this being our signal processing model of the ventral pathways, i.e., visual systems.

Independent Events in Elementary Probability Theory

ERIC Educational Resources Information Center

Csenki, Attila

2011-01-01

In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): If the n events E[subscript 1],…

Tensorial extensions of independent component analysis for multisubject FMRI analysis.

PubMed

Beckmann, C F; Smith, S M

2005-03-01

We discuss model-free analysis of multisubject or multisession FMRI data by extending the single-session probabilistic independent component analysis model (PICA; Beckmann and Smith, 2004. IEEE Trans. on Medical Imaging, 23 (2) 137-152) to higher dimensions. This results in a three-way decomposition that represents the different signals and artefacts present in the data in terms of their temporal, spatial, and subject-dependent variations. The technique is derived from and compared with parallel factor analysis (PARAFAC; Harshman and Lundy, 1984. In Research methods for multimode data analysis, chapter 5, pages 122-215. Praeger, New York). Using simulated data as well as data from multisession and multisubject FMRI studies we demonstrate that the tensor PICA approach is able to efficiently and accurately extract signals of interest in the spatial, temporal, and subject/session domain. The final decompositions improve upon PARAFAC results in terms of greater accuracy, reduced interference between the different estimated sources (reduced cross-talk), robustness (against deviations of the data from modeling assumptions and against overfitting), and computational speed. On real FMRI 'activation' data, the tensor PICA approach is able to extract plausible activation maps, time courses, and session/subject modes as well as provide a rich description of additional processes of interest such as image artefacts or secondary activation patterns. The resulting data decomposition gives simple and useful representations of multisubject/multisession FMRI data that can aid the interpretation and optimization of group FMRI studies beyond what can be achieved using model-based analysis techniques.

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

PubMed Central

Zhu, Xuqi; Liu, Yu; Zhang, Lin

2009-01-01

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency. PMID:22408560

Characterization of Nitinol Laser-Weld Joints by Nondestructive Testing

NASA Astrophysics Data System (ADS)

Wohlschlögel, Markus; Gläßel, Gunter; Sanchez, Daniela; Schüßler, Andreas; Dillenz, Alexander; Saal, David; Mayr, Peter

2015-12-01

Joining technology is an integral part of today's Nitinol medical device manufacturing. Besides crimping and riveting, laser welding is often applied to join components made from Nitinol to Nitinol, as well as Nitinol components to dissimilar materials. Other Nitinol joining techniques include adhesive bonding, soldering, and brazing. Typically, the performance of joints is assessed by destructive mechanical testing, on a process validation base. In this study, a nondestructive testing method—photothermal radiometry—is applied to characterize small Nitinol laser-weld joints used to connect two wire ends via a sleeve. Two different wire diameters are investigated. Effective joint connection cross sections are visualized using metallography techniques. Results of the nondestructive testing are correlated to data from destructive torsion testing, where the maximum torque at fracture is evaluated for the same joints and criteria for the differentiation of good and poor laser-welding quality by nondestructive testing are established.

Independent Component Analysis of Resting-State Functional Magnetic Resonance Imaging in Pedophiles.

PubMed

Cantor, J M; Lafaille, S J; Hannah, J; Kucyi, A; Soh, D W; Girard, T A; Mikulis, D J

2016-10-01

Neuroimaging and other studies have changed the common view that pedophilia is a result of childhood sexual abuse and instead is a neurologic phenomenon with prenatal origins. Previous research has identified differences in the structural connectivity of the brain in pedophilia. To identify analogous differences in functional connectivity. Functional magnetic resonance images were recorded from three groups of participants while they were at rest: pedophilic men with a history of sexual offenses against children (n = 37) and two control groups: non-pedophilic men who committed non-sexual offenses (n = 28) and non-pedophilic men with no criminal history (n = 39). Functional magnetic resonance imaging data were subjected to independent component analysis to identify known functional networks of the brain, and groups were compared to identify differences in connectivity with those networks (or "components"). The pedophilic group demonstrated wide-ranging increases in functional connectivity with the default mode network compared with controls and regional differences (increases and decreases) with the frontoparietal network. Of these brain regions (total = 23), 20 have been identified by meta-analytic studies to respond to sexually relevant stimuli. Conversely, of the brain areas known to be those that respond to sexual stimuli, nearly all emerged in the present data as significantly different in pedophiles. This study confirms the presence of significant differences in the functional connectivity of the brain in pedophilia consistent with previously reported differences in structural connectivity. The connectivity differences detected here and elsewhere are opposite in direction from those associated with anti-sociality, arguing against anti-sociality and for pedophilia as the source of the neuroanatomic differences detected. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

DEMES rotary joint: theories and applications

NASA Astrophysics Data System (ADS)

Wang, Shu; Hao, Zhaogang; Li, Mingyu; Huang, Bo; Sun, Lining; Zhao, Jianwen

2017-04-01

As a kind of dielectric elastomer actuators, dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by small voltage-induced strains, which make them an attractive candidate for use as biomimetic robotics. Considering the rotary joint is a basic and common component of many biomimetic robots, we have been fabricated rotary joint by DEMES and developed its performances in the past two years. In this paper, we have discussed the static analysis, dynamics analysis and some characteristics of the DEMES rotary joint. Based on theoretical analysis, some different applications of the DEMES rotary joint were presented, such as a flapping wing, a biomimetic fish and a two-legged walker. All of the robots are fabricated by DEMES rotary joint and can realize some basic biomimetic motions. Comparing with traditional rigid robot, the robot based on DEMES is soft and light, so it has advantage on the collision-resistant.

Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

PubMed Central

Qi, Shile; Calhoun, Vince D.; van Erp, Theo G. M.; Bustillo, Juan; Damaraju, Eswar; Turner, Jessica A.; Du, Yuhui; Chen, Jiayu; Yu, Qingbao; Mathalon, Daniel H.; Ford, Judith M.; Voyvodic, James; Mueller, Bryon A.; Belger, Aysenil; Ewen, Sarah Mc; Potkin, Steven G.; Preda, Adrian; Jiang, Tianzi

2017-01-01

Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. To date, there is increasing interest to uncover the neurocognitive mapping of specific behavioral measurement on enriched brain imaging data; hence, a supervised, goal-directed model that enables a priori information as a reference to guide multimodal data fusion is in need and a natural option. Here we proposed a fusion with reference model, called “multi-site canonical correlation analysis with reference plus joint independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to reference information, such as cognitive scores. In a 3-way fusion simulation, the proposed method was compared with its alternatives on estimation accuracy of both target component decomposition and modality linkage detection. MCCAR+jICA outperforms others with higher precision. In human imaging data, working memory performance was utilized as a reference to investigate the covarying functional and structural brain patterns among 3 modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Interestingly, similar brain maps were identified between the two cohorts, with substantial overlap in the executive control networks in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports, while MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the potential of such results to identify potential neuromarkers for mental disorders. PMID:28708547

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

PubMed

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

Decomposition of spontaneous fluctuations in tumour oxygenation using BOLD MRI and independent component analysis

PubMed Central

Gonçalves, Miguel R; Johnson, S Peter; Ramasawmy, Rajiv; Pedley, R Barbara; Lythgoe, Mark F; Walker-Samuel, Simon

2015-01-01

Background: Solid tumours can undergo cycles of hypoxia, followed by reoxygenation, which can have significant implications for the success of anticancer therapies. A need therefore exists to develop methods to aid its detection and to further characterise its biological basis. We present here a novel method for decomposing systemic and tumour-specific contributions to fluctuations in tumour deoxyhaemoglobin concentration, based on magnetic resonance imaging measurements. Methods: Fluctuations in deoxyhaemoglobin concentration in two tumour xenograft models of colorectal carcinoma were decomposed into distinct contributions using independent component analysis. These components were then correlated with systemic pulse oximetry measurements to assess the influence of systemic variations in blood oxygenation in tumours, compared with those that arise within the tumour itself (tumour-specific). Immunohistochemical staining was used to assess the physiological basis of each source of fluctuation. Results: Systemic fluctuations in blood oxygenation were found to contribute to cycling hypoxia in tumours, but tumour-specific fluctuations were also evident. Moreover, the size of the tumours was found to influence the degree of systemic, but not tumour-specific, oscillations. The degree of vessel maturation was related to the amplitude of tumour-specific, but not systemic, oscillations. Conclusions: Our results provide further insights into the complexity of spontaneous fluctuations in tumour oxygenation and its relationship with tumour pathophysiology. These observations could be used to develop improved drug delivery strategies. PMID:26484634

Adhesive properties and adhesive joints strength of graphite/epoxy composites

NASA Astrophysics Data System (ADS)

Rudawska, Anna; Stančeková, Dana; Cubonova, Nadezda; Vitenko, Tetiana; Müller, Miroslav; Valášek, Petr

2017-05-01

The article presents the results of experimental research of the adhesive joints strength of graphite/epoxy composites and the results of the surface free energy of the composite surfaces. Two types of graphite/epoxy composites with different thickness were tested which are used to aircraft structure. The single-lap adhesive joints of epoxy composites were considered. Adhesive properties were described by surface free energy. Owens-Wendt method was used to determine surface free energy. The epoxy two-component adhesive was used to preparing the adhesive joints. Zwick/Roell 100 strength device were used to determination the shear strength of adhesive joints of epoxy composites. The strength test results showed that the highest value was obtained for adhesive joints of graphite-epoxy composite of smaller material thickness (0.48 mm). Statistical analysis of the results obtained, the study showed statistically significant differences between the values of the strength of the confidence level of 0.95. The statistical analysis of the results also showed that there are no statistical significant differences in average values of surface free energy (0.95 confidence level). It was noted that in each of the results the dispersion component of surface free energy was much greater than polar component of surface free energy.

Clinical synovitis in a particular joint is associated with progression of erosions and joint space narrowing in that same joint, but not in patients initially treated with infliximab.

PubMed

Klarenbeek, N B; Güler-Yüksel, M; van der Heijde, D M F M; Hulsmans, H M J; Kerstens, P J S M; Molenaar, T H E; de Sonnaville, P B J; Huizinga, T W J; Dijkmans, B A C; Allaart, C F

2010-12-01

To assess the relationship between joint tenderness, swelling and joint damage progression in individual joints and to evaluate the influence of treatment on these relationships. First-year data of the Behandel Strategieën (BeSt) study were used, in which patients recently diagnosed as having rheumatoid arthritis (RA) were randomly assigned into four different treatment strategies. Baseline and 1-year x-rays of the hands and feet were assessed using the Sharp-van der Heijde score (SHS). With generalised estimating equations, 3-monthly assessments of tender and swollen joints of year 1 were related to erosion progression, joint space narrowing (JSN) progression and total SHS progression at the individual joint level (definition > 0.5 SHS units) in year 1, corrected for potential confounders and within-patient correlation for multiple joints per patient. During year 1, 59% of all 13 959 joints analysed were ever tender and 45% ever swollen, 2.1% showed erosion progression, 1.9% JSN progression and 3.6% SHS progression. Swelling and tenderness were both independently associated with erosion and JSN progression with comparable OR, although with higher OR in the hands than in the feet. Local swelling and tenderness were not associated with local damage progression in patients initially treated with infliximab. Clinical signs of synovitis are associated with erosion and JSN progression in individual joints after 1 year in RA. A disconnect between synovitis and joint damage progression was observed at joint level in patients who were treated with methotrexate and infliximab as initial treatment, confirming the disconnect between synovitis and the development of joint damage in tumour necrosis factor blockers seen at patient level.

[Fetal bone and joint disorders].

PubMed

Jakobovits, Akos

2008-12-21

The article discusses the physiology and pathology of fetal bone and joint development and functions. The bones provide static support for the body. The skull and the bones of spinal column encase the central and part of the peripheral nervous system. The ribs and the sternum shield the heart and the lungs, while the bones of the pelvis protect the intraabdominal organs. Pathological changes of these bony structures may impair the functions of the respective systems or internal organs. Movements of the bones are brought about by muscles. The deriving motions are facilitated by joints. Bony anomalies of the extremities limit their effective functions. Apart from skeletal and joint abnormalities, akinesia may also be caused by neurological, muscular and skin diseases that secondarily affect the functions of bones and joints. Such pathological changes may lead to various degrees of physical disability and even to death. Some of the mentioned anomalies are recognizable in utero by ultrasound. The diagnosis may serve as medical indication for abortion in those instances when the identified abnormality is incompatible with independent life.

Risk of false decision on conformity of a multicomponent material when test results of the components' content are correlated.

PubMed

Kuselman, Ilya; Pennecchi, Francesca R; da Silva, Ricardo J N B; Hibbert, D Brynn

2017-11-01

The probability of a false decision on conformity of a multicomponent material due to measurement uncertainty is discussed when test results are correlated. Specification limits of the components' content of such a material generate a multivariate specification interval/domain. When true values of components' content and corresponding test results are modelled by multivariate distributions (e.g. by multivariate normal distributions), a total global risk of a false decision on the material conformity can be evaluated based on calculation of integrals of their joint probability density function. No transformation of the raw data is required for that. A total specific risk can be evaluated as the joint posterior cumulative function of true values of a specific batch or lot lying outside the multivariate specification domain, when the vector of test results, obtained for the lot, is inside this domain. It was shown, using a case study of four components under control in a drug, that the correlation influence on the risk value is not easily predictable. To assess this influence, the evaluated total risk values were compared with those calculated for independent test results and also with those assuming much stronger correlation than that observed. While the observed statistically significant correlation did not lead to a visible difference in the total risk values in comparison to the independent test results, the stronger correlation among the variables caused either the total risk decreasing or its increasing, depending on the actual values of the test results. Copyright © 2017 Elsevier B.V. All rights reserved.

Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

NASA Astrophysics Data System (ADS)

Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

2018-04-01

Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

Detailed investigation of Long-Period activity at Campi Flegrei by Convolutive Independent Component Analysis

NASA Astrophysics Data System (ADS)

Capuano, P.; De Lauro, E.; De Martino, S.; Falanga, M.

2016-04-01

This work is devoted to the analysis of seismic signals continuously recorded at Campi Flegrei Caldera (Italy) during the entire year 2006. The radiation pattern associated with the Long-Period energy release is investigated. We adopt an innovative Independent Component Analysis algorithm for convolutive seismic series adapted and improved to give automatic procedures for detecting seismic events often buried in the high-level ambient noise. The extracted waveforms characterized by an improved signal-to-noise ratio allows the recognition of Long-Period precursors, evidencing that the seismic activity accompanying the mini-uplift crisis (in 2006), which climaxed in the three days from 26-28 October, had already started at the beginning of the month of October and lasted until mid of November. Hence, a more complete seismic catalog is then provided which can be used to properly quantify the seismic energy release. To better ground our results, we first check the robustness of the method by comparing it with other blind source separation methods based on higher order statistics; secondly, we reconstruct the radiation patterns of the extracted Long-Period events in order to link the individuated signals directly to the sources. We take advantage from Convolutive Independent Component Analysis that provides basic signals along the three directions of motion so that a direct polarization analysis can be performed with no other filtering procedures. We show that the extracted signals are mainly composed of P waves with radial polarization pointing to the seismic source of the main LP swarm, i.e. a small area in the Solfatara, also in the case of the small-events, that both precede and follow the main activity. From a dynamical point of view, they can be described by two degrees of freedom, indicating a low-level of complexity associated with the vibrations from a superficial hydrothermal system. Our results allow us to move towards a full description of the complexity of

Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

PubMed

López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

2015-04-15

Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling joint restoration strategies for interdependent infrastructure systems

PubMed Central

Simonovic, Slobodan P.

2018-01-01

Life in the modern world depends on multiple critical services provided by infrastructure systems which are interdependent at multiple levels. To effectively respond to infrastructure failures, this paper proposes a model for developing optimal joint restoration strategy for interdependent infrastructure systems following a disruptive event. First, models for (i) describing structure of interdependent infrastructure system and (ii) their interaction process, are presented. Both models are considering the failure types, infrastructure operating rules and interdependencies among systems. Second, an optimization model for determining an optimal joint restoration strategy at infrastructure component level by minimizing the economic loss from the infrastructure failures, is proposed. The utility of the model is illustrated using a case study of electric-water systems. Results show that a small number of failed infrastructure components can trigger high level failures in interdependent systems; the optimal joint restoration strategy varies with failure occurrence time. The proposed models can help decision makers to understand the mechanisms of infrastructure interactions and search for optimal joint restoration strategy, which can significantly enhance safety of infrastructure systems. PMID:29649300

Modeling joint restoration strategies for interdependent infrastructure systems.

PubMed

Zhang, Chao; Kong, Jingjing; Simonovic, Slobodan P

2018-01-01

Life in the modern world depends on multiple critical services provided by infrastructure systems which are interdependent at multiple levels. To effectively respond to infrastructure failures, this paper proposes a model for developing optimal joint restoration strategy for interdependent infrastructure systems following a disruptive event. First, models for (i) describing structure of interdependent infrastructure system and (ii) their interaction process, are presented. Both models are considering the failure types, infrastructure operating rules and interdependencies among systems. Second, an optimization model for determining an optimal joint restoration strategy at infrastructure component level by minimizing the economic loss from the infrastructure failures, is proposed. The utility of the model is illustrated using a case study of electric-water systems. Results show that a small number of failed infrastructure components can trigger high level failures in interdependent systems; the optimal joint restoration strategy varies with failure occurrence time. The proposed models can help decision makers to understand the mechanisms of infrastructure interactions and search for optimal joint restoration strategy, which can significantly enhance safety of infrastructure systems.

Independent component analysis for cochlear implant artifacts attenuation from electrically evoked auditory steady-state response measurements

NASA Astrophysics Data System (ADS)

Deprez, Hanne; Gransier, Robin; Hofmann, Michael; van Wieringen, Astrid; Wouters, Jan; Moonen, Marc

2018-02-01

Objective. Electrically evoked auditory steady-state responses (EASSRs) are potentially useful for objective cochlear implant (CI) fitting and follow-up of the auditory maturation in infants and children with a CI. EASSRs are recorded in the electro-encephalogram (EEG) in response to electrical stimulation with continuous pulse trains, and are distorted by significant CI artifacts related to this electrical stimulation. The aim of this study is to evaluate a CI artifacts attenuation method based on independent component analysis (ICA) for three EASSR datasets. Approach. ICA has often been used to remove CI artifacts from the EEG to record transient auditory responses, such as cortical evoked auditory potentials. Independent components (ICs) corresponding to CI artifacts are then often manually identified. In this study, an ICA based CI artifacts attenuation method was developed and evaluated for EASSR measurements with varying CI artifacts and EASSR characteristics. Artifactual ICs were automatically identified based on their spectrum. Main results. For 40 Hz amplitude modulation (AM) stimulation at comfort level, in high SNR recordings, ICA succeeded in removing CI artifacts from all recording channels, without distorting the EASSR. For lower SNR recordings, with 40 Hz AM stimulation at lower levels, or 90 Hz AM stimulation, ICA either distorted the EASSR or could not remove all CI artifacts in most subjects, except for two of the seven subjects tested with low level 40 Hz AM stimulation. Noise levels were reduced after ICA was applied, and up to 29 ICs were rejected, suggesting poor ICA separation quality. Significance. We hypothesize that ICA is capable of separating CI artifacts and EASSR in case the contralateral hemisphere is EASSR dominated. For small EASSRs or large CI artifact amplitudes, ICA separation quality is insufficient to ensure complete CI artifacts attenuation without EASSR distortion.

Identifying Rodent Resting-State Brain Networks with Independent Component Analysis

PubMed Central

Bajic, Dusica; Craig, Michael M.; Mongerson, Chandler R. L.; Borsook, David; Becerra, Lino

2017-01-01

Rodent models have opened the door to a better understanding of the neurobiology of brain disorders and increased our ability to evaluate novel treatments. Resting-state functional magnetic resonance imaging (rs-fMRI) allows for in vivo exploration of large-scale brain networks with high spatial resolution. Its application in rodents affords researchers a powerful translational tool to directly assess/explore the effects of various pharmacological, lesion, and/or disease states on known neural circuits within highly controlled settings. Integration of animal and human research at the molecular-, systems-, and behavioral-levels using diverse neuroimaging techniques empowers more robust interrogations of abnormal/ pathological processes, critical for evolving our understanding of neuroscience. We present a comprehensive protocol to evaluate resting-state brain networks using Independent Component Analysis (ICA) in rodent model. Specifically, we begin with a brief review of the physiological basis for rs-fMRI technique and overview of rs-fMRI studies in rodents to date, following which we provide a robust step-by-step approach for rs-fMRI investigation including data collection, computational preprocessing, and brain network analysis. Pipelines are interwoven with underlying theory behind each step and summarized methodological considerations, such as alternative methods available and current consensus in the literature for optimal results. The presented protocol is designed in such a way that investigators without previous knowledge in the field can implement the analysis and obtain viable results that reliably detect significant differences in functional connectivity between experimental groups. Our goal is to empower researchers to implement rs-fMRI in their respective fields by incorporating technical considerations to date into a workable methodological framework. PMID:29311770

Fully automated registration of first-pass myocardial perfusion MRI using independent component analysis.

