Effects of calcium leaching on diffusion properties of hardened and altered cement pastes

NASA Astrophysics Data System (ADS)

Kurumisawa, Kiyofumi; Haga, Kazuko; Hayashi, Daisuke; Owada, Hitoshi

2017-06-01

It is very important to predict alterations in the concrete used for fabricating disposal containers for radioactive waste. Therefore, it is necessary to understand the alteration of cementitious materials caused by calcium leaching when they are in contact with ground water in the long term. To evaluate the long-term transport characteristics of cementitious materials, the microstructural behavior of these materials should be considered. However, many predictive models of transport characteristics focus on the pore structure, while only few such models consider both, the spatial distribution of calcium silicate hydrate (C-S-H), portlandite, and the pore spaces. This study focused on the spatial distribution of these cement phases. The auto-correlation function of each phase of cementitious materials was calculated from two-dimensional backscattered electron imaging, and the three-dimensional spatial image of the cementitious material was produced using these auto-correlation functions. An attempt was made to estimate the diffusion coefficient of chloride from the three-dimensional spatial image. The estimated diffusion coefficient of the altered sample from the three-dimensional spatial image was found to be comparable to the measured value. This demonstrated that it is possible to predict the diffusion coefficient of the altered cement paste by using the proposed model.

Uncertainty Analysis of Downscaled CMIP5 Precipitation Data for Louisiana, USA

NASA Astrophysics Data System (ADS)

Sumi, S. J.; Tamanna, M.; Chivoiu, B.; Habib, E. H.

2014-12-01

The downscaled CMIP3 and CMIP5 Climate and Hydrology Projections dataset contains fine spatial resolution translations of climate projections over the contiguous United States developed using two downscaling techniques (monthly Bias Correction Spatial Disaggregation (BCSD) and daily Bias Correction Constructed Analogs (BCCA)). The objective of this study is to assess the uncertainty of the CMIP5 downscaled general circulation models (GCM). We performed an analysis of the daily, monthly, seasonal and annual variability of precipitation downloaded from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website for the state of Louisiana, USA at 0.125° x 0.125° resolution. A data set of daily gridded observations of precipitation of a rectangular boundary covering Louisiana is used to assess the validity of 21 downscaled GCMs for the 1950-1999 period. The following statistics are computed using the CMIP5 observed dataset with respect to the 21 models: the correlation coefficient, the bias, the normalized bias, the mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). A measure of variability simulated by each model is computed as the ratio of its standard deviation, in both space and time, to the corresponding standard deviation of the observation. The correlation and MAPE statistics are also computed for each of the nine climate divisions of Louisiana. Some of the patterns that we observed are: 1) Average annual precipitation rate shows similar spatial distribution for all the models within a range of 3.27 to 4.75 mm/day from Northwest to Southeast. 2) Standard deviation of summer (JJA) precipitation (mm/day) for the models maintains lower value than the observation whereas they have similar spatial patterns and range of values in winter (NDJ). 3) Correlation coefficients of annual precipitation of models against observation have a range of -0.48 to 0.36 with variable spatial distribution by model. 4) Most of the models show negative correlation coefficients in summer and positive in winter. 5) MAE shows similar spatial distribution for all the models within a range of 5.20 to 7.43 mm/day from Northwest to Southeast of Louisiana. 6) Highest values of correlation coefficients are found at seasonal scale within a range of 0.36 to 0.46.

Short-term and working memory impairments in aphasia.

PubMed

Potagas, Constantin; Kasselimis, Dimitrios; Evdokimidis, Ioannis

2011-08-01

The aim of the present study is to investigate short-term memory and working memory deficits in aphasics in relation to the severity of their language impairment. Fifty-eight aphasic patients participated in this study. Based on language assessment, an aphasia score was calculated for each patient. Memory was assessed in two modalities, verbal and spatial. Mean scores for all memory tasks were lower than normal. Aphasia score was significantly correlated with performance on all memory tasks. Correlation coefficients for short-term memory and working memory were approximately of the same magnitude. According to our findings, severity of aphasia is related with both verbal and spatial memory deficits. Moreover, while aphasia score correlated with lower scores in both short-term memory and working memory tasks, the lack of substantial difference between corresponding correlation coefficients suggests a possible primary deficit in information retention rather than impairment in working memory. Copyright © 2011 Elsevier Ltd. All rights reserved.

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

Correlation of morphological and molecular parameters for colon cancer

NASA Astrophysics Data System (ADS)

Yuan, Shuai; Roney, Celeste A.; Li, Qian; Jiang, James; Cable, Alex; Summers, Ronald M.; Chen, Yu

2010-02-01

Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. There is great interest in studying the relationship among microstructures and molecular processes of colorectal cancer during its progression at early stages. In this study, we use our multi-modality optical system that could obtain co-registered optical coherence tomography (OCT) and fluorescence molecular imaging (FMI) images simultaneously to study CRC. The overexpressed carbohydrate α-L-fucose on the surfaces of polyps facilitates the bond of adenomatous polyps with UEA-1 and is used as biomarker. Tissue scattering coefficient derived from OCT axial scan is used as quantitative value of structural information. Both structural images from OCT and molecular images show spatial heterogeneity of tumors. Correlations between those values are analyzed and demonstrate that scattering coefficients are positively correlated with FMI signals in conjugated. In UEA-1 conjugated samples (8 polyps and 8 control regions), the correlation coefficient is ranged from 0.45 to 0.99. These findings indicate that the microstructure of polyps is changed gradually during cancer progression and the change is well correlated with certain molecular process. Our study demonstrated that multi-parametric imaging is able to simultaneously detect morphology and molecular information and it can enable spatially and temporally correlated studies of structure-function relationships during tumor progression.

A spatially adaptive total variation regularization method for electrical resistance tomography

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2015-12-01

The total variation (TV) regularization method has been used to solve the ill-posed inverse problem of electrical resistance tomography (ERT), owing to its good ability to preserve edges. However, the quality of the reconstructed images, especially in the flat region, is often degraded by noise. To optimize the regularization term and the regularization factor according to the spatial feature and to improve the resolution of reconstructed images, a spatially adaptive total variation (SATV) regularization method is proposed. A kind of effective spatial feature indicator named difference curvature is used to identify which region is a flat or edge region. According to different spatial features, the SATV regularization method can automatically adjust both the regularization term and regularization factor. At edge regions, the regularization term is approximate to the TV functional to preserve the edges; in flat regions, it is approximate to the first-order Tikhonov (FOT) functional to make the solution stable. Meanwhile, the adaptive regularization factor determined by the spatial feature is used to constrain the regularization strength of the SATV regularization method for different regions. Besides, a numerical scheme is adopted for the implementation of the second derivatives of difference curvature to improve the numerical stability. Several reconstruction image metrics are used to quantitatively evaluate the performance of the reconstructed results. Both simulation and experimental results indicate that, compared with the TV (mean relative error 0.288, mean correlation coefficient 0.627) and FOT (mean relative error 0.295, mean correlation coefficient 0.638) regularization methods, the proposed SATV (mean relative error 0.259, mean correlation coefficient 0.738) regularization method can endure a relatively high level of noise and improve the resolution of reconstructed images.

Channel correlation and BER performance analysis of coherent optical communication systems with receive diversity over moderate-to-strong non-Kolmogorov turbulence.

PubMed

Fu, Yulong; Ma, Jing; Tan, Liying; Yu, Siyuan; Lu, Gaoyuan

2018-04-10

In this paper, new expressions of the channel-correlation coefficient and its components (the large- and small-scale channel-correlation coefficients) for a plane wave are derived for a horizontal link in moderate-to-strong non-Kolmogorov turbulence using a generalized effective atmospheric spectrum which includes finite-turbulence inner and outer scales and high-wave-number "bump". The closed-form expression of the average bit error rate (BER) of the coherent free-space optical communication system is derived using the derived channel-correlation coefficients and an α-μ distribution to approximate the sum of the square root of arbitrarily correlated Gamma-Gamma random variables. Analytical results are provided to investigate the channel correlation and evaluate the average BER performance. The validity of the proposed approximation is illustrated by Monte Carlo simulations. This work will help with further investigation of the fading correlation in spatial diversity systems.

The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors

PubMed Central

Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Wild, Damian; Lardinois, Didier

2017-01-01

The minimum apparent diffusion coefficient (ADCmin) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUVmax) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADCmin- and SUVmax-voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance (D) between ADCmin- and SUVmax-voxels was 14.0 mm (average of two readers). Spatial mismatch (D > 12 mm) between ADCmin and SUVmax was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUVmax and ADCmin was seen, while a moderate negative linear relationship (r = −0.5) between SUVmax and ADCmin was observed in tumors with a spatial match (D ≤ 12 mm). In conclusion, spatial mismatch between ADCmin and SUVmax is found in a considerable percentage of patients. The spatial connection of the two parameters SUVmax and ADCmin has a crucial influence on their numeric correlation. PMID:29391862

The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors.

PubMed

Sauter, Alexander W; Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Klarhöfer, Markus; Wild, Damian; Lardinois, Didier; Bremerich, Jens; Sommer, Gregor

2017-01-01

The minimum apparent diffusion coefficient (ADC min ) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUV max ) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADC min - and SUV max -voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance ( D ) between ADC min - and SUV max -voxels was 14.0 mm (average of two readers). Spatial mismatch ( D > 12 mm) between ADC min and SUV max was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUV max and ADC min was seen, while a moderate negative linear relationship ( r = -0.5) between SUV max and ADC min was observed in tumors with a spatial match ( D ≤ 12 mm). In conclusion, spatial mismatch between ADC min and SUV max is found in a considerable percentage of patients. The spatial connection of the two parameters SUV max and ADC min has a crucial influence on their numeric correlation.

Relationship between sugarcane rust severity and soil properties in louisiana.

PubMed

Johnson, Richard M; Grisham, Michael P; Richard, Edward P

2007-06-01

ABSTRACT The extent of spatial and temporal variability of sugarcane rust (Puccinia melanocephala) infestation was related to variation in soil properties in five commercial fields of sugarcane (interspecific hybrids of Saccharum spp., cv. LCP 85-384) in southern Louisiana. Sugarcane fields were grid-soil sampled at several intensities and rust ratings were collected at each point over 6 to 7 weeks. Soil properties exhibited significant variability (coefficients of variation = 9 to 70.1%) and were spatially correlated in 39 of 40 cases with a range of spatial correlation varying from 39 to 201 m. Rust ratings were spatially correlated in 32 of 33 cases, with a range varying from 29 to 241 m. Rust ratings were correlated with several soil properties, most notably soil phosphorus (r = 0.40 to 0.81) and soil sulfur (r = 0.36 to 0.68). Multiple linear regression analysis resulted in coefficients of determination that ranged from 0.22 to 0.73, and discriminant analysis further improved the overall predictive ability of rust models. Finally, contour plots of soil properties and rust levels clearly suggested a link between these two parameters. These combined data suggest that sugarcane growers that apply fertilizer in excess of plant requirements will increase the incidence and severity of rust infestations in their fields.

Correlation analysis of a ground-water level monitoring network, Miami-Dade County, Florida

USGS Publications Warehouse

Prinos, Scott T.

2005-01-01

The U.S. Geological Survey cooperative ground-water monitoring program in Miami-Dade County, Florida, expanded from 4 to 98 continuously recording water-level monitoring wells during the 1939-2001 period. Network design was based on area specific assessments; however, no countywide statistical assessments of network coverage had been performed for the purpose of assessing network redundancy. To aid in the assessment of network redundancy, correlation analyses were performed using S-PLUS 2000 statistical analysis software for daily maximum water-level data from 98 monitoring wells for the November 1, 1973, to October 31, 2000 period. Because of the complexities of the hydrologic, water-supply, and water-management systems in Miami-Dade County and the changes that have occurred to these systems through time, spatial and temporal variations in the degree of correlation had to be considered. To assess temporal variation in correlation, water-level data from each well were subdivided by year and by wet and dry seasons. For each well, year, and season, correlation analyses were performed on the data from those wells that had available data. For selected wells, the resulting correlation coefficients from each year and season were plotted with respect to time. To assess spatial variation in correlation, the coefficients determined from the correlation analysis were averaged. These average wet- and dry-season correlation coefficients were plotted spatially using geographic information system software. Wells with water-level data that correlated with a coefficient of 0.95 or greater were almost always located in relatively close proximity to each other. Five areas were identified where the water-level data from wells within the area remained correlated with that of other wells in the area during the wet and dry seasons. These areas are located in or near the C-1 and C-102 basins (2 wells), in or near the C-6 and C-7 basins (2 wells), near the Florida Keys Aqueduct Authority Well Field (2 wells), near the Hialeah-Miami Springs Well Field (6 wells), and near the West Well Field (21 wells). Data from the remaining 65 wells (most of the wells in the network) generally were not correlated with those of other wells during both the wet and dry seasons with an average coefficient of 0.95 or greater for the comparison. Because many of the wells near the West Well Field and some near the Hialeah-Miami Springs Well Field had not been in operation for very long (most having been installed in 1994), the averaged correlation coefficients for these wells were often determined using only a few seasons of data. For the few instances where water-level data were found to be well correlated on average for a lengthy period of record, short-term declines in correlation were often identified. In general, it would be beneficial to compare data for longer periods of record than currently available.

[Spatial patterns and influence factors of specialization in tea cultivation based on geographically weighted regression model: A case study of Anxi County of Fujian Province, China].

PubMed

Shui, Wei; DU, Yong; Chen, Yi Ping; Jian, Xiao Mei; Fan, Bing Xiong

2017-04-18

Anxi County, specializing in tea cultivation, was taken as a case in this research. Pearson correlation analysis, ordinary least squares model (OLS) and geographically weighted regression model (GWR) were used to select four primary influence factors of specialization in tea cultivation (i.e., the average elevation, net income per capita, proportion of agricultural population, and the distance from roads) by analyzing the specialization degree of each town of Anxi County. Meanwhile, the spatial patterns of specialization in tea cultivation of Anxi County were evaluated. The results indicated that specialization in tea cultivation of Anxi County showed an obvious spatial auto-correlation, and a spatial pattern with "low-middle-high" circle structure, which was similar to Von Thünen's circle structure model, appeared from the county town to its surrounding region. Meanwhile, GWR (0.624) had a better fitting degree than OLS (0.595), and GWR could reasonably expound the spatial data. Contrary to the agricultural location theory of Von Thünen's model, which indicated that distance from market was a determination factor, the specialization degree of tea cultivation in Anxi was mainly decided by natural conditions of mountain area, instead of the social factors. Specialization degree of tea cultivation was positively correlated with the average elevation, net income per capita and the proportion of agricultural population, while a negative correlation was found between the distance from roads and specialization degree of tea cultivation. Coefficients of regression between the specialization degree of tea cultivation and two factors (i.e., the average elevation and net income per capita) showed a spatial pattern of higher level in the north direction and lower level in the south direction. On the contrary, the regression coefficients for the proportion of agricultural population increased from south to north of Anxi County. Furthermore, regression coefficient for the distance from roads showed a spatial pattern of higher level in the northeast direction and lower level in the southwest direction of Anxi County.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

Depth-time interpolation of feature trends extracted from mobile microelectrode data with kernel functions.

PubMed

Wong, Stephen; Hargreaves, Eric L; Baltuch, Gordon H; Jaggi, Jurg L; Danish, Shabbar F

2012-01-01

Microelectrode recording (MER) is necessary for precision localization of target structures such as the subthalamic nucleus during deep brain stimulation (DBS) surgery. Attempts to automate this process have produced quantitative temporal trends (feature activity vs. time) extracted from mobile MER data. Our goal was to evaluate computational methods of generating spatial profiles (feature activity vs. depth) from temporal trends that would decouple automated MER localization from the clinical procedure and enhance functional localization in DBS surgery. We evaluated two methods of interpolation (standard vs. kernel) that generated spatial profiles from temporal trends. We compared interpolated spatial profiles to true spatial profiles that were calculated with depth windows, using correlation coefficient analysis. Excellent approximation of true spatial profiles is achieved by interpolation. Kernel-interpolated spatial profiles produced superior correlation coefficient values at optimal kernel widths (r = 0.932-0.940) compared to standard interpolation (r = 0.891). The choice of kernel function and kernel width resulted in trade-offs in smoothing and resolution. Interpolation of feature activity to create spatial profiles from temporal trends is accurate and can standardize and facilitate MER functional localization of subcortical structures. The methods are computationally efficient, enhancing localization without imposing additional constraints on the MER clinical procedure during DBS surgery. Copyright © 2012 S. Karger AG, Basel.

Contribution of industrial density and socioeconomic status to the spatial distribution of thyroid cancer risk in Hangzhou, China.

PubMed

Fei, Xufeng; Lou, Zhaohan; Christakos, George; Liu, Qingmin; Ren, Yanjun; Wu, Jiaping

2018-02-01

The thyroid cancer (TC) incidence in China has increased dramatically during the last three decades. Typical in this respect is the case of Hangzhou city (China), where 7147 new TC cases were diagnosed during the period 2008-2012. Hence, the assessment of the TC incidence risk increase due to environmental exposure is an important public health matter. Correlation analysis, Analysis of Variance (ANOVA) and Poisson regression were first used to evaluate the statistical association between TC and key risk factors (industrial density and socioeconomic status). Then, the Bayesian maximum entropy (BME) theory and the integrative disease predictability (IDP) criterion were combined to quantitatively assess both the overall and the spatially distributed strength of the "exposure-disease" association. Overall, higher socioeconomic status was positively correlated with higher TC risk (Pearson correlation coefficient=0.687, P<0.01). Compared to people of low socioeconomic status, people of median and high socioeconomic status showed higher TC risk: the Relative Risk (RR) and associated 95% confidence interval (CI) were found to be, respectively, RR=2.29 with 95% CI=1.99 to 2.63, and RR=3.67 with 95% CI=3.22 to 4.19. The "industrial density-TC incidence" correlation, however, was non-significant. Spatially, the "socioeconomic status-TC" association measured by the corresponding IDP coefficient was significant throughout the study area: the mean IDP value was -0.12 and the spatial IDP values were consistently negative at the township level. It was found that stronger associations were distributed among residents mainly on a stripe of land from northeast to southwest (consisting mainly of sub-district areas). The "industrial density-TC" association measured by its IDP coefficient was spatially non-consistent. Socioeconomic status is an important indicator of TC risk factor in Hangzhou (China) whose effect varies across space. Hence, socioeconomic status shows the highest TC risk effect in sub-district areas. Copyright © 2017. Published by Elsevier B.V.

Spatial and temporal variation of correlation between the Arctic total ozone and atmospheric temperature

NASA Astrophysics Data System (ADS)

Huang, Fuxiang; Ren, suling; Han, Shuangshuang; Zheng, xiangdong; Deng, xuejiao

2017-04-01

Daily total ozone and atmospheric temperature profile data in 2015 from the AIRS are used to investigate the spatial and temporal variation of the correlation between the Arctic atmospheric ozone and temperature. In the study, 11 lays atmospheric temperature profiles from the troposphere to the stratosphere are investigated. These layer heights are 20, 50, 70, 100, 200, 250, 300, 400, 500, 600 and 700 hPa respectively. The results show that a significant seasonal split exists in the correlation between the Arctic ozone and atmospheric temperature. Figure 1 shows the spatial and temporal variation of the coefficient between the atmospheric ozone and temperature at 50hPa. It can be seen from the figure that an obvious spatiotemporal difference exists in the correlation between the Arctic total ozone and atmospheric temperature in the lower stratosphere. First, the seasonal difference is very remarkable, which is shown as a significant positive correlation in most regions during winter and summer, while no correlation in the majority of regions occurs during spring and autumn, with a weak positive or negative correlation in a small number regions. Second, the spatial differences are also very obvious. The summer maximum correlation coefficient occurs in the Barents Sea and other locations at 0.8 and above, while the winter maximum occurs in the Baffin Bay area at 0.6 to 0.8. However, in a small number of regions, such as the land to the west of the Bering Strait in winter and the Arctic Ocean core area in summer, the correlation coefficients were unable to pass the significance test to show no correlation. At the same time, in spring and autumn, a positive correlation only occurs over a few low-latitude land areas, while over other Arctic areas, weak negative correlation exists. The differences in horizontal position are clearly related to the land-sea distribution, underlying surface characteristics, glacial melting, and other factors. In the troposphere, the ozone and temperature have a strong negative correlation in spring and autumn, while presenting a weak negative correlation or no correlation in winter and summer. Figure 2 shows the spatial and temporal variation of the correlation coefficient between the atmospheric ozone and temperature at 500hPa. From figure 2, it can be seen that in the Arctic troposphere, the atmospheric ozone and tropospheric temperature mainly have a negative correlation. In winter and summer, a weak negative correlation is shown overall, but more than a third of the regions show no correlation. In spring, the negative correlation is the strongest between the ozone and temperature. Especially in Greenland - Queen Elizabeth Islands and southern New Siberian Islands, the correlation is the highest, with a correlation coefficient of -0.9 and above, followed by a negative correlation in autumn. Except for a small number of low-latitude scattered regions with weak correlation, the correlation coefficients of most regions are ranged between -0.5 and -0.7. At 300 hPa near the tropopause, the horizontal distribution and seasonal change of the correlation between the Arctic total ozone and atmospheric temperature are as shown in Fig. 3.At the height near the Arctic tropopause, the atmospheric ozone mainly has no correlation to temperature, especially in winter and summer, when no correlation exists in the majority of regions, while weak positive or negative correlation occurs in a small number of areas. In the majority of regions during spring, a weak negative correlation is shown, while no correlation appears in Western Greenland - Queen Elizabeth Islands. In autumn, most regions show no correlation, while weak negative correlation is presented in Eastern Greenland, Norwegian Sea - Barents Sea, and other locations. From figure 1-3, we can see a significant difference exists from the common law of positive correlation in the lower stratosphere and negative correlation in the troposphere at mid-low latitudes. The Arctic atmospheric ozone has a relation with temperature, showing significant spatial and temporal variation characteristics. In the stratosphere, winter and summer atmospheric temperatures mainly have a positive correlation to ozone. The summer maximum occurs in the Barents Sea to achieve 0.8 and above, while the winter maximum is 0.6 to 0.8 in the Baffin Bay area. In the troposphere, the autumn and spring atmospheric temperatures mainly have a negative correlation to the ozone. The spring correlation coefficient in Greenland to the Queen Elizabeth Islands reaches up to -0.9 and above, while the autumn value is -0.5 to -0.7. At about 300 hPa, the tropopause value is reduced to 0, and further decreased in the troposphere, to show a strong negative correlation. Based on the comprehensive analysis of various influence factors, the possible action mechanism of the spatiotemporal variation pattern of the correlation between the Arctic atmospheric ozone and temperature is discussed based on the seasonal differences of various influence factors. The spatial and temporal variation characteristics of the correlation between the Arctic atmospheric ozone and temperature are determined by the seasonal variation of various influencing factors of the Arctic atmospheric ozone and temperature. These factors include the atmospheric heating effect from the ozone matching with the Arctic sunshine conditions, the influence of dynamic delivery on the ozone and heat, the impact of underlying-surface glacial melting on atmospheric radiation and heat budget, and so on. At different heights in each season, the different effects from all kinds of factors on the ozone and temperature determine the spatiotemporal variation of the correlation between the ozone and temperature.

Negative Correlation between the Diffusion Coefficient and Transcriptional Activity of the Glucocorticoid Receptor.

PubMed

Mikuni, Shintaro; Yamamoto, Johtaro; Horio, Takashi; Kinjo, Masataka

2017-08-25

The glucocorticoid receptor (GR) is a transcription factor, which interacts with DNA and other cofactors to regulate gene transcription. Binding to other partners in the cell nucleus alters the diffusion properties of GR. Raster image correlation spectroscopy (RICS) was applied to quantitatively characterize the diffusion properties of EGFP labeled human GR (EGFP-hGR) and its mutants in the cell nucleus. RICS is an image correlation technique that evaluates the spatial distribution of the diffusion coefficient as a diffusion map. Interestingly, we observed that the averaged diffusion coefficient of EGFP-hGR strongly and negatively correlated with its transcriptional activities in comparison to that of EGFP-hGR wild type and mutants with various transcriptional activities. This result suggests that the decreasing of the diffusion coefficient of hGR was reflected in the high-affinity binding to DNA. Moreover, the hyper-phosphorylation of hGR can enhance the transcriptional activity by reduction of the interaction between the hGR and the nuclear corepressors.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

Spatial distribution of SPAD value and determination of the suitable leaf for N diagnosis in cucumber

NASA Astrophysics Data System (ADS)

Hu, Jing; Li, Chenxiao; Wen, Yifang; Gao, Xinhao; Shi, Feifei; Han, Luhua

2018-01-01

To determine the best leaf position for nitrogen diagnosis in cucumber with SPAD meter, greenhouse experiments were carried out to study spatial distribution of SPAD value of different position of the 3rd fully expanded cucumber leaf in the effect of different nitrogen levels, and the correlations between SPAD values and nitrogen concentration of chlorophyll. The results show that there is remarkable different SPAD value in different positions of the 3rd fully expanded leaf in the flowering and fruiting stage. Comparing the coefficients of SPAD value variation, we find that the coefficient of variation of leaf edge was significantly higher than the edge of the main vein, and the coefficient of variation of triangular area of leaf tip is significantly higher than any other leaf area. There is a significant correlation between SPAD values and leaf nitrogen content. Preliminary study shows that triangular area of leaf tip from the 20% leaf tip to leaf edge is the best position for nitrogen diagnosis.

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Spatial and temporal variation of sources contributing to quasi-ultrafine particulate matter PM0.36 in Augsburg, Germany.

PubMed

Li, Fengxia; Schnelle-Kreis, Jürgen; Cyrys, Josef; Wolf, Kathrin; Karg, Erwin; Gu, Jianwei; Orasche, Jürgen; Abbaszade, Gülcin; Peters, Annette; Zimmermann, Ralf

2018-08-01

to study the sources contributing to quasi-ultrafine particle (UFP) organic carbon and the spatial temporal variability of the sources. 24h quasi-UFP (particulate matter <0.36μm in this study) was sampled at a reference site continuously and at one of 5 other sites (T1, T2, T3, T4 and B1) in parallel in Augsburg, Germany from April 11th, 2014 to February 22nd, 2015, attempting to conduct 2-week campaigns at each site in 3 different seasons. Positive matrix factorization (PMF) was applied to measured organic tracers for source apportionment analyses. Pearson correlation coefficient r and coefficient of divergence (COD) were calculated to investigate spatial temporal variation of source contributions. 5 sources were identified comprising biomass burning (BB), traffic emissions (Traffic), biogenic secondary organic aerosol (bioSOA), isoprene originated secondary organic aerosol (isoSOA) and biomass burning related secondary organic aerosol (bbSOA). In general, good temporal correlation and uniform distribution within the study area are found for bioSOA and bbSOA, probably resulting from regional formation/transport. Lower temporal correlation and spatial heterogeneity of isoSOA were found at the city background site with local influence from green space and less traffic impact. BB demonstrated very good temporal correlation, but higher contributions at sites influenced by local residential heating emissions were observed. Traffic showed the least seasonality and lower correlation over time among the sources. However, it demonstrated low spatial heterogeneity of absolute contribution, and only a few days of elevated contribution was found at T3 when wind came directly from the street nearby. temporal correlation and spatial variability of sources contributing to the organic fraction of quasi-UFP vary among sites and source types and show source-specific characteristics. Therefore, caution should be taken when using one monitor site measurement to assess human exposure in health effect studies of quasi-UFP. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial accessibility of primary health care in China: A case study in Sichuan Province.

PubMed

Wang, Xiuli; Yang, Huazhen; Duan, Zhanqi; Pan, Jay

2018-05-10

Access to primary health care is considered a fundamental right and an important facilitator of overall population health. Township health centers (THCs) and Community health centers (CHCs) serve as central hubs of China's primary health care system and have been emphasized during recent health care reforms. Accessibility of these hubs is poorly understood and a better understanding of the current situation is essential for proper decision making. This study assesses spatial access to health care provided by primary health care institutions (THCs/CHCs) in Sichuan Province as a microcosm in China. The Nearest-Neighbor method, Enhanced Two-Step Floating Catchment Area (E2SFCA) method, and Gini Coefficient are utilized to represent travel impedance, spatial accessibility, and disparity of primary health care resources (hospital beds, doctors, and health professionals). Accessibilities and Gini Coefficients are correlated with social development indexes (GDP, ethnicity, etc.) to identify influencing factors. Spatial access to primary health care is better in southeastern Sichuan compared to northwestern Sichuan in terms of shorter travel time, higher spatial accessibility, and lower inequity. Social development indexes all showed significant correlation with county averaged spatial accessibilities/Gini Coefficients, with population density ranking top. The disparity of access to primary health care is also apparent between ethnic minority and non-minority regions. To improve spatial access to primary health care and narrow the inequity, more township health centers staffed by qualified health professionals are recommended for northwestern Sichuan. Improved road networks will also help. Among areas with insufficient primary health care, the specific counties where demographics are dominated by older people and children due to widespread rural-urban migration of the workforce, and by ethnic minorities, should be especially emphasized in future planning. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spaced antenna diversity in temperate latitude meteor burst systems operating near 40 MHz - Variation of signal cross-correlation coefficients with antenna separation

NASA Astrophysics Data System (ADS)

Cannon, Paul S.; Shukla, Anil K.; Lester, Mark

1993-04-01

We have studied 37-MHz signals received over an 800-km temperate latitude path using 400-W continuous wave transmissions. Signals collected during a 9-day period in February 1990 on two antennas at separations of 5, 10, and 20 lambda were analyzed. Three signal categories were identified (overdense, underdense, and not known (NK)) and cross-correlation coefficients between the signals received by the two antennas were calculated for each signal category. No spatial variation, and in particular no decrease, in average cross-correlation coefficient was observed for underdense or NK signals as the antenna spacing was increased from 5 to 20 lambda. At each antenna separation the cross-correlation coefficients of these two categories were strongly dependent on time. Overdense signals, however, showed no cross-correlation time dependency at 5 and 10 lambda, but there was a strong time dependency at 20 lambda. Recommendations are made in regard to the optimum antenna spacing for a meteor burst communication system using spaced antenna diversity.

Estimated Accuracy of Three Common Trajectory Statistical Methods

NASA Technical Reports Server (NTRS)

Kabashnikov, Vitaliy P.; Chaikovsky, Anatoli P.; Kucsera, Tom L.; Metelskaya, Natalia S.

2011-01-01

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Spatial correlation and irradiance statistics in a multiple-beam terrestrial free-space optical communication link.

PubMed

Anguita, Jaime A; Neifeld, Mark A; Vasic, Bane V

2007-09-10

By means of numerical simulations we analyze the statistical properties of the power fluctuations induced by the incoherent superposition of multiple transmitted laser beams in a terrestrial free-space optical communication link. The measured signals arising from different transmitted optical beams are found to be statistically correlated. This channel correlation increases with receiver aperture and propagation distance. We find a simple scaling rule for the spatial correlation coefficient in terms of the propagation distance and we are able to predict the scintillation reduction in previously reported experiments with good accuracy. We propose an approximation to the probability density function of the received power of a spatially correlated multiple-beam system in terms of the parameters of the single-channel gamma-gamma function. A bit-error-rate evaluation is also presented to demonstrate the improvement of a multibeam system over its single-beam counterpart.

Spatial-temporal characteristics of lightning flash size in a supercell storm

NASA Astrophysics Data System (ADS)

Zhang, Zhixiao; Zheng, Dong; Zhang, Yijun; Lu, Gaopeng

2017-11-01

The flash sizes of a supercell storm, in New Mexico on October 5, 2004, are studied using the observations from the New Mexico Lightning Mapping Array and the Albuquerque, New Mexico, Doppler radar (KABX). First, during the temporal evolution of the supercell, the mean flash size is anti-correlated with the flash rate, following a unary power function, with a correlation coefficient of - 0.87. In addition, the mean flash size is linearly correlated with the area of reflectivity > 30 dBZ at 5 km normalized by the flash rate, with a correlation coefficient of 0.88. Second, in the horizontal, flash size increases along the direction from the region near the convection zone to the adjacent forward anvil. The region of minimum flash size usually corresponds to the region of maximum flash initiation and extent density. The horizontal correspondence between the mean flash size and the flash extent density can also be fitted by a unary power function, and the correlation coefficient is > 0.5 in 50% of the radar volume scans. Furthermore, the quality of fit is positively correlated to the convective intensity. Third, in the vertical direction, the height of the maximum flash initiation density is close to the height of maximum flash extent density, but corresponds to the height where the mean flash size is relatively small. In the discussion, the distribution of the small and dense charge regions when and where convection is vigorous in the storm, is deduced to be responsible for the relationship that flash size is temporally and spatially anti-correlated with flash rate and density, and the convective intensity.

Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges

USGS Publications Warehouse

Lemeshewsky, George P.; Schowengerdt, Robert A.

2000-01-01

Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Dynamical behavior of the correlation between meteorological factors

NASA Astrophysics Data System (ADS)

You, Cheol-Hwan; Chang, Ki-Ho; Lee, Jun-Ho; Kim, Kyungsik

2017-12-01

We study the temporal and spatial variation characteristics of meteorological factors (temperature, humidity, and wind velocity) at a meteorological tower located on Bosung-gun of South Korea. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation from data of meteorological factors. The relationships between meteorological factors are identified and quantified by using DCCA coefficients. From our results, we ascertain that the DCCA coefficient between temperature and humidity at time lag m = 24 has the smallest value at the height of 10 m of the measuring tower. Particularly, the DCCA coefficient between temperature and wind speed at time lag m = 24 has the largest value at a height of 10 m of the measuring tower

Role of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in local dengue epidemics in Taiwan.

PubMed

Tsai, Pui-Jen; Teng, Hwa-Jen

2016-11-09

Aedes mosquitoes in Taiwan mainly comprise Aedes albopictus and Ae. aegypti. However, the species contributing to autochthonous dengue spread and the extent at which it occurs remain unclear. Thus, in this study, we spatially analyzed real data to determine spatial features related to local dengue incidence and mosquito density, particularly that of Ae. albopictus and Ae. aegypti. We used bivariate Moran's I statistic and geographically weighted regression (GWR) spatial methods to analyze the globally spatial dependence and locally regressed relationship between (1) imported dengue incidences and Breteau indices (BIs) of Ae. albopictus, (2) imported dengue incidences and BI of Ae. aegypti, (3) autochthonous dengue incidences and BI of Ae. albopictus, (4) autochthonous dengue incidences and BI of Ae. aegypti, (5) all dengue incidences and BI of Ae. albopictus, (6) all dengue incidences and BI of Ae. aegypti, (7) BI of Ae. albopictus and human population density, and (8) BI of Ae. aegypti and human population density in 348 townships in Taiwan. In the GWR models, regression coefficients of spatially regressed relationships between the incidence of autochthonous dengue and vector density of Ae. aegypti were significant and positive in most townships in Taiwan. However, Ae. albopictus had significant but negative regression coefficients in clusters of dengue epidemics. In the global bivariate Moran's index, spatial dependence between the incidence of autochthonous dengue and vector density of Ae. aegypti was significant and exhibited positive correlation in Taiwan (bivariate Moran's index = 0.51). However, Ae. albopictus exhibited positively significant but low correlation (bivariate Moran's index = 0.06). Similar results were observed in the two spatial methods between all dengue incidences and Aedes mosquitoes (Ae. aegypti and Ae. albopictus). The regression coefficients of spatially regressed relationships between imported dengue cases and Aedes mosquitoes (Ae. aegypti and Ae. albopictus) were significant in 348 townships in Taiwan. The results indicated that local Aedes mosquitoes do not contribute to the dengue incidence of imported cases. The density of Ae. aegypti positively correlated with the density of human population. By contrast, the density of Ae. albopictus negatively correlated with the density of human population in the areas of southern Taiwan. The results indicated that Ae. aegypti has more opportunities for human-mosquito contact in dengue endemic areas in southern Taiwan. Ae. aegypti, but not Ae. albopictus, and human population density in southern Taiwan are closely associated with an increased risk of autochthonous dengue incidence.

Spatial Imaging of Strongly Interacting Rydberg Atoms

NASA Astrophysics Data System (ADS)

Thaicharoen, Nithiwadee

The strong interactions between Rydberg excitations can result in spatial correlations between the excitations. The ability to control the interaction strength and the correlations between Rydberg atoms is applicable in future technological implementations of quantum computation. In this thesis, I investigates how both the character of the Rydberg-Rydberg interactions and the details of the excitation process affect the nature of the spatial correlations and the evolution of those correlations in time. I first describes the experimental apparatus and methods used to perform high-magnification Rydberg-atom imaging, as well as three experiments in which these methods play an important role. The obtained Rydberg-atom positions reveal the correlations in the many-body Rydberg-atom system and their time dependence with sub-micron spatial resolution. In the first experiment, atoms are excited to a Rydberg state that experiences a repulsive van der Waals interaction. The Rydberg excitations are prepared with a well-defined initial separation, and the effect of van der Waals forces is observed by tracking the interatomic distance between the Rydberg atoms. The atom trajectories and thereby the interaction coefficient C6 are extracted from the pair correlation functions of the Rydberg atom positions. In the second experiment, the Rydberg atoms are prepared in a highly dipolar state by using adiabatic state transformation. The atom-pair kinetics that follow from the strong dipole-dipole interactions are observed. The pair correlation results provide the first direct visualization of the electric-dipole interaction and clearly exhibit its anisotropic nature. In both the first and the second experiment, results of semi-classical simulations of the atom-pair trajectories agree well with the experimental data. In the analysis, I use energy conservation and measurements of the initial positions and the terminal velocities of the atom pairs to extract the C6 and C 3 interaction coefficients. The final experiment demonstrates the ability to enhance or suppress the degree of spatial correlation in a system of Rydberg excitations, using a rotary-echo excitation process in concert with particular excitation laser detunings. The work in this thesis demonstrates an ability to control long-range interactions between Rydberg atoms, which paves the way towards preparing and studying increasingly complex many-body systems.

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Treesearch

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

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.

Analysis of data from NASA B-57B gust gradient program

NASA Technical Reports Server (NTRS)

Frost, W.; Lin, M. C.; Chang, H. P.; Ringnes, E.

1985-01-01

Statistical analysis of the turbulence measured in flight 6 of the NASA B-57B over Denver, Colorado, from July 7 to July 23, 1982 included the calculations of average turbulence parameters, integral length scales, probability density functions, single point autocorrelation coefficients, two point autocorrelation coefficients, normalized autospectra, normalized two point autospectra, and two point cross sectra for gust velocities. The single point autocorrelation coefficients were compared with the theoretical model developed by von Karman. Theoretical analyses were developed which address the effects spanwise gust distributions, using two point spatial turbulence correlations.

Correlation time and diffusion coefficient imaging: application to a granular flow system.

PubMed

Caprihan, A; Seymour, J D

2000-05-01

A parametric method for spatially resolved measurements for velocity autocorrelation functions, R(u)(tau) = , expressed as a sum of exponentials, is presented. The method is applied to a granular flow system of 2-mm oil-filled spheres rotated in a half-filled horizontal cylinder, which is an Ornstein-Uhlenbeck process with velocity autocorrelation function R(u)(tau) = e(- ||tau ||/tau(c)), where tau(c) is the correlation time and D = tau(c) is the diffusion coefficient. The pulsed-field-gradient NMR method consists of applying three different gradient pulse sequences of varying motion sensitivity to distinguish the range of correlation times present for particle motion. Time-dependent apparent diffusion coefficients are measured for these three sequences and tau(c) and D are then calculated from the apparent diffusion coefficient images. For the cylinder rotation rate of 2.3 rad/s, the axial diffusion coefficient at the top center of the free surface was 5.5 x 10(-6) m(2)/s, the correlation time was 3 ms, and the velocity fluctuation or granular temperature was 1.8 x 10(-3) m(2)/s(2). This method is also applicable to study transport in systems involving turbulence and porous media flows. Copyright 2000 Academic Press.

Spatial and temporal stability of temperature in the first-level basins of China during 1951-2013

NASA Astrophysics Data System (ADS)

Cheng, Yuting; Li, Peng; Xu, Guoce; Li, Zhanbin; Cheng, Shengdong; Wang, Bin; Zhao, Binhua

2018-05-01

In recent years, global warming has attracted great attention around the world. Temperature change is not only involved in global climate change but also closely linked to economic development, the ecological environment, and agricultural production. In this study, based on temperature data recorded by 756 meteorological stations in China during 1951-2013, the spatial and temporal stability characteristics of annual temperature in China and its first-level basins were investigated using the rank correlation coefficient method, the relative difference method, rescaled range (R/S) analysis, and wavelet transforms. The results showed that during 1951-2013, the spatial variation of annual temperature belonged to moderate variability in the national level. Among the first-level basins, the largest variation coefficient was 114% in the Songhuajiang basin and the smallest variation coefficient was 10% in the Huaihe basin. During 1951-2013, the spatial distribution pattern of annual temperature presented extremely strong spatial and temporal stability characteristics in the national level. The variation range of Spearman's rank correlation coefficient was 0.97-0.99, and the spatial distribution pattern of annual temperature showed an increasing trend. In the national level, the Liaohe basin, the rivers in the southwestern region, the Haihe basin, the Yellow River basin, the Yangtze River basin, the Huaihe basin, the rivers in the southeastern region, and the Pearl River basin all had representative meteorological stations for annual temperature. In the Songhuajiang basin and the rivers in the northwestern region, there was no representative meteorological station. R/S analysis, the Mann-Kendall test, and the Morlet wavelet analysis of annual temperature showed that the best representative meteorological station could reflect the variation trend and the main periodic changes of annual temperature in the region. Therefore, strong temporal stability characteristics exist for annual temperature in China and its first-level basins. It was therefore feasible to estimate the annual average temperature by the annual temperature recorded by the representative meteorological station in the region. Moreover, it was of great significance to assess average temperature changes quickly and forecast future change tendencies in the region.

Spatial Variability and Distribution of the Metals in Surface Runoff in a Nonferrous Metal Mine

PubMed Central

Ren, Bozhi; Chen, Yangbo; Zhu, Guocheng; Wang, Zhenghua; Zheng, Xie

2016-01-01

The spatial variation and distribution features of the metals tested in the surface runoff in Xikuangshan Bao Daxing miming area were analyzed by combining statistical methods with a geographic information system (GIS). The results showed that the maximum concentrations of those five kinds of the metals (Sb, Zn, Cu, Pb, and Cd) in the surface runoff of the antimony mining area were lower than the standard value except the concentration of metal Ni. Their concentrations were 497.1, 2.0, 1.8, 22.2, and 22.1 times larger than the standard value, respectively. This metal pollution was mainly concentrated in local areas, which were seriously polluted. The variation coefficient of Sb, Zn, Cu, Ni, Pb, and Cd was between 0.4 to 0.6, wherein the Sb's spatial variability coefficient is 50.56%, indicating a strong variability. Variation coefficients of the rest of metals were less than 50%, suggesting a moderate variability. The spatial structure analysis showed that the squared correlation coefficient (R 2) of the models fitting for Sb, Zn, Cu, Ni, Pb, and Cd was between 0.721 and 0.976; the ratio of the nugget value (C 0) to the abutment value (C + C 0) was between 0.0767 and 0.559; the semivariogram of Sb, Zn, Ni, and Pb was in agreement with a spherical model, while semivariogram of Cu and Cd was in agreement with Gaussian model, and both had a strong spatial correlation. The trend and spatial distribution indicated that those pollution distributions resulting from Ni, Pb, and Cd are similar, mainly concentrated in both ends of north and south in eastern part. The main reasons for the pollution were attributed to the residents living, transportation, and industrial activities; the Sb distribution was concentrated mainly in the central part, of which the pollution was assigned to the mining and the industrial activity; the pollution distributions of Zn and Cu were similar, mainly concentrated in both ends of north and south as well as in west; the sources of the metals were widely distributed. PMID:27069713

Spatial EMG potential distribution pattern of vastus lateralis muscle during isometric knee extension in young and elderly men.

PubMed

Watanabe, Kohei; Kouzaki, Motoki; Merletti, Roberto; Fujibayashi, Mami; Moritani, Toshio

2012-02-01

The aim of the present study was to compare spatial electromyographic (EMG) potential distribution during force production between elderly and young individuals using multi-channel surface EMG (SEMG). Thirteen elderly (72-79years) and 13 young (21-27years) healthy male volunteers performed ramp submaximal contraction during isometric knee extension from 0% to 65% of maximal voluntary contraction. During contraction, multi-channel EMG was recorded from the vastus lateralis muscle. To evaluate alteration in heterogeneity and pattern in spatial EMG potential distribution, coefficient of variation (CoV), modified entropy and correlation coefficients with initial torque level were calculated from multi-channel SEMG at 5% force increment. Increase in CoV and decrease in modified entropy of RMS with increase of exerted torque were significantly smaller in elderly group (p<0.05) and correlation coefficients with initial torque level were significantly higher in elderly group than in young group at moderate torque levels (p<0.05). These data suggest that the increase of heterogeneity and the change in the activation pattern are smaller in elderly individuals than in young individuals. We speculated that multi-channel SEMG pattern in elderly individual reflects neuromuscular activation strategy regulated predominantly by clustering of similar type of muscle fibers in aged muscle. Copyright © 2011 Elsevier Ltd. All rights reserved.

Breast density estimation from high spectral and spatial resolution MRI

PubMed Central

Li, Hui; Weiss, William A.; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M.; Karczmar, Gregory S.; Giger, Maryellen L.

2016-01-01

Abstract. A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists’ breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 (p<0.0001) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 (p<0.0001) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 (p=0.0076) was observed between HiSS-based breast density estimations and radiologists’ BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy. PMID:28042590

On the relationship between thermal emissivity and the Normalized Difference Vegetation Index for natural surfaces

NASA Technical Reports Server (NTRS)

Van De Griend, A. A.; Owe, M.

1993-01-01

The spatial variation of both the thermal emissivity (8-14 microns) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-IR radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0.94. This empirical relationship is of potential use for energy balance studies using thermal IR remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

Correlation of 3D Shift and 3D Tilt of the Patella in Patients With Recurrent Dislocation of the Patella and Healthy Volunteers: An In Vivo Analysis Based on 3-Dimensional Computer Models.

PubMed

Yamada, Yuzo; Toritsuka, Yukiyoshi; Nakamura, Norimasa; Horibe, Shuji; Sugamoto, Kazuomi; Yoshikawa, Hideki; Shino, Konsei

2017-11-01

The concepts of lateral deviation and lateral inclination of the patella, characterized as shift and tilt, have been applied in combination to evaluate patellar malalignment in patients with patellar dislocation. It is not reasonable, however, to describe the 3-dimensional (3D) positional relation between the patella and the femur according to measurements made on 2-dimensional (2D) images. The current study sought to clarify the relation between lateral deviation and inclination of the patella in patients with recurrent dislocation of the patella (RDP) by redefining them via 3D computer models as 3D shift and 3D tilt. Descriptive laboratory study. Altogether, 60 knees from 56 patients with RDP and 15 knees from 10 healthy volunteers were evaluated. 3D shift and tilt of the patella were analyzed with 3D computer models created by magnetic resonance imaging scans obtained at 10° intervals of knee flexion (0°-50°). 3D shift was defined as the spatial distance between the patellar reference point and the midsagittal plane of the femur; it is expressed as a percentage of the interepicondylar width. 3D tilt was defined as the spatial angle between the patellar reference plane and the transepicondylar axis. Correlations between the 2 parameters were assessed with the Pearson correlation coefficient. The patients' mean Pearson correlation coefficient was 0.895 ± 0.186 (range, -0.073 to 0.997; median, 0.965). In all, 56 knees (93%) had coefficients >0.7 (strong correlation); 1 knee (2%), >0.4 (moderate correlation); 2 knees (3%), >0.2 (weak correlation); and 1 knee (2%), <0.2 (no correlation). The mean correlation coefficient of the healthy volunteers was 0.645 ± 0.448 (range, -0.445 to 0.982; median, 0.834). A statistically significant difference was found in the distribution of the correlation coefficients between the patients and the healthy volunteers ( P = .0034). When distribution of the correlation coefficients obtained by the 3D analyses was compared with that by the 2D (conventional) analyses, based on the bisect offset index and patellar tilt angle, the 3D analyses showed statistically higher correlations between the lateral deviation and inclination of the patella ( P < .01). 3D shift and 3D tilt of the patella were moderately or strongly correlated in 95% of patients with RDP at 0° to 50° of knee flexion. It is not always necessary to use both parameters when evaluating patellar alignment, at least for knees with RDP at 0° to 50° of flexion. Such a description may enable surgeons to describe patellar alignment more simply, leading to a better, easier understanding of the characteristics of each patient with RDP.

Active motion assisted by correlated stochastic torques.

PubMed

Weber, Christian; Radtke, Paul K; Schimansky-Geier, Lutz; Hänggi, Peter

2011-07-01

The stochastic dynamics of an active particle undergoing a constant speed and additionally driven by an overall fluctuating torque is investigated. The random torque forces are expressed by a stochastic differential equation for the angular dynamics of the particle determining the orientation of motion. In addition to a constant torque, the particle is supplemented by random torques, which are modeled as an Ornstein-Uhlenbeck process with given correlation time τ(c). These nonvanishing correlations cause a persistence of the particles' trajectories and a change of the effective spatial diffusion coefficient. We discuss the mean square displacement as a function of the correlation time and the noise intensity and detect a nonmonotonic dependence of the effective diffusion coefficient with respect to both correlation time and noise strength. A maximal diffusion behavior is obtained if the correlated angular noise straightens the curved trajectories, interrupted by small pirouettes, whereby the correlated noise amplifies a straightening of the curved trajectories caused by the constant torque.

Efficient Strategies for Estimating the Spatial Coherence of Backscatter

PubMed Central

Hyun, Dongwoon; Crowley, Anna Lisa C.; Dahl, Jeremy J.

2017-01-01

The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this study, we assess existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4 and 20-fold in vivo with a downsample factor of 2. PMID:27913342

Effective screening length and quasiuniversality for the restricted primitive model of an electrolyte solution.

PubMed

Janecek, Jirí; Netz, Roland R

2009-02-21

Monte Carlo simulations for the restricted primitive model of an electrolyte solution above the critical temperature are performed at a wide range of concentrations and temperatures. Thermodynamic properties such as internal energy, osmotic coefficient, activity coefficient, as well as spatial correlation functions are determined. These observables are used to investigate whether quasiuniversality in terms of an effective screening length exists, similar to the role played by the effective electron mass in solid-state physics. To that end, an effective screening length is extracted from the asymptotic behavior of the Fourier-transformed charge-correlation function and plugged into the Debye-Huckel limiting expressions for various thermodynamic properties. Comparison with numerical results is favorable, suggesting that correlation and other effects not captured on the Debye-Huckel limiting level can be successfully incorporated by a single effective parameter while keeping the functional form of Debye-Huckel expressions. We also compare different methods to determine mean ionic activity coefficient in molecular simulations and check the internal consistency of the numerical data.

Correspondence between large-scale ictal and interictal epileptic networks revealed by single photon emission computed tomography (SPECT) and electroencephalography (EEG)-functional magnetic resonance imaging (fMRI).

PubMed

Tousseyn, Simon; Dupont, Patrick; Goffin, Karolien; Sunaert, Stefan; Van Paesschen, Wim

2015-03-01

Epilepsy is increasingly recognized as a network disorder, but the spatial relationship between ictal and interictal networks is still largely unexplored. In this work, we compared hemodynamic changes related to seizures and interictal spikes on a whole brain scale. Twenty-eight patients with refractory focal epilepsy (14 temporal and 14 extratemporal lobe) underwent both subtraction ictal single photon emission computed tomography (SPECT) coregistered to magnetic resonance imaging (MRI) (SISCOM) and spike-related electroencephalography (EEG-functional MRI (fMRI). SISCOM visualized relative perfusion changes during seizures, whereas EEG-fMRI mapped blood oxygen level-dependent (BOLD) changes related to spikes. Similarity between statistical maps of both modalities was analyzed per patient using the following two measures: (1) correlation between unthresholded statistical maps (Pearson's correlation coefficient) and (2) overlap between thresholded images (Dice coefficient). Overlap was evaluated at a regional level, for hyperperfusions and activations and for hypoperfusions and deactivations separately, using different thresholds. Nonparametric permutation tests were applied to assess statistical significance (p ≤ 0.05). We found significant and positive correlations between hemodynamic changes related to seizures and spikes in 27 (96%) of 28 cases (median correlation coefficient 0.29 [range -0.12 to 0.62]). In 20 (71%) of 28 cases, spatial overlap between hyperperfusion on SISCOM and activation on EEG-fMRI was significantly larger than expected by chance. Congruent changes were not restricted to the territory of the presumed epileptogenic zone, but could be seen at distant sites (e.g., cerebellum and basal ganglia). Overlap between ictal hypoperfusion and interictal deactivation was statistically significant in 22 (79%) of 28 patients. Despite the high rate of congruence, discrepancies were observed for both modalities. We conclude that hemodynamic changes related to seizures and spikes varied spatially with the same sign and within a common network. Overlap was present in regions nearby and distant from discharge origin. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Application of biospeckles for assessment of structural and cellular changes in muscle tissue

NASA Astrophysics Data System (ADS)

Maksymenko, Oleksandr P.; Muravsky, Leonid I.; Berezyuk, Mykola I.

