Xie, Y; Zhang, Y; Qin, W; Lu, S; Ni, C; Zhang, Q
2017-03-01
Increasing DTI studies have demonstrated that white matter microstructural abnormalities play an important role in type 2 diabetes mellitus-related cognitive impairment. In this study, the diffusional kurtosis imaging method was used to investigate WM microstructural alterations in patients with type 2 diabetes mellitus and to detect associations between diffusional kurtosis imaging metrics and clinical/cognitive measurements. Diffusional kurtosis imaging and cognitive assessments were performed on 58 patients with type 2 diabetes mellitus and 58 controls. Voxel-based intergroup comparisons of diffusional kurtosis imaging metrics were conducted, and ROI-based intergroup comparisons were further performed. Correlations between the diffusional kurtosis imaging metrics and cognitive/clinical measurements were assessed after controlling for age, sex, and education in both patients and controls. Altered diffusion metrics were observed in the corpus callosum, the bilateral frontal WM, the right superior temporal WM, the left external capsule, and the pons in patients with type 2 diabetes mellitus compared with controls. The splenium of the corpus callosum and the pons had abnormal kurtosis metrics in patients with type 2 diabetes mellitus. Additionally, altered diffusion metrics in the right prefrontal WM were significantly correlated with disease duration and attention task performance in patients with type 2 diabetes mellitus. With both conventional diffusion and additional kurtosis metrics, diffusional kurtosis imaging can provide additional information on WM microstructural abnormalities in patients with type 2 diabetes mellitus. Our results indicate that WM microstructural abnormalities occur before cognitive decline and may be used as neuroimaging markers for predicting the early cognitive impairment in patients with type 2 diabetes mellitus. © 2017 by American Journal of Neuroradiology.
A Simple Noise Correction Scheme for Diffusional Kurtosis Imaging
Glenn, G. Russell; Tabesh, Ali; Jensen, Jens H.
2014-01-01
Purpose Diffusional kurtosis imaging (DKI) is sensitive to the effects of signal noise due to strong diffusion weightings and higher order modeling of the diffusion weighted signal. A simple noise correction scheme is proposed to remove the majority of the noise bias in the estimated diffusional kurtosis. Methods Weighted linear least squares (WLLS) fitting together with a voxel-wise, subtraction-based noise correction from multiple, independent acquisitions are employed to reduce noise bias in DKI data. The method is validated in phantom experiments and demonstrated for in vivo human brain for DKI-derived parameter estimates. Results As long as the signal-to-noise ratio (SNR) for the most heavily diffusion weighted images is greater than 2.1, errors in phantom diffusional kurtosis estimates are found to be less than 5 percent with noise correction, but as high as 44 percent for uncorrected estimates. In human brain, noise correction is also shown to improve diffusional kurtosis estimates derived from measurements made with low SNR. Conclusion The proposed correction technique removes the majority of noise bias from diffusional kurtosis estimates in noisy phantom data and is applicable to DKI of human brain. Features of the method include computational simplicity and ease of integration into standard WLLS DKI post-processing algorithms. PMID:25172990
Aging in deep gray matter and white matter revealed by diffusional kurtosis imaging.
Gong, Nan-Jie; Wong, Chun-Sing; Chan, Chun-Chung; Leung, Lam-Ming; Chu, Yiu-Ching
2014-10-01
Diffusion tensor imaging has already been extensively used to probe microstructural alterations in white matter tracts, and scarcely, in deep gray matter. However, results in literature regarding age-related degenerative mechanisms in white matter tracts and parametric changes in the putamen are inconsistent. Diffusional kurtosis imaging is a mathematical extension of diffusion tensor imaging, which could more comprehensively mirror microstructure, particularly in isotropic tissues such as gray matter. In this study, we used the diffusional kurtosis imaging method and a white-matter model that provided metrics of explicit neurobiological interpretations in healthy participants (58 in total, aged from 25 to 84 years). Tract-based whole-brain analyses and regions-of-interest (anterior and posterior limbs of the internal capsule, cerebral peduncle, fornix, genu and splenium of corpus callosum, globus pallidus, substantia nigra, red nucleus, putamen, caudate nucleus, and thalamus) analyses were performed to examine parametric differences across regions and correlations with age. In white matter tracts, evidence was found supportive for anterior-posterior gradient and not completely supportive for retrogenesis theory. Age-related degenerations appeared to be broadly driven by axonal loss. Demyelination may also be a major driving mechanism, although confined to the anterior brain. In terms of deep gray matter, higher mean kurtosis and fractional anisotropy in the globus pallidus, substantia nigra, and red nucleus reflected higher microstructural complexity and directionality compared with the putamen, caudate nucleus, and thalamus. In particular, the unique age-related positive correlations for fractional anisotropy, mean kurtosis, and radial kurtosis in the putamen opposite to those in other regions call for further investigation of exact underlying mechanisms. In summary, the results suggested that diffusional kurtosis can provide measurements in a new dimension that were complementary to diffusivity metrics. Kurtosis together with diffusivity can more comprehensively characterize microstructural compositions and age-related changes than diffusivity alone. Combined with proper model, it may also assist in providing neurobiological interpretations of the identified alterations. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Jensen, Jens H.; Helpern, Joseph A.
2011-06-01
Hardware constraints typically require the use of extended gradient pulse durations for clinical applications of diffusion-weighted magnetic resonance imaging (DW-MRI), which can potentially influence the estimation of diffusion metrics. Prior studies have examined this effect for the apparent diffusion coefficient. This study employs a two-compartment exchange model in order to assess the gradient pulse duration sensitivity of the apparent diffusional kurtosis (ADK), a quantitative index of diffusional non-Gaussianity. An analytic expression is derived and numerically evaluated for parameter ranges relevant to DW-MRI of brain. It is found that the ADK differs from the true diffusional kurtosis by at most a few percent. This suggests that ADK estimates for brain may be robust with respect to changes in pulse gradient duration.
Sun, Yawen; Sun, Jinhua; Zhou, Yan; Ding, Weina; Chen, Xue; Zhuang, Zhiguo; Xu, Jianrong; Du, Yasong
2014-10-24
The aim of the current study was to investigate the utility of diffusional kurtosis imaging (DKI) in the detection of gray matter (GM) alterations in people suffering from Internet Gaming Addiction (IGA). DKI was applied to 18 subjects with IGA and to 21 healthy controls (HC). Whole-brain voxel-based analyses were performed with the following derived parameters: mean kurtosis metrics (MK), radial kurtosis (K⊥), and axial kurtosis (K//). A significance threshold was set at P <0.05, AlphaSim corrected. Pearson's correlation was performed to investigate the correlations between the Chen Internet Addiction Scale (CIAS) and the DKI-derived metrics of regions that differed between groups. Additionally, we used voxel-based morphometry (VBM) to detect GM-volume differences between the two groups. Compared with the HC group, the IGA group demonstrated diffusional kurtosis parameters that were significantly less in GM of the right anterolateral cerebellum, right inferior and superior temporal gyri, right supplementary motor area, middle occipital gyrus, right precuneus, postcentral gyrus, right inferior frontal gyrus, left lateral lingual gyrus, left paracentral lobule, left anterior cingulate cortex, and median cingulate cortex. The bilateral fusiform gyrus, insula, posterior cingulate cortex (PCC), and thalamus also exhibited less diffusional kurtosis in the IGA group. MK in the left PCC and K⊥ in the right PCC were positively correlated with CIAS scores. VBM showed that IGA subjects had higher GM volume in the right inferior and middle temporal gyri, and right parahippocampal gyrus, and lower GM volume in the left precentral gyrus. The lower diffusional kurtosis parameters in IGA suggest multiple differences in brain microstructure, which may contribute to the underlying pathophysiology of IGA. DKI may provide sensitive imaging biomarkers for assessing IGA severity.
Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain.
Mohanty, Vaibhav; McKinnon, Emilie T; Helpern, Joseph A; Jensen, Jens H
2018-05-01
To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging. For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm 2 . For the QS estimates, b-values ranging from 0 up to 10,000s/mm 2 were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions. The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values. Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel. Copyright © 2018 Elsevier Inc. All rights reserved.
Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging.
Yang, Alicia W; Jensen, Jens H; Hu, Caixia C; Tabesh, Ali; Falangola, Maria F; Helpern, Joseph A
2013-02-01
To evaluate the cerebral spinal fluid (CSF) partial volume effect on diffusional kurtosis imaging (DKI) metrics in white matter and cortical gray matter. Four healthy volunteers participated in this study. Standard DKI and fluid-attenuated inversion recovery (FLAIR) DKI experiments were performed using a twice-refocused-spin-echo diffusion sequence. The conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, D[symbol in text], D[symbol in text] together with DKI metrics of mean, axial, and radial kurtosis (MK, K[symbol in text], K[symbol in text], were measured and compared. Single image slices located above the lateral ventricles, with similar anatomical features for each subject, were selected to minimize the effect of CSF from the ventricles. In white matter, differences of less than 10% were observed between diffusion metrics measured with standard DKI and FLAIR-DKI sequences, suggesting minimal CSF contamination. For gray matter, conventional DTI metrics differed by 19% to 52%, reflecting significant CSF partial volume effects. Kurtosis metrics, however, changed by 11% or less, indicating greater robustness with respect to CSF contamination. Kurtosis metrics are less sensitive to CSF partial voluming in cortical gray matter than conventional diffusion metrics. The kurtosis metrics may then be more specific indicators of changes in tissue microstructure, provided the effect sizes for the changes are comparable. Copyright © 2012 Wiley Periodicals, Inc.
Duchêne, Gaëtan; Peeters, Frank; Peeters, André; Duprez, Thierry
2017-08-01
To compare the sensitivity and early temporal changes of diffusion parameters obtained from diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), q-space analysis (QSA) and bi-exponential modelling in hyperacute stroke patients. A single investigational acquisition allowing the four diffusion analyses was performed on seven hyperacute stroke patients with a 3T system. The percentage change between ipsi- and contralateral regions were compared at admission and 24 h later. Two out of the seven patients were imaged every 6 h during this period. Kurtoses from both DKI and QSA were the most sensitive of the tested diffusion parameters in the few hours following ischemia. An early increase-maximum-decrease pattern of evolution was highlighted during the 24-h period for all parameters proportional to diffusion coefficients. A similar pattern was observed for both kurtoses in only one of two patients. Our comparison was performed using identical diffusion encoding timings and on patients in the same stage of their condition. Although preliminary, our findings confirm those of previous studies that showed enhanced sensitivity of kurtosis. A fine time mapping of diffusion metrics in hyperacute stroke patients was presented which advocates for further investigations on larger animal or human cohorts.
Leading non-Gaussian corrections for diffusion orientation distribution function.
Jensen, Jens H; Helpern, Joseph A; Tabesh, Ali
2014-02-01
An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed from the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves on the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. 2013 John Wiley & Sons, Ltd.
Leading Non-Gaussian Corrections for Diffusion Orientation Distribution Function
Jensen, Jens H.; Helpern, Joseph A.; Tabesh, Ali
2014-01-01
An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed out of the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves upon the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. PMID:24738143
Palombo, Marco; Gentili, Silvia; Bozzali, Marco; Macaluso, Emiliano; Capuani, Silvia
2015-05-01
In this MRI study, diffusional kurtosis imaging (DKI) and T2 * multiecho relaxometry were measured from the white matter (WM) of human brains and correlated with each other, with the aim of investigating the influence of magnetic-susceptibility (Δχ (H2O-TISSUE) ) on the contrast. We focused our in vivo analysis on assessing the dependence of mean, axial, and radial kurtosis (MK, K‖ , K⊥ ), as well as DTI indices on Δχ (H2O-TISSUE) (quantified by T2 *) between extracellular water and WM tissue molecules. Moreover, Monte Carlo (MC) simulations were used to elucidate experimental data. A significant positive correlation was observed between K⊥ , MK and R2 * = 1/T2 *, suggesting that Δχ (H2O-TISSUE) could be a source of DKI contrast. In this view, K⊥ and MK-map contrasts in human WM would not just be due to different restricted diffusion processes of compartmentalized water but also to local Δχ (H2O-TISSUE) . However, MC simulations show a strong dependence on microstructure rearrangement and a feeble dependence on Δχ (H2O-TISSUE) of DKI signal. Our results suggests a concomitant and complementary existence of multi-compartmentalized diffusion process and Δχ (H2O-TISSUE) in DKI contrast that might explain why kurtosis contrast is more sensitive than DTI in discriminating between different tissues. However, more realistic numerical simulations are needed to confirm this statement. © 2014 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Ingo, Carson; Sui, Yi; Chen, Yufen; Parrish, Todd; Webb, Andrew; Ronen, Itamar
2015-03-01
In this paper, we provide a context for the modeling approaches that have been developed to describe non-Gaussian diffusion behavior, which is ubiquitous in diffusion weighted magnetic resonance imaging of water in biological tissue. Subsequently, we focus on the formalism of the continuous time random walk theory to extract properties of subdiffusion and superdiffusion through novel simplifications of the Mittag-Leffler function. For the case of time-fractional subdiffusion, we compute the kurtosis for the Mittag-Leffler function, which provides both a connection and physical context to the much-used approach of diffusional kurtosis imaging. We provide Monte Carlo simulations to illustrate the concepts of anomalous diffusion as stochastic processes of the random walk. Finally, we demonstrate the clinical utility of the Mittag-Leffler function as a model to describe tissue microstructure through estimations of subdiffusion and kurtosis with diffusion MRI measurements in the brain of a chronic ischemic stroke patient.
Zhang, Zhiyan; Wang, Yukai; Shen, Zhiwei; Yang, Zhongxian; Li, Li; Chen, Dongxiao; Yan, Gen; Cheng, Xiaofang; Shen, Yuanyu; Tang, Xiangyong; Hu, Wei; Wu, Renhua
2016-01-01
The diagnosis and pathology of neuropsychiatric systemic lupus erythematosus (NPSLE) remains challenging. Herein, we used multimodal imaging to assess anatomical and functional changes in brains of SLE patients instead of a single MRI approach generally used in previous studies. Twenty-two NPSLE patients, 21 non-NPSLE patients and 20 healthy controls (HCs) underwent 3.0 T MRI with multivoxel magnetic resonance spectroscopy, T1-weighted volumetric images for voxel based morphometry (VBM) and diffusional kurtosis imaging (DKI) scans. While there were findings in other basal ganglia regions, the most consistent findings were observed in the posterior cingulate gyrus (PCG). The reduction of multiple metabolite concentration was observed in the PCG in the two patient groups, and the NPSLE patients were more prominent. The two patient groups displayed lower diffusional kurtosis (MK) values in the bilateral PCG compared with HCs (p < 0.01) as assessed by DKI. Grey matter reduction in the PCG was observed in the NPSLE group using VBM. Positive correlations among cognitive function scores and imaging metrics in bilateral PCG were detected. Multimodal imaging is useful for evaluating SLE subjects and potentially determining disease pathology. Impairments of cognitive function in SLE patients may be interpreted by metabolic and microstructural changes in the PCG. PMID:26758023
Zhang, Yuzhen; Gao, Yu; Zhou, Minxiong; Wu, Jie; Zee, Chishing; Wang, Dengbin
2016-10-01
To investigate brain abnormalities in children with a clinical diagnosis of idiopathic generalized epilepsy (IGE) and unilateral interictal epileptiform discharges (IED) demonstrated on electroencephalography (EEG) by diffusional kurtosis imaging (DKI). DKI images were obtained from 18 patients (n=9 each in the left and right hemispheres). Fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) maps were estimated through voxel-based analyses, and compared with 18 normal controls matched for age and sex. In the left side group, the significant differences of FA were in the left fusiform gyrus and occipital lobe of the white matter (WM). The significant differences of MD were in the left pons. The significant differences of MK were in the anterior cingulate gyrus, limbic lobe, gray matter (GM) and WM of the right cerebrum. In the right side group, the significant differences of FA were in the WM of the left cerebrum. MD identified differences in the frontal, temporal, occipital, and parietal lobes of both hemispheres, especially in the limbic system, fusiform gyrus, uncus, and parahippocampal gyrus. The significant differences of MK were in the GM of the right cerebrum, particularly in the rolandic operculum and frontal lobe. DKI is sensitive for the detection of diffusion abnormalities in both WM and GM of IGE in children. Secondary brain abnormalities may exist in regions outside the unilateral epileptogenic zone through the limbic epileptic network, and can be detected by DKI indices FA, MD and MK. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Evaluating Kurtosis-based Diffusion MRI Tissue Models for White Matter with Fiber Ball Imaging
Jensen, Jens H.; McKinnon, Emilie T.; Glenn, G. Russell; Helpern, Joseph A.
2018-01-01
In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to the value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging (DKI). Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FA) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability. PMID:28085211
Huang, Yanqi; Chen, Xin; Zhang, Zhongping; Yan, Lifen; Pan, Dan; Liang, Changhong; Liu, Zaiyi
2015-02-01
Our aim was to prospectively evaluate the feasibility of diffusional kurtosis imaging (DKI) in normal human kidney and to report preliminary DKI measurements. Institutional review board approval and informed consent were obtained. Forty-two healthy volunteers underwent diffusion-weighted imaging (DWI) scans with a 3-T MR scanner. b values of 0, 500 and 1000 s/mm(2) were adopted. Maps of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (D⊥), axial diffusivity (D||), mean kurtosis (MK), radial kurtosis (K⊥) and axial kurtosis (K||) were produced. Three representative axial slices in the upper pole, mid-zone and lower pole were selected in the left and right kidney. On each selected slice, three regions of interest were drawn on the renal cortex and another three on the medulla. Statistical comparison was performed with t-test and analysis of variance. Thirty-seven volunteers successfully completed the scans. No statistically significant differences were observed between the left and right kidney for all metrics (p values in the cortex: FA, 0.114; MD, 0.531; D⊥, 0.576; D||, 0.691; MK, 0.934; K⊥, 0.722; K||, 0.891; p values in the medulla: FA, 0.348; MD, 0.732; D⊥, 0.470; D||, 0.289; MK, 0.959; K⊥, 0.780; K||, 0.287). Kurtosis metrics (MK, K||, K⊥) obtained in the renal medulla were significantly (p <0.001) higher than those in the cortex (0.552 ± 0.04, 0.637 ± 0.07 and 0.530 ± 0.08 in the medulla and 0.373 ± 0.04, 0.492 ± 0.06 and 0.295 ± 0.06 in the cortex, respectively). For the diffusivity measures, FA of the medulla (0.356 ± 0.03) was higher than that of the cortex (0.179 ± 0.03), whereas MD, D⊥ and D|| (mm(2) /ms) were lower in the medulla than in the cortex (3.88 ± 0.09, 3.50 ± 0.23 and 4.65 ± 0.29 in the cortex and 2.88 ± 0.11, 2.32 ± 0.20 and 3.47 ± 0.31 in the medulla, respectively). Our results indicate that DKI is feasible in the human kidney. We have reported the preliminary DKI measurements of normal human kidney that demonstrate well the non-Gaussian behavior of water diffusion, especially in the renal medulla. Copyright © 2014 John Wiley & Sons, Ltd.
Irie, Ryusuke; Kamagata, Koji; Kerever, Aurelien; Ueda, Ryo; Yokosawa, Suguru; Otake, Yosuke; Ochi, Hisaaki; Yoshizawa, Hidekazu; Hayashi, Ayato; Tagawa, Kazuhiko; Okazawa, Hitoshi; Takahashi, Kohske; Sato, Kanako; Hori, Masaaki; Arikawa-Hirasawa, Eri; Aoki, Shigeki
2018-01-01
Purpose: Diffusional kurtosis imaging (DKI) enables sensitive measurement of tissue microstructure by quantifying the non-Gaussian diffusion of water. Although DKI is widely applied in many situations, histological correlation with DKI analysis is lacking. The purpose of this study was to determine the relationship between DKI metrics and neurite density measured using confocal microscopy of a cleared mouse brain. Methods: One thy-1 yellow fluorescent protein 16 mouse was deeply anesthetized and perfusion fixation was performed. The brain was carefully dissected out and whole-brain MRI was performed using a 7T animal MRI system. DKI and diffusion tensor imaging (DTI) data were obtained. After the MRI scan, brain sections were prepared and then cleared using aminoalcohols (CUBIC). Confocal microscopy was performed using a two-photon confocal microscope with a laser. Forty-eight ROIs were set on the caudate putamen, seven ROIs on the anterior commissure, and seven ROIs on the ventral hippocampal commissure on the confocal microscopic image and a corresponding MR image. In each ROI, histological neurite density and the metrics of DKI and DTI were calculated. The correlations between diffusion metrics and neurite density were analyzed using Pearson correlation coefficient analysis. Results: Mean kurtosis (MK) (P = 5.2 × 10−9, r = 0.73) and radial kurtosis (P = 2.3 × 10−9, r = 0.74) strongly correlated with neurite density in the caudate putamen. The correlation between fractional anisotropy (FA) and neurite density was moderate (P = 0.0030, r = 0.42). In the anterior commissure and the ventral hippocampal commissure, neurite density and FA are very strongly correlated (P = 1.3 × 10−5, r = 0.90). MK in these areas were very high value and showed no significant correlation (P = 0.48). Conclusion: DKI accurately reflected neurite density in the area with crossing fibers, potentially allowing evaluation of complex microstructures. PMID:29213008
Irie, Ryusuke; Kamagata, Koji; Kerever, Aurelien; Ueda, Ryo; Yokosawa, Suguru; Otake, Yosuke; Ochi, Hisaaki; Yoshizawa, Hidekazu; Hayashi, Ayato; Tagawa, Kazuhiko; Okazawa, Hitoshi; Takahashi, Kohske; Sato, Kanako; Hori, Masaaki; Arikawa-Hirasawa, Eri; Aoki, Shigeki
2018-04-10
Diffusional kurtosis imaging (DKI) enables sensitive measurement of tissue microstructure by quantifying the non-Gaussian diffusion of water. Although DKI is widely applied in many situations, histological correlation with DKI analysis is lacking. The purpose of this study was to determine the relationship between DKI metrics and neurite density measured using confocal microscopy of a cleared mouse brain. One thy-1 yellow fluorescent protein 16 mouse was deeply anesthetized and perfusion fixation was performed. The brain was carefully dissected out and whole-brain MRI was performed using a 7T animal MRI system. DKI and diffusion tensor imaging (DTI) data were obtained. After the MRI scan, brain sections were prepared and then cleared using aminoalcohols (CUBIC). Confocal microscopy was performed using a two-photon confocal microscope with a laser. Forty-eight ROIs were set on the caudate putamen, seven ROIs on the anterior commissure, and seven ROIs on the ventral hippocampal commissure on the confocal microscopic image and a corresponding MR image. In each ROI, histological neurite density and the metrics of DKI and DTI were calculated. The correlations between diffusion metrics and neurite density were analyzed using Pearson correlation coefficient analysis. Mean kurtosis (MK) (P = 5.2 × 10 -9 , r = 0.73) and radial kurtosis (P = 2.3 × 10 -9 , r = 0.74) strongly correlated with neurite density in the caudate putamen. The correlation between fractional anisotropy (FA) and neurite density was moderate (P = 0.0030, r = 0.42). In the anterior commissure and the ventral hippocampal commissure, neurite density and FA are very strongly correlated (P = 1.3 × 10 -5 , r = 0.90). MK in these areas were very high value and showed no significant correlation (P = 0.48). DKI accurately reflected neurite density in the area with crossing fibers, potentially allowing evaluation of complex microstructures.
Gong, Nan-Jie; Wong, Chun-Sing; Hui, Edward S; Chan, Chun-Chung; Leung, Lam-Ming
2015-10-01
The purpose of this work was to investigate the effects of hemispheric location, gender and age on susceptibility value, as well as the association between susceptibility value and diffusional metrics, in deep gray matter. Iron content was estimated in vivo using quantitative susceptibility mapping. Microstructure was probed using diffusional kurtosis imaging. Regional susceptibility and diffusional metrics were measured for the putamen, caudate nucleus, globus pallidus, thalamus, substantia nigra and red nucleus in 42 healthy adults (age range 25-78 years). Susceptibility value was significantly higher in the left than the right side of the caudate nucleus (P = 0.043) and substantia nigra (P < 0.001). Women exhibited lower susceptibility values than men in the thalamus (P < 0.001) and red nucleus (P = 0.032). Significant age-related increases of susceptibility were observed in the putamen (P < 0.001), red nucleus (P < 0.001), substantia nigra (P = 0.004), caudate nucleus (P < 0.001) and globus pallidus (P = 0.017). The putamen exhibited the highest rate of iron accumulation with aging (slope of linear regression = 0.73 × 10(-3) ppm/year), which was nearly twice those in substantia nigra (slope = 0.40 × 10(-3) ppm/year) and caudate nucleus (slope = 0.39 × 10(-3) ppm/year). Significant positive correlations between the susceptibility value and diffusion measurements were observed for fractional anisotropy (P = 0.045) and mean kurtosis (P = 0.048) in the putamen without controlling for age. Neither correlation was significant after controlling for age. Hemisphere, gender and age-related differences in iron measurements were observed in deep gray matter. Notably, the putamen exhibited the highest rate of increase in susceptibility with aging. Correlations between susceptibility value and microstructural measurements were inconclusive. These findings could provide new clues for unveiling mechanisms underlying iron-related neurodegenerative diseases. Copyright © 2015 John Wiley & Sons, Ltd.
Can we develop pathology-specific MRI contrast for "MR-negative" epilepsy?
Feindel, Kirk W
2013-05-01
Recent improvements in magnetic resonance imaging (MRI) hardware, software, and analysis routines are helping to put cases of "MR-negative" epilepsy on the decline. However, most standard-of-care MRI relies on careful manipulation and presentation of T1, T2, and diffusion-weighted contrast, which characterize the behavior of water in "bulk" tissue rather than providing pathology-specific contrast. Research efforts in MR physics continue to identify and develop novel theory, and methods such as diffusional kurtosis imaging (DKI) and temporal diffusion spectroscopy that can better characterize tissue substructure, and chemical exchange saturation transfer (CEST) that can target underlying biochemical processes. The potential role of each technique in targeting pathologies implicated in "MR-negative" epilepsy is outlined herein. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.
Gong, Nan-Jie; Chan, Chun-Chung; Leung, Lam-Ming; Wong, Chun-Sing; Dibb, Russell; Liu, Chunlei
2017-05-01
One aim of this study is to use non-Gaussian diffusion kurtosis imaging (DKI) for capturing microstructural abnormalities in gray matter of Alzheimer's disease (AD). The other aim is to compare DKI metrics against thickness of cortical gray matter and volume of deep gray matter, respectively. A cohort of 18 patients with AD, 18 patients with amnestic mild cognitive impairment (MCI), and 18 normal controls underwent morphological and DKI MR imaging. Images were investigated using regions-of-interest-based analyses for deep gray matter and vertex-wise analyses for cortical gray matter. In deep gray matter, more regions showed DKI parametric abnormalities than atrophies at the early MCI stage. Mean kurtosis (MK) exhibited the largest number of significant abnormalities among all DKI metrics. At the later AD stage, diffusional abnormalities were observed in fewer regions than atrophies. In cortical gray matter, abnormalities in thickness were mainly in the medial and lateral temporal lobes, which fit the locations of known early pathological changes. Microstructural abnormalities were predominantly in the parietal and even frontal lobes, which fit the locations of known late pathological changes. In conclusion, MK can complement conventional diffusion metrics for detecting microstructural changes, especially in deep gray matter. This study also provides evidence supporting the notion that microstructural changes predate morphological changes. Hum Brain Mapp 38:2495-2508, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Wang, Enfeng; Wu, Yin; Cheung, Jerry S; Zhou, Iris Yuwen; Igarashi, Takahiro; Zhang, XiaoAn; Sun, Phillip Zhe
2017-10-01
Diffusion weighted imaging (DWI) has been commonly used in acute stroke examination, yet a portion of DWI lesion may be salvageable. Recently, it has been shown that diffusion kurtosis imaging (DKI) defines the most severely damaged DWI lesion that does not renormalize following early reperfusion. We postulated that the diffusion and kurtosis lesion mismatch experience heterogeneous hemodynamic and/or metabolic injury. We investigated tissue perfusion, pH, diffusion, kurtosis and relaxation from regions of the contralateral normal area, diffusion lesion, kurtosis lesion and their mismatch in an animal model of acute stroke. Our study revealed significant kurtosis and diffusion lesion volume mismatch (19.7 ± 10.7%, P < 0.01). Although there was no significant difference in perfusion and diffusion between the kurtosis lesion and kurtosis/diffusion lesion mismatch, we showed lower pH in the kurtosis lesion (pH = 6.64 ± 0.12) from that of the kurtosis/diffusion lesion mismatch (6.84 ± 0.11, P < 0.05). Moreover, pH in the kurtosis lesion and kurtosis/diffusion mismatch agreed well with literature values for regions of ischemic core and penumbra, respectively. Our work documented initial evidence that DKI may reveal the heterogeneous metabolic derangement within the commonly used DWI lesion.
Correlation between diffusion kurtosis and NODDI metrics in neonates and young children
NASA Astrophysics Data System (ADS)
Ahmed, Shaheen; Wang, Zhiyue J.; Chia, Jonathan M.; Rollins, Nancy K.
2016-03-01
Diffusion Tensor Imaging (DTI) uses single shell gradient encoding scheme for studying brain tissue diffusion. NODDI (Neurite Orientation Dispersion and Density Imaging) incorporates a gradient scheme with multiple b-values which is used to characterize neurite density and coherence of neuron fiber orientations. Similarly, the diffusion kurtosis imaging also uses a multiple shell scheme to quantify non-Gaussian diffusion but does not assume a tissue model like NODDI. In this study we investigate the connection between metrics derived by NODDI and DKI in children with ages from 46 weeks to 6 years. We correlate the NODDI metrics and Kurtosis measures from the same ROIs in multiple brain regions. We compare the range of these metrics between neonates (46 - 47 weeks), infants (2 -10 months) and young children (2 - 6 years). We find that there exists strong correlation between neurite density vs. mean kurtosis, orientation dispersion vs. kurtosis fractional anisotropy (FA) in pediatric brain imaging.
Bai, Yan; Lin, Yusong; Tian, Jie; Shi, Dapeng; Cheng, Jingliang; Haacke, E. Mark; Hong, Xiaohua; Ma, Bo; Zhou, Jinyuan
2016-01-01
Purpose To quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas. Materials and Methods This study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations. Results ADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05). Conclusion Water molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters. © RSNA, 2015 Online supplemental material is available for this article. PMID:26230975
Zhou, Iris Yuwen; Guo, Yingkun; Igarashi, Takahiro; Wang, Yu; Mandeville, Emiri; Chan, Suk-Tak; Wen, Lingyi; Vangel, Mark; Lo, Eng H; Ji, Xunming; Sun, Phillip Zhe
2016-12-01
Diffusion kurtosis imaging (DKI) has been shown to augment diffusion-weighted imaging (DWI) for the definition of irreversible ischemic injury. However, the complexity of cerebral structure/composition makes the kurtosis map heterogeneous, limiting the specificity of kurtosis hyperintensity to acute ischemia. We propose an Inherent COrrelation-based Normalization (ICON) analysis to suppress the intrinsic kurtosis heterogeneity for improved characterization of heterogeneous ischemic tissue injury. Fast DKI and relaxation measurements were performed on normal (n = 10) and stroke rats following middle cerebral artery occlusion (MCAO) (n = 20). We evaluated the correlations between mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) derived from the fast DKI sequence and relaxation rates R 1 and R 2 , and found a highly significant correlation between MK and R 1 (p < 0.001). We showed that ICON analysis suppressed the intrinsic kurtosis heterogeneity in normal cerebral tissue, enabling automated tissue segmentation in an animal stroke model. We found significantly different kurtosis and diffusivity lesion volumes: 147 ± 59 and 180 ± 66 mm 3 , respectively (p = 0.003, paired t-test). The ratio of kurtosis to diffusivity lesion volume was 84% ± 19% (p < 0.001, one-sample t-test). We found that relaxation-normalized MK (RNMK), but not MD, values were significantly different between kurtosis and diffusivity lesions (p < 0.001, analysis of variance). Our study showed that fast DKI with ICON analysis provides a promising means of demarcation of heterogeneous DWI stroke lesions. Copyright © 2016 John Wiley & Sons, Ltd.
Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation.
Jiang, Rifeng; Jiang, Jingjing; Zhao, Lingyun; Zhang, Jiaxuan; Zhang, Shun; Yao, Yihao; Yang, Shiqi; Shi, Jingjing; Shen, Nanxi; Su, Changliang; Zhang, Ju; Zhu, Wenzhen
2015-12-08
Conventional diffusion imaging techniques are not sufficiently accurate for evaluating glioma grade and cellular proliferation, which are critical for guiding glioma treatment. Diffusion kurtosis imaging (DKI), an advanced non-Gaussian diffusion imaging technique, has shown potential in grading glioma; however, its applications in this tumor have not been fully elucidated. In this study, DKI and diffusion weighted imaging (DWI) were performed on 74 consecutive patients with histopathologically confirmed glioma. The kurtosis and conventional diffusion metric values of the tumor were semi-automatically obtained. The relationships of these metrics with the glioma grade and Ki-67 expression were evaluated. The diagnostic efficiency of these metrics in grading was further compared. It was demonstrated that compared with the conventional diffusion metrics, the kurtosis metrics were more promising imaging markers in distinguishing high-grade from low-grade gliomas and distinguishing among grade II, III and IV gliomas; the kurtosis metrics also showed great potential in the prediction of Ki-67 expression. To our best knowledge, we are the first to reveal the ability of DKI to assess the cellular proliferation of gliomas, and to employ the semi-automatic method for the accurate measurement of gliomas. These results could have a significant impact on the diagnosis and subsequent therapy of glioma.
De Santis, Silvia; Bastiani, Matteo; Droby, Amgad; Kolber, Pierre; Zipp, Frauke; Pracht, Eberhard; Stoecker, Tony; Groppa, Sergiu; Roebroeck, Alard
2018-04-07
The recent introduction of advanced magnetic resonance (MR) imaging techniques to characterize focal and global degeneration in multiple sclerosis (MS), like the Composite Hindered and Restricted Model of Diffusion, or CHARMED, diffusional kurtosis imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI) made available new tools to image axonal pathology non-invasively in vivo. These methods already showed greater sensitivity and specificity compared to conventional diffusion tensor-based metrics (e.g., fractional anisotropy), overcoming some of its limitations. While previous studies uncovered global and focal axonal degeneration in MS patients compared to healthy controls, here our aim is to investigate and compare different diffusion MRI acquisition protocols in their ability to highlight microstructural differences between MS and control tissue over several much used models. For comparison, we contrasted the ability of fractional anisotropy measurements to uncover differences between lesion, normal-appearing white matter (WM), gray matter and healthy tissue under the same imaging protocols. We show that: (1) focal and diffuse differences in several microstructural parameters are observed under clinical settings; (2) advanced models (CHARMED, DKI and NODDI) have increased specificity and sensitivity to neurodegeneration when compared to fractional anisotropy measurements; and (3) both high (3 T) and ultra-high fields (7 T) are viable options for imaging tissue change in MS lesions and normal appearing WM, while higher b-values are less beneficial under the tested short-time (10 min acquisition) conditions. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains.
Kelm, Nathaniel D; West, Kathryn L; Carson, Robert P; Gochberg, Daniel F; Ess, Kevin C; Does, Mark D
2016-01-01
Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and DKI-derived white matter tract integrity metrics (WMTI) were experimentally evaluated ex vivo through comparisons to histological measurements and established magnetic resonance imaging (MRI) measures of myelin in two knockout mouse models with varying degrees of hypomyelination. DKI metrics of mean and radial kurtosis were found to be better indicators of myelin content than conventional DTI metrics. The biophysical WMTI model based on the DKI framework reported on axon water fraction with good accuracy in cases with near normal axon density, but did not provide additional specificity to myelination. Overall, DKI provided additional information regarding white matter microstructure compared with DTI, making it an attractive method for future assessments of white matter development and pathology. Copyright © 2015 Elsevier Inc. All rights reserved.
Sun, Kun; Chen, Xiaosong; Chai, Weimin; Fei, Xiaochun; Fu, Caixia; Yan, Xu; Zhan, Ying; Chen, Kemin; Shen, Kunwei; Yan, Fuhua
2015-10-01
To assess diagnostic accuracy with diffusion kurtosis imaging (DKI) in patients with breast lesions and to evaluate the potential association between DKI-derived parameters and breast cancer clinical-pathologic factors. Institutional review board approval and written informed consent were obtained. Data from 97 patients (mean age ± standard deviation, 45.7 years ± 13.1; range, 19-70 years) with 98 lesions (57 malignant and 41 benign) who were treated between January 2014 and April 2014 were retrospectively analyzed. DKI (with b values of 0-2800 sec/mm(2)) and conventional diffusion-weighted imaging data were acquired. Kurtosis and diffusion coefficients from DKI and apparent diffusion coefficients from diffusion-weighted imaging were measured by two radiologists. Student t test, Wilcoxon signed-rank test, Jonckheere-Terpstra test, receiver operating characteristic curves, and Spearman correlation were used for statistical analysis. Kurtosis coefficients were significantly higher in the malignant lesions than in the benign lesions (1.05 ± 0.22 vs 0.65 ± 0.11, respectively; P < .0001). Diffusivity and apparent diffusion coefficients in the malignant lesions were significantly lower than those in the benign lesions (1.13 ± 0.27 vs 1.97 ± 0.33 and 1.02 ± 0.18 vs 1.48 ± 0.33, respectively; P < .0001). Significantly higher specificity for differentiation of malignant from benign lesions was shown with the use of kurtosis and diffusivity coefficients than with the use of apparent diffusion coefficients (83% [34 of 41] and 83% [34 of 41] vs 76% [31 of 41], respectively; P < .0001) with equal sensitivity (95% [54 of 57]). In patients with invasive breast cancer, kurtosis was positively correlated with tumor histologic grade (r = 0.75) and expression of the Ki-67 protein (r = 0.55). Diffusivity was negatively correlated with tumor histologic grades (r = -0.44) and Ki-67 expression (r = -0.46). DKI showed higher specificity than did conventional diffusion-weighted imaging for assessment of benign and malignant breast lesions. Patients with grade 3 breast cancer or tumors with high expression of Ki-67 were associated with higher kurtosis and lower diffusivity coefficients; however, this association must be confirmed in prospective studies. (©) RSNA, 2015 Online supplemental material is available for this article.
Verma, Sadhna; Sarkar, Saradwata; Young, Jason; Venkataraman, Rajesh; Yang, Xu; Bhavsar, Anil; Patil, Nilesh; Donovan, James; Gaitonde, Krishnanath
2016-05-01
The purpose of this study was to compare high b-value (b = 2000 s/mm(2)) acquired diffusion-weighted imaging (aDWI) with computed DWI (cDWI) obtained using four diffusion models-mono-exponential (ME), intra-voxel incoherent motion (IVIM), stretched exponential (SE), and diffusional kurtosis (DK)-with respect to lesion visibility, conspicuity, contrast, and ability to predict significant prostate cancer (PCa). Ninety four patients underwent 3 T MRI including acquisition of b = 2000 s/mm(2) aDWI and low b-value DWI. High b = 2000 s/mm(2) cDWI was obtained using ME, IVIM, SE, and DK models. All images were scored on quality independently by three radiologists. Lesions were identified on all images and graded for lesion conspicuity. For a subset of lesions for which pathological truth was established, lesion-to-background contrast ratios (LBCRs) were computed and binomial generalized linear mixed model analysis was conducted to compare clinically significant PCa predictive capabilities of all DWI. For all readers and all models, cDWI demonstrated higher ratings for image quality and lesion conspicuity than aDWI except DK (p < 0.001). The LBCRs of ME, IVIM, and SE were significantly higher than LBCR of aDWI (p < 0.001). Receiver Operating Characteristic curves obtained from binomial generalized linear mixed model analysis demonstrated higher Area Under the Curves for ME, SE, IVIM, and aDWI compared to DK or PSAD alone in predicting significant PCa. High b-value cDWI using ME, IVIM, and SE diffusion models provide better image quality, lesion conspicuity, and increased LBCR than high b-value aDWI. Using cDWI can potentially provide comparable sensitivity and specificity for detecting significant PCa as high b-value aDWI without increased scan times and image degradation artifacts.
Higher-order scene statistics of breast images
NASA Astrophysics Data System (ADS)
Abbey, Craig K.; Sohl-Dickstein, Jascha N.; Olshausen, Bruno A.; Eckstein, Miguel P.; Boone, John M.
2009-02-01
Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural scenes. It is argued that this allows for sparse representation of the independent components of natural images [Olshausen and Field, Nature, 1996]. These theories have important implications for medical image perception. For example, will a system that is designed to represent the independent components of natural scenes, where objects occlude one another and illumination is typically reflected, be appropriate for X-ray imaging, where features superimpose on one another and illumination is transmissive? In this research we begin to examine these issues by evaluating higher-order statistical properties of breast images from X-ray projection mammography (PM) and dedicated breast computed tomography (bCT). We evaluate kurtosis in responses of octave bandwidth Gabor filters applied to PM and to coronal slices of bCT scans. We find that kurtosis in PM rises and quickly saturates for filter center frequencies with an average value above 0.95. By contrast, kurtosis in bCT peaks near 0.20 cyc/mm with kurtosis of approximately 2. Our findings suggest that the human visual system may be tuned to represent breast tissue more effectively in bCT over a specific range of spatial frequencies.
Budjan, Johannes; Sauter, Elke A; Zoellner, Frank G; Lemke, Andreas; Wambsganss, Jens; Schoenberg, Stefan O; Attenberger, Ulrike I
2018-01-01
Background Functional techniques like diffusion-weighted imaging (DWI) are gaining more and more importance in liver magnetic resonance imaging (MRI). Diffusion kurtosis imaging (DKI) is an advanced technique that might help to overcome current limitations of DWI. Purpose To evaluate DKI for the differentiation of hepatic lesions in comparison to conventional DWI at 3 Tesla. Material and Methods Fifty-six consecutive patients were examined using a routine abdominal MR protocol at 3 Tesla which included DWI with b-values of 50, 400, 800, and 1000 s/mm 2 . Apparent diffusion coefficient maps were calculated applying a standard mono-exponential fit, while a non-Gaussian kurtosis fit was used to obtain DKI maps. ADC as well as Kurtosis-corrected diffusion ( D) values were quantified by region of interest analysis and compared between lesions. Results Sixty-eight hepatic lesions (hepatocellular carcinoma [HCC] [n = 25]; hepatic adenoma [n = 4], cysts [n = 18]; hepatic hemangioma [HH] [n = 18]; and focal nodular hyperplasia [n = 3]) were identified. Differentiation of malignant and benign lesions was possible based on both DWI ADC as well as DKI D-values ( P values were in the range of 0.04 to < 0.0001). Conclusion In vivo abdominal DKI calculated using standard b-values is feasible and enables quantitative differentiation between malignant and benign liver lesions. Assessment of conventional ADC values leads to similar results when using b-values below 1000 s/mm 2 for DKI calculation.
Xu, Xiao-Quan; Ma, Gao; Wang, Yan-Jun; Hu, Hao; Su, Guo-Yi; Shi, Hai-Bin; Wu, Fei-Yun
2017-07-18
To evaluate the correlation between histogram parameters derived from diffusion-kurtosis (DK) imaging and the clinical stage of nasopharyngeal carcinoma (NPC). High T-stage (T3/4) NPC showed significantly higher Kapp-mean (P = 0.018), Kapp-median (P = 0.029) and Kapp-90th (P = 0.003) than low T-stage (T1/2) NPC. High N-stage NPC (N2/3) showed significantly lower Dapp-mean (P = 0.002), Dapp-median (P = 0.002) and Dapp-10th (P < 0.001) than low N-stage NPC (N0/1). High AJCC-stage NPC (III/IV) showed significantly lower Dapp-10th (P = 0.038) than low AJCC-stage NPC (I/II). ROC analyses indicated that Kapp-90th was optimal for predicting high T-stage (AUC, 0.759; sensitivity, 0.842; specificity, 0.607), while Dapp-10th was best for predicting high N- and AJCC-stage (N-stage, AUC, 0.841; sensitivity, 0.875; specificity, 0.807; AJCC-stage, AUC, 0.671; sensitivity, 0.800; specificity, 0.588). DK imaging data of forty-seven consecutive NPC patients were retrospectively analyzed. Apparent diffusion for Gaussian distribution (Dapp) and apparent kurtosis coefficient (Kapp) were generated using diffusion-kurtosis model. Histogram parameters, including mean, median, 10th, 90th percentiles, skewness and kurtosis of Dapp and Kapp were calculated. Patients were divided into low and high T, N and clinical stage based on American Joint Committee on Cancer (AJCC) staging system. Differences of histogram parameters between low and high T, N and AJCC stages were compared using t test. Multiple receiver operating characteristic (ROC) curves were used to determine and compare the value of significant parameters in predicting high T, N and AJCC stage, respectively. DK imaging-derived parameters correlated well with clinical stage of NPC, therefore could serve as an adjunctive imaging technique for evaluating NPC.
Ma, Gao; Xu, Xiao-Quan; Hu, Hao; Su, Guo-Yi; Shen, Jie; Shi, Hai-Bin; Wu, Fei-Yun
2018-01-01
To compare the diagnostic performance of readout-segmented echo-planar imaging (RS-EPI)-based diffusion kurtosis imaging (DKI) and that of diffusion-weighted imaging (DWI) for differentiating malignant from benign masses in head and neck region. Between December 2014 and April 2016, we retrospectively enrolled 72 consecutive patients with head and neck masses who had undergone RS-EPI-based DKI scan (b value of 0, 500, 1000, and 1500 s/mm 2 ) for pretreatment evaluation. Imaging data were post-processed by using monoexponential and diffusion kurtosis (DK) model for quantitation of apparent diffusion coefficient (ADC), apparent diffusion for Gaussian distribution (D app ), and apparent kurtosis coefficient (K app ). Unpaired t test and Mann-Whitney U test were used to compare differences of quantitative parameters between malignant and benign groups. Receiver operating characteristic curve analyses were performed to determine and compare the diagnostic ability of quantitative parameters in predicting malignancy. Malignant group demonstrated significantly lower ADC (0.754 ± 0.167 vs. 1.222 ± 0.420, p < 0.001) and D app (1.029 ± 0.226 vs. 1.640 ± 0.445, p < 0.001) while higher K app (1.344 ± 0.309 vs. 0.715 ± 0.249, p < 0.001) than benign group. Using a combination of D app and K app as diagnostic index, significantly better differentiating performance was achieved than using ADC alone (area under curve: 0.956 vs. 0.876, p = 0.042). Compared to DWI, DKI could provide additional data related to tumor heterogeneity with significantly better differentiating performance. Its derived quantitative metrics could serve as a promising imaging biomarker for differentiating malignant from benign masses in head and neck region.
WE-EF-303-10: Single- Detector Proton Radiography as a Portal Imaging Equivalent for Proton Therapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Doolan, P; Bentefour, E; Testa, M
2015-06-15
Purpose: In proton therapy, patient alignment is of critical importance due to the sensitivity of the proton range to tissue heterogeneities. Traditionally proton radiography is used for verification of the water-equivalent path length (WEPL), which dictates the depth protons reach. In this work we propose its use for alignment. Additionally, many new proton centers have cone-beam computed tomography in place of beamline X-ray imaging and so proton radiography offers a unique patient alignment verification similar to portal imaging in photon therapy. Method: Proton radiographs of a CIRS head phantom were acquired using the Beam Imaging System (BIS) (IBA, Louvain-la-Neuve) inmore » a horizontal beamline. A scattered beam was produced using a small, dedicated, range modulator (RM) wheel fabricated out of aluminum. The RM wheel was rotated slowly (20 sec/rev) using a stepper motor to compensate for the frame rate of the BIS (120 ms). Dose rate functions (DRFs) over two RM wheel rotations were acquired. Calibration was made with known thicknesses of homogeneous solid water. For each pixel the time width, skewness and kurtosis of the DRFs were computed. The time width was used to compute the object WEPL. In the heterogeneous phantom, the excess skewness and excess kurtosis (i.e. difference from homogeneous cases) were computed and assessed for suitability for patient set up. Results: The technique allowed for the simultaneous production of images that can be used for WEPL verification, showing few internal details, and excess skewness and kurtosis images that can be used for soft tissue alignment. These latter images highlight areas where range mixing has occurred, correlating with phantom heterogeneities. Conclusion: The excess skewness and kurtosis images contain details that are not visible in the WET images. These images, unique to the time-resolved proton radiographic method, could be used for patient set up according to soft tissues.« less
Nilsson, Markus; Szczepankiewicz, Filip; van Westen, Danielle; Hansson, Oskar
2015-01-01
Conventional motion and eddy-current correction, where each diffusion-weighted volume is registered to a non diffusion-weighted reference, suffers from poor accuracy for high b-value data. An alternative approach is to extrapolate reference volumes from low b-value data. We aim to compare the performance of conventional and extrapolation-based correction of diffusional kurtosis imaging (DKI) data, and to demonstrate the impact of the correction approach on group comparison studies. DKI was performed in patients with Parkinson's disease dementia (PDD), and healthy age-matched controls, using b-values of up to 2750 s/mm2. The accuracy of conventional and extrapolation-based correction methods was investigated. Parameters from DTI and DKI were compared between patients and controls in the cingulum and the anterior thalamic projection tract. Conventional correction resulted in systematic registration errors for high b-value data. The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics. Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method. We recommend that conventional motion and eddy-current correction should be abandoned for high b-value data in favour of more accurate methods using extrapolation-based references.
Szczepankiewicz, Filip; van Westen, Danielle; Englund, Elisabet; Westin, Carl-Fredrik; Ståhlberg, Freddy; Lätt, Jimmy; Sundgren, Pia C; Nilsson, Markus
2016-11-15
The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. We performed dMRI using a novel encoding scheme for diffusional variance decomposition (DIVIDE) in 7 meningiomas and 8 gliomas prior to surgery. The diffusional variance was quantified from dMRI in terms of the total mean kurtosis (MK T ), and DIVIDE was used to decompose MK T into components caused by microscopic anisotropy (MK A ) and isotropic heterogeneity (MK I ). Diffusion anisotropy was evaluated in terms of the fractional anisotropy (FA) and microscopic fractional anisotropy (μFA). Quantitative microscopy was performed on the excised tumor tissue, where structural anisotropy and cell density were quantified by structure tensor analysis and cell nuclei segmentation, respectively. In order to validate the DIVIDE parameters they were correlated to the corresponding parameters derived from microscopy. We found an excellent agreement between the DIVIDE parameters and corresponding microscopy parameters; MK A correlated with cell eccentricity (r=0.95, p<10 -7 ) and MK I with the cell density variance (r=0.83, p<10 -3 ). The diffusion anisotropy correlated with structure tensor anisotropy on the voxel-scale (FA, r=0.80, p<10 -3 ) and microscopic scale (μFA, r=0.93, p<10 -6 ). A multiple regression analysis showed that the conventional MK T parameter reflects both variable cell eccentricity and cell density, and therefore lacks specificity in terms of microstructure characteristics. However, specificity was obtained by decomposing the two contributions; MK A was associated only to cell eccentricity, and MK I only to cell density variance. The variance in meningiomas was caused primarily by microscopic anisotropy (mean±s.d.) MK A =1.11±0.33 vs MK I =0.44±0.20 (p<10 -3 ), whereas in the gliomas, it was mostly caused by isotropic heterogeneity MK I =0.57±0.30 vs MK A =0.26±0.11 (p<0.05). In conclusion, DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Recent developments in fast kurtosis imaging
NASA Astrophysics Data System (ADS)
Hansen, Brian; Jespersen, Sune N.
2017-09-01
Diffusion kurtosis imaging (DKI) is an extension of the popular diffusion tensor imaging (DTI) technique. DKI takes into account leading deviations from Gaussian diffusion stemming from a number of effects related to the microarchitecture and compartmentalization in biological tissues. DKI therefore offers increased sensitivity to subtle microstructural alterations over conventional diffusion imaging such as DTI, as has been demonstrated in numerous reports. For this reason, interest in routine clinical application of DKI is growing rapidly. In an effort to facilitate more widespread use of DKI, recent work by our group has focused on developing experimentally fast and robust estimates of DKI metrics. A significant increase in speed is made possible by a reduction in data demand achieved through rigorous analysis of the relation between the DKI signal and the kurtosis tensor based metrics. The fast DKI methods therefore need only 13 or 19 images for DKI parameter estimation compared to more than 60 for the most modest DKI protocols applied today. Closed form solutions also ensure rapid calculation of most DKI metrics. Some parameters can even be reconstructed in real time, which may be valuable in the clinic. The fast techniques are based on conventional diffusion sequences and are therefore easily implemented on almost any clinical system, in contrast to a range of other recently proposed advanced diffusion techniques. In addition to its general applicability, this also ensures that any acceleration achieved in conventional DKI through sequence or hardware optimization will also translate directly to fast DKI acquisitions. In this review, we recapitulate the theoretical basis for the fast kurtosis techniques and their relation to conventional DKI. We then discuss the currently available variants of the fast DKI methods, their strengths and weaknesses, as well as their respective realms of application. These range from whole body applications to methods mostly suited for spinal cord or peripheral nerve, and analysis specific to brain white matter. Having covered these technical aspects, we proceed to review the fast kurtosis literature including validation studies, organ specific optimization studies and results from clinical applications.
Diffusional spread and confinement of newly exocytosed synaptic vesicle proteins
Gimber, Niclas; Tadeus, Georgi; Maritzen, Tanja; Schmoranzer, Jan; Haucke, Volker
2015-01-01
Neurotransmission relies on the calcium-triggered exocytic fusion of non-peptide neurotransmitter-containing small synaptic vesicles (SVs) with the presynaptic membrane at active zones (AZs) followed by compensatory endocytic retrieval of SV membranes. Here, we study the diffusional fate of newly exocytosed SV proteins in hippocampal neurons by high-resolution time-lapse imaging. Newly exocytosed SV proteins rapidly disperse within the first seconds post fusion until confined within the presynaptic bouton. Rapid diffusional spread and confinement is followed by slow reclustering of SV proteins at the periactive endocytic zone. Confinement within the presynaptic bouton is mediated in part by SV protein association with the clathrin-based endocytic machinery to limit diffusional spread of newly exocytosed SV proteins. These data suggest that diffusion, and axonal escape of newly exocytosed vesicle proteins, are counteracted by the clathrin-based endocytic machinery together with a presynaptic diffusion barrier. PMID:26399746
Diffusional spread and confinement of newly exocytosed synaptic vesicle proteins
NASA Astrophysics Data System (ADS)
Gimber, Niclas; Tadeus, Georgi; Maritzen, Tanja; Schmoranzer, Jan; Haucke, Volker
2015-09-01
Neurotransmission relies on the calcium-triggered exocytic fusion of non-peptide neurotransmitter-containing small synaptic vesicles (SVs) with the presynaptic membrane at active zones (AZs) followed by compensatory endocytic retrieval of SV membranes. Here, we study the diffusional fate of newly exocytosed SV proteins in hippocampal neurons by high-resolution time-lapse imaging. Newly exocytosed SV proteins rapidly disperse within the first seconds post fusion until confined within the presynaptic bouton. Rapid diffusional spread and confinement is followed by slow reclustering of SV proteins at the periactive endocytic zone. Confinement within the presynaptic bouton is mediated in part by SV protein association with the clathrin-based endocytic machinery to limit diffusional spread of newly exocytosed SV proteins. These data suggest that diffusion, and axonal escape of newly exocytosed vesicle proteins, are counteracted by the clathrin-based endocytic machinery together with a presynaptic diffusion barrier.
[A correlation between diffusion kurtosis imaging and the proliferative activity of brain glioma].
Tonoyan, A S; Pronin, I N; Pitshelauri, D I; Shishkina, L V; Fadeeva, L M; Pogosbekyan, E L; Zakharova, N E; Shults, E I; Khachanova, N V; Kornienko, V N; Potapov, A A
2015-01-01
The aim of the study was to assess the capabilities of diffusion kurtosis imaging (DKI) in diagnosis of the glioma proliferative activity and to evaluate a relationship between the glioma proliferative activity index and diffusion parameters of the contralateral normal appearing white matter (CNAWM). The study included 47 patients with newly diagnosed brain gliomas (23 low grade, 13 grade III, and 11 grade IV gliomas). We determined a relationship between absolute and normalized parameters of the diffusion tensor (mean (MD), axial (AD), and radial (RD) diffusivities; fractional (FA) and relative (RA) anisotropies) and diffusion kurtosis (mean (MK), axial (AK), and radial (RK) kurtosis; kurtosis anisotropy (KA)) and the proliferative activity index in the most malignant glioma parts (p<0.05). We also established a relationship between the tensor and kurtosis parameters of CNAWM and the glioma proliferative activity index (p<0.05). The correlation between all the absolute and normalized diffusion parameters and the glioma proliferative activity index, except absolute and normalized FA and RA values, was found to be statistically significant (p<0.05). Kurtosis (MK, AK, and RK) and anisotropy (KA, FA, RA) values increased, and diffusivity (MD, AD, RD) values decreased as the glioma proliferative activity index increased. A strong correlation between the proliferative activity index and absolute RK (r=0,71; p=0.000001) and normalized values of MK (r=0.8; p=0.000001), AK (r=0.71; p=0.000001), RK (r=0.81; p=0.000001), and RD (r=-0.71; p=0.000001) was found. A weak, but statistically significant correlation between the glioma proliferative activity index and diffusion values RK (r=-0.36; p=0.014), KA (r=-0.39; p=0.007), RD (r=0.35; p=0.017), FA (r=-0.42; p=0.003), and RA (r=-0.41; p=0.004) of CNAWM was found. DKI has good capabilities to detect immunohistochemical changes in gliomas. DKI demonstrated a high sensitivity in detection of microstructural changes in the contralateral normal appearing white matter in patients with brain gliomas.
New Insights into the Fractional Order Diffusion Equation Using Entropy and Kurtosis.
Ingo, Carson; Magin, Richard L; Parrish, Todd B
2014-11-01
Fractional order derivative operators offer a concise description to model multi-scale, heterogeneous and non-local systems. Specifically, in magnetic resonance imaging, there has been recent work to apply fractional order derivatives to model the non-Gaussian diffusion signal, which is ubiquitous in the movement of water protons within biological tissue. To provide a new perspective for establishing the utility of fractional order models, we apply entropy for the case of anomalous diffusion governed by a fractional order diffusion equation generalized in space and in time. This fractional order representation, in the form of the Mittag-Leffler function, gives an entropy minimum for the integer case of Gaussian diffusion and greater values of spectral entropy for non-integer values of the space and time derivatives. Furthermore, we consider kurtosis, defined as the normalized fourth moment, as another probabilistic description of the fractional time derivative. Finally, we demonstrate the implementation of anomalous diffusion, entropy and kurtosis measurements in diffusion weighted magnetic resonance imaging in the brain of a chronic ischemic stroke patient.
Yin, Jianzhong; Sun, Haizhen; Wang, Zhiyun; Ni, Hongyan; Shen, Wen; Sun, Phillip Zhe
2018-05-01
Purpose To determine the relationship between diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in patients with acute stroke at admission and the tissue outcome 1 month after onset of stroke. Materials and Methods Patients with stroke underwent DWI (b values = 0, 1000 sec/mm 2 along three directions) and DKI (b values = 0, 1000, 2000 sec/mm 2 along 20 directions) within 24 hours after symptom onset and 1 month after symptom onset. For large lesions (diameter ≥ 1 cm), acute lesion volumes at DWI and DKI were compared with those at follow-up T2-weighted imaging by using Spearman correlation analysis. For small lesions (diameter < 1 cm), the number of acute lesions at DWI and DKI and follow-up T2-weighted imaging was counted and compared by using the McNemar test. Results Thirty-seven patients (mean age, 58 years; range, 35-82 years) were included. There were 32 large lesions and 138 small lesions. For large lesions, the volumes of acute lesions on kurtosis maps showed no difference from those on 1-month follow-up T2-weighted images (P = .532), with a higher correlation coefficient than those on the apparent diffusion coefficient and mean diffusivity maps (R 2 = 0.730 vs 0.479 and 0.429). For small lesions, the number of acute lesions on DKI, but not on DWI, images was consistent with that on the follow-up T2-weighted images (P = .125). Conclusion DKI complements DWI for improved prediction of outcome of acute ischemic stroke. © RSNA, 2018.
Wang, Hai-yi; Su, Zi-hua; Xu, Xiao; Sun, Zhi-peng; Duan, Fei-xue; Song, Yuan-yuan; Li, Lu; Wang, Ying-wei; Ma, Xin; Guo, Ai-tao; Ma, Lin; Ye, Hui-yi
2016-01-01
Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K trans & Ve) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters. PMID:27380733
Qi, Xi-Xun; Shi, Da-Fa; Ren, Si-Xie; Zhang, Su-Ya; Li, Long; Li, Qing-Chang; Guan, Li-Ming
2018-04-01
To investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the evaluation of glioma grading. A total of 39 glioma patients who underwent preoperative magnetic resonance imaging (MRI) were classified into low-grade (13 cases) and high-grade (26 cases) glioma groups. Parametric DKI maps were derived, and histogram metrics between low- and high-grade gliomas were analysed. The optimum diagnostic thresholds of the parameters, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were achieved using a receiver operating characteristic (ROC). Significant differences were observed not only in 12 metrics of histogram DKI parameters (P<0.05), but also in mean diffusivity (MD) and mean kurtosis (MK) values, including age as a covariate (F=19.127, P<0.001 and F=20.894, P<0.001, respectively), between low- and high-grade gliomas. Mean MK was the best independent predictor of differentiating glioma grades (B=18.934, 22.237 adjusted for age, P<0.05). The partial correlation coefficient between fractional anisotropy (FA) and kurtosis fractional anisotropy (KFA) was 0.675 (P<0.001). The AUC of the mean MK, sensitivity, and specificity were 0.925, 88.5% and 84.6%, respectively. DKI parameters can effectively distinguish between low- and high-grade gliomas. Mean MK is the best independent predictor of differentiating glioma grades. • DKI is a new and important method. • DKI can provide additional information on microstructural architecture. • Histogram analysis of DKI may be more effective in glioma grading.
Person Authentication Using Learned Parameters of Lifting Wavelet Filters
NASA Astrophysics Data System (ADS)
Niijima, Koichi
2006-10-01
This paper proposes a method for identifying persons by the use of the lifting wavelet parameters learned by kurtosis-minimization. Our learning method uses desirable properties of kurtosis and wavelet coefficients of a facial image. Exploiting these properties, the lifting parameters are trained so as to minimize the kurtosis of lifting wavelet coefficients computed for the facial image. Since this minimization problem is an ill-posed problem, it is solved by the aid of Tikhonov's regularization method. Our learning algorithm is applied to each of the faces to be identified to generate its feature vector whose components consist of the learned parameters. The constructed feature vectors are memorized together with the corresponding faces in a feature vectors database. Person authentication is performed by comparing the feature vector of a query face with those stored in the database. In numerical experiments, the lifting parameters are trained for each of the neutral faces of 132 persons (74 males and 58 females) in the AR face database. Person authentication is executed by using the smile and anger faces of the same persons in the database.
Experimental considerations for fast kurtosis imaging.
Hansen, Brian; Lund, Torben E; Sangill, Ryan; Stubbe, Ebbe; Finsterbusch, Jürgen; Jespersen, Sune Nørhøj
2016-11-01
The clinical use of kurtosis imaging is impeded by long acquisitions and postprocessing. Recently, estimation of mean kurtosis tensor W¯ and mean diffusivity ( D¯) was made possible from 13 distinct diffusion weighted MRI acquisitions (the 1-3-9 protocol) with simple postprocessing. Here, we analyze the effects of noise and nonideal diffusion encoding, and propose a new correction strategy. We also present a 1-9-9 protocol with increased robustness to experimental imperfections and minimal additional scan time. This refinement does not affect computation time and also provides a fast estimate of fractional anisotropy (FA). 1-3-9/1-9-9 data are acquired in rat and human brains, and estimates of D¯, FA, W¯ from human brains are compared with traditional estimates from an extensive diffusion kurtosis imaging data set. Simulations are used to evaluate the influence of noise and diffusion encodings deviating from the scheme, and the performance of the correction strategy. Optimal b-values are determined from simulations and data. Accuracy and precision in D¯ and W¯ are comparable to nonlinear least squares estimation, and is improved with the 1-9-9 protocol. The compensation strategy vastly improves parameter estimation in nonideal data. The framework offers a robust and compact method for estimating several diffusion metrics. The protocol is easily implemented. Magn Reson Med 76:1455-1468, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Optimization of Scan Parameters to Reduce Acquisition Time for Diffusion Kurtosis Imaging at 1.5T.
Yokosawa, Suguru; Sasaki, Makoto; Bito, Yoshitaka; Ito, Kenji; Yamashita, Fumio; Goodwin, Jonathan; Higuchi, Satomi; Kudo, Kohsuke
2016-01-01
To shorten acquisition of diffusion kurtosis imaging (DKI) in 1.5-tesla magnetic resonance (MR) imaging, we investigated the effects of the number of b-values, diffusion direction, and number of signal averages (NSA) on the accuracy of DKI metrics. We obtained 2 image datasets with 30 gradient directions, 6 b-values up to 2500 s/mm(2), and 2 signal averages from 5 healthy volunteers and generated DKI metrics, i.e., mean, axial, and radial kurtosis (MK, K∥, and K⊥) maps, from various combinations of the datasets. These maps were estimated by using the intraclass correlation coefficient (ICC) with those from the full datasets. The MK and K⊥ maps generated from the datasets including only the b-value of 2500 s/mm(2) showed excellent agreement (ICC, 0.96 to 0.99). Under the same acquisition time and diffusion directions, agreement was better of MK, K∥, and K⊥ maps obtained with 3 b-values (0, 1000, and 2500 s/mm(2)) and 4 signal averages than maps obtained with any other combination of numbers of b-value and varied NSA. Good agreement (ICC > 0.6) required at least 20 diffusion directions in all the metrics. MK and K⊥ maps with ICC greater than 0.95 can be obtained at 1.5T within 10 min (b-value = 0, 1000, and 2500 s/mm(2); 20 diffusion directions; 4 signal averages; slice thickness, 6 mm with no interslice gap; number of slices, 12).
Chen, T; Li, Y; Lu, S-S; Zhang, Y-D; Wang, X-N; Luo, C-Y; Shi, H-B
2017-11-01
To evaluate the diagnostic performance of histogram analysis of diffusion kurtosis magnetic resonance imaging (DKI) and standard diffusion-weighted imaging (DWI) in discriminating tumour grades of endometrial carcinoma (EC). Seventy-three patients with EC were included in this study. The apparent diffusion coefficient (ADC) value from standard DWI, apparent diffusion for Gaussian distribution (D app ), and apparent kurtosis coefficient (K app ) from DKI were acquired using a 3 T magnetic resonance imaging (MRI) system. The measurement was based on an entire-tumour analysis. Histogram parameters (D app , K app , and ADC) were compared between high-grade (grade 3) and low-grade (grade 1 and 2) tumours. The diagnostic performance of imaging parameters for discriminating high- from low-grade tumours was analysed using a receiver operating characteristic curve (ROC). The area under the ROC curve (AUC) of the 10th percentile of D app , 90th percentile of K app and 10th percentile of ADC were higher than other parameters in distinguishing high-grade tumours from low-grade tumours (AUC=0.821, 0.891 and 0.801, respectively). The combination of 10th percentile of D app and 90th percentile of K app improved the AUC to 0.901, which was significantly higher than that of the 10th percentile of ADC (0.810, p=0.0314) in differentiating high- from low-grade EC. Entire-tumour volume histogram analysis of DKI and standard DWI were feasible for discriminating histological tumour grades of EC. DKI was relatively better than DWI in distinguishing high-grade from low-grade tumour in EC. Copyright © 2017. Published by Elsevier Ltd.
Docx, Lise; Emsell, Louise; Van Hecke, Wim; De Bondt, Timo; Parizel, Paul M; Sabbe, Bernard; Morrens, Manuel
2017-02-28
Avolition is a core feature of schizophrenia and may arise from altered brain connectivity. Here we used diffusion kurtosis imaging (DKI) to investigate the association between white matter (WM) microstructure and volitional motor activity. Multi-shell diffusion MRI and 24-h actigraphy data were obtained from 20 right-handed patients with schizophrenia and 16 right-handed age and gender matched healthy controls. We examined correlations between fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), and motor activity level, as well as group differences in these measures. In the patient group, increasing motor activity level was positively correlated with MK in the inferior, medial and superior longitudinal fasciculus, the corpus callosum, the posterior fronto-occipital fasciculus and the posterior cingulum. This association was not found in control subjects or in DTI measures. These results show that a lack of volitional motor activity in schizophrenia is associated with potentially altered WM microstructure in posterior brain regions associated with cognitive function and motivation. This could reflect both illness related dysconnectivity which through altered cognition, manifests as reduced volitional motor activity, and/or the effects of reduced physical activity on brain WM. Copyright © 2016. Published by Elsevier B.V.
Peregrina-Barreto, Hayde; Perez-Corona, Elizabeth; Rangel-Magdaleno, Jose; Ramos-Garcia, Ruben; Chiu, Roger; Ramirez-San-Juan, Julio C
2017-06-01
Visualization of deep blood vessels in speckle images is an important task as it is used to analyze the dynamics of the blood flow and the health status of biological tissue. Laser speckle imaging is a wide-field optical technique to measure relative blood flow speed based on the local speckle contrast analysis. However, it has been reported that this technique is limited to certain deep blood vessels (about ? = 300 ?? ? m ) because of the high scattering of the sample; beyond this depth, the quality of the vessel’s image decreases. The use of a representation based on homogeneity values, computed from the co-occurrence matrix, is proposed as it provides an improved vessel definition and its corresponding diameter. Moreover, a methodology is proposed for automatic blood vessel location based on the kurtosis analysis. Results were obtained from the different skin phantoms, showing that it is possible to identify the vessel region for different morphologies, even up to 900 ?? ? m in depth.
No differences in brain microstructure between young KIBRA-C carriers and non-carriers.