PubMed

Milles, J; van der Geest, R J; Jerosch-Herold, M; Reiber, J H C; Lelieveldt, B P F

2007-01-01

This paper presents a novel method for registration of cardiac perfusion MRI. The presented method successfully corrects for breathing motion without any manual interaction using Independent Component Analysis to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of ICA, and used to compute the displacement caused by breathing for each frame. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Validation experiments showed a reduction of the average LV motion from 1.26+/-0.87 to 0.64+/-0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65+/-7.89% to 0.87+/-3.88% between registered data and manual gold standard. We conclude that this fully automatic ICA-based method shows an excellent accuracy, robustness and computation speed, adequate for use in a clinical environment.

21 CFR 888.3680 - Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Shoulder joint glenoid (hemi-shoulder) metallic... Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis. (a) Identification. A shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis is a device that has a glenoid (socket) component...

21 CFR 888.3680 - Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Shoulder joint glenoid (hemi-shoulder) metallic... Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis. (a) Identification. A shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis is a device that has a glenoid (socket) component...

21 CFR 888.3680 - Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Shoulder joint glenoid (hemi-shoulder) metallic... Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis. (a) Identification. A shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis is a device that has a glenoid (socket) component...

21 CFR 888.3680 - Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Shoulder joint glenoid (hemi-shoulder) metallic... Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis. (a) Identification. A shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis is a device that has a glenoid (socket) component...

21 CFR 888.3680 - Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Shoulder joint glenoid (hemi-shoulder) metallic... Shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis. (a) Identification. A shoulder joint glenoid (hemi-shoulder) metallic cemented prosthesis is a device that has a glenoid (socket) component...

The Standard Joint Unit.

PubMed

Casajuana Kögel, Cristina; Balcells-Olivero, María Mercedes; López-Pelayo, Hugo; Miquel, Laia; Teixidó, Lídia; Colom, Joan; Nutt, David John; Rehm, Jürgen; Gual, Antoni

2017-07-01

Reliable data on cannabis quantities is required to improve assessment of cannabis consumption for epidemiological analysis and clinical assessment, consequently a Standard Joint Unit (SJU) based on quantity of 9-Tetrahydrocannabinol (9-THC) has been established. Naturalistic study of a convenience sample recruited from February 2015-June 2016 in universities, leisure spaces, mental health services and cannabis clubs in Barcelona. Adults, reporting cannabis use in the last 60 days, without cognitive impairment or language barriers, answered a questionnaire on cannabis use and were asked to donate a joint to further determine their 9-THC and Cannabidiol (CBD) content. 492 participants donated 315 valid joints. Donators were on average 29 years old, mostly men (77%), single (75%), with at least secondary studies (73%) and in active employment (63%). Marijuana joints (N=232) contained a median of 6.56mg of 9-THC (Interquartile range-IQR=10,22) and 0.02mg of CBD (IQR=0.02); hashish joints (N=83) a median of 7.94mg of 9-THC (IQR=10,61) and 3.24mg of CBD (IQR=3.21). Participants rolled 4 joints per gram of cannabis and paid 5€ per gram (median values). Consistent 9-THC-content in joints lead to a SJU of 7mg of 9-THC, the integer number closest to the median values shared by both cannabis types. Independently if marijuana or hashish, 1 SJU = 1 joint = 0.25 g of cannabis = 7 mg of 9-THC. For CBD, only hashish SJU contained relevant levels. Similarly to the Standard Drink Unit for alcohol, the SJU is useful for clinical, epidemiological and research purposes. Copyright © 2017 Elsevier B.V. All rights reserved.

Saipan and Joint Operations

DTIC Science & Technology

1990-02-12

following postwar joint education objectives for ths armed forces: Objective i: To oroduce within each component of the armed forces a general knowledge...had acquired the pradtical knowledge to establieh::thvoe Joint educational goals which are as relevant today as when they were written. ENDNOTES 1...F2:", (- 1-1 1’A I’rn ,r’ lqA ,! Vim l ;` thO? C’~~~~~~~ a m in A i h9%t ý A din r, a INi m i t z% "h e haa I.z a:wn naval. +ac! lit! es, line~i n+f

A parametric shell analysis of the shuttle 51-L SRB AFT field joint

NASA Technical Reports Server (NTRS)

Davis, Randall C.; Bowman, Lynn M.; Hughes, Robert M., IV; Jackson, Brian J.

1990-01-01

Following the Shuttle 51-L accident, an investigation was conducted to determine the cause of the failure. Investigators at the Langley Research Center focused attention on the structural behavior of the field joints with O-ring seals in the steel solid rocket booster (SRB) cases. The shell-of-revolution computer program BOSOR4 was used to model the aft field joint of the solid rocket booster case. The shell model consisted of the SRB wall and joint geometry present during the Shuttle 51-L flight. A parametric study of the joint was performed on the geometry, including joint clearances, contact between the joint components, and on the loads, induced and applied. In addition combinations of geometry and loads were evaluated. The analytical results from the parametric study showed that contact between the joint components was a primary contributor to allowing hot gases to blow by the O-rings. Based upon understanding the original joint behavior, various proposed joint modifications are shown and analyzed in order to provide additional insight and information. Finally, experimental results from a hydro-static pressurization of a test rocket booster case to study joint motion are presented and verified analytically.

Electrically evoked compound action potentials artefact rejection by independent component analysis: procedure automation.

PubMed

Akhoun, Idrick; McKay, Colette; El-Deredy, Wael

2015-01-15

Independent-components-analysis (ICA) successfully separated electrically-evoked compound action potentials (ECAPs) from the stimulation artefact and noise (ECAP-ICA, Akhoun et al., 2013). This paper shows how to automate the ECAP-ICA artefact cancellation process. Raw-ECAPs without artefact rejection were consecutively recorded for each stimulation condition from at least 8 intra-cochlear electrodes. Firstly, amplifier-saturated recordings were discarded, and the data from different stimulus conditions (different current-levels) were concatenated temporally. The key aspect of the automation procedure was the sequential deductive source categorisation after ICA was applied with a restriction to 4 sources. The stereotypical aspect of the 4 sources enables their automatic classification as two artefact components, a noise and the sought ECAP based on theoretical and empirical considerations. The automatic procedure was tested using 8 cochlear implant (CI) users and one to four stimulus electrodes. The artefact and noise sources were successively identified and discarded, leaving the ECAP as the remaining source. The automated ECAP-ICA procedure successfully extracted the correct ECAPs compared to standard clinical forward masking paradigm in 22 out of 26 cases. ECAP-ICA does not require extracting the ECAP from a combination of distinct buffers as it is the case with regular methods. It is an alternative that does not have the possible bias of traditional artefact rejections such as alternate-polarity or forward-masking paradigms. The ECAP-ICA procedure bears clinical relevance, for example as the artefact rejection sub-module of automated ECAP-threshold detection techniques, which are common features of CI clinical fitting software. Copyright © 2014. Published by Elsevier B.V.

Recovering fNIRS brain signals: physiological interference suppression with independent component analysis

NASA Astrophysics Data System (ADS)

Zhang, Y.; Shi, M.; Sun, J.; Yang, C.; Zhang, Yajuan; Scopesi, F.; Makobore, P.; Chin, C.; Serra, G.; Wickramasinghe, Y. A. B. D.; Rolfe, P.

2015-02-01

Brain activity can be monitored non-invasively by functional near-infrared spectroscopy (fNIRS), which has several advantages in comparison with other methods, such as flexibility, portability, low cost and fewer physical restrictions. However, in practice fNIRS measurements are often contaminated by physiological interference arising from cardiac contraction, breathing and blood pressure fluctuations, thereby severely limiting the utility of the method. Hence, further improvement is necessary to reduce or eliminate such interference in order that the evoked brain activity information can be extracted reliably from fNIRS data. In the present paper, the multi-distance fNIRS probe configuration has been adopted. The short-distance fNIRS measurement is treated as the virtual channel and the long-distance fNIRS measurement is treated as the measurement channel. Independent component analysis (ICA) is employed for the fNIRS recordings to separate the brain signals and the interference. Least-absolute deviation (LAD) estimator is employed to recover the brain activity signals. We also utilized Monte Carlo simulations based on a five-layer model of the adult human head to evaluate our methodology. The results demonstrate that the ICA algorithm has the potential to separate physiological interference in fNIRS data and the LAD estimator could be a useful criterion to recover the brain activity signals.

Real-time Adaptive EEG Source Separation using Online Recursive Independent Component Analysis

PubMed Central

Hsu, Sheng-Hsiou; Mullen, Tim; Jung, Tzyy-Ping; Cauwenberghs, Gert

2016-01-01

Independent Component Analysis (ICA) has been widely applied to electroencephalographic (EEG) biosignal processing and brain-computer interfaces. The practical use of ICA, however, is limited by its computational complexity, data requirements for convergence, and assumption of data stationarity, especially for high-density data. Here we study and validate an optimized online recursive ICA algorithm (ORICA) with online recursive least squares (RLS) whitening for blind source separation of high-density EEG data, which offers instantaneous incremental convergence upon presentation of new data. Empirical results of this study demonstrate the algorithm's: (a) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; (b) capability to detect and adapt to non-stationarity in 64-ch simulated EEG data; and (c) utility for rapidly extracting principal brain and artifact sources in real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment. ORICA was implemented as functions in BCILAB and EEGLAB and was integrated in an open-source Real-time EEG Source-mapping Toolbox (REST), supporting applications in ICA-based online artifact rejection, feature extraction for real-time biosignal monitoring in clinical environments, and adaptable classifications in brain-computer interfaces. PMID:26685257

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

NASA Astrophysics Data System (ADS)

Lee, Dong-Sup; Cho, Dae-Seung; Kim, Kookhyun; Jeon, Jae-Jin; Jung, Woo-Jin; Kang, Myeng-Hwan; Kim, Jae-Ho

2015-01-01

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Comparing brain graphs in which nodes are regions of interest or independent components: A simulation study.

PubMed

Yu, Qingbao; Du, Yuhui; Chen, Jiayu; He, Hao; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D

2017-11-01

A key challenge in building a brain graph using fMRI data is how to define the nodes. Spatial brain components estimated by independent components analysis (ICA) and regions of interest (ROIs) determined by brain atlas are two popular methods to define nodes in brain graphs. It is difficult to evaluate which method is better in real fMRI data. Here we perform a simulation study and evaluate the accuracies of a few graph metrics in graphs with nodes of ICA components, ROIs, or modified ROIs in four simulation scenarios. Graph measures with ICA nodes are more accurate than graphs with ROI nodes in all cases. Graph measures with modified ROI nodes are modulated by artifacts. The correlations of graph metrics across subjects between graphs with ICA nodes and ground truth are higher than the correlations between graphs with ROI nodes and ground truth in scenarios with large overlapped spatial sources. Moreover, moving the location of ROIs would largely decrease the correlations in all scenarios. Evaluating graphs with different nodes is promising in simulated data rather than real data because different scenarios can be simulated and measures of different graphs can be compared with a known ground truth. Since ROIs defined using brain atlas may not correspond well to real functional boundaries, overall findings of this work suggest that it is more appropriate to define nodes using data-driven ICA than ROI approaches in real fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Limited independent flexion of the thumb and fingers in human subjects.

PubMed Central

Kilbreath, S L; Gandevia, S C

1994-01-01

1. We investigated whether human subjects can activate selectively flexor pollicis longus (FPL) and digital portions of flexor digitorum profundus (FDP). These muscles were selected because they are the only flexors of the distal phalanges. 2. Electromyographic activity (EMG) was recorded with intramuscular electrodes from one digital component of the deep flexors ('test') while subjects lifted weights by flexing the distal interphalangeal joint of the other digits in turn ('lifting' digits). Only recording sites at which single motor units were recruited selectively at low forces were used. The weights lifted represented 2.5-50% of the maximal voluntary contraction (MVC). We measured the lowest weight lifted which produced phasic and tonic coactivation in the 'test' muscle. 3. The extent of coactivation varied with the 'distance' between the test and lifting digits although no significant difference occurred in the pattern of coactivation thresholds among the digital flexors. The extent of coactivation increased when angular displacement or velocity at the distal interphalangeal joint of the lifting digit increased but was not critically dependent on restraint of the hand. 4. Because mechanical 'connections' could interfere with the ability to move a distal phalanx independently, the arms of nine cadavers were studied. The separation of tendons between the thumb (FPL) and the index portion of FDP, and between the index and middle portions of FDP, usually extended more proximally in the forearm than separation between the tendons to the middle and ring fingers and between the ring and little fingers. Direct intertendinous links were also noted. 5. It is not possible to direct a sufficiently focal motor command to flex selectively the distal joint of the fingers and thumb when forces exceeding 2.5% MVC are generated. For the middle, ring and little fingers in particular, movement of adjacent digits may also involve 'in-series' mechanical links between adjacent

Vacuum Brazing of Accelerator Components

NASA Astrophysics Data System (ADS)

Singh, Rajvir; Pant, K. K.; Lal, Shankar; Yadav, D. P.; Garg, S. R.; Raghuvanshi, V. K.; Mundra, G.

2012-11-01

Commonly used materials for accelerator components are those which are vacuum compatible and thermally conductive. Stainless steel, aluminum and copper are common among them. Stainless steel is a poor heat conductor and not very common in use where good thermal conductivity is required. Aluminum and copper and their alloys meet the above requirements and are frequently used for the above purpose. The accelerator components made of aluminum and its alloys using welding process have become a common practice now a days. It is mandatory to use copper and its other grades in RF devices required for accelerators. Beam line and Front End components of the accelerators are fabricated from stainless steel and OFHC copper. Fabrication of components made of copper using welding process is very difficult and in most of the cases it is impossible. Fabrication and joining in such cases is possible using brazing process especially under vacuum and inert gas atmosphere. Several accelerator components have been vacuum brazed for Indus projects at Raja Ramanna Centre for Advanced Technology (RRCAT), Indore using vacuum brazing facility available at RRCAT, Indore. This paper presents details regarding development of the above mentioned high value and strategic components/assemblies. It will include basics required for vacuum brazing, details of vacuum brazing facility, joint design, fixturing of the jobs, selection of filler alloys, optimization of brazing parameters so as to obtain high quality brazed joints, brief description of vacuum brazed accelerator components etc.

Joint Optimization of Vertical Component Gravity and Seismic P-wave First Arrivals by Simulated Annealing

NASA Astrophysics Data System (ADS)

Louie, J. N.; Basler-Reeder, K.; Kent, G. M.; Pullammanappallil, S. K.

2015-12-01

Simultaneous joint seismic-gravity optimization improves P-wave velocity models in areas with sharp lateral velocity contrasts. Optimization is achieved using simulated annealing, a metaheuristic global optimization algorithm that does not require an accurate initial model. Balancing the seismic-gravity objective function is accomplished by a novel approach based on analysis of Pareto charts. Gravity modeling uses a newly developed convolution algorithm, while seismic modeling utilizes the highly efficient Vidale eikonal equation traveltime generation technique. Synthetic tests show that joint optimization improves velocity model accuracy and provides velocity control below the deepest headwave raypath. Detailed first arrival picking followed by trial velocity modeling remediates inconsistent data. We use a set of highly refined first arrival picks to compare results of a convergent joint seismic-gravity optimization to the Plotrefa™ and SeisOpt® Pro™ velocity modeling packages. Plotrefa™ uses a nonlinear least squares approach that is initial model dependent and produces shallow velocity artifacts. SeisOpt® Pro™ utilizes the simulated annealing algorithm and is limited to depths above the deepest raypath. Joint optimization increases the depth of constrained velocities, improving reflector coherency at depth. Kirchoff prestack depth migrations reveal that joint optimization ameliorates shallow velocity artifacts caused by limitations in refraction ray coverage. Seismic and gravity data from the San Emidio Geothermal field of the northwest Basin and Range province demonstrate that joint optimization changes interpretation outcomes. The prior shallow-valley interpretation gives way to a deep valley model, while shallow antiformal reflectors that could have been interpreted as antiformal folds are flattened. Furthermore, joint optimization provides a clearer image of the rangefront fault. This technique can readily be applied to existing datasets and could

Joint Inversion of Gravity and Gravity Tensor Data Using the Structural Index as Weighting Function Rate Decay

NASA Astrophysics Data System (ADS)

Ialongo, S.; Cella, F.; Fedi, M.; Florio, G.

2011-12-01

Most geophysical inversion problems are characterized by a number of data considerably higher than the number of the unknown parameters. This corresponds to solve highly underdetermined systems. To get a unique solution, a priori information must be therefore introduced. We here analyze the inversion of the gravity gradient tensor (GGT). Previous approaches to invert jointly or independently more gradient components are by Li (2001) proposing an algorithm using a depth weighting function and Zhdanov et alii (2004), providing a well focused inversion of gradient data. Both the methods give a much-improved solution compared with the minimum length solution, which is invariably shallow and not representative of the true source distribution. For very undetermined problems, this feature is due to the role of the depth weighting matrices used by both the methods. Recently, Cella and Fedi (2011) showed however that for magnetic and gravity data the depth weighting function has to be defined carefully, under a preliminary application of Euler Deconvolution or Depth from Extreme Point methods, yielding the appropriate structural index and then using it as the rate decay of the weighting function. We therefore propose to extend this last approach to invert jointly or independently the GGT tensor using the structural index as weighting function rate decay. In case of a joint inversion, gravity data can be added as well. This multicomponent case is also relevant because the simultaneous use of several components and gravity increase the number of data and reduce the algebraic ambiguity compared to the inversion of a single component. The reduction of such ambiguity was shown in Fedi et al, (2005) decisive to get an improved depth resolution in inverse problems, independently from any form of depth weighting function. The method is demonstrated to synthetic cases and applied to real cases, such as the Vredefort impact area (South Africa), characterized by a complex density

Influence of step length and landing pattern on patellofemoral joint kinetics during running.

PubMed

Willson, J D; Ratcliff, O M; Meardon, S A; Willy, R W

2015-12-01

Elevated patellofemoral joint kinetics during running may contribute to patellofemoral joint symptoms. The purpose of this study was to test for independent effects of foot strike pattern and step length on patellofemoral joint kinetics while running. Effects were tested relative to individual steps and also taking into account the number of steps required to run a kilometer with each step length. Patellofemoral joint reaction force and stress were estimated in 20 participants running at their preferred speed. Participants ran using a forefoot strike and rearfoot strike pattern during three different step length conditions: preferred step length, long (+10%) step length, and short (-10%) step length. Patellofemoral kinetics was estimated using a biomechanical model of the patellofemoral joint that accounted for cocontraction of the knee flexors and extensors. We observed independent effects of foot strike pattern and step length. Patellofemoral joint kinetics per step was 10-13% less during forefoot strike conditions and 15-20% less with a shortened step length. Patellofemoral joint kinetics per kilometer decreased 12-13% using a forefoot strike pattern and 9-12% with a shortened step length. To the extent that patellofemoral joint kinetics contribute to symptoms among runners, these running modifications may be advisable for runners with patellofemoral pain. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Independently Controlled Wing Stroke Patterns in the Fruit Fly Drosophila melanogaster

PubMed Central

Chakraborty, Soma; Bartussek, Jan; Fry, Steven N.; Zapotocky, Martin

2015-01-01

Flies achieve supreme flight maneuverability through a small set of miniscule steering muscles attached to the wing base. The fast flight maneuvers arise from precisely timed activation of the steering muscles and the resulting subtle modulation of the wing stroke. In addition, slower modulation of wing kinematics arises from changes in the activity of indirect flight muscles in the thorax. We investigated if these modulations can be described as a superposition of a limited number of elementary deformations of the wing stroke that are under independent physiological control. Using a high-speed computer vision system, we recorded the wing motion of tethered flying fruit flies for up to 12 000 consecutive wing strokes at a sampling rate of 6250 Hz. We then decomposed the joint motion pattern of both wings into components that had the minimal mutual information (a measure of statistical dependence). In 100 flight segments measured from 10 individual flies, we identified 7 distinct types of frequently occurring least-dependent components, each defining a kinematic pattern (a specific deformation of the wing stroke and the sequence of its activation from cycle to cycle). Two of these stroke deformations can be associated with the control of yaw torque and total flight force, respectively. A third deformation involves a change in the downstroke-to-upstroke duration ratio, which is expected to alter the pitch torque. A fourth kinematic pattern consists in the alteration of stroke amplitude with a period of 2 wingbeat cycles, extending for dozens of cycles. Our analysis indicates that these four elementary kinematic patterns can be activated mutually independently, and occur both in isolation and in linear superposition. The results strengthen the available evidence for independent control of yaw torque, pitch torque, and total flight force. Our computational method facilitates systematic identification of novel patterns in large kinematic datasets. PMID:25710715

Independently controlled wing stroke patterns in the fruit fly Drosophila melanogaster.