2015-09-01

A modified spatial-temporal speckle correlation technique for operational assessment of structural changes in muscle tissues after slaughtering is considered. Coefficient of biological activity as a quantitative indicator of structural changes of biochemical processes in biological tissues is proposed. The experimental results have shown that this coefficient properly evaluates the biological activity of pig and chicken muscle tissue samples. Studying the degradation processes in muscle tissue during long-time storage in a refrigerator by measuring the spatial-temporal dynamics of biospeckle patterns is carried out. The reduction of the bioactivity level of refrigerated muscle tissue samples connected with the initiation of muscle fiber cracks and ruptures, reduction of sarcomeres, nuclei deformation, nuclear chromatin diminishing, and destruction of mitochondria is analyzed.

The Interaction Between Accretion from the Interstellar Medium and Accretion from the Evolved Binary Component in Barium Stars

NASA Astrophysics Data System (ADS)

Jeong, Yeuncheol; Yushchenko, Alexander V.; Doikov, Dmytry N.

2018-03-01

The reanalysis of the previously published abundance pattern of mild barium star HD202109 (ζ Cyg) and the chemical compositions of 129 thin disk barium stars facilitated the search for possible correlations of different stellar parameters with second ionization potentials of chemical elements. Results show that three valuable correlations exist in the atmospheres of barium stars. The first is the relationship between relative abundances and second ionization potentials. The second is the age dependence of mean correlation coefficients of relative abundances vs. second ionization potentials, and the third one is the changes in correlation coefficients of relative abundances vs. second ionization potentials as a function of stellar spatial velocities and overabundances of s-process elements. These findings demonstrate the possibility of hydrogen and helium accretion from the interstellar medium on the atmospheres of barium stars.

Water vapor variation and the effect of aerosols in China

NASA Astrophysics Data System (ADS)

Gui, Ke; Che, Huizheng; Chen, Quanliang; Zeng, Zhaoliang; Zheng, Yu; Long, Qichao; Sun, Tianze; Liu, Xinyu; Wang, Yaqiang; Liao, Tingting; Yu, Jie; Wang, Hong; Zhang, Xiaoye

2017-09-01

This study analyzes the annual and seasonal trends in precipitable water vapor (PWV) and surface temperature (Ts) over China from 1979 to 2015, and the relationships between PWV and Ts and between PWV and aerosol absorption optical depth (AAOD), using data from radiosonde stations, weather stations and multiple satellite observations. The results revealed a positive PWV trend between 1979 and 1999, and a negative PWV trend between 2000 and 2015. Analysis of the differences in the PWV trend among different stations types showed that the magnitude of the trends were in the order main urban stations > provincial capital stations > suburb stations, suggesting that anthropogenic activities have a strong influence on the PWV trend. The AAOD exhibited a significant positive trend in most regions of China from 2005 to 2015 (confidence level 95%). Using spatial correlation analysis, we showed that PWV trend derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations is correlated with Ts, with an annual correlation coefficient of 0.596. In addition, the spatial correlation between PWV and AAOD showed a negative relationship, with the highest correlation coefficients of -0.76 and -0.71 observed in mid-eastern China and central northwest China, respectively, suggesting that the increase in AAOD in recent years may be one of the reasons for the decrease in PWV since the 2000s in China.

Analysis of the correlation dimension for inertial particles

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

Gustavsson, Kristian; Department of Physics, Göteborg University, 41296 Gothenburg; Mehlig, Bernhard

2015-07-15

We obtain an implicit equation for the correlation dimension which describes clustering of inertial particles in a complex flow onto a fractal measure. Our general equation involves a propagator of a nonlinear stochastic process in which the velocity gradient of the fluid appears as additive noise. When the long-time limit of the propagator is considered our equation reduces to an existing large-deviation formalism from which it is difficult to extract concrete results. In the short-time limit, however, our equation reduces to a solvability condition on a partial differential equation. In the case where the inertial particles are much denser thanmore » the fluid, we show how this approach leads to a perturbative expansion of the correlation dimension, for which the coefficients can be obtained exactly and in principle to any order. We derive the perturbation series for the correlation dimension of inertial particles suspended in three-dimensional spatially smooth random flows with white-noise time correlations, obtaining the first 33 non-zero coefficients exactly.« less

The effects of changes in cadmium and lead air pollution on cancer incidence in children.

PubMed

Absalon, Damian; Slesak, Barbara

2010-09-15

This article presents the results of research on the effects of air pollution on cancer incidence in children in the region of Silesia (Poland), which has undergone one of the most profound anthropogenic transformations in Europe. The main objective of the research was to specify the impact of changes in cadmium and lead pollution in the years 1990-2005 on the incidence of cancers reported in children. Lead concentration ranged from 0 to 1490 x 10(-9) G m(-2)/year, and cadmium concentration ranged from 0 to 33.7 x 10(-9) G m(-2)/year. There was no strong significant correlation (max 0.3) between air pollution and incidence rate (IR) in the general population of children in any particular year. Alongside the cartographic presentation of dependences, correlation coefficients between the variables in question were calculated. This made it possible to determine the relationship between the pollution levels and incidence rates in the area. There was a significant reduction in the level of pollution during the investigated period. The study of the relationship between the number of cancers reported and the condition of the natural environment revealed increased sensitivity to toxins in boys (correlation coefficient 0.3). In addition, the spatial distribution of the number of cases reported in boys suggests a correlation with the spatial distribution of the coefficients for the entire group of children included in the study. The yearly average IR of childhood cancer in specific districts ranged from 0 to 61.48/100,000 children under 18 years of age during the 1995-2004 period. Copyright 2010 Elsevier B.V. All rights reserved.

Plasma fluctuations as Markovian noise.

PubMed

Li, B; Hazeltine, R D; Gentle, K W

2007-12-01

Noise theory is used to study the correlations of stationary Markovian fluctuations that are homogeneous and isotropic in space. The relaxation of the fluctuations is modeled by the diffusion equation. The spatial correlations of random fluctuations are modeled by the exponential decay. Based on these models, the temporal correlations of random fluctuations, such as the correlation function and the power spectrum, are calculated. We find that the diffusion process can give rise to the decay of the correlation function and a broad frequency spectrum of random fluctuations. We also find that the transport coefficients may be estimated by the correlation length and the correlation time. The theoretical results are compared with the observed plasma density fluctuations from the tokamak and helimak experiments.

Spatial heterogeneity distribution of soil total nitrogen and total phosphorus in the Yaoxiang watershed in a hilly area of northern China based on geographic information system and geostatistics.

PubMed

Liu, Yu; Gao, Peng; Zhang, Liyong; Niu, Xiang; Wang, Bing

2016-10-01

Soil total nitrogen (STN) and total phosphorus (STP) are important indicators of soil nutrients and the important indexes of soil fertility and soil quality evaluation. Using geographic information system (GIS) and geostatistics, the spatial heterogeneity distribution of STN and STP in the Yaoxiang watershed in a hilly area of northern China was studied. The results showed that: (1) The STN and STP contents showed a declining trend with the increase in soil depth; the variation coefficients ( C v ) of STN and STP in the 0- to 10-cm soil layer (42.25% and 14.77%, respectively) were higher than in the 10- to 30-cm soil layer (28.77% and 11.60%, respectively). Moreover, the C v of STN was higher than that of STP. (2) The maximum C 0 /( C 0  +  C 1 ) of STN and STP in the soil layers was less than 25%, this indicated that a strong spatial distribution autocorrelation existed for STN and STP; and the STP showed higher intensity and more stable variation than the STN. (3) From the correlation analysis, we concluded that the topographic indexes such as elevation and slope direction all influenced the spatial distribution of STN and STP (correlation coefficients were 0.688 and 0.518, respectively). (4) The overall distribution of STN and STP in the Yaoxiang watershed decreased from the northwest to the southeast. This variation trend was similar to the watershed DEM trend and was significantly influenced by vegetation and topographic factors. These results revealed the spatial heterogeneity distribution of STN and STP, and addressed the influences of forest vegetation coverage, elevation, and other topographic factors on the spatial distribution of STN and STP at the watershed scale.

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

DOE PAGES

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.; ...

2017-01-31

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

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

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Reliability and Reproducibility of Advanced ECG Parameters in Month-to-Month and Year-to-Year Recordings in Healthy Subjects

NASA Technical Reports Server (NTRS)

Starc, Vito; Abughazaleh, Ahmed S.; Schlegel, Todd T.

2014-01-01

Advanced resting ECG parameters such the spatial mean QRS-T angle and the QT variability index (QTVI) have important diagnostic and prognostic utility, but their reliability and reproducibility (R&R) are not well characterized. We hypothesized that the spatial QRS-T angle would have relatively higher R&R than parameters such as QTVI that are more responsive to transient changes in the autonomic nervous system. The R&R of several conventional and advanced ECG para-meters were studied via intraclass correlation coefficients (ICCs) and coefficients of variation (CVs) in: (1) 15 supine healthy subjects from month-to-month; (2) 27 supine healthy subjects from year-to-year; and (3) 25 subjects after transition from the supine to the seated posture. As hypothesized, for the spatial mean QRS-T angle and many conventional ECG parameters, ICCs we-re higher, and CVs lower than QTVI, suggesting that the former parameters are more reliable and reproducible.

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

NASA Astrophysics Data System (ADS)

Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen O.

2015-03-01

Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring.

PubMed

Wu, Mingquan; Li, Hua; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-01

There is a shortage of daily high spatial land surface temperature (LST) data for use in high spatial and temporal resolution environmental process monitoring. To address this shortage, this work used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and the Spatial and Temporal Data Fusion Approach (STDFA) to estimate high spatial and temporal resolution LST by combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST and Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The actual ASTER LST products were used to evaluate the precision of the combined LST images using the correlation analysis method. This method was tested and validated in study areas located in Gansu Province, China. The results show that all the models can generate daily synthetic LST image with a high correlation coefficient (r) of 0.92 between the synthetic image and the actual ASTER LST observations. The ESTARFM has the best performance, followed by the STDFA and the STARFM. Those models had better performance in desert areas than in cropland. The STDFA had better noise immunity than the other two models.

Spatial variability of macrobenthic zonation on exposed sandy beaches

NASA Astrophysics Data System (ADS)

Veiga, Puri; Rubal, Marcos; Cacabelos, Eva; Maldonado, Cristina; Sousa-Pinto, Isabel

2014-07-01

We analysed the consistence of vertical patterns of distribution (i.e. zonation) for macrofauna at different spatial scales on four intermediate exposed beaches in the North of Portugal. We tested the hypothesis that biological zonation on exposed sandy beaches would vary at the studied spatial scales. For this aim, abundance, diversity and structure of macrobenthic assemblages were examined at the scales of transect and beach. Moreover, the main environmental factors that could potentially drive zonation patterns were investigated. Univariate and multivariate analyses revealed that the number of biological zones ranged from two to three depending on the beach and from indistinct zonation to three zones at the scale of transect. Therefore, results support our working hypothesis because zonation patterns were not consistent at the studied spatial scales. The median particle size, sorting coefficient and water content were significantly correlated with zonation patterns of macrobenthic assemblages. However, a high degree of correlation was not reached when the total structure of the assemblage was considered.

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals

NASA Astrophysics Data System (ADS)

Chen, Youhua; Peng, Shushi

2017-03-01

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals.

PubMed

Chen, Youhua; Peng, Shushi

2017-03-16

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

Correlation of track irregularities and vehicle responses based on measured data

NASA Astrophysics Data System (ADS)

Karis, Tomas; Berg, Mats; Stichel, Sebastian; Li, Martin; Thomas, Dirk; Dirks, Babette

2018-06-01

Track geometry quality and dynamic vehicle response are closely related, but do not always correspond with each other in terms of maximum values and standard deviations. This can often be seen to give poor results in analyses with correlation coefficients or regression analysis. Measured data from both the EU project DynoTRAIN and the Swedish Green Train (Gröna Tåget) research programme is used in this paper to evaluate track-vehicle response for three vehicles. A single degree of freedom model is used as an inspiration to divide track-vehicle interaction into three parts, which are analysed in terms of correlation. One part, the vertical axle box acceleration divided by vehicle speed squared (?) and the second spatial derivative of the vertical track irregularities (?), is shown to be the weak link with lower correlation coefficients than the other parts. Future efforts should therefore be directed towards investigating the relation between axle box accelerations and track irregularity second derivatives.

Node Survival in Networks under Correlated Attacks

PubMed Central

Hao, Yan; Armbruster, Dieter; Hütt, Marc-Thorsten

2015-01-01

We study the interplay between correlations, dynamics, and networks for repeated attacks on a socio-economic network. As a model system we consider an insurance scheme against disasters that randomly hit nodes, where a node in need receives support from its network neighbors. The model is motivated by gift giving among the Maasai called Osotua. Survival of nodes under different disaster scenarios (uncorrelated, spatially, temporally and spatio-temporally correlated) and for different network architectures are studied with agent-based numerical simulations. We find that the survival rate of a node depends dramatically on the type of correlation of the disasters: Spatially and spatio-temporally correlated disasters increase the survival rate; purely temporally correlated disasters decrease it. The type of correlation also leads to strong inequality among the surviving nodes. We introduce the concept of disaster masking to explain some of the results of our simulations. We also analyze the subsets of the networks that were activated to provide support after fifty years of random disasters. They show qualitative differences for the different disaster scenarios measured by path length, degree, clustering coefficient, and number of cycles. PMID:25932635

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

USGS Publications Warehouse

Yang, X.; Jin, W.

2010-01-01

Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.

Relationship Study on Land Use Spatial Distribution Structure and Energy-Related Carbon Emission Intensity in Different Land Use Types of Guangdong, China, 1996–2008

PubMed Central

Huang, Yi; Yang, Lei

2013-01-01

This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996–2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective. PMID:23476128

Relationship study on land use spatial distribution structure and energy-related carbon emission intensity in different land use types of Guangdong, China, 1996-2008.

PubMed

Huang, Yi; Xia, Bin; Yang, Lei

2013-01-01

This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996-2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective.

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

NASA Astrophysics Data System (ADS)

Smith, Tony E.; Lee, Ka Lok

2012-01-01

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

Temporal behavior of a solute cloud in a fractal heterogeneous porous medium at different scales

NASA Astrophysics Data System (ADS)

Ross, Katharina; Attinger, Sabine

2010-05-01

Water pollution is still a very real problem and the need for efficient models for flow and solute transport in heterogeneous porous or fractured media is evident. In our study we focus on solute transport in heterogeneous fractured media. In heterogeneous fractured media the shape of the pores and fractures in the subsurface might be modeled as a fractal network or a heterogeneous structure with infinite correlation length. To derive explicit results for larger scale or effective transport parameters in such structures is the aim of this work. To describe flow and transport we investigate the temporal behavior of transport coefficients of solute movement through a spatially heterogeneous medium. It is necessary to distinguish between two fundamentally different quantities characterizing the solute dispersion: The effective dispersion coefficient Deff(t) represents the physical (observable) dispersion in one given realization of the medium. It is conceptually different from the mathematically simpler ensemble dispersion coefficient Dens(t) which characterizes the (abstract) dispersion with respect to the set of all possible realizations of the medium. In the framework of a stochastic approach DENTZ ET AL. (2000 I[2] & II[3]) derive explicit expressions for the temporal behavior of the center-of-mass velocity and the dispersion of the concentration distribution, using a second order perturbation expansion. In their model the authors assume a finite correlation length of the heterogeneities and use a GAUSSIAN correlation function. In a first step, we model the fractured medium as a heterogeneous porous medium with infinite correlation length and neglect single fractures. ZHAN & WHEATCRAFT (1996[4]) analyze the macrodispersivity tensor in fractal porous media using a non-integer exponent which consists of the HURST coefficient and the fractal dimension D. To avoid this non-integer exponent for numerical reasons we extend the study of DENTZ ET AL. (2000 I[2] & II[3]) and derive explicit expressions for the center-of-mass velocity and the longitudinal dispersion coefficient for isotropic and anisotropic media as well as for point-like (where the extent of the source distribution is small compared to the correlation lengths of the heterogeneities) and spatially extended injections. Our results clearly show that the difference between Deff and Dens persists for all times. In other words, ensemble mixing and effective mixing coefficients do not approach the same asymptotic limit. The center-of-mass fluctuations between different flow paths for a plume traveling through the medium never become irrelevant and ergodicity breaks down in such media. Our ongoing work concerns the investigation of the transversal dispersion coefficient and the extension of the upscaling method coarse graining[1] to heterogeneous fractal porous media with embedded single fractures. References [1]ATTINGER, S. (2003): Generalized coarse graining procedures for flow in porous media, Computational Geosciences, 7 (4), pp. 253-273. [2]DENTZ, M. / KINZELBACH, H. / ATTINGER, S. and W. KINZELBACH (2000): Temporal behavior of a solute cloud in a heterogeneous porous medium: 1. Point-like injection, Water Resources Research, 36 (12), pp. 3591-3604. [3]DENTZ, M. / KINZELBACH, H. / ATTINGER, S. and W. KINZELBACH (2000): Temporal behavior of a solute cloud in a heterogeneous porous medium: 2. Spatially extended injection, Water Resources Research, 36 (12), pp. 3605-3614. [4]ZHAN, H. and S. W. WHEATCRAFT (1996): Macrodispersivity tensor for nonreactive solute transport in isotropic and anisotropic fractal porous media: Analytical solutions, Water Resources Research, 32 (12), pp. 3461-3474.

In Situ Effective Diffusion Coefficient Profiles in Live Biofilms Using Pulsed-Field Gradient Nuclear Magnetic Resonance

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

Renslow, Ryan S.; Majors, Paul D.; McLean, Jeffrey S.

2010-08-15

Diffusive mass transfer in biofilms is characterized by the effective diffusion coefficient. It is well-documented that the effective diffusion coefficient can vary by location in a biofilm. The current literature is dominated by effective diffusion coefficient measurements for distinct cell clusters and stratified biofilms showing this spatial variation. Regardless of whether distinct cell clusters or surface-averaging methods are used, position-dependent measurements of the effective diffusion coefficient are currently: 1) invasive to the biofilm, 2) performed under unnatural conditions, 3) lethal to cells, and/or 4) spatially restricted to only certain regions of the biofilm. Invasive measurements can lead to inaccurate resultsmore » and prohibit further (time dependent) measurements which are important for the mathematical modeling of biofilms. In this study our goals were to: 1) measure the effective diffusion coefficient for water in live biofilms, 2) monitor how the effective diffusion coefficient changes over time under growth conditions, and 3) correlate the effective diffusion coefficient with depth in the biofilm. We measured in situ two-dimensional effective diffusion coefficient maps within Shewanella oneidensis MR-1biofilms using pulsed-field gradient nuclear magnetic resonance methods, and used them to calculate surface-averaged relative effective diffusion coefficient (Drs) profiles. We found that 1) Drs decreased from the top of the biofilm to the bottom, 2) Drs profiles differed for biofilms of different ages, 3) Drs profiles changed over time and generally decreased with time, 4) all the biofilms showed very similar Drs profiles near the top of the biofilm, and 5) the Drs profile near the bottom of the biofilm was different for each biofilm. Practically, our results demonstrate that advanced biofilm models should use a variable effective diffusivity which changes with time and location in the biofilm.« less

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

3D radiation belt diffusion model results using new empirical models of whistler chorus and hiss

NASA Astrophysics Data System (ADS)

Cunningham, G.; Chen, Y.; Henderson, M. G.; Reeves, G. D.; Tu, W.

2012-12-01

3D diffusion codes model the energization, radial transport, and pitch angle scattering due to wave-particle interactions. Diffusion codes are powerful but are limited by the lack of knowledge of the spatial & temporal distribution of waves that drive the interactions for a specific event. We present results from the 3D DREAM model using diffusion coefficients driven by new, activity-dependent, statistical models of chorus and hiss waves. Most 3D codes parameterize the diffusion coefficients or wave amplitudes as functions of magnetic activity indices like Kp, AE, or Dst. These functional representations produce the average value of the wave intensities for a given level of magnetic activity; however, the variability of the wave population at a given activity level is lost with such a representation. Our 3D code makes use of the full sample distributions contained in a set of empirical wave databases (one database for each wave type, including plasmaspheric hiss, lower and upper hand chorus) that were recently produced by our team using CRRES and THEMIS observations. The wave databases store the full probability distribution of observed wave intensity binned by AE, MLT, MLAT and L*. In this presentation, we show results that make use of the wave intensity sample probability distributions for lower-band and upper-band chorus by sampling the distributions stochastically during a representative CRRES-era storm. The sampling of the wave intensity probability distributions produces a collection of possible evolutions of the phase space density, which quantifies the uncertainty in the model predictions caused by the uncertainty of the chorus wave amplitudes for a specific event. A significant issue is the determination of an appropriate model for the spatio-temporal correlations of the wave intensities, since the diffusion coefficients are computed as spatio-temporal averages of the waves over MLT, MLAT and L*. The spatiotemporal correlations cannot be inferred from the wave databases. In this study we use a temporal correlation of ~1 hour for the sampled wave intensities that is informed by the observed autocorrelation in the AE index, a spatial correlation length of ~100 km in the two directions perpendicular to the magnetic field, and a spatial correlation length of 5000 km in the direction parallel to the magnetic field, according to the work of Santolik et al (2003), who used multi-spacecraft measurements from Cluster to quantify the correlation length scales for equatorial chorus . We find that, despite the small correlation length scale for chorus, there remains significant variability in the model outcomes driven by variability in the chorus wave intensities.

Comparison of perceived and modelled geographical access to accident and emergency departments: a cross-sectional analysis from the Caerphilly Health and Social Needs Study.

PubMed

Fone, David L; Christie, Stephen; Lester, Nathan

2006-04-13

Assessment of the spatial accessibility of hospital accident and emergency departments as perceived by local residents has not previously been investigated. Perceived accessibility may affect where, when, and whether potential patients attend for treatment. Using data on 11,853 respondents to a population survey in Caerphilly county borough, Wales, UK, we present an analysis comparing the accessibility of accident and emergency departments as reported by local residents and drive-time to the nearest accident and emergency department modelled using a geographical information system (GIS). Median drive-times were significantly shorter in the lowest perceived access category and longer in the best perceived access category (p < 0.001). The perceived access and GIS modelled drive-time variables were positively correlated (Spearman's rank correlation coefficient, r = 0.38, p < 0.01). The strongest correlation was found for respondents living in areas in which nearly all households had a car or van (r = 0.47, p < 0.01). Correlations were stronger among respondents reporting good access to public transport and among those reporting a recent accident and emergency attendance for injury treatment compared to other respondents. Correlation coefficients did not vary substantially by levels of household income. Drive-time, road distance and straight-line distance were highly inter-correlated and substituting road distance or straight-line distance as the GIS modelled spatial accessibility measure only marginally decreased the magnitude of the correlations between perceived and GIS modelled access. This study provides evidence that the accessibility of hospital-based health care services as perceived by local residents is related to measures of spatial accessibility modelled using GIS. For studies that aim to model geographical separation in a way that correlates well with the perception of local residents, there may be minimal advantage in using sophisticated measures. Straight-line distance, which can be calculated without GIS, may be as good as GIS-modelled drive-time or distance for this purpose. These findings will be of importance to health policy makers and local planners who seek to obtain local information on access to services through focussed assessments of residents' concerns over accessibility and GIS modelling.

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

Three-gene identity coefficients demonstrate that clonal reproduction promotes inbreeding and spatial relatedness in yellow-cedar, Callitropsis nootkatensis.

PubMed

Thompson, Stacey Lee; Bérubé, Yanik; Bruneau, Anne; Ritland, Kermit

2008-10-01

Asexual reproduction has the potential to promote population structuring through matings between clones as well as through limited dispersal of related progeny. Here we present an application of three-gene identity coefficients that tests whether clonal reproduction promotes inbreeding and spatial relatedness within populations. With this method, the first two genes are sampled to estimate pairwise relatedness or inbreeding, whereas the third gene is sampled from either a clone or a sexually derived individual. If three-gene coefficients are significantly greater for clones than nonclones, then clonality contributes excessively to genetic structure. First, we describe an estimator of three-gene identity and briefly evaluate its properties. We then use this estimator to test the effect of clonality on the genetic structure within populations of yellow-cedar (Callitropsis nootkatensis) using a molecular marker survey. Five microsatellite loci were genotyped for 485 trees sampled from nine populations. Our three-gene analyses show that clonal ramets promote inbreeding and spatial structure in most populations. Among-population correlations between clonal extent and genetic structure generally support these trends, yet with less statistical significance. Clones appear to contribute to genetic structure through the limited dispersal of offspring from replicated ramets of the same clonal genet, whereas this structure is likely maintained by mating among these relatives.

Structure-specific magnetic field inhomogeneities and its effect on the correlation time.

PubMed

Ziener, Christian H; Bauer, Wolfgang R; Melkus, Gerd; Weber, Thomas; Herold, Volker; Jakob, Peter M

2006-12-01

We describe the relationship between the correlation time and microscopic spatial inhomogeneities in the static magnetic field. The theory takes into account diffusion of nuclear spins in the inhomogeneous field created by magnetized objects. A simple general expression for the correlation time is obtained. It is shown that the correlation time is dependent on a characteristic length, the diffusion coefficient of surrounding medium, the permeability of the surface and the volume fraction of the magnetized objects. For specific geometries (spheres and cylinders), exact analytical expressions for the correlation time are given. The theory can be applied to contrast agents (magnetically labeled cells), capillary network, BOLD effect and so forth.

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

PubMed Central

Villa-Parra, Ana Cecilia; Bastos-Filho, Teodiano; López-Delis, Alberto; Frizera-Neto, Anselmo; Krishnan, Sridhar

2017-01-01

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. PMID:29186848

k-Space Image Correlation Spectroscopy: A Method for Accurate Transport Measurements Independent of Fluorophore Photophysics

PubMed Central

Kolin, David L.; Ronis, David; Wiseman, Paul W.

2006-01-01

We present the theory and application of reciprocal space image correlation spectroscopy (kICS). This technique measures the number density, diffusion coefficient, and velocity of fluorescently labeled macromolecules in a cell membrane imaged on a confocal, two-photon, or total internal reflection fluorescence microscope. In contrast to r-space correlation techniques, we show kICS can recover accurate dynamics even in the presence of complex fluorophore photobleaching and/or “blinking”. Furthermore, these quantities can be calculated without nonlinear curve fitting, or any knowledge of the beam radius of the exciting laser. The number densities calculated by kICS are less sensitive to spatial inhomogeneity of the fluorophore distribution than densities measured using image correlation spectroscopy. We use simulations as a proof-of-principle to show that number densities and transport coefficients can be extracted using this technique. We present calibration measurements with fluorescent microspheres imaged on a confocal microscope, which recover Stokes-Einstein diffusion coefficients, and flow velocities that agree with single particle tracking measurements. We also show the application of kICS to measurements of the transport dynamics of α5-integrin/enhanced green fluorescent protein constructs in a transfected CHO cell imaged on a total internal reflection fluorescence microscope using charge-coupled device area detection. PMID:16861272

Complementary aspects of spatial resolution and signal-to-noise ratio in computational imaging

NASA Astrophysics Data System (ADS)

Gureyev, T. E.; Paganin, D. M.; Kozlov, A.; Nesterets, Ya. I.; Quiney, H. M.

2018-05-01

A generic computational imaging setup is considered which assumes sequential illumination of a semitransparent object by an arbitrary set of structured coherent illumination patterns. For each incident illumination pattern, all transmitted light is collected by a photon-counting bucket (single-pixel) detector. The transmission coefficients measured in this way are then used to reconstruct the spatial distribution of the object's projected transmission. It is demonstrated that the square of the spatial resolution of such a setup is usually equal to the ratio of the image area to the number of linearly independent illumination patterns. If the noise in the measured transmission coefficients is dominated by photon shot noise, then the ratio of the square of the mean signal to the noise variance is proportional to the ratio of the mean number of registered photons to the number of illumination patterns. The signal-to-noise ratio in a reconstructed transmission distribution is always lower if the illumination patterns are nonorthogonal, because of spatial correlations in the measured data. Examples of imaging methods relevant to the presented analysis include conventional imaging with a pixelated detector, computational ghost imaging, compressive sensing, super-resolution imaging, and computed tomography.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

NASA Astrophysics Data System (ADS)

Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana

2018-04-01

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

[Wave-type time series variation of the correlation between NDVI and climatic factors].

PubMed

Bi, Xiaoli; Wang, Hui; Ge, Jianping

2005-02-01

Based on the 1992-1996 data of 1 km monthly NDVI and those of the monthly precipitation and mean temperature collected by 400 standard meteorological stations in China, this paper analyzed the temporal and spatial dynamic changes of the correlation between NDVI and climatic factors in different climate districts of this country. The results showed that there was a significant correlation between monthly precipitations and NDVI. The wave-type time series model could simulate well the temporal dynamic changes of the correlation between NDVI and climatic factors, and the simulated results of the correlation between NDVI and precipitation was better than that between NDVI and temperature. The correlation coefficients (R2) were 0.91 and 0.86, respectively for the whole country.

Laser Transmission Measurements of Soot Extinction Coefficients in the Exhaust Plume of the X-34 60K-lb Thrust Fastrac Rocket Engine

NASA Technical Reports Server (NTRS)

Dobson, C. C.; Eskridge, R. H.; Lee, M. H.

2000-01-01

A four-channel laser transmissometer has been used to probe the soot content of the exhaust plume of the X-34 60k-lb thrust Fastrac rocket engine at NASA's Marshall Space Flight Center. The transmission measurements were made at an axial location approximately equal 1.65 nozzle diameters from the exit plane and are interpreted in terms of homogeneous radial zones to yield extinction coefficients from 0.5-8.4 per meter. The corresponding soot mass density, spatially averaged over the plume cross section, is, for Rayleigh particles, approximately equal 0.7 microgram/cc, and alternative particle distributions are briefly considered. Absolute plume radiance at the laser wavelength (515 nm) is estimated from the data at approximately equal 2,200 K equivalent blackbody temperature, and temporal correlations in emission from several spatial locations are noted.

Laser Transmission Measurements of Soot Extinction Coefficients in the Exhaust Plume of the X-34 60k-lb Thrust Fastrac Rocket Engine

NASA Technical Reports Server (NTRS)

Dobson, C. C.; Eskridge, R. H.; Lee, M. H.

2000-01-01

A four-channel laser transmissometer has been used to probe the soot content of the exhaust plume of the X-34 60k-lb thrust Fastrac rocket engine at NASA's Marshall Space Flight Center. The transmission measurements were made at an axial location about equal 1.65 nozzle diameters from the exit plane and are interpreted in terms of homogeneous radial zones to yield extinction coefficients from 0.5-8.4 per meter. The corresponding soot mass density, spatially averaged over the plume cross section, is, for Rayleigh particles, approximately equal to 0.7 micrograms/cubic cm and alternative particle distributions are briefly considered. Absolute plume radiance at the laser wavelength (515 nm) is estimated from the data at approximately equal to 2.200 K equivalent blackbody temperature, and temporal correlations in emission from several spatial locations are noted.

Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter

USGS Publications Warehouse

Kim, Jin-Woo; Lu, Zhong; Jones, John W.; Shum, C.K.; Lee, Hyongki; Jia, Yuanyuan

2014-01-01

The Florida Everglades plays a significant role in controlling floods, improving water quality, supporting ecosystems, and maintaining biodiversity in south Florida. Adaptive restoration and management of the Everglades requires the best information possible regarding wetland hydrology. We developed a new and innovative approach to quantify spatial and temporal variations in wetland water levels within the Everglades, Florida. We observed high correlations between water level measured at in situ gages and L-band SAR backscatter coefficients in the freshwater marsh, though C-band SAR backscatter has no close relationship with water level. Here we illustrate the complementarity of SAR backscatter coefficient differencing and interferometry (InSAR) for improved estimation of high spatial resolution water level variations in the Everglades. This technique has a certain limitation in applying to swamp forests with dense vegetation cover, but we conclude that this new method is promising in future applications to wetland hydrology research.

Structural covariance networks across healthy young adults and their consistency.

PubMed

Guo, Xiaojuan; Wang, Yan; Guo, Taomei; Chen, Kewei; Zhang, Jiacai; Li, Ke; Jin, Zhen; Yao, Li

2015-08-01

To investigate structural covariance networks (SCNs) as measured by regional gray matter volumes with structural magnetic resonance imaging (MRI) from healthy young adults, and to examine their consistency and stability. Two independent cohorts were included in this study: Group 1 (82 healthy subjects aged 18-28 years) and Group 2 (109 healthy subjects aged 20-28 years). Structural MRI data were acquired at 3.0T and 1.5T using a magnetization prepared rapid-acquisition gradient echo sequence for these two groups, respectively. We applied independent component analysis (ICA) to construct SCNs and further applied the spatial overlap ratio and correlation coefficient to evaluate the spatial consistency of the SCNs between these two datasets. Seven and six independent components were identified for Group 1 and Group 2, respectively. Moreover, six SCNs including the posterior default mode network, the visual and auditory networks consistently existed across the two datasets. The overlap ratios and correlation coefficients of the visual network reached the maximums of 72% and 0.71. This study demonstrates the existence of consistent SCNs corresponding to general functional networks. These structural covariance findings may provide insight into the underlying organizational principles of brain anatomy. © 2014 Wiley Periodicals, Inc.

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Long-range correlations improve understanding of the influence of network structure on contact dynamics.

PubMed

Peyrard, N; Dieckmann, U; Franc, A

2008-05-01

Models of infectious diseases are characterized by a phase transition between extinction and persistence. A challenge in contemporary epidemiology is to understand how the geometry of a host's interaction network influences disease dynamics close to the critical point of such a transition. Here we address this challenge with the help of moment closures. Traditional moment closures, however, do not provide satisfactory predictions close to such critical points. We therefore introduce a new method for incorporating longer-range correlations into existing closures. Our method is technically simple, remains computationally tractable and significantly improves the approximation's performance. Our extended closures thus provide an innovative tool for quantifying the influence of interaction networks on spatially or socially structured disease dynamics. In particular, we examine the effects of a network's clustering coefficient, as well as of new geometrical measures, such as a network's square clustering coefficients. We compare the relative performance of different closures from the literature, with or without our long-range extension. In this way, we demonstrate that the normalized version of the Bethe approximation-extended to incorporate long-range correlations according to our method-is an especially good candidate for studying influences of network structure. Our numerical results highlight the importance of the clustering coefficient and the square clustering coefficient for predicting disease dynamics at low and intermediate values of transmission rate, and demonstrate the significance of path redundancy for disease persistence.

Utility of spatial frequency domain imaging (SFDI) and laser speckle imaging (LSI) to non-invasively diagnose burn depth in a porcine model☆

PubMed Central

Burmeister, David M.; Ponticorvo, Adrien; Yang, Bruce; Becerra, Sandra C.; Choi, Bernard; Durkin, Anthony J.; Christy, Robert J.

2015-01-01

Surgical intervention of second degree burns is often delayed because of the difficulty in visual diagnosis, which increases the risk of scarring and infection. Non-invasive metrics have shown promise in accurately assessing burn depth. Here, we examine the use of spatial frequency domain imaging (SFDI) and laser speckle imaging (LSI) for predicting burn depth. Contact burn wounds of increasing severity were created on the dorsum of a Yorkshire pig, and wounds were imaged with SFDI/LSI starting immediately after-burn and then daily for the next 4 days. In addition, on each day the burn wounds were biopsied for histological analysis of burn depth, defined by collagen coagulation, apoptosis, and adnexal/vascular necrosis. Histological results show that collagen coagulation progressed from day 0 to day 1, and then stabilized. Results of burn wound imaging using non-invasive techniques were able to produce metrics that correlate to different predictors of burn depth. Collagen coagulation and apoptosis correlated with SFDI scattering coefficient parameter ( μs′) and adnexal/vascular necrosis on the day of burn correlated with blood flow determined by LSI. Therefore, incorporation of SFDI scattering coefficient and blood flow determined by LSI may provide an algorithm for accurate assessment of the severity of burn wounds in real time. PMID:26138371

Using Bayesian hierarchical models to better understand nitrate sources and sinks in agricultural watersheds.

PubMed

Xia, Yongqiu; Weller, Donald E; Williams, Meghan N; Jordan, Thomas E; Yan, Xiaoyuan

2016-11-15

Export coefficient models (ECMs) are often used to predict nutrient sources and sinks in watersheds because ECMs can flexibly incorporate processes and have minimal data requirements. However, ECMs do not quantify uncertainties in model structure, parameters, or predictions; nor do they account for spatial and temporal variability in land characteristics, weather, and management practices. We applied Bayesian hierarchical methods to address these problems in ECMs used to predict nitrate concentration in streams. We compared four model formulations, a basic ECM and three models with additional terms to represent competing hypotheses about the sources of error in ECMs and about spatial and temporal variability of coefficients: an ADditive Error Model (ADEM), a SpatioTemporal Parameter Model (STPM), and a Dynamic Parameter Model (DPM). The DPM incorporates a first-order random walk to represent spatial correlation among parameters and a dynamic linear model to accommodate temporal correlation. We tested the modeling approach in a proof of concept using watershed characteristics and nitrate export measurements from watersheds in the Coastal Plain physiographic province of the Chesapeake Bay drainage. Among the four models, the DPM was the best--it had the lowest mean error, explained the most variability (R 2  = 0.99), had the narrowest prediction intervals, and provided the most effective tradeoff between fit complexity (its deviance information criterion, DIC, was 45.6 units lower than any other model, indicating overwhelming support for the DPM). The superiority of the DPM supports its underlying hypothesis that the main source of error in ECMs is their failure to account for parameter variability rather than structural error. Analysis of the fitted DPM coefficients for cropland export and instream retention revealed some of the factors controlling nitrate concentration: cropland nitrate exports were positively related to stream flow and watershed average slope, while instream nitrate retention was positively correlated with nitrate concentration. By quantifying spatial and temporal variability in sources and sinks, the DPM provides new information to better target management actions to the most effective times and places. Given the wide use of ECMs as research and management tools, our approach can be broadly applied in other watersheds and to other materials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Functional Connectivity of Resting Hemodynamic Signals in Submillimeter Orientation Columns of the Visual Cortex.

PubMed

Vasireddi, Anil K; Vazquez, Alberto L; Whitney, David E; Fukuda, Mitsuhiro; Kim, Seong-Gi

2016-09-07

Resting-state functional magnetic resonance imaging has been increasingly used for examining connectivity across brain regions. The spatial scale by which hemodynamic imaging can resolve functional connections at rest remains unknown. To examine this issue, deoxyhemoglobin-weighted intrinsic optical imaging data were acquired from the visual cortex of lightly anesthetized ferrets. The neural activity of orientation domains, which span a distance of 0.7-0.8 mm, has been shown to be correlated during evoked activity and at rest. We performed separate analyses to assess the degree to which the spatial and temporal characteristics of spontaneous hemodynamic signals depend on the known functional organization of orientation columns. As a control, artificial orientation column maps were generated. Spatially, resting hemodynamic patterns showed a higher spatial resemblance to iso-orientation maps than artificially generated maps. Temporally, a correlation analysis was used to establish whether iso-orientation domains are more correlated than orthogonal orientation domains. After accounting for a significant decrease in correlation as a function of distance, a small but significant temporal correlation between iso-orientation domains was found, which decreased with increasing difference in orientation preference. This dependence was abolished when using artificially synthetized orientation maps. Finally, the temporal correlation coefficient as a function of orientation difference at rest showed a correspondence with that calculated during visual stimulation suggesting that the strength of resting connectivity is related to the strength of the visual stimulation response. Our results suggest that temporal coherence of hemodynamic signals measured by optical imaging of intrinsic signals exists at a submillimeter columnar scale in resting state.

Novel measurement of spreading pattern of influenza epidemic by using weighted standard distance method: retrospective spatial statistical study of influenza, Japan, 1999-2009.

PubMed

Shobugawa, Yugo; Wiafe, Seth A; Saito, Reiko; Suzuki, Tsubasa; Inaida, Shinako; Taniguchi, Kiyosu; Suzuki, Hiroshi

2012-06-19

Annual influenza epidemics occur worldwide resulting in considerable morbidity and mortality. Spreading pattern of influenza is not well understood because it is often hampered by the quality of surveillance data that limits the reliability of analysis. In Japan, influenza is reported on a weekly basis from 5,000 hospitals and clinics nationwide under the scheme of the National Infectious Disease Surveillance. The collected data are available to the public as weekly reports which were summarized into number of patient visits per hospital or clinic in each of the 47 prefectures. From this surveillance data, we analyzed the spatial spreading patterns of influenza epidemics using weekly weighted standard distance (WSD) from the 1999/2000 through 2008/2009 influenza seasons in Japan. WSD is a single numerical value representing the spatial compactness of influenza outbreak, which is small in case of clustered distribution and large in case of dispersed distribution. We demonstrated that the weekly WSD value or the measure of spatial compactness of the distribution of reported influenza cases, decreased to its lowest value before each epidemic peak in nine out of ten seasons analyzed. The duration between the lowest WSD week and the peak week of influenza cases ranged from minus one week to twenty weeks. The duration showed significant negative association with the proportion of influenza A/H3N2 cases in early phase of each outbreak (correlation coefficient was -0.75, P = 0.012) and significant positive association with the proportion of influenza B cases in the early phase (correlation coefficient was 0.64, P = 0.045), but positively correlated with the proportion of influenza A/H1N1 strain cases (statistically not significant). It is assumed that the lowest WSD values just before influenza peaks are due to local outbreak which results in small standard distance values. As influenza cases disperse nationwide and an epidemic reaches its peak, WSD value changed to be a progressively increasing. The spatial distribution of nationwide influenza outbreak was measured by using a novel WSD method. We showed that spreading rate varied by type and subtypes of influenza virus using WSD as a spatial indicator. This study is the first to show a relationship between influenza epidemic trend by type/subtype and spatial distribution of influenza nationwide in Japan.

Spatial Distribution and Relationship of T1ρ and T2 Relaxation Times in Knee Cartilage With Osteoarthritis

PubMed Central

Li, Xiaojuan; Pai, Alex; Blumenkrantz, Gabrielle; Carballido-Gamio, Julio; Link, Thomas; Ma, Benjamin; Ries, Michael; Majumdar, Sharmila

2009-01-01

T1ρ and T2 relaxation time constants have been proposed to probe biochemical changes in osteoarthritic cartilage. This study aimed to evaluate the spatial correlation and distribution of T1ρ and T2 values in osteoarthritic cartilage. Ten patients with osteoarthritis (OA) and 10 controls were studied at 3T. The spatial correlation of T1ρ and T2 values was investigated using Z-scores. The spatial variation of T1ρ and T2 values in patellar cartilage was studied in different cartilage layers. The distribution of these relaxation time constants was measured using texture analysis parameters based on gray-level co-occurrence matrices (GLCM). The mean Z-scores for T1ρ and T2 values were significantly higher in OA patients vs. controls (P < 0.05). Regional correlation coefficients of T1ρ and T2 Z-scores showed a large range in both controls and OA patients (0.2– 0.7). OA patients had significantly greater GLCM contrast and entropy of T1ρ values than controls (P < 0.05). In summary, T1ρ and T2 values are not only increased but are also more heterogeneous in osteoarthritic cartilage. T1ρ and T2 values show different spatial distributions and may provide complementary information regarding cartilage degeneration in OA. PMID:19319904

Inversion of multi-frequency electromagnetic induction data for 3D characterization of hydraulic conductivity

USGS Publications Warehouse

Brosten, Troy R.; Day-Lewis, Frederick D.; Schultz, Gregory M.; Curtis, Gary P.; Lane, John W.

2011-01-01

Electromagnetic induction (EMI) instruments provide rapid, noninvasive, and spatially dense data for characterization of soil and groundwater properties. Data from multi-frequency EMI tools can be inverted to provide quantitative electrical conductivity estimates as a function of depth. In this study, multi-frequency EMI data collected across an abandoned uranium mill site near Naturita, Colorado, USA, are inverted to produce vertical distribution of electrical conductivity (EC) across the site. The relation between measured apparent electrical conductivity (ECa) and hydraulic conductivity (K) is weak (correlation coefficient of 0.20), whereas the correlation between the depth dependent EC obtained from the inversions, and K is sufficiently strong to be used for hydrologic estimation (correlation coefficient of − 0.62). Depth-specific EC values were correlated with co-located K measurements to develop a site-specific ln(EC)–ln(K) relation. This petrophysical relation was applied to produce a spatially detailed map of K across the study area. A synthetic example based on ECa values at the site was used to assess model resolution and correlation loss given variations in depth and/or measurement error. Results from synthetic modeling indicate that optimum correlation with K occurs at ~ 0.5 m followed by a gradual correlation loss of 90% at 2.3 m. These results are consistent with an analysis of depth of investigation (DOI) given the range of frequencies, transmitter–receiver separation, and measurement errors for the field data. DOIs were estimated at 2.0 ± 0.5 m depending on the soil conductivities. A 4-layer model, with varying thicknesses, was used to invert the ECa to maximize available information within the aquifer region for improved correlations with K. Results show improved correlation between K and the corresponding inverted EC at similar depths, underscoring the importance of inversion in using multi-frequency EMI data for hydrologic estimation.

Inversion of multi-frequency electromagnetic induction data for 3D characterization of hydraulic conductivity

USGS Publications Warehouse

Brosten, T.R.; Day-Lewis, F. D.; Schultz, G.M.; Curtis, G.P.; Lane, J.W.

2011-01-01

Electromagnetic induction (EMI) instruments provide rapid, noninvasive, and spatially dense data for characterization of soil and groundwater properties. Data from multi-frequency EMI tools can be inverted to provide quantitative electrical conductivity estimates as a function of depth. In this study, multi-frequency EMI data collected across an abandoned uranium mill site near Naturita, Colorado, USA, are inverted to produce vertical distribution of electrical conductivity (EC) across the site. The relation between measured apparent electrical conductivity (ECa) and hydraulic conductivity (K) is weak (correlation coefficient of 0.20), whereas the correlation between the depth dependent EC obtained from the inversions, and K is sufficiently strong to be used for hydrologic estimation (correlation coefficient of -0.62). Depth-specific EC values were correlated with co-located K measurements to develop a site-specific ln(EC)-ln(K) relation. This petrophysical relation was applied to produce a spatially detailed map of K across the study area. A synthetic example based on ECa values at the site was used to assess model resolution and correlation loss given variations in depth and/or measurement error. Results from synthetic modeling indicate that optimum correlation with K occurs at ~0.5m followed by a gradual correlation loss of 90% at 2.3m. These results are consistent with an analysis of depth of investigation (DOI) given the range of frequencies, transmitter-receiver separation, and measurement errors for the field data. DOIs were estimated at 2.0??0.5m depending on the soil conductivities. A 4-layer model, with varying thicknesses, was used to invert the ECa to maximize available information within the aquifer region for improved correlations with K. Results show improved correlation between K and the corresponding inverted EC at similar depths, underscoring the importance of inversion in using multi-frequency EMI data for hydrologic estimation. ?? 2011.

Aggregating land use quantity and intensity to link water quality in upper catchment of Miyun Reservoir

NASA Astrophysics Data System (ADS)

Xu, E.

2015-12-01

Land use is closely related to hydrological and biochemical processes influencing the water quality. Quantifying relationship between both of them can help effectively manage land use to improve water quality. Previous studies majorly utilized land use quantity as an indicator to link water quality parameters, which lacked an insight to the influence of land use intensity. Taking upper catchment of Miyun Reservoir as a case study, we proposed a method of aggregating land use quantity and intensity to build a new land use indicator and investigated its explanation empower on water quality. Six nutrient concentrations from 52 sub-watersheds covering the whole catchment were used to characterize spatial distributions of water eutrophication. Based on spatial techniques and empirical conversion coefficients, combined remote sensing with socio-economic statistical data, land use intensity was measured and mapped visually. Then the new land use indicator was calculated and linked to nutrient concentrations by Pearson correlation coefficients. Results demonstrated that our new land use indicator incorporating intensity information can quantify the potential different nutrients exporting abilities from land uses. Comparing to traditional indicators only characterized by land use quantity, most Pearson correlation coefficients between new indicator and water nutrient concentrations increased. New information enhanced the explanatory power of land use on water nutrient concentrations. Then it can help better understand the impact of land use on water quality and guide land use management for supporting decision making.

The observation-based relationships between PM2.5 and AOD over China

NASA Astrophysics Data System (ADS)

Xin, Jinyuan; Gong, Chongshui; Liu, Zirui; Cong, Zhiyuan; Gao, Wenkang; Song, Tao; Pan, Yuepeng; Sun, Yang; Ji, Dongsheng; Wang, Lili; Tang, Guiqian; Wang, Yuesi

2016-09-01

This is the first investigation of the generalized linear regressions of PM2.5 and aerosol optical depth (AOD) with the Campaign on atmospheric Aerosol Research-China network over the large high-concentration aerosol region during the period from 2012 to 2013. The map of the PM2.5 and AOD levels showed large spatial differences in the aerosol concentrations and aerosol optical properties over China. The ranges of the annual mean PM2.5 and AOD were 10-117 µg/m3 and 0.12-1.11 from the clean regions to seriously polluted regions, from the almost "arctic" and the Tibetan Plateau to tropical environments. There were significant spatial agreements and correlations between the PM2.5 and AOD. However, the linear regression functions (PM2.5 = A*AOD + B) exhibited large differences in different regions and seasons. The slopes (A) were from 13 to 90, the intercepts (B) were from 0.8 to 33.3, and the correlation coefficients (R2) ranged from 0.06 to 0.75. The slopes (A) were much higher in the north (41-99) than in the south (13-64) because the extinction efficiency of hygroscopic aerosol was rapidly increasing with the increasing humidity from the dry north to the humid south. Meanwhile, the intercepts (B) were generally lower, and the correlation coefficients (R2) were much higher in the dry north than in the humid south. There was high consistency of AOD versus PM2.5 for all sites in three ranges of the atmospheric column precipitable water vapor (PWV). The segmented linear regression functions were y = 84.66x + 9.85 (PWV < 1.0), y = 69.47x + 11.87 (1.0 < PWV < 2.5), and y = 52.37x + 8.59 (PWV > 2.5). The correlation coefficients (R2) were high from 0.64 to 0.70 across China.

The threshold signal:noise ratio in the perception of fragmented figures.

PubMed

Merkul'ev, A V; Pronin, S V; Semenov, L A; Foreman, N; Chikhman, V N; Shelepin, Yu E

2006-01-01

Perception thresholds were measured for fragmented outline figures (the Gollin test). A new approach to the question of the perception of incomplete images was developed. In this approach, figure fragmentation consisted of masking with multiplicative texture-like noise--this interference was termed "invisible" masking. The first series of studies established that the "similarity" between the amplitude-frequency spectra of test figures and "invisible" masks, expressed as a linear correlation coefficient, had significant effects on the recognition thresholds of these figures. The second series of experiments showed that progressing formation of the figures was accompanied by increases in the correlation between their spatial-frequency characteristics and the corresponding characteristics of the incomplete figure, while the correlation with the "invisible" mask decreased. It is suggested that the ratio of the correlation coefficients, characterizing the "similarity" of the fragmented figure with the intact figure and the "invisible" mask, corresponds to the signal:noise ratio. The psychophysical recognition threshold for figures for naive subjects not familiar with the test image alphabet was reached after the particular level of fragmentation at which this ratio was unity.