Hu, Li; Xu, Qunxing; Li, Jizhen; Wang, Feifei; Xu, Xinghua; Sun, Zhiyuan; Ma, Xiangxing; Liu, Yong; Wang, Qing; Wang, Dawei
2018-01-02
KIBRA rs17070145 polymorphism is associated with variations in memory function and the microstructure of related brain areas. Diffusion kurtosis imaging (DKI) as an extension of diffusion tensor imaging that can provide more information about changes in microstructure, based on the idea that water diffusion in biological tissues is heterogeneous due to structural hindrance and restriction. We used DKI to explore the relationship between KIBRA gene polymorphism and brain microstructure in young adults. We recruited 100 healthy young volunteers, including 53 TT carriers and 47 C allele carriers. No differences were detected between the TT homozygotes and C-allele carriers for any diffusion and kurtosis parameter. These results indicate KIBRA rs17070145 polymorphism likely has little or no effect on brain microstructure in young adults.
Lanzafame, S; Giannelli, M; Garaci, F; Floris, R; Duggento, A; Guerrisi, M; Toschi, N
2016-05-01
An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine. Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.
Khairnar, Amit; Latta, Peter; Drazanova, Eva; Ruda-Kucerova, Jana; Szabó, Nikoletta; Arab, Anas; Hutter-Paier, Birgit; Havas, Daniel; Windisch, Manfred; Sulcova, Alexandra; Starcuk, Zenon; Rektorova, Irena
2015-11-01
Evidence suggests that accumulation and aggregation of α-synuclein contribute to the pathogenesis of Parkinson's disease (PD). The aim of this study was to evaluate whether diffusion kurtosis imaging (DKI) will provide a sensitive tool for differentiating between α-synuclein-overexpressing transgenic mouse model of PD (TNWT-61) and wild-type (WT) littermates. This experiment was designed as a proof-of-concept study and forms a part of a complex protocol and ongoing translational research. Nine-month-old TNWT-61 mice and age-matched WT littermates underwent behavioral tests to monitor motor impairment and MRI scanning using 9.4 Tesla system in vivo. Tract-based spatial statistics (TBSS) and the DKI protocol were used to compare the whole brain white matter of TNWT-61 and WT mice. In addition, region of interest (ROI) analysis was performed in gray matter regions such as substantia nigra, striatum, hippocampus, sensorimotor cortex, and thalamus known to show higher accumulation of α-synuclein. For the ROI analysis, both DKI (6 b-values) protocol and conventional (2 b-values) diffusion tensor imaging (cDTI) protocol were used. TNWT-61 mice showed significant impairment of motor coordination. With the DKI protocol, mean, axial, and radial kurtosis were found to be significantly elevated, whereas mean and radial diffusivity were decreased in the TNWT-61 group compared to that in the WT controls with both TBSS and ROI analysis. With the cDTI protocol, the ROI analysis showed decrease in all diffusivity parameters in TNWT-61 mice. The current study provides evidence that DKI by providing both kurtosis and diffusivity parameters gives unique information that is complementary to cDTI for in vivo detection of pathological changes that underlie PD-like symptomatology in TNWT-61 mouse model of PD. This result is a crucial step in search for a candidate diagnostic biomarker with translational potential and relevance for human studies.
Application of diffusion kurtosis imaging to odontogenic lesions: Analysis of the cystic component.
Sakamoto, Junichiro; Kuribayashi, Ami; Kotaki, Shinya; Fujikura, Mamiko; Nakamura, Shin; Kurabayashi, Tohru
2016-12-01
To assess the feasibility of applying diffusion kurtosis imaging (DKI) to common odontogenic lesions and to compare its diagnostic ability versus that of the apparent diffusion coefficient (ADC) for differentiating keratocystic odontogenic tumors (KCOTs) from odontogenic cysts. Altogether, 35 odontogenic lesions were studied: 24 odontogenic cysts, six KCOTs, and five ameloblastomas. The diffusion coefficient (D) and excessive kurtosis (K) were obtained from diffusion-weighted images at b-values of 0, 500, 1000, and 1500 s/mm 2 on 3T magnetic resonance imaging (MRI). The combination of D and K values showing the maximum density of the probable density function was estimated. The ADC was obtained (0 and 1000 s/mm 2 ). Values for odontogenic cysts, KCOTs, and ameloblastomas were compared. Multivariate logistic regression modeling was performed to assess the combination of D and K model versus ADC for differentiating KCOTs from odontogenic cysts. The mean D and ADC were significantly higher for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean K was significantly lower for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean values of all parameters for odontogenic cysts and KCOTs showed no significant differences (P = 0.369 for ADC, 0.133 for D, and 0.874 for K). The accuracy of the combination of D and K model (76.7%) was superior to that of ADC (66.7%). Use of DKI may be feasible for common odontogenic lesions. A combination of DKI parameters can be expected to increase the accuracy of its diagnostic ability compared with ADC. J. Magn. Reson. Imaging 2016;44:1565-1571. © 2016 International Society for Magnetic Resonance in Medicine.
Filli, Lukas; Wurnig, Moritz; Nanz, Daniel; Luechinger, Roger; Kenkel, David; Boss, Andreas
2014-12-01
Diffusion kurtosis imaging (DKI) is based on a non-Gaussian diffusion model that should inherently better account for restricted water diffusion within the complex microstructure of most tissues than the conventional diffusion-weighted imaging (DWI), which presumes Gaussian distributed water molecule displacement probability. The aim of this investigation was to test the technical feasibility of in vivo whole-body DKI, probe for organ-specific differences, and compare whole-body DKI and DWI results. Eight healthy subjects underwent whole-body DWI on a clinical 3.0 T magnetic resonance imaging system. Echo-planar images in the axial orientation were acquired at b-values of 0, 150, 300, 500, and 800 mm²/s. Parametrical whole-body maps of the diffusion coefficient (D), the kurtosis (K), and the traditional apparent diffusion coefficient (ADC) were generated. Goodness of fit was compared between DKI and DWI fits using the sums of squared residuals. Data groups were tested for significant differences of the mean by paired Student t tests. Good-quality parametrical whole-body maps of D, K, and ADC could be computed. Compared with ADC values, D values were significantly higher in the cerebral gray matter (by 30%) and white matter (27%), renal cortex (23%) and medulla (21%), spleen (101%), as well as erector spinae muscle (34%) (each P value <0.001). No significant differences between D and ADC were found in the cerebrospinal fluid (P = 0.08) and in the liver (P = 0.13). Curves of DKI fitted the measurement points significantly better than DWI curves did in most organs. Whole-body DKI is technically feasible and may reflect tissue microstructure more meaningfully than whole-body DWI.
NASA Astrophysics Data System (ADS)
Liang, Yingjie; Ye, Allen Q.; Chen, Wen; Gatto, Rodolfo G.; Colon-Perez, Luis; Mareci, Thomas H.; Magin, Richard L.
2016-10-01
Non-Gaussian (anomalous) diffusion is wide spread in biological tissues where its effects modulate chemical reactions and membrane transport. When viewed using magnetic resonance imaging (MRI), anomalous diffusion is characterized by a persistent or 'long tail' behavior in the decay of the diffusion signal. Recent MRI studies have used the fractional derivative to describe diffusion dynamics in normal and post-mortem tissue by connecting the order of the derivative with changes in tissue composition, structure and complexity. In this study we consider an alternative approach by introducing fractal time and space derivatives into Fick's second law of diffusion. This provides a more natural way to link sub-voxel tissue composition with the observed MRI diffusion signal decay following the application of a diffusion-sensitive pulse sequence. Unlike previous studies using fractional order derivatives, here the fractal derivative order is directly connected to the Hausdorff fractal dimension of the diffusion trajectory. The result is a simpler, computationally faster, and more direct way to incorporate tissue complexity and microstructure into the diffusional dynamics. Furthermore, the results are readily expressed in terms of spectral entropy, which provides a quantitative measure of the overall complexity of the heterogeneous and multi-scale structure of biological tissues. As an example, we apply this new model for the characterization of diffusion in fixed samples of the mouse brain. These results are compared with those obtained using the mono-exponential, the stretched exponential, the fractional derivative, and the diffusion kurtosis models. Overall, we find that the order of the fractal time derivative, the diffusion coefficient, and the spectral entropy are potential biomarkers to differentiate between the microstructure of white and gray matter. In addition, we note that the fractal derivative model has practical advantages over the existing models from the perspective of computational accuracy and efficiency.
Marrale, M; Collura, G; Brai, M; Toschi, N; Midiri, F; La Tona, G; Lo Casto, A; Gagliardo, C
2016-12-01
In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher order diffusion model that is a straightforward extension of the DTI model. Here, we analyze the physics underlying this method, we report our MRI acquisition protocol with the preprocessing pipeline used and the DKI parametric maps obtained on a 1.5 T scanner, and we review the most relevant clinical applications of this technique in various neurological diseases.
White matter biomarkers from diffusion MRI
NASA Astrophysics Data System (ADS)
Nørhøj Jespersen, Sune
2018-06-01
As part of an issue celebrating 2 decades of Joseph Ackerman editing the Journal of Magnetic Resonance, this paper reviews recent progress in one of the many areas in which Ackerman and his lab has made significant contributions: NMR measurement of diffusion in biological media, specifically in brain tissue. NMR diffusion signals display exquisite sensitivity to tissue microstructure, and have the potential to offer quantitative and specific information on the cellular scale orders of magnitude below nominal image resolution when combined with biophysical modeling. Here, I offer a personal perspective on some recent advances in diffusion imaging, from diffusion kurtosis imaging to microstructural modeling, and the connection between the two. A new result on the estimation accuracy of axial and radial kurtosis with axially symmetric DKI is presented. I moreover touch upon recently suggested generalized diffusion sequences, promising to offer independent microstructural information. We discuss the need and some methods for validation, and end with an outlook on some promising future directions.
Portfolio optimization with skewness and kurtosis
NASA Astrophysics Data System (ADS)
Lam, Weng Hoe; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi
2013-04-01
Mean and variance of return distributions are two important parameters of the mean-variance model in portfolio optimization. However, the mean-variance model will become inadequate if the returns of assets are not normally distributed. Therefore, higher moments such as skewness and kurtosis cannot be ignored. Risk averse investors prefer portfolios with high skewness and low kurtosis so that the probability of getting negative rates of return will be reduced. The objective of this study is to compare the portfolio compositions as well as performances between the mean-variance model and mean-variance-skewness-kurtosis model by using the polynomial goal programming approach. The results show that the incorporation of skewness and kurtosis will change the optimal portfolio compositions. The mean-variance-skewness-kurtosis model outperforms the mean-variance model because the mean-variance-skewness-kurtosis model takes skewness and kurtosis into consideration. Therefore, the mean-variance-skewness-kurtosis model is more appropriate for the investors of Malaysia in portfolio optimization.
Martin, Allan R.; Aleksanderek, Izabela; Cohen-Adad, Julien; Tarmohamed, Zenovia; Tetreault, Lindsay; Smith, Nathaniel; Cadotte, David W.; Crawley, Adrian; Ginsberg, Howard; Mikulis, David J.; Fehlings, Michael G.
2015-01-01
Background A recent meeting of international imaging experts sponsored by the International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 state-of-the-art MRI techniques with potential to transform the field of spinal cord imaging by elucidating elements of the microstructure and function: diffusion tensor imaging (DTI), magnetization transfer (MT), myelin water fraction (MWF), MR spectroscopy (MRS), and functional MRI (fMRI). However, the progress toward clinical translation of these techniques has not been established. Methods A systematic review of the English literature was conducted using MEDLINE, MEDLINE-in-Progress, Embase, and Cochrane databases to identify all human studies that investigated utility, in terms of diagnosis, correlation with disability, and prediction of outcomes, of these promising techniques in pathologies affecting the spinal cord. Data regarding study design, subject characteristics, MRI methods, clinical measures of impairment, and analysis techniques were extracted and tabulated to identify trends and commonalities. The studies were assessed for risk of bias, and the overall quality of evidence was assessed for each specific finding using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Results A total of 6597 unique citations were identified in the database search, and after full-text review of 274 articles, a total of 104 relevant studies were identified for final inclusion (97% from the initial database search). Among these, 69 studies utilized DTI and 25 used MT, with both techniques showing an increased number of publications in recent years. The review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. Most of the studies were exploratory in nature, lacking a priori hypotheses and showing a high (72%) or moderately high (20%) risk of bias, due to issues with study design, acquisition techniques, and analysis methods. The acquisitions for each technique varied widely across studies, rendering direct comparisons of metrics invalid. The DTI metric fractional anisotropy (FA) had the strongest evidence of utility, with moderate quality evidence for its use as a biomarker showing correlation with disability in several clinical pathologies, and a low level of evidence that it identifies tissue injury (in terms of group differences) compared with healthy controls. However, insufficient evidence exists to determine its utility as a sensitive and specific diagnostic test or as a tool to predict clinical outcomes. Very low quality evidence suggests that other metrics also show group differences compared with controls, including DTI metrics mean diffusivity (MD) and radial diffusivity (RD), the diffusional kurtosis imaging (DKI) metric mean kurtosis (MK), MT metrics MT ratio (MTR) and MT cerebrospinal fluid ratio (MTCSF), and the MRS metric of N-acetylaspartate (NAA) concentration, although these results were somewhat inconsistent. Conclusions State-of-the-art spinal cord MRI techniques are emerging with great potential to improve the diagnosis and management of various spinal pathologies, but the current body of evidence has only showed limited clinical utility to date. Among these imaging tools DTI is the most mature, but further work is necessary to standardize and validate its use before it will be adopted in the clinical realm. Large, well-designed studies with a priori hypotheses, standardized acquisition methods, detailed clinical data collection, and robust automated analysis techniques are needed to fully demonstrate the potential of these rapidly evolving techniques. PMID:26862478
Novel white matter tract integrity metrics sensitive to Alzheimer disease progression.
Fieremans, E; Benitez, A; Jensen, J H; Falangola, M F; Tabesh, A; Deardorff, R L; Spampinato, M V S; Babb, J S; Novikov, D S; Ferris, S H; Helpern, J A
2013-01-01
Along with cortical abnormalities, white matter microstructural changes such as axonal loss and myelin breakdown are implicated in the pathogenesis of Alzheimer disease. Recently, a white matter model was introduced that relates non-Gaussian diffusional kurtosis imaging metrics to characteristics of white matter tract integrity, including the axonal water fraction, the intra-axonal diffusivity, and the extra-axonal axial and radial diffusivities. This study reports these white matter tract integrity metrics in subjects with amnestic mild cognitive impairment (n = 12), Alzheimer disease (n = 14), and age-matched healthy controls (n = 15) in an effort to investigate their sensitivity, diagnostic accuracy, and associations with white matter changes through the course of Alzheimer disease. With tract-based spatial statistics and region-of-interest analyses, increased diffusivity in the extra-axonal space (extra-axonal axial and radial diffusivities) in several white matter tracts sensitively and accurately discriminated healthy controls from those with amnestic mild cognitive impairment (area under the receiver operating characteristic curve = 0.82-0.95), while widespread decreased axonal water fraction discriminated amnestic mild cognitive impairment from Alzheimer disease (area under the receiver operating characteristic curve = 0.84). Additionally, these white matter tract integrity metrics in the body of the corpus callosum were strongly correlated with processing speed in amnestic mild cognitive impairment (r = |0.80-0.82|, P < .001). These findings have implications for the course and spatial progression of white matter degeneration in Alzheimer disease, suggest the mechanisms by which these changes occur, and demonstrate the viability of these white matter tract integrity metrics as potential neuroimaging biomarkers of the earliest stages of Alzheimer disease and disease progression.
A comparison of earthquake backprojection imaging methods for dense local arrays
NASA Astrophysics Data System (ADS)
Beskardes, G. D.; Hole, J. A.; Wang, K.; Michaelides, M.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Brown, L. D.; Quiros, D. A.
2018-03-01
Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-term averaging/long-term averaging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveform method to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.
In Vivo Imaging of Tau Pathology Using Magnetic Resonance Imaging Textural Analysis
Colgan, Niall; Ganeshan, Balaji; Harrison, Ian F.; Ismail, Ozama; Holmes, Holly E.; Wells, Jack A.; Powell, Nick M.; O'Callaghan, James M.; O'Neill, Michael J.; Murray, Tracey K.; Ahmed, Zeshan; Collins, Emily C.; Johnson, Ross A.; Groves, Ashley; Lythgoe, Mark F.
2017-01-01
Background: Non-invasive characterization of the pathological features of Alzheimer's disease (AD) could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA) has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden. Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG) mice and 16 litter matched wild-type (WT) mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales), followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis). MRTA was applied to manually segmented regions of interest (ROI) drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology. Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01), the hippocampus (K, p < 0.05) and in the thalamus (K, p < 0.01). In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus. Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus) based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using routinely acquired structural MR images. PMID:29163005
Guglielmetti, C.; Veraart, J.; Roelant, E.; Mai, Z.; Daans, J.; Van Audekerke, J.; Naeyaert, M.; Vanhoutte, G.; Delgado y Palacios, R.; Praet, J.; Fieremans, E.; Ponsaerts, P.; Sijbers, J.; Van der Linden, A.; Verhoye, M.
2016-01-01
Although MRI is the gold standard for the diagnosis and monitoring of multiple sclerosis (MS), current conventional MRI techniques often fail to detect cortical alterations and provide little information about gliosis, axonal damage and myelin status of lesioned areas. Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) provide sensitive and complementary measures of the neural tissue microstructure. Additionally, specific white matter tract integrity (WMTI) metrics modelling the diffusion in white matter were recently derived. In the current study we used the well-characterized cuprizone mouse model of central nervous system demyelination to assess the temporal evolution of diffusion tensor (DT), diffusion kurtosis tensor (DK) and WMTI-derived metrics following acute inflammatory demyelination and spontaneous remyelination. While DT-derived metrics were unable to detect cuprizone induced cortical alterations, the mean kurtosis (MK) and radial kurtosis (RK) were found decreased under cuprizone administration, as compared to age-matched controls, in both the motor and somatosensory cortices. The MK remained decreased in the motor cortices at the end of the recovery period, reflecting long lasting impairment of myelination. In white matter, DT, DK and WMTI-derived metrics enabled the detection of cuprizone induced changes differentially according to the stage and the severity of the lesion. More specifically, MK, RK and the axonal water fraction (AWF) were the most sensitive for the detection of cuprizone induced changes in the genu of the corpus callosum, a region less affected by cuprizone administration. Additionally, microgliosis was associated with an increase of MK and RK during the acute inflammatory demyelination phase. In regions undergoing severe demyelination, namely the body and splenium of the corpus callosum, DT-derived metrics, notably the mean diffusion (MD) and radial diffusion (RD), were among the best discriminators between cuprizone and control groups, hence highlighting their ability to detect both acute and long lasting changes. Interestingly, WMTI-derived metrics showed the aptitude to distinguish between the different stage of the disease. Both the intra-axonal diffusivity (Da) and the AWF were found to be decreased in the cuprizone treated group, Da specifically decreased during the acute inflammatory demyelinating phase whereas the AWF decrease was associated to the spontaneous remyelination and the recovery period. Altogether our results demonstrate that DKI is sensitive to alterations of cortical areas and provides, along with WMTI metrics, information that is complementary to DT-derived metrics for the characterization of demyelination in both white and grey matter and subsequent inflammatory processes associated with a demyelinating event. PMID:26525654
Garza-Villarreal, E A; Chakravarty, M M; Hansen, B; Eskildsen, S F; Devenyi, G A; Castillo-Padilla, D; Balducci, T; Reyes-Zamorano, E; Jespersen, S N; Perez-Palacios, P; Patel, R; Gonzalez-Olvera, J J
2017-05-09
The striatum and thalamus are subcortical structures intimately involved in addiction. The morphology and microstructure of these have been studied in murine models of cocaine addiction (CA), showing an effect of drug use, but also chronological age in morphology. Human studies using non-invasive magnetic resonance imaging (MRI) have shown inconsistencies in volume changes, and have also shown an age effect. In this exploratory study, we used MRI-based volumetric and novel shape analysis, as well as a novel fast diffusion kurtosis imaging sequence to study the morphology and microstructure of striatum and thalamus in crack CA compared to matched healthy controls (HCs), while investigating the effect of age and years of cocaine consumption. We did not find significant differences in volume and mean kurtosis (MKT) between groups. However, we found significant contraction of nucleus accumbens in CA compared to HCs. We also found significant age-related changes in volume and MKT of CA in striatum and thalamus that are different to those seen in normal aging. Interestingly, we found different effects and contributions of age and years of consumption in volume, displacement and MKT changes, suggesting that each measure provides different but complementing information about morphological brain changes, and that not all changes are related to the toxicity or the addiction to the drug. Our findings suggest that the use of finer methods and sequences provides complementing information about morphological and microstructural changes in CA, and that brain alterations in CA are related cocaine use and age differently.
Garza-Villarreal, E A; Chakravarty, MM; Hansen, B; Eskildsen, S F; Devenyi, G A; Castillo-Padilla, D; Balducci, T; Reyes-Zamorano, E; Jespersen, S N; Perez-Palacios, P; Patel, R; Gonzalez-Olvera, J J
2017-01-01
The striatum and thalamus are subcortical structures intimately involved in addiction. The morphology and microstructure of these have been studied in murine models of cocaine addiction (CA), showing an effect of drug use, but also chronological age in morphology. Human studies using non-invasive magnetic resonance imaging (MRI) have shown inconsistencies in volume changes, and have also shown an age effect. In this exploratory study, we used MRI-based volumetric and novel shape analysis, as well as a novel fast diffusion kurtosis imaging sequence to study the morphology and microstructure of striatum and thalamus in crack CA compared to matched healthy controls (HCs), while investigating the effect of age and years of cocaine consumption. We did not find significant differences in volume and mean kurtosis (MKT) between groups. However, we found significant contraction of nucleus accumbens in CA compared to HCs. We also found significant age-related changes in volume and MKT of CA in striatum and thalamus that are different to those seen in normal aging. Interestingly, we found different effects and contributions of age and years of consumption in volume, displacement and MKT changes, suggesting that each measure provides different but complementing information about morphological brain changes, and that not all changes are related to the toxicity or the addiction to the drug. Our findings suggest that the use of finer methods and sequences provides complementing information about morphological and microstructural changes in CA, and that brain alterations in CA are related cocaine use and age differently. PMID:28485734
Intracellular diffusion of oxygen and hypoxic sensing: role of mitochondrial respiration.
Takahashi, Eiji; Sato, Michihiko
2010-01-01
In vivo, diffusional O(2) gradients from the capillary blood to the intracellular space determine O(2) availability at the O(2) sensing molecules in the cell. With a novel technique for imaging intracellular O(2) levels using green fluorescent protein (GFP), we examined the possibility that diffusional O(2) concentration gradients might be involved in the cellular hypoxic sensing in cultured Hep3B cells. In the present study, we failed to demonstrate significant gradients of intracellular O(2) when mitochondrial respiration was maximally elevated by an uncoupler of oxidative phosphorylation. Thus, we conclude that intracellular O(2) gradients may be negligible at normal mitochondrial O(2) demand in these cells.
ERIC Educational Resources Information Center
McAlevey, Lynn G.; Stent, Alan F.
2018-01-01
The treatment of kurtosis in textbooks is both sparse and contradictory with applications rarely discussed. To address this, an easily understood definition of kurtosis is introduced and important applications are demonstrated. Two different approaches to teaching kurtosis are presented based on a financial application.
Yan, Xu; Zhou, Minxiong; Ying, Lingfang; Yin, Dazhi; Fan, Mingxia; Yang, Guang; Zhou, Yongdi; Song, Fan; Xu, Dongrong
2013-01-01
Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b-values for parameter estimation; this process is usually time-consuming. Therefore, fewer b-values are preferable to expedite acquisition. In this study, we carefully evaluated various acquisition schemas using different numbers and combinations of b-values. Acquisition schemas that sampled b-values that were distributed to two ends were optimized. Compared to conventional schemas using equally spaced b-values (ESB), optimized schemas require fewer b-values to minimize fitting errors in parameter estimation and may thus significantly reduce scanning time. Following a ranked list of optimized schemas resulted from the evaluation, we recommend the 3b schema based on its estimation accuracy and time efficiency, which needs data from only 3 b-values at 0, around 800 and around 2600 s/mm2, respectively. Analyses using voxel-based analysis (VBA) and region-of-interest (ROI) analysis with human DKI datasets support the use of the optimized 3b (0, 1000, 2500 s/mm2) DKI schema in practical clinical applications. PMID:23735303
Arab, Anas; Wojna-Pelczar, Anna; Khairnar, Amit; Szabó, Nikoletta; Ruda-Kucerova, Jana
2018-05-01
Pathology of neurodegenerative diseases can be correlated with intra-neuronal as well as extracellular changes which lead to neuronal degeneration. The central nervous system (CNS) is a complex structure comprising of many biological barriers. These microstructural barriers might be affected by a variety of pathological processes. Specifically, changes in the brain tissue's microstructure affect the diffusion of water which can be assessed non-invasively by diffusion weighted (DW) magnetic resonance imaging (MRI) techniques. Diffusion tensor imaging (DTI) is a diffusion MRI technique that considers diffusivity as a Gaussian process, i.e. does not account for any diffusion hindrance. However, environment of the brain tissues is characterized by a non-Gaussian diffusion. Therefore, diffusion kurtosis imaging (DKI) was developed as an extension of DTI method in order to quantify the non-Gaussian distribution of water diffusion. This technique represents a promising approach for early diagnosis of neurodegenerative diseases when the neurodegenerative process starts. Hence, the purpose of this article is to summarize the ongoing clinical and preclinical research on Parkinson's, Alzheimer's and Huntington diseases, using DKI and to discuss the role of this technique as an early stage biomarker of neurodegenerative conditions. Copyright © 2018 Elsevier Inc. All rights reserved.
Evaluation of Kurtosis into the product of two normally distributed variables
NASA Astrophysics Data System (ADS)
Oliveira, Amílcar; Oliveira, Teresa; Seijas-Macías, Antonio
2016-06-01
Kurtosis (κ) is any measure of the "peakedness" of a distribution of a real-valued random variable. We study the evolution of the Kurtosis for the product of two normally distributed variables. Product of two normal variables is a very common problem for some areas of study, like, physics, economics, psychology, … Normal variables have a constant value for kurtosis (κ = 3), independently of the value of the two parameters: mean and variance. In fact, the excess kurtosis is defined as κ- 3 and the Normal Distribution Kurtosis is zero. The product of two normally distributed variables is a function of the parameters of the two variables and the correlation between then, and the range for kurtosis is in [0, 6] for independent variables and in [0, 12] when correlation between then is allowed.
Kurtosis as Peakedness, 1905 - 2014. R.I.P.
Westfall, Peter H
The incorrect notion that kurtosis somehow measures "peakedness" (flatness, pointiness or modality) of a distribution is remarkably persistent, despite attempts by statisticians to set the record straight. This article puts the notion to rest once and for all. Kurtosis tells you virtually nothing about the shape of the peak - its only unambiguous interpretation is in terms of tail extremity; i.e., either existing outliers (for the sample kurtosis) or propensity to produce outliers (for the kurtosis of a probability distribution). To clarify this point, relevant literature is reviewed, counterexample distributions are given, and it is shown that the proportion of the kurtosis that is determined by the central μ ± σ range is usually quite small.
Chen, Xianglong; Zhang, Bingzhi; Feng, Fuzhou; Jiang, Pengcheng
2017-01-01
The kurtosis-based indexes are usually used to identify the optimal resonant frequency band. However, kurtosis can only describe the strength of transient impulses, which cannot differentiate impulse noises and repetitive transient impulses cyclically generated in bearing vibration signals. As a result, it may lead to inaccurate results in identifying resonant frequency bands, in demodulating fault features and hence in fault diagnosis. In view of those drawbacks, this manuscript redefines the correlated kurtosis based on kurtosis and auto-correlative function, puts forward an improved correlated kurtosis based on squared envelope spectrum of bearing vibration signals. Meanwhile, this manuscript proposes an optimal resonant band demodulation method, which can adaptively determine the optimal resonant frequency band and accurately demodulate transient fault features of rolling bearings, by combining the complex Morlet wavelet filter and the Particle Swarm Optimization algorithm. Analysis of both simulation data and experimental data reveal that the improved correlated kurtosis can effectively remedy the drawbacks of kurtosis-based indexes and the proposed optimal resonant band demodulation is more accurate in identifying the optimal central frequencies and bandwidth of resonant bands. Improved fault diagnosis results in experiment verified the validity and advantage of the proposed method over the traditional kurtosis-based indexes. PMID:28208820
Hall, Michael B H; Nissen, Ida A; van Straaten, Elisabeth C W; Furlong, Paul L; Witton, Caroline; Foley, Elaine; Seri, Stefano; Hillebrand, Arjan
2018-06-01
Kurtosis beamforming is a useful technique for analysing magnetoencephalograpy (MEG) data containing epileptic spikes. However, the implementation varies and few studies measure concordance with subsequently resected areas. We evaluated kurtosis beamforming as a means of localizing spikes in drug-resistant epilepsy patients. We retrospectively applied kurtosis beamforming to MEG recordings of 22 epilepsy patients that had previously been analysed using equivalent current dipole (ECD) fitting. Virtual electrodes were placed in the kurtosis volumetric peaks and visually inspected to select a candidate source. The candidate sources were compared to the ECD localizations and resection areas. The kurtosis beamformer produced interpretable localizations in 18/22 patients, of which the candidate source coincided with the resection lobe in 9/13 seizure-free patients and in 3/5 patients with persistent seizures. The sublobar accuracy of the kurtosis beamformer with respect to the resection zone was higher than ECD (56% and 50%, respectively), however, ECD resulted in a higher lobar accuracy (75%, 67%). Kurtosis beamforming may provide additional value when spikes are not clearly discernible on the sensors and support ECD localizations when dipoles are scattered. Kurtosis beamforming should be integrated with existing clinical protocols to assist in localizing the epileptogenic zone. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Skewness and kurtosis analysis for non-Gaussian distributions
NASA Astrophysics Data System (ADS)
Celikoglu, Ahmet; Tirnakli, Ugur
2018-06-01
In this paper we address a number of pitfalls regarding the use of kurtosis as a measure of deviations from the Gaussian. We treat kurtosis in both its standard definition and that which arises in q-statistics, namely q-kurtosis. We have recently shown that the relation proposed by Cristelli et al. (2012) between skewness and kurtosis can only be verified for relatively small data sets, independently of the type of statistics chosen; however it fails for sufficiently large data sets, if the fourth moment of the distribution is finite. For infinite fourth moments, kurtosis is not defined as the size of the data set tends to infinity. For distributions with finite fourth moments, the size, N, of the data set for which the standard kurtosis saturates to a fixed value, depends on the deviation of the original distribution from the Gaussian. Nevertheless, using kurtosis as a criterion for deciding which distribution deviates further from the Gaussian can be misleading for small data sets, even for finite fourth moment distributions. Going over to q-statistics, we find that although the value of q-kurtosis is finite in the range of 0 < q < 3, this quantity is not useful for comparing different non-Gaussian distributed data sets, unless the appropriate q value, which truly characterizes the data set of interest, is chosen. Finally, we propose a method to determine the correct q value and thereby to compute the q-kurtosis of q-Gaussian distributed data sets.
Kurtosis as Peakedness, 1905 – 2014. R.I.P.
WESTFALL, Peter H.
2014-01-01
Summary The incorrect notion that kurtosis somehow measures “peakedness” (flatness, pointiness or modality) of a distribution is remarkably persistent, despite attempts by statisticians to set the record straight. This article puts the notion to rest once and for all. Kurtosis tells you virtually nothing about the shape of the peak - its only unambiguous interpretation is in terms of tail extremity; i.e., either existing outliers (for the sample kurtosis) or propensity to produce outliers (for the kurtosis of a probability distribution). To clarify this point, relevant literature is reviewed, counterexample distributions are given, and it is shown that the proportion of the kurtosis that is determined by the central μ ± σ range is usually quite small. PMID:25678714
NASA Technical Reports Server (NTRS)
Wittenberger, J. D.; Behrendt, D. R.
1973-01-01
Diffusional creep in a polycrystalline alloy containing second-phase particles can disrupt the particle morphology. For alloys which depend on the particle distribution for strength, changes in the particle morphology can affect the mechanical properties. Recent observations of diffusional creep in alloys containing soluble particles (gamma-prime strengthened Ni base alloys) and inert particles have been reexamined in light of the basic mechanisms of diffusional creep, and a generalized model of this effect is proposed. The model indicates that diffusional creep will generally result in particle-free regions in the vicinity of grain boundaries serving as net vacancy sources. The factors which control the changes in second-phase morphology have been identified, and methods of reducing the effects of diffusional creep are suggested.
Suo, Shi-Teng; Chen, Xiao-Xi; Fan, Yu; Wu, Lian-Ming; Yao, Qiu-Ying; Cao, Meng-Qiu; Liu, Qiang; Xu, Jian-Rong
2014-08-01
To investigate the potential value of histogram analysis of apparent diffusion coefficient (ADC) obtained at standard (700 s/mm(2)) and high (1500 s/mm(2)) b values on a 3.0-T scanner in the differentiation of bladder cancer from benign lesions and in assessing bladder tumors of different pathologic T stages and to evaluate the diagnostic performance of ADC-based histogram parameters. In all, 52 patients with bladder lesions, including benign lesions (n = 7) and malignant tumors (n = 45; T1 stage or less, 23; T2 stage, 7; T3 stage, 8; and T4 stage, 7), were retrospectively evaluated. Magnetic resonance examination at 3.0 T and diffusion-weighted imaging were performed. ADC maps were obtained at two b values (b = 700 and 1500 s/mm(2); ie, ADC-700 and ADC-1500). Parameters of histogram analysis included mean, kurtosis, skewness, and entropy. The correlations between these parameters and pathologic results were revealed. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic value of histogram parameters. Significant differences were found in mean ADC-700, mean ADC-1500, skewness ADC-1500, and kurtosis ADC-1500 between bladder cancer and benign lesions (P = .002-.032). There were also significant differences in mean ADC-700, mean ADC-1500, and kurtosis ADC-1500 among bladder tumors of different pathologic T stages (P = .000-.046). No significant differences were observed in other parameters. Mean ADC-1500 and kurtosis ADC-1500 were significantly correlated with T stage, respectively (ρ = -0.614, P < .001; ρ = 0.374, P = .011). ROC analysis showed that the combination of mean ADC-1500 and kurtosis ADC-1500 has the maximal area under the ROC curve (AUC, 0.894; P < .001) in the differentiation of benign lesions and malignant tumors, with a sensitivity of 77.78% and specificity of 100%. AUCs for differentiating low- and high-stage tumors were 0.840 for mean ADC-1500 (P < .001) and 0.696 for kurtosis ADC-1500 (P = .015). Histogram analysis of ADC-1500 at 3.0 T can be useful in evaluation of bladder lesions. A combination of mean ADC-1500 and kurtosis ADC-1500 may be more beneficial in the differentiation of benign and malignant lesions. Mean ADC-1500 was the most promising parameter for differentiating low- from high-stage bladder cancer. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.
Kartalis, Nikolaos; Manikis, Georgios C; Loizou, Louiza; Albiin, Nils; Zöllner, Frank G; Del Chiaro, Marco; Marias, Kostas; Papanikolaou, Nikolaos
2016-01-01
To compare two Gaussian diffusion-weighted MRI (DWI) models including mono-exponential and bi-exponential, with the non-Gaussian kurtosis model in patients with pancreatic ductal adenocarcinoma. After written informed consent, 15 consecutive patients with pancreatic ductal adenocarcinoma underwent free-breathing DWI (1.5T, b-values: 0, 50, 150, 200, 300, 600 and 1000 s/mm 2 ). Mean values of DWI-derived metrics ADC, D, D*, f, K and D K were calculated from multiple regions of interest in all tumours and non-tumorous parenchyma and compared. Area under the curve was determined for all metrics. Mean ADC and D K showed significant differences between tumours and non-tumorous parenchyma (both P < 0.001). Area under the curve for ADC, D, D*, f, K, and D K were 0.77, 0.52, 0.53, 0.62, 0.42, and 0.84, respectively. ADC and D K could differentiate tumours from non-tumorous parenchyma with the latter showing a higher diagnostic accuracy. Correction for kurtosis effects has the potential to increase the diagnostic accuracy of DWI in patients with pancreatic ductal adenocarcinoma.
Zhang, Gu-Mu-Yang; Shi, Bing; Sun, Hao; Jin, Zheng-Yu; Xue, Hua-Dan
2017-09-01
To investigate the feasibility of using CT texture analysis (CTTA) to differentiate pheochromocytoma from lipid-poor adrenocortical adenoma (lp-ACA). Ninety-eight pheochromocytomas and 66 lp-ACAs were included in this retrospective study. CTTA was performed on unenhanced and enhanced images. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different for the objective. Diagnostic accuracies were evaluated using the cutoff values of texture parameters with the highest AUCs. Compared to lp-ACAs, pheochromocytomas had significantly higher mean gray-level intensity (Mean), entropy, and mean of positive pixels (MPP), but lower skewness and kurtosis on unenhanced images (P < 0.001). On enhanced images, these texture-quantifiers followed a similar trend where Mean, entropy, and MPP were higher, but skewness and kurtosis were lower in pheochromocytomas. Standard deviation (SD) was also significantly higher in pheochromocytomas on enhanced images. Mean and MPP quantified from no filtration on unenhanced CT images yielded the highest AUC of 0.86 ± 0.03 (95% CI 0.81-0.91) at a cutoff value of 34.0 for Mean and MPP, respectively (sensitivity = 79.6%, specificity = 83.3%, accuracy = 81.1%). It was feasible to use CTTA to differentiate pheochromocytoma from lp-ACA.
Zhang, Yujuan; Chen, Jun; Liu, Song; Shi, Hua; Guan, Wenxian; Ji, Changfeng; Guo, Tingting; Zheng, Huanhuan; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng; Liu, Tian
2017-02-01
To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer. Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm 2 ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC). There were significant differences in the 5 th , 10 th , 25 th , and 50 th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P < 0.05). There were correlations between the degrees of differentiation and histogram parameters, including the 10 th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675. Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer. 4 J. Magn. Reson. Imaging 2017;45:440-449. © 2016 International Society for Magnetic Resonance in Medicine.
Estimation of spectral kurtosis
NASA Astrophysics Data System (ADS)
Sutawanir
2017-03-01
Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to visualize the pattern of each fault. Keywords: frequency domain Fourier transform, spectral kurtosis, bearing fault
Diffusion-weighted imaging and demyelinating diseases: new aspects of an old advanced sequence.
Rueda-Lopes, Fernanda C; Hygino da Cruz, Luiz C; Doring, Thomas M; Gasparetto, Emerson L
2014-01-01
The purpose of this article is to discuss classic applications in diffusion-weighted imaging (DWI) in demyelinating disease and progression of DWI in the near future. DWI is an advanced technique used in the follow-up of demyelinating disease patients, focusing on the diagnosis of a new lesion before contrast enhancement. With technical advances, diffusion-tensor imaging; new postprocessing techniques, such as tract-based spatial statistics; new ways of calculating diffusion, such as kurtosis; and new applications for DWI and its spectrum are about to arise.
NASA Technical Reports Server (NTRS)
Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark
2016-01-01
In the field of microwave radiometry, Radio Frequency Interference (RFI) consistently degrades the value of scientific results. Through the use of digital receivers and signal processing, the effects of RFI on scientific measurements can be reduced depending on certain circumstances. As technology allows us to implement wider band digital receivers for radiometry, the problem of RFI mitigation changes. Our work focuses on finding a detector that outperforms real kurtosis in wide band scenarios. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The performance of both complex and real signal kurtosis is evaluated for continuous wave, pulsed continuous wave, and wide band quadrature phase shift keying (QPSK) modulations. The use of complex signal kurtosis increased the detectability of interference.
The Nature of Turbulence in the LITTLE THINGS Dwarf Irregular Galaxies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maier, Erin; Chien, Li-Hsin; Hollyday, Gigja
We present probability density functions and higher order (skewness and kurtosis) analyses of the galaxy-wide and spatially resolved distributions of H i column density in the LITTLE THINGS sample of dwarf irregular galaxies. This analysis follows that of Burkhart et al. for the Small Magellanic Cloud (SMC). About 60% of our sample have galaxy-wide values of kurtosis that are similar to that found for the SMC, with a range up to much higher values, and kurtosis increases with integrated star formation rate. Kurtosis and skewness were calculated for radial annuli and for a grid of 32 pixel × 32 pixel kernels acrossmore » each galaxy. For most galaxies, kurtosis correlates with skewness. For about half of the galaxies, there is a trend of increasing kurtosis with radius. The range of kurtosis and skewness values is modeled by small variations in the Mach number close to the sonic limit and by conversion of H i to molecules at high column density. The maximum H i column densities decrease with increasing radius in a way that suggests molecules are forming in the weak-field limit, where H{sub 2} formation balances photodissociation in optically thin gas at the edges of clouds.« less
Meyer, Hans Jonas; Emmer, Alexander; Kornhuber, Malte; Surov, Alexey
2018-05-01
Diffusion-weighted imaging (DWI) has the potential of being able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize tissues on MRI. The aim of this study was to correlate histogram parameters derived from apparent diffusion coefficient (ADC) maps with serological parameters in myositis. 16 patients with autoimmune myositis were included in this retrospective study. DWI was obtained on a 1.5 T scanner by using the b-values of 0 and 1000 s mm - 2 . Histogram analysis was performed as a whole muscle measurement by using a custom-made Matlab-based application. The following ADC histogram parameters were estimated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, and the following percentiles ADCp10, ADCp25, ADCp75, ADCp90, as well histogram parameters kurtosis, skewness, and entropy. In all patients, the blood sample was acquired within 3 days to the MRI. The following serological parameters were estimated: alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, C-reactive protein (CRP) and myoglobin. All patients were screened for Jo1-autobodies. Kurtosis correlated inversely with CRP (p = -0.55 and 0.03). Furthermore, ADCp10 and ADCp90 values tended to correlate with creatine kinase (p = -0.43, 0.11, and p = -0.42, = 0.12 respectively). In addition, ADCmean, p10, p25, median, mode, and entropy were different between Jo1-positive and Jo1-negative patients. ADC histogram parameters are sensitive for detection of muscle alterations in myositis patients. Advances in knowledge: This study identified that kurtosis derived from ADC maps is associated with CRP in myositis patients. Furthermore, several ADC histogram parameters are statistically different between Jo1-positive and Jo1-negative patients.
Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?
De Robertis, Riccardo; Maris, Bogdan; Cardobi, Nicolò; Tinazzi Martini, Paolo; Gobbo, Stefano; Capelli, Paola; Ortolani, Silvia; Cingarlini, Sara; Paiella, Salvatore; Landoni, Luca; Butturini, Giovanni; Regi, Paolo; Scarpa, Aldo; Tortora, Giampaolo; D'Onofrio, Mirko
2018-06-01
To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness. Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter. ADC entropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADC kurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05). Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADC entropy and ADC kurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.
Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka; Tonami, Hisao
2017-01-01
Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.
Hempel, Johann-Martin; Schittenhelm, Jens; Brendle, Cornelia; Bender, Benjamin; Bier, Georg; Skardelly, Marco; Tabatabai, Ghazaleh; Castaneda Vega, Salvador; Ernemann, Ulrike; Klose, Uwe
2017-10-01
To assess the diagnostic performance of histogram analysis of diffusion kurtosis imaging (DKI) maps for in vivo assessment of the 2016 World Health Organization Classification of Tumors of the Central Nervous System (2016 CNS WHO) integrated glioma grades. Seventy-seven patients with histopathologically-confirmed glioma who provided written informed consent were retrospectively assessed between 01/2014 and 03/2017 from a prospective trial approved by the local institutional review board. Ten histogram parameters of mean kurtosis (MK) and mean diffusivity (MD) metrics from DKI were independently assessed by two blinded physicians from a volume of interest around the entire solid tumor. One-way ANOVA was used to compare MK and MD histogram parameter values between 2016 CNS WHO-based tumor grades. Receiver operating characteristic analysis was performed on MK and MD histogram parameters for significant results. The 25th, 50th, 75th, and 90th percentiles of MK and average MK showed significant differences between IDH1/2 wild-type gliomas, IDH1/2 mutated gliomas, and oligodendrogliomas with chromosome 1p/19q loss of heterozygosity and IDH1/2 mutation (p<0.001). The 50th, 75th, and 90th percentiles showed a slightly higher diagnostic performance (area under the curve (AUC) range; 0.868-0.991) than average MK (AUC range; 0.855-0.988) in classifying glioma according to the integrated approach of 2016 CNS WHO. Histogram analysis of DKI can stratify gliomas according to the integrated approach of 2016 CNS WHO. The 50th (median), 75th , and the 90th percentiles showed the highest diagnostic performance. However, the average MK is also robust and feasible in routine clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.
Fisher information and Cramér-Rao lower bound for experimental design in parallel imaging.
Bouhrara, Mustapha; Spencer, Richard G
2018-06-01
The Cramér-Rao lower bound (CRLB) is widely used in the design of magnetic resonance (MR) experiments for parameter estimation. Previous work has considered only Gaussian or Rician noise distributions in this calculation. However, the noise distribution for multi-coil acquisitions, such as in parallel imaging, obeys the noncentral χ-distribution under many circumstances. The purpose of this paper is to present the CRLB calculation for parameter estimation from multi-coil acquisitions. We perform explicit calculations of Fisher matrix elements and the associated CRLB for noise distributions following the noncentral χ-distribution. The special case of diffusion kurtosis is examined as an important example. For comparison with analytic results, Monte Carlo (MC) simulations were conducted to evaluate experimental minimum standard deviations (SDs) in the estimation of diffusion kurtosis model parameters. Results were obtained for a range of signal-to-noise ratios (SNRs), and for both the conventional case of Gaussian noise distribution and noncentral χ-distribution with different numbers of coils, m. At low-to-moderate SNR, the noncentral χ-distribution deviates substantially from the Gaussian distribution. Our results indicate that this departure is more pronounced for larger values of m. As expected, the minimum SDs (i.e., CRLB) in derived diffusion kurtosis model parameters assuming a noncentral χ-distribution provided a closer match to the MC simulations as compared to the Gaussian results. Estimates of minimum variance for parameter estimation and experimental design provided by the CRLB must account for the noncentral χ-distribution of noise in multi-coil acquisitions, especially in the low-to-moderate SNR regime. Magn Reson Med 79:3249-3255, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Tummala, Sudhakar; Palomares, Jose; Kang, Daniel W; Park, Bumhee; Woo, Mary A; Harper, Ronald M; Kumar, Rajesh
2016-01-01
Obstructive sleep apnea (OSA) patients show brain structural injury and functional deficits in autonomic, affective, and cognitive regulatory sites, as revealed by mean diffusivity (MD) and other imaging procedures. The time course and nature of gray and white matter injury can be revealed in more detail with mean kurtosis (MK) procedures, which can differentiate acute from chronic injury, and better show extent of damage over MD procedures. Our objective was to examine global and regional MK changes in newly diagnosed OSA, relative to control subjects. Two diffusion kurtosis image series were collected from 22 recently-diagnosed, treatment-naïve OSA and 26 control subjects using a 3.0-Tesla MRI scanner. MK maps were generated, normalized to a common space, smoothed, and compared voxel-by-voxel between groups using analysis of covariance (covariates; age, sex). No age or sex differences appeared, but body mass index, sleep, neuropsychologic, and cognitive scores significantly differed between groups. MK values were significantly increased globally in OSA over controls, and in multiple localized sites, including the basal forebrain, extending to the hypothalamus, hippocampus, thalamus, insular cortices, basal ganglia, limbic regions, cerebellar areas, parietal cortices, ventral temporal lobe, ventrolateral medulla, and midline pons. Multiple sites, including the insular cortices, ventrolateral medulla, and midline pons showed more injury over previously identified damage with MD procedures, with damage often lateralized. Global mean kurtosis values are significantly increased in obstructive sleep apnea (OSA), suggesting acute tissue injury, and these changes are principally localized in critical sites mediating deficient functions in the condition. The mechanisms for injury likely include altered perfusion and hypoxemia-induced processes, leading to acute tissue changes in recently diagnosed OSA. © 2016 Associated Professional Sleep Societies, LLC.
NASA Technical Reports Server (NTRS)
Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark
2016-01-01
Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves. The complex kurtosis algorithm has the potential to reduce data rate due to onboard processing in addition to improving RFI detection performance.
NASA Astrophysics Data System (ADS)
Wang, Dong
2018-05-01
Thanks to the great efforts made by Antoni (2006), spectral kurtosis has been recognized as a milestone for characterizing non-stationary signals, especially bearing fault signals. The main idea of spectral kurtosis is to use the fourth standardized moment, namely kurtosis, as a function of spectral frequency so as to indicate how repetitive transients caused by a bearing defect vary with frequency. Moreover, spectral kurtosis is defined based on an analytic bearing fault signal constructed from either a complex filter or Hilbert transform. On the other hand, another attractive work was reported by Borghesani et al. (2014) to mathematically reveal the relationship between the kurtosis of an analytical bearing fault signal and the square of the squared envelope spectrum of the analytical bearing fault signal for explaining spectral correlation for quantification of bearing fault signals. More interestingly, it was discovered that the sum of peaks at cyclic frequencies in the square of the squared envelope spectrum corresponds to the raw 4th order moment. Inspired by the aforementioned works, in this paper, we mathematically show that: (1) spectral kurtosis can be decomposed into squared envelope and squared L2/L1 norm so that spectral kurtosis can be explained as spectral squared L2/L1 norm; (2) spectral L2/L1 norm is formally defined for characterizing bearing fault signals and its two geometrical explanations are made; (3) spectral L2/L1 norm is proportional to the square root of the sum of peaks at cyclic frequencies in the square of the squared envelope spectrum; (4) some extensions of spectral L2/L1 norm for characterizing bearing fault signals are pointed out.
NASA Technical Reports Server (NTRS)
Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark
2016-01-01
Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves.
Diffusional aspects of the high-temperature oxidation of protective coatings
NASA Technical Reports Server (NTRS)
Nesbitt, J. A.
1989-01-01
The role of diffusional transport associated with the high-temperature oxidation of coatings is examined, with special attention given to the low-pressure plasma spraying MCrAl-type overlay coatings and similar Ni-base alloys which form protective AlO3 scales. The use of diffusional analysis to predict the minimum solute concentration necessary to form and grow a solute oxide scale is illustrated. Modeling procedures designed to simulate the diffusional transport in coatings and substrates are presented to show their use in understanding coating degradation, predicting the protective life of a coating, and evaluating various coating parameters to guide coating development.
A closed form of a kurtosis parameter of a hypergeometric-Gaussian type-II beam
NASA Astrophysics Data System (ADS)
F, Khannous; A, A. A. Ebrahim; A, Belafhal
2016-04-01
Based on the irradiance moment definition and the analytical expression of waveform propagation for hypergeometric-Gaussian type-II beams passing through an ABCD system, the kurtosis parameter is derived analytically and illustrated numerically. The kurtosis parameters of the Gaussian beam, modified Bessel modulated Gaussian beam with quadrature radial and elegant Laguerre-Gaussian beams are obtained by treating them as special cases of the present treatment. The obtained results show that the kurtosis parameter depends on the change of the beam order m and the hollowness parameter p, such as its decrease with increasing m and increase with increasing p.
Zukotynski, Katherine A; Vajapeyam, Sridhar; Fahey, Frederic H; Kocak, Mehmet; Brown, Douglas; Ricci, Kelsey I; Onar-Thomas, Arzu; Fouladi, Maryam; Poussaint, Tina Young
2017-08-01
The purpose of this study was to describe baseline 18 F-FDG PET voxel characteristics in pediatric diffuse intrinsic pontine glioma (DIPG) and to correlate these metrics with baseline MRI apparent diffusion coefficient (ADC) histogram metrics, progression-free survival (PFS), and overall survival. Methods: Baseline brain 18 F-FDG PET and MRI scans were obtained in 33 children from Pediatric Brain Tumor Consortium clinical DIPG trials. 18 F-FDG PET images, postgadolinium MR images, and ADC MR images were registered to baseline fluid attenuation inversion recovery MR images. Three-dimensional regions of interest on fluid attenuation inversion recovery MR images and postgadolinium MR images and 18 F-FDG PET and MR ADC histograms were generated. Metrics evaluated included peak number, skewness, and kurtosis. Correlation between PET and MR ADC histogram metrics was evaluated. PET pixel values within the region of interest for each tumor were plotted against MR ADC values. The association of these imaging markers with survival was described. Results: PET histograms were almost always unimodal (94%, vs. 6% bimodal). None of the PET histogram parameters (skewness or kurtosis) had a significant association with PFS, although a higher PET postgadolinium skewness tended toward a less favorable PFS (hazard ratio, 3.48; 95% confidence interval [CI], 0.75-16.28 [ P = 0.11]). There was a significant association between higher MR ADC postgadolinium skewness and shorter PFS (hazard ratio, 2.56; 95% CI, 1.11-5.91 [ P = 0.028]), and there was the suggestion that this also led to shorter overall survival (hazard ratio, 2.18; 95% CI, 0.95-5.04 [ P = 0.067]). Higher MR ADC postgadolinium kurtosis tended toward shorter PFS (hazard ratio, 1.30; 95% CI, 0.98-1.74 [ P = 0.073]). PET and MR ADC pixel values were negatively correlated using the Pearson correlation coefficient. Further, the level of PET and MR ADC correlation was significantly positively associated with PFS; tumors with higher values of ADC-PET correlation had more favorable PFS (hazard ratio, 0.17; 95% CI, 0.03-0.89 [ P = 0.036]), suggesting that a higher level of negative ADC-PET correlation leads to less favorable PFS. A more significant negative correlation may indicate higher-grade elements within the tumor leading to poorer outcomes. Conclusion: 18 F-FDG PET and MR ADC histogram metrics in pediatric DIPG demonstrate different characteristics with often a negative correlation between PET and MR ADC pixel values. A higher negative correlation is associated with a worse PFS, which may indicate higher-grade elements within the tumor. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.
1997-06-01
4.53 110.00 Maximum 4.33 Symmetry- Veta I 5.00 Symmetry- Veta I 1.20 Kurtosis- Veta II 6.70 Kurtosis- Veta II 1.40 Coeff. of Variation 33.2% Coeff of...Mean) 0.64 0.62 SE(SD) 0.02 0.62 SE(SD) 0.02 277.00 Minimum 10.91 264.00 Minimum 10.39 408.00 Maximum 16.06 379.00 Maximum 14.92 Symmetry- Veta I...0.60 Symmetry- Veta I 1.3{) Kurtosis- Veta II -0.40 Kurtosis- Veta II 0.30 Coeff. ofV ariation 4.9% Coeff. of Variation 5.2% Sample Size 4447 Sarn_ple
Liang, Zhiqiang; Wei, Jianming; Zhao, Junyu; Liu, Haitao; Li, Baoqing; Shen, Jie; Zheng, Chunlei
2008-01-01
This paper presents a new algorithm making use of kurtosis, which is a statistical parameter, to distinguish the seismic signal generated by a person's footsteps from other signals. It is adaptive to any environment and needs no machine study or training. As persons or other targets moving on the ground generate continuous signals in the form of seismic waves, we can separate different targets based on the seismic waves they generate. The parameter of kurtosis is sensitive to impulsive signals, so it's much more sensitive to the signal generated by person footsteps than other signals generated by vehicles, winds, noise, etc. The parameter of kurtosis is usually employed in the financial analysis, but rarely used in other fields. In this paper, we make use of kurtosis to distinguish person from other targets based on its different sensitivity to different signals. Simulation and application results show that this algorithm is very effective in distinguishing person from other targets. PMID:27873804
Cain, Meghan K; Zhang, Zhiyong; Yuan, Ke-Hai
2017-10-01
Nonnormality of univariate data has been extensively examined previously (Blanca et al., Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(2), 78-84, 2013; Miceeri, Psychological Bulletin, 105(1), 156, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of nonnormality, this study examined 1,567 univariate distriubtions and 254 multivariate distributions collected from authors of articles published in Psychological Science and the American Education Research Journal. We found that 74 % of univariate distributions and 68 % multivariate distributions deviated from normal distributions. In a simulation study using typical values of skewness and kurtosis that we collected, we found that the resulting type I error rates were 17 % in a t-test and 30 % in a factor analysis under some conditions. Hence, we argue that it is time to routinely report skewness and kurtosis along with other summary statistics such as means and variances. To facilitate future report of skewness and kurtosis, we provide a tutorial on how to compute univariate and multivariate skewness and kurtosis by SAS, SPSS, R and a newly developed Web application.
Enhancing seismic P phase arrival picking based on wavelet denoising and kurtosis picker
NASA Astrophysics Data System (ADS)
Shang, Xueyi; Li, Xibing; Weng, Lei
2018-01-01
P phase arrival picking of weak signals is still challenging in seismology. A wavelet denoising is proposed to enhance seismic P phase arrival picking, and the kurtosis picker is applied on the wavelet-denoised signal to identify P phase arrival. It has been called the WD-K picker. The WD-K picker, which is different from those traditional wavelet-based pickers on the basis of a single wavelet component or certain main wavelet components, takes full advantage of the reconstruction of main detail wavelet components and the approximate wavelet component. The proposed WD-K picker considers more wavelet components and presents a better P phase arrival feature. The WD-K picker has been evaluated on 500 micro-seismic signals recorded in the Chinese Yongshaba mine. The comparison between the WD-K pickings and manual pickings shows the good picking accuracy of the WD-K picker. Furthermore, the WD-K picking performance has been compared with the main detail wavelet component combining-based kurtosis (WDC-K) picker, the single wavelet component-based kurtosis (SW-K) picker, and certain main wavelet component-based maximum kurtosis (MMW-K) picker. The comparison has demonstrated that the WD-K picker has better picking accuracy than the other three-wavelet and kurtosis-based pickers, thus showing the enhanced ability of wavelet denoising.
Diffusion kurtosis imaging for differentiating between the benign and malignant sinonasal lesions.
Jiang, Jing Xuan; Tang, Zuo Hua; Zhong, Yu Feng; Qiang, Jin Wei
2017-05-01
The study aimed to evaluate diffusion kurtosis imaging (DKI) in the differentiation between benign and malignant sinonasal lesions, and to compare the diagnostic performance of DKI with diffusion weighted imaging (DWI). Eight-one patients with solid sinonasal lesions confirmed by surgery and pathology (46 malignant and 35 benign) underwent conventional MRI, DWI, and DKI. DKI was performed employing a 13 extended b-value ranging from 0 to 2500 s/mm 2 . Apparent diffusion coefficient (ADC) from DWI, kurtosis (K), and diffusion coefficient (D) from DKI were measured and compared between two groups. ADC and D values were significantly lower in the malignant sinonasal lesions than in the benign sinonasal lesions (1.11 ± 0.41 versus 1.58 ± 0.50 × 10 -3 mm 2 /s and 1.45 ± 0.36 versus 2.03 ± 0.49 × 10 -3 mm 2 /s, respectively, both P < 0001). K value was significantly higher in the malignant lesions than in the benign lesions (0.91 ± 0.23 versus 0.57 ± 0.24, P < 0001). The receiver operating characteristic curve analyses yielded a cutoff ADC value of 1.27 × 10 -3 mm 2 /s for differentiating between benign and malignant lesions, with a sensitivity of 69.6%, a specificity of 77.1% and an accuracy of 74.0%; a cutoff D value of 1.75 × 10 -3 mm 2 /s, with a sensitivity of 82.6%, a specificity of 77.1% and an accuracy of 80.2%; a cutoff K value of 0.63 with a sensitivity of 95.7%, a specificity of 77.1% and an accuracy of 87.7%. The area under the curve of K value was significantly larger than that of ADC value (0.875 versus 0.762; P < 0.05). K value of DKI demonstrates significantly higher accuracy compared with ADC value for the differentiation between benign and malignant sinonasal lesions. DKI may be a noninvasive method to evaluate the sinonasal lesions. 1 J. MAGN. RESON. IMAGING 2017;45:1446-1454. © 2016 International Society for Magnetic Resonance in Medicine.
Stochastic HKMDHE: A multi-objective contrast enhancement algorithm
NASA Astrophysics Data System (ADS)
Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Maity, Srideep; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.
2018-02-01
This contribution proposes a novel extension of the existing `Hyper Kurtosis based Modified Duo-Histogram Equalization' (HKMDHE) algorithm, for multi-objective contrast enhancement of biomedical images. A novel modified objective function has been formulated by joint optimization of the individual histogram equalization objectives. The optimal adequacy of the proposed methodology with respect to image quality metrics such as brightness preserving abilities, peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM) and universal image quality metric has been experimentally validated. The performance analysis of the proposed Stochastic HKMDHE with existing histogram equalization methodologies like Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) has been given for comparative evaluation.
Jimenez-Vergara, Andrea C; Lewis, John; Hahn, Mariah S; Munoz-Pinto, Dany J
2018-04-01
Accurate characterization of hydrogel diffusional properties is of substantial importance for a range of biotechnological applications. The diffusional capacity of hydrogels has commonly been estimated using the average molecular weight between crosslinks (M c ), which is calculated based on the equilibrium degree of swelling. However, the existing correlation linking M c and equilibrium swelling fails to accurately reflect the diffusional properties of highly crosslinked hydrogel networks. Also, as demonstrated herein, the current model fails to accurately predict the diffusional properties of hydrogels when polymer concentration and molecular weight are varied simultaneously. To address these limitations, we evaluated the diffusional properties of 48 distinct hydrogel formulations using two different photoinitiator systems, employing molecular size exclusion as an alternative methodology to calculate average hydrogel mesh size. The resulting data were then utilized to develop a revised correlation between M c and hydrogel equilibrium swelling that substantially reduces the limitations associated with the current correlation. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1339-1348, 2018. © 2017 Wiley Periodicals, Inc.
Segmentation and analysis of mouse pituitary cells with graphic user interface (GUI)
NASA Astrophysics Data System (ADS)
González, Erika; Medina, Lucía.; Hautefeuille, Mathieu; Fiordelisio, Tatiana
2018-02-01
In this work we present a method to perform pituitary cell segmentation in image stacks acquired by fluorescence microscopy from pituitary slice preparations. Although there exist many procedures developed to achieve cell segmentation tasks, they are generally based on the edge detection and require high resolution images. However in the biological preparations that we worked on, the cells are not well defined as experts identify their intracellular calcium activity due to fluorescence intensity changes in different regions over time. This intensity changes were associated with time series over regions, and because they present a particular behavior they were used into a classification procedure in order to perform cell segmentation. Two logistic regression classifiers were implemented for the time series classification task using as features the area under the curve and skewness in the first classifier and skewness and kurtosis in the second classifier. Once we have found both decision boundaries in two different feature spaces by training using 120 time series, the decision boundaries were tested over 12 image stacks through a python graphical user interface (GUI), generating binary images where white pixels correspond to cells and the black ones to background. Results show that area-skewness classifier reduces the time an expert dedicates in locating cells by up to 75% in some stacks versus a 92% for the kurtosis-skewness classifier, this evaluated on the number of regions the method found. Due to the promising results, we expect that this method will be improved adding more relevant features to the classifier.
NASA Technical Reports Server (NTRS)
Kihm, Frederic; Rizzi, Stephen A.; Ferguson, Neil S.; Halfpenny, Andrew
2013-01-01
High cycle fatigue of metals typically occurs through long term exposure to time varying loads which, although modest in amplitude, give rise to microscopic cracks that can ultimately propagate to failure. The fatigue life of a component is primarily dependent on the stress amplitude response at critical failure locations. For most vibration tests, it is common to assume a Gaussian distribution of both the input acceleration and stress response. In real life, however, it is common to experience non-Gaussian acceleration input, and this can cause the response to be non-Gaussian. Examples of non-Gaussian loads include road irregularities such as potholes in the automotive world or turbulent boundary layer pressure fluctuations for the aerospace sector or more generally wind, wave or high amplitude acoustic loads. The paper first reviews some of the methods used to generate non-Gaussian excitation signals with a given power spectral density and kurtosis. The kurtosis of the response is examined once the signal is passed through a linear time invariant system. Finally an algorithm is presented that determines the output kurtosis based upon the input kurtosis, the input power spectral density and the frequency response function of the system. The algorithm is validated using numerical simulations. Direct applications of these results include improved fatigue life estimations and a method to accelerate shaker tests by generating high kurtosis, non-Gaussian drive signals.
Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka
2017-01-01
Purpose Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. Materials and methods We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. Results The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. Conclusions ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion. PMID:28207858
Kurtosis, skewness, and non-Gaussian cosmological density perturbations
NASA Technical Reports Server (NTRS)
Luo, Xiaochun; Schramm, David N.
1993-01-01
Cosmological topological defects as well as some nonstandard inflation models can give rise to non-Gaussian density perturbations. Skewness and kurtosis are the third and fourth moments that measure the deviation of a distribution from a Gaussian. Measurement of these moments for the cosmological density field and for the microwave background temperature anisotropy can provide a test of the Gaussian nature of the primordial fluctuation spectrum. In the case of the density field, the importance of measuring the kurtosis is stressed since it will be preserved through the weakly nonlinear gravitational evolution epoch. Current constraints on skewness and kurtosis of primeval perturbations are obtained from the observed density contrast on small scales and from recent COBE observations of temperature anisotropies on large scales. It is also shown how, in principle, future microwave anisotropy experiments might be able to reveal the initial skewness and kurtosis. It is shown that present data argue that if the initial spectrum is adiabatic, then it is probably Gaussian, but non-Gaussian isocurvature fluctuations are still allowed, and these are what topological defects provide.
Uğurlu, Mahmut; Aksekili, Mehmet Atıf Erol; Alkan, Berat Meryem; Kara, Halil; Çağlar, Ceyhun
2017-06-12
The aim of this study was to assess the efficacy of the Artcure Diffusional Patch, which contains a mixture of 6 herbal oils (oleum thymi, oleum limonis, oleum nigra, oleum rosmarini, oleum chamomilla, oleum lauriexpressum) and has a hypoosmolar lipid structure, in the conservative treatment of lumbar disc herniation patients and to show the advantages and/or possibility of using this as an alternative method to surgery. Of the 120 patients enrolled, 79 clinically diagnosed patients were included in the study. Clinical evaluations were performed on patients who had findings of protrusion or extrusion in their magnetic resonance results. The treatment group was treated with the Artcure Diffusional Patch while the control group received a placebo transdermal diffusional patch. The functional state of patients was measured using the Oswestry Disability Index and pain intensity was measured with a visual analog scale as primary outcomes. Secondary outcomes of the study were Lasegue's sign, the femoral stretching test, and paravertebral muscle spasm. The treatment group showed a dramatic recovery in the first month following the application in regards to Oswestry Disability Index scores and visual analog scale values. The patients treated with the Artcure Diffusional Patch showed a statistically significant difference in recovery as compared to the control group. These findings suggest that the Artcure Diffusional Patch may be an alternative for the conservative treatment of lumbar disc herniation with radiculopathy.
A Robust Post-Processing Workflow for Datasets with Motion Artifacts in Diffusion Kurtosis Imaging
Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X.; Wan, Mingxi
2014-01-01
Purpose The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). Materials and methods The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). Results The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05). Conclusion The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements. PMID:24727862
Selected PET radiomic features remain the same.
Tsujikawa, Tetsuya; Tsuyoshi, Hideaki; Kanno, Masafumi; Yamada, Shizuka; Kobayashi, Masato; Narita, Norihiko; Kimura, Hirohiko; Fujieda, Shigeharu; Yoshida, Yoshio; Okazawa, Hidehiko
2018-04-17
We investigated whether PET radiomic features are affected by differences in the scanner, scan protocol, and lesion location using 18 F-FDG PET/CT and PET/MR scans. SUV, TMR, skewness, kurtosis, entropy, and homogeneity strongly correlated between PET/CT and PET/MR images. SUVs were significantly higher on PET/MR 0-2 min and PET/MR 0-10 min than on PET/CT in gynecological cancer ( p = 0.008 and 0.008, respectively), whereas no significant difference was observed between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images in oral cavity/oropharyngeal cancer. TMRs on PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min increased in this order in gynecological cancer and oral cavity/oropharyngeal cancer. In contrast to conventional and histogram indices, 4 textural features (entropy, homogeneity, SRE, and LRE) were not significantly different between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images. 18 F-FDG PET radiomic features strongly correlated between PET/CT and PET/MR images. Dixon-based attenuation correction on PET/MR images underestimated tumor tracer uptake more significantly in oral cavity/oropharyngeal cancer than in gynecological cancer. 18 F-FDG PET textural features were affected less by differences in the scanner and scan protocol than conventional and histogram features, possibly due to the resampling process using a medium bin width. Eight patients with gynecological cancer and 7 with oral cavity/oropharyngeal cancer underwent a whole-body 18 F-FDG PET/CT scan and regional PET/MR scan in one day. PET/MR scans were performed for 10 minutes in the list mode, and PET/CT and 0-2 min and 0-10 min PET/MR images were reconstructed. The standardized uptake value (SUV), tumor-to-muscle SUV ratio (TMR), skewness, kurtosis, entropy, homogeneity, short-run emphasis (SRE), and long-run emphasis (LRE) were compared between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images.
A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging.
Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X; Wan, Mingxi
2014-01-01
The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (p<0.05). It indicated that LPCC was more sensitive in detecting motion artifacts. MSEs of all derived parameters from the reserved data after the artifacts rejection were smaller than the variance of the noise. It suggested that influence of rejected artifacts was less than influence of noise on the precision of derived parameters. The proposed workflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (p<0.05). The proposed post-processing workflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.
Comment on "Universal relation between skewness and kurtosis in complex dynamics"
NASA Astrophysics Data System (ADS)
Celikoglu, Ahmet; Tirnakli, Ugur
2015-12-01
In a recent paper [M. Cristelli, A. Zaccaria, and L. Pietronero, Phys. Rev. E 85, 066108 (2012), 10.1103/PhysRevE.85.066108], the authors analyzed the relation between skewness and kurtosis for complex dynamical systems, and they identified two power-law regimes of non-Gaussianity, one of which scales with an exponent of 2 and the other with 4 /3 . They concluded that the observed relation is a universal fact in complex dynamical systems. In this Comment, we test the proposed universal relation between skewness and kurtosis with a large number of synthetic data, and we show that in fact it is not a universal relation and originates only due to the small number of data points in the datasets considered. The proposed relation is tested using a family of non-Gaussian distribution known as q -Gaussians. We show that this relation disappears for sufficiently large datasets provided that the fourth moment of the distribution is finite. We find that kurtosis saturates to a single value, which is of course different from the Gaussian case (K =3 ), as the number of data is increased, and this indicates that the kurtosis will converge to a finite single value if all moments of the distribution up to fourth are finite. The converged kurtosis value for the finite fourth-moment distributions and the number of data points needed to reach this value depend on the deviation of the original distribution from the Gaussian case.