PubMed

Chakraborty, Soma; Bartussek, Jan; Fry, Steven N; Zapotocky, Martin

2015-01-01

Flies achieve supreme flight maneuverability through a small set of miniscule steering muscles attached to the wing base. The fast flight maneuvers arise from precisely timed activation of the steering muscles and the resulting subtle modulation of the wing stroke. In addition, slower modulation of wing kinematics arises from changes in the activity of indirect flight muscles in the thorax. We investigated if these modulations can be described as a superposition of a limited number of elementary deformations of the wing stroke that are under independent physiological control. Using a high-speed computer vision system, we recorded the wing motion of tethered flying fruit flies for up to 12,000 consecutive wing strokes at a sampling rate of 6250 Hz. We then decomposed the joint motion pattern of both wings into components that had the minimal mutual information (a measure of statistical dependence). In 100 flight segments measured from 10 individual flies, we identified 7 distinct types of frequently occurring least-dependent components, each defining a kinematic pattern (a specific deformation of the wing stroke and the sequence of its activation from cycle to cycle). Two of these stroke deformations can be associated with the control of yaw torque and total flight force, respectively. A third deformation involves a change in the downstroke-to-upstroke duration ratio, which is expected to alter the pitch torque. A fourth kinematic pattern consists in the alteration of stroke amplitude with a period of 2 wingbeat cycles, extending for dozens of cycles. Our analysis indicates that these four elementary kinematic patterns can be activated mutually independently, and occur both in isolation and in linear superposition. The results strengthen the available evidence for independent control of yaw torque, pitch torque, and total flight force. Our computational method facilitates systematic identification of novel patterns in large kinematic datasets.

76 FR 18213 - Ameren Services Company, Northern Indiana Public Service Company v. Midwest Independent...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-01

.... Midwest Independent Transmission System Operator, Inc.; Great Lakes Utilities, Indiana Municipal Power Agency, Missouri Joint Municipal Electric Utility Commission, Missouri River Energy Services, Prairie... Independent Transmission System Operator, Operator, Inc.; Wabash Valley Power Association, Inc. v. Midwest...

Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?

PubMed

Esposito, Fabrizio; Formisano, Elia; Seifritz, Erich; Goebel, Rainer; Morrone, Renato; Tedeschi, Gioacchino; Di Salle, Francesco

2002-07-01

Independent component analysis (ICA) has been successfully employed to decompose functional MRI (fMRI) time-series into sets of activation maps and associated time-courses. Several ICA algorithms have been proposed in the neural network literature. Applied to fMRI, these algorithms might lead to different spatial or temporal readouts of brain activation. We compared the two ICA algorithms that have been used so far for spatial ICA (sICA) of fMRI time-series: the Infomax (Bell and Sejnowski [1995]: Neural Comput 7:1004-1034) and the Fixed-Point (Hyvärinen [1999]: Adv Neural Inf Proc Syst 10:273-279) algorithms. We evaluated the Infomax- and Fixed Point-based sICA decompositions of simulated motor, and real motor and visual activation fMRI time-series using an ensemble of measures. Log-likelihood (McKeown et al. [1998]: Hum Brain Mapp 6:160-188) was used as a measure of how significantly the estimated independent sources fit the statistical structure of the data; receiver operating characteristics (ROC) and linear correlation analyses were used to evaluate the algorithms' accuracy of estimating the spatial layout and the temporal dynamics of simulated and real activations; cluster sizing calculations and an estimation of a residual gaussian noise term within the components were used to examine the anatomic structure of ICA components and for the assessment of noise reduction capabilities. Whereas both algorithms produced highly accurate results, the Fixed-Point outperformed the Infomax in terms of spatial and temporal accuracy as long as inferential statistics were employed as benchmarks. Conversely, the Infomax sICA was superior in terms of global estimation of the ICA model and noise reduction capabilities. Because of its adaptive nature, the Infomax approach appears to be better suited to investigate activation phenomena that are not predictable or adequately modelled by inferential techniques. Copyright 2002 Wiley-Liss, Inc.

Interrater and intrarater reliability in the measurement of ankle joint dorsiflexion is independent of examiner experience and technique used.

PubMed

Kim, Paul Jeong; Peace, Ruth; Mieras, Jamie; Thoms, Tanya; Freeman, Denise; Page, Jeffrey

2011-01-01

Goniometric measurement is currently being used as a diagnostic and outcomes assessment tool for ankle joint dorsiflexion. Despite its common use, its interrater and intrarater reliability has been questioned. This is a prospective study examining whether the experience of the examiner or the technique used affects the interrater and intrarater reliability for measuring ankle joint dorsiflexion. Fourteen asymptomatic individuals (8 male and 6 female) with a mean age of 28.2 years (range, 23-52) were enrolled into this study. The years of clinical experience of the five examiners averaged 10.4 years (range, 0-26). Four examiners used a modified Root, Weed and Orien method of measuring ankle joint dorsiflexion. The fifth examiner utilized a nonstandardized technique. A standard goniometer was used for bilateral measurements of ankle joint dorsiflexion with the knee extended and flexed. All five examiners repeated each measurement three times during each of the three sessions, with each session spaced at least 1 week apart. The interclass correlation coefficient reveals a moderate intrarater and poor interrater reliability in ankle joint dorsiflexion measurements using a standard goniometer. More importantly, further analysis indicates that the use of a standardized technique for measurement of ankle joint dorsiflexion or years of clinical experience does not increase the intrarater or interrater reliability. The utility of the goniometric measurement of ankle joint dorsiflexion may be limited.

Identification of Nonlinear Micron-Level Mechanics for a Precision Deployable Joint

NASA Technical Reports Server (NTRS)

Bullock, S. J.; Peterson, L. D.

1994-01-01

The experimental identification of micron-level nonlinear joint mechanics and dynamics for a pin-clevis joint used in a precision, adaptive, deployable space structure are investigated. The force-state mapping method is used to identify the behavior of the joint under a preload. The results of applying a single tension-compression cycle to the joint under a tensile preload are presented. The observed micron-level behavior is highly nonlinear and involves all six rigid body motion degrees-of-freedom of the joint. it is also suggests that at micron levels of motion modelling of the joint mechanics and dynamics must include the interactions between all internal components, such as the pin, bushings, and the joint node.

Micropower Mixed-signal VLSI Independent Component Analysis for Gradient Flow Acoustic Source Separation.

PubMed

Stanaćević, Milutin; Li, Shuo; Cauwenberghs, Gert

2016-07-01

A parallel micro-power mixed-signal VLSI implementation of independent component analysis (ICA) with reconfigurable outer-product learning rules is presented. With the gradient sensing of the acoustic field over a miniature microphone array as a pre-processing method, the proposed ICA implementation can separate and localize up to 3 sources in mild reverberant environment. The ICA processor is implemented in 0.5 µm CMOS technology and occupies 3 mm × 3 mm area. At 16 kHz sampling rate, ASIC consumes 195 µW power from a 3 V supply. The outer-product implementation of natural gradient and Herault-Jutten ICA update rules demonstrates comparable performance to benchmark FastICA algorithm in ideal conditions and more robust performance in noisy and reverberant environment. Experiments demonstrate perceptually clear separation and precise localization over wide range of separation angles of two speech sources presented through speakers positioned at 1.5 m from the array on a conference room table. The presented ASIC leads to a extreme small form factor and low power consumption microsystem for source separation and localization required in applications like intelligent hearing aids and wireless distributed acoustic sensor arrays.

Independent component analysis-based source-level hyperlink analysis for two-person neuroscience studies

NASA Astrophysics Data System (ADS)

Zhao, Yang; Dai, Rui-Na; Xiao, Xiang; Zhang, Zong; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-02-01

Two-person neuroscience, a perspective in understanding human social cognition and interaction, involves designing immersive social interaction experiments as well as simultaneously recording brain activity of two or more subjects, a process termed "hyperscanning." Using newly developed imaging techniques, the interbrain connectivity or hyperlink of various types of social interaction has been revealed. Functional near-infrared spectroscopy (fNIRS)-hyperscanning provides a more naturalistic environment for experimental paradigms of social interaction and has recently drawn much attention. However, most fNIRS-hyperscanning studies have computed hyperlinks using sensor data directly while ignoring the fact that the sensor-level signals contain confounding noises, which may lead to a loss of sensitivity and specificity in hyperlink analysis. In this study, on the basis of independent component analysis (ICA), a source-level analysis framework is proposed to investigate the hyperlinks in a fNIRS two-person neuroscience study. The performance of five widely used ICA algorithms in extracting sources of interaction was compared in simulative datasets, and increased sensitivity and specificity of hyperlink analysis by our proposed method were demonstrated in both simulative and real two-person experiments.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

PubMed

Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

2012-06-01

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

Do you really represent my task? Sequential adaptation effects to unexpected events support referential coding for the joint Simon effect.

PubMed

Klempova, Bibiana; Liepelt, Roman

2016-07-01

Recent findings suggest that a Simon effect (SE) can be induced in Individual go/nogo tasks when responding next to an event-producing object salient enough to provide a reference for the spatial coding of one's own action. However, there is skepticism against referential coding for the joint Simon effect (JSE) by proponents of task co-representation. In the present study, we tested assumptions of task co-representation and referential coding by introducing unexpected double response events in a joint go/nogo and a joint independent go/nogo task. In Experiment 1b, we tested if task representations are functionally similar in joint and standard Simon tasks. In Experiment 2, we tested sequential updating of task co-representation after unexpected single response events in the joint independent go/nogo task. Results showed increased JSEs following unexpected events in the joint go/nogo and joint independent go/nogo task (Experiment 1a). While the former finding is in line with the assumptions made by both accounts (task co-representation and referential coding), the latter finding supports referential coding. In contrast to Experiment 1a, we found a decreased SE after unexpected events in the standard Simon task (Experiment 1b), providing evidence against the functional equivalence assumption between joint and two-choice Simon tasks of the task co-representation account. Finally, we found an increased JSE also following unexpected single response events (Experiment 2), ruling out that the findings of the joint independent go/nogo task in Experiment 1a were due to a re-conceptualization of the task situation. In conclusion, our findings support referential coding also for the joint Simon effect.

The Rationale for Joint Mobilization.

ERIC Educational Resources Information Center

Burkhardt, Sandy

This paper presents an overview of the functions of connective tissue and the mechanisms of joint injury and contracture formation in relation to therapeutic exercise. The components of connective tissue operation are explained, including fibroblasts, macrophages, plasma cells, and collagen. An examination of the histology of connective tissue as…

In-field implementation of impedance-based structural health monitoring for insulated rail joints

NASA Astrophysics Data System (ADS)

Albakri, Mohammad I.; Malladi, V. V. N. Sriram; Woolard, Americo G.; Tarazaga, Pablo A.

2017-04-01

Track defects are a major safety concern for the railroad industry. Among different track components, insulated rail joints, which are widely used for signaling purposes, are considered a weak link in the railroad track. Several joint-related defects have been identified by the railroad community, including rail wear, torque loss, and joint bar breakage. Current track inspection techniques rely on manual and visual inspection or on specially equipped testing carts, which are costly, timeconsuming, traffic disturbing, and prone to human error. To overcome the aforementioned limitations, the feasibility of utilizing impedance-based structural health monitoring for insulated rail joints is investigated in this work. For this purpose, an insulated joint, provided by Koppers Inc., is instrumented with piezoelectric transducers and assembled with 136 AREA rail plugs. The instrumented joint is then installed and tested at the Facility for Accelerated Service Testing, Transportation Technology Center Inc. The effects of environmental and operating conditions on the measured impedance signatures are investigated through a set of experiments conducted at different temperatures and loading conditions. The capabilities of impedance-based SHM to detect several joint-related damage types are also studied by introducing reversible mechanical defects to different joint components.

Gene-expression changes in knee-joint tissues with aging and menopause: implications for the joint as an organ

PubMed Central

Rollick, Natalie C; Lemmex, Devin B; Ono, Yohei; Reno, Carol R; Hart, David A; Lo, Ian KY; Thornton, Gail M

2018-01-01

Background When considering the “joint as an organ”, the tissues in a joint act as complementary components of an organ, and the “set point” is the cellular activity for homeostasis of the joint tissues. Even in the absence of injury, joint tissues have adaptive responses to processes, like aging and menopause, which result in changes to the set point. Purpose The purpose of this study in a preclinical model was to investigate age-related and menopause-related changes in knee-joint tissues with the hypothesis that tissues will change in unique ways that reflect their differing contributions to maintaining joint function (as measured by joint laxity) and the differing processes of aging and menopause. Methods Rabbit knee-joint tissues from three groups were evaluated: young adult (gene expression, n=8; joint laxity, n=7; water content, n=8), aging adult (gene expression, n=6; joint laxity, n=7; water content, n=5), and menopausal adult (gene expression, n=8; joint laxity, n=7; water content, n=8). Surgical menopause was induced with ovariohysterectomy surgery and gene expression was assessed using reverse-transcription quantitative polymerase chain reaction. Results Aging resulted in changes to 37 of the 150 gene–tissue combinations evaluated, and menopause resulted in changes to 39 of the 150. Despite the similar number of changes, only eleven changes were the same in both aging and menopause. No differences in joint laxity were detected comparing young adult rabbits with aging adult rabbits or with menopausal adult rabbits. Conclusion Aging and menopause affected the gene-expression patterns of the tissues of the knee joint differently, suggesting unique changes to the set point of the knee. Interestingly, aging and menopause did not affect knee-joint laxity, suggesting that joint function was maintained, despite changes in gene expression. Taken together, these findings support the theory of the joint as an organ where the tissues of the joint adapt to

Performance comparison of six independent components analysis algorithms for fetal signal extraction from real fMCG data

NASA Astrophysics Data System (ADS)

Hild, Kenneth E.; Alleva, Giovanna; Nagarajan, Srikantan; Comani, Silvia

2007-01-01

In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction.

Field evaluation of three joint sealants.

DOT National Transportation Integrated Search

1987-01-01

The purpose of the study reported here was to evaluate the performance of three joint sealants compartmented (A) and closed cellular (B) preformed neoprene, and a two-component cold-mixed polysulfide (C)-- that were used in the interchanges for Inter...

Airborne and Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS)

DTIC Science & Technology

2015-12-01

Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-421 Airborne & Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS) As of FY 2017...Information Program Name Airborne & Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS) DoD Component Army Responsible Office References SAR...UNCLASSIFIED 5 Mission and Description Airborne & Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS) products are software programmable

Joint attention and oromotor abilities in young children with and without autism spectrum disorder.

PubMed

Dalton, Jennifer C; Crais, Elizabeth R; Velleman, Shelley L

2017-09-01

This study examined the relationship between joint attention ability and oromotor imitation skill in three groups of young children with and without Autism Spectrum Disorder using both nonverbal oral and verbal motor imitation tasks. Research questions addressed a) differences among joint attention and oromotor imitation abilities; b) the relationship between independently measured joint attention and oromotor imitation, both nonverbal oral and verbal motor; c) the relationships between joint attention and verbal motor imitation during interpersonal interaction; and d) the relationship between the sensory input demands (auditory, visual, and tactile) and oromotor imitation, both nonverbal oral and verbal motor. A descriptive, nonexperimental design was used to compare joint attention and oromotor skills of 10 preschool-aged children with ASD, with those of two control groups: 6 typically developing children (TD), and 6 children with suspected Childhood Apraxia of Speech (sCAS) or apraxic-like symptoms. All children had at least a 3.0 mean length utterance. Children with ASD had poorer joint attention skills overall than children with sCAS or typically developing children. Typically developing children demonstrated higher verbal motor imitation skills overall compared to children with sCAS. Correlational analyses revealed that nonverbal oral imitation and verbal motor imitation were positively related to joint attention abilities only in the children with ASD. Strong positive relationships between joint attention in a naturalistic context (e.g., shared story experience) and oromotor imitation skills, both nonverbal oral and verbal motor, were found only for children with ASD. These data suggest there is a strong positive relationship between joint attention skills and the ability to sequence nonverbal oral and verbal motor movements in children with ASD. The combined sensory input approach involving auditory, visual, and tactile modalities contributed to

ELECTRONIC COMPONENT COOLING ALTERNATIVES: COMPRESSED AIR & LIQUID NITROGEN

EPA Science Inventory

The goal of this study was to evaluate tools used to troubleshoot circuit boards with known or suspected thermally intermittent components. ailure modes for thermally intermittent components are typically mechanical defects, such as cracks in solder paths or joints, or broken bon...

Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

PubMed

Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

Coupling of Action-Perception Brain Networks during Musical Pulse Processing: Evidence from Region-of-Interest-Based Independent Component Analysis.

PubMed

Burunat, Iballa; Tsatsishvili, Valeri; Brattico, Elvira; Toiviainen, Petri

2017-01-01

Our sense of rhythm relies on orchestrated activity of several cerebral and cerebellar structures. Although functional connectivity studies have advanced our understanding of rhythm perception, this phenomenon has not been sufficiently studied as a function of musical training and beyond the General Linear Model (GLM) approach. Here, we studied pulse clarity processing during naturalistic music listening using a data-driven approach (independent component analysis; ICA). Participants' (18 musicians and 18 controls) functional magnetic resonance imaging (fMRI) responses were acquired while listening to music. A targeted region of interest (ROI) related to pulse clarity processing was defined, comprising auditory, somatomotor, basal ganglia, and cerebellar areas. The ICA decomposition was performed under different model orders, i.e., under a varying number of assumed independent sources, to avoid relying on prior model order assumptions. The components best predicted by a measure of the pulse clarity of the music, extracted computationally from the musical stimulus, were identified. Their corresponding spatial maps uncovered a network of auditory (perception) and motor (action) areas in an excitatory-inhibitory relationship at lower model orders, while mainly constrained to the auditory areas at higher model orders. Results revealed (a) a strengthened functional integration of action-perception networks associated with pulse clarity perception hidden from GLM analyses, and (b) group differences between musicians and non-musicians in pulse clarity processing, suggesting lifelong musical training as an important factor that may influence beat processing.

Independent EEG Sources Are Dipolar

PubMed Central

Delorme, Arnaud; Palmer, Jason; Onton, Julie; Oostenveld, Robert; Makeig, Scott

2012-01-01

Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition ‘dipolarity’ defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison). PMID:22355308

Modeling knee joint endoprosthesis mode of deformation

NASA Astrophysics Data System (ADS)

Skeeba, V. Yu; Ivancivsky, V. V.

2018-03-01

The purpose of the work was to define the efficient design of the endoprosthesis, working in a multiple-cycle loading environment. Methodology and methods: triangulated surfaces of the base contact surfaces of endoprosthesis butt elements have been created using the PowerShape and SolidWorks software functional environment, and the assemblies of the possible combinations of the knee joint prosthetic designs have been prepared. The mode of deformation modeling took place in the multipurpose program complex ANSYS. Results and discussion: as a result of the numerical modeling, the following data were obtained for each of the developed knee joint versions: the distribution fields of absolute (total) and relative deformations; equivalent stress distribution fields; fatigue strength coefficient distribution fields. In the course of the studies, the following efficient design assembly has been established: 1) Ti-Al-V alloy composite femoral component with polymer inserts; 2) ceramic liners of the compound separator; 3) a Ti-Al-V alloy composite tibial component. The fatigue strength coefficient for the femoral component is 4.2; for the femoral component polymer inserts is 1.2; for the ceramic liners of the compound separator is 3.1; for the tibial component is 2.7. This promising endoprosthesis structure is recommended for further design and technological development.

Intraoperative Considerations for Treatment/Prevention of Prosthetic Joint Infection.

PubMed

Suleiman, Linda I; Mesko, Daniel R; Nam, Denis

2018-06-23

Innovative measures have recently been proposed to prevent periprosthetic joint infection following total hip and knee arthroplasty. We sought to review these recent innovations to determine the reported reduction in periprosthetic joint infection. The most recent literature demonstrates promising results in regard to hydrofiber dressings as an independent risk factor for primary prosthetic joint infection reduction, which in turn is also linked with cost savings. As our understanding of safe yet effective concentrations of antiseptic solutions develops, dilute betadine in particular has demonstrated encouraging efficacy which warrants continued investigation through controlled trials. In summary, we found that the application of a hydrofiber dressing may prove beneficial in decreasing the risk of prosthetic joint infection following primary total hip and knee arthroplasty. The gold standard for an infection prevention protocol continues to be explored and optimized.