Comparison of different interpolation methods for spatial distribution of soil organic carbon and some soil properties in the Black Sea backward region of Turkey

NASA Astrophysics Data System (ADS)

Göl, Ceyhun; Bulut, Sinan; Bolat, Ferhat

2017-10-01

The purpose of this research is to compare the spatial variability of soil organic carbon (SOC) in four adjacent land uses including the cultivated area, the grassland area, the plantation area and the natural forest area in the semi - arid region of Black Sea backward region of Turkey. Some of the soil properties, including total nitrogen, SOC, soil organic matter, and bulk density were measured on a grid with a 50 m sampling distance on the top soil (0-15 cm depth). Accordingly, a total of 120 samples were taken from the four adjacent land uses. Data was analyzed using geostatistical methods. The methods used were: Block kriging (BK), co - kriging (CK) with organic matter, total nitrogen and bulk density as auxiliary variables and inverse distance weighting (IDW) methods with the power of 1, 2 and 4. The methods were compared using a performance criteria that included root mean square error (RMSE), mean absolute error (MAE) and the coefficient of correlation (r). The one - way ANOVA test showed that differences between the natural (0.6653 ± 0.2901) - plantation forest (0.7109 ± 0.2729) areas and the grassland (1.3964 ± 0.6828) - cultivated areas (1.5851 ± 0.5541) were statistically significant at 0.05 level (F = 28.462). The best model for describing spatially variation of SOC was CK with the lowest error criteria (RMSE = 0.3342, MAE = 0.2292) and the highest coefficient of correlation (r = 0.84). The spatial structure of SOC could be well described by the spherical model. The nugget effect indicated that SOC was moderately dependent on the study area. The error distributions of the model showed that the improved model was unbiased in predicting the spatial distribution of SOC. This study's results revealed that an explanatory variable linked SOC increased success of spatial interpolation methods. In subsequent studies, this case should be taken into account for reaching more accurate outputs.

Implication of the first decision on visual information-sampling in the spatial frequency domain in pulmonary nodule recognition

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Manning, David; Donovan, Tim; Dix, Alan

2010-02-01

Aim: To investigate the impact on visual sampling strategy and pulmonary nodule recognition of image-based properties of background locations in dwelled regions where the first overt decision was made. . Background: Recent studies in mammography show that the first overt decision (TP or FP) has an influence on further image reading including the correctness of the following decisions. Furthermore, the correlation between the spatial frequency properties of the local background following decision sites and the first decision correctness has been reported. Methods: Subjects with different radiological experience were eye tracked during detection of pulmonary nodules from PA chest radiographs. Number of outcomes and the overall quality of performance are analysed in terms of the cases where correct or incorrect decisions were made. JAFROC methodology is applied. The spatial frequency properties of selected local backgrounds related to a certain decisions were studied. ANOVA was used to compare the logarithmic values of energy carried by non redundant stationary wavelet packet coefficients. Results: A strong correlation has been found between the number of TP as a first decision and the JAFROC score (r = 0.74). The number of FP as a first decision was found negatively correlated with JAFROC (r = -0.75). Moreover, the differential spatial frequency profiles outcomes depend on the first choice correctness.

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

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

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

NASA Astrophysics Data System (ADS)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

CORRELATED AND ZONAL ERRORS OF GLOBAL ASTROMETRIC MISSIONS: A SPHERICAL HARMONIC SOLUTION

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

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Correlated and Zonal Errors of Global Astrometric Missions: A Spherical Harmonic Solution

NASA Astrophysics Data System (ADS)

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.; Hennessy, G. S.; Berghea, C. T.; Dudik, R. P.; Schmitt, H. R.

2012-07-01

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Spatially dependent diffusion coefficient as a model for pH sensitive microgel particles in microchannels

PubMed Central

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

Extension and Application of High-Speed Digital Imaging Analysis Via Spatiotemporal Correlation and Eigenmode Analysis of Vocal Fold Vibration Before and After Polyp Excision.

PubMed

Wang, Jun-Sheng; Olszewski, Emily; Devine, Erin E; Hoffman, Matthew R; Zhang, Yu; Shao, Jun; Jiang, Jack J

2016-08-01

To evaluate the spatiotemporal correlation of vocal fold vibration using eigenmode analysis before and after polyp removal and explore the potential clinical relevance of spatiotemporal analysis of correlation length and entropy as quantitative voice parameters. We hypothesized that increased order in the vibrating signal after surgical intervention would decrease the eigenmode-based entropy and increase correlation length. Prospective case series. Forty subjects (23 males, 17 females) with unilateral (n = 24) or bilateral (n = 16) polyps underwent polyp removal. High-speed videoendoscopy was performed preoperatively and 2 weeks postoperatively. Spatiotemporal analysis was performed to determine entropy, quantification of signal disorder, correlation length, size, and spatially ordered structure of vocal fold vibration in comparison to full spatial consistency. The signal analyzed consists of the vibratory pattern in space and time derived from the high-speed video glottal area contour. Entropy decreased (Z = -3.871, P < .001) and correlation length increased (t = -8.913, P < .001) following polyp excision. The intraclass correlation coefficients (ICC) for correlation length and entropy were 0.84 and 0.93. Correlation length and entropy are sensitive to mass lesions. These parameters could potentially be used to augment subjective visualization after polyp excision when evaluating procedural efficacy. © The Author(s) 2016.

Characterizing regional soil mineral composition using spectroscopyand geostatistics

USGS Publications Warehouse

Mulder, V.L.; de Bruin, S.; Weyermann, J.; Kokaly, Raymond F.; Schaepman, M.E.

2013-01-01

This work aims at improving the mapping of major mineral variability at regional scale using scale-dependent spatial variability observed in remote sensing data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and statistical methods were combined with laboratory-based mineral characterization of field samples to create maps of the distributions of clay, mica and carbonate minerals and their abundances. The Material Identification and Characterization Algorithm (MICA) was used to identify the spectrally-dominant minerals in field samples; these results were combined with ASTER data using multinomial logistic regression to map mineral distributions. X-ray diffraction (XRD)was used to quantify mineral composition in field samples. XRD results were combined with ASTER data using multiple linear regression to map mineral abundances. We testedwhether smoothing of the ASTER data to match the scale of variability of the target sample would improve model correlations. Smoothing was donewith Fixed Rank Kriging (FRK) to represent the mediumand long-range spatial variability in the ASTER data. Stronger correlations resulted using the smoothed data compared to results obtained with the original data. Highest model accuracies came from using both medium and long-range scaled ASTER data as input to the statistical models. High correlation coefficients were obtained for the abundances of calcite and mica (R2 = 0.71 and 0.70, respectively). Moderately-high correlation coefficients were found for smectite and kaolinite (R2 = 0.57 and 0.45, respectively). Maps of mineral distributions, obtained by relating ASTER data to MICA analysis of field samples, were found to characterize major soil mineral variability (overall accuracies for mica, smectite and kaolinite were 76%, 89% and 86% respectively). The results of this study suggest that the distributions of minerals and their abundances derived using FRK-smoothed ASTER data more closely match the spatial variability of soil and environmental properties at regional scale.

Interactions of satellite-speed helium atoms with satellite surfaces. 3: Drag coefficients from spatial and energy distributions of reflected helium atoms

NASA Technical Reports Server (NTRS)

Sharma, P. K.; Knuth, E. L.

1977-01-01

Spatial and energy distributions of helium atoms scattered from an anodized 1235-0 aluminum surface as well as the tangential and normal momentum accommodation coefficients calculated from these distributions are reported. A procedure for calculating drag coefficients from measured values of spatial and energy distributions is given. The drag coefficient calculated for a 6061 T-6 aluminum sphere is included.

Kinetic evolution and correlation of fluctuations in an expanding quark gluon plasma

NASA Astrophysics Data System (ADS)

Sarwar, Golam; Alam, Jan-E.

2018-03-01

Evolution of spatially anisotropic perturbation created in the system formed after Relativistic Heavy Ion Collisions has been studied. The microscopic evolution of the fluctuations has been examined within the ambit of Boltzmann Transport Equation (BTE) in a hydrodynamically expanding background. The expansion of the background composed of quark gluon plasma (QGP) is treated within the framework of relativistic hydrodynamics. Spatial anisotropic fluctuations with different geometries have been evolved through Boltzmann equation. It is observed that the trace of such fluctuation survives the evolution. Within the relaxation time approximation, analytical results have been obtained for the evolution of these anisotropies. Explicit relations between fluctuations and transport coefficients have been derived. The mixing of various Fourier (or k) modes of the perturbations during the evolution of the system has been explicitly demonstrated. This study is very useful in understanding the presumption that the measured anisotropies in the data from heavy ion collisions at relativistic energies imitate the initial state effects. The evolution of correlation function for the perturbation in pressure has been studied and shows that the initial correlation between two neighbouring points in real space evolves to a constant value at later time which gives rise to Dirac delta function for the correlation function in Fourier space. The power spectrum of the fluctuation in thermodynamic quantities (like temperature estimated in this work) can be connected to the fluctuation in transverse momentum of the thermal hadrons measured experimentally. The bulk viscous coefficient of the QGP has been estimated by using correlations of pressure fluctuation with the help of Green-Kubo relation. Angular power spectrum of the anisotropies has been estimated in the appendix.

Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

NASA Astrophysics Data System (ADS)

Wheeler, David C.; Waller, Lance A.

2009-03-01

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.

Spatiotemporal patterns of correlation between atmospheric nitrogen dioxide and aerosols over South Asia

NASA Astrophysics Data System (ADS)

ul-Haq, Zia; Tariq, Salman; Ali, Muhammad

2017-10-01

An accurate knowledge is needed on the complex relation between atmospheric trace gasses and aerosol variability and their sources to explain trace gases-aerosols-climate interaction and next-generation modeling of climate change and air quality. In this regard, we have used tropospheric Nitrogen Dioxide (NO2), Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) obtained from satellite-based Ozone Monitoring Instrument (OMI)/Aura and Moderate-Resolution Imaging Spectroradiometer (MODIS)/Aqua over South Asia. NO2-AOD correlation with coefficient r = 0.49 is determined over the landmass of South Asia during 2005-2015. Yearly mean NO2-AOD correlation over South Asia shows large variations ranging from r = 0.32 to 0.86 in 2008 and 2009, respectively. The highest correlation ( r = 0.66) is seen over eastern regions of Bangladesh and India, as well as adjoining areas of western Myanmar mostly linked to anthropogenic activities. A significant correlation ( r = 0.59) associated with natural causes is found over some parts of Sistan region, located at the borders of Iran, Pakistan and Afghanistan, and adjoining territory. We find significant positive correlations for monsoon and post-monsoon seasons with r = 0.50 and r = 0.61, respectively. A linear regression on the annual correlation coefficients data suggests that NO2-AOD correlation is strengthening with an increase of 12.9% over South Asia during the study period. The spatial distribution of data slopes reveals positive trends in NO2-AOD correlation over megacities Lahore, Dhaka, Mumbai and Kolkata linked to growing anthropogenic activities. Singrauli city (India) has the highest correlation ( r = 0.62) and 35% increase in correlation coefficient value per year. A negative correlation is observed for megacity Karachi ( r = -0.37) suggesting the non-commonality of NO2 and aerosols emission sources. AE has also been used to discuss its correlation with NO2 over the areas with dominance of fine-mode aerosols.

Phase correlation imaging of unlabeled cell dynamics

NASA Astrophysics Data System (ADS)

Ma, Lihong; Rajshekhar, Gannavarpu; Wang, Ru; Bhaduri, Basanta; Sridharan, Shamira; Mir, Mustafa; Chakraborty, Arindam; Iyer, Rajashekar; Prasanth, Supriya; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel

2016-09-01

We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially-resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport. Specifically, we show that PCI can extract quantitatively the diffusion coefficient map associated with live cells, as well as standard Brownian particles. Due to its high sensitivity to mass transport, PCI can be applied to studying the integrity of actin polymerization dynamics. Our results indicate that the cyto-D treatment blocking the actin polymerization has a dominant effect at the large spatial scales, in the region surrounding the cell. We found that PCI can distinguish between senescent and quiescent cells, which is extremely difficult without using specific markers currently. We anticipate that PCI will be used alongside established, fluorescence-based techniques to enable valuable new studies of cell function.

Hyperspectral diffuse reflectance for determination of the optical properties of milk and fruit and vegetable juices

NASA Astrophysics Data System (ADS)

Qin, Jianwei; Lu, Renfu

2005-11-01

Absorption and reduced scattering coefficients are two fundamental optical properties for turbid biological materials. This paper presents the technique and method of using hyperspectral diffuse reflectance for fast determination of the optical properties of fruit and vegetable juices and milks. A hyperspectral imaging system was used to acquire spatially resolved steady-state diffuse reflectance over the spectral region between 530 and 900 nm from a variety of fruit and vegetable juices (citrus, grapefruit, orange, and vegetable) and milks with different fat levels (full, skim and mixed). The system collected diffuse reflectance in the source-detector separation range from 1.1 to 10.0 mm. The hyperspectral reflectance data were analyzed by using a diffusion theory model for semi-infinite homogeneous media. The absorption and reduced scattering coefficients of the fruit and vegetable juices and milks were extracted by inverse algorithms from the scattering profiles for wavelengths of 530-900 nm. Values of the absorption and reduced scattering coefficient at 650 nm were highly correlated to the fat content of the milk samples with the correlation coefficient of 0.990 and 0.989, respectively. The hyperspectral imaging technique can be extended to the measurement of other liquid and solid foods in which light scattering is dominant.

Analysis on variability and trend in Antarctic sea ice albedo between 1983 and 2009

NASA Astrophysics Data System (ADS)

Seo, Minji; Kim, Hyun-cheol; Choi, Sungwon; Lee, Kyeong-sang; Han, Kyung-soo

2017-04-01

Sea ice is key parameter in order to understand the cryosphere climate change. Several studies indicate the different trend of sea ice between Antarctica and Arctic. Albedo is important factor for understanding the energy budget and factors for observing of environment changes of Cryosphere such as South Pole, due to it mainly covered by ice and snow with high albedo value. In this study, we analyzed variability and trend of long-term sea ice albedo data to understand the changes of sea ice over Antarctica. In addiction, sea ice albedo researched the relationship with Antarctic oscillation in order to determine the atmospheric influence. We used the sea ice albedo data at The Satellite Application Facility on Climate Monitoring and Antarctic Oscillation data at NOAA Climate Prediction Center (CPC). We analyzed the annual trend in albedo using linear regression to understand the spatial and temporal tendency. Antarctic sea ice albedo has two spatial trend. Weddle sea / Ross sea sections represent a positive trend (0.26% ˜ 0.04% yr-1) and Bellingshausen Amundsen sea represents a negative trend (- 0.14 ˜ -0.25%yr-1). Moreover, we performed the correlation analysis between albedo and Antarctic oscillation. As a results, negative area indicate correlation coefficient of - 0.3639 and positive area indicates correlation coefficient of - 0.0741. Theses results sea ice albedo has regional trend according to ocean. Decreasing sea ice trend has negative relationship with Antarctic oscillation, its represent a possibility that sea ice influence atmospheric factor.

Improving Photometry and Stellar Signal Preservation with Pixel-Level Systematic Error Correction

NASA Technical Reports Server (NTRS)

Kolodzijczak, Jeffrey J.; Smith, Jeffrey C.; Jenkins, Jon M.

2013-01-01

The Kepler Mission has demonstrated that excellent stellar photometric performance can be achieved using apertures constructed from optimally selected CCD pixels. The clever methods used to correct for systematic errors, while very successful, still have some limitations in their ability to extract long-term trends in stellar flux. They also leave poorly correlated bias sources, such as drifting moiré pattern, uncorrected. We will illustrate several approaches where applying systematic error correction algorithms to the pixel time series, rather than the co-added raw flux time series, provide significant advantages. Examples include, spatially localized determination of time varying moiré pattern biases, greater sensitivity to radiation-induced pixel sensitivity drops (SPSDs), improved precision of co-trending basis vectors (CBV), and a means of distinguishing the stellar variability from co-trending terms even when they are correlated. For the last item, the approach enables physical interpretation of appropriately scaled coefficients derived in the fit of pixel time series to the CBV as linear combinations of various spatial derivatives of the pixel response function (PRF). We demonstrate that the residuals of a fit of soderived pixel coefficients to various PRF-related components can be deterministically interpreted in terms of physically meaningful quantities, such as the component of the stellar flux time series which is correlated with the CBV, as well as, relative pixel gain, proper motion and parallax. The approach also enables us to parameterize and assess the limiting factors in the uncertainties in these quantities.

Spherical disharmonics in the Earth sciences and the spatial solution: Ridges, hotspots, slabs, geochemistry and tomography correlations

NASA Technical Reports Server (NTRS)

Ray, Terrill W.; Anderson, Don L.

1994-01-01

There is increasing use of statistical correlations between geophysical fields and between geochemical and geophysical fields in attempts to understand how the Earth works. Typically, such correlations have been based on spherical harmonic expansions. The expression of functions on the sphere as spherical harmonic series has many pitfalls, especially if the data are nonuniformly and/or sparsely sampled. Many of the difficulties involved in the use of spherical harmonic expansion techniques can be avoided through the use of spatial domain correlations, but this introduces other complications, such as the choice of a sampling lattice. Additionally, many geophysical and geochemical fields fail to satisfy the assumptions of standard statistical significance tests. This is especially problematic when the data values to be correlated with a geophysical field were collected at sample locations which themselves correlate with that field. This paper examines many correlations which have been claimed in the past between geochemistry and mantle tomography and between hotspot, ridge, and slab locations and tomography using both spherical harmonic coefficient correlations and spatial domain correlations. No conclusively significant correlations are found between isotopic geochemistry and mantle tomography. The Crough and Jurdy (short) hotspot location list shows statistically significant correlation with lowermost mantle tomography for degree 2 of the spherical harmonic expansion, but there are no statistically significant correlations in the spatial case. The Vogt (long) hotspot location list does not correlate with tomography anywhere in the mantle using either technique. Both hotspot lists show a strong correlation between hotspot locations and geoid highs when spatially correlated, but no correlations are revealed by spherical harmonic techniques. Ridge locations do not show any statistically significant correlations with tomography, slab locations, or the geoid; the strongest correlation is with lowermost mantle tomography, which is probably spurious. The most striking correlations are between mantle tomography and post-Pangean subducted slabs. The integrated locations of slabs correlate strongly with fast areas near the transition zone and the core-mantle boundary and with slow regions from 1022-1248 km depth. This seems to be consistent with the 'avalanching' downwellings which have been indicated by models of the mantle which include an endothermic phase transition at the 670-km discontinuity, although this is not a unique interpretation. Taken as a whole, these results suggest that slabs and associated cold downwellings are the dominant feature of mantle convection. Hotspot locations are no better correlated with lower mantle tomography than are ridge locations.

Bacterial taxa–area and distance–decay relationships in marine environments

PubMed Central

Zinger, L; Boetius, A; Ramette, A

2014-01-01

The taxa–area relationship (TAR) and the distance–decay relationship (DDR) both describe spatial turnover of taxa and are central patterns of biodiversity. Here, we compared TAR and DDR of bacterial communities across different marine realms and ecosystems at the global scale. To obtain reliable global estimates for both relationships, we quantified the poorly assessed effects of sequencing depth, rare taxa removal and number of sampling sites. Slope coefficients of bacterial TARs were within the range of those of plants and animals, whereas slope coefficients of bacterial DDR were much lower. Slope coefficients were mostly affected by removing rare taxa and by the number of sampling sites considered in the calculations. TAR and DDR slope coefficients were overestimated at sequencing depth <4000 sequences per sample. Noticeably, bacterial TAR and DDR patterns did not correlate with each other both within and across ecosystem types, suggesting that (i) TAR cannot be directly derived from DDR and (ii) TAR and DDR may be influenced by different ecological factors. Nevertheless, we found marine bacterial TAR and DDR to be steeper in ecosystems associated with high environmental heterogeneity or spatial isolation, namely marine sediments and coastal environments compared with pelagic ecosystems. Hence, our study provides information on macroecological patterns of marine bacteria, as well as methodological and conceptual insights, at a time when biodiversity surveys increasingly make use of high-throughput sequencing technologies. PMID:24460915

The spatiotemporal characteristics of environmental hazards caused by offshore oil and gas operations in the Gulf of Mexico.

PubMed

Meng, Qingmin

2016-09-15

Marine ecosystems are home to a host of numerous species ranging from tiny planktonic organisms, fishes, and birds, to large mammals such as the whales, manatees, and seals. However, human activities such as offshore oil and gas operations increasingly threaten marine and coastal ecosystems, for which there has been little exploration into the spatial and temporal risks of offshore oil operations. Using the Gulf of Mexico, one of the world's hottest spots of offshore oil and gas mining, as the study area, we propose a spatiotemporal approach that integrates spatial statistics and geostatistics in a geographic information system environment to provide insight to environmental management and decision making for oil and gas operators, coastal communities, local governments, and the federal government. We use the records from 1995 to 2015 of twelve types of hazards caused by offshore oil and gas operations, and analyze them spatially over a five year period. The spatial clusters of these hazards are analyzed and mapped using Getis-Ord Gi and local Moran's I statistics. We then design a spatial correlation coefficient matrix for multivariate spatial correlation, which is the ratio of the cross variogram of two types of hazards to the product of the variograms of the two hazards, showing a primary understanding of the degrees of spatial correlation among the twelve types hazards. To the best of our knowledge, it is the first application of spatiotemporal analysis methods to environmental hazards caused by offshore oil and gas operations; the proposed methods can be applied to other regions for the management and monitoring of environmental hazards caused by offshore oil operations. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial variations in shear stress in a 3-D bifurcation model at low Reynolds numbers.

PubMed

Rouhanizadeh, Mahsa; Lin, Tiantian C; Arcas, Diego; Hwang, Juliana; Hsiai, Tzung K

2005-10-01

Real-time wall shear stress is difficult to monitor precisely because it varies in space and time. Microelectromechanical systems sensor provides high spatial resolution to resolve variations in shear stress in a 3-D bifurcation model for small-scaled hemodynamics. At low Reynolds numbers from 1.34 to 6.7 skin friction coefficients (C(f)) varied circumferentially by a factor of two or more within the bifurcation. At a Reynolds number of 6.7, the C(f) value at the lateral wall of the bifurcation along the 270 degree plane was 7.1, corresponding to a shear stress value of 0.0061 dyn/cm(2). Along the 180 degree plane, C(f) was 13 or 0.0079 dyn/cm(2), and at the medial wall along the 90 degree plane, C(f) was 10.3 or 0.0091 dyn/cm(2). The experimental skin friction coefficients correlated with values derived from the Navier-Stokes solutions.

Measuring and imaging diffusion with multiple scan speed image correlation spectroscopy.

PubMed

Gröner, Nadine; Capoulade, Jérémie; Cremer, Christoph; Wachsmuth, Malte

2010-09-27

The intracellular mobility of biomolecules is determined by transport and diffusion as well as molecular interactions and is crucial for many processes in living cells. Methods of fluorescence microscopy like confocal laser scanning microscopy (CLSM) can be used to characterize the intracellular distribution of fluorescently labeled biomolecules. Fluorescence correlation spectroscopy (FCS) is used to describe diffusion, transport and photo-physical processes quantitatively. As an alternative to FCS, spatially resolved measurements of mobilities can be implemented using a CLSM by utilizing the spatio-temporal information inscribed into the image by the scan process, referred to as raster image correlation spectroscopy (RICS). Here we present and discuss an extended approach, multiple scan speed image correlation spectroscopy (msICS), which benefits from the advantages of RICS, i.e. the use of widely available instrumentation and the extraction of spatially resolved mobility information, without the need of a priori knowledge of diffusion properties. In addition, msICS covers a broad dynamic range, generates correlation data comparable to FCS measurements, and allows to derive two-dimensional maps of diffusion coefficients. We show the applicability of msICS to fluorophores in solution and to free EGFP in living cells.

Support vector machine in crash prediction at the level of traffic analysis zones: Assessing the spatial proximity effects.

PubMed

Dong, Ni; Huang, Helai; Zheng, Liang

2015-09-01

In zone-level crash prediction, accounting for spatial dependence has become an extensively studied topic. This study proposes Support Vector Machine (SVM) model to address complex, large and multi-dimensional spatial data in crash prediction. Correlation-based Feature Selector (CFS) was applied to evaluate candidate factors possibly related to zonal crash frequency in handling high-dimension spatial data. To demonstrate the proposed approaches and to compare them with the Bayesian spatial model with conditional autoregressive prior (i.e., CAR), a dataset in Hillsborough county of Florida was employed. The results showed that SVM models accounting for spatial proximity outperform the non-spatial model in terms of model fitting and predictive performance, which indicates the reasonableness of considering cross-zonal spatial correlations. The best model predictive capability, relatively, is associated with the model considering proximity of the centroid distance by choosing the RBF kernel and setting the 10% of the whole dataset as the testing data, which further exhibits SVM models' capacity for addressing comparatively complex spatial data in regional crash prediction modeling. Moreover, SVM models exhibit the better goodness-of-fit compared with CAR models when utilizing the whole dataset as the samples. A sensitivity analysis of the centroid-distance-based spatial SVM models was conducted to capture the impacts of explanatory variables on the mean predicted probabilities for crash occurrence. While the results conform to the coefficient estimation in the CAR models, which supports the employment of the SVM model as an alternative in regional safety modeling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones.

PubMed

Yang, Qiulong; Yang, Kunde; Cao, Ran; Duan, Shunli

2018-01-23

Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near the bottom in deep ocean direct-arrival zones.

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones

PubMed Central

Yang, Qiulong; Yang, Kunde; Cao, Ran; Duan, Shunli

2018-01-01

Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near the bottom in deep ocean direct-arrival zones. PMID:29360793

A geostatistical state-space model of animal densities for stream networks.

PubMed

Hocking, Daniel J; Thorson, James T; O'Neil, Kyle; Letcher, Benjamin H

2018-06-21

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty under-estimated. We developed a novel statistical method to account for spatio-temporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 years. Increasing the number of survey sites within the network improved the performance of the non-spatial model but only marginally improved the density estimates in the spatio-temporal model. We applied this model to Brook Trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 years from 1981 - 2014. We found the model including temporal and spatio-temporal autocorrelation best described young-of-the-year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately-high spatio-temporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatio-temporal correlation and higher temporal autocorrelation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

NASA Astrophysics Data System (ADS)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property helps to overcome a significant computational bottleneck of geostatistical models due to the poor scaling of the matrix inversion [4,5]. We present applications to real and simulated data sets, including the Walker lake data, and we investigate the SLI performance using various statistical cross validation measures. References [1] T. Hofmann, B. Schlkopf, A.J. Smola, Annals of Statistics, 36, 1171-1220 (2008). [2] D. T. Hristopulos, SIAM Journal on Scientific Computing, 24(6): 2125-2162 (2003). [3] D. T. Hristopulos and S. N. Elogne, IEEE Transactions on Signal Processing, 57(9): 3475-3487 (2009) [4] G. Jona Lasinio, G. Mastrantonio, and A. Pollice, Statistical Methods and Applications, 22(1):97-112 (2013) [5] Sun, Y., B. Li, and M. G. Genton (2012). Geostatistics for large datasets. In: Advances and Challenges in Space-time Modelling of Natural Events, Lecture Notes in Statistics, pp. 55-77. Springer, Berlin-Heidelberg.

Multi-frequency interpolation in spiral magnetic resonance fingerprinting for correction of off-resonance blurring.

PubMed

Ostenson, Jason; Robison, Ryan K; Zwart, Nicholas R; Welch, E Brian

2017-09-01

Magnetic resonance fingerprinting (MRF) pulse sequences often employ spiral trajectories for data readout. Spiral k-space acquisitions are vulnerable to blurring in the spatial domain in the presence of static field off-resonance. This work describes a blurring correction algorithm for use in spiral MRF and demonstrates its effectiveness in phantom and in vivo experiments. Results show that image quality of T1 and T2 parametric maps is improved by application of this correction. This MRF correction has negligible effect on the concordance correlation coefficient and improves coefficient of variation in regions of off-resonance relative to uncorrected measurements. Copyright © 2017 Elsevier Inc. All rights reserved.

Lung Cancer Mortality and Radon Concentration in a Chronically Exposed Neighborhood in Chihuahua, Mexico: A Geospatial Analysis

PubMed Central

Hinojosa de la Garza, Octavio R.; Sanín, Luz H.; Montero Cabrera, María Elena; Serrano Ramirez, Korina Ivette; Martínez Meyer, Enrique; Reyes Cortés, Manuel

2014-01-01

This study correlated lung cancer (LC) mortality with statistical data obtained from government public databases. In order to asses a relationship between LC deaths and radon accumulation in dwellings, indoor radon concentrations were measured with passive detectors randomly distributed in Chihuahua City. Kriging (K) and Inverse-Distance Weighting (IDW) spatial interpolations were carried out. Deaths were georeferenced and Moran's I correlation coefficients were calculated. The mean values (over n = 171) of the interpolation of radon concentrations of deceased's dwellings were 247.8 and 217.1 Bq/m3, for K and IDW, respectively. Through the Moran's I values obtained, correspondingly equal to 0.56 and 0.61, it was evident that LC mortality was directly associated with locations with high levels of radon, considering a stable population for more than 25 years, suggesting spatial clustering of LC deaths due to indoor radon concentrations. PMID:25165752

Novel measurement of spreading pattern of influenza epidemic by using weighted standard distance method: retrospective spatial statistical study of influenza, Japan, 1999–2009

PubMed Central

2012-01-01

Background Annual influenza epidemics occur worldwide resulting in considerable morbidity and mortality. Spreading pattern of influenza is not well understood because it is often hampered by the quality of surveillance data that limits the reliability of analysis. In Japan, influenza is reported on a weekly basis from 5,000 hospitals and clinics nationwide under the scheme of the National Infectious Disease Surveillance. The collected data are available to the public as weekly reports which were summarized into number of patient visits per hospital or clinic in each of the 47 prefectures. From this surveillance data, we analyzed the spatial spreading patterns of influenza epidemics using weekly weighted standard distance (WSD) from the 1999/2000 through 2008/2009 influenza seasons in Japan. WSD is a single numerical value representing the spatial compactness of influenza outbreak, which is small in case of clustered distribution and large in case of dispersed distribution. Results We demonstrated that the weekly WSD value or the measure of spatial compactness of the distribution of reported influenza cases, decreased to its lowest value before each epidemic peak in nine out of ten seasons analyzed. The duration between the lowest WSD week and the peak week of influenza cases ranged from minus one week to twenty weeks. The duration showed significant negative association with the proportion of influenza A/H3N2 cases in early phase of each outbreak (correlation coefficient was −0.75, P = 0.012) and significant positive association with the proportion of influenza B cases in the early phase (correlation coefficient was 0.64, P = 0.045), but positively correlated with the proportion of influenza A/H1N1 strain cases (statistically not significant). It is assumed that the lowest WSD values just before influenza peaks are due to local outbreak which results in small standard distance values. As influenza cases disperse nationwide and an epidemic reaches its peak, WSD value changed to be a progressively increasing. Conclusions The spatial distribution of nationwide influenza outbreak was measured by using a novel WSD method. We showed that spreading rate varied by type and subtypes of influenza virus using WSD as a spatial indicator. This study is the first to show a relationship between influenza epidemic trend by type/subtype and spatial distribution of influenza nationwide in Japan. PMID:22713508

Evaluation of the Gini Coefficient in Spatial Scan Statistics for Detecting Irregularly Shaped Clusters

PubMed Central

Kim, Jiyu; Jung, Inkyung

2017-01-01

Spatial scan statistics with circular or elliptic scanning windows are commonly used for cluster detection in various applications, such as the identification of geographical disease clusters from epidemiological data. It has been pointed out that the method may have difficulty in correctly identifying non-compact, arbitrarily shaped clusters. In this paper, we evaluated the Gini coefficient for detecting irregularly shaped clusters through a simulation study. The Gini coefficient, the use of which in spatial scan statistics was recently proposed, is a criterion measure for optimizing the maximum reported cluster size. Our simulation study results showed that using the Gini coefficient works better than the original spatial scan statistic for identifying irregularly shaped clusters, by reporting an optimized and refined collection of clusters rather than a single larger cluster. We have provided a real data example that seems to support the simulation results. We think that using the Gini coefficient in spatial scan statistics can be helpful for the detection of irregularly shaped clusters. PMID:28129368

Effects of variations of stage and flux at different frequencies on the estimates using river stage tomography

NASA Astrophysics Data System (ADS)

Wang, Y. L.; Yeh, T. C. J.; Wen, J. C.

2017-12-01

This study is to investigate the ability of river stage tomography to estimate the spatial distribution of hydraulic transmissivity (T), storage coefficient (S), and diffusivity (D) in groundwater basins using information of groundwater level variations induced by periodic variations of stream stage, and infiltrated flux from the stream boundary. In order to accomplish this objective, the sensitivity and correlation of groundwater heads with respect to the hydraulic properties is first conducted to investigate the spatial characteristics of groundwater level in response to the stream variations at different frequencies. Results of the analysis show that the spatial distributions of the sensitivity of heads at an observation well in response to periodic river stage variations are highly correlated despite different frequencies. On the other hand, the spatial patterns of the sensitivity of the observed head to river flux boundaries at different frequencies are different. Specifically, the observed head is highly correlated with T at the region between the stream and observation well when the high-frequency periodic flux is considered. On the other hand, it is highly correlated with T at the region between monitoring well and the boundary opposite to the stream when the low-frequency periodic flux is prescribed to the stream. We also find that the spatial distributions of the sensitivity of observed head to S variation are highly correlated with all frequencies in spite of heads or fluxes stream boundary. Subsequently, the differences of the spatial correlations of the observed heads to the hydraulic properties under the head and flux boundary conditions are further investigated by an inverse model (i.e., successive stochastic linear estimator). This investigation uses noise-free groundwater and stream data of a synthetic aquifer, where aquifer heterogeneity is known exactly. The ability of river stage tomography is then tested with these synthetic data sets to estimate T, S, and D distribution. The results reveal that boundary flux variations with different frequencies contain different information about the aquifer characteristics while the head boundary does not.

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Spatiotemporal investigation of long-term seasonal temperature variability in Libya

NASA Astrophysics Data System (ADS)

Elsharkawy, S. G.; Elmallah, E. S.

2016-09-01

Throughout this work, spatial and temporal variations of seasonal surface air temperature have been investigated. Moreover, the effects of relative internal (teleconnection) and external (solar) forcing on surface air temperature variability have been examined. Seasonal temperature time series covering 30 different meteorological locations and lasting over the last century are considered. These locations are classified into two groups based on their spatial distribution. One represents Coast Libya Surface Air Temperature (CLSAT), contains 19 locations, and the other represents Desert Libya Surface Air Temperature (DLSAT), contains 11 locations. Average temperature departure test is applied to investigate the nature of temperature variations. Temperature trends are analyzed using the nonparametric Mann-Kendall test and their coefficients are calculated using Sen's slope estimate. Cross-correlation and spectral analysis techniques are also applied. Our results showed temperature deviation from average within a band of ± 2°C at coast region, while ± 4°C at desert region. Extreme behavior intensions between summer and winter temperatures at coast region are noticed. Segmentation process declared reversal cooling/warming behavior within temperature records for all seasons. Desert region shows warming trend for all seasons with higher coefficients than obtained at coast region. Results obtained for spectral analysis show different short and medium signals and concluded that not only the spectral properties are different for different geographical regions but also different for different climatic seasons on regional scale as well. Cross-correlation results showed that highest influence for Rz upon coastal temperature is always in conjunction with highest influence of NAO upon coastal temperature during the period 1981-2010. Desert region does not obey this phenomenon, where highest temperature-NAO correlations at desert during autumn and winter seasons are not accompanied with highest correlations for temperature-Rz.

Binocular Neurons in Parastriate Cortex: Interocular ‘Matching’ of Receptive Field Properties, Eye Dominance and Strength of Silent Suppression

PubMed Central

Wang, Chun; Dreher, Bogdan

2014-01-01

Spike-responses of single binocular neurons were recorded from a distinct part of primary visual cortex, the parastriate cortex (cytoarchitectonic area 18) of anaesthetized and immobilized domestic cats. Functional identification of neurons was based on the ratios of phase-variant (F1) component to the mean firing rate (F0) of their spike-responses to optimized (orientation, direction, spatial and temporal frequencies and size) sine-wave-luminance-modulated drifting grating patches presented separately via each eye. In over 95% of neurons, the interocular differences in the phase-sensitivities (differences in F1/F0 spike-response ratios) were small (≤0.3) and in over 80% of neurons, the interocular differences in preferred orientations were ≤10°. The interocular correlations of the direction selectivity indices and optimal spatial frequencies, like those of the phase sensitivies and optimal orientations, were also strong (coefficients of correlation r ≥0.7005). By contrast, the interocular correlations of the optimal temporal frequencies, the diameters of summation areas of the excitatory responses and suppression indices were weak (coefficients of correlation r ≤0.4585). In cells with high eye dominance indices (HEDI cells), the mean magnitudes of suppressions evoked by stimulation of silent, extra-classical receptive fields via the non-dominant eyes, were significantly greater than those when the stimuli were presented via the dominant eyes. We argue that the well documented ‘eye-origin specific’ segregation of the lateral geniculate inputs underpinning distinct eye dominance columns in primary visual cortices of mammals with frontally positioned eyes (distinct eye dominance columns), combined with significant interocular differences in the strength of silent suppressive fields, putatively contribute to binocular stereoscopic vision. PMID:24927276

Geostatistical methods in the assessment of the spatial variability of the quality of river water

NASA Astrophysics Data System (ADS)

Krasowska, Małgorzata; Banaszuk, Piotr

2017-11-01

The research was conducted in the agricultural catchment in north-eastern Poland. The aim of this study was to check how geostatistical analysis can be useful for the detection zones and forms of supply stream by water from different sources. The work was included the implementation of hydrochemical profiles. These profiles were made by measuring the electrical conductivity (EC) values and temperature along the river. On the basis of these results, the authors calculated the coefficient of Moran I and performed semivariogram and found that the EC values are correlated on a stretch of about 140 m. This means that the spatial correlation between samples of water in the stream is readable over a distance of about 140 meters. Therefore it is believed that the degree of water mineralization on this section is shaped by water entering the river channel migration in different ways: through tributaries, leachate drainage and surface runoff. In the case of the analyzed catchment, the potential sources of pollution were drainage systems. Therefore, the spatial analysis allowed the identification pollution sources in a catchment, especially in drained agricultural catchments.

CALIOP near-real-time backscatter products compared to EARLINET data

NASA Astrophysics Data System (ADS)

Grigas, T.; Hervo, M.; Gimmestad, G.; Forrister, H.; Schneider, P.; Preißler, J.; Tarrason, L.; O'Dowd, C.

2015-11-01

The expedited near-real-time Level 1.5 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 3 products were evaluated against data from the ground-based European Aerosol Research Lidar Network (EARLINET). The statistical framework and results of the three-year evaluation of 48 CALIOP overpasses with ground tracks within a 100 km distance from operating EARLINET stations are presented and include analysis for the following CALIOP classifications of aerosol type: dust, polluted dust, clean marine, clean continental, polluted continental, mixed and/or smoke/biomass burning. For the complete data set comprising both the planetary boundary layer (PBL) and the free troposphere (FT) data, the correlation coefficient (R) was 0.86. When the analysis was conducted separately for the PBL and FT, the correlation coefficients were R = 0.6 and R = 0.85, respectively. From analysis of selected specific cases, it was initially thought that the presence of FT layers, with high attenuated backscatter, led to poor agreement of the PBL backscatter profiles between the CALIOP and EARLINET and prompted a further analysis to filter out such cases; however, removal of these layers did not improve the agreement as R reduced marginally from R = 0.86 to R = 0.84 for the combined PBL and FT analysis, increased marginally from R = 0.6 up to R = 0.65 for the PBL on its own, and decreased marginally from R = 0.85 to R = 0.79 for the FT analysis on its own. This suggests considerable variability, across the data set, in the spatial distribution of the aerosol over spatial scales of 100 km or less around some EARLINET stations rather than influence from elevated FT layers. For specific aerosol types, the correlation coefficient between CALIOP backscatter profiles and the EARLINET data ranged from R = 0.37 for polluted continental aerosol in the PBL to R = 0.57 for dust in the FT.

Oxygen-weighted Hyperpolarized 3He MR Imaging: A Short-term Reproducibility Study in Human Subjects

PubMed Central

Ishii, Masaru; Hamedani, Hooman; Clapp, Justin T.; Kadlecek, Stephen J.; Xin, Yi; Gefter, Warren B.; Rossman, Milton D.

2015-01-01

Purpose To determine whether hyperpolarized helium 3 magnetic resonance (MR) imaging to measure alveolar partial pressure of oxygen (Pao2) shows sufficient test-retest repeatability and between-cohort differences to be used as a reliable technique for detection of alterations in gas exchange in asymptomatic smokers. Materials and Methods The protocol was approved by the local institutional review board and was HIPAA compliant. Informed consent was obtained from all subjects. Two sets of MR images were obtained 10 minutes apart in 25 subjects: 10 nonsmokers (five men, five women; mean ± standard deviation age, 50 years ± 6) and 15 smokers (seven women, eight men; mean age, 50 years ± 8). A mixed-effects model was developed to identify the regional repeatability of Pao2 measurements as an intraclass correlation coefficient. Ten smokers were matched with the 10 nonsmokers on the basis of signal-to-noise ratio (SNR). Three separate models were generated: one for nonsmokers, one for the SNR-matched smokers, and one for the five remaining smokers, who were imaged with a significantly higher SNR. Results Short-term back-to-back regional reproducibility was assessed by using intraclass correlation coefficients, which were 0.67 and 0.65 for SNR case-matched nonsmokers and smokers, respectively. Repeatability was a strong function of SNR; a 50% increase in SNR in the remaining smokers improved the intraclass correlation coefficient to 0.82. Although repeatability was not significantly different between the SNR-matched cohorts (P = .44), the smoker group showed higher spatial and temporal variability in Pao2. Conclusion The short-term test-retest repeatability of hyperpolarized gas MR imaging of regional Pao2 was good. Asymptomatic smokers exhibited greater spatial and temporal variability in Pao2 than did the nonsmokers, which suggests that this parameter allows detection of small functional alterations associated with smoking. © RSNA, 2015 Online supplemental material is available for this article. PMID:26110668

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

PubMed

Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures.

[Spatial distribution of COD and the correlations with other parameters in the northern region of Lake Taihu].

PubMed

Zhang, Yun-lin; Yang, Long-yuan; Qin, Bo-qiang; Gao, Guang; Luo, Lian-cong; Zhu, Guang-wei; Liu, Ming-liang

2008-06-01

Spatial variation of chemical oxygen demand (COD) concentration was documented and significant correlations between COD concentration and chromophoric dissolved organic matter (CDOM) absorption, fluorescence, DOC concentration were found based on a cruise sampling in the northern region of Lake Taihu in summer including 42 samplings. The possible source of COD was also discussed using every two cruise samplings in summer and winter, respectively. The COD concentration ranged from 3.77 to 7.96 mg x L(-1) with a mean value of (5.90 +/- 1.54) mg x L(-1). The mean COD concentrations in Meiliang Bay and the central lake basin were (6.93 +/- 0.89) mg x L(-1) and (4.21 +/- 0.49) mg x L(-1) respectively. A significant spatial difference was found between Meiliang Bay and the central lake basin in COD concentration, CDOM absorption coefficient, fluorescence, DOC and phytoplankton pigment concentrations, decreasing from the river mouth to inner bay, outer bay and the central lake basin. Significant correlations between COD concentration and CDOM absorption, fluorescence, DOC concentration, suggested that COD concentration could be estimated and organic pollution could be assessed using CDOM absorption retrieved from remote sensing images. Significant and positive correlation was found between COD concentration and chlorophyll a concentration in summer. However, the correlation was weak or no correlation was found in winter. Furthermore, a significant higher COD concentration was found in summer than in winter (p < 0.001). Our results indicated that degradation of phytoplankton blooms was the main source of COD in summer, except for river terrestrial input.

REVIEWS OF TOPICAL PROBLEMS: Particle kinetics in highly turbulent plasmas (renormalization and self-consistent field methods)

NASA Astrophysics Data System (ADS)

Bykov, Andrei M.; Toptygin, Igor'N.

1993-11-01

This review presents methods available for calculating transport coefficients for impurity particles in plasmas with strong long-wave MHD-type velocity and magnetic-field fluctuations, and random ensembles of strong shock fronts. The renormalization of the coefficients of the mean-field equation of turbulent dynamo theory is also considered. Particular attention is devoted to the renormalization method developed by the authors in which the renormalized transport coefficients are calculated from a nonlinear transcendental equation (or a set of such equations) and are expressed in the form of explicit functions of pair correlation tensors describing turbulence. Numerical calculations are reproduced for different turbulence spectra. Spatial transport in a magnetic field and particle acceleration by strong turbulence are investigated. The theory can be used in a wide range of practical problems in plasma physics, atmospheric physics, ocean physics, astrophysics, cosmic-ray physics, and so on.

Evaluation of an eddy resolving global model at the Bermuda Atlantic Time-series Study site

NASA Astrophysics Data System (ADS)

Hiron, L.; Goncalves Neto, A.; Bates, N. R.; Johnson, R. J.

2016-02-01

The Bermuda Atlantic Time-series Study (BATS) commenced monthly sampling in 1988 and thus provides an invaluable 27 years of ocean temperature and salinity profiles for inferring climate relevant processes. However, the passage of mesoscale eddies through this site complicates the local heat and salinity budgets due to inadequate spatial and temporal sampling of these eddy systems. Thus, application of high resolution operational numerical models potentially offers a framework for estimating the horizontal transport due to mesoscale processes. The goal of this research was to analyze the accuracy of the MERCATOR operational 1/12° global ocean model at the BATS site by comparing temperature, salinity and heat budgets for years 2008 - 2015. Overall agreement in the upper 540m for temperature and salinity is found to be very encouraging with significant (P< 0.01) correlations at all depths for both fields. The highest value of correlation coefficient for the temperature field is 0.98 at the surface which decreases to 0.66 at 150m and then reaches a minimum of 0.50 at 320 to 540m. Similarly, the highest correlation coefficient for salinity is found at the surface, with a value of 0.83 and then decreases to a minimum of 0.25 in the subtropical mode water though then increases to 0.5 at 540m. Mixing in the MERCATOR model is also very well captured with a mixed layer depth (MLD) correlation coefficient of 0.92 for the seven year period. Finally, the total heat budget (0-540m) from MERCATOR varies coherently with the BATS observations as shown by a high correlation coefficient of 0.84 (P < 0.01). According to these analyses, daily output from the MERCATOR model represents accurately the temperature, salinity, heat budget and MLD at the BATS site. We propose this model can be used in future research at the BATS site by providing information about mesoscale structure and importantly, advective fluxes at this site.

Random field assessment of nanoscopic inhomogeneity of bone

PubMed Central

Dong, X. Neil; Luo, Qing; Sparkman, Daniel M.; Millwater, Harry R.; Wang, Xiaodu

2010-01-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to present the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. PMID:20817128

WE-H-207A-05: Spatial Co-Localization of F-18 NaF Vs. F-18 FDG Defined Disease Volumes

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

Ferjancic, P; Harmon, S; Jeraj, R

Purpose: Both [F-18]NaF and [F-18]FDG show promise for quantitative PET/CT assessment in metastatic prostate cancer to bone. Broad agreement between the tracers has been shown but voxel-wise correspondence has not been explored in depth. This study evaluates the spatial co-localization of [F-18]NaF PET and [F-18]FDG PET in bone lesions. Methods: Seventy-three lesion contours were identified in six patients receiving dynamic NaF PET/CT and FDG PET/CT scans two hours apart using identical fields-of-view. Tracer uptake (SUV) reflecting 60 minutes post-injection was modeled from kinetic parameters. Lesions were segmented by a physician separately on NaF PET and FDG PET. PET images weremore » rigidly aligned using skeletal references on CT images. Lesion size, degree of overlap, voxel-wise tracer uptake values (SUV), and CT density distributions were compared using Dice coefficient, Positive Predictive Value (PPV), and Spearman rank correlation tests. Results: Across all patients, 42 lesions were identified on NaF PET (median 1.4 cm{sup 3}, range <1–204 cm{sup 3}) compared to 31 using FDG PET (median 1.8 cm{sup 3}, range <1–244 cm{sup 3}). Spatial cooccurrence was found in 25 lesion pairs. Lesions on NaF PET had PPV of 0.91 and on FDG a PPV of 0.65. Overall, NaF-defined lesions were 47% (±24%) larger by volume with moderate overlap to FDG, resulting in mean Dice coefficient of 34% (±22%). In areas of overlap, voxel-wise correlation of NaF and FDG SUV was moderate (ρ=0.56). Expanding to regions of non-spatial overlap, voxels contained in FDG-only contours were almost exclusively low HU (median 118), compared to dense regions of NaF-only voxels (median 250). In sclerotic sub-volumes (HU > 300) NaF-defined contours encompassed 83% of total FDG volume. Conclusion: Moderate voxel-wise correlation of FDG and NaF PET/CT uptake was observed. Spatial discrepancies in FDG and NaF PET/CT imaging of boney metastases could be influenced by poor sensitivity of FDG PET/CT in sclerotic regions. Funded by Prostate Cancer Foundation.« less

Effect of Coulomb friction on orientational correlation and velocity distribution functions in a sheared dilute granular gas.

PubMed

Gayen, Bishakhdatta; Alam, Meheboob

2011-08-01

From particle simulations of a sheared frictional granular gas, we show that the Coulomb friction can have dramatic effects on orientational correlation as well as on both the translational and angular velocity distribution functions even in the Boltzmann (dilute) limit. The dependence of orientational correlation on friction coefficient (μ) is found to be nonmonotonic, and the Coulomb friction plays a dual role of enhancing or diminishing the orientational correlation, depending on the value of the tangential restitution coefficient (which characterizes the roughness of particles). From the sticking limit (i.e., with no sliding contact) of rough particles, decreasing the Coulomb friction is found to reduce the density and spatial velocity correlations which, together with diminished orientational correlation for small enough μ, are responsible for the transition from non-gaussian to gaussian distribution functions in the double limit of small friction (μ→0) and nearly elastic particles (e→1). This double limit in fact corresponds to perfectly smooth particles, and hence the maxwellian (gaussian) is indeed a solution of the Boltzmann equation for a frictional granular gas in the limit of elastic collisions and zero Coulomb friction at any roughness. The high-velocity tails of both distribution functions seem to follow stretched exponentials even in the presence of Coulomb friction, and the related velocity exponents deviate strongly from a gaussian with increasing friction.

Quantitative analysis of L-edge white line intensities: the influence of saturation and transverse coherence.

PubMed

Hahlin, A; Karis, O; Brena, B; Dunn, J H; Arvantis, D

2001-03-01

We have performed x-ray absorption spectroscopy at the Fe, Ni, and Co L2,3 edges of in situ grown thin magnetic films. We compare electron yield measurements performed at SSRL and BESSY-I. Differences in the L2,3 white line intensities are found for all three elements, comparing data from the two facilities. We propose a correlation between spectral intensities and the degree of spatial coherence of the exciting radiation. The electron yield saturation effects are stronger for light with a higher degree of spatial coherence. Therefore the observed, coherence related, intensity variations are due to an increase in the absorption coefficient, and not to secondary channel related effects.

Correlation techniques and measurements of wave-height statistics

NASA Technical Reports Server (NTRS)

Guthart, H.; Taylor, W. C.; Graf, K. A.; Douglas, D. G.

1972-01-01

Statistical measurements of wave height fluctuations have been made in a wind wave tank. The power spectral density function of temporal wave height fluctuations evidenced second-harmonic components and an f to the minus 5th power law decay beyond the second harmonic. The observations of second harmonic effects agreed very well with a theoretical prediction. From the wave statistics, surface drift currents were inferred and compared to experimental measurements with satisfactory agreement. Measurements were made of the two dimensional correlation coefficient at 15 deg increments in angle with respect to the wind vector. An estimate of the two-dimensional spatial power spectral density function was also made.

Diffusion-Weighted PROPELLER MRI for Quantitative Assessment of Liver Tumor Necrotic Fraction and Viable Tumor Volume in VX2 Rabbits

PubMed Central

Deng, Jie; Virmani, Sumeet; Young, Joseph; Harris, Kathleen; Yang, Guang-Yu; Rademaker, Alfred; Woloschak, Gayle; Omary, Reed A.; Larson, Andrew C.