Qiu, Wei; Hamernik, Roger P; Davis, Robert I
2013-05-01
A series of Gaussian and non-Gaussian equal energy noise exposures were designed with the objective of establishing the extent to which the kurtosis statistic could be used to grade the severity of noise trauma produced by the exposures. Here, 225 chinchillas distributed in 29 groups, with 6 to 8 animals per group, were exposed at 97 dB SPL. The equal energy exposures were presented either continuously for 5 d or on an interrupted schedule for 19 d. The non-Gaussian noises all differed in the level of the kurtosis statistic or in the temporal structure of the noise, where the latter was defined by different peak, interval, and duration histograms of the impact noise transients embedded in the noise signal. Noise-induced trauma was estimated from auditory evoked potential hearing thresholds and surface preparation histology that quantified sensory cell loss. Results indicated that the equal energy hypothesis is a valid unifying principle for estimating the consequences of an exposure if and only if the equivalent energy exposures had the same kurtosis. Furthermore, for the same level of kurtosis the detailed temporal structure of an exposure does not have a strong effect on trauma.
Detecting Compartmental non-Gaussian Diffusion with Symmetrized Double-PFG MRI
Paulsen, Jeffrey L.; Özarslan, Evren; Komlosh, Michal E.; Basser, Peter J.; Song, Yi-Qiao
2015-01-01
Diffusion in tissue and porous media is known to be non-Gaussian and has been used for clinical indications of stroke and other tissue pathologies. However, when conventional NMR techniques are applied to biological tissues and other heterogeneous materials, the presence of multiple compartments (pores) with different Gaussian diffusivities will also contribute to the measurement of non-Gaussian behavior. Here we present Symmetrized Double PFG (sd-PFG), which can separate these two contributions to non-Gaussian signal decay as having distinct angular modulation frequencies. In contrast to prior angular d-PFG methods, sd-PFG can unambiguously extract kurtosis as an oscillation from samples with isotropic or uniformly oriented anisotropic pores, and can generally extract a combination of compartmental anisotropy and kurtosis. The method further fixes its sensitivity with respect to the time-dependence of the apparent diffusion coefficient. We experimentally demonstrate the measurement of the fourth moment (kurtosis) of diffusion and find it consistent with theoretical predictions. By enabling the unambiguous identification of contributions of compartmental kurtosis to the signal, sd-PFG has the potential to help identify the underlying micro-structural changes corresponding to current kurtosis based diagnostics and act as a novel source of contrast to better resolve tissue micro-structure. PMID:26434812
Xie, Hong-Wei; Qiu, Wei; Heyer, Nicholas J; Zhang, Mei-Bian; Zhang, Peng; Zhao, Yi-Ming; Hamernik, Roger P
2016-01-01
To test a kurtosis-adjusted cumulative noise exposure (CNE) metric for use in evaluating the risk of hearing loss among workers exposed to industrial noises. Specifically, to evaluate whether the kurtosis-adjusted CNE (1) provides a better association with observed industrial noise-induced hearing loss, and (2) provides a single metric applicable to both complex (non-Gaussian [non-G]) and continuous or steady state (Gaussian [G]) noise exposures for predicting noise-induced hearing loss (dose-response curves). Audiometric and noise exposure data were acquired on a population of screened workers (N = 341) from two steel manufacturing plants located in Zhejiang province and a textile manufacturing plant located in Henan province, China. All the subjects from the two steel manufacturing plants (N = 178) were exposed to complex noise, whereas the subjects from textile manufacturing plant (N = 163) were exposed to a G continuous noise. Each subject was given an otologic examination to determine their pure-tone HTL and had their personal 8-hr equivalent A-weighted noise exposure (LAeq) and full-shift noise kurtosis statistic (which is sensitive to the peaks and temporal characteristics of noise exposures) measured. For each subject, an unadjusted and kurtosis-adjusted CNE index for the years worked was created. Multiple linear regression analysis controlling for age was used to determine the relationship between CNE (unadjusted and kurtosis adjusted) and the mean HTL at 3, 4, and 6 kHz (HTL346) among the complex noise-exposed group. In addition, each subject's HTLs from 0.5 to 8.0 kHz were age and sex adjusted using Annex A (ISO-1999) to determine whether they had adjusted high-frequency noise-induced hearing loss (AHFNIHL), defined as an adjusted HTL shift of 30 dB or greater at 3.0, 4.0, or 6.0 kHz in either ear. Dose-response curves for AHFNIHL were developed separately for workers exposed to G and non-G noise using both unadjusted and adjusted CNE as the exposure matric. Multiple linear regression analysis among complex exposed workers demonstrated that the correlation between HTL3,4,6 and CNE controlling for age was improved when using the kurtosis-adjusted CNE compared with the unadjusted CNE (R = 0.386 versus 0.350) and that noise accounted for a greater proportion of hearing loss. In addition, although dose-response curves for AHFNIHL were distinctly different when using unadjusted CNE, they overlapped when using the kurtosis-adjusted CNE. For the same exposure level, the prevalence of NIHL is greater in workers exposed to complex noise environments than in workers exposed to a continuous noise. Kurtosis adjustment of CNE improved the correlation with NIHL and provided a single metric for dose-response effects across different types of noise. The kurtosis-adjusted CNE may be a reasonable candidate for use in NIHL risk assessment across a wide variety of noise environments.
Wang, G J; Wang, Y; Ye, Y; Chen, F; Lu, Y T; Li, S L
2017-11-07
Objective: To investigate the features of apparent diffusion coefficient (ADC) histogram parameters based on entire tumor volume data in high resolution diffusion weighted imaging of nasopharyngeal carcinoma (NPC) and to evaluate its correlations with cancer stages. Methods: This retrospective study included 154 cases of NPC patients[102 males and 52 females, mean age (48±11) years]who had received readout segmentation of long variable echo trains of MRI scan before radiation therapy. The area of tumor was delineated on each section of axial ADC maps to generate ADC histogram by using Image J. ADC histogram of entire tumor along with the histogram parameters-the tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness and kurtosis were obtained by merging all sections with SPSS 22.0 software. Intra-observer repeatability was assessed by using intra-class correlation coefficients (ICC). The patients were subdivided into two groups according to cancer volume: small cancer group (<305 voxels, about 2 cm(3)) and large cancer group (≥2 cm(3)). The correlation between ADC histogram parameters and cancer stages was evaluated with Spearman test. Results: The ICC of measuring ADC histogram parameters of tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness, kurtosis was 0.938, 0.861, 0.885, 0.838, 0.836, 0.358 and 0.456, respectively. The tumor voxels was positively correlated with T staging ( r =0.368, P <0.05). There were significant differences in tumor voxels among patients with different T stages ( K =22.306, P <0.05). There were significant differences in the ADC(mean), ADC(25%), ADC(50%) among patients with different T stages in the small cancer group( K =8.409, 8.187, 8.699, all P <0.05), and the up-mentioned three indices were positively correlated with T staging ( r =0.221, 0.209, 0.235, all P <0.05). Skewness and kurtosis differed significantly between the groups with different cancer volume( t =-2.987, Z =-3.770, both P <0.05). Conclusion: The tumor volume, tissue uniformity of NPC are important factors affecting ADC and cancer stages, parameters of ADC histogram (ADC(mean), ADC(25%), ADC(50%)) increases with T staging in NPC smaller than 2 cm(3).
1992-01-01
entropy , energy. variance, skewness, and object. It can also be applied to an image of a phenomenon. It kurtosis. These parameters are then used as...statistic. The co-occurrence matrix method is used in this study to derive texture values of entropy . Limogeneity. energy (similar to the GLDV angular...from working with the co-occurrence matrix method. Seven convolution sizes were chosen to derive the texture values of entropy , local homogeneity, and
Anomalously Fast Diffusion of Targeted Carbon Nanotubes in Cellular Spheroids.
Wang, Yichun; Bahng, Joong Hwan; Che, Quantong; Han, Jishu; Kotov, Nicholas A
2015-08-25
Understanding transport of carbon nanotubes (CNTs) and other nanocarriers within tissues is essential for biomedical imaging and drug delivery using these carriers. Compared to traditional cell cultures in animal studies, three-dimensional tissue replicas approach the complexity of the actual organs and enable high temporal and spatial resolution of the carrier permeation. We investigated diffusional transport of CNTs in highly uniform spheroids of hepatocellular carcinoma and found that apparent diffusion coefficients of CNTs in these tissue replicas are anomalously high and comparable to diffusion rates of similarly charged molecules with molecular weights 10000× lower. Moreover, diffusivity of CNTs in tissues is enhanced after functionalization with transforming growth factor β1. This unexpected trend contradicts predictions of the Stokes-Einstein equation and previously obtained empirical dependences of diffusivity on molecular mass for permeants in gas, liquid, solid or gel. It is attributed to the planar diffusion (gliding) of CNTs along cellular membranes reducing effective dimensionality of diffusional space. These findings indicate that nanotubes and potentially similar nanostructures are capable of fast and deep permeation into the tissue, which is often difficult to realize with anticancer agents.
Detecting compartmental non-Gaussian diffusion with symmetrized double-PFG MRI.
Paulsen, Jeffrey L; Özarslan, Evren; Komlosh, Michal E; Basser, Peter J; Song, Yi-Qiao
2015-11-01
Diffusion in tissue and porous media is known to be non-Gaussian and has been used for clinical indications of stroke and other tissue pathologies. However, when conventional NMR techniques are applied to biological tissues and other heterogeneous materials, the presence of multiple compartments (pores) with different Gaussian diffusivities will also contribute to the measurement of non-Gaussian behavior. Here we present symmetrized double PFG (sd-PFG), which can separate these two contributions to non-Gaussian signal decay as having distinct angular modulation frequencies. In contrast to prior angular d-PFG methods, sd-PFG can unambiguously extract kurtosis as an oscillation from samples with isotropic or uniformly oriented anisotropic pores, and can generally extract a combination of compartmental anisotropy and kurtosis. The method further fixes its sensitivity with respect to the time dependence of the apparent diffusion coefficient. We experimentally demonstrate the measurement of the fourth cumulant (kurtosis) of diffusion and find it consistent with theoretical predictions. By enabling the unambiguous identification of contributions of compartmental kurtosis to the signal, sd-PFG has the potential to help identify the underlying micro-structural changes corresponding to current kurtosis based diagnostics, and act as a novel source of contrast to better resolve tissue micro-structure. Copyright © 2015 John Wiley & Sons, Ltd.
O'Connell, Caitlin; Ho, Leon C; Murphy, Matthew C; Conner, Ian P; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C
2016-11-09
Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.
Itoh, Yuya; Itoh, Akihiro; Kawashima, Hiroki; Ohno, Eizaburo; Nakamura, Yosuke; Hiramatsu, Takeshi; Sugimoto, Hiroyuki; Sumi, Hajime; Hayashi, Daijuro; Kuwahara, Takamichi; Morishima, Tomomasa; Funasaka, Kohei; Nakamura, Masanao; Miyahara, Ryoji; Ohmiya, Naoki; Katano, Yoshiaki; Ishigami, Masatoshi; Goto, Hidemi; Hirooka, Yoshiki
2014-07-01
An accurate diagnosis of pancreatic fibrosis is clinically important and may have potential for staging chronic pancreatitis. The aim of this study was to diagnose the grade of pancreatic fibrosis through a quantitative analysis of endoscopic ultrasound elastography (EUS-EG). From September 2004 to October 2010, 58 consecutive patients examined by EUS-EG for both pancreatic tumors and their upstream pancreas before pancreatectomy were enrolled. Preoperative EUS-EG images in the upstream pancreas were statistically quantified, and the results were retrospectively compared with postoperative histological fibrosis in the same area. For the quantification of EUS-EG images, 4 parameters (mean, standard deviation, skewness, and kurtosis) were calculated using novel software. Histological fibrosis was graded into 4 categories (normal, mild fibrosis, marked fibrosis, and severe fibrosis) according to a previously reported scoring system. The fibrosis grade in the upstream pancreas was normal in 24 patients, mild fibrosis in 19, marked fibrosis in 6, and severe fibrosis in 9. Fibrosis grade was significantly correlated with all 4 quantification parameters (mean r = -0.75, standard deviation r = -0.54, skewness r = 0.69, kurtosis r = 0.67). According to the receiver operating characteristic analysis, the mean was the most useful parameter for diagnosing pancreatic fibrosis. Using the mean, the area under the ROC curves for the diagnosis of mild or higher-grade fibrosis, marked or higher-grade fibrosis and severe fibrosis were 0.90, 0.90, and 0.90, respectively. An accurate diagnosis of pancreatic fibrosis may be possible by analyzing EUS-EG images.
The importance of correcting for signal drift in diffusion MRI.
Vos, Sjoerd B; Tax, Chantal M W; Luijten, Peter R; Ourselin, Sebastien; Leemans, Alexander; Froeling, Martijn
2017-01-01
To investigate previously unreported effects of signal drift as a result of temporal scanner instability on diffusion MRI data analysis and to propose a method to correct this signal drift. We investigated the signal magnitude of non-diffusion-weighted EPI volumes in a series of diffusion-weighted imaging experiments to determine whether signal magnitude changes over time. Different scan protocols and scanners from multiple vendors were used to verify this on phantom data, and the effects on diffusion kurtosis tensor estimation in phantom and in vivo data were quantified. Scalar metrics (eigenvalues, fractional anisotropy, mean diffusivity, mean kurtosis) and directional information (first eigenvectors and tractography) were investigated. Signal drift, a global signal decrease with subsequently acquired images in the scan, was observed in phantom data on all three scanners, with varying magnitudes up to 5% in a 15-min scan. The signal drift has a noticeable effect on the estimation of diffusion parameters. All investigated quantitative parameters as well as tractography were affected by this artifactual signal decrease during the scan. By interspersing the non-diffusion-weighted images throughout the session, the signal decrease can be estimated and compensated for before data analysis; minimizing the detrimental effects on subsequent MRI analyses. Magn Reson Med 77:285-299, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Resolving power for the diffusion orientation distribution function.
Jensen, Jens H; Helpern, Joseph A
2016-08-01
The diffusion orientation distribution function (dODF) is primarily used for white matter fiber tractography. Here the resolving power of the dODF is investigated for a simple diffusion model of two intersecting axonal fiber bundles. The resolving power for the dODF is evaluated using the Sparrow criterion. This is determined for the exact dODF and also for q-space imaging (QSI), q-ball, and kurtosis approximations. Based on theoretical and numerical calculations, the resolving power is found to depend on the eigenvalues of the diffusion model and on the degree of radial weighting for the dODF. The resolving powers of the QSI and q-ball dODFs improve with increased b-value. The kurtosis dODF has a resolving power similar to that of the exact dODF. The dODFs, whether exact or approximate, have finite resolving powers that limit their sensitivity to fiber crossings. The resolving powers for the different dODFs considered here provide convenient benchmarks for assessing and comparing their performance. Magn Reson Med 76:679-688, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Liao, Yuhe; Sun, Peng; Wang, Baoxiang; Qu, Lei
2018-05-01
The appearance of repetitive transients in a vibration signal is one typical feature of faulty rolling element bearings. However, accurate extraction of these fault-related characteristic components has always been a challenging task, especially when there is interference from large amplitude impulsive noises. A frequency domain multipoint kurtosis (FDMK)-based fault diagnosis method is proposed in this paper. The multipoint kurtosis is redefined in the frequency domain and the computational accuracy is improved. An envelope autocorrelation function is also presented to estimate the fault characteristic frequency, which is used to set the frequency hunting zone of the FDMK. Then, the FDMK, instead of kurtosis, is utilized to generate a fast kurtogram and only the optimal band with maximum FDMK value is selected for envelope analysis. Negative interference from both large amplitude impulsive noise and shaft rotational speed related harmonic components are therefore greatly reduced. The analysis results of simulation and experimental data verify the capability and feasibility of this FDMK-based method
Makanyanga, Jesica; Ganeshan, Balaji; Rodriguez-Justo, Manuel; Bhatnagar, Gauraang; Groves, Ashley; Halligan, Steve; Miles, Ken; Taylor, Stuart A
2017-02-01
To associate MRI textural analysis (MRTA) with MRI and histological Crohn's disease (CD) activity. Sixteen patients (mean age 39.5 years, 9 male) undergoing MR enterography before ileal resection were retrospectively analysed. Thirty-six small (≤3 mm) ROIs were placed on T2-weighted images and location-matched histological acute inflammatory scores (AIS) measured. MRI activity (mural thickness, T2 signal, T1 enhancement) (CDA) was scored in large ROIs. MRTA features (mean, standard deviation, mean of positive pixels (MPP), entropy, kurtosis, skewness) were extracted using a filtration histogram technique. Spatial scale filtration (SSF) ranged from 2 to 5 mm. Regression (linear/logistic) tested associations between MRTA and AIS (small ROIs), and CDA/constituent parameters (large ROIs). Skewness (SSF = 2 mm) was associated with AIS [regression coefficient (rc) 4.27, p = 0.02]. Of 120 large ROI analyses (for each MRI, MRTA feature and SSF), 15 were significant. Entropy (SSF = 2, 3 mm) and kurtosis (SSF = 3 mm) were associated with CDA (rc 0.9, 1.0, -0.45, p = 0.006-0.01). Entropy and mean (SSF = 2-4 mm) were associated with T2 signal [odds ratio (OR) 2.32-3.16, p = 0.02-0.004], [OR 1.22-1.28, p = 0.03-0.04]. MPP (SSF = 2 mm) was associated with mural thickness (OR 0.91, p = 0.04). Kurtosis (SSF = 3 mm), standard deviation (SSF = 5 mm) were associated with decreased T1 enhancement (OR 0.59, 0.42, p = 0.004, 0.007). MRTA features may be associated with CD activity. • MR texture analysis features may be associated with Crohn's disease histological activity. • Texture analysis features may correlate with MR-dependent Crohn's disease activity scores. • The utility of MR texture analysis in Crohn's disease merits further investigation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, W; Tu, S
Purpose: Pharyngeal and laryngeal carcinomas (PLC) are among the top leading cancers in Asian populations. Typically the tumor may recur and progress in a short period of time if radiotherapy fails to deliver a successful treatment. Here we used image texture features extracted from images of computed tomography (CT) planning and conducted a retrospective study to evaluate whether texture analysis is a feasible approach to predict local tumor recurrence for PLC patients received radiotherapy treatment. Methods: CT planning images of 100 patients with PLC treated by radiotherapy at our facility between 2001 and 2010 are collected. These patients were receivedmore » two separate CT scans, before and mid-course of the treatment delivery. Before the radiotherapy, a CT scanning was used for the first treatment planning. A total of 30 fractions were used in the treatment and patients were scanned with a second CT around the end of the fifteenth delivery for an adaptive treatment planning. Only patients who were treated with intensity modulated radiation therapy and RapidArc were selected. Treatment planning software of Eclipse was used. The changes of texture parameters between two CT acquisitions were computed to determine whether they were correlated to the local tumor recurrence. The following texture parameters were used in the preliminary assessment: mean, variance, standard deviation, skewness, kurtosis, energy, entropy, inverse difference moment, cluster shade, inertia, cluster prominence, gray-level co-occurrence matrix, and gray-level run-length matrix. The study was reviewed and approved by the committee of our institutional review board. Results: Our calculations suggested the following texture parameters were correlated with the local tumor recurrence: skewness, kurtosis, entropy, and inertia (p<0.0.05). Conclusion: The preliminary results were positive. However some works remain crucial to be completed, including addition of texture parameters for different image features, sensitivity of tumor segmentation variations, and effect of image filtering.« less
Mason, R P; Chester, D W
1989-01-01
A "membrane bilayer pathway" model, involving ligand partition into the bilayer, lateral diffusion, and receptor binding has been invoked to describe the 1,4-dihydropyridine (DHP) calcium channel antagonist receptor binding mechanism. In an earlier study (Chester et al. 1987. Biophys. J. 52:1021-1030), the diffusional component of this model was examined using an active fluorescence labeled DHP calcium channel antagonist, nisoldipine-lissamine rhodamine B (Ns-R), in purified cardiac sarcolemmal (CSL) lipid multibilayers. Diffusion coefficient measurements on membrane-bound drug and phospholipid at maximum bilayer hydration yielded similar values (3.8 x 10(-8) cm2/s). However, decreases in bilayer hydration resulted in dramatically reduced diffusion coefficient values for both probes with substantially greater impact on Ns-R diffusion. These data suggested that hydration dependent diffusional differences could be a function of relative probe location along the bilayer normal. In this communication, we have addressed the relative effect of the rhodamine substituent on Ns-R diffusion complex by examining the diffusional dynamics of free rhodamine B under the same conditions used to evaluate Ns-R complex and phospholipid diffusion. X-ray diffraction studies were performed to determine the Ns-R location in the membrane and model the CSL lipid bilayer profile structure to give a rationale for the differences in probe diffusional dynamics as a function of interbilayer water space. PMID:2611332
An Experimental Investigation Into The Effect Of Plasma On The Flow Features Of An Axisymmetric Jet
2007-10-01
document contains color images. 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18 . NUMBER OF PAGES 386...Prescribed by ANSI Std Z39- 18 AN EXPERIMENTAL INVESTIGATION INTO THE EFFECT OF PLASMA ON THE FLOW FEATURES OF AN AXISYMMETRIC JET BY RICHARD E. HUFFMAN...A. 18 Comparison of Plasma Effects on Skewness and Kurtosis: Case 611LINE3051 . . . . . . . . . 223 A.19 Comparison of Plasma Effects on Mean Velocity
Chantarojanasiri, Tanyaporn; Hirooka, Yoshiki; Kawashima, Hiroki; Ohno, Eizaburo; Sugimoto, Hiroyuki; Hayashi, Daijuro; Kuwahara, Takamichi; Yamamura, Takeshi; Funasaka, Kohei; Nakamura, Masanao; Miyahara, Ryoji; Ishigami, Masatoshi; Watanabe, Osamu; Hashimoto, Senju; Goto, Hidemi
2016-07-01
Ultrasound strain elastography is one of the useful methods for evaluating pancreatic lesions. During aging, several pancreatic parenchymal changes occur that may interfere with the interpretation of the ultrasound images. We studied age-related changes in pancreatic elasticity using transabdominal ultrasound strain elastography in subjects without known pancreatic disease. This study was conducted at Nagoya University Hospital, which is an academic medical center, and included 102 subjects (66 women and 39 men) aged 20-85years (mean 58.6±17.5) who underwent transabdominal ultrasonography for screening and follow-up for non-pancreatic diseases. Strain elastography of the pancreas was performed, and the results were subjected to quantitative strain histogram analysis. The correlations of age with four elastographic parameters (Mean, Standard deviation, Skewness, and Kurtosis) and other findings, including hyperechoic pancreas, hyperechoic liver, and diabetes, were evaluated. There was a significant correlation between increasing age and elastographic parameters such as the Mean (P=0.004), Skewness (P=0.007), and Kurtosis (P=0.03), and these differences became significant after the age of 40. The prevalence of hyperechoic pancreas increased with age (P<0.001), and the Means were lower in those with hyperechoic pancreas (P=0.004) and a higher body mass index (BMI, P=0.008). No significant correlations with diabetes, hyperechoic liver, or elastographic parameters were demonstrated. Strain elastography demonstrated elastographic changes in the pancreas with aging that included a decreasing Mean and increasing Skewness and Kurtosis after the age of 40. The prevalence of pancreatic hyperechogenicity increased, and the pancreatic hyperechogenicity was significantly negatively correlated with the Mean. Copyright © 2016 Elsevier B.V. All rights reserved.
Bougias, H; Ghiatas, A; Priovolos, D; Veliou, K; Christou, A
2017-05-01
To retrospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) in the characterization of breast tumors by comparing different histogram metrics. 49 patients with 53 breast lesions underwent magnetic resonance imaging (MRI). ADC histogram parameters, including the mean, mode, 10th/50th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann-Whitney U-test, area under the receiver-operating characteristic curve (AUC) were used for statistical analysis. The mean, mode and 10th/50th/90th percentile ADC values were significantly lower in malignant lesions compared with benign ones (all P < 0.0001), while skewness was significantly higher in malignant lesions P = 0.02. However, no significant difference was found between entropy and kurtosis values in malignant lesions compared with benign ones (P = 0.06 and P = 1.00, respectively). Univariate logistic regression showed that 10th and 50th percentile ADC yielded the highest AUC (0.985; 95% confidence interval [CI]: 0.902, 1.000 and 0.982; 95% confidence interval [CI]: 0.896, 1.000 respectively), whereas kurtosis value yielded the lowest AUC (0.500; 95% CI: 0.355, 0.645), indicating that 10th and 50th percentile ADC values may be more accurate for lesion discrimination. Whole-lesion ADC histogram analysis could be a helpful index in the characterization and differentiation between benign and malignant breast lesions with the 10th and 50th percentile ADC be the most accurate discriminators. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.
Lancaster, Melissa A; Olson, Daniel V; McCrea, Michael A; Nelson, Lindsay D; LaRoche, Ashley A; Muftuler, L Tugan
2016-11-01
Recent neuroimaging studies have suggested that following sport-related concussion (SRC) physiological brain alterations may persist after an athlete has shown full symptom recovery. Diffusion MRI is a versatile technique to study white matter injury following SRC, yet serial follow-up studies in the very acute stages following SRC utilizing a comprehensive set of diffusion metrics are lacking. The aim of the current study was to characterize white matter changes within 24 hours of concussion in a group of high school and collegiate athletes, using Diffusion Tensor and Diffusion Kurtosis Tensor metrics. Participants were reassessed a week later. At 24 hours post-injury, the concussed group reported significantly more concussion symptoms than a well-matched control group and demonstrated poorer performance on a cognitive screening measure, yet these differences were nonsignificant at the 8-day follow-up. Similarly, within 24-hours after injury, the concussed group exhibited a widespread decrease in mean diffusivity, increased axial kurtosis and, to a lesser extent, decreased axial and radial diffusivities compared with control subjects. At 8 days post injury, the differences in these diffusion metrics were even more widespread in the injured athletes, despite improvement of symptoms and cognitive performance. These MRI findings suggest that the athletes might not have reached full physiological recovery a week after the injury. These findings have significant implications for the management of SRC because allowing an athlete to return to play before the brain has fully recovered from injury may have negative consequences. Hum Brain Mapp 37:3821-3834, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Astronomic Position Accuracy Capability Study.
1979-10-01
sample of 37 FOs produced coefficients of skewness and excess of -0.21 and -0.28, respectively. The kurtosis of 2.72 indicates a platykurtic ...The kurtosis of 2.72 indicates a platykurtic distribution. The KS Test for Goodness of Fit was used to verify or refute that this sample is from a
Grieve, Stuart M; Korgaonkar, Mayuresh S; Clark, C Richard; Williams, Leanne M
2011-04-01
Magnetic resonance imaging (MRI) studies of structural brain development have suggested that the limbic system is relatively preserved in comparison to other brain regions with healthy aging. The goal of this study was to systematically investigate age-related changes of the limbic system using measures of cortical thickness, volumetric and diffusion characteristics. We also investigated if the "relative preservation" concept is consistent across the individual sub-regions of the limbic system. T1 weighted structural MRI and Diffusion Tensor Imaging data from 476 healthy participants from the Brain Resource International Database was used for this study. Age-related changes in grey matter (GM)/white matter (WM) volume, cortical thickness, diffusional characteristics for the pericortical WM and for the fiber tracts associated with the limbic regions were quantified. A regional variability in the aging patterns across the limbic system was present. Four important patterns of age-related changes were highlighted for the limbic sub-regions: 1. early maturation of GM with late loss in the hippocampus and amygdala; 2. an extreme pattern of GM preservation in the entorhinal cortex; 3. a flat pattern of reduced GM loss in the anterior cingulate and the parahippocampus and; 4. accelerated GM loss in the isthmus and posterior cingulate. The GM volumetric data and cortical thickness measures proved to be internally consistent, while the diffusional measures provided complementary data that seem consistent with the GM trends identified. This heterogeneity can be hypothesized to be associated with age-related changes of cognitive function specialized for that region and direct connections to the other brain regions sub-serving these functions. Copyright © 2011 Elsevier Inc. All rights reserved.
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.
NASA Astrophysics Data System (ADS)
Suo, Qiangbo; Han, Yiping; Cui, Zhiwei
2017-09-01
Based on the extended Huygens-Fresnel integral, the analytical expressions for the Wigner distribution function (WDF) and kurtosis parameter of partially coherent flat-topped vortex (PCFTV) beams propagating through atmospheric turbulence and free space are derived. The WDF and kurtosis parameter of PCFTV beams through turbulent atmosphere are discussed with numerical examples. The numerical results show that the beam quality depends on the structure constants, the inner scale turbulence, the outer scale turbulence, the spatial correlation length, the wave length and the beam order. PCFTV beams are less affected by turbulence than partially flat-topped coherent (PCFT) beams under the same conditions, and will be useful in free-space optical communications.
Cauley, K A; Hu, Y; Och, J; Yorks, P J; Fielden, S W
2018-04-01
The majority of brain growth and development occur in the first 2 years of life. This study investigated these changes by analysis of the brain radiodensity histogram of head CT scans from the clinical population, 0-2 years of age. One hundred twenty consecutive head CTs with normal findings meeting the inclusion criteria from children from birth to 2 years were retrospectively identified from 3 different CT scan platforms. Histogram analysis was performed on brain-extracted images, and histogram mean, mode, full width at half maximum, skewness, kurtosis, and SD were correlated with subject age. The effects of scan platform were investigated. Normative curves were fitted by polynomial regression analysis. Average total brain volume was 360 cm 3 at birth, 948 cm 3 at 1 year, and 1072 cm 3 at 2 years. Total brain tissue density showed an 11% increase in mean density at 1 year and 19% at 2 years. Brain radiodensity histogram skewness was positive at birth, declining logarithmically in the first 200 days of life. The histogram kurtosis also decreased in the first 200 days to approach a normal distribution. Direct segmentation of CT images showed that changes in brain radiodensity histogram skewness correlated with, and can be explained by, a relative increase in gray matter volume and an increase in gray and white matter tissue density that occurs during this period of brain maturation. Normative metrics of the brain radiodensity histogram derived from routine clinical head CT images can be used to develop a model of normal brain development. © 2018 by American Journal of Neuroradiology.
Ganesan, Vishnu; De, Shubha; Shkumat, Nicholas; Marchini, Giovanni; Monga, Manoj
2018-02-01
Preoperative determination of uric acid stones from computerized tomography imaging would be of tremendous clinical use. We sought to design a software algorithm that could apply data from noncontrast computerized tomography to predict the presence of uric acid stones. Patients with pure uric acid and calcium oxalate stones were identified from our stone registry. Only stones greater than 4 mm which were clearly traceable from initial computerized tomography to final composition were included in analysis. A semiautomated computer algorithm was used to process image data. Average and maximum HU, eccentricity (deviation from a circle) and kurtosis (peakedness vs flatness) were automatically generated. These parameters were examined in several mathematical models to predict the presence of uric acid stones. A total of 100 patients, of whom 52 had calcium oxalate and 48 had uric acid stones, were included in the final analysis. Uric acid stones were significantly larger (12.2 vs 9.0 mm, p = 0.03) but calcium oxalate stones had higher mean attenuation (457 vs 315 HU, p = 0.001) and maximum attenuation (918 vs 553 HU, p <0.001). Kurtosis was significantly higher in each axis for calcium oxalate stones (each p <0.001). A composite algorithm using attenuation distribution pattern, average attenuation and stone size had overall 89% sensitivity, 91% specificity, 91% positive predictive value and 89% negative predictive value to predict uric acid stones. A combination of stone size, attenuation intensity and attenuation pattern from conventional computerized tomography can distinguish uric acid stones from calcium oxalate stones with high sensitivity and specificity. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Jafari, Mehrnoosh; Minaei, Saeid; Safaie, Naser; Torkamani-Azar, Farah
2016-05-01
Spatial and temporal changes in surface temperature of infected and non-infected rose plant (Rosa hybrida cv. 'Angelina') leaves were visualized using digital infrared thermography. Infected areas exhibited a presymptomatic decrease in leaf temperature up to 2.3 °C. In this study, two experiments were conducted: one in the greenhouse (semi-controlled ambient conditions) and the other, in a growth chamber (controlled ambient conditions). Effect of drought stress and darkness on the thermal images were also studied in this research. It was found that thermal histograms of the infected leaves closely follow a standard normal distribution. They have a skewness near zero, kurtosis under 3, standard deviation larger than 0.6, and a Maximum Temperature Difference (MTD) more than 4. For each thermal histogram, central tendency, variability, and parameters of the best fitted Standard Normal and Laplace distributions were estimated. To classify healthy and infected leaves, feature selection was conducted and the best extracted thermal features with the largest linguistic hedge values were chosen. Among those features independent of absolute temperature measurement, MTD, SD, skewness, R2l, kurtosis and bn were selected. Then, a neuro-fuzzy classifier was trained to recognize the healthy leaves from the infected ones. The k-means clustering method was utilized to obtain the initial parameters and the fuzzy "if-then" rules. Best estimation rates of 92.55% and 92.3% were achieved in training and testing the classifier with 8 clusters. Results showed that drought stress had an adverse effect on the classification of healthy leaves. More healthy leaves under drought stress condition were classified as infected causing PPV and Specificity index values to decrease, accordingly. Image acquisition in the dark had no significant effect on the classification performance.
Zhang, G-M-Y; Sun, H; Shi, B; Xu, M; Xue, H-D; Jin, Z-Y
2018-05-21
To evaluate the accuracy of computed tomography (CT) texture analysis (TA) to differentiate uric acid (UA) stones from non-UA stones on unenhanced CT in patients with urinary calculi with ex vivo Fourier transform infrared spectroscopy (FTIR) as the reference standard. Fourteen patients with 18 UA stones and 31 patients with 32 non-UA stones were included. All the patients had preoperative CT evaluation and subsequent surgical removal of the stones. CTTA was performed on CT images using commercially available research software. Each texture feature was evaluated using the non-parametric Mann-Whitney test. Receiver operating characteristic (ROC) curves were created and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different. The features were used to train support vector machine (SVM) classifiers. Diagnostic accuracy was evaluated. Compared to non-UA stones, UA stones had significantly lower mean, standard deviation and mean of positive pixels but higher kurtosis (p<0.001) on both unfiltered and filtered texture scales. There were no significant differences in entropy or skewness between UA and non-UA stones. The average SVM accuracy of texture features for differentiating UA from non-UA stones ranged from 88% to 92% (after 10-fold cross validation). A model incorporating standard deviation, skewness, and kurtosis from unfiltered texture scale images resulted in an AUC of 0.965±00.029 with a sensitivity of 94.4% and specificity of 93.7%. CTTA can be used to accurately differentiate UA stones from non-UA stones in vivo using unenhanced CT images. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Takahashi, Masahiro; Kozawa, Eito; Tanisaka, Megumi; Hasegawa, Kousei; Yasuda, Masanori; Sakai, Fumikazu
2016-06-01
We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma. We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity. Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P < 0.05). ROC curve analysis of the 75th percentile yielded the best area under the ROC curve (AUC; 0.904), sensitivity of 100%, and specificity of 78.0%, with a cutoff value of 1.034 × 10(-3) mm(2) /s. Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307. © 2015 Wiley Periodicals, Inc.
Fault detection in rotating machines with beamforming: Spatial visualization of diagnosis features
NASA Astrophysics Data System (ADS)
Cardenas Cabada, E.; Leclere, Q.; Antoni, J.; Hamzaoui, N.
2017-12-01
Rotating machines diagnosis is conventionally related to vibration analysis. Sensors are usually placed on the machine to gather information about its components. The recorded signals are then processed through a fault detection algorithm allowing the identification of the failing part. This paper proposes an acoustic-based diagnosis method. A microphone array is used to record the acoustic field radiated by the machine. The main advantage over vibration-based diagnosis is that the contact between the sensors and the machine is no longer required. Moreover, the application of acoustic imaging makes possible the identification of the sources of acoustic radiation on the machine surface. The display of information is then spatially continuous while the accelerometers only give it discrete. Beamforming provides the time-varying signals radiated by the machine as a function of space. Any fault detection tool can be applied to the beamforming output. Spectral kurtosis, which highlights the impulsiveness of a signal as function of frequency, is used in this study. The combination of spectral kurtosis with acoustic imaging makes possible the mapping of the impulsiveness as a function of space and frequency. The efficiency of this approach lays on the source separation in the spatial and frequency domains. These mappings make possible the localization of such impulsive sources. The faulty components of the machine have an impulsive behavior and thus will be highlighted on the mappings. The study presents experimental validations of the method on rotating machines.
Evaluation of non-Gaussian diffusion in cardiac MRI.
McClymont, Darryl; Teh, Irvin; Carruth, Eric; Omens, Jeffrey; McCulloch, Andrew; Whittington, Hannah J; Kohl, Peter; Grau, Vicente; Schneider, Jürgen E
2017-09-01
The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non-Gaussian modeling. The aim of this study was to investigate non-Gaussian diffusion in healthy and hypertrophic hearts. Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion-weighted images were acquired at b-values up to 10,000 s/mm 2 . Models of diffusion were fit to the data and ranked based on the Akaike information criterion. The diffusion tensor was ranked best at b-values up to 2000 s/mm 2 but reflected the signal poorly in the high b-value regime, in which the best model was a non-Gaussian "beta distribution" model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet-normal directions. Non-Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174-1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
NASA Astrophysics Data System (ADS)
Dan, Youquan; Xu, Yonggen
2018-04-01
The evolution law of arbitrary order moments of the Wigner distribution function, which can be applied to the different spatial power spectra, is obtained for partially coherent general beams propagating in atmospheric turbulence using the extended Huygens-Fresnel principle. A coupling coefficient of radiant intensity distribution (RID) in turbulence is introduced. Analytical expressions of the evolution of the first five-order moments, kurtosis parameter, coupling coefficient of RID for general beams in turbulence are derived, and the formulas are applied to Airy beams. Results show that there exist two types for general beams in turbulence. A larger value of kurtosis parameter for Airy beams also reveals that coupling effect due to turbulence is stronger. Both theoretical analysis and numerical results show that the maximum value of kurtosis parameter for an Airy beam in turbulence is independent of turbulence strength parameter and is only determined by inner scale of turbulence. Relative angular spread, kurtosis and coupling coefficient are less influenced by turbulence for Airy beams with a smaller decay factor and a smaller initial width of the first lobe.
NASA Astrophysics Data System (ADS)
Yusop, Hanafi M.; Ghazali, M. F.; Yusof, M. F. M.; Remli, M. A. Pi; Kamarulzaman, M. H.
2017-10-01
In a recent study, the analysis of pressure transient signals could be seen as an accurate and low-cost method for leak and feature detection in water distribution systems. Transient phenomena occurs due to sudden changes in the fluid’s propagation in pipelines system caused by rapid pressure and flow fluctuation due to events such as closing and opening valves rapidly or through pump failure. In this paper, the feasibility of the Hilbert-Huang transform (HHT) method/technique in analysing the pressure transient signals in presented and discussed. HHT is a way to decompose a signal into intrinsic mode functions (IMF). However, the advantage of HHT is its difficulty in selecting the suitable IMF for the next data postprocessing method which is Hilbert Transform (HT). This paper reveals that utilizing the application of an integrated kurtosis-based algorithm for a z-filter technique (I-Kaz) to kurtosis ratio (I-Kaz-Kurtosis) allows/contributes to/leads to automatic selection of the IMF that should be used. This technique is demonstrated on a 57.90-meter medium high-density polyethylene (MDPE) pipe installed with a single artificial leak. The analysis results using the I-Kaz-kurtosis ratio revealed/confirmed that the method can be used as an automatic selection of the IMF although the noise level ratio of the signal is low. Therefore, the I-Kaz-kurtosis ratio method is recommended as a means to implement an automatic selection technique of the IMF for HHT analysis.
NASA Astrophysics Data System (ADS)
Yusop, Hanafi M.; Ghazali, M. F.; Yusof, M. F. M.; PiRemli, M. A.; Karollah, B.; Rusman
2017-10-01
Pressure transient signal occurred due to sudden changes in fluid propagation filled in pipelines system, which is caused by rapid pressure and flow fluctuation in a system, such as closing and opening valve rapidly. The application of Hilbert-Huang Transform (HHT) as the method to analyse the pressure transient signal utilised in this research. However, this method has the difficulty in selecting the suitable IMF for the further post-processing, which is Hilbert Transform (HT). This paper proposed the implementation of Integrated Kurtosis-based Algorithm for z-filter Technique (I-kaz) to kurtosis ratio (I-kaz-Kurtosis) for that allows automatic selection of intrinsic mode function (IMF) that’s should be used. This work demonstrated the synthetic pressure transient signal generates using transmission line modelling (TLM) in order to test the effectiveness of I-kaz as the autonomous selection of intrinsic mode function (IMF). A straight fluid network was designed using TLM fixing with higher resistance at some point act as a leak and connecting to the pipe feature (junction, pipefitting or blockage). The analysis results using I-kaz-kurtosis ratio revealed that the method can be utilised as an automatic selection of intrinsic mode function (IMF) although the noise level ratio of the signal is lower. I-kaz-kurtosis ratio is recommended and advised to be implemented as automatic selection of intrinsic mode function (IMF) through HHT analysis.
NASA Astrophysics Data System (ADS)
Vass, J.; Šmíd, R.; Randall, R. B.; Sovka, P.; Cristalli, C.; Torcianti, B.
2008-04-01
This paper presents a statistical technique to enhance vibration signals measured by laser Doppler vibrometry (LDV). The method has been optimised for LDV signals measured on bearings of universal electric motors and applied to quality control of washing machines. Inherent problems of LDV are addressed, particularly the speckle noise occurring when rough surfaces are measured. The presence of speckle noise is detected using a new scalar indicator kurtosis ratio (KR), specifically designed to quantify the amount of random impulses generated by this noise. The KR is a ratio of the standard kurtosis and a robust estimate of kurtosis, thus indicating the outliers in the data. Since it is inefficient to reject the signals affected by the speckle noise, an algorithm for selecting an undistorted portion of a signal is proposed. The algorithm operates in the time domain and is thus fast and simple. The algorithm includes band-pass filtering and segmentation of the signal, as well as thresholding of the KR computed for each filtered signal segment. Algorithm parameters are discussed in detail and instructions for optimisation are provided. Experimental results demonstrate that speckle noise is effectively avoided in severely distorted signals, thus improving the signal-to-noise ratio (SNR) significantly. Typical faults are finally detected using squared envelope analysis. It is also shown that the KR of the band-pass filtered signal is related to the spectral kurtosis (SK).
Measurements of water uptake of maize roots: the key function of lateral roots
NASA Astrophysics Data System (ADS)
Ahmed, M. A.; Zarebanadkouki, M.; Kroener, E.; Kaestner, A.; Carminati, A.
2014-12-01
Maize (Zea mays L.) is one of the most important crop worldwide. Despite its importance, there is limited information on the function of different root segments and root types of maize in extracting water from soils. Therefore, the aim of this study was to investigate locations of root water uptake in maize. We used neutron radiography to: 1) image the spatial distribution of maize roots in soil and 2) trace the transport of injected deuterated water (D2O) in soil and roots. Maizes were grown in aluminum containers (40×38×1 cm) filled with a sandy soil. When the plants were 16 days old, we injected D2O into selected soil regions containing primary, seminal and lateral roots. The experiments were performed during the day (transpiring plants) and night (not transpiring plants). The transport of D2O into roots was simulated using a new convection-diffusion numerical model of D2O transport into roots. By fitting the observed D2O transport we quantified the diffusional permeability and the water uptake of the different root segments. The maize root architecture consisted of a primary root, 4-5 seminal roots and many lateral roots connected to the primary and seminal roots. Laterals emerged from the proximal 15 cm of the primary and seminal roots. Water uptake occurred primarily in lateral roots. Lateral roots had the highest diffusional permeability (9.4×10-7), which was around six times higher that the diffusional permeability of the old seminal segments (1.4×10-7), and two times higher than the diffusional permeability of the young seminal segments (4.7×10-7). The radial flow of D2O into the lateral (6.7×10-5 ) was much higher than in the young seminal roots (1.1×10-12). The radial flow of D2O into the old seminal was negligible. We concluded that the function of the primary and seminal roots was to collect water from the lateral roots and transport it to the shoot. A maize root system with lateral roots branching from deep primary and seminal roots would be efficient in extracting water from the subsoil and better tolerate periods of water shortage. However, in this case the xylem axial resistance could be the limiting factor for the uptake of water.
Improvement of a picking algorithm real-time P-wave detection by kurtosis
NASA Astrophysics Data System (ADS)
Ishida, H.; Yamada, M.
2016-12-01
Earthquake early warning (EEW) requires fast and accurate P-wave detection. The current EEW system in Japan uses the STA/LTAalgorithm (Allen, 1978) to detect P-wave arrival.However, some stations did not trigger during the 2011 Great Tohoku Earthquake due to the emergent onset. In addition, accuracy of the P-wave detection is very important: on August 1, 2016, the EEW issued a false alarm with M9 in Tokyo region due to a thunder noise.To solve these problems, we use a P-wave detection method using kurtosis statistics. It detects the change of statistic distribution of the waveform amplitude. This method was recently developed (Saragiotis et al., 2002) and used for off-line analysis such as making seismic catalogs. To apply this method for EEW, we need to remove an acausal calculation and enable a real-time processing. Here, we propose a real-time P-wave detection method using kurtosis statistics with a noise filter.To avoid false triggering by a noise, we incorporated a simple filter to classify seismic signal and noise. Following Kong et al. (2016), we used the interquartilerange and zero cross rate for the classification. The interquartile range is an amplitude measure that is equal to the middle 50% of amplitude in a certain time window. The zero cross rate is a simple frequency measure that counts the number of times that the signal crosses baseline zero. A discriminant function including these measures was constructed by the linear discriminant analysis.To test this kurtosis method, we used strong motion records for 62 earthquakes between April, 2005 and July, 2015, which recorded the seismic intensity greater equal to 6 lower in the JMA intensity scale. The records with hypocentral distance < 200km were used for the analysis. An attached figure shows the error of P-wave detection speed for STA/LTA and kurtosis methods against manual picks. It shows that the median error is 0.13 sec and 0.035 sec for STA/LTA and kurtosis method. The kurtosis method tends to be more sensitive to small changes in amplitude.Our approach will contribute to improve the accuracy of source location determination of earthquakes and improve the shaking intensity estimation for an earthquake early warning.
Lattice continuum and diffusional creep.
Mesarovic, Sinisa Dj
2016-04-01
Diffusional creep is characterized by growth/disappearance of lattice planes at the crystal boundaries that serve as sources/sinks of vacancies, and by diffusion of vacancies. The lattice continuum theory developed here represents a natural and intuitive framework for the analysis of diffusion in crystals and lattice growth/loss at the boundaries. The formulation includes the definition of the Lagrangian reference configuration for the newly created lattice, the transport theorem and the definition of the creep rate tensor for a polycrystal as a piecewise uniform, discontinuous field. The values associated with each crystalline grain are related to the normal diffusional flux at grain boundaries. The governing equations for Nabarro-Herring creep are derived with coupled diffusion and elasticity with compositional eigenstrain. Both, bulk diffusional dissipation and boundary dissipation accompanying vacancy nucleation and absorption, are considered, but the latter is found to be negligible. For periodic arrangements of grains, diffusion formally decouples from elasticity but at the cost of a complicated boundary condition. The equilibrium of deviatorically stressed polycrystals is impossible without inclusion of interface energies. The secondary creep rate estimates correspond to the standard Nabarro-Herring model, and the volumetric creep is small. The initial (primary) creep rate is estimated to be much larger than the secondary creep rate.
Lattice continuum and diffusional creep
NASA Astrophysics Data System (ADS)
Mesarovic, Sinisa Dj.
2016-04-01
Diffusional creep is characterized by growth/disappearance of lattice planes at the crystal boundaries that serve as sources/sinks of vacancies, and by diffusion of vacancies. The lattice continuum theory developed here represents a natural and intuitive framework for the analysis of diffusion in crystals and lattice growth/loss at the boundaries. The formulation includes the definition of the Lagrangian reference configuration for the newly created lattice, the transport theorem and the definition of the creep rate tensor for a polycrystal as a piecewise uniform, discontinuous field. The values associated with each crystalline grain are related to the normal diffusional flux at grain boundaries. The governing equations for Nabarro-Herring creep are derived with coupled diffusion and elasticity with compositional eigenstrain. Both, bulk diffusional dissipation and boundary dissipation accompanying vacancy nucleation and absorption, are considered, but the latter is found to be negligible. For periodic arrangements of grains, diffusion formally decouples from elasticity but at the cost of a complicated boundary condition. The equilibrium of deviatorically stressed polycrystals is impossible without inclusion of interface energies. The secondary creep rate estimates correspond to the standard Nabarro-Herring model, and the volumetric creep is small. The initial (primary) creep rate is estimated to be much larger than the secondary creep rate.
Statistical variances of diffusional properties from ab initio molecular dynamics simulations
NASA Astrophysics Data System (ADS)
He, Xingfeng; Zhu, Yizhou; Epstein, Alexander; Mo, Yifei
2018-12-01
Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.
Jia, Feng; Lei, Yaguo; Shan, Hongkai; Lin, Jing
2015-01-01
The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is proposed based on maximum correlated kurtosis deconvolution (MCKD). The proposed method combines the ability of MCKD in indicating the periodic fault transients and the ability of SK in locating these transients in the frequency domain. A simulation signal overwhelmed by heavy noise is used to demonstrate the effectiveness of the proposed method. The results show that MCKD is beneficial to clarify the periodic impulse components of the bearing signals, and the method is able to detect the resonant frequency band of the signal and extract its fault characteristic frequency. Through analyzing actual vibration signals collected from wind turbines and hot strip rolling mills, we confirm that by using the proposed method, it is possible to extract fault characteristics and diagnose early faults of rolling element bearings. Based on the comparisons with the SK method, it is verified that the proposed method is more suitable to diagnose early faults of rolling element bearings. PMID:26610501
Trackside acoustic diagnosis of axle box bearing based on kurtosis-optimization wavelet denoising
NASA Astrophysics Data System (ADS)
Peng, Chaoyong; Gao, Xiaorong; Peng, Jianping; Wang, Ai
2018-04-01
As one of the key components of railway vehicles, the operation condition of the axle box bearing has a significant effect on traffic safety. The acoustic diagnosis is more suitable than vibration diagnosis for trackside monitoring. The acoustic signal generated by the train axle box bearing is an amplitude modulation and frequency modulation signal with complex train running noise. Although empirical mode decomposition (EMD) and some improved time-frequency algorithms have proved to be useful in bearing vibration signal processing, it is hard to extract the bearing fault signal from serious trackside acoustic background noises by using those algorithms. Therefore, a kurtosis-optimization-based wavelet packet (KWP) denoising algorithm is proposed, as the kurtosis is the key indicator of bearing fault signal in time domain. Firstly, the geometry based Doppler correction is applied to signals of each sensor, and with the signal superposition of multiple sensors, random noises and impulse noises, which are the interference of the kurtosis indicator, are suppressed. Then, the KWP is conducted. At last, the EMD and Hilbert transform is applied to extract the fault feature. Experiment results indicate that the proposed method consisting of KWP and EMD is superior to the EMD.
Higher order statistical analysis of /x/ in male speech.
Orr, M C; Lithgow, B
2005-03-01
This paper presents a study of kurtosis analysis for the sound /x/ in male speech, /x/ is the sound of the 'o' at the end of words such as 'ago'. The sound analysed for this paper came from the Australian National Database of Spoken Language, more specifically the male speaker 17. The /x/ was isolated and extracted from the database by the author in a quiet booth using standard multimedia software. A 5 millisecond window was used for the analysis as it was shown previously by the author to be the most appropriate size for speech phoneme analysis. The significance of the research presented here is shown in the results where a majority of coefficients had a platykurtic (kurtosis between 0 and 3) value as opposed to the previously held leptokurtic (kurtosis > 3) belief.
Transition to collective oscillations in finite Kuramoto ensembles
NASA Astrophysics Data System (ADS)
Peter, Franziska; Pikovsky, Arkady
2018-03-01
We present an alternative approach to finite-size effects around the synchronization transition in the standard Kuramoto model. Our main focus lies on the conditions under which a collective oscillatory mode is well defined. For this purpose, the minimal value of the amplitude of the complex Kuramoto order parameter appears as a proper indicator. The dependence of this minimum on coupling strength varies due to sampling variations and correlates with the sample kurtosis of the natural frequency distribution. The skewness of the frequency sample determines the frequency of the resulting collective mode. The effects of kurtosis and skewness hold in the thermodynamic limit of infinite ensembles. We prove this by integrating a self-consistency equation for the complex Kuramoto order parameter for two families of distributions with controlled kurtosis and skewness, respectively.
Probing turbulence with infrared observations in OMC1
NASA Astrophysics Data System (ADS)
Gustafsson, M.; Field, D.; Lemaire, J. L.; Pijpers, F. P.
2006-01-01
A statistical analysis is presented of the turbulent velocity structure in the Orion Molecular Cloud at scales ranging from 70 AU to 3×104 AU. Results are based on IR Fabry-Perot interferometric observations of shock and photon-excited H2 in the K-band S(1) v=1{-}0 line at 2.121 μm and refer to the dynamical characteristics of warm perturbed gas. Data consist of a spatially resolved image with a measured velocity for each resolution limited region (70 AU× 70 AU) in the image. The effect of removal of apparent large scale velocity gradients is discussed and the conclusion drawn that these apparent gradients represent part of the turbulent cascade and should remain within the data. Using our full data set, observations establish that the Larson size-linewidth relation is obeyed to the smallest scales studied here extending the range of validity of this relationship by nearly 2 orders of magnitude. The velocity probability distribution function (PDF) is constructed showing extended exponential wings, providing evidence of intermittency, further supported by the skewness (third moment) and kurtosis (fourth moment) of the velocity distribution. Variance and kurtosis of the PDF of velocity differences are constructed as a function of lag. The variance shows an approximate power law dependence on lag, with exponent significantly lower than the Kolmogorov value, and with deviations below 2000 AU which are attributed to outflows and possibly disk structures associated with low mass star formation within OMC1. The kurtosis shows strong deviation from a Gaussian velocity field, providing evidence of velocity correlations at small lags. Results agree accurately with semi-empirical simulations in Eggers & Wang (1998). In addition, 170 individual H2 emitting clumps have been analysed with sizes between 500 and 2200 AU. These show considerable diversity with regard to PDFs and variance functions (related to second order structure functions) displaying a variety of shapes of the PDF and different values of the scaling exponent within a restricted spatial region. However, a region associated with an outflow from a deeply embedded O-star shows high values of the scaling exponent of the variance function, representing a strong segregation of high and low exponent clumps. Our analysis constitutes the first characterization of the turbulent velocity field at the scale of star formation and provide a dataset which models of star-forming regions should aim to reproduce.
Nakajo, Masanori; Fukukura, Yoshihiko; Hakamada, Hiroto; Yoneyama, Tomohide; Kamimura, Kiyohisa; Nagano, Satoshi; Nakajo, Masayuki; Yoshiura, Takashi
2018-02-22
Apparent diffusion coefficient (ADC) histogram analyses have been used to differentiate tumor grades and predict therapeutic responses in various anatomic sites with moderate success. To determine the ability of diffusion-weighted imaging (DWI) with a whole-tumor ADC histogram analysis to differentiate benign peripheral neurogenic tumors (BPNTs) from soft tissue sarcomas (STSs). Retrospective study, single institution. In all, 25 BPNTs and 31 STSs. Two-b value DWI (b-values = 0, 1000s/mm 2 ) was at 3.0T. The histogram parameters of whole-tumor for ADC were calculated by two radiologists and compared between BPNTs and STSs. Nonparametric tests were performed for comparisons between BPNTs and STSs. P < 0.05 was considered statistically significant. The ability of each parameter to differentiate STSs from BPNTs was evaluated using area under the curve (AUC) values derived from a receiver operating characteristic curve analysis. The mean ADC and all percentile parameters were significantly lower in STSs than in BPNTs (P < 0.001-0.009), with AUCs of 0.703-0.773. However, the coefficient of variation (P = 0.020 and AUC = 0.682) and skewness (P = 0.012 and AUC = 0.697) were significantly higher in STSs than in BPNTs. Kurtosis (P = 0.295) and entropy (P = 0.604) did not differ significantly between BPNTs and STSs. Whole-tumor ADC histogram parameters except kurtosis and entropy differed significantly between BPNTs and STSs. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.
Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao
2018-04-01
To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (p<0.05), with the exception of between K 10th , K 90th and histological grades. In contrast, significant negative correlations were observed between 25th, 50th percentiles and mean values of ADC and D, as well as ADC 10th , with tumour T stages (p< 0.05). Meanwhile, lower 75th and 90th percentiles of ADC and D values were also correlated inversely with nodal involvement (p< 0.05). K mean showed a relatively higher area under the curve (AUC) and higher specificity than other percentiles for differentiation of lesions with nodal involvement. DKI metrics with whole-tumour volume histogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.
Poussaint, Tina Young; Vajapeyam, Sridhar; Ricci, Kelsey I.; Panigrahy, Ashok; Kocak, Mehmet; Kun, Larry E.; Boyett, James M.; Pollack, Ian F.; Fouladi, Maryam
2016-01-01
Background Diffuse intrinsic pontine glioma (DIPG) is associated with poor survival regardless of therapy. We used volumetric apparent diffusion coefficient (ADC) histogram metrics to determine associations with progression-free survival (PFS) and overall survival (OS) at baseline and after radiation therapy (RT). Methods Baseline and post-RT quantitative ADC histograms were generated from fluid-attenuated inversion recovery (FLAIR) images and enhancement regions of interest. Metrics assessed included number of peaks (ie, unimodal or bimodal), mean and median ADC, standard deviation, mode, skewness, and kurtosis. Results Based on FLAIR images, the majority of tumors had unimodal peaks with significantly shorter average survival. Pre-RT FLAIR mean, mode, and median values were significantly associated with decreased risk of progression; higher pre-RT ADC values had longer PFS on average. Pre-RT FLAIR skewness and standard deviation were significantly associated with increased risk of progression; higher pre-RT FLAIR skewness and standard deviation had shorter PFS. Nonenhancing tumors at baseline showed higher ADC FLAIR mean values, lower kurtosis, and higher PFS. For enhancing tumors at baseline, bimodal enhancement histograms had much worse PFS and OS than unimodal cases and significantly lower mean peak values. Enhancement in tumors only after RT led to significantly shorter PFS and OS than in patients with baseline or no baseline enhancement. Conclusions ADC histogram metrics in DIPG demonstrate significant correlations between diffusion metrics and survival, with lower diffusion values (increased cellularity), increased skewness, and enhancement associated with shorter survival, requiring future investigations in large DIPG clinical trials. PMID:26487690
An Automated Energy Detection Algorithm Based on Kurtosis-Histogram Excision
2018-01-01
ARL-TR-8269 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Kurtosis-Histogram Excision...needed. Do not return it to the originator. ARL-TR-8269 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources
On the Response of a Nonlinear Structure to High Kurtosis Non-Gaussian Random Loadings
NASA Technical Reports Server (NTRS)
Rizzi, Stephen A.; Przekop, Adam; Turner, Travis L.
2011-01-01
This paper is a follow-on to recent work by the authors in which the response and high-cycle fatigue of a nonlinear structure subject to non-Gaussian loadings was found to vary markedly depending on the nature of the loading. There it was found that a non-Gaussian loading having a steady rate of short-duration, high-excursion peaks produced essentially the same response as would have been incurred by a Gaussian loading. In contrast, a non-Gaussian loading having the same kurtosis, but with bursts of high-excursion peaks was found to elicit a much greater response. This work is meant to answer the question of when consideration of a loading probability distribution other than Gaussian is important. The approach entailed nonlinear numerical simulation of a beam structure under Gaussian and non-Gaussian random excitations. Whether the structure responded in a Gaussian or non-Gaussian manner was determined by adherence to, or violations of, the Central Limit Theorem. Over a practical range of damping, it was found that the linear response to a non-Gaussian loading was Gaussian when the period of the system impulse response is much greater than the rate of peaks in the loading. Lower damping reduced the kurtosis, but only when the linear response was non-Gaussian. In the nonlinear regime, the response was found to be non-Gaussian for all loadings. The effect of a spring-hardening type of nonlinearity was found to limit extreme values and thereby lower the kurtosis relative to the linear response regime. In this case, lower damping gave rise to greater nonlinearity, resulting in lower kurtosis than a higher level of damping.
Experimental Investigations on Two Potential Sound Diffuseness Measures in Enclosures
NASA Astrophysics Data System (ADS)
Bai, Xin
This study investigates two different approaches to measure sound field diffuseness in enclosures from monophonic room impulse responses. One approach quantifies sound field diffuseness in enclosures by calculating the kurtosis of the pressure samples of room impulse responses. Kurtosis is a statistical measure that is known to describe the peakedness or tailedness of the distribution of a set of data. High kurtosis indicates low diffuseness of the sound field of interest. The other one relies on multifractal detrended fluctuation analysis which is a way to evaluate the statistical self-affinity of a signal to measure diffuseness. To test these two approaches, room impulse responses are obtained under varied room-acoustic diffuseness configurations, achieved by using varied degrees of diffusely reflecting interior surfaces. This paper will analyze experimentally measured monophonic room impulse responses, and discuss results from these two approaches.
Lattice continuum and diffusional creep
2016-01-01
Diffusional creep is characterized by growth/disappearance of lattice planes at the crystal boundaries that serve as sources/sinks of vacancies, and by diffusion of vacancies. The lattice continuum theory developed here represents a natural and intuitive framework for the analysis of diffusion in crystals and lattice growth/loss at the boundaries. The formulation includes the definition of the Lagrangian reference configuration for the newly created lattice, the transport theorem and the definition of the creep rate tensor for a polycrystal as a piecewise uniform, discontinuous field. The values associated with each crystalline grain are related to the normal diffusional flux at grain boundaries. The governing equations for Nabarro–Herring creep are derived with coupled diffusion and elasticity with compositional eigenstrain. Both, bulk diffusional dissipation and boundary dissipation accompanying vacancy nucleation and absorption, are considered, but the latter is found to be negligible. For periodic arrangements of grains, diffusion formally decouples from elasticity but at the cost of a complicated boundary condition. The equilibrium of deviatorically stressed polycrystals is impossible without inclusion of interface energies. The secondary creep rate estimates correspond to the standard Nabarro–Herring model, and the volumetric creep is small. The initial (primary) creep rate is estimated to be much larger than the secondary creep rate. PMID:27274696
Shoga, Janty S; Graham, Brian T; Wang, Liyun; Price, Christopher
2017-10-01
Articular cartilage is an avascular tissue; diffusive transport is critical for its homeostasis. While numerous techniques have been used to quantify diffusivity within porous, hydrated tissues and tissue engineered constructs, these techniques have suffered from issues regarding invasiveness and spatial resolution. In the present study, we implemented and compared two separate correlation spectroscopy techniques, fluorescence correlation spectroscopy (FCS) and raster image correlation spectroscopy (RICS), for the direct, and minimally-invasive quantification of fluorescent solute diffusion in agarose and articular cartilage. Specifically, we quantified the diffusional properties of fluorescein and Alexa Fluor 488-conjugated dextrans (3k and 10k) in aqueous solutions, agarose gels of varying concentration (i.e. 1, 3, 5%), and in different zones of juvenile bovine articular cartilage explants (i.e. superficial, middle, and deep). In agarose, properties of solute diffusion obtained via FCS and RICS were inversely related to molecule size, gel concentration, and applied strain. In cartilage, the diffusional properties of solutes were similarly dependent upon solute size, cartilage zone, and compressive strain; findings that agree with work utilizing other quantification techniques. In conclusion, this study established the utility of FCS and RICS as simple and minimally invasive techniques for quantifying microscale solute diffusivity within agarose constructs and articular cartilage explants.
Choosing the Best Correction Formula for the Pearson r[superscript 2] Effect Size
ERIC Educational Resources Information Center
Skidmore, Susan Troncoso; Thompson, Bruce
2011-01-01
In the present Monte Carlo simulation study, the authors compared bias and precision of 7 sampling error corrections to the Pearson r[superscript 2] under 6 x 3 x 6 conditions (i.e., population ρ values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9, respectively; population shapes normal, skewness = kurtosis = 1, and skewness = -1.5 with kurtosis =…
Two-Dimensional Hermite Filters Simplify the Description of High-Order Statistics of Natural Images.
Hu, Qin; Victor, Jonathan D
2016-09-01
Natural image statistics play a crucial role in shaping biological visual systems, understanding their function and design principles, and designing effective computer-vision algorithms. High-order statistics are critical for conveying local features, but they are challenging to study - largely because their number and variety is large. Here, via the use of two-dimensional Hermite (TDH) functions, we identify a covert symmetry in high-order statistics of natural images that simplifies this task. This emerges from the structure of TDH functions, which are an orthogonal set of functions that are organized into a hierarchy of ranks. Specifically, we find that the shape (skewness and kurtosis) of the distribution of filter coefficients depends only on the projection of the function onto a 1-dimensional subspace specific to each rank. The characterization of natural image statistics provided by TDH filter coefficients reflects both their phase and amplitude structure, and we suggest an intuitive interpretation for the special subspace within each rank.
Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis
NASA Astrophysics Data System (ADS)
Dion, J.-L.; Tawfiq, I.; Chevallier, G.
2012-01-01
This work is a contribution in the field of Operational Modal Analysis to identify the modal parameters of mechanical structures using only measured responses. The study deals with structural responses coupled with harmonic components amplitude and frequency modulated in a short range, a common combination for mechanical systems with engines and other rotating machines in operation. These harmonic components generate misleading data interpreted erroneously by the classical methods used in OMA. The present work attempts to differentiate maxima in spectra stemming from harmonic components and structural modes. The detection method proposed is based on the so-called Optimized Spectral Kurtosis and compared with others definitions of Spectral Kurtosis described in the literature. After a parametric study of the method, a critical study is performed on numerical simulations and then on an experimental structure in operation in order to assess the method's performance.
Zhao, Yi-Ming; Qiu, Wei; Zeng, Lin; Chen, Shan-Song; Cheng, Xiao-Ru; Davis, Robert I; Hamernik, Roger P
2010-08-01
Develop dose-response relations for two groups of industrial workers exposed to Gaussian or non-Gaussian (complex) types of continuous noises and to investigate what role, if any, the kurtosis statistic can play in the evaluation of industrial noise-induced hearing loss (NIHL). Audiometric and noise exposure data were acquired on a population (N = 195) of screened workers from a textile manufacturing plant and a metal fabrication facility located in Henan province of China. Thirty-two of the subjects were exposed to non-Gaussian (non-G) noise and 163 were exposed to a Gaussian (G) continuous noise. Each subject was given a general physical and an otologic examination. Hearing threshold levels (0.5-8.0 kHz) were age adjusted (ISI-1999) and the prevalence of NIHL at 3, 4, or 6 kHz was determined. The kurtosis metric, which is sensitive to the peak and temporal characteristics of a noise, was introduced into the calculation of the cumulative noise exposure metric. Using the prevalence of hearing loss and the cumulative noise exposure metric, a dose-response relation for the G and non-G noise-exposed groups was constructed. An analysis of the noise environments in the two plants showed that the noise exposures in the textile plant were of a Gaussian type with an Leq(A)8hr that varied from 96 to 105 dB whereas the exposures in the metal fabrication facility with an Leq(A)8hr = 95 dB were of a non-G type containing high levels (up to 125 dB peak SPL) of impact noise. The kurtosis statistic was used to quantify the deviation of the non-G noise environment from the Gaussian. The dose-response relation for the non-G noise-exposed subjects showed a higher prevalence of hearing loss for a comparable cumulative noise exposure than did the G noise-exposed subjects. By introducing the kurtosis variable into the temporal component of the cumulative noise exposure calculation, the two dose-response curves could be made to overlap, essentially yielding an equivalent noise-induced effect for the two study groups. For the same exposure level, the prevalence of NIHL is greater in workers exposed to non-G noise environments than for workers exposed to G noise. The kurtosis metric may be a reasonable candidate for use in modifying exposure level calculations that are used to estimate the risk of NIHL from any type of noise exposure environment. However, studies involving a large number of workers with well-documented exposures are needed before a relation between a metric such as the kurtosis and the risk of hearing loss can be refined.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tyagi, N; Sutton, E; Hunt, M
Purpose: Capsular contracture (CC) is a serious complication in patients receiving implant-based reconstruction for breast cancer. The goal of this study was to identify image-based correlates of CC using MRI imaging in breast cancer patients who received both MRI and clinical evaluation following reconstructive surgery. Methods: We analyzed a retrospective dataset of 50 patients who had both a diagnostic MR and a plastic surgeon’s evaluations of CC score (Baker’s score) within a six month period following mastectomy and reconstructive surgery. T2w sagittal MRIs (TR/TE = 3500/102 ms, slice thickness = 4 mm) were used for morphological shape features (roundness, eccentricity,more » solidity, extent and ratio-length) and histogram features (median, skewness and kurtosis) of the implant and the pectoralis muscle overlying the implant. Implant and pectoralis muscles were segmented in 3D using Computation Environment for Radiological Research (CERR) and shape and histogram features were calculated as a function of Baker’s score. Results: Shape features such as roundness and eccentricity were statistically significant in differentiating grade 1 and grade 2 (p = 0.009; p = 0.06) as well as grade 1 and grade 3 CC (p = 0.001; p = 0.006). Solidity and extent were statistically significant in differentiating grade 1 and grade 3 CC (p = 0.04; p = 0.04). Ratio-length was statistically significant in differentiating all grades of CC except grade 2 and grade 3 that showed borderline significance (p = 0.06). The muscle thickness, median intensity and kurtosis were significant in differentiating between grade 1 and grade 3 (p = 0.02), grade 1 and grade 2 (p = 0.03) and grade 1 and grade 3 (p = 0.01) respectively. Conclusion: Morphological shape features described on MR images were associated with the severity of CC. MRI may be important in objectively evaluating outcomes in breast cancer patients who undergo implant reconstruction.« less
Sours, Chandler; Raghavan, Prashant; Medina, Alexandre E.; Roys, Steven; Jiang, Li; Zhuo, Jiachen
2017-01-01
Abstract Severe and moderate traumatic brain injury (sTBI) often results in long-term cognitive deficits such as reduced processing speed and attention. The intraparietal sulcus (IPS) is a neocortical structure that plays a crucial role in the deeply interrelated processes of multi-sensory processing and top down attention. Therefore, we hypothesized that disruptions in the functional and structural connections of the IPS may play a role in the development of such deficits. To examine these connections, we used resting state magnetic resonance imaging (rsfMRI and diffusion kurtosis imaging (DKI) in a cohort of 27 patients with sTBI (29.3 ± 8.9 years) and 27 control participants (29.8 ± 10.3 years). Participants were prospectively recruited and received rsfMRI and neuropsychological assessments including the Automated Neuropsychological Assessment Metrics (ANAM) at greater than 6 months post-injury. A subset of participants received a DKI scan. Results suggest that patients with sTBI performed worse than control participants on multiple subtests of the ANAM suggesting reduced cognitive performance. Reduced resting state functional connectivity between the IPS and cortical regions associated with multi-sensory processing and the dorsal attention network was observed in the patients with sTBI. The patients also showed reduced structural integrity of the superior longitudinal fasciculus (SLF), a key white matter tract connecting the IPS to anterior frontal areas, as measured by reduced mean kurtosis (MK) and fractional anisotropy (FA) and increased mean diffusivity (MD). Further, this reduced structural integrity of the SLF was associated with a reduction in overall cognitive performance. These findings suggest that disruptions in the structural and functional connectivity of the IPS may contribute to chronic cognitive deficits experienced by these patients. PMID:27931179
Billiet, Thibo; Mädler, Burkhard; D'Arco, Felice; Peeters, Ronald; Deprez, Sabine; Plasschaert, Ellen; Leemans, Alexander; Zhang, Hui; den Bergh, Bea Van; Vandenbulcke, Mathieu; Legius, Eric; Sunaert, Stefan; Emsell, Louise
2014-01-01
The histopathological basis of "unidentified bright objects" (UBOs) (hyperintense regions seen on T2-weighted magnetic resonance (MR) brain scans in neurofibromatosis-1 (NF1)) remains unclear. New in vivo MRI-based techniques (multi-exponential T2 relaxation (MET2) and diffusion MR imaging (dMRI)) provide measures relating to microstructural change. We combined these methods and present previously unreported data on in vivo UBO microstructure in NF1. 3-Tesla dMRI data were acquired on 17 NF1 patients, covering 30 white matter UBOs. Diffusion tensor, kurtosis and neurite orientation and dispersion density imaging parameters were calculated within UBO sites and in contralateral normal appearing white matter (cNAWM). Analysis of MET2 parameters was performed on 24 UBO-cNAWM pairs. No significant alterations in the myelin water fraction and intra- and extracellular (IE) water fraction were found. Mean T2 time of IE water was significantly higher in UBOs. UBOs furthermore showed increased axial, radial and mean diffusivity, and decreased fractional anisotropy, mean kurtosis and neurite density index compared to cNAWM. Neurite orientation dispersion and isotropic fluid fraction were unaltered. Our results suggest that demyelination and axonal degeneration are unlikely to be present in UBOs, which appear to be mainly caused by a shift towards a higher T2-value of the intra- and extracellular water pool. This may arise from altered microstructural compartmentalization, and an increase in 'extracellular-like', intracellular water, possibly due to intramyelinic edema. These findings confirm the added value of combining dMRI and MET2 to characterize the microstructural basis of T2 hyperintensities in vivo.