Extraction of fast neuronal changes from multichannel functional near-infrared spectroscopy signals using independent component analysis

NASA Astrophysics Data System (ADS)

Morren, Geert; Wolf, Martin; Lemmerling, Philippe; Wolf, Ursula; Choi, Jee H.; Gratton, Enrico; De Lathauwer, Lieven; Van Huffel, Sabine

2002-06-01

Fast changes in the range of milliseconds in the optical properties of cerebral tissue, which are associated with brain activity, can be detected using non-invasive near-infrared spectroscopy (NIRS). These changes in light scattering are due to an alteration in the refractive index at neuronal membranes. The aim of this study was to develop highly sensitive data analysis algorithms to detect this fast signal, which is small compared to other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were modulated at 110MHz was used. The amplitude, mean intensity and phase of the modulated optical signal was measured at 96Hz sample rate. The probe consisting of 4 crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest- and tapping periods of 20s each. The tapping frequency, which was set to 3.55Hz or 2.5 times the heart rate of the subject to avoid the influence of harmonics on the signal, could not be observed in any of the individual signals measured by the detectors. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent Component Analysis allowed to separate signal components in which the tapping frequency was clearly visible.

Experimental studies of glued Aluminum-glass joints

NASA Astrophysics Data System (ADS)

Ligaj, B.; Wirwicki, M.; Karolewska, K.; Jasińska, A.

2018-04-01

Glued steel-glass or aluminum-glass joints are to be found, among other things, in vehicles (cars, buses, trains, trams) as windscreen assembly pieces for the supporting structure. For the purposes of the experiments, samples were made in which the top beam was made of the AW-2017A aluminum alloy and the bottom beam was made of thermally reinforced soda-lime glass whereas the glued joints were made of one-component polyurethane glue Körapur 175. The tests were performed under four-point bending conditions at monotonic incremental bending moment values on the Instron 5965 durability machine. The experimental study of the durability of glued joints under four-point bending conditions with the monotonic incremental bending moment allows to determine the values of stresses, whose value is related to initiation of damage of the tested joint.

Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction

PubMed Central

Aguilera, Teodoro; Lozano, Jesús; Paredes, José A.; Álvarez, Fernando J.; Suárez, José I.

2012-01-01

The aim of this work is to propose an alternative way for wine classification and prediction based on an electronic nose (e-nose) combined with Independent Component Analysis (ICA) as a dimensionality reduction technique, Partial Least Squares (PLS) to predict sensorial descriptors and Artificial Neural Networks (ANNs) for classification purpose. A total of 26 wines from different regions, varieties and elaboration processes have been analyzed with an e-nose and tasted by a sensory panel. Successful results have been obtained in most cases for prediction and classification. PMID:22969387

Towards a constructionist approach to emotions: verification of the three-dimensional model of affect with EEG-independent component analysis.

PubMed

Wyczesany, Miroslaw; Ligeza, Tomasz S

2015-03-01

The locationist model of affect, which assumes separate brain structures devoted to particular discrete emotions, is currently being questioned as it has not received enough convincing experimental support. An alternative, constructionist approach suggests that our emotional states emerge from the interaction between brain functional networks, which are related to more general, continuous affective categories. In the study, we tested whether the three-dimensional model of affect based on valence, arousal, and dominance (VAD) can reflect brain activity in a more coherent way than the traditional locationist approach. Independent components of brain activity were derived from spontaneous EEG recordings and localized using the DIPFIT method. The correspondence between the spectral power of the revealed brain sources and a mood self-report quantified on the VAD space was analysed. Activation of four (out of nine) clusters of independent brain sources could be successfully explained by the specific combination of three VAD dimensions. The results support the constructionist theory of emotions.

Natural scene logo recognition by joint boosting feature selection in salient regions

NASA Astrophysics Data System (ADS)

Fan, Wei; Sun, Jun; Naoi, Satoshi; Minagawa, Akihiro; Hotta, Yoshinobu

2011-01-01

Logos are considered valuable intellectual properties and a key component of the goodwill of a business. In this paper, we propose a natural scene logo recognition method which is segmentation-free and capable of processing images extremely rapidly and achieving high recognition rates. The classifiers for each logo are trained jointly, rather than independently. In this way, common features can be shared across multiple classes for better generalization. To deal with large range of aspect ratio of different logos, a set of salient regions of interest (ROI) are extracted to describe each class. We ensure the selected ROIs to be both individually informative and two-by-two weakly dependant by a Class Conditional Entropy Maximization criteria. Experimental results on a large logo database demonstrate the effectiveness and efficiency of our proposed method.

Workspace location influences joint coordination during reaching in post-stroke hemiparesis

PubMed Central

Reisman, Darcy S.; Scholz, John P.

2006-01-01

The purpose of this study was to determine the influence of workspace location on joint coordination in persons with post-stroke hemiparesis when trunk motion was required to complete reaches beyond the arm’s functional reach length. Seven subjects with mild right hemiparesis following a stroke and seven age and gender matched control subjects participated. Joint motions and characteristics of hand and trunk movement were measured over multiple repetitions. The variance (across trials) of joint combinations was partitioned into two components at every point in the hand’s trajectory using the uncontrolled manifold approach; the first component is a measure of the extent to which equivalent joint combinations are used to control a given hand path, and reflects performance flexibility. The second component of joint variance reflects the use of non-equivalent joint combinations, which lead to hand path error. Compared to the control subjects, persons with hemiparesis demonstrated a significantly greater amount of non-equivalent joint variability related to control of the hand’s path and of the hand’s position relative to the trunk when reaching toward the hemiparetic side (ipsilaterally), but not when reaching to the less involved side. The relative timing of the hand and trunk was also altered when reaching ipsilaterally. The current findings support the idea that the previously proposed “arm compensatory synergy” may be deficient in subjects with hemiparesis. This deficiency may be due to one or a combination of factors: changes in central commands that are thought to set the gain of the arm compensatory synergy; a limited ability to combine shoulder abduction and elbow extension that limits the expression of an appropriately set arm compensatory synergy; or a reduction of the necessary degrees-of-freedom needed to adequately compensate for poor trunk control when reaching ipsilaterally. PMID:16328275

Cost component analysis.

PubMed

Lörincz, András; Póczos, Barnabás

2003-06-01

In optimizations the dimension of the problem may severely, sometimes exponentially increase optimization time. Parametric function approximatiors (FAPPs) have been suggested to overcome this problem. Here, a novel FAPP, cost component analysis (CCA) is described. In CCA, the search space is resampled according to the Boltzmann distribution generated by the energy landscape. That is, CCA converts the optimization problem to density estimation. Structure of the induced density is searched by independent component analysis (ICA). The advantage of CCA is that each independent ICA component can be optimized separately. In turn, (i) CCA intends to partition the original problem into subproblems and (ii) separating (partitioning) the original optimization problem into subproblems may serve interpretation. Most importantly, (iii) CCA may give rise to high gains in optimization time. Numerical simulations illustrate the working of the algorithm.

Shear Model Development of Limestone Joints with Incorporating Variations of Basic Friction Coefficient and Roughness Components During Shearing

NASA Astrophysics Data System (ADS)

Mehrishal, Seyedahmad; Sharifzadeh, Mostafa; Shahriar, Korosh; Song, Jae-Jon

2017-04-01

In relation to the shearing of rock joints, the precise and continuous evaluation of asperity interlocking, dilation, and basic friction properties has been the most important task in the modeling of shear strength. In this paper, in order to investigate these controlling factors, two types of limestone joint samples were prepared and CNL direct shear tests were performed on these joints under various shear conditions. One set of samples were travertine and another were onyx marble with slickensided surfaces, surfaces ground to #80, and rough surfaces were tested. Direct shear experiments conducted on slickensided and ground surfaces of limestone indicated that by increasing the applied normal stress, under different shearing rates, the basic friction coefficient decreased. Moreover, in the shear tests under constant normal stress and shearing rate, the basic friction coefficient remained constant for the different contact sizes. The second series of direct shear experiments in this research was conducted on tension joint samples to evaluate the effect of surface roughness on the shear behavior of the rough joints. This paper deals with the dilation and roughness interlocking using a method that characterizes the surface roughness of the joint based on a fundamental combined surface roughness concept. The application of stress-dependent basic friction and quantitative roughness parameters in the continuous modeling of the shear behavior of rock joints is an important aspect of this research.

Expression of proteins in serum, synovial fluid, synovial membrane, and articular cartilage samples obtained from dogs with stifle joint osteoarthritis secondary to cranial cruciate ligament disease and dogs without stifle joint arthritis.

PubMed

Garner, Bridget C; Kuroki, Keiichi; Stoker, Aaron M; Cook, Cristi R; Cook, James L

2013-03-01

To identify proteins with differential expression between healthy dogs and dogs with stifle joint osteoarthritis secondary to cranial cruciate ligament (CCL) disease. Serum and synovial fluid samples obtained from dogs with stifle joint osteoarthritis before (n = 10) and after (8) surgery and control dogs without osteoarthritis (9) and archived synovial membrane and articular cartilage samples obtained from dogs with stifle joint osteoarthritis (5) and dogs without arthritis (5). Serum and synovial fluid samples were analyzed via liquid chromatography-tandem mass spectrometry; results were compared against a nonredundant protein database. Expression of complement component 3 in archived tissue samples was determined via immunohistochemical methods. No proteins had significantly different expression between serum samples of control dogs versus those of dogs with stifle joint osteoarthritis. Eleven proteins (complement component 3 precursor, complement factor I precursor, apolipoprotein B-100 precursor, serum paraoxonase and arylesterase 1, zinc-alpha-2-glycoprotein precursor, serum amyloid A, transthyretin precursor, retinol-binding protein 4 precursor, alpha-2-macroglobulin precursor, angiotensinogen precursor, and fibronectin 1 isoform 1 preproprotein) had significantly different expression (> 2.0-fold) between synovial fluid samples obtained before surgery from dogs with stifle joint osteoarthritis versus those obtained from control dogs. Complement component 3 was strongly expressed in all (5/5) synovial membrane samples of dogs with stifle joint osteoarthritis and weakly expressed in 3 of 5 synovial membrane samples of dogs without stifle joint arthritis. Findings suggested that the complement system and proteins involved in lipid and cholesterol metabolism may have a role in stifle joint osteoarthritis, CCL disease, or both.

Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding.

PubMed

Qi, Jin; Yang, Zhiyong

2014-01-01

Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications.

Joint representation of translational and rotational components of optic flow in parietal cortex

PubMed Central

Sunkara, Adhira; DeAngelis, Gregory C.; Angelaki, Dora E.

2016-01-01

Terrestrial navigation naturally involves translations within the horizontal plane and eye rotations about a vertical (yaw) axis to track and fixate targets of interest. Neurons in the macaque ventral intraparietal (VIP) area are known to represent heading (the direction of self-translation) from optic flow in a manner that is tolerant to rotational visual cues generated during pursuit eye movements. Previous studies have also reported that eye rotations modulate the response gain of heading tuning curves in VIP neurons. We tested the hypothesis that VIP neurons simultaneously represent both heading and horizontal (yaw) eye rotation velocity by measuring heading tuning curves for a range of rotational velocities of either real or simulated eye movements. Three findings support the hypothesis of a joint representation. First, we show that rotation velocity selectivity based on gain modulations of visual heading tuning is similar to that measured during pure rotations. Second, gain modulations of heading tuning are similar for self-generated eye rotations and visually simulated rotations, indicating that the representation of rotation velocity in VIP is multimodal, driven by both visual and extraretinal signals. Third, we show that roughly one-half of VIP neurons jointly represent heading and rotation velocity in a multiplicatively separable manner. These results provide the first evidence, to our knowledge, for a joint representation of translation direction and rotation velocity in parietal cortex and show that rotation velocity can be represented based on visual cues, even in the absence of efference copy signals. PMID:27095846

Dark degeneracy and interacting cosmic components

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

Aviles, Alejandro; Cervantes-Cota, Jorge L.

2011-10-15

We study some properties of the dark degeneracy, which is the fact that what we measure in gravitational experiments is the energy-momentum tensor of the total dark sector, and any split into components (as in dark matter and dark energy) is arbitrary. In fact, just one dark fluid is necessary to obtain exactly the same cosmological and astrophysical phenomenology as the {Lambda}CDM model. We work explicitly the first-order perturbation theory and show that beyond the linear order the dark degeneracy is preserved under some general assumptions. Then we construct the dark fluid from a collection of interacting fluids. Finally, wemore » try to break the degeneracy with a general class of couplings to baryonic matter. Nonetheless, we show that these interactions can also be understood in the context of the {Lambda}CDM model as between dark matter and baryons. For this last investigation we choose two independent parametrizations for the interactions, one inspired by electromagnetism and the other by chameleon theories. Then, we constrain them with a joint analysis of CMB and supernovae observational data.« less

Idealized models of the joint probability distribution of wind speeds

NASA Astrophysics Data System (ADS)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

A Dual Role for NOTCH Signaling in Joint Cartilage Maintenance and Osteoarthritis

PubMed Central

Liu, Zhaoyang; Chen, Jianquan; Mirando, Anthony; Wang, Cuicui; Zuscik, Michael J.; O’Keefe, Regis J.; Hilton, Matthew J.

2015-01-01

Loss of NOTCH signaling in postnatal murine joints results in osteoarthritis (OA), indicating a requirement for NOTCH during joint cartilage maintenance. Unexpectedly, NOTCH components are significantly up-regulated in human and murine post-traumatic OA, suggesting either a reparative or pathological role for NOTCH activation in OA. Here we investigated the potential dual role for NOTCH in joint maintenance and OA by generating two mouse models overexpressing the NOTCH1 intracellular domain within postnatal joint cartilage; one with sustained NOTCH activation that likely resembles pathological NOTCH signaling and one with transient NOTCH activation that more closely reflects physiological NOTCH signaling. Sustained NOTCH signaling in joint cartilage leads to an early and progressive OA pathology, while on the contrary, transient NOTCH activation enhances cartilage matrix synthesis and promotes joint maintenance under normal physiological conditions. Using RNA-seq, immunohistochemical, and biochemical approaches we identified several novel targets potentially responsible for NOTCH-mediated cartilage degradation, fibrosis, and OA progression, including components of the IL6/STAT3 and ERK/p38 MAPK pathways; factors that may also contribute to post-traumatic OA development. Collectively, these data demonstrate a dual role for the NOTCH pathway in joint cartilage and identify important downstream NOTCH effectors as potential targets for disease modifying osteoarthritis drugs (DMOADs). PMID:26198357

Separation of the low-frequency atmospheric variability into non-Gaussian multidimensional sources by Independent Subspace Analysis

NASA Astrophysics Data System (ADS)

Pires, Carlos; Ribeiro, Andreia

2016-04-01

An efficient nonlinear method of statistical source separation of space-distributed non-Gaussian distributed data is proposed. The method relies in the so called Independent Subspace Analysis (ISA), being tested on a long time-series of the stream-function field of an atmospheric quasi-geostrophic 3-level model (QG3) simulating the winter's monthly variability of the Northern Hemisphere. ISA generalizes the Independent Component Analysis (ICA) by looking for multidimensional and minimally dependent, uncorrelated and non-Gaussian distributed statistical sources among the rotated projections or subspaces of the multivariate probability distribution of the leading principal components of the working field whereas ICA restrict to scalar sources. The rationale of that technique relies upon the projection pursuit technique, looking for data projections of enhanced interest. In order to accomplish the decomposition, we maximize measures of the sources' non-Gaussianity by contrast functions which are given by squares of nonlinear, cross-cumulant-based correlations involving the variables spanning the sources. Therefore sources are sought matching certain nonlinear data structures. The maximized contrast function is built in such a way that it provides the minimization of the mean square of the residuals of certain nonlinear regressions. The issuing residuals, followed by spherization, provide a new set of nonlinear variable changes that are at once uncorrelated, quasi-independent and quasi-Gaussian, representing an advantage with respect to the Independent Components (scalar sources) obtained by ICA where the non-Gaussianity is concentrated into the non-Gaussian scalar sources. The new scalar sources obtained by the above process encompass the attractor's curvature thus providing improved nonlinear model indices of the low-frequency atmospheric variability which is useful since large circulation indices are nonlinearly correlated. The non-Gaussian tested sources (dyads and

Improved separability of dipole sources by tripolar versus conventional disk electrodes: a modeling study using independent component analysis.

PubMed

Cao, H; Besio, W; Jones, S; Medvedev, A

2009-01-01

Tripolar electrodes have been shown to have less mutual information and higher spatial resolution than disc electrodes. In this work, a four-layer anisotropic concentric spherical head computer model was programmed, then four configurations of time-varying dipole signals were used to generate the scalp surface signals that would be obtained with tripolar and disc electrodes, and four important EEG artifacts were tested: eye blinking, cheek movements, jaw movements, and talking. Finally, a fast fixed-point algorithm was used for signal independent component analysis (ICA). The results show that signals from tripolar electrodes generated better ICA separation results than from disc electrodes for EEG signals with these four types of artifacts.

Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

PubMed

Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

2014-02-15

Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

Joint inversion of surface and borehole magnetic data to prospect concealed orebodies: A case study from the Mengku iron deposit, northwestern China

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Zhu, Rixiang

2018-07-01

The Mengku iron deposit is one of the largest magnetite deposits in Xinjiang Province, northwestern China. It is important to accurately delineate the positions and shapes of concealed orebodies for drillhole layout and resource quantity evaluations. Total-field surface and three-component borehole magnetic measurements were carried out in the deposit. We made a joint inversion of the surface and borehole magnetic data to investigate the characteristics of the orebodies. We recovered the distributions of the magnetization intensity using a preconditioned conjugate gradient algorithm. Synthetic examples show that the reconstructed models of the joint inversion yield a better consistency with the true models than those recovered using independent inversion. By using joint inversion, more accurate information is obtained on the position and shape of the orebodies in the Mengku iron deposit. The magnetization distribution of Line 135 reveals that the major magnetite orebodies occur at 200-400 m depth with a lenticular cross-section dipping north-east. The orebodies of Line 143 are modified and buried at 100-200 m depth with an elliptical cross-section caused by fault activities at north-northeast directions. This information is verified by well logs. The borehole component anomalies are combined with surface data to reconstruct the physical property model and improve the ability to distinguish vertical and horizontal directions, which provides an effective approach to prospect buried orebodies.

The John Charnley Award Paper. The role of joint fluid in the tribology of total joint arthroplasty.

PubMed

Mazzucco, Daniel; Spector, Myron

2004-12-01

The effect of joint fluid on the tribology (ie, lubrication, friction, and wear) of total hip arthroplasty has not yet been investigated adequately. In the current study, a friction assay was used to assess four hypotheses relating to the effect of human joint fluid and its principal components on the articulation of metal-on-polyethylene. First, joint fluid was found to produce a widely varying amount of friction between cobalt-chromium and polyethylene; this range exceeded the range produced when the articulation was lubricated by water or bovine serum. Second, it was shown that hyaluronic acid, phospholipid, albumin, and gamma-globulin were not acting as boundary lubricants, but that one or more other proteins (as yet unidentified) were responsible for reducing friction in this couple. Third, lower friction was found when oxidized zirconium alloy replaced cobalt-chromium as a bearing surface on polyethylene. Finally, a pilot study suggested that lubricin, which contributes to cartilage-on-cartilage lubrication, is not a protein responsible for the tribological variabiation found among joint fluid samples. The current study showed that joint fluid is a patient factor that influences the tribology of metal-on-polyethylene arthroplasty.

Transforming Joint Warfighting Capabilities

DTIC Science & Technology

2004-01-01

Certification guidance covers Internet or Web compatibility and the layout to include window size, color, typography , and graphic format. Further require...developed the JMF concept, defined as a package of 20,000 personnel from designated component ready forces. It is aug- mented by supporting commands...trust and confidence in joint warfighting. PACOM established standing com- mand and control relationships for cri- sis response by designating primary

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Do perceived job insecurity and annoyance due to air and noise pollution predict incident self-rated poor health? A prospective analysis of independent and joint associations using a German national representative cohort study

PubMed Central

Riedel, Natalie; Loerbroks, Adrian; Bolte, Gabriele; Li, Jian

2017-01-01

Background Current economic and social change has contributed to increasing job insecurity and traffic-related pollution in residential areas. Both job insecurity and exposure to noise and air pollution are known determinants of population health and can concur in peoples' lives. This may hold true particularly for socially disadvantaged subpopulations. Nevertheless, the potential independent and joint links of those exposures to health have been rarely examined so far. We aimed to contribute to the scarce body of evidence. Methods Information on perceived job insecurity and exposures to noise and air pollution as expressed by annoyance as well as on self-rated health were gathered from 2 waves of the population-based German Socio-Economic Panel (2009 and 2011, N=6544). We performed multivariable Poisson regression to examine the independent and joint risk of poor health in 2011 by perceived job insecurity and annoyance due to noise and air pollution in 2009. Results After the 2-year follow-up in 2011, 571 (8.7%) participants rated their health as poor. The risk of reporting incident poor health was increased by roughly 40% in employees reporting high versus low perceived job insecurity and annoyance due to noise and air pollution, respectively. This risk increased when both exposures were present at higher levels (risk ratio=1.95 (1.49 to 2.55)). Conclusions Work-related and environmental exposures may accumulate and have a joint health impact. Elaboration on the link between occupational and residential exposures is warranted in the light of their concurrence and their implications for health inequities. PMID:28115332

Wear mechanisms and improvements of wear resistance in cobalt-chromium alloy femoral components in artificial total knee joints

NASA Astrophysics Data System (ADS)

Que, Like

CrMo alloy surface roughness was higher than 0.022 mum Ra (surface roughness average), UHMWPE wear increased with increasing CoCrMo alloy surface roughness. Bone and poly(methyl methacrylate) (PMMA) bone cement abrasive particles created scratches on the alloy via a ploughing mechanism, and resulted in significantly rougher surfaces than controls without particles (P < 0.01). Solution treatments at 1230sp°C and 1245sp°C reduced the hardness and wear resistance of the as-cast F75 CoCrMo alloy. Aging at 700sp°C caused recrystallization of the forged F799 alloy and improved wear resistance. Thermo-mechanical treatments have the potential to increase the lifetime of artificial joints by increasing the wear resistance of CoCrMo components.