2010-01-01

Purpose To test the hypothesis that diffusion-weighted (DW)-PROPELLER (periodically rotated overlapping parallel lines with enhanced reconstruction) MRI provides more accurate liver tumor necrotic fraction (NF) and viable tumor volume (VTV) measurements than conventional DW-SE-EPI (spin echo echo-planar imaging) methods. Materials and Methods Our institutional Animal Care and Use Committee approved all experiments. In six rabbits implanted with 10 VX2 liver tumors, DW-PROPELLER and DW-SE-EPI scans were performed at contiguous axial slice positions covering each tumor volume. Apparent diffusion coefficient maps of each tumor were used to generate spatially resolved tumor viability maps for NF and VTV measurements. We compared NF, whole tumor volume (WTV), and VTV measurements to corresponding reference standard histological measurements based on correlation and concordance coefficients and the Bland–Altman analysis. Results DW-PROPELLER generally improved image quality with less distortion compared to DW-SE-EPI. DW-PROPELLER NF, WTV, and VTV measurements were strongly correlated and satisfactorily concordant with histological measurements. DW-SE-EPI NF measurements were weakly correlated and poorly concordant with histological measurements. Bland–Altman analysis demonstrated that DWPROPELLER WTV and VTV measurements were less biased from histological measurements than the corresponding DW-SE-EPI measurements. Conclusion DW-PROPELLER MRI can provide spatially resolved liver tumor viability maps for accurate NF and VTV measurements, superior to DW-SE-EPI approaches. DWPROPELLER measurements may serve as a noninvasive surrogate for pathology, offering the potential for more accurate assessments of therapy response than conventional anatomic size measurements. PMID:18407540

A geospatial analysis of soil lead concentrations around regional Oklahoma airports.

PubMed

McCumber, Alexander; Strevett, K A

2017-01-01

Lead has been banned from automobile gasoline since 1995; however, lead is still used as an additive to aviation gasoline (avgas). Airports are now one of the greatest sources of lead air emission in the US. The objectives of this study were (1) to evaluate soil lead levels radially from three regional airports; (2) collect historical meteorological data; (3) examine the soil organic matter content and (4) develop correlation coefficients to evaluate correlations among variables. Soil samples were collected from 3 different airports in Oklahoma and the soil lead concentration was measured using x-ray fluorescence (XRF). The measured soil lead concentrations were plotted with the corresponding GPS location in ArcGIS and Inverse Distance Weight spatial analysis was used to create modeled isopleths of soil lead concentrations. One of the three airports was found to have soil lead concentrations that correlate with soil organic matter with one other showing correlation between soil lead concentration and distance from the airport. The spatial modeled isopleths showed elevated soil lead concentrations in the direction of prevailing winds with "hot spots" near the avgas fueling stations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cardiac-driven Pulsatile Motion of Intracranial Cerebrospinal Fluid Visualized Based on a Correlation Mapping Technique.

PubMed

Yatsushiro, Satoshi; Sunohara, Saeko; Hayashi, Naokazu; Hirayama, Akihiro; Matsumae, Mitsunori; Atsumi, Hideki; Kuroda, Kagayaki

2018-04-10

A correlation mapping technique delineating delay time and maximum correlation for characterizing pulsatile cerebrospinal fluid (CSF) propagation was proposed. After proofing its technical concept, this technique was applied to healthy volunteers and idiopathic normal pressure hydrocephalus (iNPH) patients. A time-resolved three dimensional-phase contrast (3D-PC) sampled the cardiac-driven CSF velocity at 32 temporal points per cardiac period at each spatial location using retrospective cardiac gating. The proposed technique visualized distributions of propagation delay and correlation coefficient of the PC-based CSF velocity waveform with reference to a waveform at a particular point in the CSF space. The delay time was obtained as the amount of time-shift, giving the maximum correlation for the velocity waveform at an arbitrary location with that at the reference location. The validity and accuracy of the technique were confirmed in a flow phantom equipped with a cardiovascular pump. The technique was then applied to evaluate the intracranial CSF motions in young, healthy (N = 13), and elderly, healthy (N = 13) volunteers and iNPH patients (N = 13). The phantom study demonstrated that root mean square error of the delay time was 2.27%, which was less than the temporal resolution of PC measurement used in this study (3.13% of a cardiac cycle). The human studies showed a significant difference (P < 0.01) in the mean correlation coefficient between the young, healthy group and the other two groups. A significant difference (P < 0.05) was also recognized in standard deviation of the correlation coefficients in intracranial CSF space among all groups. The result suggests that the CSF space compliance of iNPH patients was lower than that of healthy volunteers. The correlation mapping technique allowed us to visualize pulsatile CSF velocity wave propagations as still images. The technique may help to classify diseases related to CSF dynamics, such as iNPH.

Temporal evolution of the spatial covariability of rainfall in South America

NASA Astrophysics Data System (ADS)

Ciemer, Catrin; Boers, Niklas; Barbosa, Henrique M. J.; Kurths, Jürgen; Rammig, Anja

2017-10-01

The climate of South America exhibits pronounced differences between rainy and dry seasons, associated with specific synoptic features such as the establishment of the South Atlantic convergence zone. Here, we analyze the spatiotemporal correlation structure and in particular teleconnections of daily rainfall associated with these features by means of evolving complex networks. A modification of Pearson's correlation coefficient is introduced to handle the intricate statistical properties of daily rainfall. On this basis, spatial correlation networks are constructed, and new appropriate network measures are introduced in order to analyze the temporal evolution of the networks' characteristics. We particularly focus on the identification of coherent areas of similar rainfall patterns and previously unknown teleconnection structures between remote areas. We show that the monsoon onset is characterized by an abrupt transition from erratic to organized regional connectivity that prevails during the monsoon season, while only the onset times themselves exhibit anomalous large-scale organization of teleconnections. Furthermore, we reveal that the two mega-droughts in the Amazon basin were already announced in the previous year by an anomalous behavior of the connectivity structure.

Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics

NASA Astrophysics Data System (ADS)

Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.

2010-08-01

An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.

Slope variation and population structure of tree species from different ecological groups in South Brazil.

PubMed

Bianchini, Edmilson; Garcia, Cristina C; Pimenta, José A; Torezan, José M D

2010-09-01

Size structure and spatial arrangement of 13 abundant tree species were determined in a riparian forest fragment in Paraná State, South Brazil (23°16'S and 51°01'W). The studied species were Aspidosperma polyneuron Müll. Arg., Astronium graveolens Jacq. and Gallesia integrifolia (Spreng) Harms (emergent species); Alseis floribunda Schott, Ruprechtia laxiflora Meisn. and Bougainvillea spectabilis Willd. (shade-intolerant canopy species); Machaerium paraguariense Hassl, Myroxylum peruiferum L. and Chrysophyllum gonocarpum (Mart. & Eichler ex Miq.) Engl. (shade-tolerant canopy species); Sorocea bonplandii (Baill.) Bürger, Trichilia casaretti C. Dc, Trichilia catigua A. Juss. and Actinostemon concolor (Spreng.) Müll. Arg. (understory small trees species). Height and diameter structures and basal area of species were analyzed. Spatial patterns and slope correlation were analyzed by Moran's / spatial autocorrelation coefficient and partial Mantel test, respectively. The emergent and small understory species showed the highest and the lowest variations in height, diameter and basal area. Size distribution differed among emergent species and also among canopy shade-intolerant species. The spatial pattern ranged among species in all groups, except in understory small tree species. The slope was correlated with spatial pattern for A. polyneuron, A. graveolens, A. floribunda, R. laxiflora, M. peruiferum and T. casaretti. The results indicated that most species occurred in specific places, suggesting that niche differentiation can be an important factor in structuring the tree community.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring.

PubMed

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-20

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring

PubMed Central

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-01-01

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA. PMID:26308017

Correlated diffusion of colloidal particles near a liquid-liquid interface.

PubMed

Zhang, Wei; Chen, Song; Li, Na; Zhang, Jia Zheng; Chen, Wei

2014-01-01

Optical microscopy and multi-particle tracking are used to investigate the cross-correlated diffusion of quasi two-dimensional colloidal particles near an oil-water interface. The behaviors of the correlated diffusion along longitudinal and transverse direction are asymmetric. It is shown that the characteristic length for longitudinal and transverse correlated diffusion are particle diameter d and the distance z from particle center to the interface, respectively, for large particle separation z. The longitudinal and transverse correlated diffusion coefficient D||(r) and D[perpendicular](r) are independent of the colloidal area fraction n when n < 0.3, which indicates that the hydrodynamic interactions(HIs) among the particles are dominated by HIs through the surrounding fluid for small n. For high area fraction n > 0.4 the power law exponent for the spatial decay of [Formula: see text] begins to decrease, which suggests the HIs are more contributed from the 2D particle monolayer self for large n.

Effect of combined digital imaging parameters on endodontic file measurements.

PubMed

de Oliveira, Matheus Lima; Pinto, Geraldo Camilo de Souza; Ambrosano, Glaucia Maria Bovi; Tosoni, Guilherme Monteiro

2012-10-01

This study assessed the effect of the combination of a dedicated endodontic filter, spatial resolution, and contrast resolution on the determination of endodontic file lengths. Forty extracted single-rooted teeth were x-rayed with K-files (ISO size 10 and 15) in the root canals. Images were acquired using the VistaScan system (Dürr Dental, Beitigheim-Bissingen, Germany) under different combining parameters of spatial resolution (10 and 25 line pairs per millimeter [lp/mm]) and contrast resolution (8- and 16-bit depths). Subsequently, a dedicated endodontic filter was applied on the 16-bit images, creating 2 additional parameters. Six observers measured the length of the endodontic files in the root canals using the software that accompanies the system. The mean values of the actual file lengths and the measurements of the radiographic images were submitted to 1-way analysis of variance and the Tukey test at a level of significance of 5%. The intraobserver reproducibility was assessed by the intraclass correlation coefficient. All combined image parameters showed excellent intraobserver agreement with intraclass correlation coefficient means higher than 0.98. The imaging parameter of 25 lp/mm and 16 bit associated with the use of the endodontic filter did not differ significantly from the actual file lengths when both file sizes were analyzed together or separately (P > .05). When the size 15 file was evaluated separately, only 8-bit images differed significantly from the actual file lengths (P ≤ .05). The combination of an endodontic filter with high spatial resolution and high contrast resolution is recommended for the determination of file lengths when using storage phosphor plates. Copyright © 2012 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Column NO2-total ozone-stratospheric temperature relationships associated with the Arctic and Antarctic ozone holes

NASA Astrophysics Data System (ADS)

Aheyeva, Viktoryia; Gruzdev, Aleksandr; Grishaev, Mikhail

Data of ground-based measurements of NO2 column contents are analyzed to study winter-spring NO2 anomalies associated with negative anomalies in column ozone and stratospheric temperature. Episodes of significant decrease in column NO2 contents in the winter-spring period of 2011 in the northern hemisphere (NH) were detected at European and Siberian stations of Zvenigorod (55.7°N, Moscow Region) and Tomsk (56.5°N, West Siberia) in the middle latitudes, Harestua (60.2°N), Sodankyla (67.4°N, both in North Europe), and Zhigansk (66.8°N, East Siberia) in the high latitudes, and at the Arctic station of Scoresbysund (70.5°N, Greenland). All the stations, except Tomsk, are a part of the Network of the Detection of Atmospheric Composition Change (NDACC), and the data are accesses at http://ndacc.org. The decrease in NO2 is generally accompanied by total ozone and stratospheric temperature decrease and is shown to be caused by the transport of stratospheric air from the region of the ozone hole observed that season in the Arctic. Overpass total ozone data from Giovanni service and radiosonde data were used for the analysis. Although negative NO2 anomalies due to the transport from the Arctic were also observed in some other years, the anomalies in 2011 reached record magnitudes. A significant positive correlation has been found between variations in NO2 and ozone columns as well as NO2 column and stratospheric temperature during the winter-spring period of 2011, whereas the correlation is much weaker in years without Arctic ozone depletion. The correlation becomes even stronger if only episodes with significant NO2 decrease are considered. For example the correlation coefficients between NO2 and ozone columns deviations are about 0.9 for Zvenigorod and Scoresbysund. Correlation coefficients between variations in column NO2 and total ozone and stratospheric temperature as well as coefficients of regression of NO2 on ozone and temperature in the winter-spring period of 2011 for the Siberian stations are less than those for European stations. For comparison analysis, data of column NO2, total ozone and stratospheric temperature at the southern hemisphere (SH) stations of Dumont D’Urville (66.7°S, the Antarctic), Macquarie Island (54.5°S) and Kerguelen Island (49.3°S) (all stations are NDACC stations) were used. Correlation and regression coefficients between variations in column NO2 and total ozone as well as in column NO2 and stratospheric temperature for the winter-spring periods at the SH stations depend on the phase of the quasi-biennial oscillation (QBO) in the 30 hPa equatorial wind velocity. The correlation coefficients and the coefficients of regression of NO2 on ozone and temperature for the west QBO phase are large compared to those for the east phase. The 2011 Arctic ozone hole was observed during the west phase of the 30 hPa QBO. The calculated correlation coefficients at the NH stations for the winter-spring period of 2011 associated with the Arctic ozone hole are close to similar coefficients at the SH stations in winter-spring periods for the west QBO phase. The regression coefficients at the NH stations are less than those at the SH stations for the west QBO phase but greater than similar coefficients for the east phase. We can conclude that physico-chemical processes specific for ozone hole conditions cause spatial correlation between distribution of stratospheric NO2 and distributions of total ozone and temperature in polar and adjacent regions, which is generally stronger for stronger ozone deficit in a polar region. This results in significant time correlation between NO2, ozone and temperature at observation sites due to transport processes.

Deriving aerosol parameters from in-situ spectrometer measurements for validation of remote sensing products

NASA Astrophysics Data System (ADS)

Riedel, Sebastian; Janas, Joanna; Gege, Peter; Oppelt, Natascha

2017-10-01

Uncertainties of aerosol parameters are the limiting factor for atmospheric correction over inland and coastal waters. For validating remote sensing products from these optically complex and spatially inhomogeneous waters the spatial resolution of automated sun photometer networks like AERONET is too coarse and additional measurements on the test site are required. We have developed a method which allows the derivation of aerosol parameters from measurements with any spectrometer with suitable spectral range and resolution. This method uses a pair of downwelling irradiance and sky radiance measurements for the extraction of the turbidity coefficient and aerosol Ångström exponent. The data can be acquired fast and reliable at almost any place during a wide range of weather conditions. A comparison to aerosol parameters measured with a Cimel sun photometer provided by AERONET shows a reasonable agreement for the Ångström exponent. The turbidity coefficient did not agree well with AERONET values due to fit ambiguities, indicating that future research should focus on methods to handle parameter correlations within the underlying model.

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

PubMed

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Information content exploitation of imaging spectrometer's images for lossless compression

NASA Astrophysics Data System (ADS)

Wang, Jianyu; Zhu, Zhenyu; Lin, Kan

1996-11-01

Imaging spectrometer, such as MAIS produces a tremendous volume of image data with up to 5.12 Mbps raw data rate, which needs urgently a real-time, efficient and reversible compression implementation. Between the lossy scheme with high compression ratio and the lossless scheme with high fidelity, we must make our choice based on the particular information content analysis of each imaging spectrometer's image data. In this paper, we present a careful analysis of information-preserving compression of imaging spectrometer MAIS with an entropy and autocorrelation study on the hyperspectral images. First, the statistical information in an actual MAIS image, captured in Marble Bar Australia, is measured with its entropy, conditional entropy, mutual information and autocorrelation coefficients on both spatial dimensions and spectral dimension. With these careful analyses, it is shown that there is high redundancy existing in the spatial dimensions, but the correlation in spectral dimension of the raw images is smaller than expected. The main reason of the nonstationarity on spectral dimension is attributed to the instruments's discrepancy on detector's response and channel's amplification in different spectral bands. To restore its natural correlation, we preprocess the signal in advance. There are two methods to accomplish this requirement: onboard radiation calibration and normalization. A better result can be achieved by the former one. After preprocessing, the spectral correlation increases so high that it contributes much redundancy in addition to spatial correlation. At last, an on-board hardware implementation for the lossless compression is presented with an ideal result.

Comparison between DMSP-OLS and S-NPP Day-Night Band in Correlating with Regional Socio-economic Variables

NASA Astrophysics Data System (ADS)

Jing, X.; Shao, X.; Cao, C.; Fu, X.

2013-12-01

Night-time light imagery offers a unique view of the Earth's surface. In the past, the nighttime light data collected by the DMSP-OLS sensors have been used as efficient means to correlate with the global socio-economic activities. With the launch of Suomi National Polar-orbiting Partnership (S-NPP) satellite in October 2011, the Day Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard S-NPP represents a major advancement in night time imaging capabilities because it surpassed its predecessor DMSP-OLS in radiometric accuracy, spatial resolution, and geometric quality. In this paper, we compared the performance of DNB image and DMSP image in correlating regional socio-economic activities and analyzed the leading causes for the differences. The correlation coefficients between the socio-economic variables such as population, regional GDP etc. and the characteristic variables derived from the night time light images of DNB and DMSP at provincial level in China were computed as performance metrics for comparison. In general, the correlation between DNB data and socio-economic data is better than that of DMSP data. To explain the difference in the correlation, we further analyzed the effects of several factors such as radiometric saturation and quantization of DMSP data, low spatial resolution, different data acquisition times between DNB and DMSP images, and difference in the transformation used in converting digital number (DN) value to radiance.

Restoring method for missing data of spatial structural stress monitoring based on correlation

NASA Astrophysics Data System (ADS)

Zhang, Zeyu; Luo, Yaozhi

2017-07-01

Long-term monitoring of spatial structures is of great importance for the full understanding of their performance and safety. The missing part of the monitoring data link will affect the data analysis and safety assessment of the structure. Based on the long-term monitoring data of the steel structure of the Hangzhou Olympic Center Stadium, the correlation between the stress change of the measuring points is studied, and an interpolation method of the missing stress data is proposed. Stress data of correlated measuring points are selected in the 3 months of the season when missing data is required for fitting correlation. Data of daytime and nighttime are fitted separately for interpolation. For a simple linear regression when single point's correlation coefficient is 0.9 or more, the average error of interpolation is about 5%. For multiple linear regression, the interpolation accuracy is not significantly increased after the number of correlated points is more than 6. Stress baseline value of construction step should be calculated before interpolating missing data in the construction stage, and the average error is within 10%. The interpolation error of continuous missing data is slightly larger than that of the discrete missing data. The data missing rate of this method should better not exceed 30%. Finally, a measuring point's missing monitoring data is restored to verify the validity of the method.

Image correlation microscopy for uniform illumination.

PubMed

Gaborski, T R; Sealander, M N; Ehrenberg, M; Waugh, R E; McGrath, J L

2010-01-01

Image cross-correlation microscopy is a technique that quantifies the motion of fluorescent features in an image by measuring the temporal autocorrelation function decay in a time-lapse image sequence. Image cross-correlation microscopy has traditionally employed laser-scanning microscopes because the technique emerged as an extension of laser-based fluorescence correlation spectroscopy. In this work, we show that image correlation can also be used to measure fluorescence dynamics in uniform illumination or wide-field imaging systems and we call our new approach uniform illumination image correlation microscopy. Wide-field microscopy is not only a simpler, less expensive imaging modality, but it offers the capability of greater temporal resolution over laser-scanning systems. In traditional laser-scanning image cross-correlation microscopy, lateral mobility is calculated from the temporal de-correlation of an image, where the characteristic length is the illuminating laser beam width. In wide-field microscopy, the diffusion length is defined by the feature size using the spatial autocorrelation function. Correlation function decay in time occurs as an object diffuses from its original position. We show that theoretical and simulated comparisons between Gaussian and uniform features indicate the temporal autocorrelation function depends strongly on particle size and not particle shape. In this report, we establish the relationships between the spatial autocorrelation function feature size, temporal autocorrelation function characteristic time and the diffusion coefficient for uniform illumination image correlation microscopy using analytical, Monte Carlo and experimental validation with particle tracking algorithms. Additionally, we demonstrate uniform illumination image correlation microscopy analysis of adhesion molecule domain aggregation and diffusion on the surface of human neutrophils.

Measurements of surface-pressure and wake-flow fluctuations in the flow field of a whitcomb supercritical airfoil

NASA Technical Reports Server (NTRS)

Roos, F. W.; Riddle, D. W.

1977-01-01

Measurements of surface pressure and wake flow fluctuations were made as part of a transonic wind tunnel investigation into the nature of a supercritical airfoil flow field. Emphasis was on a range of high subsonic Mach numbers and moderate lift coefficients corresponding to the development of drag divergence and buffeting. Fluctuation data were analyzed statistically for intensity, frequency content, and spatial coherence. Variations in these parameters were correlated with changes in the mean airfoil flow field.

Exploring the spatial variability of soil properties in an Alfisol Catena

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

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

A new correlation coefficient for bivariate time-series data

NASA Astrophysics Data System (ADS)

Erdem, Orhan; Ceyhan, Elvan; Varli, Yusuf

2014-11-01

The correlation in time series has received considerable attention in the literature. Its use has attained an important role in the social sciences and finance. For example, pair trading in finance is concerned with the correlation between stock prices, returns, etc. In general, Pearson’s correlation coefficient is employed in these areas although it has many underlying assumptions which restrict its use. Here, we introduce a new correlation coefficient which takes into account the lag difference of data points. We investigate the properties of this new correlation coefficient. We demonstrate that it is more appropriate for showing the direction of the covariation of the two variables over time. We also compare the performance of the new correlation coefficient with Pearson’s correlation coefficient and Detrended Cross-Correlation Analysis (DCCA) via simulated examples.

Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography.

PubMed

Muller, Leah; Hamilton, Liberty S; Edwards, Erik; Bouchard, Kristofer E; Chang, Edward F

2016-10-01

Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography

NASA Astrophysics Data System (ADS)

Muller, Leah; Hamilton, Liberty S.; Edwards, Erik; Bouchard, Kristofer E.; Chang, Edward F.

2016-10-01

Objective. Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Approach. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. Main results. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Significance. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

Application and evaluation of ISVR method in QuickBird image fusion

NASA Astrophysics Data System (ADS)

Cheng, Bo; Song, Xiaolu

2014-05-01

QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the integration of the spatial information and spectral information of the imagery. A fusion method for high resolution remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of radicalization targeting to remove the effect of different gain and error of satellites' sensors. Transformed from DN to radiance, the multi-spectral image's energy is used to simulate the panchromatic band. The linear regression analysis is carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this method could significantly improve the quality of fused image, especially in preserving spectral information, to maximize the spectral information of original multispectral images, while maintaining abundant spatial information.

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

PubMed

Lin, Pei-Sheng; Kung, Yi-Hung; Clayton, Murray

2016-12-01

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan. © 2016, The International Biometric Society.

Linear multivariate evaluation models for spatial perception of soundscape.

PubMed

Deng, Zhiyong; Kang, Jian; Wang, Daiwei; Liu, Aili; Kang, Joe Zhengyu

2015-11-01

Soundscape is a sound environment that emphasizes the awareness of auditory perception and social or cultural understandings. The case of spatial perception is significant to soundscape. However, previous studies on the auditory spatial perception of the soundscape environment have been limited. Based on 21 native binaural-recorded soundscape samples and a set of auditory experiments for subjective spatial perception (SSP), a study of the analysis among semantic parameters, the inter-aural-cross-correlation coefficient (IACC), A-weighted-equal sound-pressure-level (L(eq)), dynamic (D), and SSP is introduced to verify the independent effect of each parameter and to re-determine some of their possible relationships. The results show that the more noisiness the audience perceived, the worse spatial awareness they received, while the closer and more directional the sound source image variations, dynamics, and numbers of sound sources in the soundscape are, the better the spatial awareness would be. Thus, the sensations of roughness, sound intensity, transient dynamic, and the values of Leq and IACC have a suitable range for better spatial perception. A better spatial awareness seems to promote the preference slightly for the audience. Finally, setting SSPs as functions of the semantic parameters and Leq-D-IACC, two linear multivariate evaluation models of subjective spatial perception are proposed.

Transport of passive scalars in a turbulent channel flow

NASA Technical Reports Server (NTRS)

Kim, John; Moin, Parviz

1987-01-01

A direct numerical simulation of a turbulent channel flow with three passive scalars at different molecular Prandtl numbers is performed. Computed statistics including the turbulent Prandtl numbers are compared with existing experimental data. The computed fields are also examined to investigate the spatial structure of the scalar fields. The scalar fields are highly correlated with the streamwise velocity; the correlation coefficient between the temperature and the streamwise velocity is as high as 0.95 in the wall region. The joint probability distributions between the temperature and velocity fluctuations are also examined; they suggest that it might be possible to model the scalar fluxes in the wall region in a manner similar to the Reynolds stresses.

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

PubMed Central

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

2016-01-01

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

Random field assessment of nanoscopic inhomogeneity of bone.

PubMed

Dong, X Neil; Luo, Qing; Sparkman, Daniel M; Millwater, Harry R; Wang, Xiaodu

2010-12-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to represent the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. Copyright © 2010 Elsevier Inc. All rights reserved.

Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China).

PubMed

Cui, Lifang; Wang, Lunche; Singh, Ramesh P; Lai, Zhongping; Jiang, Liangliang; Yao, Rui

2018-05-23

The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.

A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Chu, D. Allen; Mattoo, Shana; Kaufman, Yoram J.; Remer, Lorraine A.; Tanre, Didier; Slutsker, Ilya; Holben, Brent N.; Lau, William K. M. (Technical Monitor)

2001-01-01

With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Tests of Hypotheses Arising In the Correlated Random Coefficient Model*

PubMed Central

Heckman, James J.; Schmierer, Daniel

2010-01-01

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model. PMID:21170148

Geometry of quantum Hall states: Gravitational anomaly and transport coefficients

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

Can, Tankut, E-mail: tcan@scgp.stonybrook.edu; Laskin, Michael; Wiegmann, Paul B.

2015-11-15

We show that universal transport coefficients of the fractional quantum Hall effect (FQHE) can be understood as a response to variations of spatial geometry. Some transport properties are essentially governed by the gravitational anomaly. We develop a general method to compute correlation functions of FQH states in a curved space, where local transformation properties of these states are examined through local geometric variations. We introduce the notion of a generating functional and relate it to geometric invariant functionals recently studied in geometry. We develop two complementary methods to study the geometry of the FQHE. One method is based on iteratingmore » a Ward identity, while the other is based on a field theoretical formulation of the FQHE through a path integral formalism.« less

An integrated fiber-optic probe combined with support vector regression for fast estimation of optical properties of turbid media.

PubMed

Zhou, Yang; Fu, Xiaping; Ying, Yibin; Fang, Zhenhuan

2015-06-23

A fiber-optic probe system was developed to estimate the optical properties of turbid media based on spatially resolved diffuse reflectance. Because of the limitations in numerical calculation of radiative transfer equation (RTE), diffusion approximation (DA) and Monte Carlo simulations (MC), support vector regression (SVR) was introduced to model the relationship between diffuse reflectance values and optical properties. The SVR models of four collection fibers were trained by phantoms in calibration set with a wide range of optical properties which represented products of different applications, then the optical properties of phantoms in prediction set were predicted after an optimal searching on SVR models. The results indicated that the SVR model was capable of describing the relationship with little deviation in forward validation. The correlation coefficient (R) of reduced scattering coefficient μ'(s) and absorption coefficient μ(a) in the prediction set were 0.9907 and 0.9980, respectively. The root mean square errors of prediction (RMSEP) of μ'(s) and μ(a) in inverse validation were 0.411 cm(-1) and 0.338 cm(-1), respectively. The results indicated that the integrated fiber-optic probe system combined with SVR model were suitable for fast and accurate estimation of optical properties of turbid media based on spatially resolved diffuse reflectance. Copyright © 2015 Elsevier B.V. All rights reserved.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh

PubMed Central

Bi, Qifang; Azman, Andrew S.; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S.; Lessler, Justin

2016-01-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures. PMID:26866926

A stochastic-dynamic model for global atmospheric mass field statistics

NASA Technical Reports Server (NTRS)

Ghil, M.; Balgovind, R.; Kalnay-Rivas, E.

1981-01-01

A model that yields the spatial correlation structure of atmospheric mass field forecast errors was developed. The model is governed by the potential vorticity equation forced by random noise. Expansion in spherical harmonics and correlation function was computed analytically using the expansion coefficients. The finite difference equivalent was solved using a fast Poisson solver and the correlation function was computed using stratified sampling of the individual realization of F(omega) and hence of phi(omega). A higher order equation for gamma was derived and solved directly in finite differences by two successive applications of the fast Poisson solver. The methods were compared for accuracy and efficiency and the third method was chosen as clearly superior. The results agree well with the latitude dependence of observed atmospheric correlation data. The value of the parameter c sub o which gives the best fit to the data is close to the value expected from dynamical considerations.

The response of the temperature of cold-point mesopause to solar activity based on SABER data set

NASA Astrophysics Data System (ADS)

Tang, Chaoli; Liu, Dong; Wei, Heli; Wang, Yingjian; Dai, Congming; Wu, Pengfei; Zhu, Wenyue; Rao, Ruizhong

2016-07-01

The thermal structure and energy balance of upper atmosphere are dominated by solar activity. The response of cold-point mesopause (CPM) to solar activity is an important form. This article presents the response of the temperature of CPM (T-CPM) to solar activity using 14 year Sounding of the Atmosphere using Broadband Emission Radiometry data series over 80°S-80°N regions. These regions are divided into 16 latitude zones with 10° interval, and the spatial areas of 80°S-80°N, 180°W-180°E are divided into 96 lattices with 10°(latitude) × 60°(longitude) grid. The annual-mean values of T-CPM and F10.7 are calculated. The least squares regression method and correlation analysis are applied to these annual-mean series. First, the results show that the global T-CPM is significantly correlated to solar activity at the 0.05 level of significance with correlation coefficient of 0.90. The global solar response of T-CPM is 4.89 ± 0.67 K/100 solar flux unit. Then, for each latitude zone, the solar response of T-CPM and its fluctuation are obtained. The solar response of T-CPM becomes stronger with increasing latitude. The fluctuation ranges of solar response at middle-latitude regions are smaller than those of the equator and high-latitude regions, and the global distribution takes on W shape. The corelationship analysis shows that the T-CPM is significantly correlated to solar activity at the 0.05 level of significance for each latitude zone. The correlation coefficients at middle-latitude regions are higher than those of the equator and high-latitude regions, and the global distribution takes on M shape. At last, for each grid cell, the response of T-CPM to solar activity and their correlation coefficient are presented.

Is the Life Space Assessment applicable to a palliative care population? Its relationship to measures of performance and quality of life.

PubMed

Phillips, Jane Louise; Lam, Lawrence; Luckett, Tim; Agar, Meera; Currow, David

2014-06-01

The spatial environments that palliative care patients frequent for business and leisure constrict as their disease progresses and their physical functioning deteriorates. Measuring a person's movement within his or her own environment is a clinically relevant and patient-centered outcome because it measures function in a way that reflects actual and not theoretical participation. This exploratory study set out to test whether the Life-Space Assessment (LSA) would correlate with other commonly used palliative care outcome measures of function and quality of life. The baseline LSA, Australia-modified Karnofsky Performance Status Scale (AKPS), and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 15-Palliative (EORTC QLQ-C15-PAL) scores from two large clinical trials were used to calculate correlation coefficients between the measures. Convergent validity analysis was undertaken by comparing LSA scores between participants with higher (≥70) and lower (≤60) AKPS scores. The LSA was correlated significantly and positively with the AKPS, with a moderate correlation coefficient of 0.54 (P<0.001). There was a significant weak negative correlation between the LSA and the EORTC QLQ-C15-PAL, with a small coefficient of -0.22 (P=0.027), but a strong correlation between the LSA and the EORTC QLQ-C15-PAL item related to independent activities of daily living (r=-0.654, P<0.01). A significant difference in the LSA score between participants with higher (≥70) and lower (≤60) AKPS scores t(97)=-4.35, P<0.001) was found. The LSA appears applicable to palliative care populations given the convergent validity and capacity of this instrument to differentiate a person's ability to move through life-space zones by performance status. Further research is required to validate and apply the LSA within community palliative care populations. Copyright © 2014 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

The Non-Gaussian Nature of Prostate Motion Based on Real-Time Intrafraction Tracking

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

Lin, Yuting; Liu, Tian; Yang, Wells

2013-10-01

Purpose: The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Methods and Materials: Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including allmore » fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. Results: There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Conclusions: Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate.« less

The non-Gaussian nature of prostate motion based on real-time intrafraction tracking.

PubMed

Lin, Yuting; Liu, Tian; Yang, Wells; Yang, Xiaofeng; Khan, Mohammad K

2013-10-01

The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including all fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate. Copyright © 2013 Elsevier Inc. All rights reserved.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Distance correlation methods for discovering associations in large astrophysical databases

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

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Spatial correlation of hydrometeor occurrence, reflectivity, and rain rate from CloudSat

NASA Astrophysics Data System (ADS)

Marchand, Roger

2012-03-01

This paper examines the along-track vertical and horizontal structure of hydrometeor occurrence, reflectivity, and column rain rate derived from CloudSat. The analysis assumes hydrometeors statistics in a given region are horizontally invariant, with the probability of hydrometeor co-occurrence obtained simply by determining the relative frequency at which hydrometeors can be found at two points (which may be at different altitudes and offset by a horizontal distance, Δx). A correlation function is introduced (gamma correlation) that normalizes hydrometeor co-occurrence values to the range of 1 to -1, with a value of 0 meaning uncorrelated in the usual sense. This correlation function is a generalization of the alpha overlap parameter that has been used in recent studies to describe the overlap between cloud (or hydrometeor) layers. Examples of joint histograms of reflectivity at two points are also examined. The analysis shows that the traditional linear (or Pearson) correlation coefficient provides a useful one-to-one measure of the strength of the relationship between hydrometeor reflectivity at two points in the horizontal (that is, two points at the same altitude). While also potentially useful in the vertical direction, the relationship between reflectivity values at different altitudes is not as well described by the linear correlation coefficient. The decrease in correlation of hydrometeor occurrence and reflectivity with horizontal distance, as well as precipitation occurrence and column rain rate, can be reasonably well fit with a simple two-parameter exponential model. In this paper, the North Pacific and tropical western Pacific are examined in detail, as is the zonal dependence.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Spatial and temporal distribution of singlet oxygen in Lake Superior.

PubMed

Peterson, Britt M; McNally, Ann M; Cory, Rose M; Thoemke, John D; Cotner, James B; McNeill, Kristopher

2012-07-03

A multiyear field study was undertaken on Lake Superior to investigate singlet oxygen ((1)O(2)) photoproduction. Specifically, trends within the lake were examined, along with an assessment of whether correlations existed between chromophoric dissolved organic matter (CDOM) characteristics and (1)O(2) production rates and quantum yields. Quantum yield values were determined and used to estimate noontime surface (1)O(2) steady-state concentrations ([(1)O(2)](ss)). Samples were subdivided into three categories based on their absorbance properties (a300): riverine, river-impacted, or open lake sites. Using calculated surface [(1)O(2)](ss), photochemical half-lives under continuous summer sunlight were calculated for cimetidine, a pharmaceutical whose reaction with (1)O(2) has been established, to be on the order of hours, days, and a week for the riverine, river-impacted, and open lake waters, respectively. Of the CDOM properties investigated, it was found that dissolved organic carbon (DOC) and a300 were the best parameters for predicting production rates of [(1)O(2)](ss). For example, given the correlations found, one could predict [(1)O(2)](ss) within a factor of 4 using a300 alone. Changes in the quantum efficiency of (1)O(2) production upon dilution of river water samples with lake water samples demonstrated that the CDOM found in the open lake is not simply diluted riverine organic matter. The open lake pool was characterized by low absorption coefficient, low fluorescence, and low DOC, but more highly efficient (1)O(2) production and predominates the Lake Superior system spatially. This study establishes that parameters that reflect the quantity of CDOM (e.g., a300 and DOC) correlate with (1)O(2) production rates, while parameters that characterize the absorbance spectrum (e.g., spectral slope coefficient and E2:E3) correlate with (1)O(2) production quantum yields.

Intercomparisons of Marine Boundary Layer Cloud Properties from the ARM CAP-MBL Campaign and Two MODIS Cloud Products

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-01-01

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R greater than 0.95 despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 micrometers band (CER(sub 2.1)) is significantly smaller than that based on the 3.7 micrometers band (CER(sub 3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(sub 3.7) and CER(sub 2.1) retrievals have a lower correlation (R is approximately 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 micrometers and 3.0 micrometers, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 micrometers.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

PubMed

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model

PubMed Central

Scott, Jacob G.

2016-01-01

Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripley’s L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis. PMID:26800503

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

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

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

Spatiotemporal analysis of tumor uptake patterns in dynamic (18)FDG-PET and dynamic contrast enhanced CT.

PubMed

Malinen, Eirik; Rødal, Jan; Knudtsen, Ingerid Skjei; Søvik, Åste; Skogmo, Hege Kippenes

2011-08-01

Molecular and functional imaging techniques such as dynamic positron emission tomography (DPET) and dynamic contrast enhanced computed tomography (DCECT) may provide improved characterization of tumors compared to conventional anatomic imaging. The purpose of the current work was to compare spatiotemporal uptake patterns in DPET and DCECT images. A PET/CT protocol comprising DCECT with an iodine based contrast agent and DPET with (18)F-fluorodeoxyglucose was set up. The imaging protocol was used for examination of three dogs with spontaneous tumors of the head and neck at sessions prior to and after fractionated radiotherapy. Software tools were developed for downsampling the DCECT image series to the PET image dimensions, for segmentation of tracer uptake pattern in the tumors and for spatiotemporal correlation analysis of DCECT and DPET images. DCECT images evaluated one minute post injection qualitatively resembled the DPET images at most imaging sessions. Segmentation by region growing gave similar tumor extensions in DCECT and DPET images, with a median Dice similarity coefficient of 0.81. A relatively high correlation (median 0.85) was found between temporal tumor uptake patterns from DPET and DCECT. The heterogeneity in tumor uptake was not significantly different in the DPET and DCECT images. The median of the spatial correlation was 0.72. DCECT and DPET gave similar temporal wash-in characteristics, and the images also showed a relatively high spatial correlation. Hence, if the limited spatial resolution of DPET is considered adequate, a single DPET scan only for assessing both tumor perfusion and metabolic activity may be considered. However, further work on a larger number of cases is needed to verify the correlations observed in the present study.

Hydrologic Evaluation of TRMM Multisatellite Precipitation Analysis for Nanliu River Basin in Humid Southwestern China.

PubMed

Zhao, Yinjun; Xie, Qiongying; Lu, Yuan; Hu, Baoqing

2017-06-01

The accuracy of Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) daily accumulated precipitation products (3B42RTV7 and 3B42V7) was evaluated for a small basin (the Nanliu river basin). A direct comparison was performed against gauge observations from a period of 9 years (2000-2009) at temporal and spatial scales. The results show that the temporal-spatial precipitation characteristics of the Nanliu river basin are highly consistent with 3B42V7 relative to 3B42RTV7, with higher correlation coefficient (CC) approximately 0.9 at all temporal scales except for the daily scale and a lower relative bias percentage. 3B42V7 slightly overestimates precipitation at all temporal scales except the yearly scale; it slightly underestimates the precipitation at the daily spatial scale. The results also reveal that the precision of TMPA products increases with longer time-aggregated data, and the detection capability of daily TMPA precipitation products are enhanced by augmentation with daily precipitation rates. In addition, daily TMPA products were input into the Xin'anjiang hydrologic model; the results show that 3B42V7-based simulated outputs were well in line with actual stream flow observations, with a high CC (0.90) and Nash-Sutcliffe efficiency coefficient (NSE, 0.79), and the results adequately captured the pattern of the observed flow curve.

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.

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient

PubMed Central

Yang, Tao; Zhang, Feipeng; Yardımcı, Galip Gürkan; Song, Fan; Hardison, Ross C.; Noble, William Stafford; Yue, Feng; Li, Qunhua

2017-01-01

Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach. PMID:28855260

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

Solutions for correlations along the coexistence curve and at the critical point of a kagomé lattice gas with three-particle interactions

NASA Astrophysics Data System (ADS)

Barry, J. H.; Muttalib, K. A.; Tanaka, T.

2008-01-01

We consider a two-dimensional (d=2) kagomé lattice gas model with attractive three-particle interactions around each triangular face of the kagomé lattice. Exact solutions are obtained for multiparticle correlations along the liquid and vapor branches of the coexistence curve and at criticality. The correlation solutions are also determined along the continuation of the curvilinear diameter of the coexistence region into the disordered fluid region. The method generates a linear algebraic system of correlation identities with coefficients dependent only upon the interaction parameter. Using a priori knowledge of pertinent solutions for the density and elementary triplet correlation, one finds a closed and linearly independent set of correlation identities defined upon a spatially compact nine-site cluster of the kagomé lattice. Resulting exact solution curves of the correlations are plotted and discussed as functions of the temperature and are compared with corresponding results in a traditional kagomé lattice gas having nearest-neighbor pair interactions. An example of application for the multiparticle correlations is demonstrated in cavitation theory.

Species distribution models predict temporal but not spatial variation in forest growth.

PubMed

van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

2017-04-01

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

Adapting the ISO 20462 softcopy ruler method for online image quality studies

NASA Astrophysics Data System (ADS)

Burns, Peter D.; Phillips, Jonathan B.; Williams, Don

2013-01-01

In this paper we address the problem of Image Quality Assessment of no reference metrics, focusing on JPEG corrupted images. In general no reference metrics are not able to measure with the same performance the distortions within their possible range and with respect to different image contents. The crosstalk between content and distortion signals influences the human perception. We here propose two strategies to improve the correlation between subjective and objective quality data. The first strategy is based on grouping the images according to their spatial complexity. The second one is based on a frequency analysis. Both the strategies are tested on two databases available in the literature. The results show an improvement in the correlations between no reference metrics and psycho-visual data, evaluated in terms of the Pearson Correlation Coefficient.

Bounds on isocurvature perturbations from cosmic microwave background and large scale structure data.

PubMed

Crotty, Patrick; García-Bellido, Juan; Lesgourgues, Julien; Riazuelo, Alain

2003-10-24

We obtain very stringent bounds on the possible cold dark matter, baryon, and neutrino isocurvature contributions to the primordial fluctuations in the Universe, using recent cosmic microwave background and large scale structure data. Neglecting the possible effects of spatial curvature, tensor perturbations, and reionization, we perform a Bayesian likelihood analysis with nine free parameters, and find that the amplitude of the isocurvature component cannot be larger than about 31% for the cold dark matter mode, 91% for the baryon mode, 76% for the neutrino density mode, and 60% for the neutrino velocity mode, at 2sigma, for uncorrelated models. For correlated adiabatic and isocurvature components, the fraction could be slightly larger. However, the cross-correlation coefficient is strongly constrained, and maximally correlated/anticorrelated models are disfavored. This puts strong bounds on the curvaton model.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data.

PubMed

Kim, Sehwi; Jung, Inkyung

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data

PubMed Central

Kim, Sehwi

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns. PMID:28753674

The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

ERIC Educational Resources Information Center

Trafimow, David

2016-01-01

Much of the science reported in the media depends on correlation coefficients. But the size of correlation coefficients depends, in part, on the reliability with which the correlated variables are measured. Understanding this is a statistical literacy issue.

Magnetocardiography and magnetoencephalography measurements at room temperature using tunnel magneto-resistance sensors

NASA Astrophysics Data System (ADS)

Fujiwara, Kosuke; Oogane, Mikihiko; Kanno, Akitake; Imada, Masahiro; Jono, Junichi; Terauchi, Takashi; Okuno, Tetsuo; Aritomi, Yuuji; Morikawa, Masahiro; Tsuchida, Masaaki; Nakasato, Nobukazu; Ando, Yasuo

2018-02-01

Magnetocardiography (MCG) and magnetoencephalography (MEG) signals were detected at room temperature using tunnel magneto-resistance (TMR) sensors. TMR sensors developed with low-noise amplifier circuits detected the MCG R wave without averaging, and the QRS complex was clearly observed with averaging at a high signal-to-noise ratio. Spatial mapping of the MCG was also achieved. Averaging of MEG signals triggered by electroencephalography (EEG) clearly observed the phase inversion of the alpha rhythm with a correlation coefficient as high as 0.7 between EEG and MEG.

Analytical solutions for solute transport in groundwater and riverine flow using Green's Function Method and pertinent coordinate transformation method

NASA Astrophysics Data System (ADS)

Sanskrityayn, Abhishek; Suk, Heejun; Kumar, Naveen

2017-04-01

In this study, analytical solutions of one-dimensional pollutant transport originating from instantaneous and continuous point sources were developed in groundwater and riverine flow using both Green's Function Method (GFM) and pertinent coordinate transformation method. Dispersion coefficient and flow velocity are considered spatially and temporally dependent. The spatial dependence of the velocity is linear, non-homogeneous and that of dispersion coefficient is square of that of velocity, while the temporal dependence is considered linear, exponentially and asymptotically decelerating and accelerating. Our proposed analytical solutions are derived for three different situations depending on variations of dispersion coefficient and velocity, respectively which can represent real physical processes occurring in groundwater and riverine systems. First case refers to steady solute transport situation in steady flow in which dispersion coefficient and velocity are only spatially dependent. The second case represents transient solute transport in steady flow in which dispersion coefficient is spatially and temporally dependent while the velocity is spatially dependent. Finally, the third case indicates transient solute transport in unsteady flow in which both dispersion coefficient and velocity are spatially and temporally dependent. The present paper demonstrates the concentration distribution behavior from a point source in realistically occurring flow domains of hydrological systems including groundwater and riverine water in which the dispersivity of pollutant's mass is affected by heterogeneity of the medium as well as by other factors like velocity fluctuations, while velocity is influenced by water table slope and recharge rate. Such capabilities give the proposed method's superiority about application of various hydrological problems to be solved over other previously existing analytical solutions. Especially, to author's knowledge, any other solution doesn't exist for both spatially and temporally variations of dispersion coefficient and velocity. In this study, the existing analytical solutions from previous widely known studies are used for comparison as validation tools to verify the proposed analytical solution as well as the numerical code of the Two-Dimensional Subsurface Flow, Fate and Transport of Microbes and Chemicals (2DFATMIC) code and the developed 1D finite difference code (FDM). All such solutions show perfect match with the respective proposed solutions.

A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.

PubMed

Cao, Cheng; Akalin Acar, Zeynep; Kreutz-Delgado, Kenneth; Makeig, Scott

2012-01-01

Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm.

Two-colour chewing gum mixing ability: digitalisation and spatial heterogeneity analysis.

PubMed

Weijenberg, R A F; Scherder, E J A; Visscher, C M; Gorissen, T; Yoshida, E; Lobbezoo, F

2013-10-01

Many techniques are available to assess masticatory performance, but not all are appropriate for every population. A proxy suitable for elderly persons suffering from dementia was lacking, and a two-colour chewing gum mixing ability test was investigated for this purpose. A fully automated digital analysis algorithm was applied to a mixing ability test using two-coloured gum samples in a stepwise increased number of chewing cycles protocol (Experiment 1: n = 14; seven men, 19-63 years), a test-retest assessment (Experiment 2: n = 10; four men, 20-49 years) and compared to an established wax cubes mixing ability test (Experiment 3: n = 13; 0 men, 21-31 years). Data were analysed with repeated measures anova (Experiment 1), the calculation of the intraclass correlation coefficient (ICC; Experiment 2) and Spearman's rho correlation coefficient (Experiment 3). The method was sensitive to increasing numbers of chewing cycles (F5,65 = 57·270, P = 0·000) and reliable in the test-retest (ICC value of 0·714, P = 0·004). There was no significant correlation between the two-coloured gum test and the wax cubes test. The two-coloured gum mixing ability test was able to adequately assess masticatory function and is recommended for use in a population of elderly persons with dementia. © 2013 John Wiley & Sons Ltd.

Performance evaluation of receive-diversity free-space optical communications over correlated Gamma-Gamma fading channels.

PubMed

Yang, Guowei; Khalighi, Mohammad-Ali; Ghassemlooy, Zabih; Bourennane, Salah

2013-08-20

The efficacy of spatial diversity in practical free-space optical communication systems is impaired by the fading correlation among the underlying subchannels. We consider in this paper the generation of correlated Gamma-Gamma random variables in view of evaluating the system outage probability and bit-error-rate under the condition of correlated fading. Considering the case of receive-diversity systems with intensity modulation and direct detection, we propose a set of criteria for setting the correlation coefficients on the small- and large-scale fading components based on scintillation theory. We verify these criteria using wave-optics simulations and further show through Monte Carlo simulations that we can effectively neglect the correlation corresponding to the small-scale turbulence in most practical systems, irrespective of the specific turbulence conditions. This has not been clarified before, to the best of our knowledge. We then present some numerical results to illustrate the effect of fading correlation on the system performance. Our conclusions can be generalized to the cases of multiple-beam and multiple-beam multiple-aperture systems.

Using an Extended Kalman Filter Learning Algorithm for Feed-Forward Neural Networks to Describe Tracer Correlations

NASA Technical Reports Server (NTRS)

Lary, David J.; Mussa, Yussuf

2004-01-01

In this study a new extended Kalman filter (EKF) learning algorithm for feed-forward neural networks (FFN) is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). The neural network was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.

A Common Calibration Source Framework for Fully-Polarimetric and Interferometric Radiometers

NASA Technical Reports Server (NTRS)

Kim, Edward J.; Davis, Brynmor; Piepmeier, Jeff; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

Two types of microwave radiometry--synthetic thinned array radiometry (STAR) and fully-polarimetric (FP) radiometry--have received increasing attention during the last several years. STAR radiometers offer a technological solution to achieving high spatial resolution imaging from orbit without requiring a filled aperture or a moving antenna, and FP radiometers measure extra polarization state information upon which entirely new or more robust geophysical retrieval algorithms can be based. Radiometer configurations used for both STAR and FP instruments share one fundamental feature that distinguishes them from more 'standard' radiometers, namely, they measure correlations between pairs of microwave signals. The calibration requirements for correlation radiometers are broader than those for standard radiometers. Quantities of interest include total powers, complex correlation coefficients, various offsets, and possible nonlinearities. A candidate for an ideal calibration source would be one that injects test signals with precisely controllable correlation coefficients and absolute powers simultaneously into a pair of receivers, permitting all of these calibration quantities to be measured. The complex nature of correlation radiometer calibration, coupled with certain inherent similarities between STAR and FP instruments, suggests significant leverage in addressing both problems together. Recognizing this, a project was recently begun at NASA Goddard Space Flight Center to develop a compact low-power subsystem for spaceflight STAR or FP receiver calibration. We present a common theoretical framework for the design of signals for a controlled correlation calibration source. A statistical model is described, along with temporal and spectral constraints on such signals. Finally, a method for realizing these signals is demonstrated using a Matlab-based implementation.

FlowShape: a runoff connectivity index for patched environments, based on shape and orientation of runoff sources

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Malkinson, Dan; Ursino, Nadia; Wittenberg, Lea

2016-04-01

The properties of vegetation cover are recognized to be a key factor in determining runoff processes and yield over natural areas. Still, how the actual vegetation spatial distribution affects these processes is not completely understood. In Mediterranean semi-arid regions, patched landscapes are often found, with clumped vegetation, grass or shrubs, surrounded by bare soil patches. These two phases produce a sink-source system for runoff, as precipitation falling over bare areas barely infiltrates and rather flows downslope. In contrast, vegetated patches have high infiltrability and can partially retain the runon water. We hypothesize that, at a relatively small scale, the shape and orientation of bare soil patches with respect to the runoff flow direction is a significant for the connectivity of the runoff flow paths, and consequently for runoff values. We derive an index, FlowShape, which is candidate to be a good proxy for runoff connectivity and thus runoff production in patched environments. FlowShape is an area-weighted average of the geometrical properties of each bare soil patch. Eight experimental plots in northern Israel were monitored during 2 years after a wildfire which occurred in 2006. Runoff was collected and measured - along with rainfall depth - after each rainfall event, at different levels of vegetation cover corresponding to post-fire recovery of vegetation and seasonality. We obtained a good correlation between FlowShape and the runoff coefficient, at two conditions: a minimal percentage of vegetation cover over the plot, and minimal rainfall depth. Our results support the hypothesis that the spatial distribution of the two phases (vegetation and bare soil) in patched landscapes dictates, at least partially, runoff yield. The correlation between the runoff coefficient and FlowShape, which accounts for shape and orientation of soil patches, is higher than the correlation between the runoff coefficient and the bare soil percentage alone. Besides that, the existence of a vegetation cover threshold under which FlowShape loses correlation with runoff yield, suggests that different processes occur at different levels of vegetation cover. On bare or almost bare plots, runoff flows as a sheet, and small isolated plants do not impose a directionality to the flow or interrupt runoff connectivity. On the other hand, rainfall depth - and possibly rainfall intensity - also affect the hydrological processes of infiltration and runoff production, and thus the applicability of any purely geometrical index. We compared the correlation to runoff coefficient with the FlowShape and FlowLength, a well-known index for runoff connectivity (Mayor et al., 2008) which is defined as the average of runoff flow paths over the plot. As microtopography was not available, our plots were idealized as planar hillslopes. We found that FlowShape is a better predictor than FlowLength for runoff yield over our experimental plots.

Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

NASA Astrophysics Data System (ADS)

Piretzidis, D.; Sra, G.; Sideris, M. G.

2016-12-01

This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

Distributed multi-criteria model evaluation and spatial association analysis

NASA Astrophysics Data System (ADS)

Scherer, Laura; Pfister, Stephan

2015-04-01

Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the high spatial association with the aridity index (ratio of mean annual precipitation to mean annual potential evapotranspiration). This association was still significant when controlling for slopes which manifested the second highest spatial association. In line with these findings, overall model efficiency of the entire Mississippi watershed appeared better when weighted with mean observed river discharge. Furthermore, the model received the highest rating with regards to PBIAS and was judged worst when considering NSE as the most comprehensive indicator. No universal performance indicator exists that considers all aspects of a hydrograph. Therefore, sound model evaluation must take into account multiple criteria. Since model efficiency varies in space which is masked by aggregated ratings spatially explicit model goodness should be communicated as standard praxis - at least as a measure of spatial variability of indicators. Furthermore, transparent documentation of the evaluation procedure also with regards to weighting of aggregated model performance is crucial but often lacking in published research. Finally, the high spatial association between model performance and aridity highlights the need to improve modelling schemes for arid conditions as priority over other aspects that might weaken model goodness.

A comparative analysis of two highly spatially resolved European atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

2013-08-01

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES-DIS for the first two sectors and to the distinct data sources that were used by the TNO and HERMES-DIS for road transport. Regarding the regression analysis, the greatest correlation occurred between the EMEParea and HERMES-DIS because the latter is derived from the first, which does not occur for the TNO emissions. The greatest correlations were encountered for agriculture NH3 emissions, due to the common use of the CORINE Land Cover database for disaggregation. The point source emissions (energy industries, industrial processes, industrial combustion and extraction/distribution of fossil fuels) resulted in the lowest coefficients of determination. The spatial variability of SOx differed among the emissions that were obtained from the different disaggregation methods. In conclusion, HERMES-DIS and TNO are two distinct emission inventories, both very well discretized and detailed, suitable for air quality modelling. However, the different databases and distinct disaggregation methodologies that were used certainly result in different spatial emission patterns. This fact should be considered when applying regional atmospheric chemical transport models. Future work will focus on the evaluation of air quality models performance and sensitivity to these spatial discrepancies in emission inventories. Air quality modelling will benefit from the availability of appropriate resolution, consistent and reliable emission inventories.

Fractal regional myocardial blood flows pattern according to metabolism, not vascular anatomy

PubMed Central

Yipintsoi, Tada; Kroll, Keith

2015-01-01

Regional myocardial blood flows are markedly heterogeneous. Fractal analysis shows strong near-neighbor correlation. In experiments to distinguish control by vascular anatomy vs. local vasomotion, coronary flows were increased in open-chest dogs by stimulating myocardial metabolism (catecholamines + atropine) with and without adenosine. During control states mean left ventricular (LV) myocardial blood flows (microspheres) were 0.5–1 ml·g−1·min−1 and increased to 2–3 ml·g−1·min−1 with catecholamine infusion and to ∼4 ml·g−1·min−1 with adenosine (Ado). Flow heterogeneity was similar in all states: relative dispersion (RD = SD/mean) was ∼25%, using LV pieces 0.1–0.2% of total. During catecholamine infusion local flows increased in proportion to the mean flows in 45% of the LV, “tracking” closely (increased proportionately to mean flow), while ∼40% trended toward the mean. Near-neighbor regional flows remained strongly spatially correlated, with fractal dimension D near 1.2 (Hurst coefficient 0.8). The spatial patterns remain similar at varied levels of metabolic stimulation inferring metabolic dominance. In contrast, adenosine vasodilation increased flows eightfold times control while destroying correlation with the control state. The Ado-induced spatial patterns differed from control but were self-consistent, inferring that with full vasodilation the relaxed arterial anatomy dominates the distribution. We conclude that vascular anatomy governs flow distributions during adenosine vasodilation but that metabolic vasoregulation dominates in normal physiological states. PMID:26589329

Fractal regional myocardial blood flows pattern according to metabolism, not vascular anatomy.

PubMed

Yipintsoi, Tada; Kroll, Keith; Bassingthwaighte, James B

2016-02-01

Regional myocardial blood flows are markedly heterogeneous. Fractal analysis shows strong near-neighbor correlation. In experiments to distinguish control by vascular anatomy vs. local vasomotion, coronary flows were increased in open-chest dogs by stimulating myocardial metabolism (catecholamines + atropine) with and without adenosine. During control states mean left ventricular (LV) myocardial blood flows (microspheres) were 0.5-1 ml·g(-1)·min(-1) and increased to 2-3 ml·g(-1)·min(-1) with catecholamine infusion and to ∼4 ml·g(-1)·min(-1) with adenosine (Ado). Flow heterogeneity was similar in all states: relative dispersion (RD = SD/mean) was ∼25%, using LV pieces 0.1-0.2% of total. During catecholamine infusion local flows increased in proportion to the mean flows in 45% of the LV, "tracking" closely (increased proportionately to mean flow), while ∼40% trended toward the mean. Near-neighbor regional flows remained strongly spatially correlated, with fractal dimension D near 1.2 (Hurst coefficient 0.8). The spatial patterns remain similar at varied levels of metabolic stimulation inferring metabolic dominance. In contrast, adenosine vasodilation increased flows eightfold times control while destroying correlation with the control state. The Ado-induced spatial patterns differed from control but were self-consistent, inferring that with full vasodilation the relaxed arterial anatomy dominates the distribution. We conclude that vascular anatomy governs flow distributions during adenosine vasodilation but that metabolic vasoregulation dominates in normal physiological states. Copyright © 2016 the American Physiological Society.

Seasonal and interannual variability of the Arctic sea ice: A comparison between AO-FVCOM and observations

NASA Astrophysics Data System (ADS)

Zhang, Yu; Chen, Changsheng; Beardsley, Robert C.; Gao, Guoping; Qi, Jianhua; Lin, Huichan

2016-11-01

A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the sea ice in the Arctic over the period 1978-2014. The spatial-varying horizontal model resolution was designed to better resolve both topographic and baroclinic dynamics scales over the Arctic slope and narrow straits. The model-simulated sea ice was in good agreement with available observed sea ice extent, concentration, drift velocity and thickness, not only in seasonal and interannual variability but also in spatial distribution. Compared with six other Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME, and UW), the AO-FVCOM-simulated ice thickness showed a higher mean correlation coefficient of ˜0.63 and a smaller residual with observations. Model-produced ice drift speed and direction errors varied with wind speed: the speed and direction errors increased and decreased as the wind speed increased, respectively. Efforts were made to examine the influences of parameterizations of air-ice external and ice-water interfacial stresses on the model-produced bias. The ice drift direction was more sensitive to air-ice drag coefficients and turning angles than the ice drift speed. Increasing or decreasing either 10% in water-ice drag coefficient or 10° in water-ice turning angle did not show a significant influence on the ice drift velocity simulation results although the sea ice drift speed was more sensitive to these two parameters than the sea ice drift direction. Using the COARE 4.0-derived parameterization of air-water drag coefficient for wind stress did not significantly influence the ice drift velocity simulation.

Estimation of regionalized compositions: A comparison of three methods

USGS Publications Warehouse

Pawlowsky, V.; Olea, R.A.; Davis, J.C.

1995-01-01

A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.

Spatial variation of peat soil properties in the oil-producing region of northeastern Sakhalin

NASA Astrophysics Data System (ADS)

Lipatov, D. N.; Shcheglov, A. I.; Manakhov, D. V.; Zavgorodnyaya, Yu. A.; Rozanova, M. S.; Brekhov, P. T.

2017-07-01

Morphology and properties of medium-deep oligotrophic peat, oligotrophic peat gley, pyrogenic oligotrophic peat gley, and peat gley soils on subshrub-cotton grass-sphagnum bogs and in swampy larch forests of northeastern Sakhalin have been studied. Variation in the thickness and reserves of litters in the studied bog and forest biogeocenoses has been analyzed. The profile distribution and spatial variability of moisture, density, ash, and pHKCl in separate groups of peat soils have been described. The content and spatial variability of petroleum hydrocarbons have been considered in relation to the accumulation of natural bitumoids by peat soils and the technogenic pressing in the oil-producing region. Variation of each parameter at different distances (10, 50, and 1000 m) has been estimated using a hierarchical sampling scheme. The spatial conjugation of soil parameters has been studied by factor analysis using the principal components method and Spearman correlation coefficients. Regression equations have been proposed to describe relationships of ash content with soil density and content of petroleum hydrocarbons in peat horizons.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

PubMed

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

Spatial and seasonal changes in optical properties of autochthonous and allochthonous chromophoric dissolved organic matter in a stratified mountain lake.

PubMed

Bracchini, Luca; Dattilo, Arduino Massimo; Hull, Vincent; Loiselle, Steven Arthur; Nannicini, Luciano; Picchi, Maria Pia; Ricci, Maso; Santinelli, Chiara; Seritti, Alfredo; Tognazzi, Antonio; Rossi, Claudio

2010-03-01

In this study, we present results on seasonal and spatial changes in CDOM absorption and fluorescence (fCDOM) in a deep mountain lake (Salto Lake, Italy). A novel approach was used to describe the shape of CDOM absorption between 250-700 nm (distribution of the spectral slope, S(lambda)) and a new fluorescence ratio is used to distinguish between humic and amino acid-like components. Solar ultraviolet irradiance, dissolved organic carbon (DOC), DOM fluorescence and absorption measurements were analysed and compared to other physicochemical parameters. We show that in the UV-exposed mixed layer: (i) fluorescence by autochthonous amino acid-like CDOM, (ii) values of S(lambda) across UV-C and UV-B wavebands increased during the summer months, whereas (i) average molar absorption coefficient and (ii) fluorescence by allochthonous humic CDOM decreased. In the unexposed deep layer of the water column (and in the entire water column in winter), humic-like CDOM presented high values of molar absorption coefficients and low values of S(lambda). UV attenuation coefficients correlated with both chlorophyll a concentrations and CDOM absorption. In agreement with changes in CDOM, minimal values in UV attenuation were found in summer. The S(lambda) curve was used as a signature of the mixture between photobleached and algal-derived CDOM with respect to the unexposed chromophoric dissolved compounds in this thermal stratified lake. Furthermore, S(lambda) curves were useful to distinguish between low and high molecular weight CDOM.

Spatial information management platform for Dunhuang Global Geopark

NASA Astrophysics Data System (ADS)

Yan-long, YU; Fa-dong, WU; Jin-fang, HAN; Yan-Jie, WANG; Hao, CHU

2017-02-01

As a member of UNESCO Global Geoparks, Dunhuang Global Geopark has developed a great quantity of landforms formed under special geological background and extremely droughty climate, which integrate together with specific geographic location and cultural relics on the “Silk Road Economic Belt”. The main geoheritage in Dunhuang Global Geopark is Yardang landform, which is formed by loose Quaternary sediments. According to different shapes, the Yardang landform were divided into five types, namely, ridge-shaped Yardang, wall-shaped Yardang, tower-shape Yardang, column Yardang and Yardang monadnock. In order to monitor and protect the unique morphological features of Yardang landforms, a spatial information management platform is established, using SPOT 6 remote sensing image, with object oriented approach and manual interactive interpretation. Study shows that the maximum area, perimeter, length and width of Yardang were 324843.1 m2, 3447.52 m, 1508.41m, and 285.81 m, respectively. Additionally, the aspect ratio of Yardang has a certain positive correlation, with the coefficient of correlation being 0.675. Furthermore, the relationship between length and width of Yardang is calculated using formula Y=2.546X, where Y = length, X = width.

Predicting chroma from luma with frequency domain intra prediction

NASA Astrophysics Data System (ADS)

Egge, Nathan E.; Valin, Jean-Marc

2015-03-01

This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conversion has the property that it decorrelates the color planes globally across an image, there is still some correlation locally at the block level.1 Previous proposals compute a linear model of the spatial relationship between the luma plane (Y) and the two chroma planes (U and V).2 In codecs that use lapped transforms this is not possible since transform support extends across the block boundaries3 and thus neighboring blocks are unavailable during intra- prediction. We design a frequency domain intra predictor for chroma that exploits the same local correlation with lower complexity than the spatial predictor and which works with lapped transforms. We then describe a low- complexity algorithm that directly uses luma coefficients as a chroma predictor based on gain-shape quantization and band partitioning. An experiment is performed that compares these two techniques inside the experimental Daala video codec and shows the lower complexity algorithm to be a better chroma predictor.

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

Spatially variable stage-driven groundwater-surface water interaction inferred from time-frequency analysis of distributed temperature sensing data

USGS Publications Warehouse

Mwakanyamale, Kisa; Slater, Lee; Day-Lewis, Frederick D.; Elwaseif, Mehrez; Johnson, Carole D.

2012-01-01

Characterization of groundwater-surface water exchange is essential for improving understanding of contaminant transport between aquifers and rivers. Fiber-optic distributed temperature sensing (FODTS) provides rich spatiotemporal datasets for quantitative and qualitative analysis of groundwater-surface water exchange. We demonstrate how time-frequency analysis of FODTS and synchronous river stage time series from the Columbia River adjacent to the Hanford 300-Area, Richland, Washington, provides spatial information on the strength of stage-driven exchange of uranium contaminated groundwater in response to subsurface heterogeneity. Although used in previous studies, the stage-temperature correlation coefficient proved an unreliable indicator of the stage-driven forcing on groundwater discharge in the presence of other factors influencing river water temperature. In contrast, S-transform analysis of the stage and FODTS data definitively identifies the spatial distribution of discharge zones and provided information on the dominant forcing periods (≥2 d) of the complex dam operations driving stage fluctuations and hence groundwater-surface water exchange at the 300-Area.

Inflation in Flatland

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

Hinterbichler, Kurt; Joyce, Austin; Khoury, Justin, E-mail: kurt.hinterbichler@case.edu, E-mail: austin.joyce@columbia.edu, E-mail: jkhoury@sas.upenn.edu

We investigate the symmetry structure of inflation in 2+1 dimensions. In particular, we show that the asymptotic symmetries of three-dimensional de Sitter space are in one-to-one correspondence with cosmological adiabatic modes for the curvature perturbation. In 2+1 dimensions, the asymptotic symmetry algebra is infinite-dimensional, given by two copies of the Virasoro algebra, and can be traced to the conformal symmetries of the two-dimensional spatial slices of de Sitter. We study the consequences of this infinite-dimensional symmetry for inflationary correlation functions, finding new soft theorems that hold only in 2+1 dimensions. Expanding the correlation functions as a power series in themore » soft momentum q , these relations constrain the traceless part of the tensorial coefficient at each order in q in terms of a lower-point function. As a check, we verify that the O( q {sup 2}) identity is satisfied by inflationary correlation functions in the limit of small sound speed.« less

Non-Gaussian diffusion in static disordered media

NASA Astrophysics Data System (ADS)

Luo, Liang; Yi, Ming

2018-04-01

Non-Gaussian diffusion is commonly considered as a result of fluctuating diffusivity, which is correlated in time or in space or both. In this work, we investigate the non-Gaussian diffusion in static disordered media via a quenched trap model, where the diffusivity is spatially correlated. Several unique effects due to quenched disorder are reported. We analytically estimate the diffusion coefficient Ddis and its fluctuation over samples of finite size. We show a mechanism of population splitting in the non-Gaussian diffusion. It results in a sharp peak in the distribution of displacement P (x ,t ) around x =0 , that has frequently been observed in experiments. We examine the fidelity of the coarse-grained diffusion map, which is reconstructed from particle trajectories. Finally, we propose a procedure to estimate the correlation length in static disordered environments, where the information stored in the sample-to-sample fluctuation has been utilized.

LASERS IN MEDICINE: Determination of the optical characteristics of turbid media by the laser optoacoustic method

NASA Astrophysics Data System (ADS)

Karabutov, Aleksander A.; Pelivanov, Ivan M.; Podymova, N. B.; Skipetrov, S. E.

1999-12-01

A method, based on the optoacoustic effect for determination of the spatial distribution of the light intensity in turbid media and of the optical characteristics of such media was proposed (and implemented experimentally). A temporal profile of the pressure of a thermo-optically excited acoustic pulse was found to be governed by the absorption coefficient and by the spatial distribution of the light intensity in the investigated medium. The absorption coefficient and the reduced light-scattering coefficient of model turbid water-like media were measured by the optoacoustic method. The results of a direct determination of the spatial light-intensity distribution agreed with a theoretical calculation made in the diffusion approximation.

SAR Interferometry: On the Coherence Estimation in non Stationary Scenes

NASA Astrophysics Data System (ADS)

Ballatore, P.

2005-05-01

The possibility of producing good quality satellite SAR interferometry allows observations of terrain mass movement as small as millimetric scales, with applicability in researches about landslides, volcanoes, seismology and others. SAR interferometric images is characterized by the presence of random speckle, whose pattern does not correspond to the underlying image structure. However the local brightness of speckle reflects the local echogenicity of the underlying scatters. Specifically, the coherence between interferometric pair is generally considered as an indicator of interferogram quality. Moreover, it leads to useful image segmentations and it can be employed in data mining and database browsing algorithms. SAR coherence is generally computed by substituting the ensemble averages with the spatial averages, by assuming ergodicity in the estimation window sub-areas. Nevertheless, the actual results may depend on the spatial size scale of the sampling window used for the computation. This is especially true in the cases of fast coherence estimator algorithms, which make use of the correlation coefficient's square root (Rignon and van Zyl, IEEE Trans. Geosci.Remote Sensing, vol. 31, n. 4, pp. 896-906, 1993; Guarnieri and Prati, IEEE Trans. Geosci. Remote Sensing, vol. 35, n. 3, pp. 660-669, 1997). In fact, the correlation coefficient is increased by image texture, due to non stationary absolute values within single sample estimation windows. For example, this can happen in the case of mountainous lands, and, specifically, in the case of the Italian Southern Appennini region around Benevento city, which is of specific geophysical attention for its numerous seismic and landslide terrain movements. In these cases, dedicated techniques are applied for compensating texture effects. This presentation shows an example of interferometric coherence image depending on the spatial size of sampling window. Moreover, the different methodologies present in literature for texture effect control are briefly summarized and applied to our specific exemplary case. A quantitative comparison among resulting coherences is illustrated and discussed in terms of different experimental applicability.

Intra-urban spatial variability of PM2.5-bound carbonaceous components

NASA Astrophysics Data System (ADS)

Xie, Mingjie; Coons, Teresa L.; Dutton, Steven J.; Milford, Jana B.; Miller, Shelly L.; Peel, Jennifer L.; Vedal, Sverre; Hannigan, Michael P.

2012-12-01

The Denver Aerosol Sources and Health (DASH) study was designed to evaluate associations between PM2.5 species and sources and adverse human health effects. The DASH study generated a five-year (2003-2007) time series of daily speciated PM2.5 concentration measurements from a single, special-purpose monitoring site in Denver, CO. To evaluate the ability of this site to adequately represent the short term temporal variability of PM2.5 concentrations in the five county Denver metropolitan area, a one year supplemental set of PM2.5 samples was collected every sixth day at the original DASH monitoring site and concurrently at three additional sites. Two of the four sites, including the original DASH site, were located in residential areas at least 1.9 km from interstate highways. The other two sites were located within 0.3 km of interstate highways. Concentrations of elemental carbon (EC), organic carbon (OC), and 58 organic molecular markers were measured at each site. To assess spatial variability, site pairs were compared using the Pearson correlation coefficient (r) and coefficient of divergence (COD), a statistic that provides information on the degree of uniformity between monitoring sites. Bi-weekly co-located samples collected from July 2004 to September 2005 were also analyzed and used to estimate the uncertainty associated with sampling and analytical measurement for each species. In general, the two near-highway sites exhibited higher concentrations of EC, OC, polycyclic aromatic hydrocarbons (PAHs), and steranes than did the more residential sites. Lower spatial heterogeneity based on r and COD was inferred for all carbonaceous species after considering their divergence and lack of perfect correlations in co-located samples. Ratio-ratio plots combined with available gasoline- and diesel-powered motor vehicle emissions profiles for the region suggested a greater impact to high molecular weight (HMW) PAHs from diesel-powered vehicles at the near-highway sites and a more uniformly distributed impact to ambient hopanes from gasoline-powered motor vehicles at all four sites.

Comparison of Satellite Data with Ground-Based Measurements for Assessing Local Distributions of PM2.5 in Northeast Mexico.

NASA Astrophysics Data System (ADS)

Carmona, J.; Mendoza, A.; Lozano, D.; Gupta, P.; Mejia, G.; Rios, J.; Hernández, I.

2017-12-01

Estimating ground-level PM2.5 from satellite-derived Aerosol Optical Depth (AOD) through statistical models is a promising method to evaluate the spatial and temporal distribution of PM2.5 in regions where there are no or few ground-based observations, i.e. Latin America. Although PM concentrations are most accurately measured using ground-based instrumentation, the spatial coverage is too sparse to determine local and regional variations in PM. AOD satellite data offer the opportunity to overcome the spatial limitation of ground-based measurements. However, estimating PM surface concentrations from AOD satellite data is challenging, since multiple factors can affect the relationship between the total-column of AOD and the surface-concentration of PM. In this study, an Assembled Multiple Linear Regression Model (MLR) and a Neural Network Model (NN) were performed to estimate the relationship between the AOD and ground-concentrations of PM2.5 within the Monterrey Metropolitan Area (MMA). The MMA is located in northeast Mexico and is the third most populated urban area in the country. Episodes of high PM pollution levels are frequent throughout the year at the MMA. Daily averages of meteorological and air quality parameters were determined from data recorded at 5 monitoring sites of the MMA air quality monitoring network. Daily AOD data were retrieved from the MODIS sensor onboard the Aqua satellite. Overall, the best performance of the models was obtained using an AOD at 550 µm from the MYD04_3k product in combination with Temperature, Relative Humidity, Wind Speed and Wind Direction ground-based data. For the MLR performed, a correlation coefficient of R 0.6 and % bias of -6% were obtained. The NN showed a better performance than the MLR, with a correlation coefficient of R 0.75 and % bias -4%. The results obtained confirmed that satellite-derived AOD in combination with meteorological fields may allow to estimate PM2.5 local distributions.

Direct observation of single layer graphene oxide reduction through spatially resolved, single sheet absorption/emission microscopy.

PubMed

Sokolov, Denis A; Morozov, Yurii V; McDonald, Matthew P; Vietmeyer, Felix; Hodak, Jose H; Kuno, Masaru

2014-06-11

Laser reduction of graphene oxide (GO) offers unique opportunities for the rapid, nonchemical production of graphene. By tuning relevant reduction parameters, the band gap and conductivity of reduced GO can be precisely controlled. In situ monitoring of single layer GO reduction is therefore essential. In this report, we show the direct observation of laser-induced, single layer GO reduction through correlated changes to its absorption and emission. Absorption/emission movies illustrate the initial stages of single layer GO reduction, its transition to reduced-GO (rGO) as well as its subsequent decomposition upon prolonged laser illumination. These studies reveal GO's photoreduction life cycle and through it native GO/rGO absorption coefficients, their intrasheet distributions as well as their spatial heterogeneities. Extracted absorption coefficients for unreduced GO are α405 nm ≈ 6.5 ± 1.1 × 10(4) cm(-1), α520 nm ≈ 2.1 ± 0.4 × 10(4) cm(-1), and α640 nm ≈ 1.1 ± 0.3 × 10(4) cm(-1) while corresponding rGO α-values are α405 nm ≈ 21.6 ± 0.6 × 10(4) cm(-1), α520 nm ≈ 16.9 ± 0.4 × 10(4) cm(-1), and α640 nm ≈ 14.5 ± 0.4 × 10(4) cm(-1). More importantly, the correlated absorption/emission imaging provides us with unprecedented insight into GO's underlying photoreduction mechanism, given our ability to spatially resolve its kinetics and to connect local rate constants to activation energies. On a broader level, the developed absorption imaging is general and can be applied toward investigating the optical properties of other two-dimensional materials, especially those that are nonemissive and are invisible to current single molecule optical techniques.

Scale effects on information theory-based measures applied to streamflow patterns in two rural watersheds

NASA Astrophysics Data System (ADS)

Pan, Feng; Pachepsky, Yakov A.; Guber, Andrey K.; McPherson, Brian J.; Hill, Robert L.

2012-01-01

SummaryUnderstanding streamflow patterns in space and time is important for improving flood and drought forecasting, water resources management, and predictions of ecological changes. Objectives of this work include (a) to characterize the spatial and temporal patterns of streamflow using information theory-based measures at two thoroughly-monitored agricultural watersheds located in different hydroclimatic zones with similar land use, and (b) to elucidate and quantify temporal and spatial scale effects on those measures. We selected two USDA experimental watersheds to serve as case study examples, including the Little River experimental watershed (LREW) in Tifton, Georgia and the Sleepers River experimental watershed (SREW) in North Danville, Vermont. Both watersheds possess several nested sub-watersheds and more than 30 years of continuous data records of precipitation and streamflow. Information content measures (metric entropy and mean information gain) and complexity measures (effective measure complexity and fluctuation complexity) were computed based on the binary encoding of 5-year streamflow and precipitation time series data. We quantified patterns of streamflow using probabilities of joint or sequential appearances of the binary symbol sequences. Results of our analysis illustrate that information content measures of streamflow time series are much smaller than those for precipitation data, and the streamflow data also exhibit higher complexity, suggesting that the watersheds effectively act as filters of the precipitation information that leads to the observed additional complexity in streamflow measures. Correlation coefficients between the information-theory-based measures and time intervals are close to 0.9, demonstrating the significance of temporal scale effects on streamflow patterns. Moderate spatial scale effects on streamflow patterns are observed with absolute values of correlation coefficients between the measures and sub-watershed area varying from 0.2 to 0.6 in the two watersheds. We conclude that temporal effects must be evaluated and accounted for when the information theory-based methods are used for performance evaluation and comparison of hydrological models.

Metal contamination in campus dust of Xi'an, China: a study based on multivariate statistics and spatial distribution.

PubMed

Chen, Hao; Lu, Xinwei; Li, Loretta Y; Gao, Tianning; Chang, Yuyu

2014-06-15

The concentrations of As, Ba, Co, Cr, Cu, Mn, Ni, Pb, V and Zn in campus dust from kindergartens, elementary schools, middle schools and universities of Xi'an, China were determined by X-ray fluorescence spectrometry. Correlation coefficient analysis, principal component analysis (PCA) and cluster analysis (CA) were used to analyze the data and to identify possible sources of these metals in the dust. The spatial distributions of metals in urban dust of Xi'an were analyzed based on the metal concentrations in campus dusts using the geostatistics method. The results indicate that dust samples from campuses have elevated metal concentrations, especially for Pb, Zn, Co, Cu, Cr and Ba, with the mean values of 7.1, 5.6, 3.7, 2.9, 2.5 and 1.9 times the background values for Shaanxi soil, respectively. The enrichment factor results indicate that Mn, Ni, V, As and Ba in the campus dust were deficiently to minimally enriched, mainly affected by nature and partly by anthropogenic sources, while Co, Cr, Cu, Pb and Zn in the campus dust and especially Pb and Zn were mostly affected by human activities. As and Cu, Mn and Ni, Ba and V, and Pb and Zn had similar distribution patterns. The southwest high-tech industrial area and south commercial and residential areas have relatively high levels of most metals. Three main sources were identified based on correlation coefficient analysis, PCA, CA, as well as spatial distribution characteristics. As, Ni, Cu, Mn, Pb, Zn and Cr have mixed sources - nature, traffic, as well as fossil fuel combustion and weathering of materials. Ba and V are mainly derived from nature, but partly also from industrial emissions, as well as construction sources, while Co principally originates from construction. Copyright © 2014 Elsevier B.V. All rights reserved.

Thinner regions of intracranial aneurysm wall correlate with regions of higher wall shear stress: a 7.0 tesla MRI

PubMed Central

Blankena, Roos; Kleinloog, Rachel; Verweij, Bon H.; van Ooij, Pim; ten Haken, Bennie; Luijten, Peter R.; Rinkel, Gabriel J.E.; Zwanenburg, Jaco J.M.

2016-01-01

Purpose To develop a method for semi-quantitative wall thickness assessment on in vivo 7.0 tesla (7T) MRI images of intracranial aneurysms for studying the relation between apparent aneurysm wall thickness and wall shear stress. Materials and Methods Wall thickness was analyzed in 11 unruptured aneurysms in 9 patients, who underwent 7T MRI with a TSE based vessel wall sequence (0.8 mm isotropic resolution). A custom analysis program determined the in vivo aneurysm wall intensities, which were normalized to signal of nearby brain tissue and were used as measure for apparent wall thickness (AWT). Spatial wall thickness variation was determined as the interquartile range in AWT (the middle 50% of the AWT range). Wall shear stress was determined using phase contrast MRI (0.5 mm isotropic resolution). We performed visual and statistical comparisons (Pearson’s correlation) to study the relation between wall thickness and wall shear stress. Results 3D colored AWT maps of the aneurysms showed spatial AWT variation, which ranged from 0.07 to 0.53, with a mean variation of 0.22 (a variation of 1.0 roughly means a wall thickness variation of one voxel (0.8mm)). In all aneurysms, AWT was inversely related to WSS (mean correlation coefficient −0.35, P<0.05). Conclusions A method was developed to measure the wall thickness semi-quantitatively, using 7T MRI. An inverse correlation between wall shear stress and AWT was determined. In future studies, this non-invasive method can be used to assess spatial wall thickness variation in relation to pathophysiologic processes such as aneurysm growth and –rupture. PMID:26892986

Subcortical structure segmentation using probabilistic atlas priors

NASA Astrophysics Data System (ADS)

Gouttard, Sylvain; Styner, Martin; Joshi, Sarang; Smith, Rachel G.; Cody Hazlett, Heather; Gerig, Guido

2007-03-01

The segmentation of the subcortical structures of the brain is required for many forms of quantitative neuroanatomic analysis. The volumetric and shape parameters of structures such as lateral ventricles, putamen, caudate, hippocampus, pallidus and amygdala are employed to characterize a disease or its evolution. This paper presents a fully automatic segmentation of these structures via a non-rigid registration of a probabilistic atlas prior and alongside a comprehensive validation. Our approach is based on an unbiased diffeomorphic atlas with probabilistic spatial priors built from a training set of MR images with corresponding manual segmentations. The atlas building computes an average image along with transformation fields mapping each training case to the average image. These transformation fields are applied to the manually segmented structures of each case in order to obtain a probabilistic map on the atlas. When applying the atlas for automatic structural segmentation, an MR image is first intensity inhomogeneity corrected, skull stripped and intensity calibrated to the atlas. Then the atlas image is registered to the image using an affine followed by a deformable registration matching the gray level intensity. Finally, the registration transformation is applied to the probabilistic maps of each structures, which are then thresholded at 0.5 probability. Using manual segmentations for comparison, measures of volumetric differences show high correlation with our results. Furthermore, the dice coefficient, which quantifies the volumetric overlap, is higher than 62% for all structures and is close to 80% for basal ganglia. The intraclass correlation coefficient computed on these same datasets shows a good inter-method correlation of the volumetric measurements. Using a dataset of a single patient scanned 10 times on 5 different scanners, reliability is shown with a coefficient of variance of less than 2 percents over the whole dataset. Overall, these validation and reliability studies show that our method accurately and reliably segments almost all structures. Only the hippocampus and amygdala segmentations exhibit relative low correlation with the manual segmentation in at least one of the validation studies, whereas they still show appropriate dice overlap coefficients.

Structure identification within a transitioning swept-wing boundary layer

NASA Astrophysics Data System (ADS)

Chapman, Keith Lance

1997-08-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use linear stochastic estimation (LSE) and proper orthogonal decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Structure Identification Within a Transitioning Swept-Wing Boundary Layer

NASA Technical Reports Server (NTRS)

Chapman, Keith; Glauser, Mark

1996-01-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use Linear Stochastic Estimation (LSE) and Proper Orthogonal Decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Spatio-temporal filtering for determination of common mode error in regional GNSS networks

NASA Astrophysics Data System (ADS)

Bogusz, Janusz; Gruszczynski, Maciej; Figurski, Mariusz; Klos, Anna

2015-04-01

The spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually estimated with the regional spatial filtering, such as the "stacking". In this paper, we show the stacking approach for the set of ASG-EUPOS permanent stations, assuming that spatial distribution of the CME is uniform over the whole region of Poland (more than 600 km extent). The ASG-EUPOS is a multifunctional precise positioning system based on the reference network designed for Poland. We used a 5- year span time series (2008-2012) of daily solutions in the ITRF2008 from Bernese 5.0 processed by the Military University of Technology EPN Local Analysis Centre (MUT LAC). At the beginning of our analyses concerning spatial dependencies, the correlation coefficients between each pair of the stations in the GNSS network were calculated. This analysis shows that spatio-temporal behaviour of the GPS-derived time series is not purely random, but there is the evident uniform spatial response. In order to quantify the influence of filtering using CME, the norms L1 and L2 were determined. The values of these norms were calculated for the North, East and Up components twice: before performing the filtration and after stacking. The observed reduction of the L1 and L2 norms was up to 30% depending on the dimension of the network. However, the question how to define an optimal size of CME-analysed subnetwork remains unanswered in this research, due to the fact that our network is not extended enough.

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

Observation and simulation of net primary productivity in Qilian Mountain, western China.

PubMed

Zhou, Y; Zhu, Q; Chen, J M; Wang, Y Q; Liu, J; Sun, R; Tang, S

2007-11-01

We modeled net primary productivity (NPP) at high spatial resolution using an advanced spaceborne thermal emission and reflection radiometer (ASTER) image of a Qilian Mountain study area using the boreal ecosystem productivity simulator (BEPS). Two key driving variables of the model, leaf area index (LAI) and land cover type, were derived from ASTER and moderate resolution imaging spectroradiometer (MODIS) data. Other spatially explicit inputs included daily meteorological data (radiation, precipitation, temperature, humidity), available soil water holding capacity (AWC), and forest biomass. NPP was estimated for coniferous forests and other land cover types in the study area. The result showed that NPP of coniferous forests in the study area was about 4.4 tCha(-1)y(-1). The correlation coefficient between the modeled NPP and ground measurements was 0.84, with a mean relative error of about 13.9%.

Velocity-vorticity correlation structures (VVCS) in spatially developing compressible turbulent boundary layer

NASA Astrophysics Data System (ADS)

Li, Shi-Yao; She, Zhen-Su; Chen, Jun

2017-11-01

A velocity-vorticity correlation structure (VVCS) analysis is applied to the direct numerical simulation (DNS) of compressible turbulent boundary layer (CTBL) at Mach numbers, Ma = 2.25 , 4.50 and 6.0 . It is shown that the VVCS analysis captures the geometry variation in the streamwise direction during the transition and in the wall-normal direction in the fully developed regime. Specifically, before transition, the VVCS captures the instability wave number, while in the transition region it displays a distinct scaling change of the dimensions. The fully developed turbulence regime is characterized by a nearly constant spatial extension of the VVCS. Particularly, after turbulence is well developed, a multi-layer structure in the wall normal direction is observed in the maximum correlation coefficient and in the length scales of the VVCS, as expected from a recent symmetry-based theory, the ensemble structure dynamics (SED). The most interesting outcome is an observed linear dependence of the length scale of the VVCS from y+ 50 to 200, which is a direct support to Townsend's attached-eddy theory. In conclusion, the VVCS analysis quantifies the geometrical characteristics of the coherent structures in turbulent compressible shear flows throughout the whole domain. Supported by NSFC (11172006, 11221062, 11452002) and by MOST (China) 973 project (2009CB724100).

Application of 3-D Urbanization Index to Assess Impact of Urbanization on Air Temperature

NASA Astrophysics Data System (ADS)

Wu, Chih-Da; Lung, Shih-Chun Candice

2016-04-01

The lack of appropriate methodologies and indicators to quantify three-dimensional (3-D) building constructions poses challenges to authorities and urban planners when formulating polices to reduce health risks due to heat stress. This study evaluated the applicability of an innovative three-dimensional Urbanization Index (3DUI), based on remote sensing database, with a 5 m spatial resolution of 3-D man-made constructions to representing intra-urban variability of air temperature by assessing correlation of 3DUI with air temperature from a 3-D perspective. The results showed robust high correlation coefficients, ranging from 0.83 to 0.85, obtained within the 1,000 m circular buffer around weather stations regardless of season, year, or spatial location. Our findings demonstrated not only the strength of 3DUI in representing intra-urban air-temperature variability, but also its great potential for heat stress assessment within cities. In view of the maximum correlation between building volumes within the 1,000 m circular buffer and ambient air temperature, urban planning should consider setting ceilings for man-made construction volume in each 2 × 2 km2 residential community for thermal environment regulation, especially in Asian metropolis with high population density in city centers.

Concentrated Animal Feeding Operations, Row Crops and their Relationship to Nitrate in Eastern Iowa Rivers

PubMed Central

Weldon, Mark B.; Hornbuckle, Keri C.

2009-01-01

Concentrated animal feeding operations (CAFO) and fertilizer application to row crops may contribute to poor water quality in surface waters. To test this hypothesis, we evaluated nutrient concentrations and fluxes in four Eastern Iowa watersheds sampled between 1996-2004. We found that these watersheds contribute nearly 10% of annual nitrate flux entering the Gulf of Mexico, while representing only 1.5% of the contributing drainage basin. Mass budget analysis shows stream flow to be a major loss of nitrogen (18% of total N output), second only to crop harvest (63%). The major watershed inputs of nitrogen include applied fertilizer for corn (54% of total N input) and nitrogen fixation by soybeans (26%). Despite the relatively small input from animal manure (~5%), the results of spatial analysis indicate that row crop and CAFO densities are significantly and independently correlated to higher nitrate concentration in streams. Pearson correlation coefficients of 0.59 and 0.89 were found between nitrate concentration and row crop and CAFO density, respectively. Multiple linear regression analysis produced a correlation for nitrate concentration with an R2 value of 85%. High spatial density of row crops and CAFOs are linked to the highest river nitrate concentrations (up to 15 mg/l normalized over five years). PMID:16749677

Application of 3-D Urbanization Index to Assess Impact of Urbanization on Air Temperature

PubMed Central

Wu, Chih-Da; Lung, Shih-Chun Candice

2016-01-01

The lack of appropriate methodologies and indicators to quantify three-dimensional (3-D) building constructions poses challenges to authorities and urban planners when formulating polices to reduce health risks due to heat stress. This study evaluated the applicability of an innovative three-dimensional Urbanization Index (3DUI), based on remote sensing database, with a 5 m spatial resolution of 3-D man-made constructions to representing intra-urban variability of air temperature by assessing correlation of 3DUI with air temperature from a 3-D perspective. The results showed robust high correlation coefficients, ranging from 0.83 to 0.85, obtained within the 1,000 m circular buffer around weather stations regardless of season, year, or spatial location. Our findings demonstrated not only the strength of 3DUI in representing intra-urban air-temperature variability, but also its great potential for heat stress assessment within cities. In view of the maximum correlation between building volumes within the 1,000 m circular buffer and ambient air temperature, urban planning should consider setting ceilings for man-made construction volume in each 2 × 2 km2 residential community for thermal environment regulation, especially in Asian metropolis with high population density in city centers. PMID:27079537

Colour image compression by grey to colour conversion

NASA Astrophysics Data System (ADS)

Drew, Mark S.; Finlayson, Graham D.; Jindal, Abhilash

2011-03-01

Instead of de-correlating image luminance from chrominance, some use has been made of using the correlation between the luminance component of an image and its chromatic components, or the correlation between colour components, for colour image compression. In one approach, the Green colour channel was taken as a base, and the other colour channels or their DCT subbands were approximated as polynomial functions of the base inside image windows. This paper points out that we can do better if we introduce an addressing scheme into the image description such that similar colours are grouped together spatially. With a Luminance component base, we test several colour spaces and rearrangement schemes, including segmentation. and settle on a log-geometric-mean colour space. Along with PSNR versus bits-per-pixel, we found that spatially-keyed s-CIELAB colour error better identifies problem regions. Instead of segmentation, we found that rearranging on sorted chromatic components has almost equal performance and better compression. Here, we sort on each of the chromatic components and separately encode windows of each. The result consists of the original greyscale plane plus the polynomial coefficients of windows of rearranged chromatic values, which are then quantized. The simplicity of the method produces a fast and simple scheme for colour image and video compression, with excellent results.

Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere.

PubMed

Genc, D Deniz; Yesilyurt, Canan; Tuncel, Gurdal

2010-07-01

Spatial and temporal variations in concentrations of CO, NO, NO(2), SO(2), and PM(10), measured between 1999 and 2000, at traffic-impacted and residential stations in Ankara were investigated. Air quality in residential areas was found to be influenced by traffic activities in the city. Pollutant ratios were proven to be reliable tracers to differentiate between different sources. Air pollution index (API) of the whole city was calculated to evaluate the level of air quality in Ankara. Multiple linear regression model was developed for forecasting API in Ankara. The correlation coefficients were found to be 0.79 and 0.63 for different time periods. The assimilative capacity of Ankara atmosphere was calculated in terms of ventilation coefficient (VC). The relation between API and VC was investigated and found that the air quality in Ankara was determined by meteorology rather than emissions.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis

PubMed Central

2011-01-01

Background Many sub-Saharan countries are confronted with persistently high levels of infant mortality because of the impact of a range of biological and social determinants. In particular, infant mortality has increased in sub-Saharan Africa in recent decades due to the HIV/AIDS epidemic. The geographic distribution of health problems and their relationship to potential risk factors can be invaluable for cost effective intervention planning. The objective of this paper is to determine and map the spatial nature of infant mortality in South Africa at a sub district level in order to inform policy intervention. In particular, the paper identifies and maps high risk clusters of infant mortality, as well as examines the impact of a range of determinants on infant mortality. A Bayesian approach is used to quantify the spatial risk of infant mortality, as well as significant associations (given spatial correlation between neighbouring areas) between infant mortality and a range of determinants. The most attributable determinants in each sub-district are calculated based on a combination of prevalence and model risk factor coefficient estimates. This integrated small area approach can be adapted and applied in other high burden settings to assist intervention planning and targeting. Results Infant mortality remains high in South Africa with seemingly little reduction since previous estimates in the early 2000's. Results showed marked geographical differences in infant mortality risk between provinces as well as within provinces as well as significantly higher risk in specific sub-districts and provinces. A number of determinants were found to have a significant adverse influence on infant mortality at the sub-district level. Following multivariable adjustment increasing maternal mortality, antenatal HIV prevalence, previous sibling mortality and male infant gender remained significantly associated with increased infant mortality risk. Of these antenatal HIV sero-prevalence, previous sibling mortality and maternal mortality were found to be the most attributable respectively. Conclusions This study demonstrates the usefulness of advanced spatial analysis to both quantify excess infant mortality risk at the lowest administrative unit, as well as the use of Bayesian modelling to quantify determinant significance given spatial correlation. The "novel" integration of determinant prevalence at the sub-district and coefficient estimates to estimate attributable fractions further elucidates the "high impact" factors in particular areas and has considerable potential to be applied in other locations. The usefulness of the paper, therefore, not only suggests where to intervene geographically, but also what specific interventions policy makers should prioritize in order to reduce the infant mortality burden in specific administration areas. PMID:22093084

Super-resolution study of polymer mobility fluctuations near c*.

PubMed

King, John T; Yu, Changqian; Wilson, William L; Granick, Steve

2014-09-23

Nanoscale dynamic heterogeneities in synthetic polymer solutions are detected using super-resolution optical microscopy. To this end, we map concentration fluctuations in polystyrene-toluene solutions with spatial resolution below the diffraction limit, focusing on critical fluctuations near the polymer overlap concentration, c*. Two-photon super-resolution microscopy was adapted to be applicable in an organic solvent, and a home-built STED-FCS system with stimulated emission depletion (STED) was used to perform fluorescence correlation spectroscopy (FCS). The polystyrene serving as the tracer probe (670 kg mol(-1), radius of gyration RG ≈ 35 nm, end-labeled with a bodipy derivative chromophore) was dissolved in toluene at room temperature (good solvent) and mixed with matrix polystyrene (3,840 kg mol(-1), RG ≈ 97 nm, Mw/Mn = 1.04) whose concentration was varied from dilute to more than 10c*. Whereas for dilute solutions the intensity-intensity correlation function follows a single diffusion process, it splits starting at c* to imply an additional relaxation process provided that the experimental focal area does not greatly exceed the polymer blob size. We identify the slower mode as self-diffusion and the increasingly rapid mode as correlated segment fluctuations that reflect the cooperative diffusion coefficient, Dcoop. These real-space measurements find quantitative agreement between correlation lengths inferred from dynamic measurements and those from determining the limit below which diffusion coefficients are independent of spot size. This study is considered to illustrate the potential of importing into polymer science the techniques of super-resolution imaging.

The Relationship Between Surface Curvature and Abdominal Aortic Aneurysm Wall Stress.

PubMed

de Galarreta, Sergio Ruiz; Cazón, Aitor; Antón, Raúl; Finol, Ender A

2017-08-01

The maximum diameter (MD) criterion is the most important factor when predicting risk of rupture of abdominal aortic aneurysms (AAAs). An elevated wall stress has also been linked to a high risk of aneurysm rupture, yet is an uncommon clinical practice to compute AAA wall stress. The purpose of this study is to assess whether other characteristics of the AAA geometry are statistically correlated with wall stress. Using in-house segmentation and meshing algorithms, 30 patient-specific AAA models were generated for finite element analysis (FEA). These models were subsequently used to estimate wall stress and maximum diameter and to evaluate the spatial distributions of wall thickness, cross-sectional diameter, mean curvature, and Gaussian curvature. Data analysis consisted of statistical correlations of the aforementioned geometry metrics with wall stress for the 30 AAA inner and outer wall surfaces. In addition, a linear regression analysis was performed with all the AAA wall surfaces to quantify the relationship of the geometric indices with wall stress. These analyses indicated that while all the geometry metrics have statistically significant correlations with wall stress, the local mean curvature (LMC) exhibits the highest average Pearson's correlation coefficient for both inner and outer wall surfaces. The linear regression analysis revealed coefficients of determination for the outer and inner wall surfaces of 0.712 and 0.516, respectively, with LMC having the largest effect on the linear regression equation with wall stress. This work underscores the importance of evaluating AAA mean wall curvature as a potential surrogate for wall stress.

Estimation of the absorption coefficients of two-layered media by a simple method using spatially and time-resolved reflectances

NASA Astrophysics Data System (ADS)

Shimada, M.; Sato, C.; Hoshi, Y.; Yamada, Y.

2009-08-01

Our newly developed method using spatially and time-resolved reflectances can easily estimate the absorption coefficients of each layer in a two-layered medium if the thickness of the upper layer and the reduced scattering coefficients of the two layers are known a priori. We experimentally validated this method using phantoms and examined its possibility of estimating the absorption coefficients of the tissues in human heads. In the case of a homogeneous plastic phantom (polyacetal block), the absorption coefficient estimated by our method agreed well with that obtained by a conventional method. Also, in the case of two-layered phantoms, our method successfully estimated the absorption coefficients of the two layers. Furthermore, the absorption coefficients of the extracerebral and cerebral tissue inside human foreheads were estimated under the assumption that the human heads were two-layered media. It was found that the absorption coefficients of the cerebral tissues were larger than those of the extracerebral tissues.

ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

PubMed

Kim, Seongho

2015-11-01

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

A Comparative Study of the Hypoxia PET Tracers [{sup 18}F]HX4, [{sup 18}F]FAZA, and [{sup 18}F]FMISO in a Preclinical Tumor Model

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

Peeters, Sarah G.J.A., E-mail: sarah.peeters@maastrichtuniversity.nl; Zegers, Catharina M.L.; Lieuwes, Natasja G.

Purpose: Several individual clinical and preclinical studies have shown the possibility of evaluating tumor hypoxia by using noninvasive positron emission tomography (PET). The current study compared 3 hypoxia PET tracers frequently used in the clinic, [{sup 18}F]FMISO, [{sup 18}F]FAZA, and [{sup 18}F]HX4, in a preclinical tumor model. Tracer uptake was evaluated for the optimal time point for imaging, tumor-to-blood ratios (TBR), spatial reproducibility, and sensitivity to oxygen modification. Methods and Materials: PET/computed tomography (CT) images of rhabdomyosarcoma R1-bearing WAG/Rij rats were acquired at multiple time points post injection (p.i.) with one of the hypoxia tracers. TBR values were calculated, andmore » reproducibility was investigated by voxel-to-voxel analysis, represented as correlation coefficients (R) or Dice similarity coefficient of the high-uptake volume. Tumor oxygen modifications were induced by exposure to either carbogen/nicotinamide treatment or 7% oxygen breathing. Results: TBR was stabilized and maximal at 2 hours p.i. for [{sup 18}F]FAZA (4.0 ± 0.5) and at 3 hours p.i. for [{sup 18}F]HX4 (7.2 ± 0.7), whereas [{sup 18}F]FMISO showed a constant increasing TBR (9.0 ± 0.8 at 6 hours p.i.). High spatial reproducibility was observed by voxel-to-voxel comparisons and Dice similarity coefficient calculations on the 30% highest uptake volume for both [{sup 18}F]FMISO (R = 0.86; Dice coefficient = 0.76) and [{sup 18}F]HX4 (R = 0.76; Dice coefficient = 0.70), whereas [{sup 18}F]FAZA was less reproducible (R = 0.52; Dice coefficient = 0.49). Modifying the hypoxic fraction resulted in enhanced mean standardized uptake values for both [{sup 18}F]HX4 and [{sup 18}F]FAZA upon 7% oxygen breathing. Only [{sup 18}F]FMISO uptake was found to be reversible upon exposure to nicotinamide and carbogen. Conclusions: This study indicates that each tracer has its own strengths and, depending on the question to be answered, a different tracer can be put forward.« less

Influences of Exciton Diffusion and Exciton-Exciton Annihilation on Photon Emission Statistics of Carbon Nanotubes.

PubMed

Ma, Xuedan; Roslyak, Oleskiy; Duque, Juan G; Pang, Xiaoying; Doorn, Stephen K; Piryatinski, Andrei; Dunlap, David H; Htoon, Han

2015-07-03

Pump-dependent photoluminescence imaging and second-order photon correlation studies have been performed on individual single-walled carbon nanotubes (SWCNTs) at room temperature. These studies enable the extraction of both the exciton diffusion constant and the Auger recombination coefficient. A linear correlation between these parameters is attributed to the effect of environmental disorder in setting the exciton mean free path and capture-limited Auger recombination at this length scale. A suppression of photon antibunching is attributed to the creation of multiple spatially nonoverlapping excitons in SWCNTs, whose diffusion length is shorter than the laser spot size. We conclude that complete antibunching at room temperature requires an enhancement of the exciton-exciton annihilation rate that may become realizable in SWCNTs allowing for strong exciton localization.

Spatial Distribution of the Coefficient of Variation and Bayesian Forecast for the Paleo-Earthquakes in Japan

NASA Astrophysics Data System (ADS)

Nomura, Shunichi; Ogata, Yosihiko

2016-04-01

We propose a Bayesian method of probability forecasting for recurrent earthquakes of inland active faults in Japan. Renewal processes with the Brownian Passage Time (BPT) distribution are applied for over a half of active faults in Japan by the Headquarters for Earthquake Research Promotion (HERP) of Japan. Long-term forecast with the BPT distribution needs two parameters; the mean and coefficient of variation (COV) for recurrence intervals. The HERP applies a common COV parameter for all of these faults because most of them have very few specified paleoseismic events, which is not enough to estimate reliable COV values for respective faults. However, different COV estimates are proposed for the same paleoseismic catalog by some related works. It can make critical difference in forecast to apply different COV estimates and so COV should be carefully selected for individual faults. Recurrence intervals on a fault are, on the average, determined by the long-term slip rate caused by the tectonic motion but fluctuated by nearby seismicities which influence surrounding stress field. The COVs of recurrence intervals depend on such stress perturbation and so have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus we introduce a spatial structure on its COV parameter by Bayesian modeling with a Gaussian process prior. The COVs on active faults are correlated and take similar values for closely located faults. It is found that the spatial trends in the estimated COV values coincide with the density of active faults in Japan. We also show Bayesian forecasts by the proposed model using Markov chain Monte Carlo method. Our forecasts are different from HERP's forecast especially on the active faults where HERP's forecasts are very high or low.

Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.

Relationships among the slopes of lines derived from various data analysis techniques and the associated correlation coefficient

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1980-01-01

A technique for fitting a straight line to a collection of data points is given. The relationships between the slopes and correlation coefficients, and between the corresponding standard deviations and correlation coefficient are given.