Sours, Chandler; Raghavan, Prashant; Medina, Alexandre E; Roys, Steven; Jiang, Li; Zhuo, Jiachen; Gullapalli, Rao P
2017-04-01
Severe and moderate traumatic brain injury (sTBI) often results in long-term cognitive deficits such as reduced processing speed and attention. The intraparietal sulcus (IPS) is a neocortical structure that plays a crucial role in the deeply interrelated processes of multi-sensory processing and top down attention. Therefore, we hypothesized that disruptions in the functional and structural connections of the IPS may play a role in the development of such deficits. To examine these connections, we used resting state magnetic resonance imaging (rsfMRI and diffusion kurtosis imaging (DKI) in a cohort of 27 patients with sTBI (29.3 ± 8.9 years) and 27 control participants (29.8 ± 10.3 years). Participants were prospectively recruited and received rsfMRI and neuropsychological assessments including the Automated Neuropsychological Assessment Metrics (ANAM) at greater than 6 months post-injury. A subset of participants received a DKI scan. Results suggest that patients with sTBI performed worse than control participants on multiple subtests of the ANAM suggesting reduced cognitive performance. Reduced resting state functional connectivity between the IPS and cortical regions associated with multi-sensory processing and the dorsal attention network was observed in the patients with sTBI. The patients also showed reduced structural integrity of the superior longitudinal fasciculus (SLF), a key white matter tract connecting the IPS to anterior frontal areas, as measured by reduced mean kurtosis (MK) and fractional anisotropy (FA) and increased mean diffusivity (MD). Further, this reduced structural integrity of the SLF was associated with a reduction in overall cognitive performance. These findings suggest that disruptions in the structural and functional connectivity of the IPS may contribute to chronic cognitive deficits experienced by these patients.
The statistical properties and possible causes of polar motion prediction errors
NASA Astrophysics Data System (ADS)
Kosek, Wieslaw; Kalarus, Maciej; Wnek, Agnieszka; Zbylut-Gorska, Maria
2015-08-01
The pole coordinate data predictions from different prediction contributors of the Earth Orientation Parameters Combination of Prediction Pilot Project (EOPCPPP) were studied to determine the statistical properties of polar motion forecasts by looking at the time series of differences between them and the future IERS pole coordinates data. The mean absolute errors, standard deviations as well as the skewness and kurtosis of these differences were computed together with their error bars as a function of prediction length. The ensemble predictions show a little smaller mean absolute errors or standard deviations however their skewness and kurtosis values are similar as the for predictions from different contributors. The skewness and kurtosis enable to check whether these prediction differences satisfy normal distribution. The kurtosis values diminish with the prediction length which means that the probability distribution of these prediction differences is becoming more platykurtic than letptokurtic. Non zero skewness values result from oscillating character of these differences for particular prediction lengths which can be due to the irregular change of the annual oscillation phase in the joint fluid (atmospheric + ocean + land hydrology) excitation functions. The variations of the annual oscillation phase computed by the combination of the Fourier transform band pass filter and the Hilbert transform from pole coordinates data as well as from pole coordinates model data obtained from fluid excitations are in a good agreement.
NASA Astrophysics Data System (ADS)
Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei
2018-03-01
A time varying filtering based empirical mode decomposition (EMD) (TVF-EMD) method was proposed recently to solve the mode mixing problem of EMD method. Compared with the classical EMD, TVF-EMD was proven to improve the frequency separation performance and be robust to noise interference. However, the decomposition parameters (i.e., bandwidth threshold and B-spline order) significantly affect the decomposition results of this method. In original TVF-EMD method, the parameter values are assigned in advance, which makes it difficult to achieve satisfactory analysis results. To solve this problem, this paper develops an optimized TVF-EMD method based on grey wolf optimizer (GWO) algorithm for fault diagnosis of rotating machinery. Firstly, a measurement index termed weighted kurtosis index is constructed by using kurtosis index and correlation coefficient. Subsequently, the optimal TVF-EMD parameters that match with the input signal can be obtained by GWO algorithm using the maximum weighted kurtosis index as objective function. Finally, fault features can be extracted by analyzing the sensitive intrinsic mode function (IMF) owning the maximum weighted kurtosis index. Simulations and comparisons highlight the performance of TVF-EMD method for signal decomposition, and meanwhile verify the fact that bandwidth threshold and B-spline order are critical to the decomposition results. Two case studies on rotating machinery fault diagnosis demonstrate the effectiveness and advantages of the proposed method.
O’Connell, Caitlin; Ho, Leon C.; Murphy, Matthew C.; Conner, Ian P.; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C.
2016-01-01
Human visual performance has been observed to exhibit superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine if the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI (DKI), respectively in 15 healthy individuals at 3 Tesla. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In DKI, the brain regions mapping to the lower visual field exhibited higher mean kurtosis but not fractional anisotropy or mean diffusivity when compared to the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing. PMID:27631541
Analysis of financial time series using multiscale entropy based on skewness and kurtosis
NASA Astrophysics Data System (ADS)
Xu, Meng; Shang, Pengjian
2018-01-01
There is a great interest in studying dynamic characteristics of the financial time series of the daily stock closing price in different regions. Multi-scale entropy (MSE) is effective, mainly in quantifying the complexity of time series on different time scales. This paper applies a new method for financial stability from the perspective of MSE based on skewness and kurtosis. To better understand the superior coarse-graining method for the different kinds of stock indexes, we take into account the developmental characteristics of the three continents of Asia, North America and European stock markets. We study the volatility of different financial time series in addition to analyze the similarities and differences of coarsening time series from the perspective of skewness and kurtosis. A kind of corresponding relationship between the entropy value of stock sequences and the degree of stability of financial markets, were observed. The three stocks which have particular characteristics in the eight piece of stock sequences were discussed, finding the fact that it matches the result of applying the MSE method to showing results on a graph. A comparative study is conducted to simulate over synthetic and real world data. Results show that the modified method is more effective to the change of dynamics and has more valuable information. The result is obtained at the same time, finding the results of skewness and kurtosis discrimination is obvious, but also more stable.
NASA Astrophysics Data System (ADS)
Carlson, William D.
1989-09-01
The spatial disposition, compositional zoning profiles, and size distributions of garnet crystals in 11 specimens of pelitic schist from the Picuris Range of New Mexico (USA) demonstrate that the kinetics of intergranular diffusion controlled the nucleation and growth mechanisms of porphyroblasts in these rocks. An ordered disposition of garnet centers and a significant correlation between crystal radius and near-neighbor distances manifest suppressed nucleation of new crystals in diffusionally depleted zones surrounding pre-existing crystals. Compositional zoning profiles require diffusionally controlled growth, the rate of which increases exponentially as temperature increases with time; an acceleration factor for growth rate can be estimated from a comparison of compositional profiles for crystals of different sizes in each specimen. Crystal size distributions are interpreted as the result of nucleation rates that accelerate exponentially with increasing temperature early in the crystallization process, but decline in the later stages because of suppression effects in the vicinity of earlier-formed nuclei. Simulations of porphyroblast crystallization, based upon thermally accelerated diffusionally influenced nucleation kinetics and diffusionally controlled growth kinetics, quantitatively replicate textural relations in the rocks. The simulations employ only two variable parameters, which are evaluated by fitting of crystal size distributions. Both have physical significance. The first is an acceleration factor for nucleation, with a magnitude reflecting the prograde increase during the nucleation interval of the chemical affinity for the reaction in undepleted regions of the rock. The second is a measure of the relative sizes of the porphyroblast and the diffusionally depleted zone surrounding it. Crystal size distributions for the Picuris Range garnets correspond very closely to those in the literature from a variety of other localities for garnet and other minerals. The same kinetic model accounts quantitatively for crystal size distributions of porphyroblastic garnet, phlogopite, sphene, and pyroxene in rocks from both regional and contact metamorphic occurrences. These commonalities indicate that intergranular diffusion may be the dominant kinetic factor in the crystallization of porphyroblasts in a wide variety of metamorphic environments.
Crack detection in oak flooring lamellae using ultrasound-excited thermography
NASA Astrophysics Data System (ADS)
Pahlberg, Tobias; Thurley, Matthew; Popovic, Djordje; Hagman, Olle
2018-01-01
Today, a large number of people are manually grading and detecting defects in wooden lamellae in the parquet flooring industry. This paper investigates the possibility of using the ensemble methods random forests and boosting to automatically detect cracks using ultrasound-excited thermography and a variety of predictor variables. When friction occurs in thin cracks, they become warm and thus visible to a thermographic camera. Several image processing techniques have been used to suppress the noise and enhance probable cracks in the images. The most successful predictor variables captured the upper part of the heat distribution, such as the maximum temperature, kurtosis and percentile values 92-100 of the edge pixels. The texture in the images was captured by Completed Local Binary Pattern histograms and cracks were also segmented by background suppression and thresholding. The classification accuracy was significantly improved from previous research through added image processing, introduction of more predictors, and by using automated machine learning. The best ensemble methods reach an average classification accuracy of 0.8, which is very close to the authors' own manual attempt at separating the images (0.83).
Chen, Xiaojian; Oshima, Kiyoko; Schott, Diane; Wu, Hui; Hall, William; Song, Yingqiu; Tao, Yalan; Li, Dingjie; Zheng, Cheng; Knechtges, Paul; Erickson, Beth; Li, X Allen
2017-01-01
In an effort for early assessment of treatment response, we investigate radiation induced changes in quantitative CT features of tumor during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. On each daily CT, the pancreatic head, the spinal cord and the aorta were delineated and the histograms of CT number (CTN) in these contours were extracted. Eight histogram-based radiomic metrics including the mean CTN (MCTN), peak position, volume, standard deviation (SD), skewness, kurtosis, energy and entropy were calculated for each fraction. Paired t-test was used to check the significance of the change of specific metric at specific time. GEE model was used to test the association between changes of metrics over time for different pathology responses. In general, CTN histogram in the pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the 1st to the 26th fraction in MCTN ranged from -15.8 to 3.9 HU with an average of -4.7 HU (p<0.001). Meanwhile the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less peaked). The changes of MCTN, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response is associated with the changes of MCTN, SD, and skewness. In cases of good response, patients tend to have large reductions in MCTN and skewness, and large increases in SD and kurtosis. Significant changes in CT radiomic features, such as the MCTN, skewness, and kurtosis in tumor were observed during the course of CRT for pancreas cancer based on quantitative analysis of daily CTs. These changes may be potentially used for early assessment of treatment response and stratification for therapeutic intensification.
Various diffusion magnetic resonance imaging techniques for pancreatic cancer
Tang, Meng-Yue; Zhang, Xiao-Ming; Chen, Tian-Wu; Huang, Xiao-Hua
2015-01-01
Pancreatic cancer is one of the most common malignant tumors and remains a treatment-refractory cancer with a poor prognosis. Currently, the diagnosis of pancreatic neoplasm depends mainly on imaging and which methods are conducive to detecting small lesions. Compared to the other techniques, magnetic resonance imaging (MRI) has irreplaceable advantages and can provide valuable information unattainable with other noninvasive or minimally invasive imaging techniques. Advances in MR hardware and pulse sequence design have particularly improved the quality and robustness of MRI of the pancreas. Diffusion MR imaging serves as one of the common functional MRI techniques and is the only technique that can be used to reflect the diffusion movement of water molecules in vivo. It is generally known that diffusion properties depend on the characterization of intrinsic features of tissue microdynamics and microstructure. With the improvement of the diffusion models, diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique to the more complex. In this review, the various diffusion MRI techniques for pancreatic cancer are discussed, including conventional diffusion weighted imaging (DWI), multi-b DWI based on intra-voxel incoherent motion theory, diffusion tensor imaging and diffusion kurtosis imaging. The principles, main parameters, advantages and limitations of these techniques, as well as future directions for pancreatic diffusion imaging are also discussed. PMID:26753059
Gaing, Byron; Sigmund, Eric E; Huang, William C; Babb, James S; Parikh, Nainesh S; Stoffel, David; Chandarana, Hersh
2015-03-01
The aim of this study was to determine if voxel-based histogram analysis of intravoxel incoherent motion imaging (IVIM) parameters can differentiate various subtypes of renal tumors, including benign and malignant lesions. A total of 44 patients with renal tumors who underwent surgery and had histopathology available were included in this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, single-institution prospective study. In addition to routine renal magnetic resonance imaging examination performed on a 1.5-T system, all patients were imaged with axial diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). A biexponential model was fitted to the diffusion signal data using a segmented algorithm to extract the IVIM parameters perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) for each voxel. Mean and histogram measures of heterogeneity (standard deviation, skewness, and kurtosis) of IVIM parameters were correlated with pathology results of tumor subtype using unequal variance t tests to compare subtypes in terms of each measure. Correction for multiple comparisons was accomplished using the Tukey honestly significant difference procedure. A total of 44 renal tumors including 23 clear cell (ccRCC), 4 papillary (pRCC), 5 chromophobe, and 5 cystic renal cell carcinomas, as well as benign lesions, 4 oncocytomas (Onc) and 3 angiomyolipomas (AMLs), were included in our analysis. Mean IVIM parameters fp and Dt differentiated 8 of 15 pairs of renal tumors. Histogram analysis of IVIM parameters differentiated 9 of 15 subtype pairs. One subtype pair (ccRCC vs pRCC) was differentiated by mean analysis but not by histogram analysis. However, 2 other subtype pairs (AML vs Onc and ccRCC vs Onc) were differentiated by histogram distribution parameters exclusively. The standard deviation of Dt [σ(Dt)] differentiated ccRCC (0.362 ± 0.136 × 10 mm/s) from AML (0.199 ± 0.043 × 10 mm/s) (P = 0.002). Kurtosis of fp separated Onc (2.767 ± 1.299) from AML (-0.325 ± 0.279; P = 0.001), ccRCC (0.612 ± 1.139; P = 0.042), and pRCC (0.308 ± 0.730; P = 0.025). Intravoxel incoherent motion imaging parameters with inclusion of histogram measures of heterogeneity can help differentiate malignant from benign lesions as well as various subtypes of renal cancers.
Population-Based Study on the Effect of a Forest Environment on Salivary Cortisol Concentration
Park, Bum-Jin; Lee, Juyoung
2017-01-01
The purpose of this study was to evaluate the effect of a forest environment on salivary cortisol concentration, particularly on the characteristics of its distribution. The participants were 348 young male subjects. The experimental sites were 34 forests and 34 urban areas across Japan. The subjects viewed the landscape (forest or urban environment) for a period of 15 min while sitting in a chair. Saliva was sampled from the participants at the end of this 15-min period and then analyzed for cortisol concentration. Differences in the skewness and kurtosis of the distributions between the two environments were tested by performing a permutation test. The cortisol concentrations exhibited larger skewness (0.76) and kurtosis (3.23) in a forest environment than in an urban environment (skewness = 0.49; kurtosis = 2.47), and these differences were statistically significant. The cortisol distribution exhibited a more peaked and longer right-tailed curve in a forest environment than in an urban environment. PMID:28820452
Population-Based Study on the Effect of a Forest Environment on Salivary Cortisol Concentration.
Kobayashi, Hiromitsu; Song, Chorong; Ikei, Harumi; Park, Bum-Jin; Lee, Juyoung; Kagawa, Takahide; Miyazaki, Yoshifumi
2017-08-18
The purpose of this study was to evaluate the effect of a forest environment on salivary cortisol concentration, particularly on the characteristics of its distribution. The participants were 348 young male subjects. The experimental sites were 34 forests and 34 urban areas across Japan. The subjects viewed the landscape (forest or urban environment) for a period of 15 min while sitting in a chair. Saliva was sampled from the participants at the end of this 15-min period and then analyzed for cortisol concentration. Differences in the skewness and kurtosis of the distributions between the two environments were tested by performing a permutation test. The cortisol concentrations exhibited larger skewness (0.76) and kurtosis (3.23) in a forest environment than in an urban environment (skewness = 0.49; kurtosis = 2.47), and these differences were statistically significant. The cortisol distribution exhibited a more peaked and longer right-tailed curve in a forest environment than in an urban environment.
Improvement of kurtosis-guided-grams via Gini index for bearing fault feature identification
NASA Astrophysics Data System (ADS)
Miao, Yonghao; Zhao, Ming; Lin, Jing
2017-12-01
A group of kurtosis-guided-grams, such as Kurtogram, Protrugram and SKRgram, is designed to detect the resonance band excited by faults based on the sparsity index. However, a common issue associated with these methods is that they tend to choose the frequency band with individual impulses rather than the desired fault impulses. This may be attributed to the selection of the sparsity index, kurtosis, which is vulnerable to impulsive noise. In this paper, to solve the problem, a sparsity index, called the Gini index, is introduced as an alternative estimator for the selection of the resonance band. It has been found that the sparsity index is still able to provide guidelines for the selection of the fault band without prior information of the fault period. More importantly, the Gini index has unique performance in random-impulse resistance, which renders the improved methods using the index free from the random impulse caused by external knocks on the bearing housing, or electromagnetic interference. By virtue of these advantages, the improved methods using the Gini index not only overcome the shortcomings but are more effective under harsh working conditions, even in the complex structure. Finally, the comparison between the kurtosis-guided-grams and the improved methods using the Gini index is made using the simulated and experimental data. The results verify the effectiveness of the improvement by both the fixed-axis bearing and planetary bearing fault signals.
Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'.
de Nijs, Robin
2015-07-21
In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.
Mahapatra, Dwarikanath; Schueffler, Peter; Tielbeek, Jeroen A W; Buhmann, Joachim M; Vos, Franciscus M
2013-10-01
Increasing incidence of Crohn's disease (CD) in the Western world has made its accurate diagnosis an important medical challenge. The current reference standard for diagnosis, colonoscopy, is time-consuming and invasive while magnetic resonance imaging (MRI) has emerged as the preferred noninvasive procedure over colonoscopy. Current MRI approaches assess rate of contrast enhancement and bowel wall thickness, and rely on extensive manual segmentation for accurate analysis. We propose a supervised learning method for the identification and localization of regions in abdominal magnetic resonance images that have been affected by CD. Low-level features like intensity and texture are used with shape asymmetry information to distinguish between diseased and normal regions. Particular emphasis is laid on a novel entropy-based shape asymmetry method and higher-order statistics like skewness and kurtosis. Multi-scale feature extraction renders the method robust. Experiments on real patient data show that our features achieve a high level of accuracy and perform better than two competing methods.
Kong, Ling-Yan; Zhang, Wei; Zhou, Yue; Xu, Hai; Shi, Hai-Bin; Feng, Qing; Xu, Xiao-Quan; Yu, Tong-Fu
2018-04-01
To investigate the value of apparent diffusion coefficients (ADCs) histogram analysis for assessing World Health Organization (WHO) pathological classification and Masaoka clinical stages of thymic epithelial tumours. 37 patients with histologically confirmed thymic epithelial tumours were enrolled. ADC measurements were performed using hot-spot ROI (ADC HS-ROI ) and histogram-based approach. ADC histogram parameters included mean ADC (ADC mean ), median ADC (ADC median ), 10 and 90 percentile of ADC (ADC 10 and ADC 90 ), kurtosis and skewness. One-way ANOVA, independent-sample t-test, and receiver operating characteristic were used for statistical analyses. There were significant differences in ADC mean , ADC median , ADC 10 , ADC 90 and ADC HS-ROI among low-risk thymoma (type A, AB, B1; n = 14), high-risk thymoma (type B2, B3; n = 9) and thymic carcinoma (type C, n = 14) groups (all p-values <0.05), while no significant difference in skewness (p = 0.181) and kurtosis (p = 0.088). ADC 10 showed best differentiating ability (cut-off value, ≤0.689 × 10 -3 mm 2 s -1 ; AUC, 0.957; sensitivity, 95.65%; specificity, 92.86%) for discriminating low-risk thymoma from high-risk thymoma and thymic carcinoma. Advanced Masaoka stages (Stage III and IV; n = 24) tumours showed significant lower ADC parameters and higher kurtosis than early Masaoka stage (Stage I and II; n = 13) tumours (all p-values <0.05), while no significant difference on skewness (p = 0.063). ADC 10 showed best differentiating ability (cut-off value, ≤0.689 × 10 -3 mm 2 s -1 ; AUC, 0.913; sensitivity, 91.30%; specificity, 85.71%) for discriminating advanced and early Masaoka stage epithelial tumours. ADC histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumours. Advances in knowledge: 1. ADC histogram analysis could help to assess WHO pathological classification of thymic epithelial tumours. 2. ADC histogram analysis could help to evaluate Masaoka clinical stages of thymic epithelial tumours. 3. ADC 10 might be a promising imaging biomarker for assessing and characterizing thymic epithelial tumours.
Terahertz time-gated spectral imaging for content extraction through layered structures
Redo-Sanchez, Albert; Heshmat, Barmak; Aghasi, Alireza; Naqvi, Salman; Zhang, Mingjie; Romberg, Justin; Raskar, Ramesh
2016-01-01
Spatial resolution, spectral contrast and occlusion are three major bottlenecks for non-invasive inspection of complex samples with current imaging technologies. We exploit the sub-picosecond time resolution along with spectral resolution provided by terahertz time-domain spectroscopy to computationally extract occluding content from layers whose thicknesses are wavelength comparable. The method uses the statistics of the reflected terahertz electric field at subwavelength gaps to lock into each layer position and then uses a time-gated spectral kurtosis to tune to highest spectral contrast of the content on that specific layer. To demonstrate, occluding textual content was successfully extracted from a packed stack of paper pages down to nine pages without human supervision. The method provides over an order of magnitude enhancement in the signal contrast and can impact inspection of structural defects in wooden objects, plastic components, composites, drugs and especially cultural artefacts with subwavelength or wavelength comparable layers. PMID:27610926
NASA Astrophysics Data System (ADS)
Glassmeier, F.; Arnold, L.; Lohmann, U.; Dietlicher, R.; Paukert, M.
2016-12-01
Our current understanding of charge generation in thunderclouds is based on collisional charge transfer between graupel and ice crystals in the presence of liquid water droplets as dominant mechanism. The physical process of charge transfer and the sign of net charge generated on graupel and ice crystals under different cloud conditions is not yet understood. The Relative-Diffusional-Growth-Rate (RDGR) theory (Baker et al. 1987) suggests that the particle with the faster diffusional radius growth is charged positively. In this contribution, we use simulations of idealized thunderclouds with two-moment warm and cold cloud microphysics to generate realistic combinations of RDGR-parameters. We find that these realistic parameter combinations result in a relationship between sign of charge, cloud temperature and effective water content that deviates from previous theoretical and laboratory studies. This deviation indicates that the RDGR theory is sensitive to correlations between parameters that occur in clouds but are not captured in studies that vary temperature and water content while keeping other parameters at fixed values. In addition, our results suggest that diffusional growth from the riming-related local water vapor field, a key component of the RDGR theory, is negligible for realistic parameter combinations. Nevertheless, we confirm that the RDGR theory results in positive or negative charging of particles under different cloud conditions. Under specific conditions, charge generation via the RDGR theory alone might thus be sufficient to explain tripolar charge structures in thunderclouds. In general, however, additional charge generation mechanisms and adaptations to the RDGR theory that consider riming other than via local vapor deposition seem necessary.
Application of two tests of multivariate discordancy to fisheries data sets
Stapanian, M.A.; Kocovsky, P.M.; Garner, F.C.
2008-01-01
The generalized (Mahalanobis) distance and multivariate kurtosis are two powerful tests of multivariate discordancies (outliers). Unlike the generalized distance test, the multivariate kurtosis test has not been applied as a test of discordancy to fisheries data heretofore. We applied both tests, along with published algorithms for identifying suspected causal variable(s) of discordant observations, to two fisheries data sets from Lake Erie: total length, mass, and age from 1,234 burbot, Lota lota; and 22 combinations of unique subsets of 10 morphometrics taken from 119 yellow perch, Perca flavescens. For the burbot data set, the generalized distance test identified six discordant observations and the multivariate kurtosis test identified 24 discordant observations. In contrast with the multivariate tests, the univariate generalized distance test identified no discordancies when applied separately to each variable. Removing discordancies had a substantial effect on length-versus-mass regression equations. For 500-mm burbot, the percent difference in estimated mass after removing discordancies in our study was greater than the percent difference in masses estimated for burbot of the same length in lakes that differed substantially in productivity. The number of discordant yellow perch detected ranged from 0 to 2 with the multivariate generalized distance test and from 6 to 11 with the multivariate kurtosis test. With the kurtosis test, 108 yellow perch (90.7%) were identified as discordant in zero to two combinations, and five (4.2%) were identified as discordant in either all or 21 of the 22 combinations. The relationship among the variables included in each combination determined which variables were identified as causal. The generalized distance test identified between zero and six discordancies when applied separately to each variable. Removing the discordancies found in at least one-half of the combinations (k=5) had a marked effect on a principal components analysis. In particular, the percent of the total variation explained by second and third principal components, which explain shape, increased by 52 and 44% respectively when the discordancies were removed. Multivariate applications of the tests have numerous ecological advantages over univariate applications, including improved management of fish stocks and interpretation of multivariate morphometric data. ?? 2007 Springer Science+Business Media B.V.
NASA Astrophysics Data System (ADS)
Moshrefzadeh, Ali; Fasana, Alessandro
2018-05-01
Envelope analysis is one of the most advantageous methods for rolling element bearing diagnostics but finding a suitable frequency band for demodulation has been a substantial challenge for a long time. Introduction of the Spectral Kurtosis (SK) and Kurtogram mostly solved this problem but in situations where signal to noise ratio is very low or in presence of non-Gaussian noise these methods will fail. This major drawback may noticeably decrease their effectiveness and goal of this paper is to overcome this problem. Vibration signals from rolling element bearings exhibit high levels of second-order cyclostationarity, especially in the presence of localized faults. The autocovariance function of a 2nd order cyclostationary signal is periodic and the proposed method, named Autogram, takes advantage of this property to enhance the conventional Kurtogram. The method computes the kurtosis of the unbiased Autocorrelation (AC) of the squared envelope of the demodulated signal, rather than the kurtosis of the filtered time signal. Moreover, to take advantage of unique features of the lower and upper portions of the AC, two modified forms of kurtosis are introduced and the resulting colormaps are called Upper and Lower Autogram. In addition, a thresholding method is also proposed to enhance the quality of the frequency spectrum analysis. A new indicator, Combined Squared Envelope Spectrum, is employed to consider all the frequency bands with valuable diagnostic information and to improve the fault detectability of the Autogram. The proposed method is tested on experimental data and compared with literature results so to assess its performances in rolling element bearing diagnostics.
Scott, Jonathan M.; Robinson, Stephen E.; Holroyd, Tom; Coppola, Richard; Sato, Susumu; Inati, Sara K.
2016-01-01
OBJECTIVE To describe and optimize an automated beamforming technique followed by identification of locations with excess kurtosis (g2) for efficient detection and localization of interictal spikes in medically refractory epilepsy patients. METHODS Synthetic Aperture Magnetometry with g2 averaged over a sliding time window (SAMepi) was performed in 7 focal epilepsy patients and 5 healthy volunteers. The effect of varied window lengths on detection of spiking activity was evaluated. RESULTS Sliding window lengths of 0.5–10 seconds performed similarly, with 0.5 and 1 second windows detecting spiking activity in one of the 3 virtual sensor locations with highest kurtosis. These locations were concordant with the region of eventual surgical resection in these 7 patients who remained seizure free at one year. Average g2 values increased with increasing sliding window length in all subjects. In healthy volunteers kurtosis values stabilized in datasets longer than two minutes. CONCLUSIONS SAMepi using g2 averaged over 1 second sliding time windows in datasets of at least 2 minutes duration reliably identified interictal spiking and the presumed seizure focus in these 7 patients. Screening the 5 locations with highest kurtosis values for spiking activity is an efficient and accurate technique for localizing interictal activity using MEG. SIGNIFICANCE SAMepi should be applied using the parameter values and procedure described for optimal detection and localization of interictal spikes. Use of this screening procedure could significantly improve the efficiency of MEG analysis if clinically validated. PMID:27760068
Morikawa, Kei; Kurimoto, Noriaki; Inoue, Takeo; Mineshita, Masamichi; Miyazawa, Teruomi
2015-01-01
Endobronchial ultrasonography using a guide sheath (EBUS-GS) is an increasingly common bronchoscopic technique, but currently, no methods have been established to quantitatively evaluate EBUS images of peripheral pulmonary lesions. The purpose of this study was to evaluate whether histogram data collected from EBUS-GS images can contribute to the diagnosis of lung cancer. Histogram-based analyses focusing on the brightness of EBUS images were retrospectively conducted: 60 patients (38 lung cancer; 22 inflammatory diseases), with clear EBUS images were included. For each patient, a 400-pixel region of interest was selected, typically located at a 3- to 5-mm radius from the probe, from recorded EBUS images during bronchoscopy. Histogram height, width, height/width ratio, standard deviation, kurtosis and skewness were investigated as diagnostic indicators. Median histogram height, width, height/width ratio and standard deviation were significantly different between lung cancer and benign lesions (all p < 0.01). With a cutoff value for standard deviation of 10.5, lung cancer could be diagnosed with an accuracy of 81.7%. Other characteristics investigated were inferior when compared to histogram standard deviation. Histogram standard deviation appears to be the most useful characteristic for diagnosing lung cancer using EBUS images. © 2015 S. Karger AG, Basel.
Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms
Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan
2014-01-01
This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701
Characterization, modeling and simulation of fused deposition modeling fabricated part surfaces
NASA Astrophysics Data System (ADS)
Taufik, Mohammad; Jain, Prashant K.
2017-12-01
Surface roughness is generally used for characterization, modeling and simulation of fused deposition modeling (FDM) fabricated part surfaces. But the average surface roughness is not able to provide the insight of surface characteristics with sharp peaks and deep valleys. It deals in the average sense for all types of surfaces, including FDM fabricated surfaces with distinct surface profile features. The present research work shows that kurtosis and skewness can be used for characterization, modeling and simulation of FDM surfaces because these roughness parameters have the ability to characterize a surface with sharp peaks and deep valleys. It can be critical in certain application areas in tribology and biomedicine, where the surface profile plays an important role. Thus, in this study along with surface roughness, skewness and kurtosis are considered to show a novel strategy to provide new transferable knowledge about FDM fabricated part surfaces. The results suggest that the surface roughness, skewness and kurtosis are significantly different at 0° and in the range (0°, 30°], [30°, 90°] of build orientation.
Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik
2018-05-01
Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our findings suggest that SVM, using features from a combination of diffusion models, improves prediction accuracy for differentiation of benign versus malignant breast tumors, and may further assist in subtyping of breast cancer. 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1205-1216. © 2017 International Society for Magnetic Resonance in Medicine.
Quantitative histogram analysis of images
NASA Astrophysics Data System (ADS)
Holub, Oliver; Ferreira, Sérgio T.
2006-11-01
A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None
Reduction of diffusional defocusing in hydrodynamically focused flows
Affleck, Rhett L.; Demas, James N.; Goodwin, Peter M.; Keller, Richard; Wu, Ming
1998-01-01
An analyte fluid stream with first molecules having relatively low molecular weight and a corresponding high coefficient of diffusion has reduced diffusional defocusing out of an analyte fluid stream. The analyte fluid stream of first molecules is associated with second molecules of relatively high molecular weight having a relatively low coefficient of diffusion and a binding constant effective to associate with the first molecules. A focused analyte fluid stream is maintained since the combined molecular weight of the associated first and second molecules is effective to minimize diffusion of the first molecules out of the analyte fluid stream.
Reduction of diffusional defocusing in hydrodynamically focused flows
Affleck, R.L.; Demas, J.N.; Goodwin, P.M.; Keller, R.; Wu, M.
1998-09-01
An analyte fluid stream with first molecules having relatively low molecular weight and a corresponding high coefficient of diffusion has reduced diffusional defocusing out of an analyte fluid stream. The analyte fluid stream of first molecules is associated with second molecules of relatively high molecular weight having a relatively low coefficient of diffusion and a binding constant effective to associate with the first molecules. A focused analyte fluid stream is maintained since the combined molecular weight of the associated first and second molecules is effective to minimize diffusion of the first molecules out of the analyte fluid stream. 6 figs.
Vázquez, M I; de Lara, R; Benavente, J
2008-12-15
A comparison of NaCl transport across two dense cellulosic membranes from different suppliers is presented. Hydraulic and diffusional permeabilities were determined from volume flow-applied pressure and concentration-time relationships, while cation transport number and membrane conductivity were determined from electromotrice force and impedance spectroscopy measurements, respectively. Chemical surface differences between both membranes are correlated to transport parameters and morphology, but differences in elastic properties of both membranes might also be considered in order to get a more complete picture of membrane behaviors and to obtain structural-transport parameters correlations.
Forecasting stock market volatility: Do realized skewness and kurtosis help?
NASA Astrophysics Data System (ADS)
Mei, Dexiang; Liu, Jing; Ma, Feng; Chen, Wang
2017-09-01
In this study, we investigate the predictability of the realized skewness (RSK) and realized kurtosis (RKU) to stock market volatility, that has not been addressed in the existing studies. Out-of-sample results show that RSK, which can significantly improve forecast accuracy in mid- and long-term, is more powerful than RKU in forecasting volatility. Whereas these variables are useless in short-term forecasting. Furthermore, we employ the realized kernel (RK) for the robustness analysis and the conclusions are consistent with the RV measures. Our results are of great importance for portfolio allocation and financial risk management.
Meng, Jie; Zhu, Lijing; Zhu, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng
2016-10-22
To explore the role of apparent diffusion coefficient (ADC) histogram shape related parameters in early assessment of treatment response during the concurrent chemo-radiotherapy (CCRT) course of advanced cervical cancers. This prospective study was approved by the local ethics committee and informed consent was obtained from all patients. Thirty-two patients with advanced cervical squamous cell carcinomas underwent diffusion weighted magnetic resonance imaging (b values, 0 and 800 s/mm 2 ) before CCRT, at the end of 2nd and 4th week during CCRT and immediately after CCRT completion. Whole lesion ADC histogram analysis generated several histogram shape related parameters including skewness, kurtosis, s-sD av , width, standard deviation, as well as first-order entropy and second-order entropies. The averaged ADC histograms of 32 patients were generated to visually observe dynamic changes of the histogram shape following CCRT. All parameters except width and standard deviation showed significant changes during CCRT (all P < 0.05), and their variation trends fell into four different patterns. Skewness and kurtosis both showed high early decline rate (43.10 %, 48.29 %) at the end of 2nd week of CCRT. All entropies kept decreasing significantly since 2 weeks after CCRT initiated. The shape of averaged ADC histogram also changed obviously following CCRT. ADC histogram shape analysis held the potential in monitoring early tumor response in patients with advanced cervical cancers undergoing CCRT.
Modeling oxygen transport in human placental terminal villi.
Gill, J S; Salafia, C M; Grebenkov, D; Vvedensky, D D
2011-12-21
Oxygen transport from maternal blood to fetal blood is a primary function of the placenta. Quantifying the effectiveness of this exchange remains key in identifying healthy placentas because of the great variability in capillary number, caliber and position within the villus-even in placentas deemed clinically "normal". By considering villous membrane to capillary membrane transport, stationary oxygen diffusion can be numerically solved in terminal villi represented by digital photomicrographs. We aim to provide a method to determine whether and if so to what extent diffusional screening may operate in placental villi. Segmented digital photomicrographs of terminal villi from the Pregnancy, Infection and Nutrition study in North Carolina 2002 are used as a geometric basis for solving the stationary diffusion equation. Constant maternal villous oxygen concentration and perfect fetal capillary membrane absorption are assumed. System efficiency is defined as the ratio of oxygen flux into a villus and the sum of the capillary areas contained within. Diffusion screening is quantified by comparing numerical and theoretical maximum oxygen fluxes. A strong link between various measures of villous oxygen transport efficiency and the number of capillaries within a villus is established. The strength of diffusional screening is also related to the number of capillaries within a villus. Our measures of diffusional efficiency are shown to decrease as a function of the number of capillaries per villus. This low efficiency, high capillary number relationship supports our hypothesis that diffusional screening is present in this system. Oxygen transport per capillary is reduced when multiple capillaries compete for diffusing oxygen. A complete picture of oxygen fluxes, capillary and villus areas is obtainable and presents an opportunity for future work. Copyright © 2011 Elsevier Ltd. All rights reserved.
Multi-model Analysis of Diffusion-weighted Imaging of Normal Testes at 3.0 T: Preliminary Findings.
Min, Xiangde; Feng, Zhaoyan; Wang, Liang; Cai, Jie; Li, Basen; Ke, Zan; Zhang, Peipei; You, Huijuan; Yan, Xu
2018-04-01
This study aimed to establish diffusion quantitative parameters (apparent diffusion coefficient [ADC], DDC, α, D app , and K app ) in normal testes at 3.0 T. Sixty-four healthy volunteers in two age groups (A: 10-39 years; B: ≥ 40 years) underwent diffusion-weighted imaging scanning at 3.0 T. ADC 1000 , ADC 2000 , ADC 3000 , DDC, α, D app , and K app were calculated using the mono-exponential, stretched-exponential, and kurtosis models. The correlations between parameters and the age were analyzed. The parameters were compared between the age groups and between the right and the left testes. The average ADC 1000 , ADC 2000 , ADC 3000 , DDC, α, D app , and K app values did not significantly differ between the right and the left testes (P > .05 for all). The following significant correlations were found: positive correlations between age and testicular ADC 1000 , ADC 2000 , ADC 3000 , DDC, and D app (r = 0.516, 0.518, 0.518, 0.521, and 0.516, respectively; P < .01 for all) and negative correlations between age and testicular α and K app (r = -0.363, -0.427, respectively; P < .01 for both). Compared to group B, in group A, ADC 1000 , ADC 2000 , ADC 3000 , DDC, and D app were significantly lower (P < .05 for all), but α and K app were significantly higher (P < .05 for both). Our study demonstrated the applicability of the testicular mono-exponential, stretched-exponential, and kurtosis models. Our results can help establish a baseline for the normal testicular parameters in these diffusion models. The contralateral normal testis can serve as a suitable reference for evaluating the abnormalities of the other side. The effect of age on these parameters requires further attention. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo
2017-08-01
The extraction of periodic impulses, which are the important indicators of rolling bearing faults, from vibration signals is considerably significance for fault diagnosis. Maximum correlated kurtosis deconvolution (MCKD) developed from minimum entropy deconvolution (MED) has been proven as an efficient tool for enhancing the periodic impulses in the diagnosis of rolling element bearings and gearboxes. However, challenges still exist when MCKD is applied to the bearings operating under harsh working conditions. The difficulties mainly come from the rigorous requires for the multi-input parameters and the complicated resampling process. To overcome these limitations, an improved MCKD (IMCKD) is presented in this paper. The new method estimates the iterative period by calculating the autocorrelation of the envelope signal rather than relies on the provided prior period. Moreover, the iterative period will gradually approach to the true fault period through updating the iterative period after every iterative step. Since IMCKD is unaffected by the impulse signals with the high kurtosis value, the new method selects the maximum kurtosis filtered signal as the final choice from all candidates in the assigned iterative counts. Compared with MCKD, IMCKD has three advantages. First, without considering prior period and the choice of the order of shift, IMCKD is more efficient and has higher robustness. Second, the resampling process is not necessary for IMCKD, which is greatly convenient for the subsequent frequency spectrum analysis and envelope spectrum analysis without resetting the sampling rate. Third, IMCKD has a significant performance advantage in diagnosing the bearing compound-fault which expands the application range. Finally, the effectiveness and superiority of IMCKD are validated by a number of simulated bearing fault signals and applying to compound faults and single fault diagnosis of a locomotive bearing.
Optimised Spectral Kurtosis for bearing diagnostics under electromagnetic interference
NASA Astrophysics Data System (ADS)
Smith, Wade A.; Fan, Zhiqi; Peng, Zhongxiao; Li, Huaizhong; Randall, Robert B.
2016-06-01
The selection of the optimal demodulation frequency band is a significant step in bearing fault diagnosis because it determines whether the fault information can be extracted from the demodulated signal via envelope analysis. Two well-known methods for selecting the demodulation band are the Fast Kurtogram, based on the kurtosis of the filtered time signal, and the Protrugram, which uses the kurtosis of the envelope (amplitude) spectrum. Although these two methods have been successfully applied in many cases, the authors have observed that they may fail in specific environments, such as in the presence of electromagnetic interference (EMI) or other impulsive masking signals. In this paper, a simple spectral kurtosis-based approach is proposed for selecting the best demodulation band to extract bearing fault-related impulsive content from vibration signals contaminated with strong EMI. The method is applied to vibration signals obtained from a planetary gearbox test rig with planet bearings seeded with inner and outer race faults. Results from the Fast Kurtogram and Protrugram methods are also included for comparison. The proposed approach is found to exhibit superior diagnostic performance in the presence of intense EMI. Another contribution of the paper is to introduce and explain the issue of EMI to the condition monitoring community. The paper outlines the characteristics of EMI arising from widely-used variable frequency drives, and these characteristics are used to simulate an EMI-contaminated vibration signal to further test the performance of the proposed approach. Although EMI has been acknowledged as a serious problem in many industrial cases, there have been very few studies showing its adverse effects on machine diagnostics. It is important for analysts to be able to identify EMI in measured vibration signals, lest it interfere with the analysis undertaken.
Bertleff, Marco; Domsch, Sebastian; Weingärtner, Sebastian; Zapp, Jascha; O'Brien, Kieran; Barth, Markus; Schad, Lothar R
2017-12-01
Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least-squares regression (LSR) and state-of-the-art multi-step fitting (LSR-MS) in Monte-Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR-MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo-diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR-MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR-MS, 19%; LSR, 8%), D* (ANN, 21%; LSR-MS, 25%; LSR, 23%) and K (ANN, 0%; LSR-MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR-MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state-of-the-art method LSR-MS with several advantages in the estimation of IVIM-kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times. Copyright © 2017 John Wiley & Sons, Ltd.
Cell biochemistry studied by single-molecule imaging.
Mashanov, G I; Nenasheva, T A; Peckham, M; Molloy, J E
2006-11-01
Over the last decade, there have been remarkable developments in live-cell imaging. We can now readily observe individual protein molecules within living cells and this should contribute to a systems level understanding of biological pathways. Direct observation of single fluorophores enables several types of molecular information to be gathered. Temporal and spatial trajectories enable diffusion constants and binding kinetics to be deduced, while analyses of fluorescence lifetime, intensity, polarization or spectra give chemical and conformational information about molecules in their cellular context. By recording the spatial trajectories of pairs of interacting molecules, formation of larger molecular complexes can be studied. In the future, multicolour and multiparameter imaging of single molecules in live cells will be a powerful analytical tool for systems biology. Here, we discuss measurements of single-molecule mobility and residency at the plasma membrane of live cells. Analysis of diffusional paths at the plasma membrane gives information about its physical properties and measurement of temporal trajectories enables rates of binding and dissociation to be derived. Meanwhile, close scrutiny of individual fluorophore trajectories enables ideas about molecular dimerization and oligomerization related to function to be tested directly.
Diffusional creep and creep degradation in the dispersion-strengthened alloy TD-NiCr
NASA Technical Reports Server (NTRS)
Whittenberger, J. D.
1972-01-01
Dispersoid-free regions were observed in TD-NiCr (Ni-20Cr-2ThO2) after slow strain rate testing in air from 1145 to 1590 K. Formation of the dispersoid-free regions appears to be the result of diffusional creep. The net effect of this creep is the degradation of TD-NiCr to a duplex microstructure. Degradation is further enhanced by the formation of voids and integranular oxidation in the thoria-free regions. These regions apparently provided sites for void formation and oxide growth since the strength and oxidation resistance of Ni-20Cr is much less than Ni-20Cr-2ThO2. This localized oxidation does not appear to reduce the static load bearing capacity of TD-NiCr since long stress rupture lives were observed even with heavily oxidized microstructures. But this oxidation does significantly reduce the ductility and impact resistance of the material. Dispersoid-free bands and voids were also observed for two other dispersion strengthened alloys, TD-NiCrAl and IN-853. Thus, it appears that diffusional creep is charactertistic of dispersion-strengthened alloys and can play a major role in the creep degradation of these materials.
Molecular-Scale Description of SPAN80 Desorption from a Squalane-Water Interface.
Tan, L; Pratt, L R; Chaudhari, M I
2018-04-05
Extensive all-atom molecular dynamics calculations on the water-squalane interface for nine different loadings with sorbitan monooleate (SPAN80), at T = 300 K, are analyzed for the surface tension equation of state, desorption free-energy profiles as they depend on loading, and to evaluate escape times for adsorbed SPAN80 into the bulk phases. These results suggest that loading only weakly affects accommodation of a SPAN80 molecule by this squalane-water interface. Specifically, the surface tension equation of state is simple through the range of high tension to high loading studied, and the desorption free-energy profiles are weakly dependent on loading here. The perpendicular motion of the centroid of the SPAN80 headgroup ring is well-described by a diffusional model near the minimum of the desorption free-energy profile. Lateral diffusional motion is weakly dependent on loading. Escape times evaluated on the basis of a diffusional model and the desorption free energies are 7 × 10 -2 s (into the squalane) and 3 × 10 2 h (into the water). The latter value is consistent with desorption times of related lab-scale experimental work.
Kurtosis Approach Nonlinear Blind Source Separation
NASA Technical Reports Server (NTRS)
Duong, Vu A.; Stubbemd, Allen R.
2005-01-01
In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation Keywords: Independent Component Analysis, Kurtosis, Higher order statistics.
NASA Astrophysics Data System (ADS)
Miranda, Rodrigo A.; Schelin, Adriane B.; Chian, Abraham C.-L.; Ferreira, José L.
2018-03-01
In a recent paper (Chian et al., 2016) it was shown that magnetic reconnection at the interface region between two magnetic flux ropes is responsible for the genesis of interplanetary intermittent turbulence. The normalized third-order moment (skewness) and the normalized fourth-order moment (kurtosis) display a quadratic relation with a parabolic shape that is commonly observed in observational data from turbulence in fluids and plasmas, and is linked to non-Gaussian fluctuations due to coherent structures. In this paper we perform a detailed study of the relation between the skewness and the kurtosis of the modulus of the magnetic field |B| during a triple interplanetary magnetic flux rope event. In addition, we investigate the skewness-kurtosis relation of two-point differences of |B| for the same event. The parabolic relation displays scale dependence and is found to be enhanced during magnetic reconnection, rendering support for the generation of non-Gaussian coherent structures via rope-rope magnetic reconnection. Our results also indicate that a direct coupling between the scales of magnetic flux ropes and the scales within the inertial subrange occurs in the solar wind.
Monitoring Mars for Electrostatic Disturbances
NASA Technical Reports Server (NTRS)
Compton, D.
2011-01-01
The DSN radio telescope DSS-13 was used to monitor Mars for electrostatic discharges from 17 February to 11 April, 2010, and from 19 April to 4 May, 2011, over a total of 72 sessions. Of these sessions, few showed noteworthy results and no outstanding electrostatic disturbances were observed on Mars from analyzing the kurtosis of radio emission from Mars. Electrostatic discharges on mars were originally detected in June of 2006 by Ruf et al. using DSS-13. he kurtosis (normalized fourth moment of the electrical field strength) is sensitive to non-thermal radiation. Two frequencies bands, either 2.4 and 8.4 GHz or 8.4 and 32 GHz were used. The non-thermal radiation spectrum should have peaks at the lowest three modes of the theoretical Schumann Resonances of Mars. The telescope was pointed away from Mars every 5 minutes for 45 seconds to confirm if Mars was indeed the sources of any events. It was shown that by including a down-link signal in one channel and by observing when the kurtosis changed as the telescope was pointed away from the source that the procedure can monitor Mars without the need of extra equipment monitoring a control source.
Asymptotic confidence intervals for the Pearson correlation via skewness and kurtosis.
Bishara, Anthony J; Li, Jiexiang; Nash, Thomas
2018-02-01
When bivariate normality is violated, the default confidence interval of the Pearson correlation can be inaccurate. Two new methods were developed based on the asymptotic sampling distribution of Fisher's z' under the general case where bivariate normality need not be assumed. In Monte Carlo simulations, the most successful of these methods relied on the (Vale & Maurelli, 1983, Psychometrika, 48, 465) family to approximate a distribution via the marginal skewness and kurtosis of the sample data. In Simulation 1, this method provided more accurate confidence intervals of the correlation in non-normal data, at least as compared to no adjustment of the Fisher z' interval, or to adjustment via the sample joint moments. In Simulation 2, this approximate distribution method performed favourably relative to common non-parametric bootstrap methods, but its performance was mixed relative to an observed imposed bootstrap and two other robust methods (PM1 and HC4). No method was completely satisfactory. An advantage of the approximate distribution method, though, is that it can be implemented even without access to raw data if sample skewness and kurtosis are reported, making the method particularly useful for meta-analysis. Supporting information includes R code. © 2017 The British Psychological Society.
Correcting Too Much or Too Little? The Performance of Three Chi-Square Corrections.
Foldnes, Njål; Olsson, Ulf Henning
2015-01-01
This simulation study investigates the performance of three test statistics, T1, T2, and T3, used to evaluate structural equation model fit under non normal data conditions. T1 is the well-known mean-adjusted statistic of Satorra and Bentler. T2 is the mean-and-variance adjusted statistic of Sattertwaithe type where the degrees of freedom is manipulated. T3 is a recently proposed version of T2 that does not manipulate degrees of freedom. Discrepancies between these statistics and their nominal chi-square distribution in terms of errors of Type I and Type II are investigated. All statistics are shown to be sensitive to increasing kurtosis in the data, with Type I error rates often far off the nominal level. Under excess kurtosis true models are generally over-rejected by T1 and under-rejected by T2 and T3, which have similar performance in all conditions. Under misspecification there is a loss of power with increasing kurtosis, especially for T2 and T3. The coefficient of variation of the nonzero eigenvalues of a certain matrix is shown to be a reliable indicator for the adequacy of these statistics.
Earthquake number forecasts testing
NASA Astrophysics Data System (ADS)
Kagan, Yan Y.
2017-10-01
We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness and kurtosis both tend to zero for large earthquake rates: for the Gaussian law, these values are identically zero. A calculation of the NBD skewness and kurtosis levels based on the values of the first two statistical moments of the distribution, shows rapid increase of these upper moments levels. However, the observed catalogue values of skewness and kurtosis are rising even faster. This means that for small time intervals, the earthquake number distribution is even more heavy-tailed than the NBD predicts. Therefore for small time intervals, we propose using empirical number distributions appropriately smoothed for testing forecasted earthquake numbers.
Characteristic of a Digital Correlation Radiometer Back End with Finite Wordlength
NASA Technical Reports Server (NTRS)
Biswas, Sayak K.; Hyde, David W.; James, Mark W.; Cecil, Daniel J.
2017-01-01
The performance characteristic of a digital correlation radiometer signal processing back end (DBE) is analyzed using a simulator. The particular design studied here corresponds to the airborne Hurricane Imaging radiometer which was jointly developed by the NASA Marshall Space Flight Center, University of Michigan, University of Central Florida and NOAA. Laboratory and flight test data is found to be in accord with the simulation results. Overall design seems to be optimum for the typical input signal dynamic range. It was found that the performance of the digital kurtosis could be improved by lowering the DBE input power level. An unusual scaling between digital correlation channels observed in the instrument data is confirmed to be a DBE characteristic.
Li, Xiaoxia; Yuan, Ying; Ren, Jiliang; Shi, Yiqian; Tao, Xiaofeng
2018-03-26
We aimed to investigate the incremental prognostic value of apparent diffusion coefficient (ADC) histogram analysis in patients with head and neck squamous cell carcinoma (HNSCC) and integrate it into a multivariate prognostic model. A retrospective review of magnetic resonance imaging findings was conducted in patients with pathologically confirmed HNSCC between June 2012 and December 2015. For each tumor, six histogram parameters were derived: the 10th, 50th, and 90th percentiles of ADC (ADC 10 , ADC 50 , and ADC 90 ); mean ADC values (ADC mean ); kurtosis; and skewness. The clinical variables included age, sex, smoking status, tumor volume, and tumor node metastasis stage. The association of these histogram and clinical variables with overall survival (OS) was determined. Further validation of the histogram parameters as independent biomarkers was performed using multivariate Cox proportional hazard models combined with clinical variables, which was compared to the clinical model. Models were assessed with C index and receiver operating characteristic curve analyses for the 12- and 36-month OS. Ninety-six patients were eligible for analysis. Median follow-up was 877 days (range, 54-1516 days). A total of 29 patients died during follow-up (30%). Patients with higher ADC values (ADC 10 > 0.958 × 10 -3 mm 2 /s, ADC 50 > 1.089 × 10 -3 mm 2 /s, ADC 90 > 1.152 × 10 -3 mm 2 /s, ADC mean > 1.047 × 10 -3 mm 2 /s) and lower kurtosis (≤0.967) were significant predictors of poor OS (P < .100 for all). After adjusting for sex and tumor node metastasis stage, the ADC 90 and kurtosis are both significant predictors of OS with hazard ratios = 1.00 (95% confidence interval: 1.001-1.004) and 0.58 (95% confidence interval: 0.37-0.90), respectively. By adding the ADC parameters into the clinical model, the C index and diagnostic accuracies for the 12- and 36-month OS showed significant improvement. ADC histogram analysis has incremental prognostic value in patients with HNSCC and increases the performance of a multivariable prognostic model in addition to clinical variables. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Non-Gaussian Distribution of DNA Barcode Extension In Nanochannels Using High-throughput Imaging
NASA Astrophysics Data System (ADS)
Sheats, Julian; Reinhart, Wesley; Reifenberger, Jeff; Gupta, Damini; Muralidhar, Abhiram; Cao, Han; Dorfman, Kevin
2015-03-01
We present experimental data for the extension of internal segments of highly confined DNA using a high-throughput experimental setup. Barcode-labeled E. coli genomic DNA molecules were imaged at a high areal density in square nanochannels with sizes ranging from 40 nm to 51 nm in width. Over 25,000 molecules were used to obtain more than 1,000,000 measurements for genomic distances between 2,500 bp and 100,000 bp. The distribution of extensions has positive excess kurtosis and is skew left due to weak backfolding in the channel. As a result, the two Odijk theories for the chain extension and variance bracket the experimental data. We compared to predictions of a harmonic approximation for the confinement free energy and show that it produces a substantial error in the variance. These results suggest an inherent error associated with any statistical analysis of barcoded DNA that relies on harmonic models for chain extension. Present address: Department of Chemical and Biological Engineering, Princeton University.
Computer-assisted bladder cancer grading: α-shapes for color space decomposition
NASA Astrophysics Data System (ADS)
Niazi, M. K. K.; Parwani, Anil V.; Gurcan, Metin N.
2016-03-01
According to American Cancer Society, around 74,000 new cases of bladder cancer are expected during 2015 in the US. To facilitate the bladder cancer diagnosis, we present an automatic method to differentiate carcinoma in situ (CIS) from normal/reactive cases that will work on hematoxylin and eosin (H and E) stained images of bladder. The method automatically determines the color deconvolution matrix by utilizing the α-shapes of the color distribution in the RGB color space. Then, variations in the boundary of transitional epithelium are quantified, and sizes of nuclei in the transitional epithelium are measured. We also approximate the "nuclear to cytoplasmic ratio" by computing the ratio of the average shortest distance between transitional epithelium and nuclei to average nuclei size. Nuclei homogeneity is measured by computing the kurtosis of the nuclei size histogram. The results show that 30 out of 34 (88.2%) images were correctly classified by the proposed method, indicating that these novel features are viable markers to differentiate CIS from normal/reactive bladder.
NASA Astrophysics Data System (ADS)
Tu, Yiyou; Tong, Zhen; Jiang, Jianqing
2013-04-01
The effect of microstructure on clad/core interactions during the brazing of 4343/3005/4343 multi-layer aluminum brazing sheet was investigated employing differential scanning calorimetry (DSC) and electron back-scattering diffraction (EBSD). The thickness of the melted clad layer gradually decreased during the brazing operation. It could be completely removed isothermally as a result of diffusional solidification at the brazing temperature. During the brazing cycle, the rate of loss of the melt in the brazing sheet, with small equiaxed grains' core layer, was higher than that with the core layer consisting of elongated large grains. The difference in microstructure affected the amount of liquid formed during brazing.
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.
Atmospheric Science Data Center
2015-11-25
... Dew/Frost Point Temperature Diffusional Growth Rate Ice Water Concent Particle Diameter Particle Number Concentration Precipitation Rate Radar Reflectivity Relative Humidity Static Pressure Vertical ...
Atmospheric Science Data Center
2015-11-25
... Dew/Frost Point Temperature Diffusional Growth Rate Ice Water Content Particle Diameter Particle Number Concentration Precipitation Rate Radar Reflectivity Relative Humidity Static Pressure Vertical ...
Atmospheric Science Data Center
2015-11-25
... Dew/Frost Point Temperature Diffusional Growth Rate Ice Water Content Particle Diameter Particle Number Concentration Preciptiation Rate Radar Reflectivity Relative Humidity Static Pressure Vertical ...
Effect of respiratory and cardiac gating on the major diffusion-imaging metrics
Hamaguchi, Hiroyuki; Sugimori, Hiroyuki; Nakanishi, Mitsuhiro; Nakagawa, Shin; Fujiwara, Taro; Yoshida, Hirokazu; Takamori, Sayaka; Shirato, Hiroki
2016-01-01
The effect of respiratory gating on the major diffusion-imaging metrics and that of cardiac gating on mean kurtosis (MK) are not known. For evaluation of whether the major diffusion-imaging metrics—MK, fractional anisotropy (FA), and mean diffusivity (MD) of the brain—varied between gated and non-gated acquisitions, respiratory-gated, cardiac-gated, and non-gated diffusion-imaging of the brain were performed in 10 healthy volunteers. MK, FA, and MD maps were constructed for all acquisitions, and the histograms were constructed. The normalized peak height and location of the histograms were compared among the acquisitions by use of Friedman and post hoc Wilcoxon tests. The effect of the repetition time (TR) on the diffusion-imaging metrics was also tested, and we corrected for its variation among acquisitions, if necessary. The results showed a shift in the peak location of the MK and MD histograms to the right with an increase in TR (p ≤ 0.01). The corrected peak location of the MK histograms, the normalized peak height of the FA histograms, the normalized peak height and the corrected peak location of the MD histograms varied significantly between the gated and non-gated acquisitions (p < 0.05). These results imply an influence of respiration and cardiac pulsation on the major diffusion-imaging metrics. The gating conditions must be kept identical if reproducible results are to be achieved. PMID:27073115
Solid-State Diffusional Behaviors of Functional Metal Oxides at Atomic Scale.
Chen, Jui-Yuan; Huang, Chun-Wei; Wu, Wen-Wei
2018-02-01
Metal/metal oxides have attracted extensive research interest because of their combination of functional properties and compatibility with industry. Diffusion and thermal reliability have become essential issues that require detailed study to develop atomic-scaled functional devices. In this work, the diffusional reaction behavior that transforms piezoelectric ZnO into magnetic Fe 3 O 4 is investigated at the atomic scale. The growth kinetics of metal oxides are systematically studied through macro- and microanalyses. The growth rates are evaluated by morphology changes, which determine whether the growth behavior was a diffusion- or reaction-controlled process. Furthermore, atom attachment on the kink step is observed at the atomic scale, which has important implications for the thermodynamics of functional metal oxides. Faster growth planes simultaneously decrease, which result in the predominance of low surface energy planes. These results directly reveal the atomic formation process of metal oxide via solid-state diffusion. In addition, the nanofabricated method provides a novel approach to investigate metal oxide evolution and sheds light on diffusional reaction behavior. More importantly, the results and phenomena of this study provide considerable inspiration to enhance the material stability and reliability of metal/oxide-based devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Astrophysics Data System (ADS)
Karamanos, K.; Mistakidis, S. I.; Massart, T. J.; Mistakidis, I. S.
2015-06-01
The entropy production and the variational functional of a Laplacian diffusional field around the first four fractal iterations of a linear self-similar tree (von Koch curve) is studied analytically and detailed predictions are stated. In a next stage, these predictions are confronted with results from numerical resolution of the Laplace equation by means of Finite Elements computations. After a brief review of the existing results, the range of distances near the geometric irregularity, the so-called "Near Field", a situation never studied in the past, is treated exhaustively. We notice here that in the Near Field, the usual notion of the active zone approximation introduced by Sapoval et al. [M. Filoche and B. Sapoval, Transfer across random versus deterministic fractal interfaces, Phys. Rev. Lett. 84(25) (2000) 5776;1 B. Sapoval, M. Filoche, K. Karamanos and R. Brizzi, Can one hear the shape of an electrode? I. Numerical study of the active zone in Laplacian transfer, Eur. Phys. J. B. Condens. Matter Complex Syst. 9(4) (1999) 739-753.]2 is strictly inapplicable. The basic new result is that the validity of the active-zone approximation based on irreversible thermodynamics is confirmed in this limit, and this implies a new interpretation of this notion for Laplacian diffusional fields.
Kaur, Dilraj Preet; Yamada, K; Park, Jin-Soo; Sekhon, S S
2009-04-23
Room temperature ionic liquid 2,3-dimethyl-1-hexylimidazolium bis(trifluoromethane sulfonyl)imide (DMHxImTFSI) has been synthesized and used in the preparation of polymer gel electrolytes containing polymethylmethacrylate and propylene carbonate (PC). The onset of ion diffusional motion has been studied by (1)H and (19)F NMR spectroscopy and the results obtained for ionic liquid, liquid electrolytes, and polymer gel electrolytes have been correlated with the ionic conductivity results for these electrolytes in the 100-400 K temperature range. The temperature at which (1)H and (19)F NMR lines show motional narrowing and hence ion diffusional motion starts has been found to be closely related to the temperature at which a large increase in ionic conductivity has been observed for these electrolytes. Polymer gel electrolytes have high ionic conductivity over a wide range of temperatures. Thermogravimetric analysis/differential scanning calorimetry studies show that the ionic liquid (DMHxImTFSI) used in the present study is thermally stable up to 400 degrees C, whereas the addition of PC lowers the thermal stability of polymer gel electrolytes containing the ionic liquid. Different electrolytes have been observed to show high ionic conductivity in different range of temperatures, which can be helpful in the design of polymer gel electrolytes for specific applications.
Omega-3 chicken egg detection system using a mobile-based image processing segmentation method
NASA Astrophysics Data System (ADS)
Nurhayati, Oky Dwi; Kurniawan Teguh, M.; Cintya Amalia, P.
2017-02-01
An Omega-3 chicken egg is a chicken egg produced through food engineering technology. It is produced by hen fed with high omega-3 fatty acids. So, it has fifteen times nutrient content of omega-3 higher than Leghorn's. Visually, its shell has the same shape and colour as Leghorn's. Each egg can be distinguished by breaking the egg's shell and testing the egg yolk's nutrient content in a laboratory. But, those methods were proven not effective and efficient. Observing this problem, the purpose of this research is to make an application to detect the type of omega-3 chicken egg by using a mobile-based computer vision. This application was built in OpenCV computer vision library to support Android Operating System. This experiment required some chicken egg images taken using an egg candling box. We used 60 omega-3 chicken and Leghorn eggs as samples. Then, using an Android smartphone, image acquisition of the egg was obtained. After that, we applied several steps using image processing methods such as Grab Cut, convert RGB image to eight bit grayscale, median filter, P-Tile segmentation, and morphology technique in this research. The next steps were feature extraction which was used to extract feature values via mean, variance, skewness, and kurtosis from each image. Finally, using digital image measurement, some chicken egg images were classified. The result showed that omega-3 chicken egg and Leghorn egg had different values. This system is able to provide accurate reading around of 91%.
Airyprime beams and their propagation characteristics
NASA Astrophysics Data System (ADS)
Zhou, Guoquan; Chen, Ruipin; Ru, Guoyun
2014-02-01
A type of Airyprime beam is introduced in this document. An analytical expression of Airyprime beams passing through a separable ABCD paraxial optical system is derived. The beam propagation factor of the Airyprime beam is proved to be 3.676. An analytical expression of the kurtosis parameter of an Airyprime beam passing through a separable ABCD paraxial optical system is also presented. The kurtosis parameter of the Airyprime beam passing through a separable ABCD paraxial optical system depends on the two ratios B/(Azrx) and B/(Azry). As a numerical example, the propagation characteristics of an Airyprime beam is demonstrated in free space. In the source plane, the Airyprime beam has nine lobes, one of which is the central dominant lobe. In the far field, the Airyprime beam becomes a dark-hollow beam with four uniform lobes. The evolvement of an Airyprime beam propagating in free space is well exhibited. Upon propagation, the intensity distribution of the Airyprime beam becomes flatter and the kurtosis parameter decreases from the maximum value 2.973 to a saturated value 1.302. The Airyprime beam is also compared with the second-order elegant Hermite-Gaussian beam. The novel propagation characteristics of Airyprime beams denote that they could have potential application prospects such as optical trapping.
Bazavov, A.; Ding, H. -T.; Hegde, P.; ...
2017-10-27
In this paper, we present results for the ratios of mean (M B), variance (σmore » $$2\\atop{B}$$), skewness (S B) and kurtosis (κ B) of net baryon-number fluctuations obtained in lattice QCD calculations with physical values of light and strange quark masses. Using next-to-leading order Taylor expansions in baryon chemical potential we find that qualitative features of these ratios closely resemble the corresponding experimentally measured cumulants ratios of net proton-number fluctuations for beam energies down to √sNN ≥ 19.6 GeV. We show that the difference in cumulant ratios for the mean net baryon-number, M B/σ$$2\\atop{B}$$ = χ$$B\\atop{1}$$ (T, µ B)/χ$$B\\atop{2}$$ (T, µ B) and the normalized skewness, S Bσ B = χ$$B\\atop{3}$$ (T, µB)/χ2 (T, µB ), nat-urally arises in QCD thermodynamics. Moreover, we establish a close relation between skewness and kurtosis ratios, S Bσ$$B\\atop{3}$$/M B = χ$$B\\atop{3}$$ (T, µ B)/χ$$B\\atop{1}$$ (T,µ B) and κ Bσ$$2\\atop{B}$$ = χ$$B\\atop{4}$$ (T,μ B)/χ$$B\\atop{2}$$ (T,μ B), valid at small values of the baryon chemical potential.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bazavov, A.; Ding, H. -T.; Hegde, P.