Benign joint hypermobility syndrome in soldiers; what is the effect of military training courses on associated joint instabilities?

PubMed

Azma, Kamran; Mottaghi, Peyman; Hosseini, Alireza; Abadi, Hossein Hassan; Nouraei, Mohammad Hadi

2014-07-01

Hypermobile joints are joints with beyond normal range of motion and may be associated with joint derangements. This study aimed to evaluate the prevalence of benign joint hypermobility syndrome (BJHS) among soldiers and effect of training courses on related joint instabilities. In a prospective cohort study on 721 soldiers of Iran Army in Isfahan in 2013 the prevalence of joint hypermobility was obtained by using Beighton criteria. Soldiers divided in two groups of healthy and suffered based on their scores. The prevalence of ankle sprain, shoulder and temporomandibular joint (TMJ) dislocations identified before beginning service by history-taking and reviewing paraclinical documents. After 3 months of military training, a recent occurrence of mentioned diseases was revaluated in two groups. The collected data were analyzed using SPSS-20 software using Independent-T and Chi-square tests. The frequency of BJHS before military training was 29.4%. After passing military training period, the incidence of ankle sprain was significantly higher in suffered group achieving the minimum Beighton score (BS) of 4 (4.3%, P = 0.03), 5 (5.5%, P = 0.005) and also 6 out of 9 (6.5%, P = 0.01). The incidence of TMJ dislocation was not significantly different based on a minimum score of 4, while it was higher in suffered group when considering the score of 5 (2.1%) and 6 (2.6%) for discrimination of two groups (P = 0.03). There was no significant difference between two groups in case of shoulder dislocation anyway. Military training can increase the incidence of ankle sprains and TMJ dislocations in hypermobility persons with higher BS in comparison with healthy people. Therefore, screening of joint hypermobility may be useful in identifying individuals at increased risk for joint instabilities.

Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

PubMed Central

Lahnakoski, Juha M.; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. PMID:22496909

Cotton-type and joint invariants for linear elliptic systems.

PubMed

Aslam, A; Mahomed, F M

2013-01-01

Cotton-type invariants for a subclass of a system of two linear elliptic equations, obtainable from a complex base linear elliptic equation, are derived both by spliting of the corresponding complex Cotton invariants of the base complex equation and from the Laplace-type invariants of the system of linear hyperbolic equations equivalent to the system of linear elliptic equations via linear complex transformations of the independent variables. It is shown that Cotton-type invariants derived from these two approaches are identical. Furthermore, Cotton-type and joint invariants for a general system of two linear elliptic equations are also obtained from the Laplace-type and joint invariants for a system of two linear hyperbolic equations equivalent to the system of linear elliptic equations by complex changes of the independent variables. Examples are presented to illustrate the results.

Cotton-Type and Joint Invariants for Linear Elliptic Systems

PubMed Central

Aslam, A.; Mahomed, F. M.

2013-01-01

Cotton-type invariants for a subclass of a system of two linear elliptic equations, obtainable from a complex base linear elliptic equation, are derived both by spliting of the corresponding complex Cotton invariants of the base complex equation and from the Laplace-type invariants of the system of linear hyperbolic equations equivalent to the system of linear elliptic equations via linear complex transformations of the independent variables. It is shown that Cotton-type invariants derived from these two approaches are identical. Furthermore, Cotton-type and joint invariants for a general system of two linear elliptic equations are also obtained from the Laplace-type and joint invariants for a system of two linear hyperbolic equations equivalent to the system of linear elliptic equations by complex changes of the independent variables. Examples are presented to illustrate the results. PMID:24453871

Design and clinical outcome of a novel 3D-printed prosthetic joint replacement for the human temporomandibular joint.

PubMed

Ackland, David; Robinson, Dale; Lee, Peter Vee Sin; Dimitroulis, George

2018-05-11

Stock prosthetic temporomandibular joint replacements come in limited sizes, and do not always encompass the joint anatomy that presents clinically. The aims of this study were twofold. Firstly, to design a personalized prosthetic total joint replacement for the treatment of a patient's end-stage temporomandibular joint osteoarthritis, to implant the prosthesis into the patient, and assess clinical outcome 12-months post-operatively; and secondly, to evaluate the influence of changes in prosthetic condyle geometry on implant load response during mastication. A 48-year-old female patient with Grade-5 osteoarthritis to the left temporomandibular joint was recruited, and a prosthesis developed to match the native temporomandibular joint anatomy. The prosthesis was 3D printed, sterilized and implanted into the patient, and pain and function measured 12-months post-operatively. The prosthesis load response during a chewing-bite and maximum-force bite was evaluated using a personalized multi-body musculoskeletal model. Simulations were performed after perturbing condyle thickness, neck length and head sphericity. Increases in prosthetic condyle neck length malaligned the mandible and perturbed temporomandibular joint force. Changes in condylar component thickness greatly influenced fixation screw stress response, while a more eccentric condylar head increased prosthetic joint-contact loading. Post-operatively, the prosthetic temporomandibular joint surgery reduced patient pain from 7/10 to 1/10 on a visual analog scale, and increased intercisal opening distance from 22 mm to 38 mm. This study demonstrates effectiveness of a personalized prosthesis that may ultimately be adapted to treat a wide-range of end-stage temporomandibular joint conditions, and highlights sensitivity of prosthesis load response to changes in condylar geometry. Copyright © 2018 Elsevier Ltd. All rights reserved.

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

PubMed

Delorme, Arnaud; Makeig, Scott

2004-03-15

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

ELECTRONIC COMPONENT COOLING ALTERNATIVES: COMPRESSED AIR AND LIQUID NITROGEN

EPA Science Inventory

The goal of this study was to evaluate topics used to troubleshoot circuit boards with known or suspected thermally intermittent components. Failure modes for thermally intermittent components are typically mechanical defects, such as cracks in solder paths or joints, or broken b...

A personalized 3D-printed prosthetic joint replacement for the human temporomandibular joint: From implant design to implantation.

PubMed

Ackland, David C; Robinson, Dale; Redhead, Michael; Lee, Peter Vee Sin; Moskaljuk, Adrian; Dimitroulis, George

2017-05-01

Personalized prosthetic joint replacements have important applications in cases of complex bone and joint conditions where the shape and size of off-the-shelf components may not be adequate. The objective of this study was to design, test and fabricate a personalized 3D-printed prosthesis for a patient requiring total joint replacement surgery of the temporomandibular joint (TMJ). The new 'Melbourne' prosthetic TMJ design featured a condylar component sized specifically to the patient and fixation screw positions that avoid potential intra-operative damage to the mandibular nerve. The Melbourne prosthetic TMJ was developed for a 58-year-old female recipient with end-stage osteoarthritis of the TMJ. The load response of the prosthesis during chewing and a maximum-force bite was quantified using a personalized musculoskeletal model of the patient's masticatory system developed using medical images. The simulations were then repeated after implantation of the Biomet Microfixation prosthetic TMJ, an established stock device. The maximum condylar stresses, screw stress and mandibular stress at the screw-bone interface were lower in the Melbourne prosthetic TMJ (259.6MPa, 312.9MPa and 198.4MPa, respectively) than those in the Biomet Microfixation device (284.0MPa, 416.0MPa and 262.2MPa, respectively) during the maximum-force bite, with similar trends also observed during the chewing bite. After trialing surgical placement and evaluating prosthetic TMJ stability using cadaveric specimens, the prosthesis was fabricated using 3D printing, sterilized, and implanted into the female recipient. Six months post-operatively, the prosthesis recipient had a normal jaw opening distance (40.0 mm), with no complications identified. The new design features and immediate load response of the Melbourne prosthetic TMJ suggests that it may provide improved clinical and biomechanical joint function compared to a commonly used stock device, and reduce risk of intra-operative nerve damage

vis-react-components

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

Richardson, Gregory D; Goodall, John R; Steed, Chad A

In developing visualizations for different data sets, the end solution often become dependent on the data being visualized. This causes engineers to have to re-develop many common components multiple times. The vis-react components library was designed to help enable creating visualizations that are independent of the underlying data. This library utilizes the React.js pattern of instantiating components that may be re-used. The library exposes an example application that allows other developers to understand how to use the components in the library.

Interdependence of torque, joint angle, angular velocity and muscle action during human multi-joint leg extension.

PubMed

Hahn, Daniel; Herzog, Walter; Schwirtz, Ansgar

2014-08-01

Force and torque production of human muscles depends upon their lengths and contraction velocity. However, these factors are widely assumed to be independent of each other and the few studies that dealt with interactions of torque, angle and angular velocity are based on isolated single-joint movements. Thus, the purpose of this study was to determine force/torque-angle and force/torque-angular velocity properties for multi-joint leg extensions. Human leg extension was investigated (n = 18) on a motor-driven leg press dynamometer while measuring external reaction forces at the feet. Extensor torque in the knee joint was calculated using inverse dynamics. Isometric contractions were performed at eight joint angle configurations of the lower limb corresponding to increments of 10° at the knee from 30 to 100° of knee flexion. Concentric and eccentric contractions were performed over the same range of motion at mean angular velocities of the knee from 30 to 240° s(-1). For contractions of increasing velocity, optimum knee angle shifted from 52 ± 7 to 64 ± 4° knee flexion. Furthermore, the curvature of the concentric force/torque-angular velocity relations varied with joint angles and maximum angular velocities increased from 866 ± 79 to 1,238 ± 132° s(-1) for 90-50° knee flexion. Normalised eccentric forces/torques ranged from 0.85 ± 0.12 to 1.32 ± 0.16 of their isometric reference, only showing significant increases above isometric and an effect of angular velocity for joint angles greater than optimum knee angle. The findings reveal that force/torque production during multi-joint leg extension depends on the combined effects of angle and angular velocity. This finding should be accounted for in modelling and optimisation of human movement.

Performance comparison of independent component analysis algorithms for fetal cardiac signal reconstruction: a study on synthetic fMCG data

NASA Astrophysics Data System (ADS)

Mantini, D.; Hild, K. E., II; Alleva, G.; Comani, S.

2006-02-01

Independent component analysis (ICA) algorithms have been successfully used for signal extraction tasks in the field of biomedical signal processing. We studied the performances of six algorithms (FastICA, CubICA, JADE, Infomax, TDSEP and MRMI-SIG) for fetal magnetocardiography (fMCG). Synthetic datasets were used to check the quality of the separated components against the original traces. Real fMCG recordings were simulated with linear combinations of typical fMCG source signals: maternal and fetal cardiac activity, ambient noise, maternal respiration, sensor spikes and thermal noise. Clusters of different dimensions (19, 36 and 55 sensors) were prepared to represent different MCG systems. Two types of signal-to-interference ratios (SIR) were measured. The first involves averaging over all estimated components and the second is based solely on the fetal trace. The computation time to reach a minimum of 20 dB SIR was measured for all six algorithms. No significant dependency on gestational age or cluster dimension was observed. Infomax performed poorly when a sub-Gaussian source was included; TDSEP and MRMI-SIG were sensitive to additive noise, whereas FastICA, CubICA and JADE showed the best performances. Of all six methods considered, FastICA had the best overall performance in terms of both separation quality and computation times.

Device-independent quantum key distribution

NASA Astrophysics Data System (ADS)

Hänggi, Esther

2010-12-01

In this thesis, we study two approaches to achieve device-independent quantum key distribution: in the first approach, the adversary can distribute any system to the honest parties that cannot be used to communicate between the three of them, i.e., it must be non-signalling. In the second approach, we limit the adversary to strategies which can be implemented using quantum physics. For both approaches, we show how device-independent quantum key distribution can be achieved when imposing an additional condition. In the non-signalling case this additional requirement is that communication is impossible between all pairwise subsystems of the honest parties, while, in the quantum case, we demand that measurements on different subsystems must commute. We give a generic security proof for device-independent quantum key distribution in these cases and apply it to an existing quantum key distribution protocol, thus proving its security even in this setting. We also show that, without any additional such restriction there always exists a successful joint attack by a non-signalling adversary.

Photonic Choke-Joints for Dual-Polarization Waveguides

NASA Technical Reports Server (NTRS)

Wollack, Edward J.; U-yen, Kongpop; Chuss, David T.

2010-01-01

Photonic choke joint (PCJ) structures for dual-polarization waveguides have been investigated for use in device and component packaging. This interface enables the realization of a high performance non-contacting waveguide joint without degrading the in-band signal propagation properties. The choke properties of two tiling approaches, symmetric square Cartesian and octagonal quasi-crystal lattices of metallic posts, are explored and optimal PCJ design parameters are presented. For each of these schemes, the experimental results for structures with finite tilings demonstrate near ideal transmission and reflection performance over a full waveguide band.

Prevention of the Post-traumatic Fibrotic Response in Joints

DTIC Science & Technology

2014-10-01

JJ, Wolman M. Aging of wound healing in an experimental model in mice. The American journal of forensic medicine and pathology . 1988; 9(4):310-2...SUPPLEMENTARY NOTES 14. ABSTRACT The ongoing study addresses the critical clinical problem of posttraumatic joint stiffness, a pathology that reduces...study is that pathological fibrotic response of injured joint tissues may be limited by targeting the formation of collagen fibrils, a main component

Different brain activations between own- and other-race face categorization: an fMRI study using group independent component analysis

NASA Astrophysics Data System (ADS)

Wei, Wenjuan; Liu, Jiangang; Dai, Ruwei; Feng, Lu; Li, Ling; Tian, Jie

2014-03-01

Previous behavioral research has proved that individuals process own- and other-race faces differently. One well-known effect is the other-race effect (ORE), which indicates that individuals categorize other-race faces more accurately and faster than own-race faces. The existed functional magnetic resonance imaging (fMRI) studies of the other-race effect mainly focused on the racial prejudice and the socio-affective differences towards own- and other-race face. In the present fMRI study, we adopted a race-categorization task to determine the activation level differences between categorizing own- and other-race faces. Thirty one Chinese participants who live in China with Chinese as the majority and who had no direct contact with Caucasian individual were recruited in the present study. We used the group independent component analysis (ICA), which is a method of blind source signal separation that has proven to be promising for analysis of fMRI data. We separated the entail data into 56 components which is estimated based on one subject using the Minimal Description Length (MDL) criteria. The components sorted based on the multiple linear regression temporal sorting criteria, and the fit regression parameters were used in performing statistical test to evaluate the task-relatedness of the components. The one way anova was performed to test the significance of the component time course in different conditions. Our result showed that the areas, which coordinates is similar to the right FFA coordinates that previous studies reported, were greater activated for own-race faces than other-race faces, while the precuneus showed greater activation for other-race faces than own-race faces.

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

PubMed Central

Ju, Jin Hyun; Crystal, Ronald G.

2017-01-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci.

PubMed

Ju, Jin Hyun; Shenoy, Sushila A; Crystal, Ronald G; Mezey, Jason G

2017-05-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In

Temporal dynamics of sensorimotor integration in speech perception and production: independent component analysis of EEG data

PubMed Central

Jenson, David; Bowers, Andrew L.; Harkrider, Ashley W.; Thornton, David; Cuellar, Megan; Saltuklaroglu, Tim

2014-01-01

Activity in anterior sensorimotor regions is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20 Hz) and alpha (~10 Hz) spectral power within the EEG μ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different) of syllables pairs (/ba/ and /da/) in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to (1) identify clusters of μ components common to all conditions and (2) examine real-time event-related spectral perturbations (ERSP) within alpha and beta bands. 17 and 15 out of 20 participants produced left and right μ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR < 0.05) early alpha event-related synchronization (ERS) prior to and during stimulus presentation and later alpha event-related desynchronization (ERD) following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that μ-beta ERD indexes early predictive coding (e.g., internal modeling) and/or overt and covert attentional/motor processes. μ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while μ-alpha ERD may index sensory feedback during speech rehearsal and production. PMID:25071633

The Effects of Fluid Absorption on the Mechanical Properties of Joint Prostheses Components

NASA Astrophysics Data System (ADS)

Yarbrough, David; Viano, Ann

2010-02-01

Ultra-high-molecular-weight polyethylene (UHMWPE) is the material playing the role of cartilage in human prosthetic joints. Wear debris from UHMWPE is a common reason for joint arthroplasty failure, and the exact mechanism responsible for wear remains an area of investigation. In this study, the microstructure of UHMWPE was examined as a function of fluid absorption. Samples with varying exposure to e-beam radiation (as part of the manufacturing process) were soaked for forty days in saline or artificial synovial fluid, under zero or 100 lbs load. Samples were then tensile-tested according to ASTM D-3895. The post-stressed material was then examined by transmission electron microscopy to evaluate the molecular response to stress, which correlates with macroscopic mechanical properties. Three parameters of the crystalline lamellae were measured: thickness, stacking ratio, and alignment to stress direction. Results indicate that fluid absorption does affect the mechanical properties of UHMWPE at both the microscopic and microscopic levels. )

Analysis and testing of a space crane articulating joint testbed

NASA Technical Reports Server (NTRS)

Sutter, Thomas R.; Wu, K. Chauncey

1992-01-01

The topics are presented in viewgraph form and include: space crane concept with mobile base; mechanical versus structural articulating joint; articulating joint test bed and reference truss; static and dynamic characterization completed for space crane reference truss configuration; improved linear actuators reduce articulating joint test bed backlash; 1-DOF space crane slew maneuver; boom 2 tip transient response finite element dynamic model; boom 2 tip transient response shear-corrected component modes torque driver profile; peak root member force vs. slew time torque driver profile; and open loop control of space crane motion.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

PubMed

Aragri, Adriana; Scarabino, Tommaso; Seifritz, Erich; Comani, Silvia; Cirillo, Sossio; Tedeschi, Gioacchino; Esposito, Fabrizio; Di Salle, Francesco

2006-09-01

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity. (c) 2006 Wiley-Liss, Inc.

Experiences in the development of rotary joints for robotic manipulators in space applications

NASA Technical Reports Server (NTRS)

Priesett, Klaus

1992-01-01

European developments in robotics for space applications have resulted in human arm-like manipulators with six or more rotational degrees of freedom. The rotary joints including their own electromechanical actuator and feedback sensors must be very compact units. The specific joint concept is presented as evolved so far. The problems encountered during the first hardware development phases are covered on both component and joint level.

Current Space Station Experiments Investigating Component Level Electronics Repair

NASA Technical Reports Server (NTRS)

Easton, John W.; Struk, Peter M.

2010-01-01

The Soldering in a Reduced Gravity Experiment (SoRGE) and Component Repair Experiment (CRE)-1 are tests performed on the International Space Station to determine the techniques, tools, and training necessary to allow future crews to perform manual electronics repairs at the component level. SoRGE provides information on the formation and internal structure of through-hole solder joints, illustrating the challenges and implications of soldering in reduced gravity. SoRGE showed a significant increase in internal void defects for joints formed in low gravity compared to normal gravity. Methods for mitigating these void defects were evaluated using a modified soldering process. CRE-1 demonstrated the removal, cleaning, and replacement of electronics components by manual means on functional circuit boards. The majority of components successful passed a post-repair functional test demonstrating the feasibility of component-level repair within the confines of a spacecraft. Together, these tasks provide information to recommend material and tool improvements, training improvements, and future work to help enable electronics repairs in future space missions.

Dietary correlates of temporomandibular joint morphology in the great apes.