In this paper, we present results for the ratios of mean (M B), variance (σmore » $$2\\atop{B}$$), skewness (S B) and kurtosis (κ B) of net baryon-number fluctuations obtained in lattice QCD calculations with physical values of light and strange quark masses. Using next-to-leading order Taylor expansions in baryon chemical potential we find that qualitative features of these ratios closely resemble the corresponding experimentally measured cumulants ratios of net proton-number fluctuations for beam energies down to √sNN ≥ 19.6 GeV. We show that the difference in cumulant ratios for the mean net baryon-number, M B/σ$$2\\atop{B}$$ = χ$$B\\atop{1}$$ (T, µ B)/χ$$B\\atop{2}$$ (T, µ B) and the normalized skewness, S Bσ B = χ$$B\\atop{3}$$ (T, µB)/χ2 (T, µB ), nat-urally arises in QCD thermodynamics. Moreover, we establish a close relation between skewness and kurtosis ratios, S Bσ$$B\\atop{3}$$/M B = χ$$B\\atop{3}$$ (T, µ B)/χ$$B\\atop{1}$$ (T,µ B) and κ Bσ$$2\\atop{B}$$ = χ$$B\\atop{4}$$ (T,μ B)/χ$$B\\atop{2}$$ (T,μ B), valid at small values of the baryon chemical potential.« less
NASA Astrophysics Data System (ADS)
Kittiwisit, Piyanat; Bowman, Judd D.; Jacobs, Daniel C.; Beardsley, Adam P.; Thyagarajan, Nithyanandan
2018-03-01
We present a baseline sensitivity analysis of the Hydrogen Epoch of Reionization Array (HERA) and its build-out stages to one-point statistics (variance, skewness, and kurtosis) of redshifted 21 cm intensity fluctuation from the Epoch of Reionization (EoR) based on realistic mock observations. By developing a full-sky 21 cm light-cone model, taking into account the proper field of view and frequency bandwidth, utilizing a realistic measurement scheme, and assuming perfect foreground removal, we show that HERA will be able to recover statistics of the sky model with high sensitivity by averaging over measurements from multiple fields. All build-out stages will be able to detect variance, while skewness and kurtosis should be detectable for HERA128 and larger. We identify sample variance as the limiting constraint of the measurements at the end of reionization. The sensitivity can also be further improved by performing frequency windowing. In addition, we find that strong sample variance fluctuation in the kurtosis measured from an individual field of observation indicates the presence of outlying cold or hot regions in the underlying fluctuations, a feature that can potentially be used as an EoR bubble indicator.
THE ALLEN TELESCOPE ARRAY SEARCH FOR ELECTROSTATIC DISCHARGES ON MARS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, Marin M.; Siemion, Andrew P. V.; Bower, Geoffrey C.
The Allen Telescope Array was used to monitor Mars between 2010 March 9 and June 2, over a total of approximately 30 hr, for radio emission indicative of electrostatic discharge. The search was motivated by the report from Ruf et al. of the detection of non-thermal microwave radiation from Mars characterized by peaks in the power spectrum of the kurtosis, or kurtstrum, at 10 Hz, coinciding with a large dust storm event on 2006 June 8. For these observations, we developed a wideband signal processor at the Center for Astronomy Signal Processing and Electronics Research. This 1024 channel spectrometer calculatesmore » the accumulated power and power-squared, from which the spectral kurtosis is calculated post-observation. Variations in the kurtosis are indicative of non-Gaussianity in the signal, which can be used to detect variable cosmic signals as well as radio frequency interference (RFI). During the three-month period of observations, dust activity occurred on Mars in the form of small-scale dust storms; however, no signals indicating lightning discharge were detected. Frequent signals in the kurtstrum that contain spectral peaks with an approximate 10 Hz fundamental were seen at both 3.2 and 8.0 GHz, but were the result of narrowband RFI with harmonics spread over a broad frequency range.« less
Adaptation to changes in higher-order stimulus statistics in the salamander retina.
Tkačik, Gašper; Ghosh, Anandamohan; Schneidman, Elad; Segev, Ronen
2014-01-01
Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution.
Intermittency of solar system plasma turbulence near Venus and Earth
NASA Astrophysics Data System (ADS)
Teodorescu, Eliza; Echim, Marius; Chang, Tom
2016-04-01
We analyze magnetic field data from Venus Express (VEX) and CLUSTER to investigate the turbulent properties of the solar wind and the Earth's and Venus' magnetosheaths. A systematic study of the PDFs (Probability Distribution Functions) of the measured magnetic fluctuations and their fourth order moments (kurtosis) reveals numerous intermittent time series. The presence of intermittency is marked by non-Gaussian PDFs with heavy wings and a scale dependent kurtosis. Higher order analyses on the scale dependence of several moment orders of the PDFs, the structure functions, along with the scaling of the kurtosis allow for a selection of scales that pertain to different scaling regimes, governed by different physics. On such sub-ranges of scales we investigate the fractal structure of fluctuations through the Rank Ordered Multifractal Analysis - ROMA (Chang and Wu, 2008). ROMA is applied to a selection of intermittent magnetic field time series in the solar wind and planetary magnetosheaths and helps to quantify the turbulence properties through the estimation of a spectrum of local Hurst exponents. Research supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 313038/STORM, and a grant of the Romanian Ministry of National Education, CNCS - UEFISCDI, project number PN-II-ID-PCE-2012-4-0418.
Kaiser, Elias; Kromdijk, Johannes; Harbinson, Jeremy; Heuvelink, Ep; Marcelis, Leo F M
2017-01-01
Plants depend on photosynthesis for growth. In nature, factors such as temperature, humidity, CO 2 partial pressure, and spectrum and intensity of irradiance often fluctuate. Whereas irradiance intensity is most influential and has been studied in detail, understanding of interactions with other factors is lacking. We tested how photosynthetic induction after dark-light transitions was affected by CO 2 partial pressure (20, 40, 80 Pa), leaf temperatures (15·5, 22·8, 30·5 °C), leaf-to-air vapour pressure deficits (VPD leaf-air ; 0·5, 0·8, 1·6, 2·3 kPa) and blue irradiance (0-20 %) in tomato leaves (Solanum lycopersicum). Rates of photosynthetic induction strongly increased with CO 2 partial pressure, due to increased apparent Rubisco activation rates and reduced diffusional limitations. High leaf temperature produced slightly higher induction rates, and increased intrinsic water use efficiency and diffusional limitation. High VPD leaf-air slowed down induction rates and apparent Rubisco activation and (at 2·3 kPa) induced damped stomatal oscillations. Blue irradiance had no effect. Slower apparent Rubisco activation in elevated VPD leaf-air may be explained by low leaf internal CO 2 partial pressure at the beginning of induction. The environmental factors CO 2 partial pressure, temperature and VPD leaf-air had significant impacts on rates of photosynthetic induction, as well as on underlying diffusional, carboxylation and electron transport processes. Furthermore, maximizing Rubisco activation rates would increase photosynthesis by at most 6-8 % in ambient CO 2 partial pressure (across temperatures and humidities), while maximizing rates of stomatal opening would increase photosynthesis by at most 1-3 %. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Diffusional Transport of Organic Solutes in Subsurface Clay Lenses and Layers
NASA Astrophysics Data System (ADS)
Demond, A. H.; Ayral, D.; Goltz, M. N.
2009-12-01
The storage of organic solvents in clay lenses and layers in the subsurface creates long-term contaminant sources. Because of the low hydraulic conductivities of clay, it is thought that organic movement into clay lenses occurs through the process of diffusion. The ratio of the effective diffusion coefficient in the porous medium and the diffusion coefficient in bulk water is usually given by the tortuosity factor which accounts for the reduced area and the increased path length in the porous medium. However, there is field evidence which suggests that the concentrations in these lenses exceed that which can be accounted for by simple diffusion. There are reports, for example, of tortuosity factors greater than 1.0, which theoretically is not possible. Clays such as montmorillonite or bentonite shrink and swell depending on water content, and similar behavior can occur in the presence of organic solvents. In fact, research has shown that the basal spacing of bentonite can decrease by 50% when permeated with heptane. Such contraction of the clay structure can lead to the formation of cracks and macropores, with a concomitant alteration of the diffusional pathways that solutes follow. Models formulated for diffusional transport in soil are available to calculate the tortuosity factor as a function of water content. In addition, models are available to simulate phenomena in which the diffusion coefficient is concentration dependent. However, calculations of diffusional transport using such models show that they may not adequately reflect the impact of the alteration of the clay structure. However, modeling the transport of organic solutes in clay as a dual-domain system with some minimal advective transport in macropores can yield tortuosity factors greater than 1.0. Thus, it appears the cracking of clay in contact with organic solvents and a resultant advective component to transport of the solute may be an explanation of field observations.
Am Ende, Mary Tanya; Miller, Lee A
2007-02-01
An asymmetric membrane (AM) tablet was developed for a soluble model compound to study the in vitro drug release mechanisms in challenge conditions, including osmotic gradients, concentration gradients, and under potential coating failure modes. Porous, semipermable membrane integrity may be compromised by a high fat meal or by the presence of a defect in the coating that could cause a safety concern about dose-dumping. The osmotic and diffusional release mechanisms of the AM tablet were independently shut down such that their individual contribution to the overall drug release was measured. Shut off of osmotic and diffusional release was accomplished by performing dissolution studies into receptor solutions with osmotic pressure above the internal core osmotic pressure and into receptor solutions saturated with drug, respectively. The effect of coating failure modes on in vitro drug release from the AM tablet was assessed through a simulated high-fat meal and by intentionally compromising the coating integrity. The predominant drug release mechanism for the AM tablet was osmotic and accounted for approximately 90-95% of the total release. Osmotic release was shutoff when the receptor media osmotic pressure exceeded 76 atm. Diffusional release of the soluble drug amounted to 5-10% of the total release mechanism. The observed negative in vitro food effect was attributed to the increased osmotic pressure from the high fat meal when compared to the predicted release rates in sucrose media with the same osmotic pressure. This suppression in drug release rate due to a high fat meal is not anticipated to affect in vivo performance of the dosage form, as the rise in pressure is short-lived. Drug release from the AM system studied was determined to be robust to varying and extreme challenge conditions. The conditions investigated included varying pH, agitation rate, media osmotic pressure, media saturated with drug to eliminate the concentration gradient, simulated high fat meal, and intentionally placed film coating defects. Osmotic and diffusional shut off experiments suggest that the mechanism governing drug release is a combination of osmotic and diffusional at approximately 90-95% and 5-10%, respectively. In addition, the coating failure mode studies revealed this formulation and design is not significantly affected by a high fat meal or by an intentionally placed defect in the film coating, and more specifically, did not result in a burst of drug release.
Anorexia Nervosa: Analysis of Trabecular Texture with CT
Tabari, Azadeh; Torriani, Martin; Miller, Karen K.; Klibanski, Anne; Kalra, Mannudeep K.
2017-01-01
Purpose To determine indexes of skeletal integrity by using computed tomographic (CT) trabecular texture analysis of the lumbar spine in patients with anorexia nervosa and normal-weight control subjects and to determine body composition predictors of trabecular texture. Materials and Methods This cross-sectional study was approved by the institutional review board and compliant with HIPAA. Written informed consent was obtained. The study included 30 women with anorexia nervosa (mean age ± standard deviation, 26 years ± 6) and 30 normal-weight age-matched women (control group). All participants underwent low-dose single-section quantitative CT of the L4 vertebral body with use of a calibration phantom. Trabecular texture analysis was performed by using software. Skewness (asymmetry of gray-level pixel distribution), kurtosis (pointiness of pixel distribution), entropy (inhomogeneity of pixel distribution), and mean value of positive pixels (MPP) were assessed. Bone mineral density and abdominal fat and paraspinal muscle areas were quantified with quantitative CT. Women with anorexia nervosa and normal-weight control subjects were compared by using the Student t test. Linear regression analyses were performed to determine associations between trabecular texture and body composition. Results Women with anorexia nervosa had higher skewness and kurtosis, lower MPP (P < .001), and a trend toward lower entropy (P = .07) compared with control subjects. Bone mineral density, abdominal fat area, and paraspinal muscle area were inversely associated with skewness and kurtosis and positively associated with MPP and entropy. Texture parameters, but not bone mineral density, were associated with lowest lifetime weight and duration of amenorrhea in anorexia nervosa. Conclusion Patients with anorexia nervosa had increased skewness and kurtosis and decreased entropy and MPP compared with normal-weight control subjects. These parameters were associated with lowest lifetime weight and duration of amenorrhea, but there were no such associations with bone mineral density. These findings suggest that trabecular texture analysis might contribute information about bone health in anorexia nervosa that is independent of that provided with bone mineral density. © RSNA, 2016 PMID:27797678
Nguyen-Kim, Thi Dan Linh; Maurer, Britta; Suliman, Yossra A; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas
2018-04-01
To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051-0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients.
Anorexia Nervosa: Analysis of Trabecular Texture with CT.
Tabari, Azadeh; Torriani, Martin; Miller, Karen K; Klibanski, Anne; Kalra, Mannudeep K; Bredella, Miriam A
2017-04-01
Purpose To determine indexes of skeletal integrity by using computed tomographic (CT) trabecular texture analysis of the lumbar spine in patients with anorexia nervosa and normal-weight control subjects and to determine body composition predictors of trabecular texture. Materials and Methods This cross-sectional study was approved by the institutional review board and compliant with HIPAA. Written informed consent was obtained. The study included 30 women with anorexia nervosa (mean age ± standard deviation, 26 years ± 6) and 30 normal-weight age-matched women (control group). All participants underwent low-dose single-section quantitative CT of the L4 vertebral body with use of a calibration phantom. Trabecular texture analysis was performed by using software. Skewness (asymmetry of gray-level pixel distribution), kurtosis (pointiness of pixel distribution), entropy (inhomogeneity of pixel distribution), and mean value of positive pixels (MPP) were assessed. Bone mineral density and abdominal fat and paraspinal muscle areas were quantified with quantitative CT. Women with anorexia nervosa and normal-weight control subjects were compared by using the Student t test. Linear regression analyses were performed to determine associations between trabecular texture and body composition. Results Women with anorexia nervosa had higher skewness and kurtosis, lower MPP (P < .001), and a trend toward lower entropy (P = .07) compared with control subjects. Bone mineral density, abdominal fat area, and paraspinal muscle area were inversely associated with skewness and kurtosis and positively associated with MPP and entropy. Texture parameters, but not bone mineral density, were associated with lowest lifetime weight and duration of amenorrhea in anorexia nervosa. Conclusion Patients with anorexia nervosa had increased skewness and kurtosis and decreased entropy and MPP compared with normal-weight control subjects. These parameters were associated with lowest lifetime weight and duration of amenorrhea, but there were no such associations with bone mineral density. These findings suggest that trabecular texture analysis might contribute information about bone health in anorexia nervosa that is independent of that provided with bone mineral density. © RSNA, 2016.
Diffusional correlations among multiple active sites in a single enzyme.
Echeverria, Carlos; Kapral, Raymond
2014-04-07
Simulations of the enzymatic dynamics of a model enzyme containing multiple substrate binding sites indicate the existence of diffusional correlations in the chemical reactivity of the active sites. A coarse-grain, particle-based, mesoscopic description of the system, comprising the enzyme, the substrate, the product and solvent, is constructed to study these effects. The reactive and non-reactive dynamics is followed using a hybrid scheme that combines molecular dynamics for the enzyme, substrate and product molecules with multiparticle collision dynamics for the solvent. It is found that the reactivity of an individual active site in the multiple-active-site enzyme is reduced substantially, and this effect is analyzed and attributed to diffusive competition for the substrate among the different active sites in the enzyme.
Analysis of the depletion of a stored aerosol in low gravity
NASA Technical Reports Server (NTRS)
Squires, P.
1977-01-01
The depletion of an aerosol stored in a container has been studied in l-g and in low gravity. Models were developed for sedimentation, coagulation and diffusional losses to the walls. The overall depletion caused by these three mechanisms is predicted to be of order 5 to 8 percent per hour in terrestrial conditions, which agrees with laboratory experience. Applying the models to a low gravity situation indicates that there only coagulation will be significant. (Gravity influences diffusional losses because of convection currents caused by random temperature gradients). For the types of aerosol studied, the rate of depletion of particles should be somewhat less than 0.001 N percent per hour, where N is the concentration per cu cm.
Vellmer, Sebastian; Tonoyan, Aram S; Suter, Dieter; Pronin, Igor N; Maximov, Ivan I
2018-02-01
Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used. In the present work we assess the effect of different pre-processing procedures such as a noise correction, different smoothing algorithms and spatial interpolation of raw diffusion data, with respect to the accuracy of brain glioma differentiation. As a set of sensitive biomarkers of the glioma malignancy grades we chose the derived scalar metrics from diffusion and kurtosis tensor imaging as well as the neurite orientation dispersion and density imaging (NODDI) biophysical model. Our results show that the application of noise correction, anisotropic diffusion filtering, and cubic-order spline interpolation resulted in the highest sensitivity and specificity for glioma malignancy grading. Thus, these pre-processing steps are recommended for the statistical analysis in brain tumour studies. Copyright © 2017. Published by Elsevier GmbH.
Spatiotemporal norepinephrine mapping using a high-density CMOS microelectrode array.
Wydallis, John B; Feeny, Rachel M; Wilson, William; Kern, Tucker; Chen, Tom; Tobet, Stuart; Reynolds, Melissa M; Henry, Charles S
2015-10-21
A high-density amperometric electrode array containing 8192 individually addressable platinum working electrodes with an integrated potentiostat fabricated using Complementary Metal Oxide Semiconductor (CMOS) processes is reported. The array was designed to enable electrochemical imaging of chemical gradients with high spatiotemporal resolution. Electrodes are arranged over a 2 mm × 2 mm surface area into 64 subarrays consisting of 128 individual Pt working electrodes as well as Pt pseudo-reference and auxiliary electrodes. Amperometric measurements of norepinephrine in tissue culture media were used to demonstrate the ability of the array to measure concentration gradients in complex media. Poly(dimethylsiloxane) microfluidics were incorporated to control the chemical concentrations in time and space, and the electrochemical response at each electrode was monitored to generate electrochemical heat maps, demonstrating the array's imaging capabilities. A temporal resolution of 10 ms can be achieved by simultaneously monitoring a single subarray of 128 electrodes. The entire 2 mm × 2 mm area can be electrochemically imaged in 64 seconds by cycling through all subarrays at a rate of 1 Hz per subarray. Monitoring diffusional transport of norepinephrine is used to demonstrate the spatiotemporal resolution capabilities of the system.
Delouche, Aurélie; Attyé, Arnaud; Heck, Olivier; Grand, Sylvie; Kastler, Adrian; Lamalle, Laurent; Renard, Felix; Krainik, Alexandre
2016-01-01
Mild traumatic brain injury (mTBI) is a leading cause of disability in adults, many of whom report a distressing combination of physical, emotional and cognitive symptoms, collectively known as post-concussion syndrome, that persist after the injury. Significant developments in magnetic resonance diffusion imaging, involving voxel-based quantitative analysis through the measurement of fractional anisotropy or mean diffusivity, have enhanced our knowledge on the different stages of mTBI pathophysiology. Other diffusion imaging-derived techniques, including diffusion kurtosis imaging with multi-shell diffusion and high-order tractography models, have recently demonstrated their usefulness in mTBI. Our review starts by briefly outlining the physical basis of diffusion tensor imaging including the pitfalls for use in brain trauma, before discussing findings from diagnostic trials testing its usefulness in assessing brain structural changes in patients with mTBI. Use of different post-processing techniques for the diffusion imaging data, identified the corpus callosum as the most frequently injured structure in mTBI, particularly at sub-acute and chronic stages, and a crucial location for evaluating functional outcome. However, structural changes appear too subtle for identification using traditional diffusion biomarkers, thus disallowing expansion of these techniques into clinical practice. In this regard, more advanced diffusion techniques are promising in the assessment of this complex disease. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thor, M; Tyagi, N; Deasy, J
2015-06-15
Purpose: The aim of this study was to explore the use of Magnetic Resonance Imaging (MRI)-derived features as indicators of Radiotherapy (RT)-induced normal tissue morbidity. We also investigate the relationship between these features and RT dose in four critical structures. Methods: We demonstrate our approach for four patients treated with RT for base of tongue cancer in 2005–2007. For each patient, two MRI scans (T1-weighted pre (T1pre) and post (T1post) gadolinium contrast-enhancement) were acquired within the first six months after RT. The assessed morbidity endpoint observed in 2/4 patients was Grade 2+ CTCAEv.3 trismus. Four ipsilateral masticatory-related structures (masseter, lateralmore » and medial pterygoid, and the temporal muscles) were delineated on both T1pre and T1post and these scans were co-registered to the treatment planning CT using a deformable demons algorithm. For each structure, the maximum and mean RT dose, and six MRI-derived features (the second order texture features entropy and homogeneity, and the first order mean, median, kurtosis, and skewness) were extracted and compared structure-wise between patients with and without trismus. All MRI-derived features were calculated as the difference between T1pre and T1post, ΔS. Results: For 5/6 features and all structures, ΔS diverged between trismus and non-trismus patients particularly for the masseter, lateral pterygoid, and temporal muscles using the kurtosis feature (−0.2 vs. 6.4 for lateral pterygoid). Both the maximum and mean RT dose in all four muscles were higher amongst the trismus patients (with the maximum dose being up to 25 Gy higher). Conclusion: Using MRI-derived features to quantify RT-induced normal tissue complications is feasible. We showed that several features are different between patients with and without morbidity and that the RT dose in all investigated structures are higher amongst patients with morbidity. MRI-derived features, therefore, has the potential to improve predictions of normal tissue morbidity.« less
Surov, Alexey; Meyer, Hans Jonas; Leifels, Leonard; Höhn, Anne-Kathrin; Richter, Cindy; Winter, Karsten
2018-04-20
Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of K trans , V e , and K ep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with K trans min ( p = -0.386, P = 0.043) and s K trans skewness ( p = 0.382, P = 0.045), V e min ( p = -0.473, P = 0.011), Ve entropy ( p = 0.424, P = 0.025), and K ep entropy ( p = 0.464, P = 0.013). Cell count correlated with K trans kurtosis ( p = 0.40, P = 0.034), V e entropy ( p = 0.475, P = 0.011). Total nucleic area correlated with V e max ( p = 0.386, P = 0.042) and V e entropy ( p = 0.411, P = 0.030). In G1/2 tumors, only K trans entropy correlated well with total ( P =0.78, P =0.013) and average nucleic areas ( p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min ( p = -0.552, P = 0.022) and V e entropy ( p = 0.524, P = 0.031). Ve max correlated with total nucleic area ( p = 0.483, P = 0.049). Kep max correlated with total area ( p = -0.51, P = 0.037), and K ep entropy with KI 67 ( p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of K trans , V e , and K ep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.
Li, Zhiwei; Ai, Tao; Hu, Yiqi; Yan, Xu; Nickel, Marcel Dominik; Xu, Xiao; Xia, Liming
2018-01-01
To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (K trans ), outflow rate of agent between interstitium and plasma (K ep ), extravascular space volume per unit volume of tissue (v e ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis. Malignant breast lesions had significantly higher K trans , K ep , and lower v e in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of v e than benign breast lesions (all P < 0.05). There was no significant difference in kurtosis values between malignant and benign breast lesions (all P > 0.05). The 90th percentile of K trans , the 90th percentile of K ep , and the 50th percentile of v e showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of K ep achieved the highest AUC value (0.927) among all histogram-derived values. The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of K ep may be the best indicator in differentiation between malignant and benign breast lesions. 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96. © 2017 International Society for Magnetic Resonance in Medicine.
Han, Xu; Suo, Shiteng; Sun, Yawen; Zu, Jinyan; Qu, Jianxun; Zhou, Yan; Chen, Zengai; Xu, Jianrong
2017-03-01
To compare four methods of region-of-interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in distinguishing low-grade gliomas (LGGs) from high-grade gliomas (HGGs). Two independent readers measured ADC parameters using four ROI methods (single-slice [single-round, five-round and freehand] and whole-volume) on 43 patients (20 LGGs, 23 HGGs) who had undergone 3.0 Tesla diffusion-weighted imaging and time required for each method of ADC measurements was recorded. Intraclass correlation coefficients (ICCs) were used to assess interobserver variability of ADC measurements. Mean and minimum ADC values and time required were compared using paired Student's t-tests. All ADC parameters (mean/minimum ADC values of three single-slice methods, mean/minimum/standard deviation/skewness/kurtosis/the10 th and 25 th percentiles/median/maximum of whole-volume method) were correlated with tumor grade (low versus high) by unpaired Student's t-tests. Discriminative ability was determined by receiver operating characteristic curves. All ADC measurements except minimum, skewness, and kurtosis of whole-volume ROI differed significantly between LGGs and HGGs (all P < 0.05). Mean ADC value of single-round ROI had the highest effect size (0.72) and the greatest areas under the curve (0.872). Three single-slice methods had good to excellent ICCs (0.67-0.89) and the whole-volume method fair to excellent ICCs (0.32-0.96). Minimum ADC values differed significantly between whole-volume and single-round ROI (P = 0.003) and, between whole-volume and five-round ROI (P = 0.001). The whole-volume method took significantly longer than all single-slice methods (all P < 0.001). ADC measurements are influenced by ROI determination methods. Whole-volume histogram analysis did not yield better results than single-slice methods and took longer. Mean ADC value derived from single-round ROI is the most optimal parameter for differentiating LGGs from HGGs. 3 J. Magn. Reson. Imaging 2017;45:722-730. © 2016 International Society for Magnetic Resonance in Medicine.
Nakamura, Akihiko; Tasaki, Tomoyuki; Ishiwata, Daiki; Yamamoto, Mayuko; Okuni, Yasuko; Visootsat, Akasit; Maximilien, Morice; Noji, Hiroyuki; Uchiyama, Taku; Samejima, Masahiro; Igarashi, Kiyohiko; Iino, Ryota
2016-01-01
Trichoderma reesei Cel6A (TrCel6A) is a cellobiohydrolase that hydrolyzes crystalline cellulose into cellobiose. Here we directly observed the reaction cycle (binding, surface movement, and dissociation) of single-molecule intact TrCel6A, isolated catalytic domain (CD), cellulose-binding module (CBM), and CBM and linker (CBM-linker) on crystalline cellulose Iα. The CBM-linker showed a binding rate constant almost half that of intact TrCel6A, whereas those of the CD and CBM were only one-tenth of intact TrCel6A. These results indicate that the glycosylated linker region largely contributes to initial binding on crystalline cellulose. After binding, all samples showed slow and fast dissociations, likely caused by the two different bound states due to the heterogeneity of cellulose surface. The CBM showed much higher specificity to the high affinity site than to the low affinity site, whereas the CD did not, suggesting that the CBM leads the CD to the hydrophobic surface of crystalline cellulose. On the cellulose surface, intact molecules showed slow processive movements (8.8 ± 5.5 nm/s) and fast diffusional movements (30–40 nm/s), whereas the CBM-Linker, CD, and a catalytically inactive full-length mutant showed only fast diffusional movements. These results suggest that both direct binding and surface diffusion contribute to searching of the hydrolysable point of cellulose chains. The duration time constant for the processive movement was 7.7 s, and processivity was estimated as 68 ± 42. Our results reveal the role of each domain in the elementary steps of the reaction cycle and provide the first direct evidence of the processive movement of TrCel6A on crystalline cellulose. PMID:27609516
Sarkar, Mitul; Koland, John G
2016-01-01
The fluorescence recovery after photobleaching (FRAP) method is a straightforward means of assessing the diffusional mobility of membrane-associated proteins that is readily performed with current confocal microscopy instrumentation. We describe here the specific application of the FRAP method in characterizing the lateral diffusion of genetically encoded green fluorescence protein (GFP)-tagged plasma membrane receptor proteins. The method is exemplified in an examination of whether the previously observed segregation of the mammalian HER3 receptor protein in discrete plasma membrane microdomains results from its physical interaction with cellular entities that restrict its mobility. Our FRAP measurements of the diffusional mobility of GFP-tagged HER3 reporters expressed in MCF7 cultured breast cancer cells showed that despite the observed segregation of HER3 receptors within plasma membrane microdomains their diffusion on the macroscopic scale is not spatially restricted. Thus, in FRAP analyses of various HER3 reporters a near-complete recovery of fluorescence after photobleaching was observed, indicating that HER3 receptors are not immobilized by long-lived physical interactions with intracellular species. An examination of HER3 proteins with varying intracellular domain sequence truncations also indicated that a proposed formation of oligomeric HER3 networks, mediated by physical interactions involving specific HER3 intracellular domain sequences, either does not occur or does not significantly reduce HER3 mobility on the macroscopic scale.
Zhou, Nan; Guo, Tingting; Zheng, Huanhuan; Pan, Xia; Chu, Chen; Dou, Xin; Li, Ming; Liu, Song; Zhu, Lijing; Liu, Baorui; Chen, Weibo; He, Jian; Yan, Jing; Zhou, Zhengyang; Yang, Xiaofeng
2017-01-01
We investigated apparent diffusion coefficient (ADC) histogram analysis to evaluate radiation-induced parotid damage and predict xerostomia degrees in nasopharyngeal carcinoma (NPC) patients receiving radiotherapy. The imaging of bilateral parotid glands in NPC patients was conducted 2 weeks before radiotherapy (time point 1), one month after radiotherapy (time point 2), and four months after radiotherapy (time point 3). From time point 1 to 2, parotid volume, skewness, and kurtosis decreased (P < 0.001, = 0.001, and < 0.001, respectively), but all other ADC histogram parameters increased (all P < 0.001, except P = 0.006 for standard deviation [SD]). From time point 2 to 3, parotid volume continued to decrease (P = 0.022), and SD, 75th and 90th percentiles continued to increase (P = 0.024, 0.010, and 0.006, respectively). Early change rates of parotid ADCmean, ADCmin, kurtosis, and 25th, 50th, 75th, 90th percentiles (from time point 1 to 2) correlated with late parotid atrophy rate (from time point 1 to 3) (all P < 0.05). Multiple linear regression analysis revealed correlations among parotid volume, time point, and ADC histogram parameters. Early mean change rates for bilateral parotid SD and ADCmax could predict late xerostomia degrees at seven months after radiotherapy (three months after time point 3) with AUC of 0.781 and 0.818 (P = 0.014, 0.005, respectively). ADC histogram parameters were reproducible (intraclass correlation coefficient, 0.830 - 0.999). ADC histogram analysis could be used to evaluate radiation-induced parotid damage noninvasively, and predict late xerostomia degrees of NPC patients treated with radiotherapy. PMID:29050274
Zhang, Wei; Zhou, Yue; Xu, Xiao-Quan; Kong, Ling-Yan; Xu, Hai; Yu, Tong-Fu; Shi, Hai-Bin; Feng, Qing
2018-01-01
To assess the performance of a whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating thymic carcinoma from lymphoma, and compare it with that of a commonly used hot-spot region-of-interest (ROI)-based ADC measurement. Diffusion weighted imaging data of 15 patients with thymic carcinoma and 13 patients with lymphoma were retrospectively collected and processed with a mono-exponential model. ADC measurements were performed by using a histogram-based and hot-spot-ROI-based approach. In the histogram-based approach, the following parameters were generated: mean ADC (ADC mean ), median ADC (ADC median ), 10th and 90th percentile of ADC (ADC 10 and ADC 90 ), kurtosis, and skewness. The difference in ADCs between thymic carcinoma and lymphoma was compared using a t test. Receiver operating characteristic analyses were conducted to determine and compare the differentiating performance of ADCs. Lymphoma demonstrated significantly lower ADC mean , ADC median , ADC 10 , ADC 90 , and hot-spot-ROI-based mean ADC than those found in thymic carcinoma (all p values < 0.05). There were no differences found in the kurtosis ( p = 0.412) and skewness ( p = 0.273). The ADC 10 demonstrated optimal differentiating performance (cut-off value, 0.403 × 10 -3 mm 2 /s; area under the receiver operating characteristic curve [AUC], 0.977; sensitivity, 92.3%; specificity, 93.3%), followed by the ADC mean , ADC median , ADC 90 , and hot-spot-ROI-based mean ADC. The AUC of ADC 10 was significantly higher than that of the hot spot ROI based ADC (0.977 vs. 0.797, p = 0.036). Compared with the commonly used hot spot ROI based ADC measurement, a histogram analysis of ADC maps can improve the differentiating performance between thymic carcinoma and lymphoma.
Zhou, Nan; Guo, Tingting; Zheng, Huanhuan; Pan, Xia; Chu, Chen; Dou, Xin; Li, Ming; Liu, Song; Zhu, Lijing; Liu, Baorui; Chen, Weibo; He, Jian; Yan, Jing; Zhou, Zhengyang; Yang, Xiaofeng
2017-09-19
We investigated apparent diffusion coefficient (ADC) histogram analysis to evaluate radiation-induced parotid damage and predict xerostomia degrees in nasopharyngeal carcinoma (NPC) patients receiving radiotherapy. The imaging of bilateral parotid glands in NPC patients was conducted 2 weeks before radiotherapy (time point 1), one month after radiotherapy (time point 2), and four months after radiotherapy (time point 3). From time point 1 to 2, parotid volume, skewness, and kurtosis decreased ( P < 0.001, = 0.001, and < 0.001, respectively), but all other ADC histogram parameters increased (all P < 0.001, except P = 0.006 for standard deviation [SD]). From time point 2 to 3, parotid volume continued to decrease ( P = 0.022), and SD, 75 th and 90 th percentiles continued to increase ( P = 0.024, 0.010, and 0.006, respectively). Early change rates of parotid ADC mean , ADC min , kurtosis, and 25 th , 50 th , 75 th , 90 th percentiles (from time point 1 to 2) correlated with late parotid atrophy rate (from time point 1 to 3) (all P < 0.05). Multiple linear regression analysis revealed correlations among parotid volume, time point, and ADC histogram parameters. Early mean change rates for bilateral parotid SD and ADC max could predict late xerostomia degrees at seven months after radiotherapy (three months after time point 3) with AUC of 0.781 and 0.818 ( P = 0.014, 0.005, respectively). ADC histogram parameters were reproducible (intraclass correlation coefficient, 0.830 - 0.999). ADC histogram analysis could be used to evaluate radiation-induced parotid damage noninvasively, and predict late xerostomia degrees of NPC patients treated with radiotherapy.
Xu, Xiao-Quan; Li, Yan; Hong, Xun-Ning; Wu, Fei-Yun; Shi, Hai-Bin
2017-02-01
To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA). Diffusion-weighted (DW) images (b = 0 and 1000 s/mm 2 ) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADC mean ), median ADC (ADC median ), 10th/25th/75th/90th percentile ADC (ADC 10 , ADC 25 , ADC 75 and ADC 90 ), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter. Significant differences were found on the ADC mean , ADC median , ADC 10 , ADC 25 , ADC 75 and ADC 90 between CPAM and VS (all p values < 0.001), while no significant difference was found on kurtosis (p = 0.562) and skewness (p = 0.047). ROC curves analysis revealed, a cut-off value of 1.126 × 10 -3 mm 2 /s for the ADC 90 value generated highest area under curves (AUC) for differentiating CPAM from VS (AUC, 0.975; sensitivity, 100%; specificity, 88.9%). Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC 90 value was the most promising parameter for differentiating these two entities.
Iyer, Sneha R; Gogate, Parag R
2017-01-01
The current work investigates the application of low intensity ultrasonic irradiation for improving the cooling crystallization of Mefenamic Acid for the first time. The crystal shape and size has been analyzed with the help of optical microscope and image analysis software respectively. The effect of ultrasonic irradiation on crystal size, particle size distribution (PSD) and yield has been investigated, also establishing the comparison with conventional approach. It has been observed that application of ultrasound not only enhances the yield but also reduces the induction time for crystallization as compared to conventional cooling crystallization technique. In the presence of ultrasound, the maximum yield was obtained at optimum conditions of power dissipation of 30W and ultrasonic irradiation time of 10min. The yield was further improved by application of ultrasound in cycles where the formed crystals are allowed to grow in the absence of ultrasonic irradiation. It was also observed that the desired crystal morphology was obtained for the ultrasound assisted crystallization. The conventionally obtained needle shaped crystals transformed into plate shaped crystals for the ultrasound assisted crystallization. The particle size distribution was analyzed using statistical means on the basis of skewness and kurtosis values. It was observed that the skewness and excess kurtosis value for ultrasound assisted crystallization was significantly lower as compared to the conventional approach. XRD analysis also revealed better crystal properties for the processed mefenamic acid using ultrasound assisted approach. The overall process intensification benefits of mefenamic acid crystallization using the ultrasound assisted approach were reduced particle size, increase in the yield and uniform PSD coupled with desired morphology. Copyright © 2016 Elsevier B.V. All rights reserved.
Revert Ventura, A J; Sanz Requena, R; Martí-Bonmatí, L; Pallardó, Y; Jornet, J; Gaspar, C
2014-01-01
To study whether the histograms of quantitative parameters of perfusion in MRI obtained from tumor volume and peritumor volume make it possible to grade astrocytomas in vivo. We included 61 patients with histological diagnoses of grade II, III, or IV astrocytomas who underwent T2*-weighted perfusion MRI after intravenous contrast agent injection. We manually selected the tumor volume and peritumor volume and quantified the following perfusion parameters on a voxel-by-voxel basis: blood volume (BV), blood flow (BF), mean transit time (TTM), transfer constant (K(trans)), washout coefficient, interstitial volume, and vascular volume. For each volume, we obtained the corresponding histogram with its mean, standard deviation, and kurtosis (using the standard deviation and kurtosis as measures of heterogeneity) and we compared the differences in each parameter between different grades of tumor. We also calculated the mean and standard deviation of the highest 10% of values. Finally, we performed a multiparametric discriminant analysis to improve the classification. For tumor volume, we found statistically significant differences among the three grades of tumor for the means and standard deviations of BV, BF, and K(trans), both for the entire distribution and for the highest 10% of values. For the peritumor volume, we found no significant differences for any parameters. The discriminant analysis improved the classification slightly. The quantification of the volume parameters of the entire region of the tumor with BV, BF, and K(trans) is useful for grading astrocytomas. The heterogeneity represented by the standard deviation of BF is the most reliable diagnostic parameter for distinguishing between low grade and high grade lesions. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.
MP estimation applied to platykurtic sets of geodetic observations
NASA Astrophysics Data System (ADS)
Wiśniewski, Zbigniew
2017-06-01
MP estimation is a method which concerns estimating of the location parameters when the probabilistic models of observations differ from the normal distributions in the kurtosis or asymmetry. The system of Pearson's distributions is the probabilistic basis for the method. So far, such a method was applied and analyzed mostly for leptokurtic or mesokurtic distributions (Pearson's distributions of types IV or VII), which predominate practical cases. The analyses of geodetic or astronomical observations show that we may also deal with sets which have moderate asymmetry or small negative excess kurtosis. Asymmetry might result from the influence of many small systematic errors, which were not eliminated during preprocessing of data. The excess kurtosis can be related with bigger or smaller (in relations to the Hagen hypothesis) frequency of occurrence of the elementary errors which are close to zero. Considering that fact, this paper focuses on the estimation with application of the Pearson platykurtic distributions of types I or II. The paper presents the solution of the corresponding optimization problem and its basic properties. Although platykurtic distributions are rare in practice, it was an interesting issue to find out what results can be provided by MP estimation in the case of such observation distributions. The numerical tests which are presented in the paper are rather limited; however, they allow us to draw some general conclusions.
Generating Multivariate Ordinal Data via Entropy Principles.
Lee, Yen; Kaplan, David
2018-03-01
When conducting robustness research where the focus of attention is on the impact of non-normality, the marginal skewness and kurtosis are often used to set the degree of non-normality. Monte Carlo methods are commonly applied to conduct this type of research by simulating data from distributions with skewness and kurtosis constrained to pre-specified values. Although several procedures have been proposed to simulate data from distributions with these constraints, no corresponding procedures have been applied for discrete distributions. In this paper, we present two procedures based on the principles of maximum entropy and minimum cross-entropy to estimate the multivariate observed ordinal distributions with constraints on skewness and kurtosis. For these procedures, the correlation matrix of the observed variables is not specified but depends on the relationships between the latent response variables. With the estimated distributions, researchers can study robustness not only focusing on the levels of non-normality but also on the variations in the distribution shapes. A simulation study demonstrates that these procedures yield excellent agreement between specified parameters and those of estimated distributions. A robustness study concerning the effect of distribution shape in the context of confirmatory factor analysis shows that shape can affect the robust [Formula: see text] and robust fit indices, especially when the sample size is small, the data are severely non-normal, and the fitted model is complex.
Gas sensor with attenuated drift characteristic
Chen, Ing-Shin [Danbury, CT; Chen, Philip S. H. [Bethel, CT; Neuner, Jeffrey W [Bethel, CT; Welch, James [Fairfield, CT; Hendrix, Bryan [Danbury, CT; Dimeo, Jr., Frank [Danbury, CT
2008-05-13
A sensor with an attenuated drift characteristic, including a layer structure in which a sensing layer has a layer of diffusional barrier material on at least one of its faces. The sensor may for example be constituted as a hydrogen gas sensor including a palladium/yttrium layer structure formed on a micro-hotplate base, with a chromium barrier layer between the yttrium layer and the micro-hotplate, and with a tantalum barrier layer between the yttrium layer and an overlying palladium protective layer. The gas sensor is useful for detection of a target gas in environments susceptible to generation or incursion of such gas, and achieves substantial (e.g., >90%) reduction of signal drift from the gas sensor in extended operation, relative to a corresponding gas sensor lacking the diffusional barrier structure of the invention
Barriers to the free diffusion of proteins and lipids in the plasma membrane
Trimble, William S.
2015-01-01
Biological membranes segregate into specialized functional domains of distinct composition, which can persist for the entire life of the cell. How separation of their lipid and (glyco)protein components is generated and maintained is not well understood, but the existence of diffusional barriers has been proposed. Remarkably, the physical nature of such barriers and the manner whereby they impede the free diffusion of molecules in the plane of the membrane has rarely been studied in depth. Moreover, alternative mechanisms capable of generating membrane inhomogeneity are often disregarded. Here we describe prototypical biological systems where membrane segregation has been amply documented and discuss the role of diffusional barriers and other processes in the generation and maintenance of their structural and functional compartmentalization. PMID:25646084
Barriers to the free diffusion of proteins and lipids in the plasma membrane.
Trimble, William S; Grinstein, Sergio
2015-02-02
Biological membranes segregate into specialized functional domains of distinct composition, which can persist for the entire life of the cell. How separation of their lipid and (glyco)protein components is generated and maintained is not well understood, but the existence of diffusional barriers has been proposed. Remarkably, the physical nature of such barriers and the manner whereby they impede the free diffusion of molecules in the plane of the membrane has rarely been studied in depth. Moreover, alternative mechanisms capable of generating membrane inhomogeneity are often disregarded. Here we describe prototypical biological systems where membrane segregation has been amply documented and discuss the role of diffusional barriers and other processes in the generation and maintenance of their structural and functional compartmentalization. © 2015 Trimble and Grinstein.
Effect of respiratory and cardiac gating on the major diffusion-imaging metrics.
Hamaguchi, Hiroyuki; Tha, Khin Khin; Sugimori, Hiroyuki; Nakanishi, Mitsuhiro; Nakagawa, Shin; Fujiwara, Taro; Yoshida, Hirokazu; Takamori, Sayaka; Shirato, Hiroki
2016-08-01
The effect of respiratory gating on the major diffusion-imaging metrics and that of cardiac gating on mean kurtosis (MK) are not known. For evaluation of whether the major diffusion-imaging metrics-MK, fractional anisotropy (FA), and mean diffusivity (MD) of the brain-varied between gated and non-gated acquisitions, respiratory-gated, cardiac-gated, and non-gated diffusion-imaging of the brain were performed in 10 healthy volunteers. MK, FA, and MD maps were constructed for all acquisitions, and the histograms were constructed. The normalized peak height and location of the histograms were compared among the acquisitions by use of Friedman and post hoc Wilcoxon tests. The effect of the repetition time (TR) on the diffusion-imaging metrics was also tested, and we corrected for its variation among acquisitions, if necessary. The results showed a shift in the peak location of the MK and MD histograms to the right with an increase in TR (p ≤ 0.01). The corrected peak location of the MK histograms, the normalized peak height of the FA histograms, the normalized peak height and the corrected peak location of the MD histograms varied significantly between the gated and non-gated acquisitions (p < 0.05). These results imply an influence of respiration and cardiac pulsation on the major diffusion-imaging metrics. The gating conditions must be kept identical if reproducible results are to be achieved. © The Author(s) 2016.
NASA Astrophysics Data System (ADS)
Herrmann, K.
2009-11-01
Information-theoretic approaches still play a minor role in financial market analysis. Nonetheless, there have been two very similar approaches evolving during the last years, one in the so-called econophysics and the other in econometrics. Both generalize the notion of GARCH processes in an information-theoretic sense and are able to capture kurtosis better than traditional models. In this article we present both approaches in a more general framework. The latter allows the derivation of a wide range of new models. We choose a third model using an entropy measure suggested by Kapur. In an application to financial market data, we find that all considered models - with similar flexibility in terms of skewness and kurtosis - lead to very similar results.
Saleh, M; Karfoul, A; Kachenoura, A; Senhadji, L; Albera, L
2016-08-01
Improving the execution time and the numerical complexity of the well-known kurtosis-based maximization method, the RobustICA, is investigated in this paper. A Newton-based scheme is proposed and compared to the conventional RobustICA method. A new implementation using the nonlinear Conjugate Gradient one is investigated also. Regarding the Newton approach, an exact computation of the Hessian of the considered cost function is provided. The proposed approaches and the considered implementations inherit the global plane search of the initial RobustICA method for which a better convergence speed for a given direction is still guaranteed. Numerical results on Magnetic Resonance Spectroscopy (MRS) source separation show the efficiency of the proposed approaches notably the quasi-Newton one using the BFGS method.
Javidi, Soroush; Mandic, Danilo P.; Took, Clive Cheong; Cichocki, Andrzej
2011-01-01
A new class of complex domain blind source extraction algorithms suitable for the extraction of both circular and non-circular complex signals is proposed. This is achieved through sequential extraction based on the degree of kurtosis and in the presence of non-circular measurement noise. The existence and uniqueness analysis of the solution is followed by a study of fast converging variants of the algorithm. The performance is first assessed through simulations on well understood benchmark signals, followed by a case study on real-time artifact removal from EEG signals, verified using both qualitative and quantitative metrics. The results illustrate the power of the proposed approach in real-time blind extraction of general complex-valued sources. PMID:22319461
Foldnes, Njål; Olsson, Ulf Henning
2016-01-01
We present and investigate a simple way to generate nonnormal data using linear combinations of independent generator (IG) variables. The simulated data have prespecified univariate skewness and kurtosis and a given covariance matrix. In contrast to the widely used Vale-Maurelli (VM) transform, the obtained data are shown to have a non-Gaussian copula. We analytically obtain asymptotic robustness conditions for the IG distribution. We show empirically that popular test statistics in covariance analysis tend to reject true models more often under the IG transform than under the VM transform. This implies that overly optimistic evaluations of estimators and fit statistics in covariance structure analysis may be tempered by including the IG transform for nonnormal data generation. We provide an implementation of the IG transform in the R environment.
Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data
NASA Astrophysics Data System (ADS)
Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho
2018-05-01
We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.
Evaluation of a breast software model for 2D and 3D X-ray imaging studies of the breast.
Baneva, Yanka; Bliznakova, Kristina; Cockmartin, Lesley; Marinov, Stoyko; Buliev, Ivan; Mettivier, Giovanni; Bosmans, Hilde; Russo, Paolo; Marshall, Nicholas; Bliznakov, Zhivko
2017-09-01
In X-ray imaging, test objects reproducing breast anatomy characteristics are realized to optimize issues such as image processing or reconstruction, lesion detection performance, image quality and radiation induced detriment. Recently, a physical phantom with a structured background has been introduced for both 2D mammography and breast tomosynthesis. A software version of this phantom and a few related versions are now available and a comparison between these 3D software phantoms and the physical phantom will be presented. The software breast phantom simulates a semi-cylindrical container filled with spherical beads of different diameters. Four computational breast phantoms were generated with a dedicated software application and for two of these, physical phantoms are also available and they are used for the side by side comparison. Planar projections in mammography and tomosynthesis were simulated under identical incident air kerma conditions. Tomosynthesis slices were reconstructed with an in-house developed reconstruction software. In addition to a visual comparison, parameters like fractal dimension, power law exponent β and second order statistics (skewness, kurtosis) of planar projections and tomosynthesis reconstructed images were compared. Visually, an excellent agreement between simulated and real planar and tomosynthesis images is observed. The comparison shows also an overall very good agreement between parameters evaluated from simulated and experimental images. The computational breast phantoms showed a close match with their physical versions. The detailed mathematical analysis of the images confirms the agreement between real and simulated 2D mammography and tomosynthesis images. The software phantom is ready for optimization purpose and extrapolation of the phantom to other breast imaging techniques. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Lab and Pore-Scale Study of Low Permeable Soils Diffusional Tortuosity
NASA Astrophysics Data System (ADS)
Lekhov, V.; Pozdniakov, S. P.; Denisova, L.
2016-12-01
Diffusion plays important role in contaminant spreading in low permeable units. The effective diffusion coefficient of saturated porous medium depends on this coefficient in water, porosity and structural parameter of porous space - tortuosity. Theoretical models of relationship between porosity and diffusional tortuosity are usually derived for conceptual granular models of medium filled by solid particles of simple geometry. These models usually do not represent soils with complex microstructure. The empirical models, like as Archie's law, based on the experimental electrical conductivity data are mostly useful for practical applications. Such models contain empirical parameters that should be defined experimentally for given soil type. In this work, we compared tortuosity values obtained in lab-scale diffusional experiments and pore scale diffusion simulation for the studied soil microstructure and exanimated relationship between tortuosity and porosity. Samples for the study were taken from borehole cores of low-permeable silt-clay formation. Using the samples of 50 cm3 we performed lab scale diffusional experiments and estimated the lab-scale tortuosity. Next using these samples we studied the microstructure with X-ray microtomograph. Shooting performed on undisturbed microsamples of size 1,53 mm with a resolution ×300 (10243 vox). After binarization of each obtained 3-D structure, its spatial correlation analysis was performed. This analysis showed that the spatial correlation scale of the indicator variogram is considerably smaller than microsample length. Then there was the numerical simulation of the Laplace equation with binary coefficients for each microsamples. The total number of simulations at the finite-difference grid of 1753 cells was 3500. As a result the effective diffusion coefficient, tortuosity and porosity values were obtained for all studied microsamples. The results were analyzed in the form of graph of tortuosity versus porosity. The 6 experimental tortuosity values well agree with pore-scale simulations falling in the general pattern that shows nonlinear decreasing of tortuosity with decreasing of porosity. Fitting this graph by Archie model we found exponent value in the range between 1,8 and 2,4. This work was supported by RFBR via grant 14-05-00409.
Diffusional creep of fine-grained olivine aggregates: Chemical and melt effects
NASA Astrophysics Data System (ADS)
Yabe, K.; Hiraga, T.
2017-12-01
Since olivine is the major constituent mineral of the earth's upper mantle, flow properties of the upper mantle are often estimated based on flow laws of olivine aggregate which are determined by high-temperature creep experiments. Recently, Miyazaki et al. (2013) showed that crystallographic preferred orientation (CPO) which has been interpreted as the main cause for seismic wave anisotropy in mantle asthenosphere could be formed in diffusional creep regime. The detail of diffusional creep of olivine aggregates is not clear yet. The strength of olivine aggregates synthesized using sol-gel method (Faul and Jackson 2007) was more than one order of magnitude harder in viscosity than those synthesized from natural mantle rocks (Hirth and Kohlstedt 1995, Hansen et al. 2011) even at the same experimental conditions. This discrepancy can be interpreted by a presence of melt and/or impurity. The purpose of this study is to examine the effects of chemical composition and presence of the melt phase on the creep properties of olivine aggregates. At first, Fe-bearing olivine aggregates were prepared by vacuum sintering of nano-sized olivine powder synthesized from highly pure and fine-grained (<100 nm) source powders. Samples with and without dopants of Al2O3 and CaO were prepared. Then uniaxial compression tests at 1 atm were conducted. Deformation experiments showed that all the samples were deformed by diffusional creep mechanism. Both doped and non-doped samples exhibited sample strength at low temperature (=1150˚C), while the doped sample became significantly weaker with showing higher temperature sensitivity compared to non-doped samples at higher temperature. The temperature sensitivity of doped samples didn't change below and above solidus, which indicate the weakening due to chemical effect, not by the melting. Non-doped samples exhibits essentially the same strength as olivine aggregates synthesized from sol-gel method (Faul and Jackson 2007), while doped sample is still harder than olivine aggregates synthesized from naturally derived olivine crystals. Trace elements other than Ca and Al, which segregate at grain boundaries in naturally-derived olivine aggregates, is likely to induce further weakening of olivine aggregates.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, X; Schott, D; Song, Y
Purpose: In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogrammore » including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two-tailed t-test and the correlations were analyzed using Spearman rank correlation tests. Results: In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response. Conclusion: Significant changes in HU histogram and the histogram-based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.« less
Maurer, Britta; Suliman, Yossra A.; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas
2018-01-01
Background To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. Methods From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. Results With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051–0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Conclusions Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients. PMID:29850118
Single-Molecule Light-Sheet Imaging of Suspended T Cells.
Ponjavic, Aleks; McColl, James; Carr, Alexander R; Santos, Ana Mafalda; Kulenkampff, Klara; Lippert, Anna; Davis, Simon J; Klenerman, David; Lee, Steven F
2018-05-08
Adaptive immune responses are initiated by triggering of the T cell receptor. Single-molecule imaging based on total internal reflection fluorescence microscopy at coverslip/basal cell interfaces is commonly used to study this process. These experiments have suggested, unexpectedly, that the diffusional behavior and organization of signaling proteins and receptors may be constrained before activation. However, it is unclear to what extent the molecular behavior and cell state is affected by the imaging conditions, i.e., by the presence of a supporting surface. In this study, we implemented single-molecule light-sheet microscopy, which enables single receptors to be directly visualized at any plane in a cell to study protein dynamics and organization in live, resting T cells. The light sheet enabled the acquisition of high-quality single-molecule fluorescence images that were comparable to those of total internal reflection fluorescence microscopy. By comparing the apical and basal surfaces of surface-contacting T cells using single-molecule light-sheet microscopy, we found that most coated-glass surfaces and supported lipid bilayers profoundly affected the diffusion of membrane proteins (T cell receptor and CD45) and that all the surfaces induced calcium influx to various degrees. Our results suggest that, when studying resting T cells, surfaces are best avoided, which we achieve here by suspending cells in agarose. Copyright © 2018. Published by Elsevier Inc.
Iima, Mami; Kataoka, Masako; Kanao, Shotaro; Onishi, Natsuko; Kawai, Makiko; Ohashi, Akane; Sakaguchi, Rena; Toi, Masakazu; Togashi, Kaori
2018-05-01
Purpose To investigate the performance of integrated approaches that combined intravoxel incoherent motion (IVIM) and non-Gaussian diffusion parameters compared with the Breast Imaging and Reporting Data System (BI-RADS) to establish multiparameter thresholds scores or probabilities by using Bayesian analysis to distinguish malignant from benign breast lesions and their correlation with molecular prognostic factors. Materials and Methods Between May 2013 and March 2015, 411 patients were prospectively enrolled and 199 patients (allocated to training [n = 99] and validation [n = 100] sets) were included in this study. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm 2 [ADC 0 ] and kurtosis [K]) by using IVIM and kurtosis models were estimated from diffusion-weighted image series (16 b values up to 2500 sec/mm 2 ), as well as a synthetic ADC (sADC) calculated by using b values of 200 and 1500 (sADC 200-1500 ) and a standard ADC calculated by using b values of 0 and 800 sec/mm 2 (ADC 0-800 ). The performance of two diagnostic approaches (combined parameter thresholds and Bayesian analysis) combining IVIM and diffusion parameters was evaluated and compared with BI-RADS performance. The Mann-Whitney U test and a nonparametric multiple comparison test were used to compare their performance to determine benignity or malignancy and as molecular prognostic biomarkers and subtypes of breast cancer. Results Significant differences were found between malignant and benign breast lesions for IVIM and non-Gaussian diffusion parameters (ADC 0 , K, fIVIM, fIVIM · D*, sADC 200-1500, and ADC 0-800 ; P < .05). Sensitivity and specificity for the validation set by radiologists A and B were as follows: sensitivity, 94.7% and 89.5%, and specificity, 75.0% and 79.2% for sADC 200-1500 , respectively; sensitivity, 94.7% and 96.1%, and specificity, 75.0% and 66.7%, for the combined thresholds approach, respectively; sensitivity, 92.1% and 92.1%, and specificity, 83.3% and 66.7%, for Bayesian analysis, respectively; and sensitivity and specificity, 100% and 79.2%, for BI-RADS, respectively. The significant difference in values of sADC 200-1500 in progesterone receptor status (P = .002) was noted. sADC 200-1500 was significantly different between histologic subtypes (P = .006). Conclusion Approaches that combined various IVIM and non-Gaussian diffusion MR imaging parameters may provide BI-RADS-equivalent scores almost comparable to BI-RADS categories without the use of contrast agents. Non-Gaussian diffusion parameters also differed by biologic prognostic factors. © RSNA, 2017 Online supplemental material is available for this article.
Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven
2012-01-01
The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task. PMID:23093921
Yasaka, Koichiro; Akai, Hiroyuki; Mackin, Dennis; Court, Laurence; Moros, Eduardo; Ohtomo, Kuni; Kiryu, Shigeru
2017-05-01
Quantitative computed tomography (CT) texture analyses for images with and without filtration are gaining attention to capture the heterogeneity of tumors. The aim of this study was to investigate how quantitative texture parameters using image filtering vary among different computed tomography (CT) scanners using a phantom developed for radiomics studies.A phantom, consisting of 10 different cartridges with various textures, was scanned under 6 different scanning protocols using four CT scanners from four different vendors. CT texture analyses were performed for both unfiltered images and filtered images (using a Laplacian of Gaussian spatial band-pass filter) featuring fine, medium, and coarse textures. Forty-five regions of interest were placed for each cartridge (x) in a specific scan image set (y), and the average of the texture values (T(x,y)) was calculated. The interquartile range (IQR) of T(x,y) among the 6 scans was calculated for a specific cartridge (IQR(x)), while the IQR of T(x,y) among the 10 cartridges was calculated for a specific scan (IQR(y)), and the median IQR(y) was then calculated for the 6 scans (as the control IQR, IQRc). The median of their quotient (IQR(x)/IQRc) among the 10 cartridges was defined as the variability index (VI).The VI was relatively small for the mean in unfiltered images (0.011) and for standard deviation (0.020-0.044) and entropy (0.040-0.044) in filtered images. Skewness and kurtosis in filtered images featuring medium and coarse textures were relatively variable across different CT scanners, with VIs of 0.638-0.692 and 0.430-0.437, respectively.Various quantitative CT texture parameters are robust and variable among different scanners, and the behavior of these parameters should be taken into consideration.
Kelly, B. G.; Loether, A.; Unruh, K. M.; ...
2017-02-01
An in situ optical pump and x-ray probe technique has been utilized to study photoinitiated solid-state diffusion in a Ni-Pt multilayer system. Hard x-ray diffraction has been used to follow the systematic growth of the NiPt alloy as a function of laser intensity and total energy deposited. It is observed that new phase growth can be driven in as little as one laser pulse, and that repeated photoexcitation can completely convert the entire multilayer structure into a single metallic alloy. In conclusion, the data suggest that lattice strain relaxation takes place prior to atomic diffusion and the formation of amore » NiPt alloy.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kelly, B. G.; Loether, A.; Unruh, K. M.
An in situ optical pump and x-ray probe technique has been utilized to study photoinitiated solid-state diffusion in a Ni-Pt multilayer system. Hard x-ray diffraction has been used to follow the systematic growth of the NiPt alloy as a function of laser intensity and total energy deposited. It is observed that new phase growth can be driven in as little as one laser pulse, and that repeated photoexcitation can completely convert the entire multilayer structure into a single metallic alloy. In conclusion, the data suggest that lattice strain relaxation takes place prior to atomic diffusion and the formation of amore » NiPt alloy.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kimmich, G.A.; Randles, J.
1981-01-01
The unidirectional influx of ..cap alpha..-methylglucoside (..cap alpha..-MG) by isolated chicken intestinal epithelial cells is 98% inhibited by phlorizin. The remaining 2% of the total influx occurs in the absence of Na/sup +/, is not sensitive to phloretin, and is equal to the diffusional entry rate for 2-deoxyglucose. The glucoside is much more strongly accumulated (75-fold) than 3-O-methylglucose (3-OMG) (10-fold). Inhibitors of the serosal sugar carrier (phloretin, cytochalasin B, theophylline, and flavanoids) do not enhance ..cap alpha..-MG accumulation. It is concluded that the glycoside is not a substrate for the intestinal serosal transport system. Steady-state gradients of the sugar canmore » be represented accurately by a concentrative, phlorizin-sensitive system that is opposed by a diffusional efflux process.« less
Deformation processes in forging ceramics
NASA Technical Reports Server (NTRS)
Cannon, R. M.; Rhodes, W. H.
1973-01-01
The deformation processes involved in the forging of refractory ceramic oxides were investigated. A combination of mechanical testing and forging was utilized to investigate both the flow and fracture processes involved. Deformation studies of very fine grain Al203 revealed an apparent transition in behavior, characterized by a shift in the strain rate sensitivity from 0.5 at low stresses to near unity at higher stresses. The behavior is indicative of a shift in control between two dependent mechanisms, one of which is indicated to be cation limited diffusional creep with significant boundary enhancement. The possible contributions of slip, indicated by crystallographic texture, interface control of the diffusional creep and inhomogeneous boundary sliding are also discussed. Additional experiments indicated an independence of deformation behavior on MgO doping and retained hot pressing impurities, at least for ultrafine grained material, and also an independence of test atmosphere.
Chemical consequences of the initial diffusional growth of cloud droplets - A clean marine case
NASA Technical Reports Server (NTRS)
Twohy, C. H.; Charlson, R. J.; Austin, P. H.
1989-01-01
A simple microphysical cloud parcel model and a simple representation of the background marine aerosol are used to predict the concentrations and compositions of droplets of various sizes near cloud base. The aerosol consists of an externally-mixed ammonium bisulfate accumulation mode and a sea-salt coarse particle mode. The difference in diffusional growth rates between the small and large droplets as well as the differences in composition between the two aerosol modes result in substantial differences in solute concentration and composition with size of droplets in the parcel. The chemistry of individual droplets is not, in general, representative of the bulk (volume-weighted mean) cloud water sample. These differences, calculated to occur early in the parcel's lifetime, should have important consequences for chemical reactions such as aqueous phase sulfate production.
Hoffman, Matthew P; Taylor, Erik N; Aninwene, George E; Sadayappan, Sakthivel; Gilbert, Richard J
2018-02-01
Contraction of muscular tissue requires the synchronized shortening of myofibers arrayed in complex geometrical patterns. Imaging such myofiber patterns with diffusion-weighted MRI reveals architectural ensembles that underlie force generation at the organ scale. Restricted proton diffusion is a stochastic process resulting from random translational motion that may be used to probe the directionality of myofibers in whole tissue. During diffusion-weighted MRI, magnetic field gradients are applied to determine the directional dependence of proton diffusion through the analysis of a diffusional probability distribution function (PDF). The directions of principal (maximal) diffusion within the PDF are associated with similarly aligned diffusion maxima in adjacent voxels to derive multivoxel tracts. Diffusion-weighted MRI with tractography thus constitutes a multiscale method for depicting patterns of cellular organization within biological tissues. We provide in this review, details of the method by which generalized Q-space imaging is used to interrogate multidimensional diffusion space, and thereby to infer the organization of muscular tissue. Q-space imaging derives the lowest possible angular separation of diffusion maxima by optimizing the conditions by which magnetic field gradients are applied to a given tissue. To illustrate, we present the methods and applications associated with Q-space imaging of the multiscale myoarchitecture associated with the human and rodent tongues. These representations emphasize the intricate and continuous nature of muscle fiber organization and suggest a method to depict structural "blueprints" for skeletal and cardiac muscle tissue. © 2016 Wiley Periodicals, Inc.
The Levy sections theorem revisited
NASA Astrophysics Data System (ADS)
Figueiredo, Annibal; Gleria, Iram; Matsushita, Raul; Da Silva, Sergio
2007-06-01
This paper revisits the Levy sections theorem. We extend the scope of the theorem to time series and apply it to historical daily returns of selected dollar exchange rates. The elevated kurtosis usually observed in such series is then explained by their volatility patterns. And the duration of exchange rate pegs explains the extra elevated kurtosis in the exchange rates of emerging markets. In the end, our extension of the theorem provides an approach that is simpler than the more common explicit modelling of fat tails and dependence. Our main purpose is to build up a technique based on the sections that allows one to artificially remove the fat tails and dependence present in a data set. By analysing data through the lenses of the Levy sections theorem one can find common patterns in otherwise very different data sets.
Distributional properties of relative phase in bimanual coordination.
James, Eric; Layne, Charles S; Newell, Karl M
2010-10-01
Studies of bimanual coordination have typically estimated the stability of coordination patterns through the use of the circular standard deviation of relative phase. The interpretation of this statistic depends upon the assumption of a von Mises distribution. The present study tested this assumption by examining the distributional properties of relative phase in three bimanual coordination patterns. There were significant deviations from the von Mises distribution due to differences in the kurtosis of distributions. The kurtosis depended upon the relative phase pattern performed, with leptokurtic distributions occurring in the in-phase and antiphase patterns and platykurtic distributions occurring in the 30° pattern. Thus, the distributional assumptions needed to validly and reliably use the standard deviation are not necessarily present in relative phase data though they are qualitatively consistent with the landscape properties of the intrinsic dynamics.
Higher-order cumulants and spectral kurtosis for early detection of subterranean termites
NASA Astrophysics Data System (ADS)
de la Rosa, Juan José González; Moreno Muñoz, Antonio
2008-02-01
This paper deals with termite detection in non-favorable SNR scenarios via signal processing using higher-order statistics. The results could be extrapolated to all impulse-like insect emissions; the situation involves non-destructive termite detection. Fourth-order cumulants in time and frequency domains enhance the detection and complete the characterization of termite emissions, non-Gaussian in essence. Sliding higher-order cumulants offer distinctive time instances, as a complement to the sliding variance, which only reveal power excesses in the signal; even for low-amplitude impulses. The spectral kurtosis reveals non-Gaussian characteristics (the peakedness of the probability density function) associated to these non-stationary measurements, specially in the near ultrasound frequency band. Contrasted estimators have been used to compute the higher-order statistics. The inedited findings are shown via graphical examples.
EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification
NASA Astrophysics Data System (ADS)
Nita, Gelu M.; Hickish, Jack; MacMahon, David; Gary, Dale E.
2016-03-01
We describe in general terms the practical use in astronomy of a higher-order statistical quantity called spectral kurtosis (SK), and describe the first implementation of SK-enabled firmware in the Fourier transform-engine (F-engine) of a digital FX correlator for the Expanded Owens Valley Solar Array (EOVSA). The development of the theory for SK is summarized, leading to an expression for generalized SK that is applicable to both SK spectrometers and those not specifically designed for SK. We also give the means for computing both the SK̂ estimator and thresholds for its application as a discriminator of RFI contamination. Tests of the performance of EOVSA as an SK spectrometer are shown to agree precisely with theoretical expectations, and the methods for configuring the correlator for correct SK operation are described.
NASA Astrophysics Data System (ADS)
Kong, Yun; Wang, Tianyang; Li, Zheng; Chu, Fulei
2017-09-01
Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.
NASA Astrophysics Data System (ADS)
Tao, Xie; Shang-Zhuo, Zhao; William, Perrie; He, Fang; Wen-Jin, Yu; Yi-Jun, He
2016-06-01
To study the electromagnetic backscattering from a one-dimensional drifting fractal sea surface, a fractal sea surface wave-current model is derived, based on the mechanism of wave-current interactions. The numerical results show the effect of the ocean current on the wave. Wave amplitude decreases, wavelength and kurtosis of wave height increase, spectrum intensity decreases and shifts towards lower frequencies when the current occurs parallel to the direction of the ocean wave. By comparison, wave amplitude increases, wavelength and kurtosis of wave height decrease, spectrum intensity increases and shifts towards higher frequencies if the current is in the opposite direction to the direction of ocean wave. The wave-current interaction effect of the ocean current is much stronger than that of the nonlinear wave-wave interaction. The kurtosis of the nonlinear fractal ocean surface is larger than that of linear fractal ocean surface. The effect of the current on skewness of the probability distribution function is negligible. Therefore, the ocean wave spectrum is notably changed by the surface current and the change should be detectable in the electromagnetic backscattering signal. Project supported by the National Natural Science Foundation of China (Grant No. 41276187), the Global Change Research Program of China (Grant No. 2015CB953901), the Priority Academic Development Program of Jiangsu Higher Education Institutions (PAPD), Program for the Innovation Research and Entrepreneurship Team in Jiangsu Province, China, the Canadian Program on Energy Research and Development, and the Canadian World Class Tanker Safety Service.
NASA Astrophysics Data System (ADS)
Borghesani, P.; Antoni, J.
2017-06-01
Second-order cyclostationary (CS2) analysis has become popular in the field of machine diagnostics and a series of digital signal processing techniques have been developed to extract CS2 components from the background noise. Among those techniques, squared envelope spectrum (SES) and cyclic modulation spectrum (CMS) have gained popularity thanks to their high computational efficiency and simple implementation. The effectiveness of CMS and SES has been previously quantified based on the hypothesis of Gaussian background noise and has led to statistical tests for the presence of CS2 peaks in squared envelope spectra and cyclic modulation spectra. However a recently established link of CMS with SES and of SES with kurtosis has exposed a potential weakness of those indicators in the case of highly leptokurtic background noise. This case is often present in practice when the machine is subjected to highly impulsive phenomena, either due to harsh operating conditions or to electric noise generated by power electronics and captured by the sensor. This study investigates and quantifies for the first time the effect of leptokurtic noise on the capabilities of SES and CMS, by analysing three progressively harsh situations: high kurtosis, infinite kurtosis and alpha-stable background noise (for which even first and second-order moments are not defined). Then the resilience of a recently proposed family of CS2 indicators, based on the log-envelope, is verified analytically, numerically and experimentally in the case of highly leptokurtic noise.
Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma.
Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang
2016-06-01
The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001).MR histogram analyses-in particular for 1th percentile for PVP images-held promise for prediction of MVI of HCC.
Yuan, Jing; Yeung, David Ka Wai; Mok, Greta S P; Bhatia, Kunwar S; Wang, Yi-Xiang J; Ahuja, Anil T; King, Ann D
2014-01-01
To technically investigate the non-Gaussian diffusion of head and neck diffusion weighted imaging (DWI) at 3 Tesla and compare advanced non-Gaussian diffusion models, including diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), intravoxel incoherent motion (IVIM) and statistical model in the patients with nasopharyngeal carcinoma (NPC). After ethics approval was granted, 16 patients with NPC were examined using DWI performed at 3T employing an extended b-value range from 0 to 1500 s/mm(2). DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models on primary tumor, metastatic node, spinal cord and muscle. Non-Gaussian parameter maps were generated and compared to apparent diffusion coefficient (ADC) maps in NPC. Diffusion in NPC exhibited non-Gaussian behavior at the extended b-value range. Non-Gaussian models achieved significantly better fitting of DWI signal than the mono-exponential model. Non-Gaussian diffusion coefficients were substantially different from mono-exponential ADC both in magnitude and histogram distribution. Non-Gaussian diffusivity in head and neck tissues and NPC lesions could be assessed by using non-Gaussian diffusion models. Non-Gaussian DWI analysis may reveal additional tissue properties beyond ADC and holds potentials to be used as a complementary tool for NPC characterization.
Koldsø, Heidi; Reddy, Tyler; Fowler, Philip W; Duncan, Anna L; Sansom, Mark S P
2016-09-01
The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.
Shaking Eden: Voyages, Bodies and Change in the Social Construction of South American Skies
NASA Astrophysics Data System (ADS)
López, Alejandro Martín
2015-05-01
South America presents a clear example of the importance of displacements and exchanges in shaping human societies. Nevertheless, the academic works, following the ideas of the first European visitors, have tended to see it as an undisturbed Eden in a `state of nature.´ For too long, South American societies were thought of as small units without history, isolated from each other. The opposition to the excesses of diffusionism helped to reinforce that image. However, in recent years this static and `naturaĺ representation has collapsed. New works from the most varied perspectives show us a changing and interconnected South America, where the notions of body, person and territory are complex social constructions and not the expression of an 'unmediated' experience of the world. We discuss the implications of these new perspectives of thinking on South America for the study of ways of perceiving and representing the sky in this region.
Can we trust the calculation of texture indices of CT images? A phantom study.
Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie
2018-04-01
Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.
Advanced diffusion MRI and biomarkers in the central nervous system: a new approach.
Martín Noguerol, T; Martínez Barbero, J P
The introduction of diffusion-weighted sequences has revolutionized the detection and characterization of central nervous system (CNS) disease. Nevertheless, the assessment of diffusion studies of the CNS is often limited to qualitative estimation. Moreover, the pathophysiological complexity of the different entities that affect the CNS cannot always be correctly explained through classical models. The development of new models for the analysis of diffusion sequences provides numerous parameters that enable a quantitative approach to both diagnosis and prognosis as well as to monitoring the response to treatment; these parameters can be considered potential biomarkers of health and disease. In this update, we review the physical bases underlying diffusion studies and diffusion tensor imaging, advanced models for their analysis (intravoxel coherent motion and kurtosis), and the biological significance of the parameters derived. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.
Entropic Approach to Brownian Movement.
ERIC Educational Resources Information Center
Neumann, Richard M.
1980-01-01
A diffusional driving force, called the radial force, which is responsible for the increase with time of the scalar separation between a fixed point and a particle undergoing three-dimensional Brownian motion, is derived using Boltzmann's equation. (Author/HM)
Efthymiou, George S.; Shuler, Michael L.
1989-08-29
An improved multilayer continuous biological membrane reactor and a process to eliminate diffusional limitations in membrane reactors in achieved by causing a convective flux of nutrient to move into and out of an immobilized biocatalyst cell layer. In a pressure cycled mode, by increasing and decreasing the pressure in the respective layers, the differential pressure between the gaseous layer and the nutrient layer is alternately changed from positive to negative. The intermittent change in pressure differential accelerates the transfer of nutrient from the nutrient layers to the biocatalyst cell layer, the transfer of product from the cell layer to the nutrient layer and the transfer of byproduct gas from the cell layer to the gaseous layer. Such intermittent cycling substantially eliminates mass transfer gradients in diffusion inhibited systems and greatly increases product yield and throughput in both inhibited and noninhibited systems.
Probability shapes perceptual precision: A study in orientation estimation.
Jabar, Syaheed B; Anderson, Britt
2015-12-01
Probability is known to affect perceptual estimations, but an understanding of mechanisms is lacking. Moving beyond binary classification tasks, we had naive participants report the orientation of briefly viewed gratings where we systematically manipulated contingent probability. Participants rapidly developed faster and more precise estimations for high-probability tilts. The shapes of their error distributions, as indexed by a kurtosis measure, also showed a distortion from Gaussian. This kurtosis metric was robust, capturing probability effects that were graded, contextual, and varying as a function of stimulus orientation. Our data can be understood as a probability-induced reduction in the variability or "shape" of estimation errors, as would be expected if probability affects the perceptual representations. As probability manipulations are an implicit component of many endogenous cuing paradigms, changes at the perceptual level could account for changes in performance that might have traditionally been ascribed to "attention." (c) 2015 APA, all rights reserved).
Real-time evolution of non-Gaussian cumulants in the QCD critical regime
NASA Astrophysics Data System (ADS)
Mukherjee, Swagato; Venugopalan, Raju; Yin, Yi
2015-09-01
We derive a coupled set of equations that describe the nonequilibrium evolution of cumulants of critical fluctuations for spacetime trajectories on the crossover side of the QCD phase diagram. In particular, novel expressions are obtained for the nonequilibrium evolution of non-Gaussian skewness and kurtosis cumulants. UBy utilizing a simple model of the spacetime evolution of a heavy-ion collision, we demonstrate that, depending on the relaxation rate of critical fluctuations, skewness and kurtosis can differ significantly in magnitude as well as in sign from equilibrium expectations. Memory effects are important and shown to persist even for trajectories that skirt the edge of the critical regime. We use phenomenologically motivated parametrizations of freeze-out curves and of the beam-energy dependence of the net baryon chemical potential to explore the implications of our model study for the critical-point search in heavy-ion collisions.
Instabilities and spatiotemporal patterns behind predator invasions with nonlocal prey competition.
Merchant, Sandra M; Nagata, Wayne
2011-12-01
We study the influence of nonlocal intraspecies prey competition on the spatiotemporal patterns arising behind predator invasions in two oscillatory reaction-diffusion integro-differential models. We use three common types of integral kernels as well as develop a caricature system, to describe the influence of the standard deviation and kurtosis of the kernel function on the patterns observed. We find that nonlocal competition can destabilize the spatially homogeneous state behind the invasion and lead to the formation of complex spatiotemporal patterns, including stationary spatially periodic patterns, wave trains and irregular spatiotemporal oscillations. In addition, the caricature system illustrates how large standard deviation and low kurtosis facilitate the formation of these spatiotemporal patterns. This suggests that nonlocal competition may be an important mechanism underlying spatial pattern formation, particularly in systems where the competition between individuals varies over space in a platykurtic manner. Copyright © 2011 Elsevier Inc. All rights reserved.
Gao, Zheyu; Lin, Jing; Wang, Xiufeng; Xu, Xiaoqiang
2017-05-24
Rolling bearings are widely used in rotating equipment. Detection of bearing faults is of great importance to guarantee safe operation of mechanical systems. Acoustic emission (AE), as one of the bearing monitoring technologies, is sensitive to weak signals and performs well in detecting incipient faults. Therefore, AE is widely used in monitoring the operating status of rolling bearing. This paper utilizes Empirical Wavelet Transform (EWT) to decompose AE signals into mono-components adaptively followed by calculation of the correlated kurtosis (CK) at certain time intervals of these components. By comparing these CK values, the resonant frequency of the rolling bearing can be determined. Then the fault characteristic frequencies are found by spectrum envelope. Both simulation signal and rolling bearing AE signals are used to verify the effectiveness of the proposed method. The results show that the new method performs well in identifying bearing fault frequency under strong background noise.
Analysis of Realized Volatility for Nikkei Stock Average on the Tokyo Stock Exchange
NASA Astrophysics Data System (ADS)
Takaishi, Tetsuya; Watanabe, Toshiaki
2016-04-01
We calculate realized volatility of the Nikkei Stock Average (Nikkei225) Index on the Tokyo Stock Exchange and investigate the return dynamics. To avoid the bias on the realized volatility from the non-trading hours issue we calculate realized volatility separately in the two trading sessions, i.e. morning and afternoon, of the Tokyo Stock Exchange and find that the microstructure noise decreases the realized volatility at small sampling frequency. Using realized volatility as a proxy of the integrated volatility we standardize returns in the morning and afternoon sessions and investigate the normality of the standardized returns by calculating variance, kurtosis and 6th moment. We find that variance, kurtosis and 6th moment are consistent with those of the standard normal distribution, which indicates that the return dynamics of the Nikkei Stock Average are well described by a Gaussian random process with time-varying volatility.
Weak Fault Feature Extraction of Rolling Bearings Based on an Improved Kurtogram.
Chen, Xianglong; Feng, Fuzhou; Zhang, Bingzhi
2016-09-13
Kurtograms have been verified to be an efficient tool in bearing fault detection and diagnosis because of their superiority in extracting transient features. However, the short-time Fourier Transform is insufficient in time-frequency analysis and kurtosis is deficient in detecting cyclic transients. Those factors weaken the performance of the original kurtogram in extracting weak fault features. Correlated Kurtosis (CK) is then designed, as a more effective solution, in detecting cyclic transients. Redundant Second Generation Wavelet Packet Transform (RSGWPT) is deemed to be effective in capturing more detailed local time-frequency description of the signal, and restricting the frequency aliasing components of the analysis results. The authors in this manuscript, combining the CK with the RSGWPT, propose an improved kurtogram to extract weak fault features from bearing vibration signals. The analysis of simulation signals and real application cases demonstrate that the proposed method is relatively more accurate and effective in extracting weak fault features.
Real time evolution of non-Gaussian cumulants in the QCD critical regime
Mukherjee, Swagato; Venugopalan, Raju; Yin, Yi
2015-09-23
In this study, we derive a coupled set of equations that describe the nonequilibrium evolution of cumulants of critical fluctuations for spacetime trajectories on the crossover side of the QCD phase diagram. In particular, novel expressions are obtained for the nonequilibrium evolution of non-Gaussian skewness and kurtosis cumulants. UBy utilizing a simple model of the spacetime evolution of a heavy-ion collision, we demonstrate that, depending on the relaxation rate of critical fluctuations, skewness and kurtosis can differ significantly in magnitude as well as in sign from equilibrium expectations. Memory effects are important and shown to persist even for trajectories thatmore » skirt the edge of the critical regime. We use phenomenologically motivated parametrizations of freeze-out curves and of the beam-energy dependence of the net baryon chemical potential to explore the implications of our model study for the critical-point search in heavy-ion collisions.« less
NASA Astrophysics Data System (ADS)
Zhang, W.; Jia, M. P.
2018-06-01
When incipient fault appear in the rolling bearing, the fault feature is too small and easily submerged in the strong background noise. In this paper, wavelet total variation denoising based on kurtosis (Kurt-WATV) is studied, which can extract the incipient fault feature of the rolling bearing more effectively. The proposed algorithm contains main steps: a) establish a sparse diagnosis model, b) represent periodic impulses based on the redundant wavelet dictionary, c) solve the joint optimization problem by alternating direction method of multipliers (ADMM), d) obtain the reconstructed signal using kurtosis value as criterion and then select optimal wavelet subbands. This paper uses overcomplete rational-dilation wavelet transform (ORDWT) as a dictionary, and adjusts the control parameters to achieve the concentration in the time-frequency plane. Incipient fault of rolling bearing is used as an example, and the result shows that the effectiveness and superiority of the proposed Kurt- WATV bearing fault diagnosis algorithm.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.
Using data from the Magnetospheric Multiscale (MMS) and Cluster missions obtained in the solar wind, we examine second-order and fourth-order structure functions at varying spatial lags normalized to ion inertial scales. The analysis includes direct two-spacecraft results and single-spacecraft results employing the familiar Taylor frozen-in flow approximation. Several familiar statistical results, including the spectral distribution of energy, and the sale-dependent kurtosis, are extended down to unprecedented spatial scales of ∼6 km, approaching electron scales. The Taylor approximation is also confirmed at those small scales, although small deviations are present in the kinetic range. The kurtosis is seen to attain verymore » high values at sub-proton scales, supporting the previously reported suggestion that monofractal behavior may be due to high-frequency plasma waves at kinetic scales.« less
Mechanistic insights from DGT and soil solution measurements on the uptake of Ni and Cd by radish.
Luo, Jun; Cheng, Hao; Ren, Jinghua; Davison, William; Zhang, Hao
2014-07-01
This work tests the previously proposed hypothesis that plant uptake of metals is determined dominantly by diffusional controlled or plant limiting uptake mechanisms at, respectively, low and high metal concentrations. Radish (Raphanus sativus) was grown in 13 soils spiked with Ni (10 and 100 mg kg(-1)) and Cd (0.5 and 4 mg kg(-1)) for 4 weeks to investigate the mechanisms affecting plant uptake. Soil solution concentrations, Css, of Ni and Cd were measured, along with the DGT interfacial concentration, CDGT, and the derived effective concentration in soil solution, CE. Free ion activities, aNi(2+) and aCd(2+), were obtained using WHAM 6. Although there was a poor relationship between Ni in radish roots and either Css or aNi(2+) in unamended soils, the distribution of data could be rationalized in terms of the extent of release of Ni from the soil solid phase, as identified by DGT and soil solution measurements. By contrast Ni in radish was linearly related to CE, demonstrating diffusion limited uptake. For soils amended with high concentrations of Ni, linear relationships were obtained for Ni in radish plotted against, Css, aNi(2+), and CE, consistent with the plant controlling uptake. For Ni the hypothesis concerning dominant diffusional and plant limiting uptake mechanisms was demonstrated. Poor relationships between Cd in radish and Css, aCd(2+), and CE, irrespective of amendment by Cd, showed the importance of factors other than diffusional supply, such as rhizosphere and inhibitory processes, and that fulfilment of this hypothesis is plant and metal specific.
NASA Astrophysics Data System (ADS)
Stephenson, D. B.
1997-10-01
The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, Larry K.; Newsom, Rob K.; Turner, David D.
One year of Coherent Doppler Lidar (CDL) data collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) site in Oklahoma is analyzed to provide profiles of vertical velocity variance, skewness, and kurtosis for cases of cloud-free convective boundary layers. The variance was scaled by the Deardorff convective velocity scale, which was successful when the boundary layer depth was stationary but failed in situations when the layer was changing rapidly. In this study the data are sorted according to time of day, season, wind direction, surface shear stress, degree of instability, and wind shear across the boundary-layer top. Themore » normalized variance was found to have its peak value near a normalized height of 0.25. The magnitude of the variance changes with season, shear stress, and degree of instability, but was not impacted by wind shear across the boundary-layer top. The skewness was largest in the top half of the boundary layer (with the exception of wintertime conditions). The skewness was found to be a function of the season, shear stress, wind shear across the boundary-layer top, with larger amounts of shear leading to smaller values. Like skewness, the vertical profile of kurtosis followed a consistent pattern, with peak values near the boundary-layer top (also with the exception of wintertime data). The altitude of the peak values of kurtosis was found to be lower when there was a large amount of wind shear at the boundary-layer top.« less
Rigby, Robert A; Stasinopoulos, D Mikis
2004-10-15
The Box-Cox power exponential (BCPE) distribution, developed in this paper, provides a model for a dependent variable Y exhibiting both skewness and kurtosis (leptokurtosis or platykurtosis). The distribution is defined by a power transformation Y(nu) having a shifted and scaled (truncated) standard power exponential distribution with parameter tau. The distribution has four parameters and is denoted BCPE (mu,sigma,nu,tau). The parameters, mu, sigma, nu and tau, may be interpreted as relating to location (median), scale (approximate coefficient of variation), skewness (transformation to symmetry) and kurtosis (power exponential parameter), respectively. Smooth centile curves are obtained by modelling each of the four parameters of the distribution as a smooth non-parametric function of an explanatory variable. A Fisher scoring algorithm is used to fit the non-parametric model by maximizing a penalized likelihood. The first and expected second and cross derivatives of the likelihood, with respect to mu, sigma, nu and tau, required for the algorithm, are provided. The centiles of the BCPE distribution are easy to calculate, so it is highly suited to centile estimation. This application of the BCPE distribution to smooth centile estimation provides a generalization of the LMS method of the centile estimation to data exhibiting kurtosis (as well as skewness) different from that of a normal distribution and is named here the LMSP method of centile estimation. The LMSP method of centile estimation is applied to modelling the body mass index of Dutch males against age. 2004 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Syam, Nur Syamsi; Maeng, Seongjin; Kim, Myo Gwang; Lim, Soo Yeon; Lee, Sang Hoon
2018-05-01
A large dead time of a Geiger Mueller (GM) detector may cause a large count loss in radiation measurements and consequently may cause distortion of the Poisson statistic of radiation events into a new distribution. The new distribution will have different statistical parameters compared to the original distribution. Therefore, the variance, skewness, and excess kurtosis in association with the observed count rate of the time interval distribution for well-known nonparalyzable, paralyzable, and nonparalyzable-paralyzable hybrid dead time models of a Geiger Mueller detector were studied using Monte Carlo simulation (GMSIM). These parameters were then compared with the statistical parameters of a perfect detector to observe the change in the distribution. The results show that the behaviors of the statistical parameters for the three dead time models were different. The values of the skewness and the excess kurtosis of the nonparalyzable model are equal or very close to those of the perfect detector, which are ≅2 for skewness, and ≅6 for excess kurtosis, while the statistical parameters in the paralyzable and hybrid model obtain minimum values that occur around the maximum observed count rates. The different trends of the three models resulting from the GMSIM simulation can be used to distinguish the dead time behavior of a GM counter; i.e. whether the GM counter can be described best by using the nonparalyzable, paralyzable, or hybrid model. In a future study, these statistical parameters need to be analyzed further to determine the possibility of using them to determine a dead time for each model, particularly for paralyzable and hybrid models.
Motion artifact removal algorithm by ICA for e-bra: a women ECG measurement system
NASA Astrophysics Data System (ADS)
Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.
2013-04-01
Wearable ECG(ElectroCardioGram) measurement systems have increasingly been developing for people who suffer from CVD(CardioVascular Disease) and have very active lifestyles. Especially, in the case of female CVD patients, several abnormal CVD symptoms are accompanied with CVDs. Therefore, monitoring women's ECG signal is a significant diagnostic method to prevent from sudden heart attack. The E-bra ECG measurement system from our previous work provides more convenient option for women than Holter monitor system. The e-bra system was developed with a motion artifact removal algorithm by using an adaptive filter with LMS(least mean square) and a wandering noise baseline detection algorithm. In this paper, ICA(independent component analysis) algorithms are suggested to remove motion artifact factor for the e-bra system. Firstly, the ICA algorithms are developed with two kinds of statistical theories: Kurtosis, Endropy and evaluated by performing simulations with a ECG signal created by sgolayfilt function of MATLAB, a noise signal including 0.4Hz, 1.1Hz and 1.9Hz, and a weighed vector W estimated by kurtosis or entropy. A correlation value is shown as the degree of similarity between the created ECG signal and the estimated new ECG signal. In the real time E-Bra system, two pseudo signals are extracted by multiplying with a random weighted vector W, the measured ECG signal from E-bra system, and the noise component signal by noise extraction algorithm from our previous work. The suggested ICA algorithm basing on kurtosis or entropy is used to estimate the new ECG signal Y without noise component.
NASA Technical Reports Server (NTRS)
Vali, G.
1982-01-01
A low gravity experiment to assess the effect of the presence of supercooled cloud droplets on the diffusional growth rate of ice crystals is described. The theoretical work and the feasibility studies are summarized. The nucleation of ice crystals in supercooled clouds is also discussed.
Classification of Liss IV Imagery Using Decision Tree Methods
NASA Astrophysics Data System (ADS)
Verma, Amit Kumar; Garg, P. K.; Prasad, K. S. Hari; Dadhwal, V. K.
2016-06-01
Image classification is a compulsory step in any remote sensing research. Classification uses the spectral information represented by the digital numbers in one or more spectral bands and attempts to classify each individual pixel based on this spectral information. Crop classification is the main concern of remote sensing applications for developing sustainable agriculture system. Vegetation indices computed from satellite images gives a good indication of the presence of vegetation. It is an indicator that describes the greenness, density and health of vegetation. Texture is also an important characteristics which is used to identifying objects or region of interest is an image. This paper illustrate the use of decision tree method to classify the land in to crop land and non-crop land and to classify different crops. In this paper we evaluate the possibility of crop classification using an integrated approach methods based on texture property with different vegetation indices for single date LISS IV sensor 5.8 meter high spatial resolution data. Eleven vegetation indices (NDVI, DVI, GEMI, GNDVI, MSAVI2, NDWI, NG, NR, NNIR, OSAVI and VI green) has been generated using green, red and NIR band and then image is classified using decision tree method. The other approach is used integration of texture feature (mean, variance, kurtosis and skewness) with these vegetation indices. A comparison has been done between these two methods. The results indicate that inclusion of textural feature with vegetation indices can be effectively implemented to produce classifiedmaps with 8.33% higher accuracy for Indian satellite IRS-P6, LISS IV sensor images.
Cui, Helen W; Devlies, Wout; Ravenscroft, Samuel; Heers, Hendrik; Freidin, Andrew J; Cleveland, Robin O; Ganeshan, Balaji; Turney, Benjamin W
2017-07-01
Understanding the factors affecting success of extracorporeal shockwave lithotripsy (SWL) would improve informed decision-making on the most appropriate treatment modality for an individual patient. Although stone size and skin-to-stone distance do correlate with fragmentation efficacy, it has been shown that stone composition and architecture, as reflected by structural heterogeneity on CT, are also important factors. This study aims to determine if CT texture analysis (CTTA), a novel, nondestructive, and objective tool that generates statistical metrics reflecting stone heterogeneity, could have utility in predicting likelihood of SWL success. Seven spontaneously passed, intact renal tract stones, were scanned ex vivo using standard CT KUB and micro-CT. The stones were then fragmented in vitro using a clinical lithotripter, after which, chemical composition analysis was performed. CTTA was used to generate a number of metrics that were correlated to the number of shocks needed to fragment the stone. CTTA metrics reflected stone characteristics and composition, and predicted ease of SWL fragmentation. The strongest correlation with number of shocks required to fragment the stone was mean Hounsfield unit (HU) density (r = 0.806, p = 0.028) and a CTTA metric measuring the entropy of the pixel distribution of the stone image (r = 0.804, p = 0.039). Using multiple linear regression analysis, the best model showed that CTTA metrics of entropy and kurtosis could predict 92% of the outcome of number of shocks needed to fragment the stone. This was superior to using stone volume or density. CTTA metrics entropy and kurtosis have been shown in this experimental ex vivo setting to strongly predict fragmentation by SWL. This warrants further investigation in a larger clinical study for the contribution of CT textural metrics as a measure of stone heterogeneity, along with other known clinical factors, to predict likelihood of SWL success.
Iima, Mami; Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori
2018-01-01
We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0-2500 s/mm2 with one number of excitations [NEX]) and five b-values (0-2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.
Kataoka, Masako; Kanao, Shotaro; Kawai, Makiko; Onishi, Natsuko; Koyasu, Sho; Murata, Katsutoshi; Ohashi, Akane; Sakaguchi, Rena; Togashi, Kaori
2018-01-01
We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0–2500 s/mm2 with one number of excitations [NEX]) and five b-values (0–2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions. PMID:29494639
Sklyar, Oleg; Träuble, Markus; Zhao, Chuan; Wittstock, Gunther
2006-08-17
The BEM algorithm developed earlier for steady-state experiments in the scanning electrochemical microscopy (SECM) feedback mode has been expanded to allow for the treatment of more than one independently diffusing species. This allows the treatment of substrate-generation/tip-collection SECM experiments. The simulations revealed the interrelation of sample layout, local kinetics, imaging conditions, and the quality of the obtained SECM images. Resolution in the SECM SG/TC images has been evaluated, and it depends on several factors. For most practical situations, the resolution is limited by the diffusion profiles of the sample. When a dissolved compound is converted at the sample (e.g., oxygen reduction or enzymatic reaction at the sample), the working distance should be significantly larger than in SECM feedback experiments (ca. 3 r(T) for RG = 5) in order to avoid diffusional shielding of the active regions on the sample by the UME body. The resolution ability also depends on the kinetics of the active regions. The best resolution can be expected if all the active regions cause the same flux. In one simulated example, which might mimic a possible scenario of a low-density protein array, considerable compromises in the resolving power, were noted when the flux from two neighboring spots differs by more than a factor of 2.
Kotovich, D; Guedalia, J S B; Hoffmann, C; Sze, G; Eisenkraft, A; Yaniv, G
2017-07-01
Cytomegalovirus is the leading intrauterine infection. Fetal MR imaging is an accepted tool for fetal brain evaluation, yet it still lacks the ability to accurately predict the extent of the neurodevelopmental impairment, especially in fetal MR imaging scans with unremarkable findings. Our hypothesis was that intrauterine cytomegalovirus infection causes diffusional changes in fetal brains and that those changes may correlate with the severity of neurodevelopmental deficiencies. A retrospective analysis was performed on 90 fetal MR imaging scans of cytomegalovirus-infected fetuses with unremarkable results and compared with a matched gestational age control group of 68 fetal head MR imaging scans. ADC values were measured and averaged in the frontal, parietal, occipital, and temporal lobes; basal ganglia; thalamus; and pons. For neurocognitive assessment, the Vineland Adaptive Behavior Scales, Second Edition (VABS-II) was used on 58 children in the cytomegalovirus-infected group. ADC values were reduced for the cytomegalovirus-infected fetuses in most brain areas studied. The VABS-II showed no trend for the major domains or the composite score of the VABS-II for the cytomegalovirus-infected children compared with the healthy population distribution. Some subdomains showed an association between ADC values and VABS-II scores. Cytomegalovirus infection causes diffuse reduction in ADC values in the fetal brain even in unremarkable fetal MR imaging scans. Cytomegalovirus-infected children with unremarkable fetal MR imaging scans do not deviate from the healthy population in the VABS-II neurocognitive assessment. ADC values were not correlated with VABS-II scores. However, the lack of clinical findings, as seen in most cytomegalovirus-infected fetuses, does not eliminate the possibility of future neurodevelopmental pathology. © 2017 by American Journal of Neuroradiology.
ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.
Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey
2018-06-21
Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.
Yuan, Jing; Yeung, David Ka Wai; Mok, Greta S. P.; Bhatia, Kunwar S.; Wang, Yi-Xiang J.; Ahuja, Anil T.; King, Ann D.
2014-01-01
Purpose To technically investigate the non-Gaussian diffusion of head and neck diffusion weighted imaging (DWI) at 3 Tesla and compare advanced non-Gaussian diffusion models, including diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), intravoxel incoherent motion (IVIM) and statistical model in the patients with nasopharyngeal carcinoma (NPC). Materials and Methods After ethics approval was granted, 16 patients with NPC were examined using DWI performed at 3T employing an extended b-value range from 0 to 1500 s/mm2. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models on primary tumor, metastatic node, spinal cord and muscle. Non-Gaussian parameter maps were generated and compared to apparent diffusion coefficient (ADC) maps in NPC. Results Diffusion in NPC exhibited non-Gaussian behavior at the extended b-value range. Non-Gaussian models achieved significantly better fitting of DWI signal than the mono-exponential model. Non-Gaussian diffusion coefficients were substantially different from mono-exponential ADC both in magnitude and histogram distribution. Conclusion Non-Gaussian diffusivity in head and neck tissues and NPC lesions could be assessed by using non-Gaussian diffusion models. Non-Gaussian DWI analysis may reveal additional tissue properties beyond ADC and holds potentials to be used as a complementary tool for NPC characterization. PMID:24466318
A quantitative study of nanoparticle skin penetration with interactive segmentation.
Lee, Onseok; Lee, See Hyun; Jeong, Sang Hoon; Kim, Jaeyoung; Ryu, Hwa Jung; Oh, Chilhwan; Son, Sang Wook
2016-10-01
In the last decade, the application of nanotechnology techniques has expanded within diverse areas such as pharmacology, medicine, and optical science. Despite such wide-ranging possibilities for implementation into practice, the mechanisms behind nanoparticle skin absorption remain unknown. Moreover, the main mode of investigation has been qualitative analysis. Using interactive segmentation, this study suggests a method of objectively and quantitatively analyzing the mechanisms underlying the skin absorption of nanoparticles. Silica nanoparticles (SNPs) were assessed using transmission electron microscopy and applied to the human skin equivalent model. Captured fluorescence images of this model were used to evaluate degrees of skin penetration. These images underwent interactive segmentation and image processing in addition to statistical quantitative analyses of calculated image parameters including the mean, integrated density, skewness, kurtosis, and area fraction. In images from both groups, the distribution area and intensity of fluorescent silica gradually increased in proportion to time. Since statistical significance was achieved after 2 days in the negative charge group and after 4 days in the positive charge group, there is a periodic difference. Furthermore, the quantity of silica per unit area showed a dramatic change after 6 days in the negative charge group. Although this quantitative result is identical to results obtained by qualitative assessment, it is meaningful in that it was proven by statistical analysis with quantitation by using image processing. The present study suggests that the surface charge of SNPs could play an important role in the percutaneous absorption of NPs. These findings can help achieve a better understanding of the percutaneous transport of NPs. In addition, these results provide important guidance for the design of NPs for biomedical applications.
Habibi-Moini, S; D'mello, A P
2001-03-14
Microencapsulated phenylalanine ammonia lyase (PAL) exhibits a marked reduction in activity compared to the activity of the free enzyme in pH 8.5 Tris buffer. The purpose of this investigation was to evaluate the contribution of incomplete entrapment, the internal environment of cellulose nitrate membrane microcapsules, the diffusional barrier of the membrane and the microcapsulation process to the low activity of encapsulated PAL. A solution of PAL and 10% w/v hemoglobin was incorporated into cellulose nitrate membrane microcapsules. Hemoglobin incorporation was used as a surrogate marker of PAL entrapment. Using 14C hemoglobin, the encapsulation efficiency was determined to be 70% and suggested that incomplete entrapment might partially account for the low activity of encapsulated PAL. The effect of the internal environment of the microcapsule (10% hemoglobin solution) on PAL activity was evaluated by comparing enzyme activity in 10% w/v hemoglobin solution and pH 8.5 Tris buffer. Similar K(M) and V(max) values of PAL in the two media indicated that the internal environment of the microcapsule did not contribute to the reduction in activity of the encapsulated enzyme. The contribution of a membrane diffusional barrier was determined by breaking the putative barrier and measuring PAL activity in intact and broken microcapsules. Similar activity of PAL in these two conditions is evidence for the lack of a diffusional barrier. The effect of the microencapsulation process on PAL activity was evaluated by comparing K(M) and V(max) of free and encapsulated PAL. Similar K(M) values in these two media suggested that the process did not affect the conformation of PAL. However, encapsulated PAL had a 50% lower V(max) value compared to free PAL, which showed that the microencapsulation process deactivated a substantial proportion of the enzyme.
NASA Astrophysics Data System (ADS)
Troncossi, M.; Di Sante, R.; Rivola, A.
2016-10-01
In the field of vibration qualification testing, random excitations are typically imposed on the tested system in terms of a power spectral density (PSD) profile. This is the one of the most popular ways to control the shaker or slip table for durability tests. However, these excitations (and the corresponding system responses) exhibit a Gaussian probability distribution, whereas not all real-life excitations are Gaussian, causing the response to be also non-Gaussian. In order to introduce non-Gaussian peaks, a further parameter, i.e., kurtosis, has to be controlled in addition to the PSD. However, depending on the specimen behaviour and input signal characteristics, the use of non-Gaussian excitations with high kurtosis and a given PSD does not automatically imply a non-Gaussian stress response. For an experimental investigation of these coupled features, suitable measurement methods need to be developed in order to estimate the stress amplitude response at critical failure locations and consequently evaluate the input signals most representative for real-life, non-Gaussian excitations. In this paper, a simple test rig with a notched cantilevered specimen was developed to measure the response and examine the kurtosis values in the case of stationary Gaussian, stationary non-Gaussian, and burst non-Gaussian excitation signals. The laser Doppler vibrometry technique was used in this type of test for the first time, in order to estimate the specimen stress amplitude response as proportional to the differential displacement measured at the notch section ends. A method based on the use of measurements using accelerometers to correct for the occasional signal dropouts occurring during the experiment is described. The results demonstrate the ability of the test procedure to evaluate the output signal features and therefore to select the most appropriate input signal for the fatigue test.
Suga, Kazuyoshi; Kawakami, Yasuhiko; Koike, Hiroaki; Iwanaga, Hideyuki; Tokuda, Osamu; Okada, Munemasa; Matsunaga, Naofumi
2010-05-01
Tc-99m-Technegas-MAA single photon emission computed tomography (SPECT)-derived ventilation (V)/perfusion (Q) quotient SPECT was used to assess lung V-Q imbalance in patients with pulmonary emphysema. V/Q quotient SPECT and V/Q profile were automatically built in 38 patients with pulmonary emphysema and 12 controls, and V/Q distribution and V/Q profile parameters were compared. V/Q distribution on V/Q quotient SPECT was correlated with low attenuation areas (LAA) on density-mask computed tomography (CT). Parameters of V/Q profile such as the median, standard deviation (SD), kurtosis and skewness were proposed to objectively evaluate the severity of lung V-Q imbalance. In contrast to uniform V/Q distribution on V/Q quotient SPECT and a sharp peak with symmetrical V/Q distribution on V/Q profile in controls, lung areas showing heterogeneously high or low V/Q and flattened peaks with broadened V/Q distribution were frequently seen in patients with emphysema, including lung areas with only slight LAA. V/Q distribution was also often asymmetric regardless of symmetric LAA. All the proposed parameters of V/Q profile in entire lungs of patients with emphysema showed large variations compared with controls; SD and kurtosis were significantly different from controls (P < 0.0001 and P < 0.001, respectively), and a significant correlation was found between SD and A-aDO2 (P < 0.0001). V/Q quotient SPECT appears to be more sensitive to detect emphysematous lungs compared with morphologic CT in patients with emphysema. SD and kurtosis of V/Q profile can be adequate parameters to assess the severity of lung V-Q imbalance causing gas-exchange impairment in patients with emphysema.
Gas kinematics in FIRE simulated galaxies compared to spatially unresolved H I observations
NASA Astrophysics Data System (ADS)
El-Badry, Kareem; Bradford, Jeremy; Quataert, Eliot; Geha, Marla; Boylan-Kolchin, Michael; Weisz, Daniel R.; Wetzel, Andrew; Hopkins, Philip F.; Chan, T. K.; Fitts, Alex; Kereš, Dušan; Faucher-Giguère, Claude-André
2018-06-01
The shape of a galaxy's spatially unresolved, globally integrated 21-cm emission line depends on its internal gas kinematics: galaxies with rotationally supported gas discs produce double-horned profiles with steep wings, while galaxies with dispersion-supported gas produce Gaussian-like profiles with sloped wings. Using mock observations of simulated galaxies from the FIRE project, we show that one can therefore constrain a galaxy's gas kinematics from its unresolved 21-cm line profile. In particular, we find that the kurtosis of the 21-cm line increases with decreasing V/σ and that this trend is robust across a wide range of masses, signal-to-noise ratios, and inclinations. We then quantify the shapes of 21-cm line profiles from a morphologically unbiased sample of ˜2000 low-redshift, H I-detected galaxies with Mstar = 107-11 M⊙ and compare to the simulated galaxies. At Mstar ≳ 1010 M⊙, both the observed and simulated galaxies produce double-horned profiles with low kurtosis and steep wings, consistent with rotationally supported discs. Both the observed and simulated line profiles become more Gaussian like (higher kurtosis and less-steep wings) at lower masses, indicating increased dispersion support. However, the simulated galaxies transition from rotational to dispersion support more strongly: at Mstar = 108-10 M⊙, most of the simulations produce more Gaussian-like profiles than typical observed galaxies with similar mass, indicating that gas in the low-mass simulated galaxies is, on average, overly dispersion supported. Most of the lower-mass-simulated galaxies also have somewhat lower gas fractions than the median of the observed population. The simulations nevertheless reproduce the observed line-width baryonic Tully-Fisher relation, which is insensitive to rotational versus dispersion support.
Numerical Modeling of High-Temperature Corrosion Processes
NASA Technical Reports Server (NTRS)
Nesbitt, James A.
1995-01-01
Numerical modeling of the diffusional transport associated with high-temperature corrosion processes is reviewed. These corrosion processes include external scale formation and internal subscale formation during oxidation, coating degradation by oxidation and substrate interdiffusion, carburization, sulfidation and nitridation. The studies that are reviewed cover such complexities as concentration-dependent diffusivities, cross-term effects in ternary alloys, and internal precipitation where several compounds of the same element form (e.g., carbides of Cr) or several compounds exist simultaneously (e.g., carbides containing varying amounts of Ni, Cr, Fe or Mo). In addition, the studies involve a variety of boundary conditions that vary with time and temperature. Finite-difference (F-D) techniques have been applied almost exclusively to model either the solute or corrodant transport in each of these studies. Hence, the paper first reviews the use of F-D techniques to develop solutions to the diffusion equations with various boundary conditions appropriate to high-temperature corrosion processes. The bulk of the paper then reviews various F-D modeling studies of diffusional transport associated with high-temperature corrosion.
NASA Astrophysics Data System (ADS)
Babanova, Sofia; Artyushkova, Kateryna; Ulyanova, Yevgenia; Singhal, Sameer; Atanassov, Plamen
2014-01-01
Two statistical methods, design of experiments (DOE) and principal component analysis (PCA) are employed to investigate and improve performance of air-breathing gas-diffusional enzymatic electrodes. DOE is utilized as a tool for systematic organization and evaluation of various factors affecting the performance of the composite system. Based on the results from the DOE, an improved cathode is constructed. The current density generated utilizing the improved cathode (755 ± 39 μA cm-2 at 0.3 V vs. Ag/AgCl) is 2-5 times higher than the highest current density previously achieved. Three major factors contributing to the cathode performance are identified: the amount of enzyme, the volume of phosphate buffer used to immobilize the enzyme, and the thickness of the gas-diffusion layer (GDL). PCA is applied as an independent confirmation tool to support conclusions made by DOE and to visualize the contribution of factors in individual cathode configurations.
Molecular and Subcellular-Scale Modeling of Nucleotide Diffusion in the Cardiac Myofilament Lattice
Kekenes-Huskey, Peter M.; Liao, Tao; Gillette, Andrew K.; Hake, Johan E.; Zhang, Yongjie; Michailova, Anushka P.; McCulloch, Andrew D.; McCammon, J. Andrew
2013-01-01
Contractile function of cardiac cells is driven by the sliding displacement of myofilaments powered by the cycling myosin crossbridges. Critical to this process is the availability of ATP, which myosin hydrolyzes during the cross-bridge cycle. The diffusion of adenine nucleotides through the myofilament lattice has been shown to be anisotropic, with slower radial diffusion perpendicular to the filament axis relative to parallel, and is attributed to the periodic hexagonal arrangement of the thin (actin) and thick (myosin) filaments. We investigated whether atomistic-resolution details of myofilament proteins can refine coarse-grain estimates of diffusional anisotropy for adenine nucleotides in the cardiac myofibril, using homogenization theory and atomistic thin filament models from the Protein Data Bank. Our results demonstrate considerable anisotropy in ATP and ADP diffusion constants that is consistent with experimental measurements and dependent on lattice spacing and myofilament overlap. A reaction-diffusion model of the half-sarcomere further suggests that diffusional anisotropy may lead to modest adenine nucleotide gradients in the myoplasm under physiological conditions. PMID:24209858
Velocity measurements by laser resonance fluorescence. [single atom diffusional motion
NASA Technical Reports Server (NTRS)
She, C. Y.; Fairbank, W. M., Jr.
1980-01-01
The photonburst correlation method was used to detect single atoms in a buffer gas. Real time flow velocity measurements with laser induced resonance fluorescence from single or multiple atoms was demonstrated and this method was investigated as a tool for wind tunnel flow measurement. Investigations show that single atoms and their real time diffusional motion on a buffer gas can be measured by resonance fluorescence. By averaging over many atoms, flow velocities up to 88 m/s were measured in a time of 0.5 sec. It is expected that higher flow speeds can be measured and that the measurement time can be reduced by a factor of 10 or more by careful experimental design. The method is clearly not ready for incorporation in high speed wind tunnels because it is not yet known whether the stray light level will be higher or lower, and it is not known what detection efficiency can be obtained in a wind tunnel situation.
Automated detection of Martian water ice clouds: the Valles Marineris
NASA Astrophysics Data System (ADS)
Ogohara, Kazunori; Munetomo, Takafumi; Hatanaka, Yuji; Okumura, Susumu
2016-10-01
We need to extract water ice clouds from the large number of Mars images in order to reveal spatial and temporal variations of water ice cloud occurrence and to meteorologically understand climatology of water ice clouds. However, visible images observed by Mars orbiters for several years are too many to visually inspect each of them even though the inspection was limited to one region. Therefore, an automated detection algorithm of Martian water ice clouds is necessary for collecting ice cloud images efficiently. In addition, it may visualize new aspects of spatial and temporal variations of water ice clouds that we have never been aware. We present a method for automatically evaluating the presence of Martian water ice clouds using difference images and cross-correlation distributions calculated from blue band images of the Valles Marineris obtained by the Mars Orbiter Camera onboard the Mars Global Surveyor (MGS/MOC). We derived one subtracted image and one cross-correlation distribution from two reflectance images. The difference between the maximum and the average, variance, kurtosis, and skewness of the subtracted image were calculated. Those of the cross-correlation distribution were also calculated. These eight statistics were used as feature vectors for training Support Vector Machine, and its generalization ability was tested using 10-fold cross-validation. F-measure and accuracy tended to be approximately 0.8 if the maximum in the normalized reflectance and the difference of the maximum and the average in the cross-correlation were chosen as features. In the process of the development of the detection algorithm, we found many cases where the Valles Marineris became clearly brighter than adjacent areas in the blue band. It is at present unclear whether the bright Valles Marineris means the occurrence of water ice clouds inside the Valles Marineris or not. Therefore, subtracted images showing the bright Valles Marineris were excluded from the detection of water ice clouds
Variable Screening for Cluster Analysis.
ERIC Educational Resources Information Center
Donoghue, John R.
Inclusion of irrelevant variables in a cluster analysis adversely affects subgroup recovery. This paper examines using moment-based statistics to screen variables; only variables that pass the screening are then used in clustering. Normal mixtures are analytically shown often to possess negative kurtosis. Two related measures, "m" and…
NASA Astrophysics Data System (ADS)
Zhou, GuoQuan; Cai, YangJian; Dai, ChaoQing
2013-05-01
A kind of hollow vortex Gaussian beam is introduced. Based on the Collins integral, an analytical propagation formula of a hollow vortex Gaussian beam through a paraxial ABCD optical system is derived. Due to the special distribution of the optical field, which is caused by the initial vortex phase, the dark region of a hollow vortex Gaussian beam will not disappear upon propagation. The analytical expressions for the beam propagation factor, the kurtosis parameter, and the orbital angular momentum density of a hollow vortex Gaussian beam passing through a paraxial ABCD optical system are also derived, respectively. The beam propagation factor is determined by the beam order and the topological charge. The kurtosis parameter and the orbital angular momentum density depend on beam order n, topological charge m, parameter γ, and transfer matrix elements A and D. As a numerical example, the propagation properties of a hollow vortex Gaussian beam in free space are demonstrated. The hollow vortex Gaussian beam has eminent propagation stability and has crucial application prospects in optical micromanipulation.
Statistical detection of systematic election irregularities
Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan
2012-01-01
Democratic societies are built around the principle of free and fair elections, and that each citizen’s vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons. PMID:23010929
Statistical detection of systematic election irregularities.
Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan
2012-10-09
Democratic societies are built around the principle of free and fair elections, and that each citizen's vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons.
Naylor, Andrew; Talwalkar, Sumedh C.; Trail, Ian A.; Joyce, Thomas J.
2016-01-01
The articulating surfaces of four different sizes of unused pyrolytic carbon proximal interphalangeal prostheses (PIP) were evaluated though measuring several topographical parameters using a white light interferometer: average roughness (Sa); root mean-square roughness (Sq); skewness (Ssk); and kurtosis (Sku). The radii of the articulating surfaces were measured using a coordinate measuring machine, and were found to be: 2.5, 3.3, 4.2 and 4.7 mm for proximal, and 4.0, 5.1, 5.6 and 6.3 mm for medial components. ANOVA was used to assess the relationship between the component radii and each roughness parameter. Sa, Sq and Ssk correlated negatively with radius (p = 0.001, 0.001, 0.023), whilst Sku correlated positively with radius (p = 0.03). Ergo, the surfaces with the largest radii possessed the better topographical characteristics: low roughness, negative skewness, high kurtosis. Conversely, the surfaces with the smallest radii had poorer topographical characteristics. PMID:27089375
Statistical approach for the detection of motion/noise artifacts in Photoplethysmogram.
Selvaraj, Nandakumar; Mendelson, Yitzhak; Shelley, Kirk H; Silverman, David G; Chon, Ki H
2011-01-01
Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory and clinical settings. The accuracy of the fusion of kurtosis and SE metrics for the artifact detection was 99.0%, 94.8% and 93.3% in simultaneously recorded ear, finger and forehead PPGs obtained in a clinical setting, respectively. For laboratory PPG data recorded from a finger with contrived artifacts, the accuracy was 88.8%. It was identified that the measurements from the forehead PPG sensor contained the most artifacts followed by finger and ear. The proposed MNA algorithm can be implemented in real-time as the computation time was 0.14 seconds using Matlab®.
Skewness in large-scale structure and non-Gaussian initial conditions
NASA Technical Reports Server (NTRS)
Fry, J. N.; Scherrer, Robert J.
1994-01-01
We compute the skewness of the galaxy distribution arising from the nonlinear evolution of arbitrary non-Gaussian intial conditions to second order in perturbation theory including the effects of nonlinear biasing. The result contains a term identical to that for a Gaussian initial distribution plus terms which depend on the skewness and kurtosis of the initial conditions. The results are model dependent; we present calculations for several toy models. At late times, the leading contribution from the initial skewness decays away relative to the other terms and becomes increasingly unimportant, but the contribution from initial kurtosis, previously overlooked, has the same time dependence as the Gaussian terms. Observations of a linear dependence of the normalized skewness on the rms density fluctuation therefore do not necessarily rule out initially non-Gaussian models. We also show that with non-Gaussian initial conditions the first correction to linear theory for the mean square density fluctuation is larger than for Gaussian models.
Weak Fault Feature Extraction of Rolling Bearings Based on an Improved Kurtogram
Chen, Xianglong; Feng, Fuzhou; Zhang, Bingzhi
2016-01-01
Kurtograms have been verified to be an efficient tool in bearing fault detection and diagnosis because of their superiority in extracting transient features. However, the short-time Fourier Transform is insufficient in time-frequency analysis and kurtosis is deficient in detecting cyclic transients. Those factors weaken the performance of the original kurtogram in extracting weak fault features. Correlated Kurtosis (CK) is then designed, as a more effective solution, in detecting cyclic transients. Redundant Second Generation Wavelet Packet Transform (RSGWPT) is deemed to be effective in capturing more detailed local time-frequency description of the signal, and restricting the frequency aliasing components of the analysis results. The authors in this manuscript, combining the CK with the RSGWPT, propose an improved kurtogram to extract weak fault features from bearing vibration signals. The analysis of simulation signals and real application cases demonstrate that the proposed method is relatively more accurate and effective in extracting weak fault features. PMID:27649171
NASA Astrophysics Data System (ADS)
Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin
2018-02-01
This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.
USDA-ARS?s Scientific Manuscript database
Arabinoxylan (AX) gels entrapping standard model proteins at different mass ratios were formed. The distribution of protein through the network was investigated by confocal laser scanning microscopy (CLSM). In mixed gels, protein aggregates forming clusters were detected at protein/polysaccharide ra...
Robust Bayesian Factor Analysis
ERIC Educational Resources Information Center
Hayashi, Kentaro; Yuan, Ke-Hai
2003-01-01
Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…
A Proposed Mechanism for Hypobaria Induced Neuronal Injury: A Swine Model
2017-04-22
Non-hypoxic hypobaric exposure in Air Force U-2 pilots and hypobaric chamber personnel is associated with increased brain white matter...utilizing advanced techniques such as multi-b-value diffusion (Q-space) and kurtosis anisotropy. We developed a swine model to test this theory.
NASA Astrophysics Data System (ADS)
Chen, BinQiang; Zhang, ZhouSuo; Zi, YanYang; He, ZhengJia; Sun, Chuang
2013-10-01
Detecting transient vibration signatures is of vital importance for vibration-based condition monitoring and fault detection of the rotating machinery. However, raw mechanical signals collected by vibration sensors are generally mixtures of physical vibrations of the multiple mechanical components installed in the examined machinery. Fault-generated incipient vibration signatures masked by interfering contents are difficult to be identified. The fast kurtogram (FK) is a concise and smart gadget for characterizing these vibration features. The multi-rate filter-bank (MRFB) and the spectral kurtosis (SK) indicator of the FK are less powerful when strong interfering vibration contents exist, especially when the FK are applied to vibration signals of short duration. It is encountered that the impulsive interfering contents not authentically induced by mechanical faults complicate the optimal analyzing process and lead to incorrect choosing of the optimal analysis subband, therefore the original FK may leave out the essential fault signatures. To enhance the analyzing performance of FK for industrial applications, an improved version of fast kurtogram, named as "fast spatial-spectral ensemble kurtosis kurtogram", is presented. In the proposed technique, discrete quasi-analytic wavelet tight frame (QAWTF) expansion methods are incorporated as the detection filters. The QAWTF, constructed based on dual tree complex wavelet transform, possesses better vibration transient signature extracting ability and enhanced time-frequency localizability compared with conventional wavelet packet transforms (WPTs). Moreover, in the constructed QAWTF, a non-dyadic ensemble wavelet subband generating strategy is put forward to produce extra wavelet subbands that are capable of identifying fault features located in transition-band of WPT. On the other hand, an enhanced signal impulsiveness evaluating indicator, named "spatial-spectral ensemble kurtosis" (SSEK), is put forward and utilized as the quantitative measure to select optimal analyzing parameters. The SSEK indicator is robuster in evaluating the impulsiveness intensity of vibration signals due to its better suppressing ability of Gaussian noise, harmonics and sporadic impulsive shocks. Numerical validations, an experimental test and two engineering applications were used to verify the effectiveness of the proposed technique. The analyzing results of the numerical validations, experimental tests and engineering applications demonstrate that the proposed technique possesses robuster transient vibration content detecting performance in comparison with the original FK and the WPT-based FK method, especially when they are applied to the processing of vibration signals of relative limited duration.
Guan, Yue; Shi, Hua; Chen, Ying; Liu, Song; Li, Weifeng; Jiang, Zhuoran; Wang, Huanhuan; He, Jian; Zhou, Zhengyang; Ge, Yun
2016-01-01
The aim of this study was to explore the application of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) values of cervical cancer. A total of 54 women (mean age, 53 years) with cervical cancers underwent 3-T diffusion-weighted imaging with b values of 0 and 800 s/mm prospectively. Whole-lesion histogram analysis of ADC values was performed. Paired sample t test was used to compare differences in ADC histogram parameters between cervical cancers and normal cervical tissues. Receiver operating characteristic curves were constructed to identify the optimal threshold of each parameter. All histogram parameters in this study including ADCmean, ADCmin, ADC10%-ADC90%, mode, skewness, and kurtosis of cervical cancers were significantly lower than those of normal cervical tissues (all P < 0.0001). ADC90% had the largest area under receiver operating characteristic curve of 0.996. Whole-lesion histogram analysis of ADC maps is useful in the assessment of cervical cancer.
NASA Astrophysics Data System (ADS)
Ma, L.; Zhou, M.; Li, C.
2017-09-01
In this study, a Random Forest (RF) based land covers classification method is presented to predict the types of land covers in Miyun area. The returned full-waveforms which were acquired by a LiteMapper 5600 airborne LiDAR system were processed, including waveform filtering, waveform decomposition and features extraction. The commonly used features that were distance, intensity, Full Width at Half Maximum (FWHM), skewness and kurtosis were extracted. These waveform features were used as attributes of training data for generating the RF prediction model. The RF prediction model was applied to predict the types of land covers in Miyun area as trees, buildings, farmland and ground. The classification results of these four types of land covers were obtained according to the ground truth information acquired from CCD image data of the same region. The RF classification results were compared with that of SVM method and show better results. The RF classification accuracy reached 89.73% and the classification Kappa was 0.8631.
New simulation of QSO X-ray heating during the Cosmic Dawn
NASA Astrophysics Data System (ADS)
Ross, Hannah E.; Dixon, Keri; Iliev, Ilian; Mellema, Garrelt
2018-05-01
The upcoming radio interferometer Square Kilometre Array is expected to directly detect the redshifted 21-cm signal from the Cosmic Dawn for the first time. In this era temperature fluctuations from X-ray heating of the neutral intergalactic medium can impact this signal dramatically. Previously, in Ross et al. (2017), we presented the first large-volume, 244 h-1 Mpc=349 Mpc a side, fully numerical radiative transfer simulations of X-ray heating. This work is a follow-up where we now also consider QSO-like sources in addition to high mass X-ray binaries. Images of the two cases are clearly distinguishable at SKA1-LOW resolution and have RMS fluctuations above the expected noise. The inclusion of QSOs leads to a dramatic increase in non-Gaussianity of the signal, as measured by the skewness and kurtosis of the 21-cm signal. We conclude that this increased non-Gaussianity is a promising signature of early QSOs.
NASA Astrophysics Data System (ADS)
Abdelmalek, B. F.; Karpyn, Z.; Liu, S.
2014-12-01
Over the last several years, hydrocarbon exploitation and development in North America has been heavily centered on shale gas plays. However, the physical attributes of shales and their manifestation on transport properties and storage capacity remain poorly understood. Therefore, more experimentally based data are needed to fill the gaps in understanding both transport and storage of fluids in shale. The proposed work includes installation and testing of an experimental system which is capable of monitoring the dynamic evolution of shale core permeability under variable loading conditions and in coordination with X-ray microCT imaging. The goal of this study is to better understand and quantify fluid flow patterns and associated transport dynamics of fractured shale samples. The independent variables considered in this study are: mechanical loading and pore pressure. The mechanical response of shale core is captured for different loading paths. To best replicate the in-situ production scenario, the pore pressure is progressively depleted to mimic pressure decline. During the course of experimentation, permeability is estimated using the pulse-decay method under tri-axial stress boundary conditions. Simultaneously, X-ray microCT imaging is used with a tracer gas that is allowed to flow through the sample as an illuminating agent. In the presence of an illuminating agent, either Xenon or Krypton, the X-ray CT scanner can image fractures, global pathways and diffusional fronts in the matrix, as well as sorption sites that reflect heterogeneities in the sample and localized deformation. Anticipated results from these experiments will help quantify permeability evolution as a function of different loading conditions and pore pressure depletion. Also, the X-ray images will help visualize the change of flow patterns and the intensity of sorption as a function of mechanical loading and pore pressure.
Parcellation of the human orbitofrontal cortex based on gray matter volume covariance.
Liu, Huaigui; Qin, Wen; Qi, Haotian; Jiang, Tianzi; Yu, Chunshui
2015-02-01
The human orbitofrontal cortex (OFC) is an enigmatic brain region that cannot be parcellated reliably using diffusional and functional magnetic resonance imaging (fMRI) because there is signal dropout that results from an inherent defect in imaging techniques. We hypothesise that the OFC can be reliably parcellated into subregions based on gray matter volume (GMV) covariance patterns that are derived from artefact-free structural images. A total of 321 healthy young subjects were examined by high-resolution structural MRI. The OFC was parcellated into subregions-based GMV covariance patterns; and then sex and laterality differences in GMV covariance pattern of each OFC subregion were compared. The human OFC was parcellated into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. This parcellation scheme was validated by the same analyses of the left OFC and the bilateral OFCs in male and female subjects. Both visual observation and quantitative comparisons indicated a unique GMV covariance pattern for each OFC subregion. These OFC subregions mainly covaried with the prefrontal and temporal cortices, cingulate cortex and amygdala. In addition, GMV correlations of most OFC subregions were similar across sex and laterality except for significant laterality difference in the OFCl. The right OFCl had stronger GMV correlation with the right inferior frontal cortex. Using high-resolution structural images, we established a reliable parcellation scheme for the human OFC, which may provide an in vivo guide for subregion-level studies of this region and improve our understanding of the human OFC at subregional levels. © 2014 Wiley Periodicals, Inc.
Caspers, Svenja; Moebus, Susanne; Lux, Silke; Pundt, Noreen; Schütz, Holger; Mühleisen, Thomas W; Gras, Vincent; Eickhoff, Simon B; Romanzetti, Sandro; Stöcker, Tony; Stirnberg, Rüdiger; Kirlangic, Mehmet E; Minnerop, Martina; Pieperhoff, Peter; Mödder, Ulrich; Das, Samir; Evans, Alan C; Jöckel, Karl-Heinz; Erbel, Raimund; Cichon, Sven; Nöthen, Markus M; Sturma, Dieter; Bauer, Andreas; Jon Shah, N; Zilles, Karl; Amunts, Katrin
2014-01-01
The ongoing 1000 brains study (1000BRAINS) is an epidemiological and neuroscientific investigation of structural and functional variability in the human brain during aging. The two recruitment sources are the 10-year follow-up cohort of the German Heinz Nixdorf Recall (HNR) Study, and the HNR MultiGeneration Study cohort, which comprises spouses and offspring of HNR subjects. The HNR is a longitudinal epidemiological investigation of cardiovascular risk factors, with a comprehensive collection of clinical, laboratory, socioeconomic, and environmental data from population-based subjects aged 45-75 years on inclusion. HNR subjects underwent detailed assessments in 2000, 2006, and 2011, and completed annual postal questionnaires on health status. 1000BRAINS accesses these HNR data and applies a separate protocol comprising: neuropsychological tests of attention, memory, executive functions and language; examination of motor skills; ratings of personality, life quality, mood and daily activities; analysis of laboratory and genetic data; and state-of-the-art magnetic resonance imaging (MRI, 3 Tesla) of the brain. The latter includes (i) 3D-T1- and 3D-T2-weighted scans for structural analyses and myelin mapping; (ii) three diffusion imaging sequences optimized for diffusion tensor imaging, high-angular resolution diffusion imaging for detailed fiber tracking and for diffusion kurtosis imaging; (iii) resting-state and task-based functional MRI; and (iv) fluid-attenuated inversion recovery and MR angiography for the detection of vascular lesions and the mapping of white matter lesions. The unique design of 1000BRAINS allows: (i) comprehensive investigation of various influences including genetics, environment and health status on variability in brain structure and function during aging; and (ii) identification of the impact of selected influencing factors on specific cognitive subsystems and their anatomical correlates.
NASA Astrophysics Data System (ADS)
He, Ting; Fan, Ming; Zhang, Peng; Li, Hui; Zhang, Juan; Shao, Guoliang; Li, Lihua
2018-03-01
Breast cancer can be classified into four molecular subtypes of Luminal A, Luminal B, HER2 and Basal-like, which have significant differences in treatment and survival outcomes. We in this study aim to predict immunohistochemistry (IHC) determined molecular subtypes of breast cancer using image features derived from tumor and peritumoral stroma region based on diffusion weighted imaging (DWI). A dataset of 126 breast cancer patients were collected who underwent preoperative breast MRI with a 3T scanner. The apparent diffusion coefficients (ADCs) were recorded from DWI, and breast image was segmented into regions comprising the tumor and the surrounding stromal. Statistical characteristics in various breast tumor and peritumoral regions were computed, including mean, minimum, maximum, variance, interquartile range, range, skewness, and kurtosis of ADC values. Additionally, the difference of features between each two regions were also calculated. The univariate logistic based classifier was performed for evaluating the performance of the individual features for discriminating subtypes. For multi-class classification, multivariate logistic regression model was trained and validated. The results showed that the tumor boundary and proximal peritumoral stroma region derived features have a higher performance in classification compared to that of the other regions. Furthermore, the prediction model using statistical features, difference features and all the features combined from these regions generated AUC values of 0.774, 0.796 and 0.811, respectively. The results in this study indicate that ADC feature in tumor and peritumoral stromal region would be valuable for estimating the molecular subtype in breast cancer.
Pharmacological MRI (phMRI) of the Human Central Nervous System.
Lanfermann, H; Schindler, C; Jordan, J; Krug, N; Raab, P
2015-10-01
Pharmacological magnetic resonance imaging (phMRI) of the central nervous system (CNS) addresses the increasing demands in the biopharma industry for new methods that can accurately predict, as early as possible, whether novel CNS agents will be effective and safe. Imaging of physiological and molecular-level function can provide a more direct measure of a drug mechanism of action, enabling more predictive measures of drug activity. The availability of phMRI of the nervous system within the professional infrastructure of the Clinical Research Center (CRC) Hannover as proof of concept center ensures that advances in basic science progress swiftly into benefits for patients. Advanced standardized MRI techniques including quantitative MRI, kurtosis determination, functional MRI, and spectroscopic imaging of the entire brain are necessary for phMRI. As a result, MR scanners will evolve into high-precision measuring instruments for assessment of desirable and undesirable effects of drugs as the basic precondition for individually tailored therapy. The CRC's Imaging Unit with high-end large-scale equipment will allow the following unique opportunities: for example, identification of MR-based biomarkers to assess the effect of drugs (surrogate parameters), establishment of normal levels and reference ranges for MRI-based biomarkers, evaluation of the most relevant MRI sequences for drug monitoring in outpatient care. Another very important prerequisite for phMRI is the MHH Core Facility as the scientific and operational study unit of the CRC partner Hannover Medical School. This unit is responsible for the study coordination, conduction, complete study logistics, administration, and application of the quality assurance system based on required industry standards.
The influence of acid diffusion on the performance of lead-acid cells
NASA Astrophysics Data System (ADS)
Kappus, W.; Bohmann, J.
1983-11-01
A model for the discharge performance of the lead-acid cell is proposed. Diffusion of acid into the porous electrodes, which is connected with diffusio Curves of diffusional polarizations as a function of the discharge time are presented. Calculated discharge capacities show the influence of various pa
Electroreleasing Composite Membranes for Delivery of Insulin and Other Biomacromolecules
1990-04-05
electrochemistry to control the delivery of a chemical or drug (1, 2). The major advantage of electroreleasing systems (over conventional diffusional drug...used to deliver insulin and vitamin B-12. The composite membrane fabrication procedure is shown schematically in Figure 1. An Anopore ( Alltech ) A1203
Pre-processing, registration and selection of adaptive optics corrected retinal images.
Ramaswamy, Gomathy; Devaney, Nicholas
2013-07-01
In this paper, the aim is to demonstrate enhanced processing of sequences of fundus images obtained using a commercial AO flood illumination system. The purpose of the work is to (1) correct for uneven illumination at the retina (2) automatically select the best quality images and (3) precisely register the best images. Adaptive optics corrected retinal images are pre-processed to correct uneven illumination using different methods; subtracting or dividing by the average filtered image, homomorphic filtering and a wavelet based approach. These images are evaluated to measure the image quality using various parameters, including sharpness, variance, power spectrum kurtosis and contrast. We have carried out the registration in two stages; a coarse stage using cross-correlation followed by fine registration using two approaches; parabolic interpolation on the peak of the cross-correlation and maximum-likelihood estimation. The angle of rotation of the images is measured using a combination of peak tracking and Procrustes transformation. We have found that a wavelet approach (Daubechies 4 wavelet at 6th level decomposition) provides good illumination correction with clear improvement in image sharpness and contrast. The assessment of image quality using a 'Designer metric' works well when compared to visual evaluation, although it is highly correlated with other metrics. In image registration, sub-pixel translation measured using parabolic interpolation on the peak of the cross-correlation function and maximum-likelihood estimation are found to give very similar results (RMS difference 0.047 pixels). We have confirmed that correcting rotation of the images provides a significant improvement, especially at the edges of the image. We observed that selecting the better quality frames (e.g. best 75% images) for image registration gives improved resolution, at the expense of poorer signal-to-noise. The sharpness map of the registered and de-rotated images shows increased sharpness over most of the field of view. Adaptive optics assisted images of the cone photoreceptors can be better pre-processed using a wavelet approach. These images can be assessed for image quality using a 'Designer Metric'. Two-stage image registration including correcting for rotation significantly improves the final image contrast and sharpness. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.
ERIC Educational Resources Information Center
Zimmerman, Donald W.
2011-01-01
This study investigated how population parameters representing heterogeneity of variance, skewness, kurtosis, bimodality, and outlier-proneness, drawn from normal and eleven non-normal distributions, also characterized the ranks corresponding to independent samples of scores. When the parameters of population distributions from which samples were…
Directional Dependence in Developmental Research
ERIC Educational Resources Information Center
von Eye, Alexander; DeShon, Richard P.
2012-01-01
In this article, we discuss and propose methods that may be of use to determine direction of dependence in non-normally distributed variables. First, it is shown that standard regression analysis is unable to distinguish between explanatory and response variables. Then, skewness and kurtosis are discussed as tools to assess deviation from…
A Comparison of Normal and Elliptical Estimation Methods in Structural Equation Models.
ERIC Educational Resources Information Center
Schumacker, Randall E.; Cheevatanarak, Suchittra
Monte Carlo simulation compared chi-square statistics, parameter estimates, and root mean square error of approximation values using normal and elliptical estimation methods. Three research conditions were imposed on the simulated data: sample size, population contamination percent, and kurtosis. A Bentler-Weeks structural model established the…
Mullins, Roger J.; Xu, Su; Pereira, Edna F.R.; Pescrille, Joseph D.; Todd, Spencer W.; Mamczarz, Jacek; Albuquerque, Edson X.; Gullapalli, Rao P.
2015-01-01
This study was designed to test the hypothesis that prenatal exposure of guinea pigs to the organophosphorus (OP) pesticide chlorpyrifos (CPF) disrupts the structural and functional integrity of the brain. Pregnant guinea pigs were injected with chlorpyrifos (20 mg/kg, s.c.) or vehicle (peanut oil) once per day for ten consecutive days, starting approximately on the 50th day of gestation. Cognitive behavior of female offspring was examined starting at 40–45 post-natal days (PND) using the Morris Water Maze (MWM), and brain structural integrity was analyzed at PND 70 using magnetic resonance imaging (MRI) methods, including T2-weighted anatomical scans and Diffusion Kurtosis Imaging (DKI). The offspring of exposed mothers had significantly decreased body weight and brain volume, particularly in the frontal regions of the brain including the striatum. Furthermore, the offspring demonstrated significant spatial learning deficits in MWM recall compared to the vehicle group. Diffusion measures revealed reduced white matter integrity within the striatum and amygdala that correlated with spatial learning performance. These findings reveal the lasting effect of pre-natal exposure to CPF as well as the danger of mother to child transmission of CPF in the environment. PMID:25704171
Lackey, Daniel P; Carruth, Eric D; Lasher, Richard A; Boenisch, Jan; Sachse, Frank B; Hitchcock, Robert W
2011-11-01
Gap junctions play a fundamental role in intercellular communication in cardiac tissue. Various types of heart disease including hypertrophy and ischemia are associated with alterations of the spatial arrangement of gap junctions. Previous studies applied two-dimensional optical and electron-microscopy to visualize gap junction arrangements. In normal cardiomyocytes, gap junctions were primarily found at cell ends, but can be found also in more central regions. In this study, we extended these approaches toward three-dimensional reconstruction of gap junction distributions based on high-resolution scanning confocal microscopy and image processing. We developed methods for quantitative characterization of gap junction distributions based on analysis of intensity profiles along the principal axes of myocytes. The analyses characterized gap junction polarization at cell ends and higher-order statistical image moments of intensity profiles. The methodology was tested in rat ventricular myocardium. Our analysis yielded novel quantitative data on gap junction distributions. In particular, the analysis demonstrated that the distributions exhibit significant variability with respect to polarization, skewness, and kurtosis. We suggest that this methodology provides a quantitative alternative to current approaches based on visual inspection, with applications in particular in characterization of engineered and diseased myocardium. Furthermore, we propose that these data provide improved input for computational modeling of cardiac conduction.
NASA Astrophysics Data System (ADS)
Beskardes, G. D.; Hole, J. A.; Wang, K.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Michaelides, M.; Brown, L. D.; Quiros, D. A.
2016-12-01
Back-projection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. Back-projection is scalable to earthquakes with a wide range of magnitudes from very tiny to very large. Local dense arrays provide the opportunity to capture very tiny events for a range applications, such as tectonic microseismicity, source scaling studies, wastewater injection-induced seismicity, hydraulic fracturing, CO2 injection monitoring, volcano studies, and mining safety. While back-projection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed to overcome imaging issues. We compare the performance of back-projection using four previously used data pre-processing methods: full waveform, envelope, short-term averaging / long-term averaging (STA/LTA), and kurtosis. The goal is to identify an optimized strategy for an entirely automated imaging process that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the energy imaged at the source, preserves magnitude information, and considers computational cost. Real data issues include aliased station spacing, low signal-to-noise ratio (to <1), large noise bursts and spatially varying waveform polarity. For evaluation, the four imaging methods were applied to the aftershock sequence of the 2011 Virginia earthquake as recorded by the AIDA array with 200-400 m station spacing. These data include earthquake magnitudes from -2 to 3 with highly variable signal to noise, spatially aliased noise, and large noise bursts: realistic issues in many environments. Each of the four back-projection methods has advantages and disadvantages, and a combined multi-pass method achieves the best of all criteria. Preliminary imaging results from the 2011 Virginia dataset will be presented.