PubMed

Terhune, Claire E

2013-02-01

Behavioral observations of great apes have consistently identified differences in feeding behavior among species, and these differences have been linked to variation in masticatory form. As the point at which the mandible and cranium articulate, the temporomandibular joint (TMJ) is an important component of the masticatory apparatus. Forces are transmitted between the mandible and cranium via the TMJ, and this joint helps govern mandibular range of motion. This study examined the extent to which TMJ form covaries with feeding behavior in the great apes by testing a series of biomechanical hypotheses relating to specific components of joint shape using linear measurements extracted from three-dimensional coordinate data. Results of these analyses found that taxa differ significantly in TMJ shape, particularly in the mandibular fossa. Chimpanzees have relatively more anteroposteriorly elongated joint surfaces, whereas gorillas tend to have relatively anteroposteriorly compressed joints. Orangutans were most commonly intermediate in form between Pan and Gorilla, perhaps reflecting a trade-off between jaw gape and load resistance capabilities. Importantly, much of the observed variation among taxa reflects differences in morphologies that facilitate gape over force production. These data therefore continue to emphasize the unclear relationship between mandibular loading and bony morphology, but highlight the need for further data regarding food material properties, jaw gape, and ingestive/food processing behaviors. Copyright © 2012 Wiley Periodicals, Inc.

Nuclear domain 10 components promyelocytic leukemia protein and hDaxx independently contribute to an intrinsic antiviral defense against human cytomegalovirus infection.

PubMed

Tavalai, Nina; Papior, Peer; Rechter, Sabine; Stamminger, Thomas

2008-01-01

Infection with DNA viruses commonly results in the association of viral genomes with a cellular subnuclear structure known as nuclear domain 10 (ND10). Recent studies demonstrated that individual ND10 components, like hDaxx or promyelocytic leukemia protein (PML), mediate an intrinsic immune response against human cytomegalovirus (HCMV) infection, strengthening the assumption that ND10 components are part of a cellular antiviral defense mechanism. In order to further define the role of hDaxx and PML for HCMV replication, we generated either primary human fibroblasts with a stable, individual knockdown of PML or hDaxx (PML-kd and hDaxx-kd, respectively) or cells exhibiting a double knockdown. Comparative analysis of HCMV replication in PML-kd or hDaxx-kd cells revealed that immediate-early (IE) gene expression increased to a similar extent, regardless of which ND10 constituent was depleted. Since a loss of PML, the defining component of ND10, results in a dispersal of the entire nuclear substructure, the increased replication efficacy of HCMV in PML-kd cells could be a consequence of the dissociation of the repressor protein hDaxx from its optimal subnuclear localization. However, experiments using three different recombinant HCMVs revealed a differential growth complementation in PML-kd versus hDaxx-kd cells, strongly arguing for an independent involvement in suppressing HCMV replication. Furthermore, infection experiments using double-knockdown cells devoid of both PML and hDaxx illustrated an additional enhancement in the replication efficacy of HCMV compared to the single-knockdown cells. Taken together, our data indicate that both proteins, PML and hDaxx, mediate an intrinsic immune response against HCMV infection by contributing independently to the silencing of HCMV IE gene expression.

The Independent and Joint Association of Blood Pressure, Serum Total Homocysteine, and Fasting Serum Glucose Levels With Brachial-Ankle Pulse Wave Velocity in Chinese Hypertensive Adults.

PubMed

Liu, Xiaoyun; Sun, Ningling; Yu, Tao; Fan, Fangfang; Zheng, Meili; Qian, Geng; Wang, Binyan; Wang, Yu; Tang, Genfu; Li, Jianping; Qin, Xianhui; Hou, Fanfan; Xu, Xiping; Yang, Xinchun; Chen, Yundai; Wang, Xiaobin; Huo, Yong

2016-09-28

This study aimed to investigate the independent and joint association of blood pressure (BP), homocysteine (Hcy), and fasting blood glucose (FBG) levels with brachial-ankle pulse wave velocity (baPWV, a measure of arterial stiffness) in Chinese hypertensive adults.The analyses included 3967 participants whose BP, Hcy, FBG, and baPWV were measured along with other covariates. Systolic BP (SBP) was analyzed as 3 categories (SBP < 160 mmHg; 160 to 179 mmHg; ≥ 180 mmHg); Hcy as 3 categories (< 10 μmol/L; 10 to 14.9 μmol/L; ≥ 15.0 μmol/L) and FBG: normal (FBG < 5.6 mmol/L), impaired (5.6 mmol/L ≤ FBG < 7.0 mmol/L), and diabetes mellitus (FBG ≥ 7.0 mmol/L). We performed linear regression analyses to evaluate their associations with baPWV with adjustment for covariables.When analyzed individually, BP, Hcy, and FBG were each associated with baPWV. When BP and FBG were analyzed jointly, the highest baPWV value (mean ± SD: 2227 ± 466 cm/s) was observed in participants with FBG ≥ 7.0 mmol/L and SBP ≥ 180 mmHg (β = 432.5, P < 0.001), and the lowest baPWV value (mean ± SD: 1692 ± 289 cm/s) was seen in participants with NFG and SBP < 160 mmHg. When Hcy and FBG were analyzed jointly, the highest baPWV value (2072 ± 480 cm/s) was observed in participants with FBG ≥ 7.0 mmol/L and Hcy ≥ 15.0 μmol/L (β = 167.6, P < 0.001), while the lowest baPWV value (mean ± SD: 1773 ± 334 cm/s) was observed in participants with NFG and Hcy < 10 μmol/L.In Chinese hypertensive adults, SBP, Hcy, and FBG are individually and jointly associated with baPWV.Our findings underscore the importance of identifying individuals with multiple risk factors of baPWV including high SBP, FBG, and Hcy.

Stealthy false data injection attacks using matrix recovery and independent component analysis in smart grid

NASA Astrophysics Data System (ADS)

JiWei, Tian; BuHong, Wang; FuTe, Shang; Shuaiqi, Liu

2017-05-01

Exact state estimation is vital important to maintain common operations of smart grids. Existing researches demonstrate that state estimation output could be compromised by malicious attacks. However, to construct the attack vectors, a usual presumption in most works is that the attacker has perfect information regarding the topology and so on even such information is difficult to acquire in practice. Recent research shows that Independent Component Analysis (ICA) can be used for inferring topology information which can be used to originate undetectable attacks and even to alter the price of electricity for the profits of attackers. However, we found that the above ICA-based blind attack tactics is merely feasible in the environment with Gaussian noises. If there are outliers (device malfunction and communication errors), the Bad Data Detector will easily detect the attack. Hence, we propose a robust ICA based blind attack strategy that one can use matrix recovery to circumvent the outlier problem and construct stealthy attack vectors. The proposed attack strategies are tested with IEEE representative 14-bus system. Simulations verify the feasibility of the proposed method.

Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis.

PubMed

Lin, Yuan-Pin; Duann, Jeng-Ren; Feng, Wenfeng; Chen, Jyh-Horng; Jung, Tzyy-Ping

2014-02-28

Music conveys emotion by manipulating musical structures, particularly musical mode- and tempo-impact. The neural correlates of musical mode and tempo perception revealed by electroencephalography (EEG) have not been adequately addressed in the literature. This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo. Empirical results showed that music with major mode augmented delta-band activity over the right sensorimotor cortex, suppressed theta activity over the superior parietal cortex, and moderately suppressed beta activity over the medial frontal cortex, compared to minor-mode music, whereas fast-tempo music engaged significant alpha suppression over the right sensorimotor cortex. The resultant EEG brain sources were comparable with previous studies obtained by other neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and entertainment in naturalistic environments.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-01

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: the case of domain motions.

PubMed

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-14

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Jointness or Jointless at Leyte

DTIC Science & Technology

1989-03-31

tol JOINTNESS OR JOINTLESS AT LEYTE BY LIEUTENANT COLONEL KENNY J. JEFFERSON DESTRIBUTION STATMMERT A: Approved IoT Publ.C rx f. df trf~iitien Is...and to -support the operation with naval, air force, and submarine weapon systems and Vrotect against Japanese invasion forces from the surrounding...as the "early warning system " for the fleet and independently engage targets with torpedoes. Admiral Nishimura’s Force C would be the first to enter

Accelerated hand bone mineral density loss is associated with progressive joint damage in hands and feet in recent-onset rheumatoid arthritis.

PubMed

Güler-Yüksel, Melek; Klarenbeek, Naomi B; Goekoop-Ruiterman, Yvonne P M; de Vries-Bouwstra, Jeska K; van der Kooij, Sjoerd M; Gerards, Andreas H; Ronday, H Karel; Huizinga, Tom W J; Dijkmans, Ben A C; Allaart, Cornelia F; Lems, Willem F

2010-01-01

To investigate whether accelerated hand bone mineral density (BMD) loss is associated with progressive joint damage in hands and feet in the first year of rheumatoid arthritis (RA) and whether it is an independent predictor of subsequent progressive total joint damage after 4 years. In 256 recent-onset RA patients, baseline and 1-year hand BMD was measured in metacarpals 2-4 by digital X-ray radiogrammetry. Joint damage in hands and feet were scored in random order according to the Sharp-van der Heijde method at baseline and yearly up to 4 years. 68% of the patients had accelerated hand BMD loss (>-0.003 g/cm2) in the first year of RA. Hand BMD loss was associated with progressive joint damage after 1 year both in hands and feet with odds ratios (OR) (95% confidence intervals [CI]) of 5.3 (1.3-20.9) and 3.1 (1.0-9.7). In univariate analysis, hand BMD loss in the first year was a predictor of subsequent progressive total joint damage after 4 years with an OR (95% CI) of 3.1 (1.3-7.6). Multivariate analysis showed that only progressive joint damage in the first year and anti-citrullinated protein antibody positivity were independent predictors of long-term progressive joint damage. In the first year of RA, accelerated hand BMD loss is associated with progressive joint damage in both hands and feet. Hand BMD loss in the first year of recent-onset RA predicts subsequent progressive total joint damage, however not independent of progressive joint damage in the first year.

N-ethylmaleimide activates a Cl−-independent component of K+ flux in mouse erythrocytes

PubMed Central

Shmukler, Boris E.; Hsu, Ann; Alves, Jessica; Trudel, Marie; Rust, Marco B.; Hubner, Christian A.; Rivera, Alicia; Alper, Seth L.

2013-01-01

The K-Cl cotransporters (KCCs) of mouse erythrocytes exhibit higher basal activity than those of human erythrocytes, but are similarly activated by cell swelling, by hypertonic urea, and by staurosporine. However, the dramatic stimulation of human erythroid KCCs by N-ethylmaleimide (NEM) is obscured in mouse erythrocytes by a prominent NEM-stimulated K+ efflux that lacks Cl−-dependence. The NEM-sensitivity of Cl−-independent K+ efflux of mouse erythrocytes is lower than that of KCC. The genetically engineered absence of the K-Cl cotransporters KCC3 and KCC1 from mouse erythrocytes does not modify Cl−-independent K+ efflux. Mouse erythrocytes genetically devoid of the Gardos channel KCNN4 show increased NEM-sensitivity of both Cl−-independent K+ efflux and K-Cl cotransport. The increased NEM-sensitivity and stimulation magnitude of Cl−-independent K+ efflux in mouse erythrocytes expressing transgenic hypersickling human hemoglobin SAD (HbSAD) is independent of the presence of KCC3 and KCC1, but absence of KCNN4 reduces the stimulatory effect of HbSAD. NEM-stimulated Cl−-independent K+ efflux of mouse red cells is insensitive to ouabain and bumetanide, but partially inhibited by chloroquine, barium, and amiloride. The NEM-stimulated activity is modestly reduced at pH 6.0, but not significantly altered at pH 8.0, and abolished at 0°C. Although the molecular identity of this little-studied K+ efflux pathway of mouse erythrocytes remains unknown, it’s potential role in the pathophysiology of sickle red cell dehydration will be important for extrapolation of studies in mouse models of sickle cell disease to our understanding of humans with sickle cell anemia. PMID:23481459

Software component quality evaluation

NASA Technical Reports Server (NTRS)

Clough, A. J.

1991-01-01

The paper describes a software inspection process that can be used to evaluate the quality of software components. Quality criteria, process application, independent testing of the process and proposed associated tool support are covered. Early results indicate that this technique is well suited for assessing software component quality in a standardized fashion. With automated machine assistance to facilitate both the evaluation and selection of software components, such a technique should promote effective reuse of software components.

Using the in-line component for fixed-wing EM 1D inversion

NASA Astrophysics Data System (ADS)

Smiarowski, Adam

2015-09-01

Numerous authors have discussed the utility of multicomponent measurements. Generally speaking, for a vertical-oriented dipole source, the measured vertical component couples to horizontal planar bodies while the horizontal in-line component couples best to vertical planar targets. For layered-earth cases, helicopter EM systems have little or no in-line component response and as a result much of the in-line signal is due to receiver coil rotation and appears as noise. In contrast to this, the in-line component of a fixed-wing airborne electromagnetic (AEM) system with large transmitter-receiver offset can be substantial, exceeding the vertical component in conductive areas. This paper compares the in-line and vertical response of a fixed-wing airborne electromagnetic (AEM) system using a half-space model and calculates sensitivity functions. The a posteriori inversion model parameter uncertainty matrix is calculated for a bathymetry model (conductive layer over more resistive half-space) for two inversion cases; use of vertical component alone is compared to joint inversion of vertical and in-line components. The joint inversion is able to better resolve model parameters. An example is then provided using field data from a bathymetry survey to compare the joint inversion to vertical component only inversion. For each inversion set, the difference between the inverted water depth and ship-measured bathymetry is calculated. The result is in general agreement with that expected from the a posteriori inversion model parameter uncertainty calculation.

Interoperability Assets for Patient Summary Components: A Gap Analysis.

PubMed

Heitmann, Kai U; Cangioli, Giorgio; Melgara, Marcello; Chronaki, Catherine

2018-01-01

The International Patient Summary (IPS) standards aim to define the specifications for a minimal and non-exhaustive Patient Summary, which is specialty-agnostic and condition-independent, but still clinically relevant. Meanwhile, health systems are developing and implementing their own variation of a patient summary while, the eHealth Digital Services Infrastructure (eHDSI) initiative is deploying patient summary services across countries in the Europe. In the spirit of co-creation, flexible governance, and continuous alignment advocated by eStandards, the Trillum-II initiative promotes adoption of the patient summary by engaging standards organizations, and interoperability practitioners in a community of practice for digital health to share best practices, tools, data, specifications, and experiences. This paper compares operational aspects of patient summaries in 14 case studies in Europe, the United States, and across the world, focusing on how patient summary components are used in practice, to promote alignment and joint understanding that will improve quality of standards and lower costs of interoperability.

Laser hybrid joining of plastic and metal components for lightweight components

NASA Astrophysics Data System (ADS)

Rauschenberger, J.; Cenigaonaindia, A.; Keseberg, J.; Vogler, D.; Gubler, U.; Liébana, F.

2015-03-01

Plastic-metal hybrids are replacing all-metal structures in the automotive, aerospace and other industries at an accelerated rate. The trend towards lightweight construction increasingly demands the usage of polymer components in drive trains, car bodies, gaskets and other applications. However, laser joining of polymers to metals presents significantly greater challenges compared with standard welding processes. We present recent advances in laser hybrid joining processes. Firstly, several metal pre-structuring methods, including selective laser melting (SLM) are characterized and their ability to provide undercut structures in the metal assessed. Secondly, process parameter ranges for hybrid joining of a number of metals (steel, stainless steel, etc.) and polymers (MABS, PA6.6-GF35, PC, PP) are given. Both transmission and direct laser joining processes are presented. Optical heads and clamping devices specifically tailored to the hybrid joining process are introduced. Extensive lap-shear test results are shown that demonstrate that joint strengths exceeding the base material strength (cohesive failure) can be reached with metal-polymer joining. Weathering test series prove that such joints are able to withstand environmental influences typical in targeted fields of application. The obtained results pave the way toward implementing metalpolymer joints in manufacturing processes.

Estimation of joint stiffness with a compliant load.

PubMed

Ludvig, Daniel; Kearney, Robert E

2009-01-01

Joint stiffness defines the dynamic relationship between the position of the joint and the torque acting about it. It consists of two components: intrinsic and reflex stiffness. Many previous studies have investigated joint stiffness in an open-loop environment, because the current algorithm in use is an open-loop algorithm. This paper explores issues related to the estimation of joint stiffness when subjects interact with compliant loads. First, we show analytically how the bias in closed-loop estimates of joint stiffness depends on the properties of the load, the noise power, and length of the estimated impulse response functions (IRF). We then demonstrate with simulations that the open-loop analysis will fail completely for an elastic load but may succeed for an inertial load. We further show that the open-loop analysis can yield unbiased results with an inertial load and document IRF length, signal-to-noise ratio needed, and minimum inertia needed for the analysis to succeed. Thus, by using a load with a properly selected inertia, open-loop analysis can be used under closed-loop conditions.

Hierarchical Time-Lagged Independent Component Analysis: Computing Slow Modes and Reaction Coordinates for Large Molecular Systems.

PubMed

Pérez-Hernández, Guillermo; Noé, Frank

2016-12-13

Analysis of molecular dynamics, for example using Markov models, often requires the identification of order parameters that are good indicators of the rare events, i.e. good reaction coordinates. Recently, it has been shown that the time-lagged independent component analysis (TICA) finds the linear combinations of input coordinates that optimally represent the slow kinetic modes and may serve in order to define reaction coordinates between the metastable states of the molecular system. A limitation of the method is that both computing time and memory requirements scale with the square of the number of input features. For large protein systems, this exacerbates the use of extensive feature sets such as the distances between all pairs of residues or even heavy atoms. Here we derive a hierarchical TICA (hTICA) method that approximates the full TICA solution by a hierarchical, divide-and-conquer calculation. By using hTICA on distances between heavy atoms we identify previously unknown relaxation processes in the bovine pancreatic trypsin inhibitor.

Artificial atlanto-odontoid joint replacement through a transoral approach.

PubMed

Lu, Bin; He, Xi Jing; Zhao, Chen Guang; Li, Hao Peng; Wang, Dong

2009-01-01

Resection of the odontoid process and anterior arch of the atlas results in atlantoaxial instability, which if left uncorrected may lead to severe neurological complications. Currently, such atlantoaxial instability is corrected by anterior and/or posterior C1-C2 fusion. However, this results in considerable loss of rotation function of the atlantoaxial complex. From the viewpoint of retaining the rotation function and providing stability, we designed an artificial atlanto-odontoid joint based on anatomical measurements of 50 pairs of dry atlantoaxial specimens by digital calipers and 10 fresh cadaveric specimens by microsurgical techniques. The metal-on-metal titanium alloy joint has an arc-shaped atlas component, and a hollow cylindrical bushing into which fits a rotation axle of an inverted v-shaped axis component and is implanted through a transoral approach. After the joint was implanted onto specimens with anterior decompression, biomechanical tests were performed to compare the stability parameters in the intact state, after decompression, after artificial joint replacement, and after fatigue test. Compared to the intact state, artificial joint replacement resulted in a significant decrease in the range of motion (ROM) and neutral zone (NZ) during flexion, extension, and lateral bending (P < 0.001); however, with regard to axial rotation, there was no significant difference in ROM (P = 0.405), a significant increase in NZ (P = 0.008), and a significant decrease in stiffness (P = 0.003). Compared to the decompressed state, artificial joint replacement resulted in a significantly decreased ROM (P B 0.021) and NZ (P B 0.002) and a significantly increased stiffness (P \\ 0.001) in all directions. Following artificial joint replacement, there was no significant difference in ROM (P C 0.719), NZ (P C 0.580), and stiffness (P C 0.602) in all directions before and after the fatigue test. The artificial joint showed no signs of wear and tear after the fatigue test

Artificial atlanto-odontoid joint replacement through a transoral approach

PubMed Central

Lu, Bin; Zhao, Chen Guang; Li, Hao Peng; Wang, Dong

2008-01-01

Resection of the odontoid process and anterior arch of the atlas results in atlantoaxial instability, which if left uncorrected may lead to severe neurological complications. Currently, such atlantoaxial instability is corrected by anterior and/or posterior C1–C2 fusion. However, this results in considerable loss of rotation function of the atlantoaxial complex. From the viewpoint of retaining the rotation function and providing stability, we designed an artificial atlanto-odontoid joint based on anatomical measurements of 50 pairs of dry atlantoaxial specimens by digital calipers and 10 fresh cadaveric specimens by microsurgical techniques. The metal-on-metal titanium alloy joint has an arc-shaped atlas component, and a hollow cylindrical bushing into which fits a rotation axle of an inverted v-shaped axis component and is implanted through a transoral approach. After the joint was implanted onto specimens with anterior decompression, biomechanical tests were performed to compare the stability parameters in the intact state, after decompression, after artificial joint replacement, and after fatigue test. Compared to the intact state, artificial joint replacement resulted in a significant decrease in the range of motion (ROM) and neutral zone (NZ) during flexion, extension, and lateral bending (P < 0.001); however, with regard to axial rotation, there was no significant difference in ROM (P = 0.405), a significant increase in NZ (P = 0.008), and a significant decrease in stiffness (P = 0.003). Compared to the decompressed state, artificial joint replacement resulted in a significantly decreased ROM (P ≤ 0.021) and NZ (P ≤ 0.002) and a significantly increased stiffness (P < 0.001) in all directions. Following artificial joint replacement, there was no significant difference in ROM (P ≥ 0.719), NZ (P ≥ 0.580), and stiffness (P ≥ 0.602) in all directions before and after the fatigue test. The artificial joint showed no signs of wear and

Associations between different components of fitness and fatness with academic performance in Chilean youths

PubMed Central

2016-01-01

Objectives To analyze the associations between different components of fitness and fatness with academic performance, adjusting the analysis by sex, age, socio-economic status, region and school type in a Chilean sample. Methods Data of fitness, fatness and academic performance was obtained from the Chilean System for the Assessment of Educational Quality test for eighth grade in 2011 and includes a sample of 18,746 subjects (49% females). Partial correlations adjusted by confounders were done to explore association between fitness and fatness components, and between the academic scores. Three unadjusted and adjusted linear regression models were done in order to analyze the associations of variables. Results Fatness has a negative association with academic performance when Body Mass Index (BMI) and Waist to Height Ratio (WHR) are assessed independently. When BMI and WHR are assessed jointly and adjusted by cofounders, WHR is more associated with academic performance than BMI, and only the association of WHR is positive. For fitness components, strength was the variable most associated with the academic performance. Cardiorespiratory capacity was not associated with academic performance if fatness and other fitness components are included in the model. Conclusions Fitness and fatness are associated with academic performance. WHR and strength are more related with academic performance than BMI and cardiorespiratory capacity. PMID:27761345

Associations between different components of fitness and fatness with academic performance in Chilean youths.