Pressure pumping of carbon dioxide from soil
E. S. Takle; J. R. Brandle; R. A. Schmidt; R. Garcia; I. V. Litvina; G. Doyle; X. Zhou; Q. Hou; C. W. Rice; W. J. Massman
2000-01-01
Recent interest in atmospheric increases in carbon dioxide have heightened the need for improved accuracy in measurements of fluxes of carbon dioxide from soils. Diffusional movement has long been considered the dominant process by which trace gases move from the subsurface source to the surface, although there has been some indication that atmospheric pressure...
Wu, Fei; Pelster, Lindsey N; Minteer, Shelley D
2015-01-25
Dynamics of metabolon formation in mitochondria was probed by studying diffusional motion of two sequential Krebs cycle enzymes in a microfluidic channel. Enhanced directional co-diffusion of both enzymes against a substrate concentration gradient was observed in the presence of intermediate generation. This reveals a metabolite directed compartmentation of metabolic pathways.
NASA Astrophysics Data System (ADS)
Alexandrov, Dmitri V.; Ivanov, Alexander A.; Alexandrova, Irina V.
2018-01-01
The processes of particle nucleation and their evolution in a moving metastable layer of phase transition (supercooled liquid or supersaturated solution) are studied analytically. The transient integro-differential model for the density distribution function and metastability level is solved for the kinetic and diffusionally controlled regimes of crystal growth. The Weber-Volmer-Frenkel-Zel'dovich and Meirs mechanisms for nucleation kinetics are used. We demonstrate that the phase transition boundary lying between the mushy and pure liquid layers evolves with time according to the following power dynamic law:
In Situ TEM Nanoindentation Studies on Stress-Induced Phase Transformations in Metallic Materials
Liu, Y.; Wang, H.; Zhang, X.
2015-11-30
Though abundant phase transformations are in general thermally driven processes, there are many examples wherein stresses can induce phase transformations. We applied numerous in situ techniques, such as in situ x-ray diffraction and neutron diffraction in order to reveal phase transformations. Recently, an in situ nanoindentation technique coupled with transmission electron microscopy demonstrated the capability to directly correlating stresses with phase transformations and microstructural evolutions at a submicron length scale. We briefly review in situ studies on stress-induced diffusional and diffusionless phase transformations in amorphous CuZrAl alloy and NiFeGa shape memory alloy. Moreover, in the amorphous CuZrAl, in situ nanoindentationmore » studies show that the nucleation of nanocrystals (a diffusional process) occurs at ultra-low stresses manifested by a prominent stress drop. In the NiFeGa shape memory alloy, two distinctive types of martensitic (diffusionless) phase transformations accompanied by stress plateaus are observed, including a reversible gradual phase transformation at low stress levels, and an irreversible abrupt phase transition at higher stress levels.« less
Investigating fuel-cell transport limitations using hydrogen limiting current
Spingler, Franz B.; Phillips, Adam; Schuler, Tobias; ...
2017-03-09
Reducing mass-transport losses in polymer-electrolyte fuel cells (PEFCs) is essential to increase their power density and reduce overall stack cost. At the same time, cost also motivates the reduction in expensive precious-metal catalysts, which results in higher local transport losses in the catalyst layers. Here, we use a hydrogen-pump limiting-current setup to explore the gas-phase transport losses through PEFC catalyst layers and various gas-diffusion and microporous layers. It is shown that the effective diffusivity in the gas-diffusion layers is a strong function of liquid saturation. Additionally, it is shown how the catalyst layer unexpectedly contributes significantly to the overall measuredmore » transport resistance. This is especially true for low catalyst loadings. It is also shown how the various losses can be separated into different mechanisms including diffusional processes and mass-dependent and independent ones, where the data suggests that a large part of the transport resistance in catalyst layers cannot be attributed to a gas-phase diffusional process. The technique is promising for deconvoluting transport losses in PEFCs.« less
Unsteady Oxygen Transfer in Space-Filling Models of the Pulmonary Acinus
NASA Astrophysics Data System (ADS)
Hofemeier, Philipp; Shachar-Berman, Lihi; Filoche, Marcel; Sznitman, Josue
2014-11-01
Diffusional screening in the pulmonary acinus is a well-known physical phenomenon that results from the depletion of fresh oxygen in proximal acinar generations diffusing through the alveolar wall membranes and effectively creating a gradient in the oxygen partial pressure along the acinar airways. Until present, most studies have focused on steady-state oxygen diffusion in generic sub-acinar structures and discarded convective oxygen transport due to low Peclet numbers in this region. Such studies, however, fall typically short in capturing the complex morphology of acinar airways as well as the oscillatory nature of convecive acinar breathing. Here, we revisit this problem and solve the convective-diffusive transport equations in breathing 3D acinar structures, underlining the significance of convective flows in proximal acinar generations as well as recirculating alveolar flow patterns. In particular, to assess diffusional screening, we monitor time-dependent efficiencies of the acinus under cyclic breathing motion. Our study emphasizes the necessity of capturing both a dynamically breathing and anatomically-realistic model of the sub-acinus to characterize unsteady oxygen transport across the acinar walls.
Dodin, Dmitry V; Ivanov, Anatoly I; Burshtein, Anatoly I
2008-02-07
The Hamiltonian description of the spin-conversion induced by a hyperfine interaction (HFI) in photogenerated radical-ion pairs is substituted for the rate (incoherent) description of the same conversion provided by the widely used earlier elementary spin model. The quantum yields of the free ions as well as the singlet and triplet products of geminate recombination are calculated using distant dependent ionization and recombination rates, instead of their contact analogs. Invoking the simplest models of these rates, we demonstrate with the example of a spin-less system that the diffusional acceleration of radical-ion pair recombination at lower viscosity gives way to its diffusional deceleration (Angulo effect), accomplished with a kinetic plateau inherent with the primitive exponential model. Qualitatively the same behavior is found in real systems, assuming both ionization and recombination is carried out by the Marcus electron-transfer rates. Neglecting the Coulomb interaction between solvated ions, the efficiencies of radical-ion pair recombination to the singlet and triplet products are well fitted to the available experimental data. The magnetic field dependence of these yields is specified.
ERIC Educational Resources Information Center
Ho, Andrew D.; Yu, Carol C.
2015-01-01
Many statistical analyses benefit from the assumption that unconditional or conditional distributions are continuous and normal. More than 50 years ago in this journal, Lord and Cook chronicled departures from normality in educational tests, and Micerri similarly showed that the normality assumption is met rarely in educational and psychological…
The Inverted Student Density and Test Scores.
ERIC Educational Resources Information Center
Boldt, Robert F.
The inverted density is one whose contour lines are spheroidal as in the normal distribution, but whose moments differ from those of the normal in that its conditional arrays are not homoscedastic, being quadratic functions of the values of the linear regression functions. It is also platykurtic, its measure of kurtosis ranging from that of the…
Particle Formation and Deposition from Supercritical Solutions.
1986-12-12
1.06 PLATYKURTIC -64- - ’ , - . •- - . • , . .U . p# "* " " COULTER ELECTRONICS, INC. 680 Wtet 20th Street Hfr ean. FL 33010 1-800-327-6531 Fine...1.98 UM COEF. VAR.: 166.82 % SKEWNESS: 1.23 NEGATIJE KURTOSIS: 1.93 PLATYKURTIC -66- COULTER ELECTRONICS, INC. 680 West 20th Street Hialean. FL
Propagation properties of cylindrical sinc Gaussian beam
NASA Astrophysics Data System (ADS)
Eyyuboğlu, Halil T.; Bayraktar, Mert
2016-09-01
We investigate the propagation properties of cylindrical sinc Gaussian beam in turbulent atmosphere. Since an analytic solution is hardly derivable, the study is carried out with the aid of random phase screens. Evolutions of the beam intensity profile, beam size and kurtosis parameter are analysed. It is found that on the source plane, cylindrical sinc Gaussian beam has a dark hollow appearance, where the side lobes also start to emerge with increase in width parameter and Gaussian source size. During propagation, beams with small width and Gaussian source size exhibit off-axis behaviour, losing the dark hollow shape, accumulating the intensity asymmetrically on one side, whereas those with large width and Gaussian source size retain dark hollow appearance even at long propagation distances. It is seen that the beams with large widths expand more in beam size than the ones with small widths. The structure constant values chosen do not seem to alter this situation. The kurtosis parameters of the beams having small widths are seen to be larger than the ones with the small widths. Again the choice of the structure constant does not change this trend.
NASA Astrophysics Data System (ADS)
Lahmiri, S.; Boukadoum, M.
2015-10-01
Accurate forecasting of stock market volatility is an important issue in portfolio risk management. In this paper, an ensemble system for stock market volatility is presented. It is composed of three different models that hybridize the exponential generalized autoregressive conditional heteroscedasticity (GARCH) process and the artificial neural network trained with the backpropagation algorithm (BPNN) to forecast stock market volatility under normal, t-Student, and generalized error distribution (GED) assumption separately. The goal is to design an ensemble system where each single hybrid model is capable to capture normality, excess skewness, or excess kurtosis in the data to achieve complementarity. The performance of each EGARCH-BPNN and the ensemble system is evaluated by the closeness of the volatility forecasts to realized volatility. Based on mean absolute error and mean of squared errors, the experimental results show that proposed ensemble model used to capture normality, skewness, and kurtosis in data is more accurate than the individual EGARCH-BPNN models in forecasting the S&P 500 intra-day volatility based on one and five-minute time horizons data.
NASA Technical Reports Server (NTRS)
Li, C. J.; Devries, W. R.; Ludema, K. C.
1983-01-01
Measurements made with a stylus surface tracer which provides a digitized representation of a surface profile are discussed. Parameters are defined to characterize the height (e.g., RMS roughness, skewness, and kurtosis) and length (e.g., autocorrelation) of the surface topography. These are applied to the characterization of crank shaft journals which were manufactured by different grinding and lopping procedures known to give significant differences in crank shaft bearing life. It was found that three parameters (RMS roughness, skewness, and kurtosis) are necessary to adequately distinguish the character of these surfaces. Every surface specimen has a set of values for these three parameters. They can be regarded as a set coordinate in a space constituted by three characteristics axes. The various journal surfaces can be classified along with the determination of a proper wavelength cutoff (0.25 mm) by using a method of separated subspace. The finite radius of the stylus used for profile tracing gives an inherent measurement error as it passes over the fine structure of the surface. A mathematical model is derived to compensate for this error.
Extended AIC model based on high order moments and its application in the financial market
NASA Astrophysics Data System (ADS)
Mao, Xuegeng; Shang, Pengjian
2018-07-01
In this paper, an extended method of traditional Akaike Information Criteria(AIC) is proposed to detect the volatility of time series by combining it with higher order moments, such as skewness and kurtosis. Since measures considering higher order moments are powerful in many aspects, the properties of asymmetry and flatness can be observed. Furthermore, in order to reduce the effect of noise and other incoherent features, we combine the extended AIC algorithm with multiscale wavelet analysis, in which the newly extended AIC algorithm is applied to wavelet coefficients at several scales and the time series are reconstructed by wavelet transform. After that, we create AIC planes to derive the relationship among AIC values using variance, skewness and kurtosis respectively. When we test this technique on the financial market, the aim is to analyze the trend and volatility of the closing price of stock indices and classify them. And we also adapt multiscale analysis to measure complexity of time series over a range of scales. Empirical results show that the singularity of time series in stock market can be detected via extended AIC algorithm.
The use of SESK as a trend parameter for localized bearing fault diagnosis in induction machines.
Saidi, Lotfi; Ben Ali, Jaouher; Benbouzid, Mohamed; Bechhoefer, Eric
2016-07-01
A critical work of bearing fault diagnosis is locating the optimum frequency band that contains faulty bearing signal, which is usually buried in the noise background. Now, envelope analysis is commonly used to obtain the bearing defect harmonics from the envelope signal spectrum analysis and has shown fine results in identifying incipient failures occurring in the different parts of a bearing. However, the main step in implementing envelope analysis is to determine a frequency band that contains faulty bearing signal component with the highest signal noise level. Conventionally, the choice of the band is made by manual spectrum comparison via identifying the resonance frequency where the largest change occurred. In this paper, we present a squared envelope based spectral kurtosis method to determine optimum envelope analysis parameters including the filtering band and center frequency through a short time Fourier transform. We have verified the potential of the spectral kurtosis diagnostic strategy in performance improvements for single-defect diagnosis using real laboratory-collected vibration data sets. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Generation of Stationary Non-Gaussian Time Histories with a Specified Cross-spectral Density
Smallwood, David O.
1997-01-01
The paper reviews several methods for the generation of stationary realizations of sampled time histories with non-Gaussian distributions and introduces a new method which can be used to control the cross-spectral density matrix and the probability density functions (pdfs) of the multiple input problem. Discussed first are two methods for the specialized case of matching the auto (power) spectrum, the skewness, and kurtosis using generalized shot noise and using polynomial functions. It is then shown that the skewness and kurtosis can also be controlled by the phase of a complex frequency domain description of the random process. The general casemore » of matching a target probability density function using a zero memory nonlinear (ZMNL) function is then covered. Next methods for generating vectors of random variables with a specified covariance matrix for a class of spherically invariant random vectors (SIRV) are discussed. Finally the general case of matching the cross-spectral density matrix of a vector of inputs with non-Gaussian marginal distributions is presented.« less
Structural changes in cross-border liabilities: A multidimensional approach
NASA Astrophysics Data System (ADS)
Araújo, Tanya; Spelta, Alessandro
2014-01-01
We study the international interbank market through a geometric analysis of empirical data. The geometric analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small dimension. Geometric spaces of financial relations across countries are developed, for which the space volume, multivariate skewness and multivariate kurtosis are computed. The behavior of these coefficients reveals an important modification acting in the financial linkages since 1997 and allows us to relate the shape of the geometric space that emerges in recent years to the globally turbulent period that has characterized financial systems since the late 1990s. Here we show that, besides a persistent decrease in the volume of the geometric space since 1997, the observation of a generalized increase in the values of the multivariate skewness and kurtosis sheds some light on the behavior of cross-border interdependencies during periods of financial crises. This was found to occur in such a systematic fashion, that these coefficients may be used as a proxy for systemic risk.
Granulometric analysis at Lampulo Fishing Port (LFP) substrate, Banda Aceh, Indonesia
NASA Astrophysics Data System (ADS)
Purnawan, S.; Setiawan, I.; Haridhi, H. A.; Irham, M.
2018-01-01
The study of sediment granulometry was completed at Lampulo fishing port (LFP). The LFP is a main fishing port in Aceh Province, Indonesia, located at 5°34’35” N; 95°19’23” E. The purpose of the research is to study and construct the environment condition of the bottom substrate. The data was taken by incorporating coring method at 10 stations using purposive random sampling. The wet sieve method was used to analyze the grain size for geostatistical analysis. The geostatistical parameters analysis in this study is classified as mean, sorting, skewness and kurtosis. The result informs that the types of sediments are sand, sandy clay and clayey sand for all stations. Station 1, however, is found as the coarsest compares to the other stations. All of the sediment collected at each station displays moderately sorted to poor sorted, while kurtosis values may be categorized as very leptokurtic. The results of the sediment parameters indicate that the environment of harbor pool was in a stable state, related to a sheltered condition.
MO-FG-202-06: Improving the Performance of Gamma Analysis QA with Radiomics- Based Image Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wootton, L; Nyflot, M; Ford, E
2016-06-15
Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributedmore » (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for Healthcare Research and Quality, grant number R18 HS022244-01.« less
Singh, Shardendu K; Badgujar, Girish; Reddy, Vangimalla R; Fleisher, David H; Bunce, James A
2013-06-15
Nutrients such as phosphorus may exert a major control over plant response to rising atmospheric carbon dioxide concentration (CO2), which is projected to double by the end of the 21st century. Elevated CO2 may overcome the diffusional limitations to photosynthesis posed by stomata and mesophyll and alter the photo-biochemical limitations resulting from phosphorus deficiency. To evaluate these ideas, cotton (Gossypium hirsutum) was grown in controlled environment growth chambers with three levels of phosphate (Pi) supply (0.2, 0.05 and 0.01mM) and two levels of CO2 concentration (ambient 400 and elevated 800μmolmol(-1)) under optimum temperature and irrigation. Phosphate deficiency drastically inhibited photosynthetic characteristics and decreased cotton growth for both CO2 treatments. Under Pi stress, an apparent limitation to the photosynthetic potential was evident by CO2 diffusion through stomata and mesophyll, impairment of photosystem functioning and inhibition of biochemical process including the carboxylation efficiency of ribulose-1,5-bisphosphate carboxylase/oxyganase and the rate of ribulose-1,5-bisphosphate regeneration. The diffusional limitation posed by mesophyll was up to 58% greater than the limitation due to stomatal conductance (gs) under Pi stress. As expected, elevated CO2 reduced these diffusional limitations to photosynthesis across Pi levels; however, it failed to reduce the photo-biochemical limitations to photosynthesis in phosphorus deficient plants. Acclimation/down regulation of photosynthetic capacity was evident under elevated CO2 across Pi treatments. Despite a decrease in phosphorus, nitrogen and chlorophyll concentrations in leaf tissue and reduced stomatal conductance at elevated CO2, the rate of photosynthesis per unit leaf area when measured at the growth CO2 concentration tended to be higher for all except the lowest Pi treatment. Nevertheless, plant biomass increased at elevated CO2 across Pi nutrition with taller plants, increased leaf number and larger leaf area. Copyright © 2013 Elsevier GmbH. All rights reserved.
Nucleocytoplasmic Distribution and Dynamics of the Autophagosome Marker EGFP-LC3
Drake, Kimberly R.; Kang, Minchul; Kenworthy, Anne K.
2010-01-01
The process of autophagy involves the formation of autophagosomes, double-membrane structures that encapsulate cytosol. Microtubule-associated protein light chain 3 (LC3) was the first protein shown to specifically label autophagosomal membranes in mammalian cells, and subsequently EGFP-LC3 has become one of the most widely utilized reporters of autophagy. Although LC3 is currently thought to function primarily in the cytosol, the site of autophagosome formation, EGFP-LC3 often appears to be enriched in the nucleoplasm relative to the cytoplasm in published fluorescence images. However, the nuclear pool of EGFP-LC3 has not been specifically studied in previous reports, and mechanisms by which LC3 shuttles between the cytoplasm and nucleoplasm are currently unknown. In this study, we therefore investigated the regulation of the nucleo-cytoplasmic distribution of EGFP-LC3 in living cells. By quantitative fluorescence microscopy analysis, we demonstrate that soluble EGFP-LC3 is indeed enriched in the nucleus relative to the cytoplasm in two commonly studied cell lines, COS-7 and HeLa. Although LC3 contains a putative nuclear export signal (NES), inhibition of active nuclear export or mutation of the NES had no effect on the nucleo-cytoplasmic distribution of EGFP-LC3. Furthermore, FRAP analysis indicates that EGFP-LC3 undergoes limited passive nucleo-cytoplasmic transport under steady state conditions, and that the diffusional mobility of EGFP-LC3 was substantially slower in the nucleus and cytoplasm than predicted for a freely diffusing monomer. Induction of autophagy led to a visible decrease in levels of soluble EGFP-LC3 relative to autophagosome-bound protein, but had only modest effects on the nucleo-cytoplasmic ratio or diffusional mobility of the remaining soluble pools of EGFP-LC3. We conclude that the enrichment of soluble EGFP-LC3 in the nucleus is maintained independently of active nuclear export or induction of autophagy. Instead, incorporation of soluble EGFP-LC3 into large macromolecular complexes within both the cytoplasm and nucleus may prevent its rapid equilibrium between the two compartments. PMID:20352102
Is coverage a factor in non-Gaussianity of IMF parameters?
NASA Technical Reports Server (NTRS)
Ahluwalia, H. S.; Fikani, M. M.
1995-01-01
Recently, Feynman and Ruzmaikin (1994) showed that IMF parameters for the 1973 to 1990 period are not log-normally distributed as previously suggested by Burlaga and King (1979) for the data obtained over a shorter time period (1963-75). They studied the first four moments, namely: mean, variance, skewness, and kurtosis. For a Gaussian distribution, moments higher than the variance should vanish. In particular, Feynman and Ruzmaikin obtained very high values of kurtosis during some periods of their analysis. We note that the coverage for IMF parameters is very uneven for the period analyzed by them, ranging from less than 40% to greater than 80%. So a question arises as to whether the amount of coverage is a factor in their analysis. We decided to test this for the B(sub z) component of IMF, since it is an effective geoactive parameter for short term disturbances. Like them, we used 1-hour averaged data available on the Omnitape. We studied the scatter plots of the annual mean values of B(sub z)(nT) and its kurtosis versus the percent coverage for the year. We obtain a correlation coefficient of 0.48 and 0.42 respectively for the 1973-90 period. The probability for a chance occurrence of these correlation coefficients for 18 pair of points is less than 8%. As a rough measure of skewness, we determined the percent asymmetry between the areas of the histograms representing the distributions of the positive and the negative values of B(sub z) and studied its correlation with the coverage for the year. This analysis yields a correlation coefficient of 0.41 When we extended the analysis for the whole period for which IMF data are available (1963-93) the corresponding correlation coefficients are 0.59, 0.14, and 0.42. Our findings will be presented and discussed
NASA Astrophysics Data System (ADS)
Leka, K. D.; Barnes, G.
2003-10-01
We apply statistical tests based on discriminant analysis to the wide range of photospheric magnetic parameters described in a companion paper by Leka & Barnes, with the goal of identifying those properties that are important for the production of energetic events such as solar flares. The photospheric vector magnetic field data from the University of Hawai'i Imaging Vector Magnetograph are well sampled both temporally and spatially, and we include here data covering 24 flare-event and flare-quiet epochs taken from seven active regions. The mean value and rate of change of each magnetic parameter are treated as separate variables, thus evaluating both the parameter's state and its evolution, to determine which properties are associated with flaring. Considering single variables first, Hotelling's T2-tests show small statistical differences between flare-producing and flare-quiet epochs. Even pairs of variables considered simultaneously, which do show a statistical difference for a number of properties, have high error rates, implying a large degree of overlap of the samples. To better distinguish between flare-producing and flare-quiet populations, larger numbers of variables are simultaneously considered; lower error rates result, but no unique combination of variables is clearly the best discriminator. The sample size is too small to directly compare the predictive power of large numbers of variables simultaneously. Instead, we rank all possible four-variable permutations based on Hotelling's T2-test and look for the most frequently appearing variables in the best permutations, with the interpretation that they are most likely to be associated with flaring. These variables include an increasing kurtosis of the twist parameter and a larger standard deviation of the twist parameter, but a smaller standard deviation of the distribution of the horizontal shear angle and a horizontal field that has a smaller standard deviation but a larger kurtosis. To support the ``sorting all permutations'' method of selecting the most frequently occurring variables, we show that the results of a single 10-variable discriminant analysis are consistent with the ranking. We demonstrate that individually, the variables considered here have little ability to differentiate between flaring and flare-quiet populations, but with multivariable combinations, the populations may be distinguished.
Quality of corneal lamellar cuts quantified using atomic force microscopy
Ziebarth, Noël M.; Dias, Janice; Hürmeriç, Volkan; Shousha, Mohamed Abou; Yau, Chiyat Ben; Moy, Vincent T.; Culbertson, William; Yoo, Sonia H.
2012-01-01
PURPOSE To quantify the cut quality of lamellar dissections made with the femtosecond laser using atomic force microscopy (AFM). SETTING Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, USA. DESIGN Experimental study. METHODS Experiments were performed on 3 pairs of human cadaver eyes. The cornea was thinned to physiologic levels by placing the globe, cornea side down, in 25% dextran for 24 hours. The eyes were reinflated to normal pressures by injecting a balanced salt solution into the vitreous cavity. The eyes were placed in a holder, the epithelium was removed, and the eyes were cut with a Visumax femtosecond laser. The energy level was 180 nJ for the right eye and 340 nJ for the left eye of each pair. The cut depths were 200 μm, 300 μm, and 400 μm, with the cut depth maintained for both eyes of each pair. A 12.0 mm trephination was then performed. The anterior portion of the lamellar surface was placed in a balanced salt solution and imaged with AFM. As a control, the posterior surface was placed in 2% formalin and imaged with environmental scanning electron microscopy (SEM). Four quantitative parameters (root-mean-square deviation, average deviation, skewness, kurtosis) were calculated from the AFM images. RESULTS From AFM, the 300 μm low-energy cuts were the smoothest. Similar results were seen qualitatively in the environmental SEM images. CONCLUSION Atomic force microscopy provided quantitative information on the quality of lamellar dissections made using a femtosecond laser, which is useful in optimizing patient outcomes in refractive and lamellar keratoplasty surgeries. PMID:23141078
Dahdouh, Sonia; Andescavage, Nickie; Yewale, Sayali; Yarish, Alexa; Lanham, Diane; Bulas, Dorothy; du Plessis, Adre J; Limperopoulos, Catherine
2018-02-01
To investigate the ability of three-dimensional (3D) MRI placental shape and textural features to predict fetal growth restriction (FGR) and birth weight (BW) for both healthy and FGR fetuses. We recruited two groups of pregnant volunteers between 18 and 39 weeks of gestation; 46 healthy subjects and 34 FGR. Both groups underwent fetal MR imaging on a 1.5 Tesla GE scanner using an eight-channel receiver coil. We acquired T2-weighted images on either the coronal or the axial plane to obtain MR volumes with a slice thickness of either 4 or 8 mm covering the full placenta. Placental shape features (volume, thickness, elongation) were combined with textural features; first order textural features (mean, variance, kurtosis, and skewness of placental gray levels), as well as, textural features computed on the gray level co-occurrence and run-length matrices characterizing placental homogeneity, symmetry, and coarseness. The features were used in two machine learning frameworks to predict FGR and BW. The proposed machine-learning based method using shape and textural features identified FGR pregnancies with 86% accuracy, 77% precision and 86% recall. BW estimations were 0.3 ± 13.4% (mean percentage error ± standard error) for healthy fetuses and -2.6 ± 15.9% for FGR. The proposed FGR identification and BW estimation methods using in utero placental shape and textural features computed on 3D MR images demonstrated high accuracy in our healthy and high-risk cohorts. Future studies to assess the evolution of each feature with regard to placental development are currently underway. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:449-458. © 2017 International Society for Magnetic Resonance in Medicine.
Alizadeh, Mahdi; Conklin, Chris J; Middleton, Devon M; Shah, Pallav; Saksena, Sona; Krisa, Laura; Finsterbusch, Jürgen; Faro, Scott H; Mulcahey, M J; Mohamed, Feroze B
2018-04-01
Ghost artifacts are a major contributor to degradation of spinal cord diffusion tensor images. A multi-stage post-processing pipeline was designed, implemented and validated to automatically remove ghost artifacts arising from reduced field of view diffusion tensor imaging (DTI) of the pediatric spinal cord. A total of 12 pediatric subjects including 7 healthy subjects (mean age=11.34years) with no evidence of spinal cord injury or pathology and 5 patients (mean age=10.96years) with cervical spinal cord injury were studied. Ghost/true cords, labeled as region of interests (ROIs), in non-diffusion weighted b0 images were segmented automatically using mathematical morphological processing. Initially, 21 texture features were extracted from each segmented ROI including 5 first-order features based on the histogram of the image (mean, variance, skewness, kurtosis and entropy) and 16s-order feature vector elements, incorporating four statistical measures (contrast, correlation, homogeneity and energy) calculated from co-occurrence matrices in directions of 0°, 45°, 90° and 135°. Next, ten features with a high value of mutual information (MI) relative to the pre-defined target class and within the features were selected as final features which were input to a trained classifier (adaptive neuro-fuzzy interface system) to separate the true cord from the ghost cord. The implemented pipeline was successfully able to separate the ghost artifacts from true cord structures. The results obtained from the classifier showed a sensitivity of 91%, specificity of 79%, and accuracy of 84% in separating the true cord from ghost artifacts. The results show that the proposed method is promising for the automatic detection of ghost cords present in DTI images of the spinal cord. This step is crucial towards development of accurate, automatic DTI spinal cord post processing pipelines. Copyright © 2017 Elsevier Inc. All rights reserved.
Towner, Rheal A; Wisniewski, Amy B; Wu, Dee H; Van Gordon, Samuel B; Smith, Nataliya; North, Justin C; McElhaney, Rayburt; Aston, Christopher E; Shobeiri, S Abbas; Kropp, Bradley P; Greenwood-Van Meerveld, Beverley; Hurst, Robert E
2016-03-01
Interstitial cystitis/bladder pain syndrome is a bladder pain disorder associated with voiding symptomatology and other systemic chronic pain disorders. Currently diagnosing interstitial cystitis/bladder pain syndrome is complicated as patients present with a wide range of symptoms, physical examination findings and clinical test responses. One hypothesis is that interstitial cystitis symptoms arise from increased bladder permeability to urine solutes. This study establishes the feasibility of using contrast enhanced magnetic resonance imaging to quantify bladder permeability in patients with interstitial cystitis. Permeability alterations in bladder urothelium were assessed by intravesical administration of the magnetic resonance imaging contrast agent Gd-DTPA (Gd-diethylenetriaminepentaacetic acid) in a small cohort of patients. Magnetic resonance imaging signal intensity in patient and control bladders was compared regionally and for entire bladders. Quantitative assessment of magnetic resonance imaging signal intensity indicated a significant increase in signal intensity in anterior bladder regions compared to posterior regions in patients with interstitial cystitis (p <0.01) and significant increases in signal intensity in anterior bladder regions (p <0.001). Kurtosis (shape of probability distribution) and skewness (measure of probability distribution asymmetry) were associated with contrast enhancement in total bladders in patients with interstitial cystitis vs controls (p <0.05). Regarding symptomatology interstitial cystitis cases differed significantly from controls on the SF-36®, PUF (Pelvic Pain and Urgency/Frequency) and ICPI (Interstitial Cystitis Problem Index) questionnaires with no overlap in the score range in each group. ICSI (Interstitial Cystitis Symptom Index) differed significantly but with a slight overlap in the range of scores. Data suggest that contrast enhanced magnetic resonance imaging provides an objective, quantifiable measurement of bladder permeability that could be used to stratify bladder pain patients and monitor therapy. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
The spine neck filters membrane potentials.
Araya, Roberto; Jiang, Jiang; Eisenthal, Kenneth B; Yuste, Rafael
2006-11-21
Dendritic spines receive most synaptic inputs in the forebrain. Their morphology, with a spine head isolated from the dendrite by a slender neck, indicates a potential role in isolating inputs. Indeed, biochemical compartmentalization occurs at spine heads because of the diffusional bottleneck created by the spine neck. Here we investigate whether the spine neck also isolates inputs electrically. Using two-photon uncaging of glutamate on spine heads from mouse layer-5 neocortical pyramidal cells, we find that the amplitude of uncaging potentials at the soma is inversely proportional to neck length. This effect is strong and independent of the position of the spine in the dendritic tree and size of the spine head. Moreover, spines with long necks are electrically silent at the soma, although their heads are activated by the uncaging event, as determined with calcium imaging. Finally, second harmonic measurements of membrane potential reveal an attenuation of somatic voltages into the spine head, an attenuation directly proportional to neck length. We conclude that the spine neck plays an electrical role in the transmission of membrane potentials, isolating synapses electrically.
The spine neck filters membrane potentials
Araya, Roberto; Jiang, Jiang; Eisenthal, Kenneth B.; Yuste, Rafael
2006-01-01
Dendritic spines receive most synaptic inputs in the forebrain. Their morphology, with a spine head isolated from the dendrite by a slender neck, indicates a potential role in isolating inputs. Indeed, biochemical compartmentalization occurs at spine heads because of the diffusional bottleneck created by the spine neck. Here we investigate whether the spine neck also isolates inputs electrically. Using two-photon uncaging of glutamate on spine heads from mouse layer-5 neocortical pyramidal cells, we find that the amplitude of uncaging potentials at the soma is inversely proportional to neck length. This effect is strong and independent of the position of the spine in the dendritic tree and size of the spine head. Moreover, spines with long necks are electrically silent at the soma, although their heads are activated by the uncaging event, as determined with calcium imaging. Finally, second harmonic measurements of membrane potential reveal an attenuation of somatic voltages into the spine head, an attenuation directly proportional to neck length. We conclude that the spine neck plays an electrical role in the transmission of membrane potentials, isolating synapses electrically. PMID:17093040
Age-related apparent diffusion coefficient changes in the normal brain.
Watanabe, Memi; Sakai, Osamu; Ozonoff, Al; Kussman, Steven; Jara, Hernán
2013-02-01
To measure the mean diffusional age-related changes of the brain over the full human life span by using diffusion-weighted spin-echo single-shot echo-planar magnetic resonance (MR) imaging and sequential whole-brain apparent diffusion coefficient (ADC) histogram analysis and, secondarily, to build mathematical models of these normal age-related changes throughout human life. After obtaining institutional review board approval, a HIPAA-compliant retrospective search was conducted for brain MR imaging studies performed in 2007 for various clinical indications. Informed consent was waived. The brain data of 414 healthy subjects (189 males and 225 females; mean age, 33.7 years; age range, 2 days to 89.3 years) were obtained with diffusion-weighted spin-echo single-shot echo-planar MR imaging. ADC histograms of the whole brain were generated. ADC peak values, histogram widths, and intracranial volumes were plotted against age, and model parameters were estimated by using nonlinear regression. Four different stages were identified for aging changes in ADC peak values, as characterized by specific mathematical terms: There were age-associated exponential decays for the maturation period and the development period, a constant term for adulthood, and a linear increase for the senescence period. The age dependency of ADC peak value was simulated by using four-term six-coefficient function, including biexponential and linear terms. This model fit the data very closely (R(2) = 0.91). Brain diffusivity as a whole demonstrated age-related changes through four distinct periods of life. These results could contribute to establishing an ADC baseline of the normal brain, covering the full human life span.
Enhancement of breast periphery region in digital mammography
NASA Astrophysics Data System (ADS)
Menegatti Pavan, Ana Luiza; Vacavant, Antoine; Petean Trindade, Andre; Quini, Caio Cesar; Rodrigues de Pina, Diana
2018-03-01
Volumetric breast density has been shown to be one of the strongest risk factor for breast cancer diagnosis. This metric can be estimated using digital mammograms. During mammography acquisition, breast is compressed and part of it loses contact with the paddle, resulting in an uncompressed region in periphery with thickness variation. Therefore, reliable density estimation in the breast periphery region is a problem, which affects the accuracy of volumetric breast density measurement. The aim of this study was to enhance breast periphery to solve the problem of thickness variation. Herein, we present an automatic algorithm to correct breast periphery thickness without changing pixel value from internal breast region. The correction pixel values from periphery was based on mean values over iso-distance lines from the breast skin-line using only adipose tissue information. The algorithm detects automatically the periphery region where thickness should be corrected. A correction factor was applied in breast periphery image to enhance the region. We also compare our contribution with two other algorithms from state-of-the-art, and we show its accuracy by means of different quality measures. Experienced radiologists subjectively evaluated resulting images from the tree methods in relation to original mammogram. The mean pixel value, skewness and kurtosis from histogram of the three methods were used as comparison metric. As a result, the methodology presented herein showed to be a good approach to be performed before calculating volumetric breast density.
NASA Astrophysics Data System (ADS)
Torrents-Barrena, Jordina; Puig, Domenec; Melendez, Jaime; Valls, Aida
2016-03-01
Breast cancer is one of the most dangerous diseases that attack women in their 40s worldwide. Due to this fact, it is estimated that one in eight women will develop a malignant carcinoma during their life. In addition, the carelessness of performing regular screenings is an important reason for the increase of mortality. However, computer-aided diagnosis systems attempt to enhance the quality of mammograms as well as the detection of early signs related to the disease. In this paper we propose a bank of Gabor filters to calculate the mean, standard deviation, skewness and kurtosis features by four-sized evaluation windows. Therefore, an active strategy is used to select the most relevant pixels. Finally, a supervised classification stage using two-class support vector machines is utilised through an accurate estimation of kernel parameters. In order to show the development of our methodology based on mammographic image analysis, two main experiments are fulfilled: abnormal/normal breast tissue classification and the ability to detect the different breast cancer types. Moreover, the public screen-film mini-MIAS database is compared with a digitised breast cancer database to evaluate the method robustness. The area under the receiver operating characteristic curve is used to measure the performance of the method. Furthermore, both confusion matrix and accuracy are calculated to assess the results of the proposed algorithm.
Schob, Stefan; Münch, Benno; Dieckow, Julia; Quäschling, Ulf; Hoffmann, Karl-Titus; Richter, Cindy; Garnov, Nikita; Frydrychowicz, Clara; Krause, Matthias; Meyer, Hans-Jonas; Surov, Alexey
2018-04-01
Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis. Copyright © 2018. Published by Elsevier Inc.
Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma
Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang
2016-01-01
Abstract The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement. The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001). MR histogram analyses—in particular for 1th percentile for PVP images—held promise for prediction of MVI of HCC. PMID:27368028
O'Connor, Timothy; Rawat, Siddharth; Markman, Adam; Javidi, Bahram
2018-03-01
We propose a compact imaging system that integrates an augmented reality head mounted device with digital holographic microscopy for automated cell identification and visualization. A shearing interferometer is used to produce holograms of biological cells, which are recorded using customized smart glasses containing an external camera. After image acquisition, segmentation is performed to isolate regions of interest containing biological cells in the field-of-view, followed by digital reconstruction of the cells, which is used to generate a three-dimensional (3D) pseudocolor optical path length profile. Morphological features are extracted from the cell's optical path length map, including mean optical path length, coefficient of variation, optical volume, projected area, projected area to optical volume ratio, cell skewness, and cell kurtosis. Classification is performed using the random forest classifier, support vector machines, and K-nearest neighbor, and the results are compared. Finally, the augmented reality device displays the cell's pseudocolor 3D rendering of its optical path length profile, extracted features, and the identified cell's type or class. The proposed system could allow a healthcare worker to quickly visualize cells using augmented reality smart glasses and extract the relevant information for rapid diagnosis. To the best of our knowledge, this is the first report on the integration of digital holographic microscopy with augmented reality devices for automated cell identification and visualization.
Bourlier, Christophe
2005-07-10
The emissivity of two-dimensional anisotropic rough sea surfaces with non-Gaussian statistics is investigated. The emissivity derivation is of importance for retrieval of the sea-surface temperature or equivalent temperature of a rough sea surface by infrared thermal imaging. The well-known Cox-Munk slope probability-density function, considered non-Gaussian, is used for the emissivity derivation, in which the skewness and the kurtosis (related to the third- and fourth-order statistics, respectively) are included. The shadowing effect, which is significant for grazing angles, is also taken into account. The geometric optics approximation is assumed to be valid, which means that the rough surface is modeled as a collection of facets reflecting locally the light in the specular direction. In addition, multiple reflections are ignored. Numerical results of the emissivity are presented for Gaussian and non-Gaussian statistics, for moderate wind speeds, for near-infrared wavelengths, for emission angles ranging from 0 degrees (nadir) to 90 degrees (horizon), and according to the wind direction. In addition, the emissivity is compared with both measurements and a Monte Carlo ray-tracing method.
Parameters Comparsion of Leads Detection in Arctic Sea Ice Using CRYOSAT-2 Waveform Data
NASA Astrophysics Data System (ADS)
Li, J.; Zhang, S.; Xiao, F.; Zhu, C.; Zhang, Y.; Zhu, T.; Yuan, L.
2018-04-01
Leads are only a small part of the polar sea ice structure, but they play a dominant role on the turbulence exchange between the ocean and the atmosphere, they are also important factors about sea ice thickness inversion. Since the early 2000s, Satellite altimetry has been applied to monitor the Arctic sea ice thickness, Satellite altimetry data can be used to distinguish leads and sea ice. In this paper, four parameters including Pulse peakiness (PP), stack standard deviation (SSD), stack kurtosis (SKU) and stack skewness (SSK) are extracted from CryoSat-2 satellite altimetry waveform data. The four parameters are combined into five combinations (PP, PP&SSD, PP&SSD&SKU, PP&SSD&SSK, PP&SSD&SSK&SKU) with constrain conditions to detect the leads. The results of the five methods are compared with MODIS (moderate-resolution imagining spectroradiometer) images and show that, the combination of PP&SSD is better than the single PP, the rest of combinations are the same as the combination of PP&SSD. It turns out, there is no promotion when we add SSK and SKU, successively or simultaneously.
Liang, He-Yue; Huang, Ya-Qin; Yang, Zhao-Xia; Ying-Ding; Zeng, Meng-Su; Rao, Sheng-Xiang
2016-07-01
To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard. Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm(2)) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters. The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000-0.002) with area under the ROC curve (AUCs) of 0.76-0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups. Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases. • ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. • Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. • MR enhancement histogram analyses are not reliable to predict response.
Zhang, Yuxin; Holmes, James; Rabanillo, Iñaki; Guidon, Arnaud; Wells, Shane; Hernando, Diego
2018-09-01
To evaluate the reproducibility of quantitative diffusion measurements obtained with reduced Field of View (rFOV) and Multi-shot EPI (msEPI) acquisitions, using single-shot EPI (ssEPI) as a reference. Diffusion phantom experiments, and prostate diffusion-weighted imaging in healthy volunteers and patients with known or suspected prostate cancer were performed across the three different sequences. Quantitative diffusion measurements of apparent diffusion coefficient, and diffusion kurtosis parameters (healthy volunteers), were obtained and compared across diffusion sequences (rFOV, msEPI, and ssEPI). Other possible confounding factors like b-value combinations and acquisition parameters were also investigated. Both msEPI and rFOV have shown reproducible quantitative diffusion measurements relative to ssEPI; no significant difference in ADC was observed across pulse sequences in the standard diffusion phantom (p = 0.156), healthy volunteers (p ≥ 0.12) or patients (p ≥ 0.26). The ADC values within the non-cancerous central gland and peripheral zone of patients were 1.29 ± 0.17 × 10 -3 mm 2 /s and 1.74 ± 0.23 × 10 -3 mm 2 /s respectively. However, differences in quantitative diffusion parameters were observed across different number of averages for rFOV, and across b-value groups and diffusion models for all the three sequences. Both rFOV and msEPI have the potential to provide high image quality with reproducible quantitative diffusion measurements in prostate diffusion MRI. Copyright © 2018 Elsevier Inc. All rights reserved.
Browndye: A Software Package for Brownian Dynamics
McCammon, J. Andrew
2010-01-01
A new software package, Browndye, is presented for simulating the diffusional encounter of two large biological molecules. It can be used to estimate second-order rate constants and encounter probabilities, and to explore reaction trajectories. Browndye builds upon previous knowledge and algorithms from software packages such as UHBD, SDA, and Macrodox, while implementing algorithms that scale to larger systems. PMID:21132109
Over the past two decades, more than 20 mass transfer models have been developed for the sources, sinks, and barriers for volatile and semivolatile organic compounds (VOCs and SVOCs) in the indoor environment. While these models have greatly improved our understanding of VOC and ...
CO2 flux through a Wyoming seasonal snowpack: Diffusional and pressure pumping effects
William Massman; Richard Sommerfeld; Karl Zeller; Ted Hehn; Laura Hudnell; Shannon Rochelle
1995-01-01
The movement of trace gases through porous media results from a combination of molecular diffusion and natural convection forced by turbulent atmospheric pressure pumping. This study presents observational and modeling results of an experiment to estimate the C02 flux through a seasonal snowpack in the Rocky Mountains of southern Wyoming, USA. Profiles of C02 mole...
Potassium transport in monkey erythrocytes.
Stewart, G W; Blackstock, E J; Hall, A C; Ellory, J C
1989-01-01
K transport in Rhesus and Cynomolgus monkey erythrocytes has been characterised and compared to that in human erythrocytes. Transport due to the NaK pump, residual (diffusional) leak, volume-, pressure- and N-ethyl-maleimide-stimulated KCl system and internal Ca2+-stimulated K channel were similar to that in man but in the monkey it differed, in lacking the loop-diuretic-sensitive NaKCl cotransport system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salvadori, P.
1962-10-31
The proton (p ) and gamma energy and angular distributions from the elastic (Compton) interaction p + gamma -- p + gamma are calculated. The results are tabulated for 25-Mev gamma increments, from 300 to 1500 Mev. (T.F.H.)
USDA-ARS?s Scientific Manuscript database
Nutrients such as phosphorus availability may exert a major control over plant response to rising atmospheric carbon dioxide concentration (CO2), which is projected to double by the end of 21st century. Elevated CO2 may overcome the diffusional limitation to photosynthesis posed by stomata and mesop...
A pulse NMR study of water exchange across the erythrocyte membrane
NASA Astrophysics Data System (ADS)
Lahajnar, G.
1993-03-01
A pulse nuclear magnetic resonance (NMR) technique is employed to study the temperature dependence (5-40°C) of the diffusional water exchange time τexch for normal and p-hydroxymercuribenzoate ( p-HMB) treated bovine erythrocytes. The Arrhenius plot of τexch for normal erythrocytes implies the activation energy Ea of 20.4 kJ/mol, similar to that for self-diffusion of water ( Ea = 19.3 - 20.1 kJ/mol), and the value τexch of 12.5 ms at 20°C corresponds to the cell membrane diffusional water permeability coefficient P d of 3.6 × 10 -3 cm/s. The data for p-HMB treated cells display lengthening of τexch (i.e., τexch = 17.3 ms at 20°C) and increased E a of 29.0 kJ/mol. This E a value and a permeability coefficient P d of 2.6 × 10 -3 cm/s at 20°C, if compared to corresponding data for artificial lipid bilayer membranes, indicate either incomplete closure of the specialized water-selective protein channels on binding of p-HMB to their SH-groups, or complete channel closure plus new leaks.
NASA Astrophysics Data System (ADS)
Dayamani, Allumolu; Shinde, Ganesh S.; Chaupatnaik, Anshuman; Rao, R. Prasada; Adams, Stefan; Barpanda, Prabeer
2018-05-01
Solvothermal synthetic routes can provide energy-savvy platforms to fabricate battery anode materials involving relatively milder annealing steps vis-à-vis the conventional solid-state synthesis. These energy efficient routes in turn restrict aggressive grain growth to form nanoscale particles favouring efficient Li+ diffusion. Here, we report an economic solution combustion synthesis of SrLi2Ti6O14 anode involving nitrate-urea complexation with a short annealing duration of only 2 h (900 °C). Rietveld refinement confirms the phase purity of target product assuming an orthorhombic framework (Cmca symmetry). It delivers reversible capacity of ∼125 mAh.g-1 at a rate of C/20 involving a 1.38 V Ti4+/Ti3+ redox activity with excellent rate kinetics and cycling stability. Bond valence site energy (BVSE) calculations gauge SrLi2Ti6O14 to be an anisotropic 3D Li+ ion conductor with the highest ionic conductivity along the c direction. The electrochemical and diffusional pathways have been elucidated for combustion prepared SrLi2Ti6O14 as an efficient and safe negative electrode candidate for Li-ion batteries.
Random element method for numerical modeling of diffusional processes
NASA Technical Reports Server (NTRS)
Ghoniem, A. F.; Oppenheim, A. K.
1982-01-01
The random element method is a generalization of the random vortex method that was developed for the numerical modeling of momentum transport processes as expressed in terms of the Navier-Stokes equations. The method is based on the concept that random walk, as exemplified by Brownian motion, is the stochastic manifestation of diffusional processes. The algorithm based on this method is grid-free and does not require the diffusion equation to be discritized over a mesh, it is thus devoid of numerical diffusion associated with finite difference methods. Moreover, the algorithm is self-adaptive in space and explicit in time, resulting in an improved numerical resolution of gradients as well as a simple and efficient computational procedure. The method is applied here to an assortment of problems of diffusion of momentum and energy in one-dimension as well as heat conduction in two-dimensions in order to assess its validity and accuracy. The numerical solutions obtained are found to be in good agreement with exact solution except for a statistical error introduced by using a finite number of elements, the error can be reduced by increasing the number of elements or by using ensemble averaging over a number of solutions.
Chen, Tianwu; Zhao, Peng; Guo, Xu; Zhang, Sulin
2017-04-12
Phosphorus represents a promising anode material for sodium ion batteries owing to its extremely high theoretical capacity. Recent in situ transmission electron microscopy studies evidenced anisotropic swelling in sodiated black phosphorus, which may find an origin from the two intrinsic anisotropic properties inherent to the layered structure of black phosphorus: sodium diffusional directionality and insertion strain anisotropy. To understand the morphological evolution and stress generation in sodiated black phosphorus, we develop a chemo-mechanical model by incorporating the intrinsic anisotropic properties into the large elasto-plastic deformation. Our modeling results reveal that the apparent morphological evolution in sodiated black phosphorus is critically controlled by the coupled effect of the two intrinsic anisotropic properties. In particular, sodium diffusional directionality generates sharp interphases along the [010] and [001] directions, which constrain anisotropic development of the insertion strain. The coupled effect renders distinctive stress-generation and fracture mechanisms when sodiation starts from different crystal facets. In addition to providing a powerful modeling framework for sodiation and lithiation of layered structures, our findings shed significant light on the sodiation-induced chemo-mechanical degradation of black phosphorus as a promising anode for the next-generation sodium ion batteries.
Kinetics of Diffusional Droplet Growth in a Liquid/Liquid Two-Phase System
NASA Technical Reports Server (NTRS)
Glicksman, M. E.; Fradkov, V. E.
1996-01-01
We address the problem of diffusional interactions in a finite sized cluster of spherical particles for volume fractions, V(sub v) in the range 0-0.01. We determined the quasi-static monopole diffusion solution for n particles distributed at random in a continuous matrix. A global mass conservation condition is employed, obviating the need for any external boundary condition. The numerical results provide the instantaneous (snapshot) growth or shrinkage rate of each particle, precluding the need for extensive time-dependent computations. The close connection between these snapshot results and the coarsegrained kinetic constants are discussed. A square-root dependence of the deviations of the rate constants from their zero volume fraction value is found for the higher V(sub v) investigated. This behavior is consistent with predictions from diffusion Debye-Huckel screening theory. By contrast, a cube-root dependence, reported in earlier numerical studies, is found for the lower V(sub v) investigated. The roll-over region of the volume fraction where the two asymptotics merge depends on the number of particles, n, alone. A theoretical estimate for the roll-over point predicts that the corresponding V(sub v) varies as n(sup -2), in good agreement with the numerical results.
Evolution of a phase separated gravity independent bioreactor
NASA Technical Reports Server (NTRS)
Villeneuve, Peter E.; Dunlop, Eric H.
1992-01-01
The evolution of a phase-separated gravity-independent bioreactor is described. The initial prototype, a zero head-space manifold silicone membrane based reactor, maintained large diffusional resistances. Obtaining oxygen transfer rates needed to support carbon-recycling aerobic microbes is impossible if large resistances are maintained. Next generation designs (Mark I and II) mimic heat exchanger design to promote turbulence at the tubing-liquid interface, thereby reducing liquid and gas side diffusional resistances. While oxygen transfer rates increased by a factor of ten, liquid channeling prevented further increases. To overcome these problems, a Mark III reactor was developed which maintains inverted phases, i.e., media flows inside the silicone tubing, oxygen gas is applied external to the tubing. This enhances design through changes in gas side driving force concentration and liquid side turbulence levels. Combining an applied external pressure of 4 atm with increased Reynolds numbers resulted in oxygen transfer intensities of 232 mmol O2/l per hr (1000 times greater than the first prototype and comparable to a conventional fermenter). A 1.0 liter Mark III reactor can potentially deliver oxygen supplies necessary to support cell cultures needed to recycle a 10-astronaut carbon load continuously.
ERIC Educational Resources Information Center
Olsson, Ulf Henning; Foss, Tron; Troye, Sigurd V.; Howell, Roy D.
2000-01-01
Used simulation to demonstrate how the choice of estimation method affects indexes of fit and parameter bias for different sample sizes when nested models vary in terms of specification error and the data demonstrate different levels of kurtosis. Discusses results for maximum likelihood (ML), generalized least squares (GLS), and weighted least…
ERIC Educational Resources Information Center
Pant, Mohan Dev
2011-01-01
The Burr families (Type III and Type XII) of distributions are traditionally used in the context of statistical modeling and for simulating non-normal distributions with moment-based parameters (e.g., Skew and Kurtosis). In educational and psychological studies, the Burr families of distributions can be used to simulate extremely asymmetrical and…
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
Cloud Forecast Simulation Model.
1981-10-01
creasing the kurtosis of the distribution, i.e., making it more negative (more platykurtic ). Case (a) might be the distribution of forecast cloud cover be...fore smoothing, and (b) might be the distribution after smoothing. Character- istically, smoothing makes cloud cover distributions less platykurtic ...19, this effect of smoothing can be described in terms of making the smoothed distribu- tion less platykurtic than the unsmoothed distribution
Algorithm Development for a Real-Time Military Noise Monitor
2006-03-24
Duration ESLM Enhanced Sound Level Meter ERDC-CERL Engineer Research and Development Center/Construction Engineering Research Laboratory FFT...Fast Fourier Transform FTIG Fort Indiantown Gap Kurt Kurtosis LD Larson Davis Leq Equivalent Sound Level L8eq 8-hr Equivalent...Sound Level Lpk Peak Sound Level m Spectral Slope MCBCL Marine Corps Base Camp Lejeune Neg Number of negative samples NI National
Customized Multiwavelets for Planetary Gearbox Fault Detection Based on Vibration Sensor Signals
Sun, Hailiang; Zi, Yanyang; He, Zhengjia; Yuan, Jing; Wang, Xiaodong; Chen, Lue
2013-01-01
Planetary gearboxes exhibit complicated dynamic responses which are more difficult to detect in vibration signals than fixed-axis gear trains because of the special gear transmission structures. Diverse advanced methods have been developed for this challenging task to reduce or avoid unscheduled breakdown and catastrophic accidents. It is feasible to make fault features distinct by using multiwavelet denoising which depends on the feature separation and the threshold denoising. However, standard and fixed multiwavelets are not suitable for accurate fault feature detections because they are usually independent of the measured signals. To overcome this drawback, a method to construct customized multiwavelets based on the redundant symmetric lifting scheme is proposed in this paper. A novel indicator which combines kurtosis and entropy is applied to select the optimal multiwavelets, because kurtosis is sensitive to sharp impulses and entropy is effective for periodic impulses. The improved neighboring coefficients method is introduced into multiwavelet denoising. The vibration signals of a planetary gearbox from a satellite communication antenna on a measurement ship are captured under various motor speeds. The results show the proposed method could accurately detect the incipient pitting faults on two neighboring teeth in the planetary gearbox. PMID:23334609
NASA Astrophysics Data System (ADS)
Ali, Naseem; Aseyev, A.; McCraney, J.; Vuppuluri, V.; Abbass, O.; Al Jubaree, T.; Melius, M.; Cal, R. B.
2014-11-01
Hot-wire measurements obtained in a 3 × 3 wind turbine array boundary layer are utilized to analyze higher order statistics which include skewness, kurtosis as well as the ratios of structure functions and spectra. The ratios consist of wall-normal to streamwise components for both quantities. The aim is to understand the degree of anisotropy in the flow for the near- and far-wakes of the flow field where profiles at one diameter and five diameters are considered, respectively. The skewness at top tip for both wakes show a negative skewness while below the turbine canopy, this terms are positive. The kurtosis shows a Gaussian behavior in the near-wake immediately at hub-height. In addition, the effect due to the passage of the rotor in tandem with the shear layer at the top tip renders relatively high differences in the fourth order moment. The second order structure function and spectral ratios are found to exhibit anisotropic behavior at the top and bottom-tips for the large scales. Mixed structure functions and co-spectra are also considered in the context of isotropy.
Month-to-month and year-to-year reproducibility of high frequency QRS ECG signals
NASA Technical Reports Server (NTRS)
Batdorf, Niles J.; Feiveson, Alan H.; Schlegel, Todd T.
2004-01-01
High frequency electrocardiography analyzing the entire QRS complex in the frequency range of 150 to 250 Hz may prove useful in the detection of coronary artery disease, yet the long-term stability of these waveforms has not been fully characterized. Therefore, we prospectively investigated the reproducibility of the root mean squared voltage, kurtosis, and the presence versus absence of reduced amplitude zones in signal averaged 12-lead high frequency QRS recordings acquired in the supine position one month apart in 16 subjects and one year apart in 27 subjects. Reproducibility of root mean squared voltage and kurtosis was excellent over these time intervals in the limb leads, and acceptable in the precordial leads using both the V-lead and CR-lead derivations. The relative error of root mean squared voltage was 12% month-to-month and 16% year-to-year in the serial recordings when averaged over all 12 leads. Reduced amplitude zones were also reproducible up to a rate of 87% and 81%, respectively, for the month-to-month and year-to-year recordings. We conclude that 12-lead high frequency QRS electrocardiograms are sufficiently reproducible for clinical use.
Month-to-Month and Year-to-Year Reproducibility of High Frequency QRS ECG signals
NASA Technical Reports Server (NTRS)
Batdorf, Niles; Feiveson, Alan H.; Schlegel, Todd T.
2006-01-01
High frequency (HF) electrocardiography analyzing the entire QRS complex in the frequency range of 150 to 250 Hz may prove useful in the detection of coronary artery disease, yet the long-term stability of these waveforms has not been fully characterized. We therefore prospectively investigated the reproducibility of the root mean squared (RMS) voltage, kurtosis, and the presence versus absence of reduced amplitude zones (RAzs) in signal averaged 12-lead HF QRS recordings acquired in the supine position one month apart in 16 subjects and one year apart in 27 subjects. Reproducibility of RMS voltage and kurtosis was excellent over these time intervals in the limb leads, and acceptable in the precordial leads using both the V-lead and CR-lead derivations. The relative error of RMS voltage was 12% month-to-month and 16% year-to-year in the serial recordings when averaged over all 12 leads. RAzs were also reproducible at a rate of up to 87% and 8 1 %, respectively, for the month-to-month and year-to-year recordings. We conclude that 12-lead HF QRS electrocardiograms are sufficiently reproducible for clinical use.
NASA Astrophysics Data System (ADS)
Xu, Yonggen; Dan, Youquan; Yu, Jiayi; Cai, Yangjian
2017-10-01
General analytical formulae for the kurtosis parameters K (K parameters) of the arbitrary electromagnetic (AE) beams propagating through non-Kolmogorov turbulence are derived, and according to the unified theory of polarization and coherence, the effect of degree of polarization (DOP) of an electromagnetic beam on the K parameter is studied. The analytical formulae can be given by the second-order moments and fourth-order moments of the Wigner distribution function for AE beams at source plane, the two turbulence quantities relating to the spatial power spectrum, and the propagation distance. Our results can also be extended to the arbitrary beams and the arbitrary spatial power spectra of Kolmogorov turbulence or non-Kolmogorov turbulence. Taking the stochastic electromagnetic Gaussian Schell-model (SEGSM) beam as an example, the numerical examples indicate that the K parameters of a SEGSM beam in non-Kolmogorov turbulence depend on propagation distance, the beam parameters and turbulence parameters. The K parameter of a SEGM beam is more sensitive to effect of turbulence with smaller inner scale and generalized exponent parameter. A non-polarized light has the strongest ability of resisting turbulence (ART), however, a fully polarized SEGSM beam has the poorest ART.
Intermittency in 2D soap film turbulence
NASA Astrophysics Data System (ADS)
Cerbus, R. T.; Goldburg, W. I.
2013-10-01
The Reynolds number dependency of intermittency for 2D turbulence is studied in a flowing soap film. The Reynolds number used here is the Taylor microscale Reynolds number Rλ, which ranges from 20 to 800. Strong intermittency is found for both the inverse energy and direct enstrophy cascades as measured by (a) the pdf of velocity differences P(δu(r)) at inertial scales r, (b) the kurtosis of P(∂xu), and (c) the scaling of the so-called intermittency exponent μ, which is zero if intermittency is absent. Measures (b) and (c) are quantitative, while (a) is qualitative. These measurements are in disagreement with some previous results but not all. The velocity derivatives are nongaussian at all Rλ but show signs of becoming gaussian as Rλ increases beyond the largest values that could be reached. The kurtosis of P(δu(r)) at various r indicates that the intermittency is scale dependent. The structure function scaling exponents also deviate strongly from the Kraichnan prediction. For the enstrophy cascade, the intermittency decreases as a power law in Rλ. This study suggests the need for a new look at the statistics of 2D turbulence.
Analysis of impact/impulse noise for predicting noise induced hearing loss
NASA Astrophysics Data System (ADS)
Vipperman, Jeffrey S.; Prince, Mary M.; Flamm, Angela M.
2003-04-01
Studies indicate that the statistical properties and temporal structure of the sound signal are important in determining the extent of hearing hazard. As part of a pilot study to examine hearing conservation program effectiveness, NIOSH collected noise samples of impact noise sources in an automobile stamping plant, focusing on jobs with peak sound levels (Lpk) of greater than 120 dB. Digital tape recordings of sounds were collected using a Type I Precision Sound Level Meter and microphone connected to a DAT tape recorder. The events were archived and processed as .wav files to extract single events of interest on CD-R media and CD audio media. A preliminary analysis of sample wavelet files was conducted to characterize each event using metrics such as the number of impulses per unit time, the repetition rate or temporal pattern of these impulses, index of peakedness, crest factor, kurtosis, coefficient of kurtosis, rise time, fall time, and peak time. The spectrum, duration, and inverse of duration for each waveform were also computed. Finally, the data were evaluated with the Auditory Hazard Assessment Algorithm (AHAAH). Improvements to data collection for a future study examining different strategies for evaluating industrial noise exposure will be discussed.
2013-01-01
Background The biting cycle of anopheline mosquitoes is an important component in the transmission of malaria. Inter- and intraspecific biting patterns of anophelines have been investigated using the number of mosquitoes caught over time to compare general tendencies in host-seeking activity and cumulative catch. In this study, all-night biting catch data from 32 consecutive months of collections in three riverine villages were used to compare biting cycles of the five most abundant vector species using common statistics to quantify variability and deviations of nightly catches from a normal distribution. Methods Three communities were selected for study. All-night human landing catches of mosquitoes were made each month in the peridomestic environment of four houses (sites) for nine consecutive days from April 2003 to November 2005. Host-seeking activities of the five most abundant species that were previously captured infected with Plasmodium falciparum, Plasmodium malariae or Plasmodium vivax, were analysed and compared by measuring the amount of variation in numbers biting per unit time (co-efficient of variation, V), the degree to which the numbers of individuals per unit time were asymmetrical (skewness = g1) and the relative peakedness or flatness of the distribution (kurtosis = g2). To analyse variation in V, g1, and g2 within species and villages, we used mixed model nested ANOVAs (PROC GLM in SAS) with independent variables (sources of variation): year, month (year), night (year X month) and collection site (year X month). Results The biting cycles of the most abundant species, Anopheles darlingi, had the least pronounced biting peaks, the lowest mean V values, and typically non-significant departures from normality in g1 and g2. By contrast, the species with the most sharply defined crepuscular biting peaks, Anopheles marajoara, Anopheles nuneztovari and Anopheles triannulatus, showed high to moderate mean V values and, most commonly, significantly positive skewness (g1) and kurtosis (g2) moments. Anopheles intermedius was usually, but not always, crepuscular in host seeking, and showed moderate mean V values and typically positive skewness and kurtosis. Among sites within villages, significant differences in frequencies of departures from normality (g1 and g2) were detected for An. marajoara and An. darlingi, suggesting that local environments, such as host availability, may affect the shape of biting pattern curves of these two species. Conclusions Analyses of co-efficients of variation, skewness and kurtosis facilitated quantitative comparisons of host-seeking activity patterns that differ among species, sites, villages, and dates. The variable and heterogeneous nightly host-seeking behaviours of the five exophilic vector species contribute to the maintenance of stable malaria transmission in these Amazonian villages. The abundances of An. darlingi and An. marajoara, their propensities to seek hosts throughout the night, and their ability to adapt host-seeking behaviour to local environments, contribute to their impact as the most important of these vector species. PMID:23890413
Modelling of squall with the generalised kinetic equation
NASA Astrophysics Data System (ADS)
Annenkov, Sergei; Shrira, Victor
2014-05-01
We study the long-term evolution of random wind waves using the new generalised kinetic equation (GKE). The GKE derivation [1] does not assume the quasi-stationarity of a random wave field. In contrast with the Hasselmann kinetic equation, the GKE can describe fast spectral changes occurring when a wave field is driven out of a quasi-equilibrium state by a fast increase or decrease of wind, or by other factors. In these cases, a random wave field evolves on the dynamic timescale typical of coherent wave processes, rather than on the kinetic timescale predicted by the conventional statistical theory. Besides that, the generalised theory allows to trace the evolution of higher statistical moments of the field, notably the kurtosis, which is important for assessing the risk of freak waves and other applications. A new efficient and highly parallelised algorithm for the numerical simulation of the generalised kinetic equation is presented and discussed. Unlike in the case of the Hasselmann equation, the algorithm takes into account all (resonant and non-resonant) nonlinear wave interactions, but only approximately resonant interactions contribute to the spectral evolution. However, counter-intuitively, all interactions contribute to the kurtosis. Without forcing or dissipation, the algorithm is shown to conserve the relevant integrals. We show that under steady wind forcing the wave field evolution predicted by the GKE is close to the predictions of the conventional statistical theory, which is applicable in this case. In particular, we demonstrate the known long-term asymptotics for the evolution of the spectrum. When the wind forcing is not steady (in the simplest case, an instant increase or decrease of wind occurs), the generalised theory is the only way to study the spectral evolution, apart from the direct numerical simulation. The focus of the work is a detailed analysis of the fast evolution after an instant change of forcing, and of the subsequent transition to the new quasi-stationary state of a wave field. It is shown that both increase and decrease of wind lead to a significant transient increase of the dynamic kurtosis, although these changes remain small compared to the changes of the other component of the kurtosis, which is due to bound harmonics. A special consideration is given to the case of the squall, i.e. an instant and large (by a factor of 2-4) increase of wind, which lasts for O(102) characteristic wave periods. We show that fast adjustment processes lead to the formation of a transient spectrum, which has a considerably narrower peak than the spectra developed under a steady forcing. These transient spectra differ qualitatively from those predicted by the Hasselmann kinetic equation under the squall with the same parameters. 1. S.Annenkov, V.Shrira (2006) Role of non-resonant interactions in evolution of nonlinear random water wave fields, J. Fluid Mech. 561, 181-207.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nyflot, MJ; Yang, F; Byrd, D
Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850,more » 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials which incorporate textural features are properly designed to detect clinical endpoints. Supported by NIH grants R01 CA169072, U01 CA148131, NCI Contract (SAIC-Frederick) 24XS036-004, and a research contract from GE Healthcare.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, C; Bradshaw, T; Perk, T
2015-06-15
Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative {sup 18}F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm{sup 3} were identified and automatically segmented using a SUV>15 threshold. From eachmore » lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm{sup 3} for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria for NaF PET-based treatment response assessment. Prostate Cancer Foundation (PCF)« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boffi, V.C.; Molinari, V.G.; Parks, D.E.
1962-05-01
Features of the pulsed neution source theory connected with the measurement of diffusion parameters are discussed. Various analytical procedures for determining the decay constant of the fully thermalized neutron flux are compared. The problem of the diffusion coefficient definition is also considered in some detail. (auth)
Estimation of population mean under systematic sampling
NASA Astrophysics Data System (ADS)
Noor-ul-amin, Muhammad; Javaid, Amjad
2017-11-01
In this study we propose a generalized ratio estimator under non-response for systematic random sampling. We also generate a class of estimators through special cases of generalized estimator using different combinations of coefficients of correlation, kurtosis and variation. The mean square errors and mathematical conditions are also derived to prove the efficiency of proposed estimators. Numerical illustration is included using three populations to support the results.
Nam, Se Jin; Yoo, Jaeheung; Lee, Hye Sun; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; Kwak, Jin Young
2016-04-01
To evaluate the diagnostic value of histogram analysis using grayscale sonograms for differentiation of malignant and benign thyroid nodules. From July 2013 through October 2013, 579 nodules in 563 patients who had undergone ultrasound-guided fine-needle aspiration were included. For the grayscale histogram analysis, pixel echogenicity values in regions of interest were measured as 0 to 255 (0, black; 255, white) with in-house software. Five parameters (mean, skewness, kurtosis, standard deviation, and entropy) were obtained for each thyroid nodule. With principal component analysis, an index was derived. Diagnostic performance rates for the 5 histogram parameters and the principal component analysis index were calculated. A total of 563 patients were included in the study (mean age ± SD, 50.3 ± 12.3 years;range, 15-79 years). Of the 579 nodules, 431 were benign, and 148 were malignant. Among the 5 parameters and the principal component analysis index, the standard deviation (75.546 ± 14.153 versus 62.761 ± 16.01; P < .001), kurtosis (3.898 ± 2.652 versus 6.251 ± 9.102; P < .001), entropy (0.16 ± 0.135 versus 0.239 ± 0.185; P < .001), and principal component analysis index (-0.386±0.774 versus 0.134 ± 0.889; P < .001) were significantly different between the malignant and benign nodules. With the calculated cutoff values, the areas under the curve were 0.681 (95% confidence interval, 0.643-0.721) for standard deviation, 0.661 (0.620-0.703) for principal component analysis index, 0.651 (0.607-0.691) for kurtosis, 0.638 (0.596-0.681) for entropy, and 0.606 (0.563-0.647) for skewness. The subjective analysis of grayscale sonograms by radiologists alone showed an area under the curve of 0.861 (0.833-0.888). Grayscale histogram analysis was feasible for differentiating malignant and benign thyroid nodules but did not show better diagnostic performance than subjective analysis performed by radiologists. Further technical advances will be needed to objectify interpretations of thyroid grayscale sonograms. © 2016 by the American Institute of Ultrasound in Medicine.
Probability Distribution Extraction from TEC Estimates based on Kernel Density Estimation
NASA Astrophysics Data System (ADS)
Demir, Uygar; Toker, Cenk; Çenet, Duygu
2016-07-01
Statistical analysis of the ionosphere, specifically the Total Electron Content (TEC), may reveal important information about its temporal and spatial characteristics. One of the core metrics that express the statistical properties of a stochastic process is its Probability Density Function (pdf). Furthermore, statistical parameters such as mean, variance and kurtosis, which can be derived from the pdf, may provide information about the spatial uniformity or clustering of the electron content. For example, the variance differentiates between a quiet ionosphere and a disturbed one, whereas kurtosis differentiates between a geomagnetic storm and an earthquake. Therefore, valuable information about the state of the ionosphere (and the natural phenomena that cause the disturbance) can be obtained by looking at the statistical parameters. In the literature, there are publications which try to fit the histogram of TEC estimates to some well-known pdf.s such as Gaussian, Exponential, etc. However, constraining a histogram to fit to a function with a fixed shape will increase estimation error, and all the information extracted from such pdf will continue to contain this error. In such techniques, it is highly likely to observe some artificial characteristics in the estimated pdf which is not present in the original data. In the present study, we use the Kernel Density Estimation (KDE) technique to estimate the pdf of the TEC. KDE is a non-parametric approach which does not impose a specific form on the TEC. As a result, better pdf estimates that almost perfectly fit to the observed TEC values can be obtained as compared to the techniques mentioned above. KDE is particularly good at representing the tail probabilities, and outliers. We also calculate the mean, variance and kurtosis of the measured TEC values. The technique is applied to the ionosphere over Turkey where the TEC values are estimated from the GNSS measurement from the TNPGN-Active (Turkish National Permanent GNSS Network) network. This study is supported by by TUBITAK 115E915 and Joint TUBITAK 114E092 and AS CR14/001 projects.
Hao, Yonghong; Pan, Chu; Chen, WeiWei; Li, Tao; Zhu, WenZhen; Qi, JianPin
2016-12-01
To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. Mean ADC, median ADC, 5 th percentile ADC, 25 th percentile ADC, 75 th percentile ADC, 95 th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10 -6 mm 2 /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5 th percentile ADC, and 25 th percentile ADC. The 5 th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10 -6 mm 2 /s for differentiating between PTCs with and without extrathyroidal extension. Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555. © 2016 International Society for Magnetic Resonance in Medicine.
Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Yu-Chuan; Nan, Hai-Yan; Yang, Yang; Liu, Zhi-Cheng; Wang, Wen; Cui, Guang-Bin
2016-08-24
Type 2 diabetes mellitus (T2DM) is a risk factor for dementia. Mild cognitive impairment (MCI), an intermediary state between normal cognition and dementia, often occurs during the prodromal diabetic stage, making early diagnosis and intervention of MCI very important. Latest neuroimaging techniques revealed some underlying microstructure alterations for diabetic MCI, from certain aspects. But there still lacks an integrated multimodal MRI system to detect early neuroimaging changes in diabetic MCI patients. Thus, we intended to conduct a diagnostic trial using multimodal MRI techniques to detect early diabetic MCI that is determined by the Montreal Cognitive Assessment (MoCA). In this study, healthy controls, prodromal diabetes and diabetes subjects (53 subjects/group) aged 40-60 years will be recruited from the physical examination center of Tangdu Hospital. The neuroimaging and psychometric measurements will be repeated at a 0.5 year-interval for 2.5 years' follow-up. The primary outcome measures are 1) Microstructural and functional alterations revealed with multimodal MRI scans including structure magnetic resonance imaging (sMRI), resting state functional magnetic resonance imaging (rs-fMRI), diffusion kurtosis imaging (DKI), and three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL); 2) Cognition evaluation with MoCA. The second outcome measures are obesity, metabolic characteristics, lifestyle and quality of life. The study will provide evidence for the potential use of multimodal MRI techniques with psychometric evaluation in diagnosing MCI at prodromal diabetic stage so as to help decision making in early intervention and improve the prognosis of T2DM. This study has been registered to ClinicalTrials.gov ( NCT02420470 ) on April 2, 2015 and published on July 29, 2015.
Synthesis of Biofluidic Microsystems (SYNBIOSYS)
2007-10-01
reaction system. 58 FIGURE 41. The micro reactor is represented by a PFR network model. The calculation of reaction and convection is conducted in...one column of PFRs and the calculation of diffusional mixing is conducted between two columns of PFRs. 59 FIGURE 42. Apply the numerical method of...lines to calculate the diffusion in the channel width direction. Here, we take 10 discretized concentration points in the channel: ci1 - ci10. Points
Equation of state of heated glassy carbon
NASA Technical Reports Server (NTRS)
Sekine, Toshimori; Ahrens, Thomas J.
1991-01-01
New Hugoniot data are presented for glassy carbon preheated to 1550 K and shocked to 20 GPa. The high-temperature Hugoniot is very similar to the principal Hugoniot. This results argues against the diffusional mechanism for the shock-induced transformaton of amorphous carbon to diamond, although the present results are obviously limited to below 20 GPa. This study provides the first Higoniot data for carbon preheated to significantly high temperatures.
1981-07-01
C. McGill and J. 0. McCaldin ..... ............. .. 160 Diffusional Instability of p /n Heterojunctions J. J. Gilman...Preliminary Ideas on a Ductile-Brittle Transition in Fe-Si Single Crystals R. Thomson and J. P . Hirth. . . . . . . . . . . . . . . . 199 Comment on a...Baltimore, MD 21218 Professor Alan J. Heeger Department of Physics/El University of Pennsylvania Philadelphia, PA 19104 Professor John P . Hirth
SDA 7: A modular and parallel implementation of the simulation of diffusional association software
Martinez, Michael; Romanowska, Julia; Kokh, Daria B.; Ozboyaci, Musa; Yu, Xiaofeng; Öztürk, Mehmet Ali; Richter, Stefan
2015-01-01
The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein–protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration‐dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object‐oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26123630
Heo, Tae Wook; Chen, Long-Qing; Wood, Brandon C.
2015-04-08
In this paper, we present a comprehensive phase-field model for simulating diffusion-mediated kinetic phase behaviors near the surface of a solid particle. The model incorporates elastic inhomogeneity and anisotropy, diffusion mobility anisotropy, interfacial energy anisotropy, and Cahn–Hilliard diffusion kinetics. The free energy density function is formulated based on the regular solution model taking into account the possible solute-surface interaction near the surface. The coherency strain energy is computed using the Fourier-spectral iterative-perturbation method due to the strong elastic inhomogeneity with a zero surface traction boundary condition. Employing a phase-separating Li XFePO 4 electrode particle for Li-ion batteries as a modelmore » system, we perform parametric three-dimensional computer simulations. The model permits the observation of surface phase behaviors that are different from the bulk counterpart. For instance, it reproduces the theoretically well-established surface modes of spinodal decomposition of an unstable solid solution: the surface mode of coherent spinodal decomposition and the surface-directed spinodal decomposition mode. We systematically investigate the influences of major factors on the kinetic surface phase behaviors during the diffusional process. Finally, our simulation study provides insights for tailoring the internal phase microstructure of a particle by controlling the surface phase morphology.« less
Thermal-diffusional Instability in White Dwarf Flames: Regimes of Flame Pulsation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xing, Guangzheng; Zhao, Yibo; Zhou, Cheng
Thermal-diffusional pulsation behaviors in planar as well as outwardly and inwardly propagating white dwarf (WD) carbon flames are systematically studied. In the 1D numerical simulation, the asymptotic degenerate equation of state and simplified one-step reaction rates for nuclear reactions are used to study the flame propagation and pulsation in WDs. The numerical critical Zel’dovich numbers of planar flames at different densities ( ρ = 2, 3, and 4 × 10{sup 7} g cm{sup −3}) and of spherical flames (with curvature c = −0.01, 0, 0.01, and 0.05) at a particular density ( ρ = 2 × 10{sup 7} g cm{supmore » −3}) are presented. Flame front pulsation in different environmental densities and temperatures are obtained to form the regime diagram of pulsation, showing that carbon flames pulsate in the typical density of 2 × 10{sup 7} g cm{sup −3} and temperature of 0.6 × 10{sup 9} K. While being stable at higher temperatures, at relatively lower temperatures, the amplitude of the flame pulsation becomes larger. In outwardly propagating spherical flames the pulsation instability is enhanced and flames are also easier to quench due to pulsation at small radius, while the inwardly propagating flames are more stable.« less
Kaiser, Alexander; Ismailova, Oksana; Koskela, Antti; Huber, Stefan E.; Ritter, Marcel; Cosenza, Biagio; Benger, Werner; Nazmutdinov, Renat; Probst, Michael
2014-01-01
Molecular dynamics simulations of liquid ethylene glycol described by the OPLS-AA force field were performed to gain insight into its hydrogen-bond structure. We use the population correlation function as a statistical measure for the hydrogen-bond lifetime. In an attempt to understand the complicated hydrogen-bonding, we developed new molecular visualization tools within the Vish Visualization shell and used it to visualize the life of each individual hydrogen-bond. With this tool hydrogen-bond formation and breaking as well as clustering and chain formation in hydrogen-bonded liquids can be observed directly. Liquid ethylene glycol at room temperature does not show significant clustering or chain building. The hydrogen-bonds break often due to the rotational and vibrational motions of the molecules leading to an H-bond half-life time of approximately 1.5 ps. However, most of the H-bonds are reformed again so that after 50 ps only 40% of these H-bonds are irreversibly broken due to diffusional motion. This hydrogen-bond half-life time due to diffusional motion is 80.3 ps. The work was preceded by a careful check of various OPLS-based force fields used in the literature. It was found that they lead to quite different angular and H-bond distributions. PMID:24748697
Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey
2017-04-12
Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm². Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.
Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey
2017-01-01
Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm2. Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. Conclusions: histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted. PMID:28417929
NASA Astrophysics Data System (ADS)
Gan, Yu; Tsay, David; Amir, Syed B.; Marboe, Charles C.; Hendon, Christine P.
2016-03-01
Remodeling of the myocardium is associated with increased risk of arrhythmia and heart failure. Our objective is to automatically identify regions of fibrotic myocardium, dense collagen, and adipose tissue, which can serve as a way to guide radiofrequency ablation therapy or endomyocardial biopsies. Using computer vision and machine learning, we present an automated algorithm to classify tissue compositions from cardiac optical coherence tomography (OCT) images. Three dimensional OCT volumes were obtained from 15 human hearts ex vivo within 48 hours of donor death (source, NDRI). We first segmented B-scans using a graph searching method. We estimated the boundary of each region by minimizing a cost function, which consisted of intensity, gradient, and contour smoothness. Then, features, including texture analysis, optical properties, and statistics of high moments, were extracted. We used a statistical model, relevance vector machine, and trained this model with abovementioned features to classify tissue compositions. To validate our method, we applied our algorithm to 77 volumes. The datasets for validation were manually segmented and classified by two investigators who were blind to our algorithm results and identified the tissues based on trichrome histology and pathology. The difference between automated and manual segmentation was 51.78 +/- 50.96 μm. Experiments showed that the attenuation coefficients of dense collagen were significantly different from other tissue types (P < 0.05, ANOVA). Importantly, myocardial fibrosis tissues were different from normal myocardium in entropy and kurtosis. The tissue types were classified with an accuracy of 84%. The results show good agreements with histology.
Suppression of the Near Wall Burst Process of a Fully Developed Turbulent Pipe Flow
1993-05-01
tunmel turbulent boundary layer a) velocity fluctuation skewness levels and b) velocity fluctuation kurtosis levels ...by the undisturbed total uv level and u*. a) quadrants I and 2 and b) quadrants 3 and 4 ...................... 105 5.20 Spanwise development of the uw...and radial velocity skewness levels . Normalization with ref. u". .............................. 111 xi 5.23 Spanwise development of profi!s of the
Robust functional statistics applied to Probability Density Function shape screening of sEMG data.
Boudaoud, S; Rix, H; Al Harrach, M; Marin, F
2014-01-01
Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.
Feature study of hysterical blindness EEG based on FastICA with combined-channel information.
Qin, Xuying; Wang, Wei; Hu, Lintao; Wang, Xu; Yuan, Xiaojie
2015-01-01
An appropriate feature study of hysteria electroencephalograms (EEG) would provide new insights into neural mechanisms of the disease, and also make improvements in patient diagnosis and management. The objective of this paper is to provide an explanation for what causes a particular visual loss, by associating the features of hysterical blindness EEG with brain function. An idea for the novel feature extraction for hysterical blindness EEG, utilizing combined-channel information, was applied in this paper. After channels had been combined, the sliding-window-FastICA was applied to process the combined normal EEG and hysteria EEG, respectively. Kurtosis features were calculated from the processed signals. As the comparison feature, the power spectral density of normal and hysteria EEG were computed. According to the feature analysis results, a region of brain dysfunction was located at the occipital lobe, O1 and O2. Furthermore, new abnormality was found at the parietal lobe, C3, C4, P3, and P4, that provided us with a new perspective for understanding hysterical blindness. Indicated by the kurtosis results which were consistent with brain function and the clinical diagnosis, our method was found to be a useful tool to capture features in hysterical blindness EEG.
Probability and the changing shape of response distributions for orientation.
Anderson, Britt
2014-11-18
Spatial attention and feature-based attention are regarded as two independent mechanisms for biasing the processing of sensory stimuli. Feature attention is held to be a spatially invariant mechanism that advantages a single feature per sensory dimension. In contrast to the prediction of location independence, I found that participants were able to report the orientation of a briefly presented visual grating better for targets defined by high probability conjunctions of features and locations even when orientations and locations were individually uniform. The advantage for high-probability conjunctions was accompanied by changes in the shape of the response distributions. High-probability conjunctions had error distributions that were not normally distributed but demonstrated increased kurtosis. The increase in kurtosis could be explained as a change in the variances of the component tuning functions that comprise a population mixture. By changing the mixture distribution of orientation-tuned neurons, it is possible to change the shape of the discrimination function. This prompts the suggestion that attention may not "increase" the quality of perceptual processing in an absolute sense but rather prioritizes some stimuli over others. This results in an increased number of highly accurate responses to probable targets and, simultaneously, an increase in the number of very inaccurate responses. © 2014 ARVO.
Faraday dispersion functions of galaxies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ideguchi, Shinsuke; Tashiro, Yuichi; Takahashi, Keitaro
2014-09-01
The Faraday dispersion function (FDF), which can be derived from an observed polarization spectrum by Faraday rotation measure synthesis, is a profile of polarized emissions as a function of Faraday depth. We study intrinsic FDFs along sight lines through face-on Milky Way like galaxies by means of a sophisticated galactic model incorporating three-dimensional MHD turbulence, and investigate how much information the FDF intrinsically contains. Since the FDF reflects distributions of thermal and cosmic-ray electrons as well as magnetic fields, it has been expected that the FDF could be a new probe to examine internal structures of galaxies. We, however, findmore » that an intrinsic FDF along a sight line through a galaxy is very complicated, depending significantly on actual configurations of turbulence. We perform 800 realizations of turbulence and find no universal shape of the FDF even if we fix the global parameters of the model. We calculate the probability distribution functions of the standard deviation, skewness, and kurtosis of FDFs and compare them for models with different global parameters. Our models predict that the presence of vertical magnetic fields and the large-scale height of cosmic-ray electrons tend to make the standard deviation relatively large. In contrast, the differences in skewness and kurtosis are relatively less significant.« less
Hierarchy of N-point functions in the ΛCDM and ReBEL cosmologies
NASA Astrophysics Data System (ADS)
Hellwing, Wojciech A.; Juszkiewicz, Roman; van de Weygaert, Rien
2010-11-01
In this work we investigate higher-order statistics for the ΛCDM and ReBEL scalar-interacting dark matter models by analyzing 180h-1Mpc dark matter N-body simulation ensembles. The N-point correlation functions and the related hierarchical amplitudes, such as skewness and kurtosis, are computed using the counts-in-cells method. Our studies demonstrate that the hierarchical amplitudes Sn of the scalar-interacting dark matter model significantly deviate from the values in the ΛCDM cosmology on scales comparable and smaller than the screening length rs of a given scalar-interacting model. The corresponding additional forces that enhance the total attractive force exerted on dark matter particles at galaxy scales lower the values of the hierarchical amplitudes Sn. We conclude that hypothetical additional exotic interactions in the dark matter sector should leave detectable markers in the higher-order correlation statistics of the density field. We focused in detail on the redshift evolution of the dark matter field’s skewness and kurtosis. From this investigation we find that the deviations from the canonical ΛCDM model introduced by the presence of the “fifth” force attain a maximum value at redshifts 0.5
NASA Astrophysics Data System (ADS)
Nita, Gelu M.; Gary, Dale E.
2016-08-01
Following our prior theoretical and instrumental work addressing the problem of automatic real-time radio frequency interference (RFI) detection and excision from astronomical signals, the wideband Spectral Kurtosis (SK) spectrometer design we proposed is currently being considered as an alternative to the traditional spectrometers when building the new generation of radio instruments. The unique characteristic of an SK spectrometer is that it accumulates both power and power-squared, which are then used to compute an SK statistical estimator proven to be very effective in detecting and excising certain types of RFI signals. In this paper we introduce a novel measurement technique that exploits the power and power square statistics of an SK spectrometer to determine durations and signal-to-noise ratios of transient signals, whether they are RFI or natural signals, even when they are below the time resolution of the instrument. We demonstrate this novel experimental technique by analyzing a segment of data recorded by the Expanded Owens Valley Solar Array Subsystem Testbed (EST) during a solar radio burst in which microwave spike bursts occurred with durations shorter than the 20 ms time resolution of the instrument. The duration of one well-observed spike is quantitatively shown to be within a few percent of 8 ms despite the 20 ms resolution of the data.
The Shock Pulse Index and Its Application in the Fault Diagnosis of Rolling Element Bearings
Sun, Peng; Liao, Yuhe; Lin, Jin
2017-01-01
The properties of the time domain parameters of vibration signals have been extensively studied for the fault diagnosis of rolling element bearings (REBs). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are the most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock Pulse Index (SPI), is proposed in this paper. It integrates the mutual advantages of both the parameters mentioned above and can help effectively identify fault-related impulse components under conditions of interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the transient information of interest contained in the filtered signal can be highlighted through demodulation with the Teager Energy Operator (TEO). Fault-related impulse components can therefore be extracted accurately. Simulations show the SPI can correctly indicate the fault impulses under the influence of strong background noises, other harmonic components and aperiodic impulse and experiment analyses verify the effectiveness and correctness of the proposed method. PMID:28282883
From one to one million: How does community structure track disturbance across time and space?
NASA Astrophysics Data System (ADS)
Webb, A. E.
2012-12-01
The rate and severity of disturbances to the biosphere have been increasing over the last millennium due in part to anthropogenic effects, and the results of these disturbances are of increasing interest to the scientific and public communities. This project examines the impact of acidification and global warming on communities across a spectrum of temporal and spatial scales in both modern and fossil systems. Twenty datasets were selected from published zoo- and phyto-plankton literature to represent a temporal and spatial gradient, from small lakes to the open ocean, and from one year to one million years. Each dataset is associated with a proxy for an environmental disturbance (isotopes, pH, sedimentology, etc.) and consists of 15-300 samples across the interval of disturbance. To test the biotic changes induced by disturbance, community structure is measured by quantifying species-abundance distributions using rank-abundance curves and ordinations. A community consists of the individuals present in a given location at a given time, and the relative abundance of different species serves as a proxy for resource-partitioning. Disturbances cause a change in resource-partitioning, either by changing resource availability or by removing/adding species which compete for those resources. Therefore, shifts in resource-partitioning resulting from disturbance can be tracked by changes in community composition. Prior to an environmental disturbance, communities typically consist of many species that evenly partition resources and thereby abundance. After a disturbance, communities are dominated by a few species that can tolerate or thrive in the new conditions. Non-metric multi-dimensional scaling and Bray-Curtis polar ordinations reveal a progression from pre-disturbance communities, through the disturbance, and into the eventual recovery, which may or may not resemble the pre-disturbance communities. Larger disturbances (in terms of spatial extent or temporal duration) result in more extensive faunal turnover, thereby reducing the utility of ordinations that require at least some faunal similarity. Rank-abundance curves can be applied even in intervals of complete taxonomic turnover; curve shape is quantified by kurtosis, a statistical measure of whether a distribution is more (>3) or less (<3) peaked than a Gaussian distribution (kurtosis = 3). Rank-abundance curve kurtosis values are always greater than 3 for disturbed communities (n=20), and pre-disturbance and recovered communities generally range from 0 to 4. The average kurtosis for a pre-disturbance or recovered community is unique for each type of community (taxonomically or environmentally defined), requiring the establishment of a baseline for rank-abundance curve analysis. In each dataset, both rank-abundance curves and ordinations show a similar pattern of change in community structure during a disturbance. The rate and pattern of recovery varies relative to the spatial and temporal extent of the disturbance. The results of this study reveal that community structure is a useful measure of the impact of a disturbance, both in terms of the severity of the disturbance and in measuring the subsequent recovery. The methods and results of this research are applicable to multiple fields, from conservation biology to ecosystem health to paleoceanography and paleobiology.
q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans.
Golkov, Vladimir; Dosovitskiy, Alexey; Sperl, Jonathan I; Menzel, Marion I; Czisch, Michael; Samann, Philipp; Brox, Thomas; Cremers, Daniel
2016-05-01
Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines. An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive microstructure assessment method with a prominent application in neuroimaging. Advanced diffusion models providing accurate microstructural characterization so far have required long acquisition times and thus have been inapplicable for children and adults who are uncooperative, uncomfortable, or unwell. We show that the long scan time requirements are mainly due to disadvantages of classical data processing. We demonstrate how deep learning, a group of algorithms based on recent advances in the field of artificial neural networks, can be applied to reduce diffusion MRI data processing to a single optimized step. This modification allows obtaining scalar measures from advanced models at twelve-fold reduced scan time and detecting abnormalities without using diffusion models. We set a new state of the art by estimating diffusion kurtosis measures from only 12 data points and neurite orientation dispersion and density measures from only 8 data points. This allows unprecedentedly fast and robust protocols facilitating clinical routine and demonstrates how classical data processing can be streamlined by means of deep learning.
Simulations on the Influence of Myelin Water in Diffusion-Weighted Imaging
Harkins, Kevin D.; Does, Mark D.
2016-01-01
While myelinated axons present an important barrier to water diffusion, many models used to interpret DWI signal neglect other potential influences of myelin. In this work, Monte Carlo simulations were used to test the sensitivity of DWI results to the diffusive properties of water within myelin. Within these simulations, the apparent diffusion coefficient (Dapp) varied slowly over several orders of magnitude of the coefficient of myelin water diffusion (Dm), but exhibited important differences compared to Dapp values simulated that neglect Dm (=0). Compared to Dapp, the apparent diffusion kurtosis (Kapp) was generally more sensitive to Dm. Simulations also tested the sensitivity of Dapp and Kapp to the amount of myelin present. Unique variations in Dapp and Kapp caused by differences in the myelin volume fraction were diminished when myelin water diffusion was included. Also, expected trends in Dapp and Kapp with experimental echo time were reduced or inverted when accounting for myelin water diffusion, and these reduced/inverted trends were seen experimentally in ex vivo rat brain DWI experiments. In general, myelin water has the potential to subtly influence DWI results and bias models of DWI that neglect these components of white matter. PMID:27271991
Nealy, Jennifer; Benz, Harley M.; Hayes, Gavin; Berman, Eric; Barnhart, William
2017-01-01
The 2008 Wells, NV earthquake represents the largest domestic event in the conterminous U.S. outside of California since the October 1983 Borah Peak earthquake in southern Idaho. We present an improved catalog, magnitude complete to 1.6, of the foreshock-aftershock sequence, supplementing the current U.S. Geological Survey (USGS) Preliminary Determination of Epicenters (PDE) catalog with 1,928 well-located events. In order to create this catalog, both subspace and kurtosis detectors are used to obtain an initial set of earthquakes and associated locations. The latter are then calibrated through the implementation of the hypocentroidal decomposition method and relocated using the BayesLoc relocation technique. We additionally perform a finite fault slip analysis of the mainshock using InSAR observations. By combining the relocated sequence with the finite fault analysis, we show that the aftershocks occur primarily updip and along the southwestern edge of the zone of maximum slip. The aftershock locations illuminate areas of post-mainshock strain increase; aftershock depths, ranging from 5 to 16 km, are consistent with InSAR imaging, which shows that the Wells earthquake was a buried source with no observable near-surface offset.
Feng, Zhaoyan; Min, Xiangde; Margolis, Daniel J. A.; Duan, Caohui; Chen, Yuping; Sah, Vivek Kumar; Chaudhary, Nabin; Li, Basen; Ke, Zan; Zhang, Peipei; Wang, Liang
2017-01-01
Objectives To evaluate the diagnostic performance of different mathematical models and different b-value ranges of diffusion-weighted imaging (DWI) in peripheral zone prostate cancer (PZ PCa) detection. Methods Fifty-six patients with histologically proven PZ PCa who underwent DWI-magnetic resonance imaging (MRI) using 21 b-values (0–4500 s/mm2) were included. The mean signal intensities of the regions of interest (ROIs) placed in benign PZs and cancerous tissues on DWI images were fitted using mono-exponential, bi-exponential, stretched-exponential, and kurtosis models. The b-values were divided into four ranges: 0–1000, 0–2000, 0–3200, and 0–4500 s/mm2, grouped as A, B, C, and D, respectively. ADC,
NASA Astrophysics Data System (ADS)
Tanaka, Rie; Matsuda, Hiroaki; Sanada, Shigeru
2017-03-01
The density of lung tissue changes as demonstrated on imagery is dependent on the relative increases and decreases in the volume of air and lung vessels per unit volume of lung. Therefore, a time-series analysis of lung texture can be used to evaluate relative pulmonary function. This study was performed to assess a time-series analysis of lung texture on dynamic chest radiographs during respiration, and to demonstrate its usefulness in the diagnosis of pulmonary impairments. Sequential chest radiographs of 30 patients were obtained using a dynamic flat-panel detector (FPD; 100 kV, 0.2 mAs/pulse, 15 frames/s, SID = 2.0 m; Prototype, Konica Minolta). Imaging was performed during respiration, and 210 images were obtained over 14 seconds. Commercial bone suppression image-processing software (Clear Read Bone Suppression; Riverain Technologies, Miamisburg, Ohio, USA) was applied to the sequential chest radiographs to create corresponding bone suppression images. Average pixel values, standard deviation (SD), kurtosis, and skewness were calculated based on a density histogram analysis in lung regions. Regions of interest (ROIs) were manually located in the lungs, and the same ROIs were traced by the template matching technique during respiration. Average pixel value effectively differentiated regions with ventilatory defects and normal lung tissue. The average pixel values in normal areas changed dynamically in synchronization with the respiratory phase, whereas those in regions of ventilatory defects indicated reduced variations in pixel value. There were no significant differences between ventilatory defects and normal lung tissue in the other parameters. We confirmed that time-series analysis of lung texture was useful for the evaluation of pulmonary function in dynamic chest radiography during respiration. Pulmonary impairments were detected as reduced changes in pixel value. This technique is a simple, cost-effective diagnostic tool for the evaluation of regional pulmonary function.
NASA Astrophysics Data System (ADS)
Nowacki, A.; Shi, P.; Angus, D. A.; Rost, S.; Birnie, C. E.; Yuan, S.
2017-12-01
Modern, large seismic datasets place a huge burden on human analysts who traditionally have been required to manually pick distinct phase arrivals in order to locate seismic events. This burden becomes insurmountable when real-time monitoring is needed, and hence automated approaches are necessary. Whilst many methods exist, noisy data often defeat them. We propose here a novel method to migrate seismic energy back to its spatial and temporal source, based on an improved imaging condition with greater tolerance to noise. The multichannel coherency migration (MCM) method sums the correlation coefficients of traces between all available station pairs, using the predicted P- and S-wave windows for any given imaging point in the target volume. Grid searching in time and space allows the point of maximum waveform coherency and event likelihood to be found. The only adjustable parameter in the method is the cross-correlation window length, but this is determined by the dominant frequency of the signal. This is in contrast with most other methods, such as the STA-LTA imaging function, which require several parameters to be adjusted and optimised for each application. Because we use the cross-correlation between stations, incoherent noise is effectively suppressed, and even temporally coherent noise which is not located within the target volume can be minimised also. We apply the MCM to synthetic tests, and real data in geological carbon storage and volcanic settings. In comparison to migrations based on waveform envelope, STA-LTA and kurtosis imaging functions, the MCM more reliably finds the true source and better suppresses noise. Synthetic tests with real noise show that the MCM remains robust up to noise-to-signal (not a typo) ratios (NSR) of about 40. Tests with incorrect velocity models further suggest that the MCM will be a useful event detection method in the future.
Statistics of Visual Responses to Image Object Stimuli from Primate AIT Neurons to DNN Neurons.
Dong, Qiulei; Wang, Hong; Hu, Zhanyi
2018-02-01
Under the goal-driven paradigm, Yamins et al. ( 2014 ; Yamins & DiCarlo, 2016 ) have shown that by optimizing only the final eight-way categorization performance of a four-layer hierarchical network, not only can its top output layer quantitatively predict IT neuron responses but its penultimate layer can also automatically predict V4 neuron responses. Currently, deep neural networks (DNNs) in the field of computer vision have reached image object categorization performance comparable to that of human beings on ImageNet, a data set that contains 1.3 million training images of 1000 categories. We explore whether the DNN neurons (units in DNNs) possess image object representational statistics similar to monkey IT neurons, particularly when the network becomes deeper and the number of image categories becomes larger, using VGG19, a typical and widely used deep network of 19 layers in the computer vision field. Following Lehky, Kiani, Esteky, and Tanaka ( 2011 , 2014 ), where the response statistics of 674 IT neurons to 806 image stimuli are analyzed using three measures (kurtosis, Pareto tail index, and intrinsic dimensionality), we investigate the three issues in this letter using the same three measures: (1) the similarities and differences of the neural response statistics between VGG19 and primate IT cortex, (2) the variation trends of the response statistics of VGG19 neurons at different layers from low to high, and (3) the variation trends of the response statistics of VGG19 neurons when the numbers of stimuli and neurons increase. We find that the response statistics on both single-neuron selectivity and population sparseness of VGG19 neurons are fundamentally different from those of IT neurons in most cases; by increasing the number of neurons in different layers and the number of stimuli, the response statistics of neurons at different layers from low to high do not substantially change; and the estimated intrinsic dimensionality values at the low convolutional layers of VGG19 are considerably larger than the value of approximately 100 reported for IT neurons in Lehky et al. ( 2014 ), whereas those at the high fully connected layers are close to or lower than 100. To the best of our knowledge, this work is the first attempt to analyze the response statistics of DNN neurons with respect to primate IT neurons in image object representation.
Diffusional flux of CO2 through snow: Spatial and temporal variability among alpine-subalpine sites
Richard A. Sommerfeld; William J. Massman; Robert C. Musselman
1996-01-01
Three alpine and three subalpine sites were monitored for up to 4 years to acquire data on the temporal and spatial variability of CO2 flux through snowpacks. We conclude that the snow formed a passive cap which controlled the concentration of CO2 at the snow-soil interface, while the flux of CO2 into the atmosphere was controlled by CO2 production in the soil....
Plasma Assisted Combustion: Flame Regimes and Kinetic Studies
2015-01-05
Kinetic model Fuel: Dimethyl ether Oxidizer= (1-x)O2 + xO3, x=0 - 0.1, p=1 atm Ozone chemistry & Dimethyl ether model ...diffusional cool flames • A heated counterflow burner integrated with vaporization system1 • n-heptane/nitrogen vs. oxygen/ ozone • Ozone generator...micro-DBD) produces 2- 5 % of ozone in oxygen stream, depending on oxygen flow rate • Speciation profiles by using a micro-probe sampling with a
2012-07-01
regulate microfluidic flow rates within the TTB, including flow channel height variation and incorporation of valves (see Figure 2 and Supplemental...cartridge. As an alternative to individual channel TURN valve -adjusted flow regulators, we investigated use of pre-fabricated microfluidic flow resistance...Small Parts, Inc. and B) Microfluidic manifolds with built-in TURN valves . Supplemental Figure S3. Simplified 2D and 3D diffusional model
Defining Soil Materials for 3-D Models of the Near Surface: Preliminary Findings
2012-03-01
platykurtic . The corresponding box plot and 95 percent confidence intervals for mean and median are below histogram. .......................... 22...ERDC/GSL TR-12-9 20 platykurtic (Table 3). A higher kurtosis means more of the variance1 in a dataset is the result of infrequent extreme...Descriptive term > 1.0 Excessively peaked (leptokurtic) 1.0 Normally peaked (mesokurtic) < 1.0 Deficiently peaked ( platykurtic ) 4.2.3 Applications of
1977-01-01
balanced at the mean, with the central part steeper ( platykurtic : broad mode or truncated tails) -r flatter (leptokurtic: peaked mode or extended...and NUPUR, have negative kurtosis (they are platykurtic , with truncated tails and/or broad modes relative to their standard deviations) FERRO, on the...the other areas, and its gradients are platykurtic but almost unskewed. Hence the square root of sine transformation (Fig,15) and the log tangent
Control of water uptake by rice ( Oryza sativa L.): role of the outer part of the root.
Ranathunge, Kosala; Steudle, Ernst; Lafitte, Renee
2003-06-01
A new pressure-perfusion technique was used to measure hydraulic and osmotic properties of the outer part of roots (OPR) of 30-day-old rice plants (lowland cultivar: IR64, and upland cultivar: Azucena). The OPR comprised rhizodermis, exodermis, sclerenchyma and one cortical cell layer. The technique involved perfusion of aerenchyma of segments from two different root zones (20-50 mm and 50-100 mm from the tip) at precise rates using aerated nutrient solution. The hydraulic conductivity of the OPR (Lp(OPR)=1.2x10(-6) m s(-1) MPa(-1)) was larger by a factor of 30 than the overall hydraulic conductivity (Lp(r)=4x10(-8) m s(-1) MPa(-1)) as measured by pressure chamber and root pressure probe. Low reflection coefficients were obtained for mannitol and NaCl for the OPR (sigma(sOPR)=0.14 and 0.09, respectively). The diffusional water permeability ( P(dOPR)) estimated from isobaric flow of heavy water was smaller by three orders of magnitude than the hydraulic conductivity (Lp(OPR)/ P(fOPR)). Although detailed root anatomy showed well-defined Casparian bands and suberin lamellae in the exodermis, the findings strongly indicate a predominantly apoplastic water flow in the OPR. The Lp(OPR) of heat-killed root segments increased by a factor of only 2, which is in line with the conclusion of a dominating apoplastic water flow. The hydraulic resistance of the OPR was not limiting the passage of water across the root cylinder. Estimations of the hydraulic properties of aerenchyma suggested that the endodermis was rate-limiting the water flow, although the aerenchyma may contribute to the overall resistance. The resistance of the aerenchyma was relatively low, because mono-layered cortical septa crossing the aerenchyma ('spokes') short-circuited the air space between the stele and the OPR. Spokes form hydraulic bridges that act like wicks. Low diffusional water permeabilities of the OPR suggest that radial oxygen losses from aerenchyma to medium are also low. It is concluded that in rice roots, water uptake and oxygen retention are optimized in such a way that hydraulic water flow can be kept high in the presence of a low efflux of oxygen which is diffusional in nature.
Benga, Gheorghe; Chapman, Bogdan E; Matei, Horea; Cox, Guy C; Romeo, Tony; Mironescu, Eugen; Kuchel, Philip W
2010-03-08
As part of a programme of comparative measurements of Pd (diffusional water permeability) the RBCs (red blood cells) from dingo (Canis familiaris dingo) and greyhound dog (Canis familiaris) were studied. The morphologies of the dingo and greyhound RBCs [examined by light and SEM (scanning electron microscopy)] were found to be very similar, with regard to aspect ratio and size; the mean diameters were estimated to be the same (approximately 7.2 microm) for both dingo and greyhound RBCs. The water diffusional permeability was monitored by using an Mn2+-doping 1H NMR technique at 400 MHz. The Pd (cm/s) values of dingo and greyhound RBCs were similar: 6.5 x 10(-3) at 25 degrees C, 7.5 x 10(-3) at 30 degrees C, 10 x 10(-3) at 37 degrees C and 11.5 x 10(-3) at 42 degrees C. The inhibitory effect of a mercury-containing SH (sulfhydryl)-modifying reagent PCMBS (p-chloromercuribenzene sulfonate) was investigated. The maximal inhibition of dingo and greyhound RBCs was reached in 15-30 min at 37 degrees C with 2 mmol/l PCMBS. The values of maximal inhibition were in the range 72-74% when measured at 25 degrees C and 30 degrees C, and approximately 66% at 37 degrees C. The lowest value of Pd (corresponding to the basal permeability to water) was approximately 2-3 x 10(-3) cm/s in the temperature range 25-37 degrees C. The Ea,d (activation energy of water diffusion) was 25 kJ/mol for dingo RBC and 23 kJ/mol for greyhound RBCs. After incubation with PCMBS, the values of Ea,d increased, reaching 46-48 kJ/mol in the condition of maximal inhibition of water exchange. The electrophoretograms of membrane polypeptides of the dingo and greyhound RBCs were compared and seen to be very similar. We postulate that the RBC parameters reported in the present study are characteristic of all canine species and, in particular in the two cases presented here, these parameters have not been changed by the peculiar Australian habitat over the millennia (as in the case of the dingo) or over shorter time periods, decades or centuries (as in the case of the domestic greyhound).
NASA Astrophysics Data System (ADS)
Tomas, A.; Menendez, M.; Mendez, F. J.; Coco, G.; Losada, I. J.
2012-04-01
In the last decades, freak or rogue waves have become an important topic in engineering and science. Forecasting the occurrence probability of freak waves is a challenge for oceanographers, engineers, physicists and statisticians. There are several mechanisms responsible for the formation of freak waves, and different theoretical formulations (primarily based on numerical models with simplifying assumption) have been proposed to predict the occurrence probability of freak wave in a sea state as a function of N (number of individual waves) and kurtosis (k). On the other hand, different attempts to parameterize k as a function of spectral parameters such as the Benjamin-Feir Index (BFI) and the directional spreading (Mori et al., 2011) have been proposed. The objective of this work is twofold: (1) develop a statistical model to describe the uncertainty of maxima individual wave height, Hmax, considering N and k as covariates; (2) obtain a predictive formulation to estimate k as a function of aggregated sea state spectral parameters. For both purposes, we use free surface measurements (more than 300,000 20-minutes sea states) from the Spanish deep water buoy network (Puertos del Estado, Spanish Ministry of Public Works). Non-stationary extreme value models are nowadays widely used to analyze the time-dependent or directional-dependent behavior of extreme values of geophysical variables such as significant wave height (Izaguirre et al., 2010). In this work, a Generalized Extreme Value (GEV) statistical model for the dimensionless maximum wave height (x=Hmax/Hs) in every sea state is used to assess the probability of freak waves. We allow the location, scale and shape parameters of the GEV distribution to vary as a function of k and N. The kurtosis-dependency is parameterized using third-order polynomials and the model is fitted using standard log-likelihood theory, obtaining a very good behavior to predict the occurrence probability of freak waves (x>2). Regarding the second objective of this work, we apply different algorithms using three spectral parameters (wave steepness, directional dispersion, frequential dispersion) as predictors, to estimate the probability density function of the kurtosis for a given sea state. ACKNOWLEDGMENTS The authors thank to Puertos del Estado (Spanish Ministry of Public Works) for providing the free surface measurement database.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paul, J; Gore, E; Li, X
Purpose: Tumor treatment response may potentially be assessed during radiation therapy (RT) by analyzing changes in CT-textures. We investigated the different early RT-responses between small cell (SCLC) and non-small cell lung cancer (NSCLC) as assessed by CT-texture. Methods: Daily diagnostic-quality CT acquired during routine CT-guided RT using a CT-on-Rails for 13-NSCLC and 5-SCLC patients were analyzed. These patient had ages ranging from 45–78 and 38–63 years, respectively, for NSCLC and SCLC groups, and tumor-stages ranging from T2-T4, and were treated with either RT or chemotherapy and RT with 45–66Gy/ 20–34 fractions. Gross-tumor volume (GTV) contour was generated on each dailymore » CT by populating GTV contour from simulation to daily CTs with manual editing if necessary. CT-texture parameters, such as Hounsfield Unit (HU) histogram, mean HU, skewness, kurtosis, entropy, and short-run high-gray level emphasis (SRHGLE), were calculated in GTV from each daily CT-set using an in house software tool. Difference in changes of these texture parameters during RT between NSCLC and SCLC was analyzed and compared with GTV volume changes. Results: Radiation-induced changes in CT-texture were different between SCLC and NSCLC. Average changes from first to the last fractions for NSCLC and SCLC in GTV were 28±10(12–44) and 30±15(11–47) HU (mean HU reduction), 12.7% and 18.3% (entropy), 50% and 55% (SRHGLE), 19% and 22% (kurtosis), and 5.2% and 22% (skewness), respectively. Good correlation in kurtosis changes and GTV was seen (R{sup 2}=0.8923) for SCLC, but not for NSCLC (R{sup 2}=0.4748). SCLC had better correlations between GTV volume reduction and entropy (SCLC R{sup 2}=0.847; NSCLC R{sup 2}=0.6485), skewness (SCLC R{sup 2}=0.935; NSCLC R{sup 2}=0.7666), or SRHGLE (SCLC R{sup 2}=0.9619; NSCLC R{sup 2}=0.787). Conclusion: NSCLC and SCLC exhibited different early RT-responses as assessed by CT-texture changes during RT-delivery. The observed larger changes in various CT-texture parameters for SCLC indicate that SCLC may respond to RT more rapid than NSCLC.« less
Kurtosis based weighted sparse model with convex optimization technique for bearing fault diagnosis
NASA Astrophysics Data System (ADS)
Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yan, Ruqiang
2016-12-01
The bearing failure, generating harmful vibrations, is one of the most frequent reasons for machine breakdowns. Thus, performing bearing fault diagnosis is an essential procedure to improve the reliability of the mechanical system and reduce its operating expenses. Most of the previous studies focused on rolling bearing fault diagnosis could be categorized into two main families, kurtosis-based filter method and wavelet-based shrinkage method. Although tremendous progresses have been made, their effectiveness suffers from three potential drawbacks: firstly, fault information is often decomposed into proximal frequency bands and results in impulsive feature frequency band splitting (IFFBS) phenomenon, which significantly degrades the performance of capturing the optimal information band; secondly, noise energy spreads throughout all frequency bins and contaminates fault information in the information band, especially under the heavy noisy circumstance; thirdly, wavelet coefficients are shrunk equally to satisfy the sparsity constraints and most of the feature information energy are thus eliminated unreasonably. Therefore, exploiting two pieces of prior information (i.e., one is that the coefficient sequences of fault information in the wavelet basis is sparse, and the other is that the kurtosis of the envelope spectrum could evaluate accurately the information capacity of rolling bearing faults), a novel weighted sparse model and its corresponding framework for bearing fault diagnosis is proposed in this paper, coined KurWSD. KurWSD formulates the prior information into weighted sparse regularization terms and then obtains a nonsmooth convex optimization problem. The alternating direction method of multipliers (ADMM) is sequentially employed to solve this problem and the fault information is extracted through the estimated wavelet coefficients. Compared with state-of-the-art methods, KurWSD overcomes the three drawbacks and utilizes the advantages of both family tools. KurWSD has three main advantages: firstly, all the characteristic information scattered in proximal sub-bands is gathered through synthesizing those impulsive dominant sub-band signals and thus eliminates the dilemma of the IFFBS phenomenon. Secondly, the noises in the focused sub-bands could be alleviated efficiently through shrinking or removing the dense wavelet coefficients of Gaussian noise. Lastly, wavelet coefficients with faulty information are reliably detected and preserved through manipulating wavelet coefficients discriminatively based on the contribution to the impulsive components. Moreover, the reliability and effectiveness of the KurWSD are demonstrated through simulated and experimental signals.
The Kramers-Kronig relations for usual and anomalous Poisson-Nernst-Planck models.
Evangelista, Luiz Roberto; Lenzi, Ervin Kaminski; Barbero, Giovanni
2013-11-20
The consistency of the frequency response predicted by a class of electrochemical impedance expressions is analytically checked by invoking the Kramers-Kronig (KK) relations. These expressions are obtained in the context of Poisson-Nernst-Planck usual or anomalous diffusional models that satisfy Poisson's equation in a finite length situation. The theoretical results, besides being successful in interpreting experimental data, are also shown to obey the KK relations when these relations are modified accordingly.
Garzon, Fernando H.; Brosha, Eric L.
1997-01-01
A potentiometric oxygen sensor is formed having a logarithmic response to a differential oxygen concentration while operating as a Nernstian-type sensor. Very thin films of mixed conducting oxide materials form electrode services while permitting diffusional oxygen access to the interface between the zirconia electrolyte and the electrode. Diffusion of oxygen through the mixed oxide is not rate-limiting. Metal electrodes are not used so that morphological changes in the electrode structure do not occur during extended operation at elevated temperatures.
Garzon, F.H.; Brosha, E.L.
1997-12-09
A potentiometric oxygen sensor is formed having a logarithmic response to a differential oxygen concentration while operating as a Nernstian-type sensor. Very thin films of mixed conducting oxide materials form electrode services while permitting diffusional oxygen access to the interface between the zirconia electrolyte and the electrode. Diffusion of oxygen through the mixed oxide is not rate-limiting. Metal electrodes are not used so that morphological changes in the electrode structure do not occur during extended operation at elevated temperatures. 6 figs.
Optimal startup control of a jacketed tubular reactor.
NASA Technical Reports Server (NTRS)
Hahn, D. R.; Fan, L. T.; Hwang, C. L.
1971-01-01
The optimal startup policy of a jacketed tubular reactor, in which a first-order, reversible, exothermic reaction takes place, is presented. A distributed maximum principle is presented for determining weak necessary conditions for optimality of a diffusional distributed parameter system. A numerical technique is developed for practical implementation of the distributed maximum principle. This involves the sequential solution of the state and adjoint equations, in conjunction with a functional gradient technique for iteratively improving the control function.
Membrane Bioreactor With Pressure Cycle
NASA Technical Reports Server (NTRS)
Efthymiou, George S.; Shuler, Michael L.
1991-01-01
Improved class of multilayer membrane bioreactors uses convention forced by differences in pressure to overcome some of diffusional limitations of prior bioreactors. In reactor of new class, flow of nutrient solution reduces adverse gradients of concentration, keeps cells supplied with fresh nutrient, and sweeps away products faster than diffusion alone. As result, overall yield and rate of reaction increased. Pressures in sweeping gas and nutrient alternated to force nutrient liquid into and out of biocatalyst layer through hyrophilic membrane.
The Effect of Welding Process on the Microstructure of HY-130 Steel Weldments
1988-12-01
low -carbon, high-strength, low - alloy (HSLA) steels (C below 0.07 per- cent), the weld metal changed from coarse polygonal ferrite to...17. Ricks. R. A., Barritte, G. S., and Howell, P. R., "The Influence of Second Phase Particles on Diffusional Phase Transformations in Steels ... phase , austenite, may transform to mar- tensite on rapid cooling. The martensite has the exact same composi- tion as the austenite (up to two
Chou, Howard A; Zavitz, Daniel H; Ovadia, Marc
2003-01-01
To study in vivo modification of the SAM equivalent circuit when a highly ordered SAM is used as a bioelectrode, dodecanethiolate SAM-Au intramuscular electrodes were studied in living rat heart in a challenging in situ perfused rat model by impedance spectroscopy, cyclic voltammetry, and neutron activation analysis (NAA). The SAM layer experienced disintegration in vivo biological system, as NAA detected the presence of Au atoms that had leached into the surrounding living tissue. Therefore, the underlying Au surface became exposed during biological implant. Study by impedance spectroscopy, however, revealed perfect capacitive behavior for the SAM, similar to in vitro behavior. Electrodes showed a pure capacitive Nyquist plot with 86.1-89.4 degrees near-vertical line segments as the equivalent circuit locus, as for a parallel plate capacitor. Impedance magnitude varied linearly with 1/omega excluding diffusionally limited ionic charge transport. There was no diffusional conductive element Z(W infinity ) or spatially confined Warburg impedance Z(D). The effect of in vivo exposure of a highly ordered SAM is a 'sealing over' effect of new defects by the binding of proteinaceous or lipid species in the biological milieu, a fact of significance for SAM electrodes used either as pacemaker electrodes or as a platform for in vivo biosensors.
Pieprzyk, S.; Heyes, D. M.; Brańka, A. C.
2016-01-01
Solute transport and intermixing in microfluidic devices is strongly dependent on diffusional processes. Brownian Dynamics simulations of pressure-driven flow of model microgel particles in microchannels have been carried out to explore these processes and the factors that influence them. The effects of a pH-field that induces a spatial dependence of particle size and consequently the self-diffusion coefficient and system thermodynamic state were focused on. Simulations were carried out in 1D to represent some of the cross flow dependencies, and in 2D and 3D to include the effects of flow and particle concentration, with typical stripe-like diffusion coefficient spatial variations. In 1D, the mean square displacement and particle displacement probability distribution function agreed well with an analytically solvable model consisting of infinitely repulsive walls and a discontinuous pH-profile in the middle of the channel. Skew category Brownian motion and non-Gaussian dynamics were observed, which follows from correlations of step lengths in the system, and can be considered to be an example of so-called “diffusing diffusivity.” In Poiseuille flow simulations, the particles accumulated in regions of larger diffusivity and the largest particle concentration throughput was found when this region was in the middle of the channel. The trends in the calculated cross-channel diffusional behavior were found to be very similar in 2D and 3D. PMID:27795750
Haggie, Peter M; Verkman, A S
2002-10-25
It has been proposed that enzymes in many metabolic pathways, including the tricarboxylic acid cycle in the mitochondrial matrix, are physically associated to facilitate substrate channeling and overcome diffusive barriers. We have used fluorescence recovery after photobleaching to measure the diffusional mobilities of chimeras consisting of green fluorescent protein (GFP) fused to the C terminus of four tricarboxylic acid cycle enzymes: malate dehydrogenase, citrate synthase, isocitrate dehydrogenase, and succinyl-CoA synthetase. The GFP-enzyme chimeras were localized selectively in the mitochondrial matrix in transfected Chinese hamster ovary (CHO) and COS7 cells. Laser photobleaching using a 0.7-microm diameter spot demonstrated restricted diffusion of the GFP-enzyme chimeras. Interestingly, all four chimeras had similar diffusional characteristics, approximately 45% of each chimera was mobile and had a diffusion coefficient of 4 x 10(-8) cm(2)/s. In contrast, unconjugated GFP in the mitochondrial matrix (targeted using COX8 leader sequence) diffused freely (nearly 100% mobility) with a greater diffusion coefficient of 20 x 10(-8) cm(2)/s. The mobility of the GFP-enzyme chimeras was insensitive to substrate source, ATP depletion, or inhibition of the adenine nucleotide translocase. These results indicate similar mobility characteristics of unrelated tricarboxylic acid cycle enzymes having different sizes and physical properties, providing biophysical evidence for a diffusible multienzyme complex in the mitochondrial matrix.
Interdiffusion in Ternary Magnesium Solid Solutions of Aluminum and Zinc
Kammerer, Catherine; Kulkarni, Nagraj S; Warmack, Robert J Bruce; ...
2016-01-11
Al and Zn are two of the most common alloying elements in commercial Mg alloys, which can improve the physical properties through solid solution strengthening and precipitation hardening. Diffusion plays a key role in the kinetics of these and other microstructural design relevant to Mg-alloy development. However, there is a lack of multicomponent diffusion data available for Mg alloys. Through solid-to-solid diffusion couples, diffusional interactions of Al and Zn in ternary Mg solid-solution at 400° and 450 °C were examined by an extension of the Boltzmann-Matano analysis based on Onsager s formalism. Concentration profiles of Mg-Al-Zn ternary alloys were determinedmore » by electron probe microanalysis, and analyzed to determine the ternary interdiffusion coefficients as a function of composition. Zn was determined to interdiffuse the fastest, followed by Mg and Al. Appreciable diffusional interactions among Mg, Al, and Zn were observed by variations in sign and magnitude of cross interdiffusion coefficients. In particular, Zn was found to significantly influence the interdiffusion of Mg and Al significantly: the and ternary cross interdiffusion coefficients were both negative, and large in magnitude, in comparison to and , respectively. Al and Mg were observed influence the interdiffusion of Mg and Al, respectively, with positive and interdiffusion coefficients, but their influence on the Zn interdiffusion was negligible.« less
Peinetti, Ana Sol; Gilardoni, Rodrigo S; Mizrahi, Martín; Requejo, Felix G; González, Graciela A; Battaglini, Fernando
2016-06-07
Nanoelectrode arrays have introduced a complete new battery of devices with fascinating electrocatalytic, sensitivity, and selectivity properties. To understand and predict the electrochemical response of these arrays, a theoretical framework is needed. Cyclic voltammetry is a well-fitted experimental technique to understand the undergoing diffusion and kinetics processes. Previous works describing microelectrode arrays have exploited the interelectrode distance to simulate its behavior as the summation of individual electrodes. This approach becomes limited when the size of the electrodes decreases to the nanometer scale due to their strong radial effect with the consequent overlapping of the diffusional fields. In this work, we present a computational model able to simulate the electrochemical behavior of arrays working either as the summation of individual electrodes or being affected by the overlapping of the diffusional fields without previous considerations. Our computational model relays in dividing a regular electrode array in cells. In each of them, there is a central electrode surrounded by neighbor electrodes; these neighbor electrodes are transformed in a ring maintaining the same active electrode area than the summation of the closest neighbor electrodes. Using this axial neighbor symmetry approximation, the problem acquires a cylindrical symmetry, being applicable to any diffusion pattern. The model is validated against micro- and nanoelectrode arrays showing its ability to predict their behavior and therefore to be used as a designing tool.
Benga, Gheorghe; Chapman, Bogdan E; Cox, Guy C; Kuchel, Philip W
2010-07-01
As part of a programme of comparative measurements of Pd (diffusional water permeability) the RBCs (red blood cells) from an aquatic monotreme, platypus (Ornithorhynchus anatinus), and an aquatic reptile, saltwater crocodile (Crocodylus porosus) were studied. The mean diameter of platypus RBCs was estimated by light microscopy and found to be approximately 6.3 microm. Pd was measured by using an Mn2+-doping 1H NMR (nuclear magnetic resonance) technique. The Pd (cm/s) values were relatively low: approximately 2.1 x 10(-3) at 25 degrees C, 2.5 x 10(-3) at 30 degrees C, 3.4 x 10(-3) at 37 degrees C and 4.5 at 42 degrees C for the platypus RBCs and approximately 2.8 x 10(-3) at 25 degrees C, 3.2 x 10(-3) at 30 degrees C, 4.5 x 10(-3) at 37 degrees C and 5.7 x 10(-3) at 42 degrees C for the crocodile RBCs. In parallel with the low water permeability, the Ea,d (activation energy of water diffusion) was relatively high, approximately 35 kJ/mol. These results suggest that "conventional" WCPs (water channel proteins), or AQPs (aquaporins), are probably absent from the plasma membranes of RBCs from both the platypus and the saltwater crocodile.
Inferring shallow groundwater flow in saprolite and fractured rock using environmental tracers
Cook, P.G.; Solomon, D.K.; Sanford, W.E.; Busenberg, E.; Plummer, Niel; Poreda, R.J.
1996-01-01
The Ridge and Valley Province of eastern Tennessee is characterized by (1) substantial topographic relief, (2) folded and highly fractured rocks of various lithologies that have low primary permeability and porosity, and (3) a shallow residuum of medium permeability and high total porosity. Conceptual models of shallow groundwater flow and solute transport in this system have been developed but are difficult to evaluate using physical characterization or short‐term tracer methods due to extreme spatial variability in hydraulic properties. In this paper we describe how chlorofluorocarbon 12, 3H, and 3He were used to infer groundwater flow and solute transport in saprolite and fractured rock near Oak Ridge, Tennessee. In the shallow residuum, fracture spacings are <0.05 m, suggesting that concentrations of these tracers in fractures and in the matrix have time to diffusionally equilibrate. The relatively smooth nature of tracer concentrations with depth in the residuum is consistent with this model and quantitatively suggests recharge fluxes of 0.2 to 0.4 m yr−1. In contrast, groundwater flow within the unweathered rock appears to be controlled by fractures with spacings of the order of 2 to 5 m, and diffusional equilibration of fractures and matrix has not occurred. For this reason, vertical fluid fluxes in the unweathered rock cannot be estimated from the tracer data.
Diffusional encounter of barnase and barstar.
Spaar, Alexander; Dammer, Christian; Gabdoulline, Razif R; Wade, Rebecca C; Helms, Volkhard
2006-03-15
We present an analysis of trajectories from Brownian dynamics simulations of diffusional protein-protein encounter for the well-studied system of barnase and barstar. This analysis reveals details about the optimal association pathways, the regions of the encounter complex, possible differences of the pathways for dissociation and association, the coupling of translational and rotation motion, and the effect of mutations on the trajectories. We found that a small free-energy barrier divides the energetically most favorable region into a region of the encounter complex above the barnase binding interface and a region around a second energy minimum near the RNA binding loop. When entering the region of the encounter complex from the region near the RNA binding loop, barstar has to change its orientation to increase the electrostatic attraction between the proteins. By concentrating the analysis on the successful binding trajectories, we found that the region of the second minimum is not essential for the binding of barstar to barnase. Nevertheless, this region may be helpful to steer barstar into the region of the encounter complex. When applying the same analysis to several barnase mutants, we found that single mutations may drastically change the free-energy landscape and may significantly alter the population of the two minima. Therefore, certain protein-protein pairs may require careful adaptation of the positions of encounter and transition states when interpreting mutation effects on kinetic rates of association and/or dissociation.
Reinhold, Caroline; Alsharif, Shaza S.; Addley, Helen; Arceneau, Jocelyne; Molinari, Nicolas; Guiu, Boris; Sala, Evis
2015-01-01
Purpose To investigate magnetic resonance (MR) volumetry of endometrial tumors and its association with deep myometrial invasion, tumor grade, and lymphovascular invasion and to assess the value of apparent diffusion coefficient (ADC) histographic analysis of the whole tumor volume for prediction of tumor grade and lymphovascular invasion. Materials and Methods The institutional review board approved this retrospective study; patient consent was not required. Between May 2010 and May 2012, 70 women (mean age, 64 years; range, 24–91 years) with endometrial cancer underwent preoperative MR imaging, including axial oblique and sagittal T2-weighted, dynamic contrast material–enhanced, and diffusion-weighted imaging. Volumetry of the tumor and uterus was performed during the six sequences, with manual tracing of each section, and the tumor volume ratio (TVR) was calculated. ADC histograms were generated from pixel ADCs from the whole tumor volume. The threshold of TVR associated with myometrial invasion was assessed by using receiver operating characteristic curves. An independent sample Mann Whitney U test was used to compare differences in ADCs, skewness, and kurtosis between tumor grade and the presence of lymphovascular invasion. Results No significant difference in tumor volume and TVR was found among the six MR imaging sequences (P = .95 and .86, respectively). A TVR greater than or equal to 25% allowed prediction of deep myometrial invasion with sensitivity of 100% and specificity of 93% (area under the curve, 0.96; 95% confidence interval: 0.86, 0.99) at axial oblique diffusion-weighted imaging. A TVR of greater than or equal to 25% was associated with grade 3 tumors (P = .0007) and with lymphovascular invasion (P < .0001). There was no significant difference in the ADCs between grades 1 and 2 tumors (P > .05). The minimum, 10th, 25th, 50th, 75th, and 90th percentile ADCs were significantly lower in grade 3 tumors than in grades 1 and 2 tumors (P < .02). Conclusion The combination of whole tumor volume and ADC can be used for prediction of tumor grade, lymphovascular invasion, and depth of myometrial invasion. © RSNA, 2015 PMID:25928157
Color variations within glacial till, east-central North Dakota--A preliminary investigation
Kelly, T.E.; Baker, Claud H.
1966-01-01
Color variations (orange zones within buff-colored till) in drift in east-central North Dakota are believed to represent two tills of separate origin. Mean size, standard deviation, and number and type of pebbles show greater difference between the two tills than do skewness, kurtosis, and partial chemical analyses. Probably blocks of older till were moved by the last glacier crossing the area and were redeposited in a matrix of younger till.
Features of the Paired Soliton Interactions Within the Framework of the Gardner Equation
NASA Astrophysics Data System (ADS)
Shurgalina, E. G.
2018-02-01
We study the dynamics of the two-soliton interaction within the framework of a completely integrable model, namely, the Gardner equation with negative cubic nonlinearity, which admits the existence of a limiting soliton. The features of the soliton interaction with participation of a thick soliton are demonstrated. Special attention is paid to the nonlinear-interaction influence on the wave-field moments, which determine the skewness and the kurtosis in the theory of turbulence.
Mass and Momentum Turbulent Transport Experiments with Confined Coaxial Jets
NASA Technical Reports Server (NTRS)
Johnson, B. V.; Bennett, J. C.
1981-01-01
Downstream mixing of coaxial jets discharging in an expanded duct was studied to obtain data for the evaluation and improvement of turbulent transport models currently used in a variety of computational procedures throughout the propulsion community for combustor flow modeling. Flow visualization studies showed four major shear regions occurring; a wake region immediately downstream of the inlet jet inlet duct; a shear region further downstream between the inner and annular jets; a recirculation zone; and a reattachment zone. A combination of turbulent momentum transport rate and two velocity component data were obtained from simultaneous measurements with a two color laser velocimeter (LV) system. Axial, radial and azimuthal velocities and turbulent momentum transport rate measurements in the r-z and r-theta planes were used to determine the mean value, second central moment (or rms fluctuation from mean), skewness and kurtosis for each data set probability density function (p.d.f.). A combination of turbulent mass transport rate, concentration and velocity data were obtained system. Velocity and mass transport in all three directions as well as concentration distributions were used to obtain the mean, second central moments, skewness and kurtosis for each p.d.f. These LV/LIF measurements also exposed the existence of a large region of countergradient turbulent axial mass transport in the region where the annular jet fluid was accelerating the inner jet fluid.
Diffusion of active chiral particles
NASA Astrophysics Data System (ADS)
Sevilla, Francisco J.
2016-12-01
The diffusion of chiral active Brownian particles in three-dimensional space is studied analytically, by consideration of the corresponding Fokker-Planck equation for the probability density of finding a particle at position x and moving along the direction v ̂ at time t , and numerically, by the use of Langevin dynamics simulations. The analysis is focused on the marginal probability density of finding a particle at a given location and at a given time (independently of its direction of motion), which is found from an infinite hierarchy of differential-recurrence relations for the coefficients that appear in the multipole expansion of the probability distribution, which contains the whole kinematic information. This approach allows the explicit calculation of the time dependence of the mean-squared displacement and the time dependence of the kurtosis of the marginal probability distribution, quantities from which the effective diffusion coefficient and the "shape" of the positions distribution are examined. Oscillations between two characteristic values were found in the time evolution of the kurtosis, namely, between the value that corresponds to a Gaussian and the one that corresponds to a distribution of spherical shell shape. In the case of an ensemble of particles, each one rotating around a uniformly distributed random axis, evidence is found of the so-called effect "anomalous, yet Brownian, diffusion," for which particles follow a non-Gaussian distribution for the positions yet the mean-squared displacement is a linear function of time.
The retest distribution of the visual field summary index mean deviation is close to normal.
Anderson, Andrew J; Cheng, Allan C Y; Lau, Samantha; Le-Pham, Anne; Liu, Victor; Rahman, Farahnaz
2016-09-01
When modelling optimum strategies for how best to determine visual field progression in glaucoma, it is commonly assumed that the summary index mean deviation (MD) is normally distributed on repeated testing. Here we tested whether this assumption is correct. We obtained 42 reliable 24-2 Humphrey Field Analyzer SITA standard visual fields from one eye of each of five healthy young observers, with the first two fields excluded from analysis. Previous work has shown that although MD variability is higher in glaucoma, the shape of the MD distribution is similar to that found in normal visual fields. A Shapiro-Wilks test determined any deviation from normality. Kurtosis values for the distributions were also calculated. Data from each observer passed the Shapiro-Wilks normality test. Bootstrapped 95% confidence intervals for kurtosis encompassed the value for a normal distribution in four of five observers. When examined with quantile-quantile plots, distributions were close to normal and showed no consistent deviations across observers. The retest distribution of MD is not significantly different from normal in healthy observers, and so is likely also normally distributed - or nearly so - in those with glaucoma. Our results increase our confidence in the results of influential modelling studies where a normal distribution for MD was assumed. © 2016 The Authors Ophthalmic & Physiological Optics © 2016 The College of Optometrists.
Coarse-grained molecular dynamics simulation of water diffusion in the presence of carbon nanotubes.
Lado Touriño, Isabel; Naranjo, Arisbel Cerpa; Negri, Viviana; Cerdán, Sebastián; Ballesteros, Paloma
2015-11-01
Computational modeling of the translational diffusion of water molecules in anisotropic environments entails vital relevance to understand correctly the information contained in the magnetic resonance images weighted in diffusion (DWI) and of the diffusion tensor images (DTI). In the present work we investigated the validity, strengths and weaknesses of a coarse-grained (CG) model based on the MARTINI force field to simulate water diffusion in a medium containing carbon nanotubes (CNTs) as models of anisotropic water diffusion behavior. We show that water diffusion outside the nanotubes follows Ficḱs law, while water diffusion inside the nanotubes is not described by a Ficḱs behavior. We report on the influence on water diffusion of various parameters such as length and concentration of CNTs, comparing the CG results with those obtained from the more accurate classic force field calculation, like the all-atom approach. Calculated water diffusion coefficients decreased in the presence of nanotubes in a concentration dependent manner. We also observed smaller water diffusion coefficients for longer CNTs. Using the CG methodology we were able to demonstrate anisotropic diffusion of water inside the nanotube scaffold, but we could not prove anisotropy in the surrounding medium, suggesting that grouping several water molecules in a single diffusing unit may affect the diffusional anisotropy calculated. The methodologies investigated in this work represent a first step towards the study of more complex models, including anisotropic cohorts of CNTs or even neuronal axons, with reasonable savings in computation time. Copyright © 2015 Elsevier Inc. All rights reserved.
Holographic Gratings for Optical Processing
NASA Technical Reports Server (NTRS)
Kukhtarev, Nickolai
2002-01-01
Investigation of astronomical objects and tracking of man-made space objects lead to generation of huge amount of information for optical processing. Traditional big-size optical elements (such as optical telescopes) have a tendency for increasing aperture size in order to improve sensitivity. This tendency leads to increasing of weight and costs of optical systems and stimulate search for the new, more adequate technologies. One approach to meet these demands is based on developing of holographic optical elements using new polymeric materials. We have investigated possibility to use new material PQ-PMMA (phenantrenequinone-doped PMMA (Polymethyl Methacrylate)) for fabrication of highly selective optical filters and fast spatial-temporal light modulators. This material was originally developed in Russia and later was tested in CalTech as a candidate material for optical storage. Our theoretical investigation predicts the possibility of realization of fast spatial and temporal light modulation, using volume reflection-type spectral filter. We have developed also model of holographic-grating recording in PQ-PMMA material, based on diffusional amplification. This mechanism of recording allow to receive high diffraction efficiency during recording of reflection-type volume holographic grating (holographic mirror). We also investigated recording of dynamic gratings in the photorefractive crystals LiNbO3 (LN) for space-based spectroscopy and for adaptive correction of aberrations in the telescope's mirrors. We have shown, that specific 'photogalvanic' mechanism of holographic grating recording in LN allow to realize recording of blazed gratings for volume and surface gratings. Possible applications of dynamic gratings in LN for amplification of images, transmitted through an imaging fiber guide was also demonstrated.
Lu, Shan Shan; Kim, Sang Joon; Kim, Namkug; Kim, Ho Sung; Choi, Choong Gon; Lim, Young Min
2015-04-01
This study intended to investigate the usefulness of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating primary CNS lymphomas (PCNSLs), especially atypical PCNSLs, from tumefactive demyelinating lesions (TDLs). Forty-seven patients with PCNSLs and 18 with TDLs were enrolled in our study. Hyperintense lesions seen on T2-weighted images were defined as ROIs after ADC maps were registered to the corresponding T2-weighted image. ADC histograms were calculated from the ROIs containing the entire lesion on every section and on a voxel-by-voxel basis. The ADC histogram parameters were compared among all PCNSLs and TDLs as well as between the subgroup of atypical PCNSLs and TDLs. ROC curves were constructed to evaluate the diagnostic performance of the histogram parameters and to determine the optimum thresholds. The differences between the PCNSLs and TDLs were found in the minimum ADC values (ADCmin) and in the 5th and 10th percentiles (ADC5% and ADC10%) of the cumulative ADC histograms. However, no statistical significance was found in the mean ADC value or in the ADC value concerning the mode, kurtosis, and skewness. The ADCmin, ADC5%, and ADC10% were also lower in atypical PCNSLs than in TDLs. ADCmin was the best indicator for discriminating atypical PCNSLs from TDLs, with a threshold of 556×10(-6) mm2/s (sensitivity, 81.3 %; specificity, 88.9%). Histogram analysis of ADC maps may help to discriminate PCNSLs from TDLs and may be particularly useful in differentiating atypical PCNSLs from TDLs.
Diagnosis of response and non-response to dry eye treatment using infrared thermography images
NASA Astrophysics Data System (ADS)
Acharya, U. Rajendra; Tan, Jen Hong; Vidya, S.; Yeo, Sharon; Too, Cheah Loon; Lim, Wei Jie Eugene; Chua, Kuang Chua; Tong, Louis
2014-11-01
The dry eye treatment outcome depends on the assessment of clinical relevance of the treatment effect. The potential approach to assess the clinical relevance of the treatment is to identify the symptoms responders and non-responders to the given treatments using the responder analysis. In our work, we have performed the responder analysis to assess the clinical relevance effect of the dry eye treatments namely, hot towel, EyeGiene®, and Blephasteam® twice daily and 12 min session of Lipiflow®. Thermography is performed at week 0 (baseline), at weeks 4 and 12 after treatment. The clinical parameters such as, change in the clinical irritations scores, tear break up time (TBUT), corneal staining and Schirmer's symptoms tests values are used to obtain the responders and non-responders groups. We have obtained the infrared thermography images of dry eye symptoms responders and non-responders to the three types of warming treatments. The energy, kurtosis, skewness, mean, standard deviation, and various entropies namely Shannon, Renyi and Kapoor are extracted from responders and non-responders thermograms. The extracted features are ranked based on t-values. These ranked features are fed to the various classifiers to get the highest performance using minimum features. We have used decision tree (DT), K nearest neighbour (KNN), Naves Bayesian (NB) and support vector machine (SVM) to classify the features into responder and non-responder classes. We have obtained an average accuracy of 99.88%, sensitivity of 99.7% and specificity of 100% using KNN classifier using ten-fold cross validation.