PubMed

Olivares, Pedro R; García-Rubio, Javier

2016-01-01

To analyze the associations between different components of fitness and fatness with academic performance, adjusting the analysis by sex, age, socio-economic status, region and school type in a Chilean sample. Data of fitness, fatness and academic performance was obtained from the Chilean System for the Assessment of Educational Quality test for eighth grade in 2011 and includes a sample of 18,746 subjects (49% females). Partial correlations adjusted by confounders were done to explore association between fitness and fatness components, and between the academic scores. Three unadjusted and adjusted linear regression models were done in order to analyze the associations of variables. Fatness has a negative association with academic performance when Body Mass Index (BMI) and Waist to Height Ratio (WHR) are assessed independently. When BMI and WHR are assessed jointly and adjusted by cofounders, WHR is more associated with academic performance than BMI, and only the association of WHR is positive. For fitness components, strength was the variable most associated with the academic performance. Cardiorespiratory capacity was not associated with academic performance if fatness and other fitness components are included in the model. Fitness and fatness are associated with academic performance. WHR and strength are more related with academic performance than BMI and cardiorespiratory capacity.

Measurement of gastrocnemius muscle elasticity by shear wave elastography: association with passive ankle joint stiffness and sex differences.

PubMed

Chino, Kentaro; Takahashi, Hideyuki

2016-04-01

Passive joint stiffness is an important quantitative measure of flexibility, but is affected by muscle volume and all of the anatomical structures located within and over the joint. Shear wave elastography can assess muscle elasticity independent of the influences of muscle volume and the other nearby anatomical structures. We determined how muscle elasticity, as measured using shear wave elastography, is associated with passive joint stiffness and patient sex. Twenty-six healthy men (24.4 ± 5.9 years) and 26 healthy women (25.2 ± 4.8 years) participated in this study. The passive ankle joint stiffness and tissue elasticity of the medial gastrocnemius (MG) were quantified with the ankle in 30° plantar flexion (PF), a neutral anatomical position (NE), and 20° dorsiflexion (DF). No significant difference in passive joint stiffness by sex was observed with the ankle in PF, but significantly greater passive ankle joint stiffness in men than in women was observed in NE and DF. The MG elasticity was not significantly associated with joint stiffness in PF or NE, but it was significantly associated with joint stiffness in DF. There were no significant differences in MG elasticity by sex at any ankle position. Muscle elasticity, measured independent of the confounding effects of muscle volume and the other nearby anatomical structures, is associated with passive joint stiffness in the joint position where the muscle is sufficiently lengthened, but does not vary by sex in any joint position tested.

N-ethylmaleimide activates a Cl(-)-independent component of K(+) flux in mouse erythrocytes.

PubMed

Shmukler, Boris E; Hsu, Ann; Alves, Jessica; Trudel, Marie; Rust, Marco B; Hubner, Christian A; Rivera, Alicia; Alper, Seth L

2013-06-01

The K-Cl cotransporters (KCCs) of mouse erythrocytes exhibit higher basal activity than those of human erythrocytes, but are similarly activated by cell swelling, by hypertonic urea, and by staurosporine. However, the dramatic stimulation of human erythroid KCCs by N-ethylmaleimide (NEM) is obscured in mouse erythrocytes by a prominent NEM-stimulated K(+) efflux that lacks Cl(-)-dependence. The NEM-sensitivity of Cl(-)-independent K(+) efflux of mouse erythrocytes is lower than that of KCC. The genetically engineered absence of the K-Cl cotransporters KCC3 and KCC1 from mouse erythrocytes does not modify Cl(-)-independent K(+) efflux. Mouse erythrocytes genetically devoid of the Gardos channel KCNN4 show increased NEM-sensitivity of both Cl(-)-independent K(+) efflux and K-Cl cotransport. The increased NEM-sensitivity and stimulation magnitude of Cl(-)-independent K(+) efflux in mouse erythrocytes expressing transgenic hypersickling human hemoglobin SAD (HbSAD) are independent of the presence of KCC3 and KCC1, but absence of KCNN4 reduces the stimulatory effect of HbSAD. NEM-stimulated Cl(-)-independent K(+) efflux of mouse red cells is insensitive to ouabain and bumetanide, but partially inhibited by chloroquine, barium, and amiloride. The NEM-stimulated activity is modestly reduced at pH6.0 but not significantly altered at pH8.0, and is abolished at 0°C. Although the molecular identity of this little-studied K(+) efflux pathway of mouse erythrocytes remains unknown, its potential role in the pathophysiology of sickle red cell dehydration will be important for the extrapolation of studies in mouse models of sickle cell disease to our understanding of humans with sickle cell anemia. Copyright © 2013 Elsevier Inc. All rights reserved.

Interventions for treating osteoarthritis of the big toe joint.

PubMed

Zammit, Gerard V; Menz, Hylton B; Munteanu, Shannon E; Landorf, Karl B; Gilheany, Mark F

2010-09-08

Osteoarthritis affecting of the big toe joint of the foot (hallux limitus or rigidus) is a common and painful condition. Although several treatments have been proposed, few have been adequately evaluated. To identify controlled trials evaluating interventions for osteoarthritis of the big toe joint and to determine the optimum intervention(s). Literature searches were conducted across the following electronic databases: CENTRAL; MEDLINE; EMBASE; CINAHL; and PEDro (to 14th January 2010). No language restrictions were applied. Randomised controlled trials, quasi-randomised trials, or controlled clinical trials that assessed treatment outcomes for osteoarthritis of the big toe joint. Participants of any age or gender with osteoarthritis of the big toe joint (defined either radiographically or clinically) were included. Two authors examined the list of titles and abstracts identified by the literature searches. One content area expert and one methodologist independently applied the pre-determined inclusion and exclusion criteria to the full text of identified trials. To minimise error and reduce potential bias, data were extracted independently by two content experts. Only one trial satisfactorily fulfilled the inclusion criteria and was included in this review. This trial evaluated the effectiveness of two physical therapy programs in 20 individuals with osteoarthritis of the big toe joint. Assessment outcomes included pain levels, big toe joint range of motion and plantar flexion strength of the hallux. Mean differences at four weeks follow up were 3.80 points (95% CI 2.74 to 4.86) for self reported pain, 28.30 degrees (95% CI 21.37 to 35.23) for big toe joint range of motion, and 2.80 kg (95% CI 2.13 to 3.47) for muscle strength. Although differences in outcomes between treatment and control groups were reported, the risk of bias was high. The trial failed to employ appropriate randomisation or adequate allocation concealment, used a relatively small sample and

Report of the Commission to Study the Adequacy and Equity of Certain Cost Components of the School Funding Formula. Report to Joint Standing Committee on Education and Cultural Affairs, Maine State Legislature

ERIC Educational Resources Information Center

Center for Education Policy, Applied Research, and Evaluation, 2015

2015-01-01

The Commission to Study the Adequacy and Equity of Certain Cost Components of the School Funding Formula was created in legislation crafted by the Joint Standing Committee on Education of the 126th Legislature (the "Education Committee"). The legislation was enacted as Resolve 2014, chapter 114. Creation of the Commission is the latest…

Assessment of Musculoskeletal Function and its Correlation with Radiological Joint Score in Children with Hemophilia A.

PubMed

Gupta, Samriti; Garg, Kapil; Singh, Jagdish

2015-12-01

To evaluate the functional independence of children with hemophilia A and its correlation to radiological joint score. The present cross sectional study was conducted at SPMCHI, SMS Medical College, Jaipur, India. Children in the age group of 4-18 y affected with severe, moderate and mild hemophilia A and with a history of hemarthrosis who attended the OPD, emergency or got admitted in wards of SPMCHI, SMS Medical College were examined. Musculoskeletal function was measured in 98 patients using Functional Independence Score in Hemophilia (FISH) and index joints (joints most commonly affected with repeated bleeding) were assessed radiologically with plain X rays using Pettersson score. The mean FISH score was 28.07 ± 3.90 (range 17-32) with squatting, running and step climbing as most affected tasks. The mean Pettersson score was 3.8 ± 3.2. A significant correlation was found between mean Pettersson score and FISH (r = -0.875, P < 0.001) with knee and elbow having r = -0.810 and -0.861 respectively, but not in case of ankle with r = -0.420 (P 0.174). The FISH and radiological joint (Pettersson's) scores may be extremely useful in the clinical practice in the absence of magnetic resonance imaging (MRI), which is considered very sensitive to detect early joint damage, but at a cost that makes it relatively inaccessible. FISH seems to be a reliable tool for assessment of functional independence in patients with hemophilia A.

New design for a rotatory joint actuator made with shape memory alloy contractile wire

NASA Astrophysics Data System (ADS)

Wang, Guoping; Shahinpoor, Mohsen

1996-05-01

A design approach for a rotatory joint actuator using a contractile shape memory alloy (SMA) wire is presented and an example design is followed. In this example, the output torque of the actuator is 18 Newton-meters, and its angular range is 30 degrees. Compared with a SMA spring type actuating component, a SMA wire type actuating component uses less SMA material and uses less electrical energy when it is electrically powered. On the other hand, a SMA wire type actuating component must have a large SMA wire length to produce a required amount of angular rotation of the joint. When pulleys are used to arrange a lengthy SMA wire in a small space, the friction between pulleys and pins is introduced and the performance of the joint actuator is degenerated to some degree. The investigated joint actuator provides a good chance for developing powered orthoses with SMA actuators for disabled individuals. It can relieve the weight concern with hydraulic and motor-powered orthoses and the safety concern with motor-powered orthoses. When electrically powered, a SMA actuator has the disadvantage of low energy efficiency.

Spry1 and Spry2 Are Essential for Development of the Temporomandibular Joint

PubMed Central

Purcell, P.; Jheon, A.; Vivero, M.P.; Rahimi, H.; Joo, A.; Klein, O.D.

2012-01-01

The temporomandibular joint (TMJ) is a specialized synovial joint essential for the function of the mammalian jaw. The main components of the TMJ are the mandibular condyle, the glenoid fossa of the temporal bone, and a fibrocartilagenous disc interposed between them. The genetic program for the development of the TMJ remains poorly understood. Here we show the crucial role of sprouty (Spry) genes in TMJ development. Sprouty genes encode intracellular inhibitors of receptor tyrosine kinase (RTK) signaling pathways, including those triggered by fibroblast growth factors (Fgfs). Using in situ hybridization, we show that Spry1 and Spry2 are highly expressed in muscles attached to the TMJ, including the lateral pterygoid and temporalis muscles. The combined inactivation of Spry1 and Spry2 results in overgrowth of these muscles, which disrupts normal development of the glenoid fossa. Remarkably, condyle and disc formation are not affected in these mutants, demonstrating that the glenoid fossa is not required for development of these structures. Our findings demonstrate the importance of regulated RTK signaling during TMJ development and suggest multiple skeletal origins for the fossa. Notably, our work provides the evidence that the TMJ condyle and disc develop independently of the mandibular fossa. PMID:22328578

Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

PubMed

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A; Park, Hyunwook; Yoo, Seung-Schik

2009-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.

Joint Coordination and Muscle Activities of Ballet Dancers During Tiptoe Standing.

PubMed

Tanabe, Hiroko; Fujii, Keisuke; Kouzaki, Motoki

2017-01-01

We aimed to investigate joint coordination of lower limbs in dancers during tiptoe standing and the relationship between joint coordination and muscle coactivation. Seven female ballet dancers performed tiptoe standing with six leg positions (fi e classical dance positions and one modern dance position) for 10 s. The kinematic data of the metatarsophalangeal (MP), ankle, knee, and hip joints was collected, and surface electromyography (EMG) of over 13 lower limb muscles was conducted. Principal component analysis was performed to determine joint coordination. MP-ankle and ankle-knee had in-phase coordination, whereas knee-hip showed anti-phase coordination in the sagittal plane. In addition, most EMG-EMG coherence around the MP and ankle joints was significant up to 50 Hz when these two joints swayed with in-phase. This suggests that different joint coordination patterns are associated with neural processing related to different muscle coactivation patterns. In conclusion, ballet dancers showed in-phase coordination from the MP to knee joints, which was associated with muscle coactivation to a higher frequency domain (up to 50 Hz) in comparison with anti-phase coordination.

Decentralized control of large flexible structures by joint decoupling

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Juang, Jer-Nan

1994-01-01

This paper presents a novel method to design decentralized controllers for large complex flexible structures by using the idea of joint decoupling. Decoupling of joint degrees of freedom from the interior degrees of freedom is achieved by setting the joint actuator commands to cancel the internal forces exerting on the joint degrees of freedom. By doing so, the interactions between substructures are eliminated. The global structure control design problem is then decomposed into several substructure control design problems. Control commands for interior actuators are set to be localized state feedback using decentralized observers for state estimation. The proposed decentralized controllers can operate successfully at the individual substructure level as well as at the global structure level. Not only control design but also control implementation is decentralized. A two-component mass-spring-damper system is used as an example to demonstrate the proposed method.

Temporomandibular joint formation requires two distinct hedgehog-dependent steps.

PubMed

Purcell, Patricia; Joo, Brian W; Hu, Jimmy K; Tran, Pamela V; Calicchio, Monica L; O'Connell, Daniel J; Maas, Richard L; Tabin, Clifford J

2009-10-27

We conducted a genetic analysis of the developing temporo-mandibular or temporomandi-bular joint (TMJ), a highly specialized synovial joint that permits movement and function of the mammalian jaw. First, we used laser capture microdissection to perform a genome-wide expression analysis of each of its developing components. The expression patterns of genes identified in this screen were examined in the TMJ and compared with those of other synovial joints, including the shoulder and the hip joints. Striking differences were noted, indicating that the TMJ forms via a distinct molecular program. Several components of the hedgehog (Hh) signaling pathway are among the genes identified in the screen, including Gli2, which is expressed specifically in the condyle and in the disk of the developing TMJ. We found that mice deficient in Gli2 display aberrant TMJ development such that the condyle loses its growth-plate-like cellular organization and no disk is formed. In addition, we used a conditional strategy to remove Smo, a positive effector of the Hh signaling pathway, from chondrocyte progenitors. This cell autonomous loss of Hh signaling allows for disk formation, but the resulting structure fails to separate from the condyle. Thus, these experiments establish that Hh signaling acts at two distinct steps in disk morphogenesis, condyle initiation, and disk-condyle separation and provide a molecular framework for future studies of the TMJ.

Temporomandibular joint formation requires two distinct hedgehog-dependent steps

PubMed Central

Purcell, Patricia; Joo, Brian W.; Hu, Jimmy K.; Tran, Pamela V.; Calicchio, Monica L.; O'Connell, Daniel J.; Maas, Richard L.; Tabin, Clifford J.

2009-01-01

We conducted a genetic analysis of the developing temporo-mandibular or temporomandi-bular joint (TMJ), a highly specialized synovial joint that permits movement and function of the mammalian jaw. First, we used laser capture microdissection to perform a genome-wide expression analysis of each of its developing components. The expression patterns of genes identified in this screen were examined in the TMJ and compared with those of other synovial joints, including the shoulder and the hip joints. Striking differences were noted, indicating that the TMJ forms via a distinct molecular program. Several components of the hedgehog (Hh) signaling pathway are among the genes identified in the screen, including Gli2, which is expressed specifically in the condyle and in the disk of the developing TMJ. We found that mice deficient in Gli2 display aberrant TMJ development such that the condyle loses its growth-plate-like cellular organization and no disk is formed. In addition, we used a conditional strategy to remove Smo, a positive effector of the Hh signaling pathway, from chondrocyte progenitors. This cell autonomous loss of Hh signaling allows for disk formation, but the resulting structure fails to separate from the condyle. Thus, these experiments establish that Hh signaling acts at two distinct steps in disk morphogenesis, condyle initiation, and disk–condyle separation and provide a molecular framework for future studies of the TMJ. PMID:19815519

A systematic review of the relationship between subchondral bone features, pain and structural pathology in peripheral joint osteoarthritis.

PubMed

Barr, Andrew J; Campbell, T Mark; Hopkinson, Devan; Kingsbury, Sarah R; Bowes, Mike A; Conaghan, Philip G

2015-08-25

Bone is an integral part of the osteoarthritis (OA) process. We conducted a systematic literature review in order to understand the relationship between non-conventional radiographic imaging of subchondral bone, pain, structural pathology and joint replacement in peripheral joint OA. A search of the Medline, EMBASE and Cochrane library databases was performed for original articles reporting association between non-conventional radiographic imaging-assessed subchondral bone pathologies and joint replacement, pain or structural progression in knee, hip, hand, ankle and foot OA. Each association was qualitatively characterised by a synthesis of the data from each analysis based upon study design, adequacy of covariate adjustment and quality scoring. In total 2456 abstracts were screened and 139 papers were included (70 cross-sectional, 71 longitudinal analyses; 116 knee, 15 hip, six hand, two ankle and involved 113 MRI, eight DXA, four CT, eight scintigraphic and eight 2D shape analyses). BMLs, osteophytes and bone shape were independently associated with structural progression or joint replacement. BMLs and bone shape were independently associated with longitudinal change in pain and incident frequent knee pain respectively. Subchondral bone features have independent associations with structural progression, pain and joint replacement in peripheral OA in the hip and hand but especially in the knee. For peripheral OA sites other than the knee, there are fewer associations and independent associations of bone pathologies with these important OA outcomes which may reflect fewer studies; for example the foot and ankle were poorly studied. Subchondral OA bone appears to be a relevant therapeutic target. PROSPERO registration number: CRD 42013005009.

A general probabilistic model for group independent component analysis and its estimation methods

PubMed Central

Guo, Ying

2012-01-01

SUMMARY Independent component analysis (ICA) has become an important tool for analyzing data from functional magnetic resonance imaging (fMRI) studies. ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix and the uncertainty in between-subjects variability in fMRI data. We present a general probabilistic ICA (PICA) model that can accommodate varying group structures of multi-subject spatio-temporal processes. An advantage of the proposed model is that it can flexibly model various types of group structures in different underlying neural source signals and under different experimental conditions in fMRI studies. A maximum likelihood method is used for estimating this general group ICA model. We propose two EM algorithms to obtain the ML estimates. The first method is an exact EM algorithm which provides an exact E-step and an explicit noniterative M-step. The second method is an variational approximation EM algorithm which is computationally more efficient than the exact EM. In simulation studies, we first compare the performance of the proposed general group PICA model and the existing probabilistic group ICA approach. We then compare the two proposed EM algorithms and show the variational approximation EM achieves comparable accuracy to the exact EM with significantly less computation time. An fMRI data example is used to illustrate application of the proposed methods. PMID:21517789

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Multi-Scale Computational Modeling of Ni-Base Superalloy Brazed Joints for Gas Turbine Applications

NASA Astrophysics Data System (ADS)

Riggs, Bryan

Brazed joints are commonly used in the manufacture and repair of aerospace components including high temperature gas turbine components made of Ni-base superalloys. For such critical applications, it is becoming increasingly important to account for the mechanical strength and reliability of the brazed joint. However, material properties of brazed joints are not readily available and methods for evaluating joint strength such as those listed in AWS C3.2 have inherent challenges compared with testing bulk materials. In addition, joint strength can be strongly influenced by the degree of interaction between the filler metal (FM) and the base metal (BM), the joint design, and presence of flaws or defects. As a result, there is interest in the development of a multi-scale computational model to predict the overall mechanical behavior and fitness-for-service of brazed joints. Therefore, the aim of this investigation was to generate data and methodology to support such a model for Ni-base superalloy brazed joints with conventional Ni-Cr-B based FMs. Based on a review of the technical literature a multi-scale modeling approach was proposed to predict the overall performance of brazed joints by relating mechanical properties to the brazed joint microstructure. This approach incorporates metallurgical characterization, thermodynamic/kinetic simulations, mechanical testing, fracture mechanics and finite element analysis (FEA) modeling to estimate joint properties based on the initial BM/FM composition and brazing process parameters. Experimental work was carried out in each of these areas to validate the multi-scale approach and develop improved techniques for quantifying brazed joint properties. Two Ni-base superalloys often used in gas turbine applications, Inconel 718 and CMSX-4, were selected for study and vacuum furnace brazed using two common FMs, BNi-2 and BNi-9. Metallurgical characterization of these brazed joints showed two primary microstructural regions; a soft

Joint and tendon involvement predict disease progression in systemic sclerosis: a EUSTAR prospective study.

PubMed

Avouac, Jérôme; Walker, Ulrich A; Hachulla, Eric; Riemekasten, Gabriela; Cuomo, Giovanna; Carreira, Patricia E; Caramaschi, Paola; Ananieva, Lidia P; Matucci-Cerinic, Marco; Czirjak, Laszlo; Denton, Christopher; Ladner, Ulf Müller; Allanore, Yannick

2016-01-01

To determine whether joint synovitis and tendon friction rubs (TFRs) can predict the progression of systemic sclerosis (SSc) over time. We performed a prospective cohort study that included 1301 patients with SSc from the EUSTAR database with disease duration ≤3 years at inclusion and with a follow-up of at least 2 years. Presence or absence at clinical examination of synovitis and TFRs was extracted at baseline. Outcomes were skin, cardiovascular, renal and lung progression. Overall disease progression was defined according to the occurrence of at least one organ progression. Joint synovitis (HR: 1.26, 95% CI 1.01 to 1.59) and TFRs (HR: 1.32, 95% CI 1.03 to 1.70) were independently predictive of overall disease progression, as were also the diffuse cutaneous subset (HR: 1.30, 95% CI 1.05 to 1.61) and positive antitopoisomerase-I antibodies (HR: 1.25, 95% CI 1.02 to 1.53). Regarding skin progression, joint synovitis (HR: 1.67, 95% CI 1.06 to 2.64) and TFRs (HR: 1.69, 95% CI 1.02 to 2.77) were also independently predictive of worsening of the modified Rodnan skin score. For cardiovascular progression, joint synovitis was predictive of the occurrence of new digital ulcer(s) (HR: 1.45, 95% CI 1.08 to 1.96) and decreased left ventricular ejection fraction (HR: 2.20, 95% CI 1.06 to 4.57); TFRs were confirmed to be an independent predictor of scleroderma renal crisis (HR: 2.33, 95% CI 1.03 to 6.19). Joint synovitis and TFRs are independent predictive factors for disease progression in patients with early SSc. These easily detected clinical markers may be useful for the risk stratification of patients with SSc. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Ethnicity and patient's perception of risk in joint replacement surgery.

PubMed

Gandhi, Rajiv; Razak, Fahad; Davey, J Roderick; Mahomed, Nizar N

2008-08-01

Despite much evidence showing racial disparities in the use of surgical procedures, it is unknown whether ethnicity affects perception of surgical risk. We surveyed 1609 patients undergoing primary hip or knee replacement surgery. Relevant covariates including demographic data, body mass index (BMI), sex, comorbidities, education, and ethnicity were recorded. Pain and joint functional status were assessed at baseline and at 1-year followup with the Western Ontario McMaster University Osteoarthritis Index (WOMAC) pain and function scores. Risk perception was assessed with 3 survey questions. Non-European patients had greater functional disability and pain prior to surgery and demonstrated significantly greater perception of risk than European patients (p < 0.001). Independent of other covariates, non-European ethnicity was an independent predictor of a greater perception of risk (p < 0.05). Patient ethnicity is an important factor to consider in understanding a patient's perception of risk in joint replacement surgery.

Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro

Do perceived job insecurity and annoyance due to air and noise pollution predict incident self-rated poor health? A prospective analysis of independent and joint associations using a German national representative cohort study.

PubMed

Riedel, Natalie; Loerbroks, Adrian; Bolte, Gabriele; Li, Jian

2017-01-23

Current economic and social change has contributed to increasing job insecurity and traffic-related pollution in residential areas. Both job insecurity and exposure to noise and air pollution are known determinants of population health and can concur in peoples' lives. This may hold true particularly for socially disadvantaged subpopulations. Nevertheless, the potential independent and joint links of those exposures to health have been rarely examined so far. We aimed to contribute to the scarce body of evidence. Information on perceived job insecurity and exposures to noise and air pollution as expressed by annoyance as well as on self-rated health were gathered from 2 waves of the population-based German Socio-Economic Panel (2009 and 2011, N=6544). We performed multivariable Poisson regression to examine the independent and joint risk of poor health in 2011 by perceived job insecurity and annoyance due to noise and air pollution in 2009. After the 2-year follow-up in 2011, 571 (8.7%) participants rated their health as poor. The risk of reporting incident poor health was increased by roughly 40% in employees reporting high versus low perceived job insecurity and annoyance due to noise and air pollution, respectively. This risk increased when both exposures were present at higher levels (risk ratio=1.95 (1.49 to 2.55)). Work-related and environmental exposures may accumulate and have a joint health impact. Elaboration on the link between occupational and residential exposures is warranted in the light of their concurrence and their implications for health inequities. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Detection of independent functional networks during music listening using electroencephalogram and sLORETA-ICA.

PubMed

Jäncke, Lutz; Alahmadi, Nsreen

2016-04-13

The measurement of brain activation during music listening is a topic that is attracting increased attention from many researchers. Because of their high spatial accuracy, functional MRI measurements are often used for measuring brain activation in the context of music listening. However, this technique faces the issues of contaminating scanner noise and an uncomfortable experimental environment. Electroencephalogram (EEG), however, is a neural registration technique that allows the measurement of neurophysiological activation in silent and more comfortable experimental environments. Thus, it is optimal for recording brain activations during pleasant music stimulation. Using a new mathematical approach to calculate intracortical independent components (sLORETA-IC) on the basis of scalp-recorded EEG, we identified specific intracortical independent components during listening of a musical piece and scales, which differ substantially from intracortical independent components calculated from the resting state EEG. Most intracortical independent components are located bilaterally in perisylvian brain areas known to be involved in auditory processing and specifically in music perception. Some intracortical independent components differ between the music and scale listening conditions. The most prominent difference is found in the anterior part of the perisylvian brain region, with stronger activations seen in the left-sided anterior perisylvian regions during music listening, most likely indicating semantic processing during music listening. A further finding is that the intracortical independent components obtained for the music and scale listening are most prominent in higher frequency bands (e.g. beta-2 and beta-3), whereas the resting state intracortical independent components are active in lower frequency bands (alpha-1 and theta). This new technique for calculating intracortical independent components is able to differentiate independent neural networks associated

A patterned microtexture to reduce friction and increase longevity of prosthetic hip joints

PubMed Central

Chyr, Anthony; Qiu, Mingfeng; Speltz, Jared; Jacobsen, Ronald L.; Sanders, Anthony P.; Raeymaekers, Bart

2014-01-01

More than 285,000 total hip replacement surgeries are performed in the US each year. Most prosthetic hip joints consist of a cobalt-chromium (CoCr) femoral head that articulates with a polyethylene acetabular component, lubricated with synovial fluid. The statistical survivorship of these metal-on-polyethylene prosthetic hip joints declines significantly after 10 to 15 years of use, primarily as a result of polyethylene wear and wear debris incited disease. The current engineering paradigm to increase the longevity of prosthetic hip joints is to improve the mechanical properties of the polyethylene component, and to manufacture ultra-smooth articulating surfaces. In contrast, we show that adding a patterned microtexture to the ultra-smooth CoCr femoral head reduces friction when articulating with the polyethylene acetabular liner. The microtexture increases the load-carrying capacity and the thickness of the joint lubricant film, which reduces contact between the articulating surfaces. As a result, friction and wear is reduced. We have used a lubrication model to design the geometry of the patterned microtexture, and experimentally demonstrate reduced friction for the microtextured compared to conventional smooth surrogate prosthetic hip joints. PMID:25013240

Analysis of the Los Angeles Basin ground subsidence with InSAR data by independent component analysis approach

NASA Astrophysics Data System (ADS)

Xu, B.

2017-12-01

Interferometric Synthetic Aperture Radar (InSAR) has the advantages of high spatial resolution which enable measure line of sight (LOS) surface displacements with nearly complete spatial continuity and a satellite's perspective that permits large areas view of Earth's surface quickly and efficiently. However, using InSAR to observe long wavelength and small magnitude deformation signals is still significantly limited by various unmodeled errors sources i.e. atmospheric delays, orbit induced errors, Digital Elevation Model (DEM) errors. Independent component analysis (ICA) is a probabilistic method for separating linear mixed signals generated by different underlying physical processes.The signal sources which form the interferograms are statistically independent both in space and in time, thus, they can be separated by ICA approach.The seismic behavior in the Los Angeles Basin is active and the basin has experienced numerous moderate to large earthquakes since the early Pliocene. Hence, understanding the seismotectonic deformation in the Los Angeles Basin is important for analyzing seismic behavior. Compare with the tectonic deformations, nontectonic deformations due to groundwater and oil extraction may be mainly responsible for the surface deformation in the Los Angeles basin. Using the small baseline subset (SBAS) InSAR method, we extracted the surface deformation time series in the Los Angeles basin with a time span of 7 years (September 27, 2003-September 25,2010). Then, we successfully separate the atmospheric noise from InSAR time series and detect different processes caused by different mechanisms.

Anaerobic prosthetic joint infection.

PubMed

Shah, Neel B; Tande, Aaron J; Patel, Robin; Berbari, Elie F

2015-12-01

In an effort to improve mobility and alleviate pain from degenerative and connective tissue joint disease, an increasing number of individuals are undergoing prosthetic joint replacement in the United States. Joint replacement is a highly effective intervention, resulting in improved quality of life and increased independence [1]. By 2030, it is predicted that approximately 4 million total hip and knee arthroplasties will be performed yearly in the United States [2]. One of the major complications associated with this procedure is prosthetic joint infection (PJI), occurring at a rate of 1-2% [3-7]. In 2011, the Musculoskeletal Infectious Society created a unifying definition for prosthetic joint infection [8]. The following year, the Infectious Disease Society of America published practice guidelines that focused on the diagnosis and management of PJI. These guidelines focused on the management of commonly encountered organisms associated with PJI, including staphylococci, streptococci and select aerobic Gram-negative bacteria. However, with the exception of Propionibacterium acnes, management of other anaerobic organisms was not addressed in these guidelines [1]. Although making up approximately 3-6% of PJI [9,10], anaerobic microorganisms cause devastating complications, and similar to the more common organisms associated with PJI, these bacteria also result in significant morbidity, poor outcomes and increased health-care costs. Data on diagnosis and management of anaerobic PJI is mostly derived from case reports, along with a few cohort studies [3]. There is a paucity of published data outlining factors associated with risks, diagnosis and management of anaerobic PJI. We therefore reviewed available literature on anaerobic PJI by systematically searching the PubMed database, and collected data from secondary searches to determine information on pathogenesis, demographic data, clinical features, diagnosis and management. We focused our search on five commonly

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Calhoun, Vince D.

2013-01-01

Extraction of relevant features from multitask functional MRI (fMRI) data in order to identify potential biomarkers for disease, is an attractive goal. In this paper, we introduce a novel feature-based framework, which is sensitive and accurate in detecting group differences (e.g. controls vs. patients) by proposing three key ideas. First, we integrate two goal-directed techniques: coefficient-constrained independent component analysis (CC-ICA) and principal component analysis with reference (PCA-R), both of which improve sensitivity to group differences. Secondly, an automated artifact-removal method is developed for selecting components of interest derived from CC-ICA, with an average accuracy of 91%. Finally, we propose a strategy for optimal feature/component selection, aiming to identify optimal group-discriminative brain networks as well as the tasks within which these circuits are engaged. The group-discriminating performance is evaluated on 15 fMRI feature combinations (5 single features and 10 joint features) collected from 28 healthy control subjects and 25 schizophrenia patients. Results show that a feature from a sensorimotor task and a joint feature from a Sternberg working memory (probe) task and an auditory oddball (target) task are the top two feature combinations distinguishing groups. We identified three optimal features that best separate patients from controls, including brain networks consisting of temporal lobe, default mode and occipital lobe circuits, which when grouped together provide improved capability in classifying group membership. The proposed framework provides a general approach for selecting optimal brain networks which may serve as potential biomarkers of several brain diseases and thus has wide applicability in the neuroimaging research community. PMID:19457398

The Influence Of Component Alignment On The Life Of Total Knee Prostheses

NASA Astrophysics Data System (ADS)

Bugariu, Delia; Bereteu, Liviu

2012-12-01

An arthritic knee affects the patient's life by causing pain and limiting movement. If the cartilage and the bone surfaces are severely affected, the natural joint is replaced with an artificial joint. The procedure is called total knee arthroplasty (TKA). Lately, the numbers of implanted total knee prostheses grow steadily. An important factor in TKA is the perfect alignment of the total knee prosthesis (TKP) components. Component misalignment can lead to the prosthesis loss by producing wear particles. The paper proposes a study on mechanical behaviors of a TKP based on numerical analysis, using ANSYS software. The numerical analysis is based on both the normal and the changed angle of the components alignment.

Multidisciplinary approach for in-deep assessment of joint prosthesis failure.

PubMed

Tessarolo, F; Caola, I; Piccoli, F; Dorigotti, P; Demattè, E; Molinari, M; Malavolta, M; Barbareschi, M; Caciagli, P; Nollo, G

2009-01-01

In spite of advancement in biomaterials and biomechanics, in development of new osteo-integrative materials and coatings, and in macro- micro- component design, a non negligible fraction of the implanted prosthesis fails before the expected lifetime. A prospective observational clinical study has been conducted to define and apply a set of experimental techniques to in-deep assess the failure of joint prosthesis. Microbiological, histological and micro-structural techniques were implemented to specifically address phenomena occurring at the tissue-implant interface. Results obtained from 27 cases of prosthetic joint failure are discussed in terms of sensitivity and specificity. A procedural flow-chart is finally proposed for the assessment of joint prosthesis failure.

Comparison of Extensive Thermal Cycling Effects on Microstructure Development in Micro-alloyed Sn-Ag-Cu Solder Joints

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

Anderson, Iver E.; Boesenberg, Adam; Harringa, Joel

2011-09-28

Pb-free solder alloys based on the Sn-Ag-Cu (SAC) ternary eutectic have promise for widespread adoption across assembly conditions and operating environments, but enhanced microstructural control is needed. Micro-alloying with elements such as Zn was demonstrated for promoting a preferred solidification path and joint microstructure earlier in simple (Cu/Cu) solder joints studies for different cooling rates. This beneficial behavior now has been verified in reworked ball grid array (BGA) joints, using dissimilar SAC305 (Sn-3.0Ag-0.5Cu, wt.%) solder paste. After industrial assembly, BGA components joined with Sn-3.5Ag-0.74Cu-0.21Zn solder were tested in thermal cycling (-55 C/+125 C) along with baseline SAC305 BGA joints beyondmore » 3000 cycles with continuous failure monitoring. Weibull analysis of the results demonstrated that BGA components joined with SAC + Zn/SAC305 have less joint integrity than SAC305 joints, but their lifetime is sufficient for severe applications in consumer, defense, and avionics electronic product field environments. Failure analysis of the BGA joints revealed that cracking did not deviate from the typical top area (BGA component side) of each joint, in spite of different Ag3Sn blade content. Thus, SAC + Zn solder has not shown any advantage over SAC305 solder in these thermal cycling trials, but other characteristics of SAC + Zn solder may make it more attractive for use across the full range of harsh conditions of avionics or defense applications.« less

The Measurement Of Total Joint Loosening By X-Ray Photogrammetry

NASA Astrophysics Data System (ADS)

Lippert, Frederick G.; Veress, Sandor A.; Tiwari, Rama S.; Harrington, Richard M.

1980-07-01

Failure of total joint replacement due to loosening of the composents either between the implant and cement or between the cement and bone is emerging as a late complication with an incidence as high as 20 percent. Loosening may not only cause pain but progressive loss of support for the prosthesis with eventual structural failure. Early diagnosis is important so that revision may be carried when deterioration or pain occurs. No method is currently available which clearly establishes loosening at an early stage except surgical exploration. We have devised a method based on our in vivo photogrammetry studies of patellar tracking patterns using metallic markers placed in bone near both components of the total joint. Stereo x-rays taken with the joint loaded and unloaded are measured for relative motion between the implant and the metallic markers. Laboratory studies using prosthetic hip components mounted in plastic bone have revealed the ability of this method to detect pistoning movements as small as 80 microns. These findings were confirmed by physical measurements.

Independent Consulting and the American Evaluation Association: Twenty Years Later

ERIC Educational Resources Information Center

Bonnet, Deborah G.

2006-01-01

This article reviews the evolution of American Evaluation Association's (AEA) Independent Consulting Topical Interest Group (IC TIG). The TIG goes back a joint meeting held in San Francisco in 1984 of the Evaluation Network (ENet) and the Evaluation Research Society (ERS), two years before the organizations merged to become the AEA. On the fringes…

Characteristics of solder joints under fatigue loads using piezomechanical actuation

NASA Astrophysics Data System (ADS)

Shim, Dong-Jin; Spearing, S. Mark

2003-07-01

Crack initiation and growth characteristics of solder joints under fatigue loads are investigated using piezomechanical actuation. Cracks in solder joints, which can cause failure in microelectronics components, are induced via piezoelectricity in piezo-ceramic bonded joints. Lead-zirconate-titanate ceramic plates and eutectic Sn-Pb solder bonded in a double-lap shear configuration are used in the investigation. Electric field across each piezo-ceramic plate is applied such that shear stresses/strains are induced in the solder joints. The experiments show that cracks initiate in the solder joints around defects such as voids and grow in length until they coalesce with other cracks from adjacent voids. These observations are compared with the similar thermal cycling tests from the literature to show feasibility and validity of the current method in investigating the fatigue characteristics of solder joints. In some specimens, cracks in the piezo-ceramic plates are observed, and failure in the specimens generally occurred due to piezo-ceramic plate fracture. The issues encountered in implementing this methodology such as low actuation and high processing temperatures are further discussed.

Fatigue properties of dissimilar metal laser welded lap joints

NASA Astrophysics Data System (ADS)

Dinsley, Christopher Paul

This work involves laser welding austenitic and duplex stainless steel to zinc-coated mild steel, more specifically 1.2mm V1437, which is a Volvo Truck Coiporation rephosphorised mild steel. The work investigates both tensile and lap shear properties of similar and dissimilar metal laser welded butt and lap joints, with the majority of the investigation concentrating on the fatigue properties of dissimilar metal laser welded lap joints. The problems encountered when laser welding zinc-coated steel are addressed and overcome with regard to dissimilar metal lap joints with stainless steel. The result being the production of a set of guidelines for laser welding stainless steel to zinc-coated mild steel. The stages of laser welded lap joint fatigue life are defined and the factors affecting dissimilar metal laser welded lap joint fatigue properties are analysed and determined; the findings suggesting that dissimilar metal lap joint fatigue properties are primarily controlled by the local stress at the internal lap face and the early crack growth rate of the material at the internal lap face. The lap joint rotation, in turn, is controlled by sheet thickness, weld width and interfacial gap. Laser welded lap joint fatigue properties are found to be independent of base material properties, allowing dissimilar metal lap joints to be produced without fatigue failure occurring preferentially in the weaker parent material, irrespective of large base material property differences. The effects of Marangoni flow on the compositions of the laser weld beads are experimentally characterised. The results providing definite proof of the stirring mechanism within the weld pool through the use of speeds maps for chromium and nickel. Keywords: Laser welding, dissimilar metal, Zinc-coated mild steel, Austenitic stainless steel, Duplex stainless steel, Fatigue, Lap joint rotation, Automotive.

Posterior Predictive Checks for Conditional Independence between Response Time and Accuracy