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (p<0.0001), I 2 =73%, test for overall effect Z=8.67 (p<0.00001). ADC min correlated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Relationships among video gaming proficiency and spatial orientation, laparoscopic, and traditional surgical skills of third-year veterinary students.

PubMed

Millard, Heather A Towle; Millard, Ralph P; Constable, Peter D; Freeman, Lyn J

2014-02-01

To determine the relationships among traditional and laparoscopic surgical skills, spatial analysis skills, and video gaming proficiency of third-year veterinary students. Prospective, randomized, controlled study. A convenience sample of 29 third-year veterinary students. The students had completed basic surgical skills training with inanimate objects but had no experience with soft tissue, orthopedic, or laparoscopic surgery; the spatial analysis test; or the video games that were used in the study. Scores for traditional surgical, laparoscopic, spatial analysis, and video gaming skills were determined, and associations among these were analyzed by means of Spearman's rank order correlation coefficient (rs). A significant positive association (rs = 0.40) was detected between summary scores for video game performance and laparoscopic skills, but not between video game performance and traditional surgical skills scores. Spatial analysis scores were positively (rs = 0.30) associated with video game performance scores; however, that result was not significant. Spatial analysis scores were not significantly associated with laparoscopic surgical skills scores. Traditional surgical skills scores were not significantly associated with laparoscopic skills or spatial analysis scores. Results of this study indicated video game performance of third-year veterinary students was predictive of laparoscopic but not traditional surgical skills, suggesting that laparoscopic performance may be improved with video gaming experience. Additional studies would be required to identify methods for improvement of traditional surgical skills.

Correlation of human papillomavirus status with apparent diffusion coefficient of diffusion-weighted MRI in head and neck squamous cell carcinomas.

PubMed

Driessen, Juliette P; van Bemmel, Alexander J M; van Kempen, Pauline M W; Janssen, Luuk M; Terhaard, Chris H J; Pameijer, Frank A; Willems, Stefan M; Stegeman, Inge; Grolman, Wilko; Philippens, Marielle E P

2016-04-01

Identification of prognostic patient characteristics in head and neck squamous cell carcinoma (HNSCC) is of great importance. Human papillomavirus (HPV)-positive HNSCCs have favorable response to (chemo)radiotherapy. Apparent diffusion coefficient, derived from diffusion-weighted MRI, has also shown to predict treatment response. The purpose of this study was to evaluate the correlation between HPV status and apparent diffusion coefficient. Seventy-three patients with histologically proven HNSCC were retrospectively analyzed. Mean pretreatment apparent diffusion coefficient was calculated by delineation of total tumor volume on diffusion-weighted MRI. HPV status was analyzed and correlated to apparent diffusion coefficient. Six HNSCCs were HPV-positive. HPV-positive HNSCC showed significantly lower apparent diffusion coefficient compared to HPV-negative. This correlation was independent of other patient characteristics. In HNSCC, positive HPV status correlates with low mean apparent diffusion coefficient. The favorable prognostic value of low pretreatment apparent diffusion coefficient might be partially attributed to patients with a positive HPV status. © 2015 Wiley Periodicals, Inc. Head Neck 38: E613-E618, 2016. © 2015 Wiley Periodicals, Inc.

Design of an all-optical fractional-order differentiator with terahertz bandwidth based on a fiber Bragg grating in transmission.

PubMed

Liu, Xin; Shu, Xuewen

2017-08-20

All-optical fractional-order temporal differentiators with bandwidths reaching terahertz (THz) values are demonstrated with transmissive fiber Bragg gratings. Since the designed fractional-order differentiator is a minimum phase function, the reflective phase of the designed function can be chosen arbitrarily. As examples, we first design several 0.5th-order differentiators with bandwidths reaching the THz range for comparison. The reflective phases of the 0.5th-order differentiators are chosen to be linear phase, quadratic phase, cubic phase, and biquadratic phase, respectively. We find that both the maximum coupling coefficient and the spatial resolution of the designed grating increase when the reflective phase varies from quadratic function to cubic function to biquadratic function. Furthermore, when the reflective phase is chosen to be a quadratic function, the obtained grating coupling coefficient and period are more likely to be achieved in practice. Then we design fractional-order differentiators with different orders when the reflective phase is chosen to be a quadratic function. We see that when the designed order of the differentiator increases, the obtained maximum coupling coefficient also increases while the oscillation of the coupling coefficient decreases. Finally, we give the numerical performance of the designed 0.5th-order differentiator by showing its temporal response and calculating its cross-correlation coefficient.

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

PubMed Central

Someswara Rao, Chinta; Viswanadha Raju, S.

2016-01-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc. PMID:26981409

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

PubMed

Someswara Rao, Chinta; Viswanadha Raju, S

2016-03-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

Polarized 3He Spin Filters for Slow Neutron Physics

PubMed Central

Gentile, T. R.; Chen, W. C.; Jones, G. L.; Babcock, E.; Walker, T. G.

2005-01-01

Polarized 3He spin filters are needed for a variety of experiments with slow neutrons. Their demonstrated utility for highly accurate determination of neutron polarization are critical to the next generation of betadecay correlation coefficient measurements. In addition, they are broadband devices that can polarize large area and high divergence neutron beams with little gamma-ray background, and allow for an additional spin-flip for systematic tests. These attributes are relevant to all neutron sources, but are particularly well-matched to time of flight analysis at spallation sources. There are several issues in the practical use of 3He spin filters for slow neutron physics. Besides the essential goal of maximizing the 3He polarization, we also seek to decrease the constraints on cell lifetimes and magnetic field homogeneity. In addition, cells with highly uniform gas thickness are required to produce the spatially uniform neutron polarization needed for beta-decay correlation coefficient experiments. We are currently employing spin-exchange (SE) and metastability-exchange (ME) optical pumping to polarize 3He, but will focus on SE. We will discuss the recent demonstration of 75 % 3He polarization, temperature-dependent relaxation mechanism of unknown origin, cell development, spectrally narrowed lasers, and hybrid spin-exchange optical pumping. PMID:27308140

A foreground object features-based stereoscopic image visual comfort assessment model

NASA Astrophysics Data System (ADS)

Jin, Xin; Jiang, G.; Ying, H.; Yu, M.; Ding, S.; Peng, Z.; Shao, F.

2014-11-01

Since stereoscopic images provide observers with both realistic and discomfort viewing experience, it is necessary to investigate the determinants of visual discomfort. By considering that foreground object draws most attention when human observing stereoscopic images. This paper proposes a new foreground object based visual comfort assessment (VCA) metric. In the first place, a suitable segmentation method is applied to disparity map and then the foreground object is ascertained as the one having the biggest average disparity. In the second place, three visual features being average disparity, average width and spatial complexity of foreground object are computed from the perspective of visual attention. Nevertheless, object's width and complexity do not consistently influence the perception of visual comfort in comparison with disparity. In accordance with this psychological phenomenon, we divide the whole images into four categories on the basis of different disparity and width, and exert four different models to more precisely predict its visual comfort in the third place. Experimental results show that the proposed VCA metric outperformance other existing metrics and can achieve a high consistency between objective and subjective visual comfort scores. The Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are over 0.84 and 0.82, respectively.

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient.

PubMed

Yang, Tao; Zhang, Feipeng; Yardımcı, Galip Gürkan; Song, Fan; Hardison, Ross C; Noble, William Stafford; Yue, Feng; Li, Qunhua

2017-11-01

Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach. © 2017 Yang et al.; Published by Cold Spring Harbor Laboratory Press.

Wave-induced fluid flow in random porous media: Attenuation and dispersion of elastic waves

NASA Astrophysics Data System (ADS)

Müller, Tobias M.; Gurevich, Boris

2005-05-01

A detailed analysis of the relationship between elastic waves in inhomogeneous, porous media and the effect of wave-induced fluid flow is presented. Based on the results of the poroelastic first-order statistical smoothing approximation applied to Biot's equations of poroelasticity, a model for elastic wave attenuation and dispersion due to wave-induced fluid flow in 3-D randomly inhomogeneous poroelastic media is developed. Attenuation and dispersion depend on linear combinations of the spatial correlations of the fluctuating poroelastic parameters. The observed frequency dependence is typical for a relaxation phenomenon. Further, the analytic properties of attenuation and dispersion are analyzed. It is shown that the low-frequency asymptote of the attenuation coefficient of a plane compressional wave is proportional to the square of frequency. At high frequencies the attenuation coefficient becomes proportional to the square root of frequency. A comparison with the 1-D theory shows that attenuation is of the same order but slightly larger in 3-D random media. Several modeling choices of the approach including the effect of cross correlations between fluid and solid phase properties are demonstrated. The potential application of the results to real porous materials is discussed. .

Polarized (3) He Spin Filters for Slow Neutron Physics.

PubMed

Gentile, T R; Chen, W C; Jones, G L; Babcock, E; Walker, T G

2005-01-01

Polarized (3)He spin filters are needed for a variety of experiments with slow neutrons. Their demonstrated utility for highly accurate determination of neutron polarization are critical to the next generation of betadecay correlation coefficient measurements. In addition, they are broadband devices that can polarize large area and high divergence neutron beams with little gamma-ray background, and allow for an additional spin-flip for systematic tests. These attributes are relevant to all neutron sources, but are particularly well-matched to time of flight analysis at spallation sources. There are several issues in the practical use of (3)He spin filters for slow neutron physics. Besides the essential goal of maximizing the (3)He polarization, we also seek to decrease the constraints on cell lifetimes and magnetic field homogeneity. In addition, cells with highly uniform gas thickness are required to produce the spatially uniform neutron polarization needed for beta-decay correlation coefficient experiments. We are currently employing spin-exchange (SE) and metastability-exchange (ME) optical pumping to polarize (3)He, but will focus on SE. We will discuss the recent demonstration of 75 % (3)He polarization, temperature-dependent relaxation mechanism of unknown origin, cell development, spectrally narrowed lasers, and hybrid spin-exchange optical pumping.

Unraveling spurious properties of interaction networks with tailored random networks.

PubMed

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Unraveling Spurious Properties of Interaction Networks with Tailored Random Networks

PubMed Central

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis. PMID:21850239

The Role and Modeling of Dispersive Stresses

NASA Astrophysics Data System (ADS)

Shavit, U.; Moltchanov, S.

2012-12-01

Dispersive stresses represent momentum fluxes that are induced by the spatial heterogeneity of flow environments such as forest canopies, river vegetation and coral reefs. When deriving the average momentum equation for such flow environments, these dispersive stresses resemble the Reynolds stresses but instead of correlations of temporal fluctuations they represent correlations of spatial fluctuations. Surprisingly, these stresses are ignored in flow models and very few studies attempted to provide a physical interpretation, let alone a closure model. Typical arguments that justify such modeling are that these stresses are small and negligible; however, recent studies have shown that they may be important. In a recent study we showed that dispersive stresses at the inlet to obstructed region (made of glass cylinders) are larger than the Reynolds stresses and their contribution to the momentum balance is as important as the pressure and the drag forces. In this presentation we will try to explain what they are, provide some intuitive physical interoperation and show that closure models can be developed. Our results are based on highly detailed particle image velocimeter (PIV) measurements that were obtained inside a canopy model made of vertical thin glass plates. Forty nine vertical cross sections were obtained 1000 times generating a huge dataset of more than 250 million data points for each flow conditions. A careful spatial averaging procedure was developed and both temporal and spatial correlations were obtained. An order of magnitude analysis will be presented and the role of each of the terms in the momentum equation will be evaluated. It will be shown that the dispersive stresses are large and significant within the area of the canopy leading edge. Since dispersive stresses do not exist upstream from the canopy they are expected to grow once the flow enters the canopy. Our PIV data shows an initial fast growth up to about one length scale into the patch. Following this peak value the dispersive stresses decrease, reaching low and constant values further downstream. The actual distance of importance depends on the drag imposed by the canopy. The challenging task of studying dispersive stresses is the development of closure models. We will demonstrate a linear relationship between the normal dispersive stresses and the square of the double-average velocity. We will also show that the non-constant proportionality coefficient depends on the area of the wakes behind the obstacles. We will propose a simple formulation for this coefficient and will use our detailed PIV measurements to demonstrate the good agreement between the modeled and measured stresses, both at the entry region and in the fully-developed region.

Correlative measurements of the stratospheric aerosols

NASA Astrophysics Data System (ADS)

Santer, R.; Brogniez, C.; Herman, M.; Diallo, S.; Ackerman, M.

1992-12-01

Joint experiments were organized or available during stratospheric flights of a photopolarimeter, referred to as RADIBAL (radiometer balloon). In May 1984, RADIBAL flew simultaneously with another balloonborne experiment conducted by the Institut d'Aeronomie Spatiale de Belgique (IASB), which provides multiwavelength vertical profiles of the aerosol scattering coefficient. At this time, the El Chichon layer was observable quite directly from mountain sites. A ground-based station set up at Pic du Midi allowed an extensive description of the aerosol optical properties. The IASB and the Pic du Midi observations are consistent with the aerosol properties derived from the RADIBAL measurement analysis.

Improved workflow for quantification of left ventricular volumes and mass using free-breathing motion corrected cine imaging.

PubMed

Cross, Russell; Olivieri, Laura; O'Brien, Kendall; Kellman, Peter; Xue, Hui; Hansen, Michael

2016-02-25

Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which are subsequently motion corrected and reformatted to yield a single image series displaying one cardiac cycle with high temporal and spatial resolution. Application of these algorithms has required significant additional reconstruction time. The use of distributed computing was recently proposed as a way to improve clinical workflow with such algorithms. In this study, we have deployed a distributed computing version of motion corrected re-binning reconstruction for free-breathing evaluation of cardiac function. Twenty five patients and 25 volunteers underwent cardiovascular magnetic resonance (CMR) for evaluation of left ventricular end-systolic volume (ESV), end-diastolic volume (EDV), and end-diastolic mass. Measurements using motion corrected re-binning were compared to those using breath-held SSFP and to free-breathing SSFP with multiple averages, and were performed by two independent observers. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Concordance correlation coefficient and Bland-Altman analysis tested inter-observer variability. Total scan plus reconstruction times were tested for significant differences using paired t-test. Measured volumes and mass obtained by motion corrected re-binning and by averaged free-breathing SSFP compared favorably to those obtained by breath-held SSFP (r = 0.9863/0.9813 for EDV, 0.9550/0.9685 for ESV, 0.9952/0.9771 for mass). Inter-observer variability was good with concordance correlation coefficients between observers across all acquisition types suggesting substantial agreement. Both motion corrected re-binning and averaged free-breathing SSFP acquisition and reconstruction times were shorter than breath-held SSFP techniques (p < 0.0001). On average, motion corrected re-binning required 3 min less than breath-held SSFP imaging, a 37% reduction in acquisition and reconstruction time. The motion corrected re-binning image reconstruction technique provides robust cardiac imaging that can be used for quantification that compares favorably to breath-held SSFP as well as multiple average free-breathing SSFP, but can be obtained in a fraction of the time when using cloud-based distributed computing reconstruction.

Correlation coefficient measurement of the mode-locked laser tones using four-wave mixing.

PubMed

Anthur, Aravind P; Panapakkam, Vivek; Vujicic, Vidak; Merghem, Kamel; Lelarge, Francois; Ramdane, Abderrahim; Barry, Liam P

2016-06-01

We use four-wave mixing to measure the correlation coefficient of comb tones in a quantum-dash mode-locked laser under passive and active locked regimes. We study the uncertainty in the measurement of the correlation coefficient of the proposed method.

Challenge of assessing symptoms in seriously ill intensive care unit patients: can proxy reporters help?

PubMed

Puntillo, Kathleen A; Neuhaus, John; Arai, Shoshana; Paul, Steven M; Gropper, Michael A; Cohen, Neal H; Miaskowski, Christine

2012-10-01

Determine levels of agreement among intensive care unit patients and their family members, nurses, and physicians (proxies) regarding patients' symptoms and compare levels of mean intensity (i.e., the magnitude of a symptom sensation) and distress (i.e., the degree of emotionality that a symptom engenders) of symptoms among patients and proxy reporters. Prospective study of proxy reporters of symptoms in seriously ill patients. Two intensive care units in a tertiary medical center in the Western United States. Two hundred and forty-five intensive care unit patients, 243 family members, 103 nurses, and 92 physicians. None. On the basis of the magnitude of intraclass correlation coefficients, where coefficients from .35 to .78 are considered to be appropriately robust, correlation coefficients between patients' and family members' ratings met this criterion (≥.35) for intensity in six of ten symptoms. No intensity ratings between patients and nurses had intraclass correlation coefficients >.32. Three symptoms had intensity correlation coefficients of ≥.36 between patients' and physicians' ratings. Correlation coefficients between patients and family members were >.40 for five symptom-distress ratings. No symptoms had distress correlation coefficients of ≥.28 between patients' and nurses' ratings. Two symptoms had symptom-distress correlation coefficients between patients' and physicians' ratings at >.39. Family members, nurses, and physicians reported higher symptom-intensity scores than patients did for 80%, 60%, and 60% of the symptoms, respectively. Family members, nurses, and physicians reported higher symptom-distress scores than patients did for 90%, 70%, and 80% of the symptoms, respectively. Patient-family intraclass correlation coefficients were sufficiently close for us to consider using family members to help assess intensive care unit patients' symptoms. Relatively low intraclass correlation coefficients between intensive care unit clinicians' and patients' symptom ratings indicate that some proxy raters overestimate whereas others underestimate patients' symptoms. Proxy overestimation of patients' symptom scores warrants further study because this may influence decisions about treating patients' symptoms.

Rotational biomechanics of the elite golf swing: benchmarks for amateurs.

PubMed

Meister, David W; Ladd, Amy L; Butler, Erin E; Zhao, Betty; Rogers, Andrew P; Ray, Conrad J; Rose, Jessica

2011-08-01

The purpose of this study was to determine biomechanical factors that may influence golf swing power generation. Three-dimensional kinematics and kinetics were examined in 10 professional and 5 amateur male golfers. Upper-torso rotation, pelvic rotation, X-factor (relative hip-shoulder rotation), O-factor (pelvic obliquity), S-factor (shoulder obliquity), and normalized free moment were assessed in relation to clubhead speed at impact (CSI). Among professional golfers, results revealed that peak free moment per kilogram, peak X-factor, and peak S-factor were highly consistent, with coefficients of variation of 6.8%, 7.4%, and 8.4%, respectively. Downswing was initiated by reversal of pelvic rotation, followed by reversal of upper-torso rotation. Peak X-factor preceded peak free moment in all swings for all golfers, and occurred during initial downswing. Peak free moment per kilogram, X-factor at impact, peak X-factor, and peak upper-torso rotation were highly correlated to CSI (median correlation coefficients of 0.943, 0.943, 0.900, and 0.900, respectively). Benchmark curves revealed kinematic and kinetic temporal and spatial differences of amateurs compared with professional golfers. For amateurs, the number of factors that fell outside 1-2 standard deviations of professional means increased with handicap. This study identified biomechanical factors highly correlated to golf swing power generation and may provide a basis for strategic training and injury prevention.

Medium-range Performance of the Global NWP Model

NASA Astrophysics Data System (ADS)

Kim, J.; Jang, T.; Kim, J.; Kim, Y.

2017-12-01

The medium-range performance of the global numerical weather prediction (NWP) model in the Korea Meteorological Administration (KMA) is investigated. The performance is based on the prediction of the extratropical circulation. The mean square error is expressed by sum of spatial variance of discrepancy between forecasts and observations and the square of the mean error (ME). Thus, it is important to investigate the ME effect in order to understand the model performance. The ME is expressed by the subtraction of an anomaly from forecast difference against the real climatology. It is found that the global model suffers from a severe systematic ME in medium-range forecasts. The systematic ME is dominant in the entire troposphere in all months. Such ME can explain at most 25% of root mean square error. We also compare the extratropical ME distribution with that from other NWP centers. NWP models exhibit similar spatial ME structure each other. It is found that the spatial ME pattern is highly correlated to that of an anomaly, implying that the ME varies with seasons. For example, the correlation coefficient between ME and anomaly ranges from -0.51 to -0.85 by months. The pattern of the extratropical circulation also has a high correlation to an anomaly. The global model has trouble in faithfully simulating extratropical cyclones and blockings in the medium-range forecast. In particular, the model has a hard to simulate an anomalous event in medium-range forecasts. If we choose an anomalous period for a test-bed experiment, we will suffer from a large error due to an anomaly.

Energy-angle correlation correction algorithm for monochromatic computed tomography based on Thomson scattering X-ray source

NASA Astrophysics Data System (ADS)

Chi, Zhijun; Du, Yingchao; Huang, Wenhui; Tang, Chuanxiang

2017-12-01

The necessity for compact and relatively low cost x-ray sources with monochromaticity, continuous tunability of x-ray energy, high spatial coherence, straightforward polarization control, and high brightness has led to the rapid development of Thomson scattering x-ray sources. To meet the requirement of in-situ monochromatic computed tomography (CT) for large-scale and/or high-attenuation materials based on this type of x-ray source, there is an increasing demand for effective algorithms to correct the energy-angle correlation. In this paper, we take advantage of the parametrization of the x-ray attenuation coefficient to resolve this problem. The linear attenuation coefficient of a material can be decomposed into a linear combination of the energy-dependent photoelectric and Compton cross-sections in the keV energy regime without K-edge discontinuities, and the line integrals of the decomposition coefficients of the above two parts can be determined by performing two spectrally different measurements. After that, the line integral of the linear attenuation coefficient of an imaging object at a certain interested energy can be derived through the above parametrization formula, and monochromatic CT can be reconstructed at this energy using traditional reconstruction methods, e.g., filtered back projection or algebraic reconstruction technique. Not only can monochromatic CT be realized, but also the distributions of the effective atomic number and electron density of the imaging object can be retrieved at the expense of dual-energy CT scan. Simulation results validate our proposal and will be shown in this paper. Our results will further expand the scope of application for Thomson scattering x-ray sources.

Empirical correlations for axial dispersion coefficient and Peclet number in fixed-bed columns.

PubMed

Rastegar, Seyed Omid; Gu, Tingyue

2017-03-24

In this work, a new correlation for the axial dispersion coefficient was obtained using experimental data in the literature for axial dispersion in fixed-bed columns packed with particles. The Chung and Wen correlation, the De Ligny correlation are two popular empirical correlations. However, the former lacks the molecular diffusion term and the latter does not consider bed voidage. The new axial dispersion coefficient correlation in this work was based on additional experimental data in the literature by considering both molecular diffusion and bed voidage. It is more comprehensive and accurate. The Peclet number correlation from the new axial dispersion coefficient correlation on the average leads to 12% lower Peclet number values compared to the values from the Chung and Wen correlation, and in many cases much smaller than those from the De Ligny correlation. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial Interpolation of Aerosol Optical Depth Pollution: Comparison of Methods for the Development of Aerosol Distribution

NASA Astrophysics Data System (ADS)

Safarpour, S.; Abdullah, K.; Lim, H. S.; Dadras, M.

2017-09-01

Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters are important due to health impact. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. Seasonal aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellites, for the 10 years period of 2000 - 2010 were used to test 7 different spatial interpolation methods in the present study. The accuracy of estimations was assessed through visual analysis as well as independent validation based on basic statistics, such as root mean square error (RMSE) and correlation coefficient. Based on the RMSE and R values of predictions made using measured values from 2000 to 2010, Radial Basis Functions (RBFs) yielded the best results for spring, summer and winter and ordinary kriging yielded the best results for fall.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Can DCE-MRI Explain the Heterogeneity in Radiopeptide Uptake Imaged by SPECT in a Pancreatic Neuroendocrine Tumor Model?

PubMed Central

Groen, Harald C.; Niessen, Wiro J.; Bernsen, Monique R.; de Jong, Marion; Veenland, Jifke F.

2013-01-01

Although efficient delivery and distribution of treatment agents over the whole tumor is essential for successful tumor treatment, the distribution of most of these agents cannot be visualized. However, with single-photon emission computed tomography (SPECT), both delivery and uptake of radiolabeled peptides can be visualized in a neuroendocrine tumor model overexpressing somatostatin receptors. A heterogeneous peptide uptake is often observed in these tumors. We hypothesized that peptide distribution in the tumor is spatially related to tumor perfusion, vessel density and permeability, as imaged and quantified by DCE-MRI in a neuroendocrine tumor model. Four subcutaneous CA20948 tumor-bearing Lewis rats were injected with the somatostatin-analog 111In-DTPA-Octreotide (50 MBq). SPECT-CT and MRI scans were acquired and MRI was spatially registered to SPECT-CT. DCE-MRI was analyzed using semi-quantitative and quantitative methods. Correlation between SPECT and DCE-MRI was investigated with 1) Spearman’s rank correlation coefficient; 2) SPECT uptake values grouped into deciles with corresponding median DCE-MRI parametric values and vice versa; and 3) linear regression analysis for median parameter values in combined datasets. In all tumors, areas with low peptide uptake correlated with low perfusion/density/ /permeability for all DCE-MRI-derived parameters. Combining all datasets, highest linear regression was found between peptide uptake and semi-quantitative parameters (R2>0.7). The average correlation coefficient between SPECT and DCE-MRI-derived parameters ranged from 0.52-0.56 (p<0.05) for parameters primarily associated with exchange between blood and extracellular extravascular space. For these parameters a linear relation with peptide uptake was observed. In conclusion, the ‘exchange-related’ DCE-MRI-derived parameters seemed to predict peptide uptake better than the ‘contrast amount- related’ parameters. Consequently, fast and efficient diffusion through the vessel wall into tissue is an important factor for peptide delivery. DCE-MRI helps to elucidate the relation between vascular characteristics, peptide delivery and treatment efficacy, and may form a basis to predict targeting efficiency. PMID:24116203

The Bayesian group lasso for confounded spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Fine-Scale Mapping by Spatial Risk Distribution Modeling for Regional Malaria Endemicity and Its Implications under the Low-to-Moderate Transmission Setting in Western Cambodia

PubMed Central

Okami, Suguru; Kohtake, Naohiko

2016-01-01

The disease burden of malaria has decreased as malaria elimination efforts progress. The mapping approach that uses spatial risk distribution modeling needs some adjustment and reinvestigation in accordance with situational changes. Here we applied a mathematical modeling approach for standardized morbidity ratio (SMR) calculated by annual parasite incidence using routinely aggregated surveillance reports, environmental data such as remote sensing data, and non-environmental anthropogenic data to create fine-scale spatial risk distribution maps of western Cambodia. Furthermore, we incorporated a combination of containment status indicators into the model to demonstrate spatial heterogeneities of the relationship between containment status and risks. The explanatory model was fitted to estimate the SMR of each area (adjusted Pearson correlation coefficient R2 = 0.774; Akaike information criterion AIC = 149.423). A Bayesian modeling framework was applied to estimate the uncertainty of the model and cross-scale predictions. Fine-scale maps were created by the spatial interpolation of estimated SMRs at each village. Compared with geocoded case data, corresponding predicted values showed conformity [Spearman’s rank correlation r = 0.662 in the inverse distance weighed interpolation and 0.645 in ordinal kriging (95% confidence intervals of 0.414–0.827 and 0.368–0.813, respectively), Welch’s t-test; Not significant]. The proposed approach successfully explained regional malaria risks and fine-scale risk maps were created under low-to-moderate malaria transmission settings where reinvestigations of existing risk modeling approaches were needed. Moreover, different representations of simulated outcomes of containment status indicators for respective areas provided useful insights for tailored interventional planning, considering regional malaria endemicity. PMID:27415623

Autoregressive spatially varying coefficients model for predicting daily PM2.5 using VIIRS satellite AOT

NASA Astrophysics Data System (ADS)

Schliep, E. M.; Gelfand, A. E.; Holland, D. M.

2015-12-01

There is considerable demand for accurate air quality information in human health analyses. The sparsity of ground monitoring stations across the United States motivates the need for advanced statistical models to predict air quality metrics, such as PM2.5, at unobserved sites. Remote sensing technologies have the potential to expand our knowledge of PM2.5 spatial patterns beyond what we can predict from current PM2.5 monitoring networks. Data from satellites have an additional advantage in not requiring extensive emission inventories necessary for most atmospheric models that have been used in earlier data fusion models for air pollution. Statistical models combining monitoring station data with satellite-obtained aerosol optical thickness (AOT), also referred to as aerosol optical depth (AOD), have been proposed in the literature with varying levels of success in predicting PM2.5. The benefit of using AOT is that satellites provide complete gridded spatial coverage. However, the challenges involved with using it in fusion models are (1) the correlation between the two data sources varies both in time and in space, (2) the data sources are temporally and spatially misaligned, and (3) there is extensive missingness in the monitoring data and also in the satellite data due to cloud cover. We propose a hierarchical autoregressive spatially varying coefficients model to jointly model the two data sources, which addresses the foregoing challenges. Additionally, we offer formal model comparison for competing models in terms of model fit and out of sample prediction of PM2.5. The models are applied to daily observations of PM2.5 and AOT in the summer months of 2013 across the conterminous United States. Most notably, during this time period, we find small in-sample improvement incorporating AOT into our autoregressive model but little out-of-sample predictive improvement.

Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

NASA Astrophysics Data System (ADS)

Fernandes, A.; Riffler, M.; Ferreira, J.; Wunderle, S.; Borrego, C.; Tchepel, O.

2015-04-01

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.

Spatial correspondence of 4D CT ventilation and SPECT pulmonary perfusion defects in patients with malignant airway stenosis

NASA Astrophysics Data System (ADS)

Castillo, Richard; Castillo, Edward; McCurdy, Matthew; Gomez, Daniel R.; Block, Alec M.; Bergsma, Derek; Joy, Sarah; Guerrero, Thomas

2012-04-01

To determine the spatial overlap agreement between four-dimensional computed tomography (4D CT) ventilation and single photon emission computed tomography (SPECT) perfusion hypo-functioning pulmonary defect regions in a patient population with malignant airway stenosis. Treatment planning 4D CT images were obtained retrospectively for ten lung cancer patients with radiographically demonstrated airway obstruction due to gross tumor volume. Each patient also received a SPECT perfusion study within one week of the planning 4D CT, and prior to the initiation of treatment. Deformable image registration was used to map corresponding lung tissue elements between the extreme component phase images, from which quantitative three-dimensional (3D) images representing the local pulmonary specific ventilation were constructed. Semi-automated segmentation of the percentile perfusion distribution was performed to identify regional defects distal to the known obstructing lesion. Semi-automated segmentation was similarly performed by multiple observers to delineate corresponding defect regions depicted on 4D CT ventilation. Normalized Dice similarity coefficient (NDSC) indices were determined for each observer between SPECT perfusion and 4D CT ventilation defect regions to assess spatial overlap agreement. Tidal volumes determined from 4D CT ventilation were evaluated versus measurements obtained from lung parenchyma segmentation. Linear regression resulted in a linear fit with slope = 1.01 (R2 = 0.99). Respective values for the average DSC, NDSC1 mm and NDSC2 mm for all cases and multiple observers were 0.78, 0.88 and 0.99, indicating that, on average, spatial overlap agreement between ventilation and perfusion defect regions was comparable to the threshold for agreement within 1-2 mm uncertainty. Corresponding coefficients of variation for all metrics were similarly in the range: 0.10%-19%. This study is the first to quantitatively assess 3D spatial overlap agreement between clinically acquired SPECT perfusion and specific ventilation from 4D CT. Results suggest high correlation between methods within the sub-population of lung cancer patients with malignant airway stenosis.

a Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

NASA Astrophysics Data System (ADS)

Niazi, S.; Mokhtarzade, M.; Saeedzadeh, F.

2015-12-01

Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial distortions in the resulting fused image. The amount of these distortions varies highly depending on the pan sharpening technique as well as the type of data. Among the existing pan sharpening methods, the Intensity-Hue-Saturation (IHS) technique is the most widely used for its efficiency and high spatial resolution. When the IHS method is used for IKONOS or QuickBird imagery, there is a significant color distortion which is mainly due to the wavelengths range of the panchromatic image. Regarding the fact that in the green vegetated regions panchromatic gray values are much larger than the gray values of intensity image. A novel method is proposed which spatially adjusts the intensity image in vegetated areas. To do so the normalized difference vegetation index (NDVI) is used to identify vegetation areas where the green band is enhanced according to the red and NIR bands. In this way an intensity image is obtained in which the gray values are comparable to the panchromatic image. Beside the genetic optimization algorithm is used to find the optimum weight parameters in order to gain the best intensity image. Visual and statistical analysis proved the efficiency of the proposed method as it significantly improved the fusion quality in comparison to conventional IHS technique. The accuracy of the proposed pan sharpening technique was also evaluated in terms of different spatial and spectral metrics. In this study, 7 metrics (Correlation Coefficient, ERGAS, RASE, RMSE, SAM, SID and Spatial Coefficient) have been used in order to determine the quality of the pan-sharpened images. Experiments were conducted on two different data sets obtained by two different imaging sensors, IKONOS and QuickBird. The result of this showed that the evaluation metrics are more promising for our fused image in comparison to other pan sharpening methods.

Correlations of daily flows at streamgages in and near West Virginia, 1930-2011, and streamflow characteristics relevant to the use of index streamgages

USGS Publications Warehouse

Messinger, Terence; Paybins, Katherine S.

2014-01-01

Correlation of flows at pairs of streamgages were evaluated using a Spearman’s rho correlation coefficient to better identify gages that can be used as index gages to estimate daily flow at ungaged stream sites in West Virginia. Much of West Virginia (77 percent) is within areas where Spearman’s rho for daily streamflow between streamgages on unregulated streams (unregulated streamgages) is greater than 0.9; most withdrawals from ungaged streams for shale gas well hydraulic fracturing are being made in these areas. Most of West Virginia (>99 percent) is within zones where Spearman’s rho between streamgages on unregulated streams is greater than 0.85. Withdrawals for hydraulic fracturing are made from ungaged streams in areas where Spearman’s rho between streamgages on unregulated streams is less than 0.9, but because spatial correlation is partly a function of the density of the streamgaging network, adding or reactivating several streamgages would be likely to result in correlations of 0.90 or higher in these areas. Seasonal differences in the strength and spatial extent of correlations of daily streamflows are great. The strongest correlations among streamgages are for fall, followed by spring, then winter. One possible explanation for the weak correlations for summer may be that precipitation and runoff associated with convective storms affect one basin and miss nearby basins. A comparison of correlation patterns during previously identified climatic periods shows that the strongest correlations occurred during 1963–69, a period of drought, and the weakest during 1970–79, a wet period. The apparent effect of frequent rain during 1970–79 overshadowed streamgage-network density, which was at its historic maximum in West Virginia at that time, so that the extent of areas with high correlation to at least one streamgage was smaller during 1970–79 than during 1963–69. Correlations for 1992 to 2011 were slightly weaker than those for 1963 to 1969. The relation between correlation and distance between basin centroids was determined to be stronger for streamgage pairs in the Ohio River Basin than for pairs in the Atlantic Slope River Basins, which in turn was stronger than the relation between pairs of streamgages split between the two major basins. Quantile regression equations were developed for these three comparisons to estimate the Spearman’s rho correlation coefficient for streamgage pairs using distance between basin centroids as a predictor variable. The equations can be used for streamgage network planning. For the Ohio River Basin, the distance between basin centroids at which 50 percent of streamgage pairs would exceed a Spearman’s rho of 0.95 is 9 miles. The distance between basin centroids at which 50 percent of streamgage pairs would exceed a Spearman’s rho of 0.90 is 25 miles, and the distance at which 50 percent of streamgage pairs would exceed a Spearman’s rho of 0.85 is 48 miles. For the Atlantic Slope River Basins, the distance between basin centroids at which 50 percent of streamgage pairs would exceed a Spearman’s rho of 0.95 is 1 mile. The distance between basin centroids at which 50 percent of streamgage pairs would exceed a Spearman’s rho of 0.90 is 13 miles, and the distance at which 50 percent of streamgage pairs would exceed a Spearman’s rho of 0.85 is 41 miles. For pairs of streamgages split between the two major basins, the regression equation gives a value of 0.84 for the correlation coefficient at zero miles. On maps of correlations, the shape of strongly correlated areas for streamgages in the Ohio River Basin is generally round. In the Valley and Ridge Physiographic Province, which generally coincides with the Atlantic Slope River Basins within the study area, areas strongly correlated with streamgages generally coincide with major valleys.

Flux measurements in the surface Marine Atmospheric Boundary Layer over the Aegean Sea, Greece.

PubMed

Kostopoulos, V E; Helmis, C G

2014-10-01

Micro-meteorological measurements within the surface Marine Atmospheric Boundary Layer took place at the shoreline of two islands at northern and south-eastern Aegean Sea of Greece. The primary goal of these experimental campaigns was to study the momentum, heat and humidity fluxes over this part of the north-eastern Mediterranean Sea, characterized by limited spatial and temporal scales which could affect these exchanges at the air-sea interface. The great majority of the obtained records from both sites gave higher values up to factor of two, compared with the estimations from the most widely used parametric formulas that came mostly from measurements over open seas and oceans. Friction velocity values from both campaigns varied within the same range and presented strong correlation with the wind speed at 10 m height while the calculated drag coefficient values at the same height for both sites were found to be constant in relation with the wind speed. Using eddy correlation analysis, the heat flux values were calculated (virtual heat fluxes varied from -60 to 40 W/m(2)) and it was found that they are affected by the limited spatial and temporal scales of the responding air-sea interaction mechanism. Similarly, the humidity fluxes appeared to be strongly influenced by the observed intense spatial heterogeneity of the sea surface temperature. Copyright © 2014 Elsevier B.V. All rights reserved.

Small-scale variation in ecosystem CO2 fluxes in an alpine meadow depends on plant biomass and species richness.

PubMed

Hirota, Mitsuru; Zhang, Pengcheng; Gu, Song; Shen, Haihua; Kuriyama, Takeo; Li, Yingnian; Tang, Yanhong

2010-07-01

Characterizing the spatial variation in the CO2 flux at both large and small scales is essential for precise estimation of an ecosystem's CO2 sink strength. However, little is known about small-scale CO2 flux variations in an ecosystem. We explored these variations in a Kobresia meadow ecosystem on the Qinghai-Tibetan plateau in relation to spatial variability in species composition and biomass. We established 14 points and measured net ecosystem production (NEP), gross primary production (GPP), and ecosystem respiration (Re) in relation to vegetation biomass, species richness, and environmental variables at each point, using an automated chamber system during the 2005 growing season. Mean light-saturated NEP and GPP were 30.3 and 40.5 micromol CO2 m(-2) s(-1) [coefficient of variation (CV), 42.7 and 29.4], respectively. Mean Re at 20 degrees C soil temperature, Re(20), was -10.9 micromol CO2 m(-2) s(-1) (CV, 27.3). Re(20) was positively correlated with vegetation biomass. GPP(max) was positively correlated with species richness, but 2 of the 14 points were outliers. Vegetation biomass was the main determinant of spatial variation of Re, whereas species richness mainly affected that of GPP, probably reflecting the complexity of canopy structure and light partitioning in this small grassland patch.

Soil respiration across a permafrost transition zone: spatial structure and environmental correlates

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

Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben

Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but onlymore » in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Finally, combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.« less

Soil respiration across a permafrost transition zone: spatial structure and environmental correlates

DOE PAGES

Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben; ...

2017-09-28

Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but onlymore » in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Finally, combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.« less

Soil respiration across a permafrost transition zone: spatial structure and environmental correlates

NASA Astrophysics Data System (ADS)

Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben; Crump, Alex R.; Chen, Xingyuan; Hess, Nancy

2017-09-01

Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but only in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Combining such an approach with broader knowledge of thresholding behavior - here related to active layer depth - would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

Ackerman, Matthew S.; Johri, Parul; Spitze, Ken; Xu, Sen; Doak, Thomas G.; Young, Kimberly; Lynch, Michael

2017-01-01

Population structure can be described by genotypic-correlation coefficients between groups of individuals, the most basic of which are the pairwise relatedness coefficients between any two individuals. There are nine pairwise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates all seven reduced coefficients from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone mates. Statistically significant negative estimates of these pairwise relatedness coefficients, including inbreeding coefficients that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent. PMID:28341647

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.

Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

PubMed

Chen, Shi; Ilany, Amiyaal; White, Brad J; Sanderson, Michael W; Lanzas, Cristina

2015-01-01

Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.

Yield variability prediction by remote sensing sensors with different spatial resolution

NASA Astrophysics Data System (ADS)

Kumhálová, Jitka; Matějková, Štěpánka

2017-04-01

Currently, remote sensing sensors are very popular for crop monitoring and yield prediction. This paper describes how satellite images with moderate (Landsat satellite data) and very high (QuickBird and WorldView-2 satellite data) spatial resolution, together with GreenSeeker hand held crop sensor, can be used to estimate yield and crop growth variability. Winter barley (2007 and 2015) and winter wheat (2009 and 2011) were chosen because of cloud-free data availability in the same time period for experimental field from Landsat satellite images and QuickBird or WorldView-2 images. Very high spatial resolution images were resampled to worse spatial resolution. Normalised difference vegetation index was derived from each satellite image data sets and it was also measured with GreenSeeker handheld crop sensor for the year 2015 only. Results showed that each satellite image data set can be used for yield and plant variability estimation. Nevertheless, better results, in comparison with crop yield, were obtained for images acquired in later phenological phases, e.g. in 2007 - BBCH 59 - average correlation coefficient 0.856, and in 2011 - BBCH 59-0.784. GreenSeeker handheld crop sensor was not suitable for yield estimation due to different measuring method.

Soliton tunneling in the nonlinear Schrödinger equation with variable coefficients and an external harmonic potential.

PubMed

Zhong, Wei-Ping; Belić, Milivoj R

2010-05-01

We report on the nonlinear tunneling effects of spatial solitons of the generalized nonlinear Schrödinger equation with distributed coefficients in an external harmonic potential. By using the homogeneous balance principle and the F-expansion technique we find the spatial bright and dark soliton solutions. We then display tunneling effects of such solutions occurring under special conditions; specifically when the spatial solitons pass unchanged through the potential barriers and wells affected by special choices of the diffraction and/or the nonlinearity coefficients. Our results show that the solitons display tunneling effects not only when passing through the nonlinear potential barriers or wells but also when passing through the diffractive barriers or wells. During tunneling the solitons may also undergo a controllable compression.

Relatedness in spatially structured populations with empty sites: An approach based on spatial moment equations.

PubMed

Lion, Sébastien

2009-09-07

Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.

Relevant magnetic and soil parameters as potential indicators of soil conservation status of Mediterranean agroecosystems

NASA Astrophysics Data System (ADS)

Quijano, Laura; Chaparro, Marcos A. E.; Marié, Débora C.; Gaspar, Leticia; Navas, Ana

2014-09-01

The main sources of magnetic minerals in soils unaffected by anthropogenic pollution are iron oxides and hydroxides derived from parent materials through soil formation processes. Soil magnetic minerals can be used as indicators of environmental factors including soil forming processes, degree of pedogenesis, weathering processes and biological activities. In this study measurements of magnetic susceptibility are used to detect the presence and the concentration of soil magnetic minerals in topsoil and bulk samples in a small cultivated field, which forms a hydrological unit that can be considered to be representative of the rainfed agroecosystems of Mediterranean mountain environments. Additional magnetic studies such as isothermal remanent magnetization (IRM), anhysteretic remanent magnetization (ARM) and thermomagnetic measurements are used to identify and characterize the magnetic mineralogy of soil minerals. The objectives were to analyse the spatial variability of the magnetic parameters to assess whether topographic factors, soil redistribution processes, and soil properties such as soil texture, organic matter and carbonate contents analysed in this study, are related to the spatial distribution pattern of magnetic properties. The medians of mass specific magnetic susceptibility at low frequency (χlf) were 36.0 and 31.1 × 10-8 m3 kg-1 in bulk and topsoil samples respectively. High correlation coefficients were found between the χlf in topsoil and bulk core samples (r = 0.951, p < 0.01). In addition, volumetric magnetic susceptibility was measured in situ in the field (κis) and values varied from 13.3 to 64.0 × 10-5 SI. High correlation coefficients were found between χlf in topsoil measured in the laboratory and volumetric magnetic susceptibility field measurements (r = 0.894, p < 0.01). The results obtained from magnetic studies such as IRM, ARM and thermomagnetic measurements show the presence of magnetite, which is the predominant magnetic carrier, and hematite. The predominance of superparamagnetic minerals in upper soil layers suggests enrichment in pedogenic minerals. The finer soil particles, the organic matter content and the magnetic susceptibility values are statistically correlated and their spatial variability is related to similar physical processes. Runoff redistributes soil components including magnetic minerals and exports fine particles out the field. This research contributed to further knowledge on the application of soil magnetic properties to derive useful information on soil processes in Mediterranean cultivated soils.

A Wavelet-Based Algorithm for the Spatial Analysis of Poisson Data

NASA Astrophysics Data System (ADS)

Freeman, P. E.; Kashyap, V.; Rosner, R.; Lamb, D. Q.

2002-01-01

Wavelets are scalable, oscillatory functions that deviate from zero only within a limited spatial regime and have average value zero, and thus may be used to simultaneously characterize the shape, location, and strength of astronomical sources. But in addition to their use as source characterizers, wavelet functions are rapidly gaining currency within the source detection field. Wavelet-based source detection involves the correlation of scaled wavelet functions with binned, two-dimensional image data. If the chosen wavelet function exhibits the property of vanishing moments, significantly nonzero correlation coefficients will be observed only where there are high-order variations in the data; e.g., they will be observed in the vicinity of sources. Source pixels are identified by comparing each correlation coefficient with its probability sampling distribution, which is a function of the (estimated or a priori known) background amplitude. In this paper, we describe the mission-independent, wavelet-based source detection algorithm ``WAVDETECT,'' part of the freely available Chandra Interactive Analysis of Observations (CIAO) software package. Our algorithm uses the Marr, or ``Mexican Hat'' wavelet function, but may be adapted for use with other wavelet functions. Aspects of our algorithm include: (1) the computation of local, exposure-corrected normalized (i.e., flat-fielded) background maps; (2) the correction for exposure variations within the field of view (due to, e.g., telescope support ribs or the edge of the field); (3) its applicability within the low-counts regime, as it does not require a minimum number of background counts per pixel for the accurate computation of source detection thresholds; (4) the generation of a source list in a manner that does not depend upon a detailed knowledge of the point spread function (PSF) shape; and (5) error analysis. These features make our algorithm considerably more general than previous methods developed for the analysis of X-ray image data, especially in the low count regime. We demonstrate the robustness of WAVDETECT by applying it to an image from an idealized detector with a spatially invariant Gaussian PSF and an exposure map similar to that of the Einstein IPC; to Pleiades Cluster data collected by the ROSAT PSPC; and to simulated Chandra ACIS-I image of the Lockman Hole region.

Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Observations

PubMed Central

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. PMID:24691358

Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.

PubMed

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.

Significance tests for functional data with complex dependence structure.

PubMed

Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J

2015-01-01

We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.

Runoff Response at Three Spatial Scale from a Burned Watershed

NASA Astrophysics Data System (ADS)

Moody, J. A.; Kinner, D. A.

2007-12-01

The hypothesis that the magnitude and timing of runoff from burned watersheds are functions of the properties of flow paths at multiple scales was investigated at three nested spatial scales within an area burned by the 2005 Harvard Fire near Burbank, California. Water depths were measured using pressure sensors: at the outlet of a subwatershed (10000 m2); in 3-inch Parshall flumes near the outlets of three mini-watersheds (820-1780 m2) within the subwatershed; and by 12 overland-flow detectors in 6 micro-watersheds (~11-15 m2) within one of the mini-watersheds. Rainfall intensities were measured using recording raingages deployed around the perimeter of the mini-watersheds and at the subwatershed outlet. Time-to-concentration, TC, and lag time, TL, were computed for the 15 largest of 30 rainstorms (maximum 30- minute intensities were 3.3-13.0 mm/h) between December 2005 and April 2006. TC , elapsed time from the beginning of the rain until the first increase in water depth, averaged 1.0 hours at the micro-scale, 1.7 hours at the mini-scale, and 1.5 hours at the subwatershed scale. TL is the lag time that produced the maximum cross- correlation coefficient between the time series of rainfall intensities and the series of water depths. TL averaged 0.15 hours at the micro-scale, 0.35 hours at the mini-scale, and 0.39 hours at the subwatershed scale. The coefficient was >0.50 for 43% (N=168) of the measurements at the micro-scale, for 61% (N=54) at the mini- scale, and for 67% (N=6) at the subwatershed scale indicating the runoff response lagged but was often well correlated with the time-varying rainfall intensity.

Statistical dynamo theory: Mode excitation.

PubMed

Hoyng, P

2009-04-01

We compute statistical properties of the lowest-order multipole coefficients of the magnetic field generated by a dynamo of arbitrary shape. To this end we expand the field in a complete biorthogonal set of base functions, viz. B= summation operator_{k}a;{k}(t)b;{k}(r) . The properties of these biorthogonal function sets are treated in detail. We consider a linear problem and the statistical properties of the fluid flow are supposed to be given. The turbulent convection may have an arbitrary distribution of spatial scales. The time evolution of the expansion coefficients a;{k} is governed by a stochastic differential equation from which we infer their averages a;{k} , autocorrelation functions a;{k}(t)a;{k *}(t+tau) , and an equation for the cross correlations a;{k}a;{l *} . The eigenfunctions of the dynamo equation (with eigenvalues lambda_{k} ) turn out to be a preferred set in terms of which our results assume their simplest form. The magnetic field of the dynamo is shown to consist of transiently excited eigenmodes whose frequency and coherence time is given by Ilambda_{k} and -1/Rlambda_{k} , respectively. The relative rms excitation level of the eigenmodes, and hence the distribution of magnetic energy over spatial scales, is determined by linear theory. An expression is derived for |a;{k}|;{2}/|a;{0}|;{2} in case the fundamental mode b;{0} has a dominant amplitude, and we outline how this expression may be evaluated. It is estimated that |a;{k}|;{2}/|a;{0}|;{2} approximately 1/N , where N is the number of convective cells in the dynamo. We show that the old problem of a short correlation time (or first-order smoothing approximation) has been partially eliminated. Finally we prove that for a simple statistically steady dynamo with finite resistivity all eigenvalues obey Rlambda_{k}<0 .

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.

Statistical Study of Turbulence: Spectral Functions and Correlation Coefficients

NASA Technical Reports Server (NTRS)

Frenkiel, Francois N.

1958-01-01

In reading the publications on turbulence of different authors, one often runs the risk of confusing the various correlation coefficients and turbulence spectra. We have made a point of defining, by appropriate concepts, the differences which exist between these functions. Besides, we introduce in the symbols a few new characteristics of turbulence. In the first chapter, we study some relations between the correlation coefficients and the different turbulence spectra. Certain relations are given by means of demonstrations which could be called intuitive rather than mathematical. In this way we demonstrate that the correlation coefficients between the simultaneous turbulent velocities at two points are identical, whether studied in Lagrange's or in Euler's systems. We then consider new spectra of turbulence, obtained by study of the simultaneous velocities along a straight line of given direction. We determine some relations between these spectra and the correlation coefficients. Examining the relation between the spectrum of the turbulence measured at a fixed point and the longitudinal-correlation curve given by G. I. Taylor, we find that this equation is exact only when the coefficient is very small.

Differences in Callosal and Forniceal Diffusion between Patients with and without Postconcussive Migraine.

PubMed

Alhilali, L M; Delic, J; Fakhran, S

2017-04-01

Posttraumatic migraines are common after mild traumatic brain injury. The purpose of this study was to determine if a specific axonal injury pattern underlies posttraumatic migraines after mild traumatic brain injury utilizing Tract-Based Spatial Statistics analysis of diffusion tensor imaging. DTI was performed in 58 patients with mild traumatic brain injury with posttraumatic migraines. Controls consisted of 17 patients with mild traumatic brain injury without posttraumatic migraines. Fractional anisotropy and diffusivity maps were generated to measure white matter integrity and were evaluated by using Tract-Based Spatial Statistics regression analysis with a general linear model. DTI findings were correlated with symptom severity, neurocognitive test scores, and time to recovery with the Pearson correlation coefficient. Patients with mild traumatic brain injury with posttraumatic migraines were not significantly different from controls in terms of age, sex, type of injury, or neurocognitive test performance. Patients with posttraumatic migraines had higher initial symptom severity ( P = .01) than controls. Compared with controls, patients with mild traumatic brain injury with posttraumatic migraines had decreased fractional anisotropy in the corpus callosum ( P = .03) and fornix/septohippocampal circuit ( P = .045). Injury to the fornix/septohippocampal circuit correlated with decreased visual memory ( r = 0.325, P = .01). Injury to corpus callosum trended toward inverse correlation with recovery ( r = -0.260, P = .05). Injuries to the corpus callosum and fornix/septohippocampal circuit were seen in patients with mild traumatic brain injury with posttraumatic migraines, with injuries in the fornix/septohippocampal circuit correlating with decreased performance on neurocognitive testing. © 2017 by American Journal of Neuroradiology.

Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

NASA Astrophysics Data System (ADS)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.

Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander's overlap coefficient.

PubMed

Adler, Jeremy; Parmryd, Ingela

2010-08-01

The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.

Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2018-04-01

Our purpose was to provide data regarding relationships between different imaging and histopathological parameters in HNSCC. MEDLINE library was screened for associations between different imaging parameters and histopathological features in HNSCC up to December 2017. Only papers containing correlation coefficients between different imaging parameters and histopathological findings were acquired for the analysis. Associations between 18 F-FDG positron emission tomography (PET) and KI 67 were reported in 8 studies (236 patients). The pooled correlation coefficient was 0.20 (95% CI = [-0.04; 0.44]). Furthermore, in 4 studies (64 patients), associations between 18 F-fluorothymidine PET and KI 67 were analyzed. The pooled correlation coefficient between SUV max and KI 67 was 0.28 (95% CI = [-0.06; 0.94]). In 2 studies (23 patients), relationships between KI 67 and dynamic contrast-enhanced magnetic resonance imaging were reported. The pooled correlation coefficient between K trans and KI 67 was -0.68 (95% CI = [-0.91; -0.44]). Two studies (31 patients) investigated correlation between apparent diffusion coefficient (ADC) and KI 67. The pooled correlation coefficient was -0.61 (95% CI = [-0.84; -0.38]). In 2 studies (117 patients), relationships between 18 F-FDG PET and p53 were analyzed. The pooled correlation coefficient was 0.0 (95% CI = [-0.87; 0.88]). There were 3 studies (48 patients) that investigated associations between ADC and tumor cell count in HNSCC. The pooled correlation coefficient was -0.53 (95% CI = [-0.74; -0.32]). Associations between 18 F-FDG PET and HIF-1α were investigated in 3 studies (72 patients). The pooled correlation coefficient was 0.44 (95% CI = [-0.20; 1.08]). ADC may predict cell count and proliferation activity, and SUV max may predict expression of HIF-1α in HNSCC. SUV max cannot be used as surrogate marker for expression of KI 67 and p53. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

NASA Astrophysics Data System (ADS)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

Heterogeneity in Intratumor Correlations of 18F-FDG, 18F-FLT, and 61Cu-ATSM PET in Canine Sinonasal Tumors

PubMed Central

Bradshaw, Tyler J.; Bowen, Stephen R.; Jallow, Ngoneh; Forrest, Lisa J.; Jeraj, Robert

2014-01-01

Intratumor heterogeneity in biologic properties and in relationships between various phenotypes may present a challenge for biologically targeted therapies. Understanding the relationships between different phenotypes in individual tumor types could help inform treatment selection. The goal of this study was to characterize spatial correlations of glucose metabolism, proliferation, and hypoxia in 2 histologic types of tumors. Methods Twenty canine veterinary patients with spontaneously occurring sinonasal tumors (13 carcinomas and 7 sarcomas) were imaged with 18F-FDG, 18F-labeled 39-deoxy-39-fluorothymidine (18F-FLT), and 61Cu-labeled diacetyl-bis(N4-methylthiosemicarbazone) (61Cu-ATSM) PET/CT on 3 consecutive days. Precise positioning and immobilization techniques coupled with anesthesia enabled motionless scans with repeatable positioning. Standardized uptake values (SUVs) of gross sarcoma and carcinoma volumes were compared by use of Mann– Whitney U tests. Patient images were rigidly registered together, and intratumor tracer uptake distributions were compared. Voxel-based Spearman correlation coefficients were used to quantify intertracer correlations, and the correlation coefficients of sarcomas and carcinomas were compared. The relative overlap of the highest uptake volumes of the 3 tracers was quantified, and the values were compared for sarcomas and carcinomas. Results Large degrees of heterogeneity in SUV measures and phenotype correlations were observed. Carcinoma and sarcoma tumors differed significantly in SUV measures, with carcinoma tumors having significantly higher 18F-FDG maximum SUVs than sarcoma tumors (11.1 vs. 5.0; P = 0.01) as well as higher 61Cu-ATSM mean SUVs (2.6 vs. 1.2; P = 0.02). Carcinomas had significantly higher population-averaged Spearman correlation coefficients than sarcomas in comparisons of 18F-FDG and 18F-FLT (0.80 vs. 0.61; P = 0.02), 18F-FLT and 61Cu-ATSM (0.83 vs. 0.38; P < 0.0001), and 18F-FDG and 61Cu-ATSM (0.82 vs. 0.69; P = 0.04). Additionally, the highest uptake volumes of the 3 tracers had significantly greater overlap in carcinomas than in sarcomas. Conclusion The relationships of glucose metabolism, proliferation, and hypoxia were heterogeneous across different tumors, with carcinomas tending to have high correlations and sarcomas having low correlations. Consequently, canine carcinoma tumors are robust targets for therapies that target a single biologic property, whereas sarcoma tumors may not be well suited for such therapies. Histology-specific PET correlations have far-reaching implications for the robustness of biologic target definition. PMID:24042031

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

PubMed

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

PubMed

Wang, Fang; Wang, Lin; Chen, Yuming

2017-08-31

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

Analysis of parenchymal patterns using conspicuous spatial frequency features in mammograms applied to the BI-RADS density rating scheme

NASA Astrophysics Data System (ADS)

Perconti, Philip; Loew, Murray

2006-03-01

Automatic classification of the density of breast parenchyma is shown using a measure that is correlated to the human observer performance, and compared against the BI-RADS density rating. Increasingly popular in the United States, the Breast Imaging Reporting and Data System (BI-RADS) is used to draw attention to the increased screening difficulty associated with greater breast density; however, the BI-RADS rating scheme is subjective and is not intended as an objective measure of breast density. So, while popular, BI-RADS does not define density classes using a standardized measure, which leads to increased variability among observers. The adaptive thresholding technique is a more quantitative approach for assessing the percentage breast density, but considerable reader interaction is required. We calculate an objective density rating that is derived using a measure of local feature salience. Previously, this measure was shown to correlate well with radiologists' localization and discrimination of true positive and true negative regions-of-interest. Using conspicuous spatial frequency features, an objective density rating is obtained and correlated with adaptive thresholding, and the subjectively ascertained BI-RADS density ratings. Using 100 cases, obtained from the University of South Florida's DDSM database, we show that an automated breast density measure can be derived that is correlated with the interactive thresholding method for continuous percentage breast density, but not with the BI-RADS density rating categories for the selected cases. Comparison between interactive thresholding and the new salience percentage density resulted in a Pearson correlation of 76.7%. Using a four-category scale equivalent to the BI-RADS density categories, a Spearman correlation coefficient of 79.8% was found.

Asteroid (21) Lutetia: Semi-Automatic Impact Craters Detection and Classification

NASA Astrophysics Data System (ADS)

Jenerowicz, M.; Banaszkiewicz, M.

2018-05-01

The need to develop an automated method, independent of lighting and surface conditions, for the identification and measurement of impact craters, as well as the creation of a reliable and efficient tool, has become a justification of our studies. This paper presents a methodology for the detection of impact craters based on their spectral and spatial features. The analysis aims at evaluation of the algorithm capabilities to determinate the spatial parameters of impact craters presented in a time series. In this way, time-consuming visual interpretation of images would be reduced to the special cases. The developed algorithm is tested on a set of OSIRIS high resolution images of asteroid Lutetia surface which is characterized by varied landforms and the abundance of craters created by collisions with smaller bodies of the solar system.The proposed methodology consists of three main steps: characterisation of objects of interest on limited set of data, semi-automatic extraction of impact craters performed for total set of data by applying the Mathematical Morphology image processing (Serra, 1988, Soille, 2003), and finally, creating libraries of spatial and spectral parameters for extracted impact craters, i.e. the coordinates of the crater center, semi-major and semi-minor axis, shadow length and cross-section. The overall accuracy of the proposed method is 98 %, the Kappa coefficient is 0.84, the correlation coefficient is ∼ 0.80, the omission error 24.11 %, the commission error 3.45 %. The obtained results show that methods based on Mathematical Morphology operators are effective also with a limited number of data and low-contrast images.

Consequences of using nonlinear particle trajectories to compute spatial diffusion coefficients. [for cosmic ray propagation in interstellar and interplanetary space

NASA Technical Reports Server (NTRS)

Goldstein, M. L.

1977-01-01

In a study of cosmic ray propagation in interstellar and interplanetary space, a perturbed orbit resonant scattering theory for pitch angle diffusion in a slab model of magnetostatic turbulence is slightly generalized and used to compute the diffusion coefficient for spatial propagation parallel to the mean magnetic field. This diffusion coefficient has been useful for describing the solar modulation of the galactic cosmic rays, and for explaining the diffusive phase in solar flares in which the initial anisotropy of the particle distribution decays to isotropy.

Limits of the memory coefficient in measuring correlated bursts

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Hiraoka, Takayuki

2018-03-01

Temporal inhomogeneities in event sequences of natural and social phenomena have been characterized in terms of interevent times and correlations between interevent times. The inhomogeneities of interevent times have been extensively studied, while the correlations between interevent times, often called correlated bursts, are far from being fully understood. For measuring the correlated bursts, two relevant approaches were suggested, i.e., memory coefficient and burst size distribution. Here a burst size denotes the number of events in a bursty train detected for a given time window. Empirical analyses have revealed that the larger memory coefficient tends to be associated with the heavier tail of the burst size distribution. In particular, empirical findings in human activities appear inconsistent, such that the memory coefficient is close to 0, while burst size distributions follow a power law. In order to comprehend these observations, by assuming the conditional independence between consecutive interevent times, we derive the analytical form of the memory coefficient as a function of parameters describing interevent time and burst size distributions. Our analytical result can explain the general tendency of the larger memory coefficient being associated with the heavier tail of burst size distribution. We also find that the apparently inconsistent observations in human activities are compatible with each other, indicating that the memory coefficient has limits to measure the correlated bursts.

Investigation of spatial resolution dependent variability in transcutaneous oxygen saturation using point spectroscopy system

NASA Astrophysics Data System (ADS)

Philimon, Sheena P.; Huong, Audrey K. C.; Ngu, Xavier T. I.

2017-08-01

This paper aims to investigate the variation in one’s percent mean transcutaneous oxygen saturation (StO2) with differences in spatial resolution of data. This work required the knowledge of extinction coefficient of hemoglobin derivatives in the wavelength range of 520 - 600 nm to solve for the StO2 value via an iterative fitting procedure. A pilot study was conducted on three healthy subjects with spectroscopic data collected from their right index finger at different arbitrarily selected distances. The StO2 value estimated by Extended Modified Lambert Beer (EMLB) model revealed a higher mean StO2 of 91.1 ± 1.3% at a proximity distance of 30 mm compared to 60.83 ± 2.8% at 200 mm. The results showed a high correlation between data spatial resolution and StO2 value, and revealed a decrease in StO2 value as the sampling distance increased. The preliminary findings from this study contribute to the knowledge of the appropriate distance range for consistent and high repeatability measurement of skin oxygenation.

Using sequential self-calibration method to identify conductivity distribution: Conditioning on tracer test data

USGS Publications Warehouse

Hu, B.X.; He, C.

2008-01-01

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases. ?? International Association for Mathematical Geology 2008.

Correlation Coefficients: Appropriate Use and Interpretation.

PubMed

Schober, Patrick; Boer, Christa; Schwarte, Lothar A

2018-05-01

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

Clinical Validation of 4-Dimensional Computed Tomography Ventilation With Pulmonary Function Test Data

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

Brennan, Douglas; Schubert, Leah; Diot, Quentin

Purpose: A new form of functional imaging has been proposed in the form of 4-dimensional computed tomography (4DCT) ventilation. Because 4DCTs are acquired as part of routine care for lung cancer patients, calculating ventilation maps from 4DCTs provides spatial lung function information without added dosimetric or monetary cost to the patient. Before 4DCT-ventilation is implemented it needs to be clinically validated. Pulmonary function tests (PFTs) provide a clinically established way of evaluating lung function. The purpose of our work was to perform a clinical validation by comparing 4DCT-ventilation metrics with PFT data. Methods and Materials: Ninety-eight lung cancer patients withmore » pretreatment 4DCT and PFT data were included in the study. Pulmonary function test metrics used to diagnose obstructive lung disease were recorded: forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity. Four-dimensional CT data sets and spatial registration were used to compute 4DCT-ventilation images using a density change–based and a Jacobian-based model. The ventilation maps were reduced to single metrics intended to reflect the degree of ventilation obstruction. Specifically, we computed the coefficient of variation (SD/mean), ventilation V20 (volume of lung ≤20% ventilation), and correlated the ventilation metrics with PFT data. Regression analysis was used to determine whether 4DCT ventilation data could predict for normal versus abnormal lung function using PFT thresholds. Results: Correlation coefficients comparing 4DCT-ventilation with PFT data ranged from 0.63 to 0.72, with the best agreement between FEV1 and coefficient of variation. Four-dimensional CT ventilation metrics were able to significantly delineate between clinically normal versus abnormal PFT results. Conclusions: Validation of 4DCT ventilation with clinically relevant metrics is essential. We demonstrate good global agreement between PFTs and 4DCT-ventilation, indicating that 4DCT-ventilation provides a reliable assessment of lung function. Four-dimensional CT ventilation enables exciting opportunities to assess lung function and create functional avoidance radiation therapy plans. The present work provides supporting evidence for the integration of 4DCT-ventilation into clinical trials.« less

Stress Field Variation after the 2001 Skyros Earthquake, Greece, Derived from Seismicity Rate Changes

NASA Astrophysics Data System (ADS)

Leptokaropoulos, K.; Papadimitriou, E.; Orlecka-Sikora, B.; Karakostas, V.

2012-04-01

The spatial variation of the stress field (ΔCFF) after the 2001 strong (Mw=6.4) Skyros earthquake in North Aegean Sea, Greece, is investigated in association with the changes of earthquake production rates. A detailed slip model is considered in which the causative fault is consisted of several sub-faults with different coseismic slip onto each one of them. First the spatial distribution of aftershock productivity is compared with the static stress changes due to the coseismic slip. Calculations of ΔCFF are performed at different depths inside the seismogenic layer, defined from the vertical distribution of the aftershocks. Seismicity rates of the smaller magnitude events with M≥Mc for different time increments before and after the main shock are then derived from the application of a Probability Density Function (PDF). These rates are computed by spatially smoothing the seismicity and for this purpose a normal grid of rectangular cells is superimposed onto the area and the PDF determines seismicity rate values at the center of each cell. The differences between the earthquake occurrence rates before and after the main shock are compared and used as input data in a stress inversion algorithm based upon the Rate/State dependent friction concept in order to provide an independent estimation of stress changes. This model incorporates the physical properties of the fault zones (characteristic relaxation time, fault constitutive parameters, effective friction coefficient) with a probabilistic estimation of the spatial distribution of seismicity rates, derived from the application of the PDF. The stress patterns derived from the previously mentioned approaches are compared and the quantitative correlation between the respective results is accomplished by the evaluation of Pearson linear correlation coefficient and its confidence intervals to quantify their significance. Different assumptions and combinations of the physical and statistical parameters are tested for the model performance and robustness to be evaluated. Simulations will provide a measure of how robust is the use of seismicity rate changes as a stress meter for both positive and negative stress steps. This work was partially prepared within the framework of the research projects No. N N307234937 and 3935/B/T02/2010/39 financed by the Ministry of Education and Science of Poland during the period 2009 to 2011 and 2010 to 2012, respectively.

Recent advancement in the field of two-dimensional correlation spectroscopy

NASA Astrophysics Data System (ADS)

Noda, Isao

2008-07-01

The recent advancement in the field of 2D correlation spectroscopy is reviewed with the emphasis on a number of papers published during the last two years. Topics covered by this comprehensive review include books, review articles, and noteworthy developments in the theory and applications of 2D correlation spectroscopy. New 2D correlation techniques are discussed, such as kernel analysis and augmented 2D correlation, model-based correlation, moving window analysis, global phase angle, covariance and correlation coefficient mapping, sample-sample correlation, hybrid and hetero correlation, pretreatment and transformation of data, and 2D correlation combined with other chemometrics techniques. Perturbation methods of both static (e.g., temperature, composition, pressure and stress, spatial distribution and orientation) and dynamic types (e.g., rheo-optical and acoustic, chemical reactions and kinetics, H/D exchange, sorption and diffusion) currently in use are examined. Analytical techniques most commonly employed in 2D correlation spectroscopy are IR, Raman, and NIR, but the growing use of other probes is also noted, including fluorescence, emission, Raman optical activity and vibrational circular dichroism, X-ray absorption and scattering, NMR, mass spectrometry, and even chromatography. The field of applications for 2D correlation spectroscopy is very diverse, encompassing synthetic polymers, liquid crystals, Langmuir-Blodgett films, proteins and peptides, natural polymers and biomaterials, pharmaceuticals, food and agricultural products, water, solutions, inorganic, organic, hybrid or composite materials, and many more.

The influence of bed friction variability due to land cover on storm-driven barrier island morphodynamics

USGS Publications Warehouse

Passeri, Davina L.; Long, Joseph W.; Plant, Nathaniel G.; Bilskie, Matthew V.; Hagen, Scott C.

2018-01-01

Variations in bed friction due to land cover type have the potential to influence morphologic change during storm events; the importance of these variations can be studied through numerical simulation and experimentation at locations with sufficient observational data to initialize realistic scenarios, evaluate model accuracy and guide interpretations. Two-dimensional in the horizontal plane (2DH) morphodynamic (XBeach) simulations were conducted to assess morphodynamic sensitivity to spatially varying bed friction at Dauphin Island, AL using hurricanes Ivan (2004) and Katrina (2005) as experimental test cases. For each storm, three bed friction scenarios were simulated: (1) a constant Chezy coefficient across land and water, (2) a constant Chezy coefficient across land and depth-dependent Chezy coefficients across water, and (3) spatially varying Chezy coefficients across land based on land use/land cover (LULC) data and depth-dependent Chezy coefficients across water. Modeled post-storm bed elevations were compared qualitatively and quantitatively with post-storm lidar data. Results showed that implementing spatially varying bed friction influenced the ability of XBeach to accurately simulate morphologic change during both storms. Accounting for frictional effects due to large-scale variations in vegetation and development reduced cross-barrier sediment transport and captured overwash and breaching more accurately. Model output from the spatially varying friction scenarios was used to examine the need for an existing sediment transport limiter, the influence of pre-storm topography and the effects of water level gradients on storm-driven morphodynamics.

Correlates of anxiety and depression among patients with type 2 diabetes mellitus.

PubMed

Balhara, Yatan Pal Singh; Sagar, Rajesh

2011-07-01

Research has established the relation between diabetes and depression. Both diabetes and anxiety/depression are independently associated with increased morbidity and mortality. The present study aims at assessing the prevalence of anxiety/depression among outpatients receiving treatment for type 2 diabetes. The study was conducted in the endocrinology outpatient department of an urban tertiary care center. The instruments used included a semi-structured questionnaire, HbA1c levels, fasting blood glucose and postprandial blood glucose, Brief Patient Health Questionnaire, and Hospital Anxiety and Depression Scale (HADS). Analysis was carried out using the SPSS version 16.0. Pearson's correlation coefficient was calculated to find out the correlations. ANOVA was carried out for the in between group comparisons. There was a significant correlation between the HADS-Anxiety scale and Body Mass Index (BMI) with a correlation coefficient of 0.34 (P = 0.008). Also, a significant correlation existed between HADS-Depression scale and BMI (correlation coefficient, 0.36; P = 0.004). Significant correlation were observed between the duration of daily physical exercise and HADS-Anxiety (coefficient of correlation, -0.25; P = 0.04) scores. HADS-Anxiety scores were found to be related to HbA1c levels (correlation-coefficient, 0.41; P = 0.03) and postprandial blood glucose levels (correlation-coefficient, 0.51; P = 0.02). Monitoring of biochemical parameters like HbA1c and postprandial blood glucose levels and BMI could be a guide to development of anxiety in these patients. Also, physical exercise seems to have a protective effect on anxiety in those with type 2 diabetes mellitus.

Regression approach to non-invasive determination of bilirubin in neonatal blood

NASA Astrophysics Data System (ADS)

Lysenko, S. A.; Kugeiko, M. M.

2012-07-01

A statistical ensemble of structural and biophysical parameters of neonatal skin was modeled based on experimental data. Diffuse scattering coefficients of the skin in the visible and infrared regions were calculated by applying a Monte-Carlo method to each realization of the ensemble. The potential accuracy of recovering the bilirubin concentration in dermis (which correlates closely with that in blood) was estimated from spatially resolved spectrometric measurements of diffuse scattering. The possibility to determine noninvasively the bilirubin concentration was shown by measurements of diffuse scattering at λ = 460, 500, and 660 nm at three source-detector separations under conditions of total variability of the skin biophysical parameters.

LASER BEAMS: On alternative methods for measuring the radius and propagation ratio of axially symmetric laser beams

NASA Astrophysics Data System (ADS)

Dementjev, Aleksandr S.; Jovaisa, A.; Silko, Galina; Ciegis, Raimondas

2005-11-01

Based on the developed efficient numerical methods for calculating the propagation of light beams, the alternative methods for measuring the beam radius and propagation ratio proposed in the international standard ISO 11146 are analysed. The specific calculations of the alternative beam propagation ratios Mi2 performed for a number of test beams with a complicated spatial structure showed that the correlation coefficients ci used in the international standard do not establish the universal one-to-one relation between the alternative propagation ratios Mi2 and invariant propagation ratios Mσ2 found by the method of moments.

Comparison and evaluation of fusion methods used for GF-2 satellite image in coastal mangrove area

NASA Astrophysics Data System (ADS)

Ling, Chengxing; Ju, Hongbo; Liu, Hua; Zhang, Huaiqing; Sun, Hua

2018-04-01

GF-2 satellite is the highest spatial resolution Remote Sensing Satellite of the development history of China's satellite. In this study, three traditional fusion methods including Brovey, Gram-Schmidt and Color Normalized (CN were used to compare with the other new fusion method NNDiffuse, which used the qualitative assessment and quantitative fusion quality index, including information entropy, variance, mean gradient, deviation index, spectral correlation coefficient. Analysis results show that NNDiffuse method presented the optimum in qualitative and quantitative analysis. It had more effective for the follow up of remote sensing information extraction and forest, wetland resources monitoring applications.

Quiet geomagnetic field representation for all days and latitudes

USGS Publications Warehouse

Campbell, W.H.; Schiffmacher, E.R.; Arora, B.R.

1992-01-01

Describes a technique for obtaining the quiet-time geomagnetic field variation expected for all days of the year and distribution of latitudes from a limited set of selected quiet days within a year at a discrete set of locations. A data set of observatories near 75??E longitude was used as illustration. The method relies upon spatial smoothing of the decomposed spectral components. An evaluation of the fidelity of the resulting model shows correlation coefficients usually above 0.9 at the lower latitudes and near 0.7 at the higher latitudes with variations identified as dependent upon season and field element. -from Authors

Prediction of friction coefficients for gases

NASA Technical Reports Server (NTRS)

Taylor, M. F.

1969-01-01

Empirical relations are used for correlating laminar and turbulent friction coefficients for gases, with large variations in the physical properties, flowing through smooth tubes. These relations have been used to correlate friction coefficients for hydrogen, helium, nitrogen, carbon dioxide and air.

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River.

PubMed

Ouyang, Wei; Hao, Fanghua; Skidmore, Andrew K; Toxopeus, A G

2010-12-15

Soil erosion is a significant concern when considering regional environmental protection, especially in the Yellow River Basin in China. This study evaluated the temporal-spatial interaction of land cover status with soil erosion characteristics in the Longliu Catchment of China, using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physical hydrological model which uses the RUSLE equation as a sediment algorithm. Considering the spatial and temporal scale of the relationship between soil erosion and sediment yield, simulations were undertaken at monthly and annual temporal scales and basin and sub-basin spatial scales. The corresponding temporal and spatial Normalized Difference Vegetation Index (NDVI) information was summarized from MODIS data, which can integrate regional land cover and climatic features. The SWAT simulation revealed that the annual soil erosion and sediment yield showed similar spatial distribution patterns, but the monthly variation fluctuated significantly. The monthly basin soil erosion varied from almost no erosion load to 3.92 t/ha and the maximum monthly sediment yield was 47,540 tones. The inter-annual simulation focused on the spatial difference and relationship with the corresponding vegetation NDVI value for every sub-basin. It is concluded that, for this continental monsoon climate basin, the higher NDVI vegetation zones prevented sediment transport, but at the same time they also contributed considerable soil erosion. The monthly basin soil erosion and sediment yield both correlated with NDVI, and the determination coefficients of their exponential correlation model were 0.446 and 0.426, respectively. The relationships between soil erosion and sediment yield with vegetation NDVI indicated that the vegetation status has a significant impact on sediment formation and transport. The findings can be used to develop soil erosion conservation programs for the study area. Copyright © 2010 Elsevier B.V. All rights reserved.

The Robustness of Designs for Trials with Nested Data against Incorrect Initial Intracluster Correlation Coefficient Estimates

ERIC Educational Resources Information Center

Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.

2010-01-01

In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…

The Correlation Between Atmospheric Dust Deposition to the Surface Ocean and SeaWiFS Ocean Color: A Global Satellite-Based Analysis

NASA Technical Reports Server (NTRS)

Erickson, D. J., III; Hernandez, J.; Ginoux, P.; Gregg, W.; Kawa, R.; Behrenfeld, M.; Esaias, W.; Einaudi, Franco (Technical Monitor)

2000-01-01

Since the atmospheric deposition of iron has been linked to primary productivity in various oceanic regions, we have conducted an objective study of the correlation of dust deposition and satellite remotely sensed surface ocean chlorophyll concentrations. We present a global analysis of the correlation between atmospheric dust deposition derived from a satellite-based 3-D atmospheric transport model and SeaWiFs estimates of ocean color. We use the monthly mean dust deposition fields of Ginoux et al. which are based on a global model of dust generation and transport. This model is driven by atmospheric circulation from the Data Assimilation Office (DAO) for the period 1995-1998. This global dust model is constrained by several satellite estimates of standard circulation characteristics. We then perform an analysis of the correlation between the dust deposition and the 1998 SeaWIFS ocean color data for each 2.0 deg x 2.5 deg lat/long grid point, for each month of the year. The results are surprisingly robust. The region between 40 S and 60 S has correlation coefficients from 0.6 to 0.95, statistically significant at the 0.05 level. There are swaths of high correlation at the edges of some major ocean current systems. We interpret these correlations as reflecting areas that have shear related turbulence bringing nitrogen and phosphorus from depth into the surface ocean, and the atmospheric supply of iron provides the limiting nutrient and the correlation between iron deposition and surface ocean chlorophyll is high. There is a region in the western North Pacific with high correlation, reflecting the input of Asian dust to that region. The southern hemisphere has an average correlation coefficient of 0.72 compared that in the northern hemisphere of 0.42 consistent with present conceptual models of where atmospheric iron deposition may play a role in surface ocean biogeochemical cycles. The spatial structure of the correlation fields will be discussed within the context of guiding the design of field programs.

Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

PubMed

Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

2018-07-14

In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Forest above ground biomass estimation and forest/non-forest classification for Odisha, India, using L-band Synthetic Aperture Radar (SAR) data

NASA Astrophysics Data System (ADS)

Suresh, M.; Kiran Chand, T. R.; Fararoda, R.; Jha, C. S.; Dadhwal, V. K.

2014-11-01

Tropical forests contribute to approximately 40 % of the total carbon found in terrestrial biomass. In this context, forest/non-forest classification and estimation of forest above ground biomass over tropical regions are very important and relevant in understanding the contribution of tropical forests in global biogeochemical cycles, especially in terms of carbon pools and fluxes. Information on the spatio-temporal biomass distribution acts as a key input to Reducing Emissions from Deforestation and forest Degradation Plus (REDD+) action plans. This necessitates precise and reliable methods to estimate forest biomass and to reduce uncertainties in existing biomass quantification scenarios. The use of backscatter information from a host of allweather capable Synthetic Aperture Radar (SAR) systems during the recent past has demonstrated the potential of SAR data in forest above ground biomass estimation and forest / nonforest classification. In the present study, Advanced Land Observing Satellite (ALOS) / Phased Array L-band Synthetic Aperture Radar (PALSAR) data along with field inventory data have been used in forest above ground biomass estimation and forest / non-forest classification over Odisha state, India. The ALOSPALSAR 50 m spatial resolution orthorectified and radiometrically corrected HH/HV dual polarization data (digital numbers) for the year 2010 were converted to backscattering coefficient images (Schimada et al., 2009). The tree level measurements collected during field inventory (2009-'10) on Girth at Breast Height (GBH at 1.3 m above ground) and height of all individual trees at plot (plot size 0.1 ha) level were converted to biomass density using species specific allometric equations and wood densities. The field inventory based biomass estimations were empirically integrated with ALOS-PALSAR backscatter coefficients to derive spatial forest above ground biomass estimates for the study area. Further, The Support Vector Machines (SVM) based Radial Basis Function classification technique was employed to carry out binary (forest-non forest) classification using ALOSPALSAR HH and HV backscatter coefficient images and field inventory data. The textural Haralick's Grey Level Cooccurrence Matrix (GLCM) texture measures are determined on HV backscatter image for Odisha, for the year 2010. PALSAR HH, HV backscatter coefficient images, their difference (HHHV) and HV backscatter coefficient based eight textural parameters (Mean, Variance, Dissimilarity, Contrast, Angular second moment, Homogeneity, Correlation and Contrast) are used as input parameters for Support Vector Machines (SVM) tool. Ground based inputs for forest / non-forest were taken from field inventory data and high resolution Google maps. Results suggested significant relationship between HV backscatter coefficient and field based biomass (R2 = 0.508, p = 0.55) compared to HH with biomass values ranging from 5 to 365 t/ha. The spatial variability of biomass with reference to different forest types is in good agreement. The forest / nonforest classified map suggested a total forest cover of 50214 km2 with an overall accuracy of 92.54 %. The forest / non-forest information derived from the present study showed a good spatial agreement with the standard forest cover map of Forest Survey of India (FSI) and corresponding published area of 50575 km2. Results are discussed in the paper.

Study on Spatial Spillover Effects of Logistics Industry Development for Economic Growth in the Yangtze River Delta City Cluster Based on Spatial Durbin Model

PubMed Central

Xu, Xinxing

2017-01-01

The overall entropy method is used to evaluate the development level of the logistics industry in the city based on a mechanism analysis of the spillover effect of the development of the logistics industry on economic growth, according to the panel data of 26 cities in the Yangtze River delta. On this basis, the paper uses the spatial durbin model to study the direct impact of the development of the logistics industry on economic growth and the spatial spillover effect. The results show that the direct impact coefficient of the development of the logistics industry in the Yangtze River Delta urban agglomeration on local economic growth is 0.092, and the significant spatial spillover effect on the economic growth in the surrounding area is 0.197. Compared with the labor force input, capital investment and the degree of opening to the world, and government functions, the logistics industry’s direct impact coefficient is the largest, other than capital investment; the coefficient of the spillover effect is higher than other control variables, making it a “strong engine” of the Yangtze River Delta urban agglomeration economic growth. PMID:29207555

Study on Spatial Spillover Effects of Logistics Industry Development for Economic Growth in the Yangtze River Delta City Cluster Based on Spatial Durbin Model.

PubMed

Xu, Xinxing; Wang, Yuhong

2017-12-04

The overall entropy method is used to evaluate the development level of the logistics industry in the city based on a mechanism analysis of the spillover effect of the development of the logistics industry on economic growth, according to the panel data of 26 cities in the Yangtze River delta. On this basis, the paper uses the spatial durbin model to study the direct impact of the development of the logistics industry on economic growth and the spatial spillover effect. The results show that the direct impact coefficient of the development of the logistics industry in the Yangtze River Delta urban agglomeration on local economic growth is 0.092, and the significant spatial spillover effect on the economic growth in the surrounding area is 0.197. Compared with the labor force input, capital investment and the degree of opening to the world, and government functions, the logistics industry's direct impact coefficient is the largest, other than capital investment; the coefficient of the spillover effect is higher than other control variables, making it a "strong engine" of the Yangtze River Delta urban agglomeration economic growth.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Spatial Representativeness of Surface-Measured Variations of Downward Solar Radiation

NASA Astrophysics Data System (ADS)

Schwarz, M.; Folini, D.; Hakuba, M. Z.; Wild, M.

2017-12-01

When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05°) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R2 ranges from 0.85 for distances up to 25 km between the stations to 0.25 at distances of 500 km. A decorrelation length (i.e., the e-folding distance of R2) on the order of 400 km (with spread of 100-600 km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1° grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1° grid of 8 (3) W/m2 for monthly (annual) time series. The SSE based on a 1° grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.

Evaluation of the Correlation Coefficient of Polyethylene Glycol Treated and Direct Prolactin Results and Comparability with Different Assay System Results.

PubMed

Pal, Shyamali

2017-12-01

The presence of Macro prolactin is a significant cause of elevated prolactin resulting in misdiagnosis in all automated systems. Poly ethylene glycol (PEG) pretreatment is the preventive process but such process includes the probability of loss of a fraction of bioactive prolactin. Surprisingly, PEG treated EQAS & IQAS samples in Cobas e 411 are found out to be correlating with direct results of at least 3 immunoassay systems and treated and untreated Cobas e 411 results are comparable by a correlation coefficient. Comparison of EQAS, IQAS and patient samples were done to find out the trueness of such correlation factor. Study with patient's results have established the correlation coefficient is valid for very small concentration of prolactin also. EQAS, IQAS and 150 patient samples were treated with PEG and prolactin results of treated and untreated samples obtained from Roche Cobas e 411. 25 patient's results (treated) were compared with direct results in Advia Centaur, Architect I & Access2 systems. Correlation coefficient was obtained from trend line of the treated and untreated results. Two tailed p-value obtained from regression coefficient(r) and sample size. The correlation coefficient is in the range (0.761-0.771). Reverse correlation range is (1.289-1.301). r value of two sets of calculated results were 0.995. Two tailed p- value is zero approving dismissal of null hypothesis. The z-score of EQAS does not always assure authenticity of resultsPEG precipitation is correlated by the factor 0.761 even in very small concentrationsAbbreviationsGFCgel filtration chromatographyPEGpolyethylene glycolEQASexternal quality assurance systemM-PRLmacro prolactinPRLprolactinECLIAelectro-chemiluminescence immunoassayCLIAclinical laboratory improvement amendmentsIQASinternal quality assurance systemrregression coefficient.

A human visual model-based approach of the visual attention and performance evaluation

NASA Astrophysics Data System (ADS)

Le Meur, Olivier; Barba, Dominique; Le Callet, Patrick; Thoreau, Dominique

2005-03-01

In this paper, a coherent computational model of visual selective attention for color pictures is described and its performances are precisely evaluated. The model based on some important behaviours of the human visual system is composed of four parts: visibility, perception, perceptual grouping and saliency map construction. This paper focuses mainly on its performances assessment by achieving extended subjective and objective comparisons with real fixation points captured by an eye-tracking system used by the observers in a task-free viewing mode. From the knowledge of the ground truth, qualitatively and quantitatively comparisons have been made in terms of the measurement of the linear correlation coefficient (CC) and of the Kulback Liebler divergence (KL). On a set of 10 natural color images, the results show that the linear correlation coefficient and the Kullback Leibler divergence are of about 0.71 and 0.46, respectively. CC and Kl measures with this model are respectively improved by about 4% and 7% compared to the best model proposed by L.Itti. Moreover, by comparing the ability of our model to predict eye movements produced by an average observer, we can conclude that our model succeeds quite well in predicting the spatial locations of the most important areas of the image content.

Plant phenological synchrony increases under rapid within-spring warming.

PubMed

Wang, Cong; Tang, Yanhong; Chen, Jin

2016-05-05

Phenological synchrony influences many ecological processes. Recent climate change has altered the synchrony of phenology, but little is known about the underlying mechanisms. Here using in situ phenological records from Europe, we found that the standard deviation (SD, as a measure of synchrony) of first leafing day (FLD) and the SD of first flowering day (FFD) among local plants were significantly smaller in the years and/or in the regions with a more rapid within-spring warming speed (WWS, the linear slope of the daily mean temperature against the days during spring, in (o)C/day) with correlation coefficients of -0.75 and -0.48 for FLD and -0.55 and -0.23 for FFD. We further found that the SDs of temperature sensitivity of local plants were smaller under the rapid WWS conditions with correlation coefficients of -0.46 and -0.33 for FLD and FFD respectively. This study provides the first evidence that the within-season rate of change of the temperature but not the magnitude determines plant phenological synchrony. It implies that temporally, the asymmetric seasonal climatic warming may decrease the synchrony via increasing WWS, especially in arctic regions; spatially, plants in coastal and low latitude areas with low WWS would have more diverse spring phenological traits.

Simulating floods in the Amazon River Basin: Impacts of new river geomorphic and dynamic flow parameterizations

NASA Astrophysics Data System (ADS)

Coe, M. T.; Costa, M. H.; Howard, E. A.

2006-12-01

In this paper we analyze the hydrology of the Amazon River system for the latter half of the 20th century with our recently completed model of terrestrial hydrology (Terrestrial Hydrology Model with Biogeochemistry, THMB). We evaluate the simulated hydrology of the Central Amazon basin against limited observations of river discharge, floodplain inundation, and water height and analyze the spatial and temporal variability of the hydrology for the period 1939-1998. We compare the simulated discharge and floodplain inundated area to the simulations by Coe et al., 2002 using a previous version of this model. The new model simulates the discharge and flooded area in better agreement with the observations than the previous model. The coefficient of correlation between the simulated and observed discharge for the greater than 27000 monthly observations of discharge at 120 sites throughout the Brazilian Amazon is 0.9874 compared to 0.9744 for the previous model. The coefficient of correlation between the simulated monthly flooded area and the satellite-based estimates by Sippel et al., 1998 exceeds 0.7 for 8 of the 12 mainstem reaches. The seasonal and inter-annual variability of the water height and the river slope compares favorably to the satellite altimetric measurements of height reported by Birkett et al., 2002.

Satellite remote sensing of fine particulate air pollutants over Indian mega cities

NASA Astrophysics Data System (ADS)

Sreekanth, V.; Mahesh, B.; Niranjan, K.

2017-11-01

In the backdrop of the need for high spatio-temporal resolution data on PM2.5 mass concentrations for health and epidemiological studies over India, empirical relations between Aerosol Optical Depth (AOD) and PM2.5 mass concentrations are established over five Indian mega cities. These relations are sought to predict the surface PM2.5 mass concentrations from high resolution columnar AOD datasets. Current study utilizes multi-city public domain PM2.5 data (from US Consulate and Embassy's air monitoring program) and MODIS AOD, spanning for almost four years. PM2.5 is found to be positively correlated with AOD. Station-wise linear regression analysis has shown spatially varying regression coefficients. Similar analysis has been repeated by eliminating data from the elevated aerosol prone seasons, which has improved the correlation coefficient. The impact of the day to day variability in the local meteorological conditions on the AOD-PM2.5 relationship has been explored by performing a multiple regression analysis. A cross-validation approach for the multiple regression analysis considering three years of data as training dataset and one-year data as validation dataset yielded an R value of ∼0.63. The study was concluded by discussing the factors which can improve the relationship.

Post-Seismic Deformation from the 2009 Mw 6.3 Dachaidan Earthquake in the Northern Qaidam Basin Detected by Small Baseline Subset InSAR Technique

PubMed Central

Liu, Yang; Xu, Caijun; Wen, Yangmao; Li, Zhicai

2016-01-01

On 28 August 2009, one thrust-faulting Mw 6.3 earthquake struck the northern Qaidam basin, China. Due to the lack of ground observations in this remote region, this study presents high-precision and high spatio-temporal resolution post-seismic deformation series with a small baseline subset InSAR technique. At the temporal scale, this changes from fast to slow with time, with a maximum uplift up to 7.4 cm along the line of sight 334 days after the event. At the spatial scale, this is more obvious at the hanging wall than that at the footwall, and decreases from the middle to both sides at the hanging wall. We then propose a method to calculate the correlation coefficient between co-seismic and post-seismic deformation by normalizing them. The correlation coefficient is found to be 0.73, indicating a similar subsurface process occurring during both phases. The results indicate that afterslip may dominate the post-seismic deformation during 19–334 days after the event, which mainly occurs with the fault geometry and depth similar to those of the c-seismic rupturing, and partly extends to the shallower and deeper depths. PMID:26861330

Post-Seismic Deformation from the 2009 Mw 6.3 Dachaidan Earthquake in the Northern Qaidam Basin Detected by Small Baseline Subset InSAR Technique.

PubMed

Liu, Yang; Xu, Caijun; Wen, Yangmao; Li, Zhicai

2016-02-05

On 28 August 2009, one thrust-faulting Mw 6.3 earthquake struck the northern Qaidam basin, China. Due to the lack of ground observations in this remote region, this study presents high-precision and high spatio-temporal resolution post-seismic deformation series with a small baseline subset InSAR technique. At the temporal scale, this changes from fast to slow with time, with a maximum uplift up to 7.4 cm along the line of sight 334 days after the event. At the spatial scale, this is more obvious at the hanging wall than that at the footwall, and decreases from the middle to both sides at the hanging wall. We then propose a method to calculate the correlation coefficient between co-seismic and post-seismic deformation by normalizing them. The correlation coefficient is found to be 0.73, indicating a similar subsurface process occurring during both phases. The results indicate that afterslip may dominate the post-seismic deformation during 19-334 days after the event, which mainly occurs with the fault geometry and depth similar to those of the c-seismic rupturing, and partly extends to the shallower and deeper depths.

An implicit spatial and high-order temporal finite difference scheme for 2D acoustic modelling

NASA Astrophysics Data System (ADS)

Wang, Enjiang; Liu, Yang

2018-01-01

The finite difference (FD) method exhibits great superiority over other numerical methods due to its easy implementation and small computational requirement. We propose an effective FD method, characterised by implicit spatial and high-order temporal schemes, to reduce both the temporal and spatial dispersions simultaneously. For the temporal derivative, apart from the conventional second-order FD approximation, a special rhombus FD scheme is included to reach high-order accuracy in time. Compared with the Lax-Wendroff FD scheme, this scheme can achieve nearly the same temporal accuracy but requires less floating-point operation times and thus less computational cost when the same operator length is adopted. For the spatial derivatives, we adopt the implicit FD scheme to improve the spatial accuracy. Apart from the existing Taylor series expansion-based FD coefficients, we derive the least square optimisation based implicit spatial FD coefficients. Dispersion analysis and modelling examples demonstrate that, our proposed method can effectively decrease both the temporal and spatial dispersions, thus can provide more accurate wavefields.

Nasendoscopy: an analysis of measurement uncertainties.

PubMed

Gilleard, Onur; Sommerlad, Brian; Sell, Debbie; Ghanem, Ali; Birch, Malcolm

2013-05-01

Objective : The purpose of this study was to analyze the optical characteristics of two different nasendoscopes used to assess velopharyngeal insufficiency and to quantify the measurement uncertainties that will occur in a typical set of clinical data. Design : The magnification and barrel distortion associated with nasendoscopy was estimated by using computer software to analyze the apparent dimensions of a spatially calibrated test object at varying object-lens distances. In addition, a method of semiquantitative analysis of velopharyngeal closure using nasendoscopy and computer software is described. To calculate the reliability of this method, 10 nasendoscopy examinations were analyzed two times by three separate operators. The measure of intraoperator and interoperator agreement was evaluated using Pearson's r correlation coefficient. Results : Over an object lens distance of 9 mm, magnification caused the visualized dimensions of the test object to increase by 80%. In addition, dimensions of objects visualized in the far-peripheral field of the nasendoscopic examinations appeared approximately 40% smaller than those visualized in the central field. Using computer software to analyze velopharyngeal closure, the mean correlation coefficient for intrarater reliability was .94 and for interrater reliability was .90. Conclusion : Using a custom-designed apparatus, the effect object-lens distance has on the magnification of nasendoscopic images has been quantified. Barrel distortion has also been quantified and was found to be independent of object-lens distance. Using computer software to analyze clinical images, the intraoperator and interoperator correlation appears to show that ratio-metric measurements are reliable.

Anthropometry of Women of the U.S. Army--1977. Report Number 4. Correlation Coefficients

DTIC Science & Technology

1980-02-01

S.... •, 0 76 x:. ADo5 //64 ! TECHNICAL REPORT NATICK/TR-80/016 (/ II ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY-1977 Report No. 4 Correlation...NUMBER NATICK/TR-80/016 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED ANTHROPOMETRY OF WOMEN OF THE U.S. ARMY--1977 Technical Report REPORT NO... Anthropometry Survey(s) Coefficients of correlation Measurement(s) U.S. Army Correlation coefficients Body size Military personnel Equation(s) Sizes

In vivo characterization of a reporter gene system for imaging hypoxia-induced gene expression.

PubMed

Carlin, Sean; Pugachev, Andrei; Sun, Xiaorong; Burke, Sean; Claus, Filip; O'Donoghue, Joseph; Ling, C Clifton; Humm, John L

2009-10-01

To characterize a tumor model containing a hypoxia-inducible reporter gene and to demonstrate utility by comparison of reporter gene expression to the uptake and distribution of the hypoxia tracer (18)F-fluoromisonidazole ((18)F-FMISO). Three tumors derived from the rat prostate cancer cell line R3327-AT were grown in each of two rats as follows: (1) parental R3327-AT, (2) positive control R3327-AT/PC in which the HSV1-tkeGFP fusion reporter gene was expressed constitutively, (3) R3327-AT/HRE in which the reporter gene was placed under the control of a hypoxia-inducible factor-responsive promoter sequence (HRE). Animals were coadministered a hypoxia-specific marker (pimonidazole) and the reporter gene probe (124)I-2'-fluoro-2'-deoxy-1-beta-d-arabinofuranosyl-5-iodouracil ((124)I-FIAU) 3 h prior to sacrifice. Statistical analysis of the spatial association between (124)I-FIAU uptake and pimonidazole fluorescent staining intensity was then performed on a pixel-by-pixel basis. Utility of this system was demonstrated by assessment of reporter gene expression versus the exogenous hypoxia probe (18)F-FMISO. Two rats, each bearing a single R3327-AT/HRE tumor, were injected with (124)I-FIAU (3 h before sacrifice) and (18)F-FMISO (2 h before sacrifice). Statistical analysis of the spatial association between (18)F-FMISO and (124)I-FIAU on a pixel-by-pixel basis was performed. Correlation coefficients between (124)I-FIAU uptake and pimonidazole staining intensity were: 0.11 in R3327-AT tumors, -0.66 in R3327-AT/PC and 0.76 in R3327-AT/HRE, confirming that only in the R3327-AT/HRE tumor was HSV1-tkeGFP gene expression associated with hypoxia. Correlation coefficients between (18)F-FMISO and (124)I-FIAU uptakes in R3327-AT/HRE tumors were r=0.56, demonstrating good spatial correspondence between the two tracers. We have confirmed hypoxia-specific expression of the HSV1-tkeGFP fusion gene in the R3327-AT/HRE tumor model and demonstrated the utility of this model for the evaluation of radiolabeled hypoxia tracers.

Spatial and Temporal Dynamics of the Leaf Area Index of the Caatinga Biome

NASA Astrophysics Data System (ADS)

Alves Rodrigues Pinheiro, Everton; de Jong van Lier, Quirijn; Metselaar, Klaas

2015-04-01

Leaf Area Index (LAI) is an important characteristic of ecosystems with a prominent role in processes such as transpiration, photosynthesis and interception. The Caatinga biome is a unique semiarid ecosystem ocurring in a specific region of Brazil. An important main feature of this biome is the leaf shedding and regenerative capacity of its species. The aim of this study was to quantify both spatial and temporal dynamics of the LAI of the Caatinga biome in the Aiuaba Experimental Basin, an integrally-preserved Caatinga reserve, coordinates 6°42'S; 40°17'W. The research site (12 km2) was divided into three main Soil and Vegatation Associations (SVA). For each SVA the soil type and root depth are respectively, Acrisol -0.8 m, Luvisol - 0.6 m and Regosol - 0.4 m. The LAI was estimated by SEBAL algorithm applied to eleven satellite images from Landsat 5. The values of LAI estimated by SEBAL were correlated to the mean soil water content of the 15 days previous to the satellite image date. Eight images were used to generate a simple regression model, yielding a range of coefficient of determination from 0.89 to 0.92. Three other images were used to validate the equations. The Nash-Sutcliffe efficiency coefficient ranged from 0.76 to 0.94. Using the validated correlations, the LAI was calculated over the time for each of the three SVA, from 2004 to 2012. For SVA1, SVA2 and SVA3, the avarage values of LAI during the rainy season were 0.97, 1.12 and 1.07, respectively. During the dry season, the mean values were 0.15 for SVA1 and 0.11 for SVA2 and SVA3. The vegetation showed abrupt LAI changes, and the average previous 15 days soil water content was a good indicator for this. The study has shown that the maximum LAI was relatively stable over the years, occurring between March and April. The spatial behavior of LAI appeared to be similar, independently of the soil type and root depth.

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

Matching the quasiparton distribution in a momentum subtraction scheme

NASA Astrophysics Data System (ADS)

Stewart, Iain W.; Zhao, Yong

2018-03-01

The quasiparton distribution is a spatial correlation of quarks or gluons along the z direction in a moving nucleon which enables direct lattice calculations of parton distribution functions. It can be defined with a nonperturbative renormalization in a regularization independent momentum subtraction scheme (RI/MOM), which can then be perturbatively related to the collinear parton distribution in the MS ¯ scheme. Here we carry out a direct matching from the RI/MOM scheme for the quasi-PDF to the MS ¯ PDF, determining the non-singlet quark matching coefficient at next-to-leading order in perturbation theory. We find that the RI/MOM matching coefficient is insensitive to the ultraviolet region of convolution integral, exhibits improved perturbative convergence when converting between the quasi-PDF and PDF, and is consistent with a quasi-PDF that vanishes in the unphysical region as the proton momentum Pz→∞ , unlike other schemes. This direct approach therefore has the potential to improve the accuracy for converting quasidistribution lattice calculations to collinear distributions.

A TV-constrained decomposition method for spectral CT

NASA Astrophysics Data System (ADS)

Guo, Xiaoyue; Zhang, Li; Xing, Yuxiang

2017-03-01

Spectral CT is attracting more and more attention in medicine, industrial nondestructive testing and security inspection field. Material decomposition is an important issue to a spectral CT to discriminate materials. Because of the spectrum overlap of energy channels, as well as the correlation of basis functions, it is well acknowledged that decomposition step in spectral CT imaging causes noise amplification and artifacts in component coefficient images. In this work, we propose materials decomposition via an optimization method to improve the quality of decomposed coefficient images. On the basis of general optimization problem, total variance minimization is constrained on coefficient images in our overall objective function with adjustable weights. We solve this constrained optimization problem under the framework of ADMM. Validation on both a numerical dental phantom in simulation and a real phantom of pig leg on a practical CT system using dual-energy imaging is executed. Both numerical and physical experiments give visually obvious better reconstructions than a general direct inverse method. SNR and SSIM are adopted to quantitatively evaluate the image quality of decomposed component coefficients. All results demonstrate that the TV-constrained decomposition method performs well in reducing noise without losing spatial resolution so that improving the image quality. The method can be easily incorporated into different types of spectral imaging modalities, as well as for cases with energy channels more than two.

Modeling Monthly Spatial Distribution of Ommastrephes bartramii CPUE in the Northwest Pacific and Its Spatially Nonstationary Relationships with the Marine Environment

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Liu, Yang; Chen, Xinjun

2018-06-01

There are substantial spatial variations in the relationships between catch-per-unit-effort (CPUE) and oceanographic conditions with respect to pelagic species. This study examines the monthly spatiotemporal distribution of CPUE of the neon flying squid, Ommastrephes bartramii, in the Northwest Pacific from July to November during 2004-2013, and analyzes the relationships with oceanographic conditions using a generalized additive model (GAM) and geographically weighted regression (GWR) model. The results show that most of the squids were harvested in waters with sea surface temperature (SST) between 7.6 and 24.6°C, chlorophyll- a (Chl- a) concentration below 1.0 mg m-3, sea surface salinity (SSS) between 32.7 and 34.6, and sea surface height (SSH) between -12.8 and 28.4 cm. The monthly spatial distribution patterns of O. bartramii predicted using GAM and GWR models are similar to observed patterns for all months. There are notable variations in the local coefficients of GWR, indicating the presence of spatial non-stationarity in the relationship between O. bartramii CPUE and oceanographic conditions. The statistical results show that there were nearly equal positive and negative coefficients for Chl- a, more positive than negative coefficients for SST, and more negative than positive coefficients for SSS and SSH. The overall accuracies of the hot spots predicted by GWR exceed 60% (except for October), indicating a good performance of this model and its improvement over GAM. Our study provides a better understanding of the ecological dynamics of O. bartramii CPUE and makes it possible to use GWR to study the spatially nonstationary characteristics of other pelagic species.

Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

PubMed

Mukaka, M M

2012-09-01

Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.

[Correlation of molecular weight and nanofiltration mass transfer coefficient of phenolic acid composition from Salvia miltiorrhiza].

PubMed

Li, Cun-Yu; Wu, Xin; Gu, Jia-Mei; Li, Hong-Yang; Peng, Guo-Ping

2018-04-01

Based on the molecular sieving and solution-diffusion effect in nanofiltration separation, the correlation between initial concentration and mass transfer coefficient of three typical phenolic acids from Salvia miltiorrhiza was fitted to analyze the relationship among mass transfer coefficient, molecular weight and concentration. The experiment showed a linear relationship between operation pressure and membrane flux. Meanwhile, the membrane flux was gradually decayed with the increase of solute concentration. On the basis of the molecular sieving and solution-diffusion effect, the mass transfer coefficient and initial concentration of three phenolic acids showed a power function relationship, and the regression coefficients were all greater than 0.9. The mass transfer coefficient and molecular weight of three phenolic acids were negatively correlated with each other, and the order from high to low is protocatechualdehyde >rosmarinic acid> salvianolic acid B. The separation mechanism of nanofiltration for phenolic acids was further clarified through the analysis of the correlation of molecular weight and nanofiltration mass transfer coefficient. The findings provide references for nanofiltration separation, especially for traditional Chinese medicine with phenolic acids. Copyright© by the Chinese Pharmaceutical Association.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

White Matter Tract Integrity in Alzheimer's Disease vs. Late Onset Bipolar Disorder and Its Correlation with Systemic Inflammation and Oxidative Stress Biomarkers.

PubMed

Besga, Ariadna; Chyzhyk, Darya; Gonzalez-Ortega, Itxaso; Echeveste, Jon; Graña-Lecuona, Marina; Graña, Manuel; Gonzalez-Pinto, Ana

2017-01-01

Background: Late Onset Bipolar Disorder (LOBD) is the development of Bipolar Disorder (BD) at an age above 50 years old. It is often difficult to differentiate from other aging dementias, such as Alzheimer's Disease (AD), because they share cognitive and behavioral impairment symptoms. Objectives: We look for WM tract voxel clusters showing significant differences when comparing of AD vs. LOBD, and its correlations with systemic blood plasma biomarkers (inflammatory, neurotrophic factors, and oxidative stress). Materials: A sample of healthy controls (HC) ( n = 19), AD patients ( n = 35), and LOBD patients ( n = 24) was recruited at the Alava University Hospital. Blood plasma samples were obtained at recruitment time and analyzed to extract the inflammatory, oxidative stress, and neurotrophic factors. Several modalities of MRI were acquired for each subject, Methods: Fractional anisotropy (FA) coefficients are obtained from diffusion weighted imaging (DWI). Tract based spatial statistics (TBSS) finds FA skeleton clusters of WM tract voxels showing significant differences for all possible contrasts between HC, AD, and LOBD. An ANOVA F -test over all contrasts is carried out. Results of F -test are used to mask TBSS detected clusters for the AD > LOBD and LOBD > AD contrast to select the image clusters used for correlation analysis. Finally, Pearson's correlation coefficients between FA values at cluster sites and systemic blood plasma biomarker values are computed. Results: The TBSS contrasts with by ANOVA F -test has identified strongly significant clusters in the forceps minor, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and cingulum gyrus. The correlation analysis of these tract clusters found strong negative correlation of AD with the nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) blood biomarkers. Negative correlation of AD and positive correlation of LOBD with inflammation biomarker IL6 was also found. Conclusion: TBSS voxel clusters tract atlas localizations are consistent with greater behavioral impairment and mood disorders in LOBD than in AD. Correlation analysis confirms that neurotrophic factors (i.e., NGF, BDNF) play a great role in AD while are absent in LOBD pathophysiology. Also, correlation results of IL1 and IL6 suggest stronger inflammatory effects in LOBD than in AD.

Comparisons of traffic-related ultrafine particle number concentrations measured in two urban areas by central, residential, and mobile monitoring

NASA Astrophysics Data System (ADS)

Simon, Matthew C.; Hudda, Neelakshi; Naumova, Elena N.; Levy, Jonathan I.; Brugge, Doug; Durant, John L.

2017-11-01

Traffic-related ultrafine particles (UFP; <100 nm diameter) are ubiquitous in urban air. While studies have shown that UFP are toxic, epidemiological evidence of health effects, which is needed to inform risk assessment at the population scale, is limited due to challenges of accurately estimating UFP exposures. Epidemiologic studies often use empirical models to estimate UFP exposures; however, the monitoring strategies upon which the models are based have varied between studies. Our study compares particle number concentrations (PNC; a proxy for UFP) measured by three different monitoring approaches (central-site, short-term residential-site, and mobile on-road monitoring) in two study areas in metropolitan Boston (MA, USA). Our objectives were to quantify ambient PNC differences between the three monitoring platforms, compare the temporal patterns and the spatial heterogeneity of PNC between the monitoring platforms, and identify factors that affect correlations across the platforms. We collected >12,000 h of measurements at the central sites, 1000 h of measurements at each of 20 residential sites in the two study areas, and >120 h of mobile measurements over the course of ∼1 year in each study area. Our results show differences between the monitoring strategies: mean 1 min PNC on-roads were higher (64,000 and 32,000 particles/cm3 in Boston and Chelsea, respectively) compared to central-site measurements (23,000 and 19,000 particles/cm3) and both were higher than at residences (14,000 and 15,000 particles/cm3). Temporal correlations and spatial heterogeneity also differed between the platforms. Temporal correlations were generally highest between central and residential sites, and lowest between central-site and on-road measurements. We observed the greatest spatial heterogeneity across monitoring platforms during the morning rush hours (06:00-09:00) and the lowest during the overnight hours (18:00-06:00). Longer averaging times (days and hours vs. minutes) increased temporal correlations (Pearson correlations were 0.69 and 0.60 vs. 0.39 in Boston; 0.71 and 0.61 vs. 0.45 in Chelsea) and reduced spatial heterogeneity (coefficients of divergence were 0.24 and 0.29 vs. 0.33 in Boston; 0.20 and 0.27 vs. 0.31 in Chelsea). Our results suggest that combining stationary and mobile monitoring may lead to improved characterization of UFP in urban areas.

Markov chain formalism for generalized radiative transfer in a plane-parallel medium, accounting for polarization

NASA Astrophysics Data System (ADS)

Xu, Feng; Davis, Anthony B.; Diner, David J.

2016-11-01

A Markov chain formalism is developed for computing the transport of polarized radiation according to Generalized Radiative Transfer (GRT) theory, which was developed recently to account for unresolved random fluctuations of scattering particle density and can also be applied to unresolved spectral variability of gaseous absorption as an improvement over the standard correlated-k method. Using Gamma distribution to describe the probability density function of the extinction or absorption coefficient, a shape parameter a that quantifies the variability is introduced, defined as the mean extinction or absorption coefficient squared divided by its variance. It controls the decay rate of a power-law transmission that replaces the usual exponential Beer-Lambert-Bouguer law. Exponential transmission, hence classic RT, is recovered when a→∞. The new approach is verified to high accuracy against numerical benchmark results obtained with a custom Monte Carlo method. For a<∞, angular reciprocity is violated to a degree that increases with the spatial variability, as observed for finite portions of real-world cloudy scenes. While the degree of linear polarization in liquid water cloudbows, supernumerary bows, and glories is affected by spatial heterogeneity, the positions in scattering angle of these features are relatively unchanged. As a result, a single-scattering model based on the assumption of subpixel homogeneity can still be used to derive droplet size distributions from polarimetric measurements of extended stratocumulus clouds.

Snapping Sharks, Maddening Mindreaders, and Interactive Images: Teaching Correlation.

ERIC Educational Resources Information Center

Mitchell, Mark L.

Understanding correlation coefficients is difficult for students. A free computer program that helps introductory psychology students distinguish between positive and negative correlation, and which also teaches them to understand the differences between correlation coefficients of different size is described in this paper. The program is…

Technical Note: Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: methodology and system evaluation

NASA Astrophysics Data System (ADS)

Kountouris, Panagiotis; Gerbig, Christoph; Rödenbeck, Christian; Karstens, Ute; Koch, Thomas Frank; Heimann, Martin

2018-03-01

Atmospheric inversions are widely used in the optimization of surface carbon fluxes on a regional scale using information from atmospheric CO2 dry mole fractions. In many studies the prior flux uncertainty applied to the inversion schemes does not directly reflect the true flux uncertainties but is used to regularize the inverse problem. Here, we aim to implement an inversion scheme using the Jena inversion system and applying a prior flux error structure derived from a model-data residual analysis using high spatial and temporal resolution over a full year period in the European domain. We analyzed the performance of the inversion system with a synthetic experiment, in which the flux constraint is derived following the same residual analysis but applied to the model-model mismatch. The synthetic study showed a quite good agreement between posterior and true fluxes on European, country, annual and monthly scales. Posterior monthly and country-aggregated fluxes improved their correlation coefficient with the known truth by 7 % compared to the prior estimates when compared to the reference, with a mean correlation of 0.92. The ratio of the SD between the posterior and reference and between the prior and reference was also reduced by 33 % with a mean value of 1.15. We identified temporal and spatial scales on which the inversion system maximizes the derived information; monthly temporal scales at around 200 km spatial resolution seem to maximize the information gain.

Spatiotemporal drivers of dissolved organic matter in high alpine lakes: Role of Saharan dust inputs and bacterial activity.

PubMed

Mladenov, Natalie; Pulido-Villena, Elvira; Morales-Baquero, Rafael; Ortega-Retuerta, Eva; Sommaruga, Ruben; Reche, Isabel

2008-01-01

The effects of many environmental stressors such as UV radiation are mediated by dissolved organic matter (DOM) properties. Therefore, determining the factors shaping spatial and temporal patterns is particularly essential in the most susceptible, low dissolved organic carbon (DOC) lakes. We analyzed spatiotemporal variations in dissolved organic carbon concentration and dissolved organic matter optical properties (absorption and fluorescence) in 11 transparent lakes located above tree line in the Sierra Nevada Mountains (Spain), and we assessed potential external (evaporation and atmospheric deposition) and internal (bacterial abundance, bacterial production, chlorophyll a, and catchment vegetation) drivers of DOM patterns. At spatial and temporal scales, bacteria were related to chromophoric DOM (CDOM). At the temporal scale, water soluble organic carbon (WSOC) in dust deposition and evaporation were found to have a significant influence on DOC and CDOM in two Sierra Nevada lakes studied during the ice-free periods of 2000-2002. DOC concentrations and absorption coefficients at 320 nm were strongly correlated over the spatial scale (n = 11, R(2) = 0.86; p < 0.01), but inconsistently correlated over time, indicating seasonal and interannual variability in external factors and a differential response of DOC concentration and CDOM to these factors. At the continental scale, higher mean DOC concentrations and more CDOM in lakes of the Sierra Nevada than in lakes of the Pyrenees and Alps may be due to a combination of more extreme evaporation, and greater atmospheric dust deposition.

Spatiotemporal drivers of dissolved organic matter in high alpine lakes: Role of Saharan dust inputs and bacterial activity

PubMed Central

Mladenov, Natalie; Pulido-Villena, Elvira; Morales-Baquero, Rafael; Ortega-Retuerta, Eva; Sommaruga, Ruben; Reche, Isabel

2010-01-01

The effects of many environmental stressors such as UV radiation are mediated by dissolved organic matter (DOM) properties. Therefore, determining the factors shaping spatial and temporal patterns is particularly essential in the most susceptible, low dissolved organic carbon (DOC) lakes. We analyzed spatiotemporal variations in dissolved organic carbon concentration and dissolved organic matter optical properties (absorption and fluorescence) in 11 transparent lakes located above tree line in the Sierra Nevada Mountains (Spain), and we assessed potential external (evaporation and atmospheric deposition) and internal (bacterial abundance, bacterial production, chlorophyll a, and catchment vegetation) drivers of DOM patterns. At spatial and temporal scales, bacteria were related to chromophoric DOM (CDOM). At the temporal scale, water soluble organic carbon (WSOC) in dust deposition and evaporation were found to have a significant influence on DOC and CDOM in two Sierra Nevada lakes studied during the ice-free periods of 2000–2002. DOC concentrations and absorption coefficients at 320 nm were strongly correlated over the spatial scale (n = 11, R2 = 0.86; p < 0.01), but inconsistently correlated over time, indicating seasonal and interannual variability in external factors and a differential response of DOC concentration and CDOM to these factors. At the continental scale, higher mean DOC concentrations and more CDOM in lakes of the Sierra Nevada than in lakes of the Pyrenees and Alps may be due to a combination of more extreme evaporation, and greater atmospheric dust deposition. PMID:20582227

Investigation of Influential Factors for Bicycle Crashes Using a Spatiotemporal Model

NASA Astrophysics Data System (ADS)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Despite the numerous potential advantages of indulging in bicycling, such as elevation of health and environment along with mitigation of congestion, the cyclists are a vulnerable group of commuters which is exposed to safety risks. This study aims to investigate the explanatory variables at transportation planning level which have a significant impact on the bicycle crashes. To account for the serial changes around the built environment, the linear time trend as well as time-varying coefficients are utilized for the covariates. These model modifications help account for the variations in the environment which may escape the incorporated variables due to lack of robustness in data. Also, to incorporate the interaction of roadway, demographic, and socioeconomic features within a Traffic Analysis Zone (TAZ), with the bicycle crashes of that area, a spatial correlation is integrated. This spatial correlation accounts for the spatially structured random effects which capture the unobserved heterogeneity and add towards building more comprehensive model with relatively precise estimates. Two different age groups, the student population in the TAZs, the presence of arterial roads and bike lanes, were observed to be statistically significant variables related with bicycle crashes. These observations will guide the transportation planning organizations which focus on the entity of TAZ while developing policies. The results of the current study establish a quantifies relationship between the significant factors and the crash count which will enable the planners to choose the most cost-efficient, yet most productive, factors which needs to be addressed for mitigation of crashes.

Urbanisation and human health in China: spatial features and a systemic perspective.

PubMed

Li, Xinhu; Wang, Cuiping; Zhang, Guoqin; Xiao, Lishan; Dixon, Jane

2012-06-01

Current studies have paid little attention to the dynamism in urban spatial expansion and its possible environmental and health effects or to the health effects of rapid urban environmental change at different points along the urbanisation gradient. This study adopts a public health ecology approach to systematically understand the relationship between urbanisation, urban environmental change and human health in China. Remote sensing image analysis, based on night light data at five different time periods in recent decades, was used to determine changes to the overall urban area. Through a review of the evidence on the relationships between environmental health, urbanisation and health, we advance a pathway framework for explaining urban human health ecology. The Spearman rank correlation coefficient was used to measure the correlation between disease prevalence and urbanisation level, adding a further dimension to a systemic understanding of urban health. Urban areas have been increasing spatially, but unevenly, in recent decades, with medium and small cities also expanding rapidly in the past decade. Urbanisation and urban expansion result in changes to land use/coverage change, the urban environment and the residents' lifestyle, which result in human health problems. Regions with the highest urbanisation level were more inclined to have a high prevalence of chronic disease in recent decades. An ecological public health approach provides insights into the multiple types of data which need to be routinely collected if human disease is not to become a barrier to social and economic development.

40 CFR 53.34 - Test procedure for methods for PM10 and Class I methods for PM2.5.

Code of Federal Regulations, 2011 CFR

2011-07-01

... linear regression parameters (slope, intercept, and correlation coefficient) describing the relationship... correlation coefficient. (2) To pass the test for comparability, the slope, intercept, and correlation...

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Total Water-Vapor Distribution in the Summer Cloudless Atmosphere over the South of Western Siberia

NASA Astrophysics Data System (ADS)

Troshkin, D. N.; Bezuglova, N. N.; Kabanov, M. V.; Pavlov, V. E.; Sokolov, K. I.; Sukovatov, K. Yu.

2017-12-01

The spatial distribution of the total water vapor in different climatic zones of the south of Western Siberia in summer of 2008-2011 is studied on the basis of Envisat data. The correlation analysis of the water-vapor time series from the Envisat data W and radiosonde observations w for the territory of Omsk aerological station show that the absolute values of W and w are linearly correlated with a coefficient of 0.77 (significance level p < 0.05). The distribution functions of the total water vapor are calculated based on the number of its measurements by Envisat for a cloudless sky of three zones with different physical properties of the underlying surface, in particular, steppes to the south of the Vasyugan Swamp and forests to the northeast of the Swamp. The distribution functions are bimodal; each mode follows the lognormal law. The parameters of these functions are given.

Temporal correlation coefficient for directed networks.

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

Previous studies dealing with network theory focused mainly on the static aggregation of edges over specific time window lengths. Thus, most of the dynamic information gets lost. To assess the quality of such a static aggregation the temporal correlation coefficient can be calculated. It measures the overall possibility for an edge to persist between two consecutive snapshots. Up to now, this measure is only defined for undirected networks. Therefore, we introduce the adaption of the temporal correlation coefficient to directed networks. This new methodology enables the distinction between ingoing and outgoing edges. Besides a small example network presenting the single calculation steps, we also calculated the proposed measurements for a real pig trade network to emphasize the importance of considering the edge direction. The farm types at the beginning of the pork supply chain showed clearly higher values for the outgoing temporal correlation coefficient compared to the farm types at the end of the pork supply chain. These farm types showed higher values for the ingoing temporal correlation coefficient. The temporal correlation coefficient is a valuable tool to understand the structural dynamics of these systems, as it assesses the consistency of the edge configuration. The adaption of this measure for directed networks may help to preserve meaningful additional information about the investigated network that might get lost if the edge directions are ignored.

Effective diffusion coefficient including the Marangoni effect

NASA Astrophysics Data System (ADS)

Kitahata, Hiroyuki; Yoshinaga, Natsuhiko

2018-04-01

Surface-active molecules supplied from a particle fixed at the water surface create a spatial gradient of the molecule concentration, resulting in Marangoni convection. Convective flow transports the molecules far from the particle, enhancing diffusion. We analytically derive the effective diffusion coefficient associated with the Marangoni convection rolls. The resulting estimated effective diffusion coefficient is consistent with our numerical results and the apparent diffusion coefficient measured in experiments.

Correlation characteristics of phase and amplitude chimeras in an ensemble of nonlocally coupled maps

NASA Astrophysics Data System (ADS)

Vadivasova, T. E.; Strelkova, G. I.; Bogomolov, S. A.; Anishchenko, V. S.

2017-01-01

Correlation characteristics of chimera states have been calculated using the coefficient of mutual correlation of elements in a closed-ring ensemble of nonlocally coupled chaotic maps. Quantitative differences between the coefficients of mutual correlation for phase and amplitude chimeras are established for the first time.

Comparison of RNFL thickness and RPE-normalized RNFL attenuation coefficient for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Vermeer, K. A.; van der Schoot, J.; Lemij, H. G.; de Boer, J. F.

2013-03-01

Recently, a method to determine the retinal nerve fiber layer (RNFL) attenuation coefficient, based on normalization on the retinal pigment epithelium, was introduced. In contrast to conventional RNFL thickness measures, this novel measure represents a scattering property of the RNFL tissue. In this paper, we compare the RNFL thickness and the RNFL attenuation coefficient on 10 normal and 8 glaucomatous eyes by analyzing the correlation coefficient and the receiver operator curves (ROCs). The thickness and attenuation coefficient showed moderate correlation (r=0.82). Smaller correlation coefficients were found within normal (r=0.55) and glaucomatous (r=0.48) eyes. The full separation between normal and glaucomatous eyes based on the RNFL attenuation coefficient yielded an area under the ROC (AROC) of 1.0. The AROC for the RNFL thickness was 0.9875. No statistically significant difference between the two measures was found by comparing the AROC. RNFL attenuation coefficients may thus replace current RNFL thickness measurements or be combined with it to improve glaucoma diagnosis.

Spatial consistency of Chinook salmon redd distribution within and among years in the Cowlitz River, Washington

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

Klett, Katherine J.; Torgersen, Christian; Henning, Julie

2013-04-28

We investigated the spawning patterns of Chinook salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington (USA) using a unique set of fine- and coarse-scale 35 temporal and spatial data collected during bi-weekly aerial surveys conducted in 1991-2009 (500 m to 28 km resolution) and 2008-2009 (100-500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held global positioning system (GPS) synchronized with in-flight audio recordings. We examined spatial patterns of Chinook salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook salmon spawned in the same sections each yearmore » with little variation among years. On a coarse scale, five years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years resulting in a minimum correlation coefficient of 0.90 (adjusted P = 0.002). Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations (P < 0.001). On a finer temporal scale, we observed that salmon spawned in the same sections during the first and last week (2008: P < 0.02; and 2009: P < 0.001). Redds were clustered in both 2008 and 2009 (P < 0.001). Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook salmon spawning surveys.« less

Spatial and decadal variations in satellite-based terrestrial evapotranspiration and drought over Inner Mongolia Autonomous Region of China during 1982-2009

NASA Astrophysics Data System (ADS)

Zhang, Zhaolu; Kang, Hui; Yao, Yunjun; Fadhil, Ayad M.; Zhang, Yuhu; Jia, Kun

2017-12-01

Evapotranspiration ( ET) plays an important role in exchange of water budget and carbon cycles over the Inner Mongolia autonomous region of China (IMARC). However, the spatial and decadal variations in terrestrial ET and drought over the IMARC in the past was calculated by only using sparse meteorological point-based data which remain quite uncertain. In this study, by combining satellite and meteorology datasets, a satellite-based semi-empirical Penman ET (SEMI-PM) algorithm is used to estimate regional ET and evaporative wet index (EWI) calculated by the ratio of ET and potential ET ( PET) over the IMARC. Validation result shows that the square of the correlation coefficients (R2) for the four sites varies from 0.45 to 0.84 and the root-mean-square error (RMSE) is 0.78 mm. We found that the ET has decreased on an average of 4.8 mm per decade (p=0.10) over the entire IMARC during 1982-2009 and the EWI has decreased on an average of 1.1% per decade (p=0.08) during the study period. Importantly, the patterns of monthly EWI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from 1982 to 2009, indicating EWI can be used to monitor regional surface drought with high spatial resolution. In high-latitude ecosystems of northeast region of the IMARC, both air temperature (Ta) and incident solar radiation (Rs) are the most important parameters in determining ET. However, in semiarid and arid areas of the central and southwest regions of the IMARC, both relative humidity (RH) and normalized difference vegetation index (NDVI) are the most important factors controlling annual variation of ET.

Practical guidance on characterizing availability in resource selection functions under a use-availability design

USGS Publications Warehouse

Northrup, Joseph M.; Hooten, Mevin B.; Anderson, Charles R.; Wittemyer, George

2013-01-01

Habitat selection is a fundamental aspect of animal ecology, the understanding of which is critical to management and conservation. Global positioning system data from animals allow fine-scale assessments of habitat selection and typically are analyzed in a use-availability framework, whereby animal locations are contrasted with random locations (the availability sample). Although most use-availability methods are in fact spatial point process models, they often are fit using logistic regression. This framework offers numerous methodological challenges, for which the literature provides little guidance. Specifically, the size and spatial extent of the availability sample influences coefficient estimates potentially causing interpretational bias. We examined the influence of availability on statistical inference through simulations and analysis of serially correlated mule deer GPS data. Bias in estimates arose from incorrectly assessing and sampling the spatial extent of availability. Spatial autocorrelation in covariates, which is common for landscape characteristics, exacerbated the error in availability sampling leading to increased bias. These results have strong implications for habitat selection analyses using GPS data, which are increasingly prevalent in the literature. We recommend researchers assess the sensitivity of their results to their availability sample and, where bias is likely, take care with interpretations and use cross validation to assess robustness.

Spatial Variability of AERONET Aerosol Optical Properties and Satellite Data in South Korea during NASA DRAGON-Asia Campaign.

PubMed

Lee, Hyung Joo; Son, Youn-Suk

2016-04-05

We investigated spatial variability in aerosol optical properties, including aerosol optical depth (AOD), fine-mode fraction (FMF), and single scattering albedo (SSA), observed at 21 Aerosol Robotic Network (AERONET) sites and satellite remote sensing data in South Korea during the spring of 2012. These dense AERONET networks established in a National Aeronautics and Space Administration (NASA) field campaign enabled us to examine the spatially detailed aerosol size distribution and composition as well as aerosol levels. The springtime particle air quality was characterized by high background aerosol levels and high contributions of coarse-mode aerosols to total aerosols. We found that between-site correlations and coefficient of divergence for AOD and FMF strongly relied on the distance between sites, particularly in the south-north direction. Higher AOD was related to higher population density and lower distance from highways, and the aerosol size distribution and composition reflected source-specific characteristics. The ratios of satellite NO2 to AOD, which indicate the relative contributions of local combustion sources to aerosol levels, represented higher local contributions in metropolitan Seoul and Pusan. Our study demonstrates that the aerosol levels were determined by both local and regional pollution and that the relative contributions of these pollutions to aerosols generated spatial heterogeneity in the particle air quality.

Nanoscale Spatiotemporal Diffusion Modes Measured by Simultaneous Confocal and Stimulated Emission Depletion Nanoscopy Imaging.

PubMed

Schneider, Falk; Waithe, Dominic; Galiani, Silvia; Bernardino de la Serna, Jorge; Sezgin, Erdinc; Eggeling, Christian

2018-06-19

The diffusion dynamics in the cellular plasma membrane provide crucial insights into molecular interactions, organization, and bioactivity. Beam-scanning fluorescence correlation spectroscopy combined with super-resolution stimulated emission depletion nanoscopy (scanning STED-FCS) measures such dynamics with high spatial and temporal resolution. It reveals nanoscale diffusion characteristics by measuring the molecular diffusion in conventional confocal mode and super-resolved STED mode sequentially for each pixel along the scanned line. However, to directly link the spatial and the temporal information, a method that simultaneously measures the diffusion in confocal and STED modes is needed. Here, to overcome this problem, we establish an advanced STED-FCS measurement method, line interleaved excitation scanning STED-FCS (LIESS-FCS), that discloses the molecular diffusion modes at different spatial positions with a single measurement. It relies on fast beam-scanning along a line with alternating laser illumination that yields, for each pixel, the apparent diffusion coefficients for two different observation spot sizes (conventional confocal and super-resolved STED). We demonstrate the potential of the LIESS-FCS approach with simulations and experiments on lipid diffusion in model and live cell plasma membranes. We also apply LIESS-FCS to investigate the spatiotemporal organization of glycosylphosphatidylinositol-anchored proteins in the plasma membrane of live cells, which, interestingly, show multiple diffusion modes at different spatial positions.

Spatial distribution patterns of soil mite communities and their relationships with edaphic factors in a 30-year tillage cornfield in northeast China.

PubMed

Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui

2018-01-01

Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.

The Physical Significance of the Synthetic Running Correlation Coefficient and Its Applications in Oceanic and Atmospheric Studies

NASA Astrophysics Data System (ADS)

Zhao, Jinping; Cao, Yong; Wang, Xin

2018-06-01

In order to study the temporal variations of correlations between two time series, a running correlation coefficient (RCC) could be used. An RCC is calculated for a given time window, and the window is then moved sequentially through time. The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient, calculated with the data within the time window, which we call the local running correlation coefficient (LRCC). The LRCC is calculated via the two anomalies corresponding to the two local means, meanwhile, the local means also vary. It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means. To address this problem, two unchanged means obtained from all available data are adopted to calculate an RCC, which is called the synthetic running correlation coefficient (SRCC). When the anomaly variations are dominant, the two RCCs are similar. However, when the variations of the means are dominant, the difference between the two RCCs becomes obvious. The SRCC reflects the correlations of both the anomaly variations and the variations of the means. Therefore, the SRCCs from different time points are intercomparable. A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data. The SRCC always meets this criterion, while the LRCC sometimes fails. Therefore, the SRCC is better than the LRCC for running correlations. We suggest using the SRCC to calculate the RCCs.

Cross-comparison and evaluation of air pollution field estimation methods

NASA Astrophysics Data System (ADS)

Yu, Haofei; Russell, Armistead; Mulholland, James; Odman, Talat; Hu, Yongtao; Chang, Howard H.; Kumar, Naresh

2018-04-01

Accurate estimates of human exposure is critical for air pollution health studies and a variety of methods are currently being used to assign pollutant concentrations to populations. Results from these methods may differ substantially, which can affect the outcomes of health impact assessments. Here, we applied 14 methods for developing spatiotemporal air pollutant concentration fields of eight pollutants to the Atlanta, Georgia region. These methods include eight methods relying mostly on air quality observations (CM: central monitor; SA: spatial average; IDW: inverse distance weighting; KRIG: kriging; TESS-D: discontinuous tessellation; TESS-NN: natural neighbor tessellation with interpolation; LUR: land use regression; AOD: downscaled satellite-derived aerosol optical depth), one using the RLINE dispersion model, and five methods using a chemical transport model (CMAQ), with and without using observational data to constrain results. The derived fields were evaluated and compared. Overall, all methods generally perform better at urban than rural area, and for secondary than primary pollutants. We found the CM and SA methods may be appropriate only for small domains, and for secondary pollutants, though the SA method lead to large negative spatial correlations when using data withholding for PM2.5 (spatial correlation coefficient R = -0.81). The TESS-D method was found to have major limitations. Results of the IDW, KRIG and TESS-NN methods are similar. They are found to be better suited for secondary pollutants because of their satisfactory temporal performance (e.g. average temporal R2 > 0.85 for PM2.5 but less than 0.35 for primary pollutant NO2). In addition, they are suitable for areas with relatively dense monitoring networks due to their inability to capture spatial concentration variabilities, as indicated by the negative spatial R (lower than -0.2 for PM2.5 when assessed using data withholding). The performance of LUR and AOD methods were similar to kriging. Using RLINE and CMAQ fields without fusing observational data led to substantial errors and biases, though the CMAQ model captured spatial gradients reasonably well (spatial R = 0.45 for PM2.5). Two unique tests conducted here included quantifying autocorrelation of method biases (which can be important in time series analyses) and how well the methods capture the observed interspecies correlations (which would be of particular importance in multipollutant health assessments). Autocorrelation of method biases lasted longest and interspecies correlations of primary pollutants was higher than observations when air quality models were used without data fusing. Use of hybrid methods that combine air quality model outputs with observational data overcome some of these limitations and is better suited for health studies. Results from this study contribute to better understanding the strengths and weaknesses of different methods for estimating human exposures.

Where Does Road Salt Go - a Static Salt Model

NASA Astrophysics Data System (ADS)

Yu, C. W.; Liu, F.; Moriarty, V. W.

2017-12-01

Each winter, more than 15 million tons of road salt is applied in the United States for the de-icing purpose. Considerable amount of chloride in road salt flows into streams/drainage systems with the snow melt runoff and spring storms, and eventually goes into ecologically sensitive low-lying areas in the watershed, such as ponds and lakes. In many watersheds in the northern part of US, the chloride level in the water body has increased significantly in the past decades, and continues an upward trend. The environmental and ecological impact of the elevated chloride level can no longer be ignored. However although there are many studies on the biological impact of elevated chloride levels, there are few investigations on how the spatially distributed road salt application affects various parts of the watershed. In this presentation, we propose a static road salt model as a first-order metric to address spacial distribution of salt loading. Derived from the Topological Wetness Index (TWI) in many hydrological models, this static salt model provides a spatial impact as- sessment of road salt applications. To demonstrate the effectiveness of the static model, National Elevation Dataset (NED) of ten-meter resolution of Lake George watershed in New York State is used to generate the TWI, which is used to compute a spatially dis- tributed "salt-loading coefficient" of the whole watershed. Spatially varying salt applica- tion rate is then aggregated, using the salt-loading coefficients as weights, to provide salt loading assessments of streams in the watershed. Time-aggregated data from five CTD (conductivity-temperature-depth) sensors in selected streams are used for calibration. The model outputs and the sensor data demonstrate a strong linear correlation, with the R value of 0.97. The investigation shows that the static modeling approach may provide an effective method for the understanding the input and transport of road salt to within watersheds.

The importance of regional models in assessing canine cancer incidences in Switzerland

PubMed Central

Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships. PMID:29652921

The importance of regional models in assessing canine cancer incidences in Switzerland.

PubMed

Boo, Gianluca; Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships.

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248

Smoothing effect for spatially distributed renewable resources and its impact on power grid robustness.

PubMed

Nagata, Motoki; Hirata, Yoshito; Fujiwara, Naoya; Tanaka, Gouhei; Suzuki, Hideyuki; Aihara, Kazuyuki

2017-03-01

In this paper, we show that spatial correlation of renewable energy outputs greatly influences the robustness of the power grids against large fluctuations of the effective power. First, we evaluate the spatial correlation among renewable energy outputs. We find that the spatial correlation of renewable energy outputs depends on the locations, while the influence of the spatial correlation of renewable energy outputs on power grids is not well known. Thus, second, by employing the topology of the power grid in eastern Japan, we analyze the robustness of the power grid with spatial correlation of renewable energy outputs. The analysis is performed by using a realistic differential-algebraic equations model. The results show that the spatial correlation of the energy resources strongly degrades the robustness of the power grid. Our results suggest that we should consider the spatial correlation of the renewable energy outputs when estimating the stability of power grids.

Comparison of HSPF and PRMS model simulated flows using different temporal and spatial scales in the Black Hills, South Dakota

USGS Publications Warehouse

Chalise, D. R.; Haj, Adel E.; Fontaine, T.A.

2018-01-01

The hydrological simulation program Fortran (HSPF) [Hydrological Simulation Program Fortran version 12.2 (Computer software). USEPA, Washington, DC] and the precipitation runoff modeling system (PRMS) [Precipitation Runoff Modeling System version 4.0 (Computer software). USGS, Reston, VA] models are semidistributed, deterministic hydrological tools for simulating the impacts of precipitation, land use, and climate on basin hydrology and streamflow. Both models have been applied independently to many watersheds across the United States. This paper reports the statistical results assessing various temporal (daily, monthly, and annual) and spatial (small versus large watershed) scale biases in HSPF and PRMS simulations using two watersheds in the Black Hills, South Dakota. The Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (r">rr), and coefficient of determination (R2">R2R2) statistics for the daily, monthly, and annual flows were used to evaluate the models’ performance. Results from the HSPF models showed that the HSPF consistently simulated the annual flows for both large and small basins better than the monthly and daily flows, and the simulated flows for the small watershed better than flows for the large watershed. In comparison, the PRMS model results show that the PRMS simulated the monthly flows for both the large and small watersheds better than the daily and annual flows, and the range of statistical error in the PRMS models was greater than that in the HSPF models. Moreover, it can be concluded that the statistical error in the HSPF and the PRMSdaily, monthly, and annual flow estimates for watersheds in the Black Hills was influenced by both temporal and spatial scale variability.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

A Robust Post-Processing Workflow for Datasets with Motion Artifacts in Diffusion Kurtosis Imaging

PubMed Central

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

A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging.

PubMed

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.

Pearson's Correlation between Three Variables; Using Students' Basic Knowledge of Geometry for an Exercise in Mathematical Statistics

ERIC Educational Resources Information Center

Vos, Pauline

2009-01-01

When studying correlations, how do the three bivariate correlation coefficients between three variables relate? After transforming Pearson's correlation coefficient r into a Euclidean distance, undergraduate students can tackle this problem using their secondary school knowledge of geometry (Pythagoras' theorem and similarity of triangles).…

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

WE-AB-202-07: Ventilation CT: Voxel-Level Comparison with Hyperpolarized Helium-3 & Xenon-129 MRI

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

Tahir, B; Marshall, H; Hughes, P

Purpose: To compare the spatial correlation of ventilation surrogates computed from inspiratory and expiratory breath-hold CT with hyperpolarized Helium-3 & Xenon-129 MRI in a cohort of lung cancer patients. Methods: 5 patients underwent expiration & inspiration breath-hold CT. Xenon-129 & {sup 1}H MRI were also acquired at the same inflation state as inspiratory CT. This was followed immediately by acquisition of Helium-3 & {sup 1}H MRI in the same breath and at the same inflation state as inspiratory CT. Expiration CT was deformably registered to inspiration CT for calculation of ventilation CT from voxel-wise differences in Hounsfield units. Inspiration CTmore » and the Xenon-129’s corresponding anatomical {sup 1}H MRI were registered to Helium-3 MRI via the same-breath anatomical {sup 1}H MRI. This enabled direct comparison of CT ventilation with Helium-3 MRI & Xenon-129 MRI for the median values in corresponding regions of interest, ranging from finer to coarser in-plane dimensions of 10 by 10, 20 by 20, 30 by 30 and 40 by 40, located within the lungs as defined by the same-breath {sup 1}H MRI lung mask. Spearman coefficients were used to assess voxel-level correlation. Results: The median Spearman’s coefficients of ventilation CT with Helium-3 & Xenon-129 MRI for ROIs of 10 by 10, 20 by 20, 30 by 30 and 40 by 40 were 0.52, 0.56, 0.60 and 0.68 and 0.40, 0.42, 0.52 and 0.70, respectively. Conclusion: This work demonstrates a method of acquiring CT & hyperpolarized gas MRI (Helium-3 & Xenon-129 MRI) in similar breath-holds to enable direct spatial comparison of ventilation maps. Initial results show moderate correlation between ventilation CT & hyperpolarized gas MRI, improving for coarser regions which could be attributable to the inherent noise in CT intensity, non-ventilatory effects and registration errors at the voxel-level. Thus, it may be more beneficial to quantify ventilation at a more regional level.« less

Quantitative 3D Ultrashort Time-to-Echo (UTE) MRI and Micro-CT (μCT) Evaluation of the Temporomandibular Joint (TMJ) Condylar Morphology

PubMed Central

Geiger, Daniel; Bae, Won C.; Statum, Sheronda; Du, Jiang; Chung, Christine B.

2014-01-01

Objective Temporomandibular dysfunction involves osteoarthritis of the TMJ, including degeneration and morphologic changes of the mandibular condyle. Purpose of this study was to determine accuracy of novel 3D-UTE MRI versus micro-CT (μCT) for quantitative evaluation of mandibular condyle morphology. Material & Methods Nine TMJ condyle specimens were harvested from cadavers (2M, 3F; Age 85 ± 10 yrs., mean±SD). 3D-UTE MRI (TR=50ms, TE=0.05 ms, 104 μm isotropic-voxel) was performed using a 3-T MR scanner and μCT (18 μm isotropic-voxel) was performed. MR datasets were spatially-registered with μCT dataset. Two observers segmented bony contours of the condyles. Fibrocartilage was segmented on MR dataset. Using a custom program, bone and fibrocartilage surface coordinates, Gaussian curvature, volume of segmented regions and fibrocartilage thickness were determined for quantitative evaluation of joint morphology. Agreement between techniques (MRI vs. μCT) and observers (MRI vs. MRI) for Gaussian curvature, mean curvature and segmented volume of the bone were determined using intraclass correlation correlation (ICC) analyses. Results Between MRI and μCT, the average deviation of surface coordinates was 0.19±0.15 mm, slightly higher than spatial resolution of MRI. Average deviation of the Gaussian curvature and volume of segmented regions, from MRI to μCT, was 5.7±6.5% and 6.6±6.2%, respectively. ICC coefficients (MRI vs. μCT) for Gaussian curvature, mean curvature and segmented volumes were respectively 0.892, 0.893 and 0.972. Between observers (MRI vs. MRI), the ICC coefficients were 0.998, 0.999 and 0.997 respectively. Fibrocartilage thickness was 0.55±0.11 mm, as previously described in literature for grossly normal TMJ samples. Conclusion 3D-UTE MR quantitative evaluation of TMJ condyle morphology ex-vivo, including surface, curvature and segmented volume, shows high correlation against μCT and between observers. In addition, UTE MRI allows quantitative evaluation of the fibrocartilaginous condylar component. PMID:24092237

A Generalized Framework for Reduced-Order Modeling of a Wind Turbine Wake

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

Hamilton, Nicholas; Viggiano, Bianca; Calaf, Marc

A reduced-order model for a wind turbine wake is sought from large eddy simulation data. Fluctuating velocity fields are combined in the correlation tensor to form the kernel of the proper orthogonal decomposition (POD). Proper orthogonal decomposition modes resulting from the decomposition represent the spatially coherent turbulence structures in the wind turbine wake; eigenvalues delineate the relative amount of turbulent kinetic energy associated with each mode. Back-projecting the POD modes onto the velocity snapshots produces dynamic coefficients that express the amplitude of each mode in time. A reduced-order model of the wind turbine wake (wakeROM) is defined through a seriesmore » of polynomial parameters that quantify mode interaction and the evolution of each POD mode coefficients. The resulting system of ordinary differential equations models the wind turbine wake composed only of the large-scale turbulent dynamics identified by the POD. Tikhonov regularization is used to recalibrate the dynamical system by adding additional constraints to the minimization seeking polynomial parameters, reducing error in the modeled mode coefficients. The wakeROM is periodically reinitialized with new initial conditions found by relating the incoming turbulent velocity to the POD mode coefficients through a series of open-loop transfer functions. The wakeROM reproduces mode coefficients to within 25.2%, quantified through the normalized root-mean-square error. A high-level view of the modeling approach is provided as a platform to discuss promising research directions, alternate processes that could benefit stability and efficiency, and desired extensions of the wakeROM.« less

Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

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

Pino, Francisco; Roé, Nuria; Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es

2015-02-15

Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Threemore » methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery coefficients in the reconstructed images. To avoid the appearance of ring-type artifacts, the number of iterations should be limited. In low magnification systems, the intrinsic detector PSF plays a major role in improvement of the image-quality parameters.« less

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

PubMed

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Measurement of carbon nanotube microstructure relative density by optical attenuation and observation of size-dependent variations.

PubMed

Park, Sei Jin; Schmidt, Aaron J; Bedewy, Mostafa; Hart, A John

2013-07-21

Engineering the density of carbon nanotube (CNT) forest microstructures is vital to applications such as electrical interconnects, micro-contact probes, and thermal interface materials. For CNT forests on centimeter-scale substrates, weight and volume can be used to calculate density. However, this is not suitable for smaller samples, including individual microstructures, and moreover does not enable mapping of spatial density variations within the forest. We demonstrate that the relative mass density of individual CNT microstructures can be measured by optical attenuation, with spatial resolution equaling the size of the focused spot. For this, a custom optical setup was built to measure the transmission of a focused laser beam through CNT microstructures. The transmittance was correlated with the thickness of the CNT microstructures by Beer-Lambert-Bouguer law to calculate the attenuation coefficient. We reveal that the density of CNT microstructures grown by CVD can depend on their size, and that the overall density of arrays of microstructures is affected significantly by run-to-run process variations. Further, we use the technique to quantify the change in CNT microstructure density due to capillary densification. This is a useful and accessible metrology technique for CNTs in future microfabrication processes, and will enable direct correlation of density to important properties such as stiffness and electrical conductivity.

Linking the soil moisture distribution pattern to dynamic processes along slope transects in the Loess Plateau, China.

PubMed

Wang, Shuai; Fu, Bojie; Gao, Guangyao; Zhou, Ji; Jiao, Lei; Liu, Jianbo

2015-12-01

Soil moisture pulses are a prerequisite for other land surface pulses at various spatiotemporal scales in arid and semi-arid areas. The temporal dynamics and profile variability of soil moisture in relation to land cover combinations were studied along five slopes transect on the Loess Plateau during the rainy season of 2011. Within the 3 months of the growing season coupled with the rainy season, all of the soil moisture was replenished in the area, proving that a type stability exists between different land cover soil moisture levels. Land cover combinations disturbed the trend determined by topography and increased soil moisture variability in space and time. The stability of soil moisture resulting from the dynamic processes could produce stable patterns on the slopes. The relationships between the mean soil moisture and vertical standard deviation (SD) and coefficient of variation (CV) were more complex, largely due to the fact that different land cover types had distinctive vertical patterns of soil moisture. The spatial SD of each layer had a positive correlation and the spatial CV exhibited a negative correlation with the increase in mean soil moisture. The soil moisture stability implies that sampling comparisons in this area can be conducted at different times to accurately compare different land use types.

Global Terrestrial Water Storage Changes and Connections to ENSO Events

NASA Astrophysics Data System (ADS)

Ni, Shengnan; Chen, Jianli; Wilson, Clark R.; Li, Jin; Hu, Xiaogong; Fu, Rong

2018-01-01

Improved data quality of extended record of the Gravity Recovery and Climate Experiment (GRACE) satellite gravity solutions enables better understanding of terrestrial water storage (TWS) variations. Connections of TWS and climate change are critical to investigate regional and global water cycles. In this study, we provide a comprehensive analysis of global connections between interannual TWS changes and El Niño Southern Oscillation (ENSO) events, using multiple sources of data, including GRACE measurements, land surface model (LSM) predictions and precipitation observations. We use cross-correlation and coherence spectrum analysis to examine global connections between interannual TWS changes and the Niño 3.4 index, and select four river basins (Amazon, Orinoco, Colorado, and Lena) for more detailed analysis. The results indicate that interannual TWS changes are strongly correlated with ENSO over much of the globe, with maximum cross-correlation coefficients up to 0.70, well above the 95% significance level ( 0.29) derived by the Monte Carlo experiments. The strongest correlations are found in tropical and subtropical regions, especially in the Amazon, Orinoco, and La Plata basins. While both GRACE and LSM TWS estimates show reasonably good correlations with ENSO and generally consistent spatial correlation patterns, notably higher correlations are found between GRACE TWS and ENSO. The existence of significant correlations in middle-high latitudes shows the large-scale impact of ENSO on the global water cycle.

Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

PubMed

Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J

2010-07-27

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.

Polygenic variation maintained by balancing selection: pleiotropy, sex-dependent allelic effects and G x E interactions.

PubMed Central

Turelli, Michael; Barton, N H

2004-01-01

We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G x E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G x E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., rho(ij)2>3/4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms. PMID:15020487

Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

DOE PAGES

Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

2015-04-01

The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu 40Zr 51Al 9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T x ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T m ~ 900K),more » and the crossover temperature is roughly twice of the glass-transition temperature (T g). Below T x, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T x and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

Correlation Between Geometric Similarity of Ice Shapes and the Resulting Aerodynamic Performance Degradation: A Preliminary Investigation Using WIND

NASA Technical Reports Server (NTRS)

Wright, William B.; Chung, James

1999-01-01

Aerodynamic performance calculations were performed using WIND on ten experimental ice shapes and the corresponding ten ice shapes predicted by LEWICE 2.0. The resulting data for lift coefficient and drag coefficient are presented. The difference in aerodynamic results between the experimental ice shapes and the LEWICE ice shapes were compared to the quantitative difference in ice shape geometry presented in an earlier report. Correlations were generated to determine the geometric features which have the most effect on performance degradation. Results show that maximum lift and stall angle can be correlated to the upper horn angle and the leading edge minimum thickness. Drag coefficient can be correlated to the upper horn angle and the frequency-weighted average of the Fourier coefficients. Pitching moment correlated with the upper horn angle and to a much lesser extent to the upper and lower horn thicknesses.

Spatial-Temporal Heterogeneity in Regional Watershed Phosphorus Cycles Driven by Changes in Human Activity over the Past Century

NASA Astrophysics Data System (ADS)

Hale, R. L.; Grimm, N. B.; Vorosmarty, C. J.

2014-12-01

An ongoing challenge for society is to harness the benefits of phosphorus (P) while minimizing negative effects on downstream ecosystems. To meet this challenge we must understand the controls on the delivery of anthropogenic P from landscapes to downstream ecosystems. We used a model that incorporates P inputs to watersheds, hydrology, and infrastructure (sewers, waste-water treatment plants, and reservoirs) to reconstruct historic P yields for the northeastern U.S. from 1930 to 2002. At the regional scale, increases in P inputs were paralleled by increased fractional retention, thus P loading to the coast did not increase significantly. We found that temporal variation in regional P yield was correlated with P inputs. Spatial patterns of watershed P yields were best predicted by inputs, but the correlation between inputs and yields in space weakened over time, due to infrastructure development. Although the magnitude of infrastructure effect was small, its role changed over time and was important in creating spatial and temporal heterogeneity in input-yield relationships. We then conducted a hierarchical cluster analysis to identify a typology of anthropogenic P cycling, using data on P inputs (fertilizer, livestock feed, and human food), infrastructure (dams, wastewater treatment plants, sewers), and hydrology (runoff coefficient). We identified 6 key types of watersheds that varied significantly in climate, infrastructure, and the types and amounts of P inputs. Annual watershed P yields and retention varied significantly across watershed types. Although land cover varied significantly across typologies, clusters based on land cover alone did not explain P budget patterns, suggesting that this variable is insufficient to understand patterns of P cycling across large spatial scales. Furthermore, clusters varied over time as patterns of climate, P use, and infrastructure changed. Our results demonstrate that the drivers of P cycles are spatially and temporally heterogeneous, yet they also suggest that a relatively simple typology of watersheds can be useful for understanding regional P cycles and may help inform P management approaches.

Confidence Intervals and "F" Tests for Intraclass Correlation Coefficients Based on Three-Way Mixed Effects Models

ERIC Educational Resources Information Center

Zhou, Hong; Muellerleile, Paige; Ingram, Debra; Wong, Seok P.

2011-01-01

Intraclass correlation coefficients (ICCs) are commonly used in behavioral measurement and psychometrics when a researcher is interested in the relationship among variables of a common class. The formulas for deriving ICCs, or generalizability coefficients, vary depending on which models are specified. This article gives the equations for…

Photo-induced Mass Transport through Polymer Networks

NASA Astrophysics Data System (ADS)

Meng, Yuan; Anthamatten, Mitchell

2014-03-01

Among adaptable materials, photo-responsive polymers are especially attractive as they allow for spatiotemporal stimuli and response. We have recently developed a macromolecular network capable of photo-induced mass transport of covalently bound species. The system comprises of crosslinked chains that form an elastic network and photosensitive fluorescent arms that become mobile upon irradiation. We form loosely crosslinked polymer networks by Michael-Addition between multifunctional thiols and small molecule containing acrylate end-groups. The arms are connected to the network by allyl sulfide, that undergoes addition-fragmentation chain transfer (AFCT) in the presence of free radicals, releasing diffusible fluorophore. The networks are loaded with photoinitiator to allow for spatial modulation of the AFCT reactions. FRAP experiments within bulk elastomers are conducted to establish correlations between the fluorophore's diffusion coefficient and experimental variables such as network architecture, temperature and UV intensity. Photo-induced mass transport between two contacted films is demonstrated, and release of fluorophore into a solvent is investigated. Spatial and temporal control of mass transport could benefit drug release, printing, and sensing applications.

An approach for mapping large-area impervious surfaces: Synergistic use of Landsat-7 ETM+ and high spatial resolution imagery

USGS Publications Warehouse

Yang, Limin; Huang, Chengquan; Homer, Collin G.; Wylie, Bruce K.; Coan, Michael

2003-01-01

A wide range of urban ecosystem studies, including urban hydrology, urban climate, land use planning, and resource management, require current and accurate geospatial data of urban impervious surfaces. We developed an approach to quantify urban impervious surfaces as a continuous variable by using multisensor and multisource datasets. Subpixel percent impervious surfaces at 30-m resolution were mapped using a regression tree model. The utility, practicality, and affordability of the proposed method for large-area imperviousness mapping were tested over three spatial scales (Sioux Falls, South Dakota, Richmond, Virginia, and the Chesapeake Bay areas of the United States). Average error of predicted versus actual percent impervious surface ranged from 8.8 to 11.4%, with correlation coefficients from 0.82 to 0.91. The approach is being implemented to map impervious surfaces for the entire United States as one of the major components of the circa 2000 national land cover database.

Antibiotics in the coastal environment of the Hailing Bay region, South China Sea: Spatial distribution, source analysis and ecological risks.

PubMed

Chen, Hui; Liu, Shan; Xu, Xiang-Rong; Zhou, Guang-Jie; Liu, Shuang-Shuang; Yue, Wei-Zhong; Sun, Kai-Feng; Ying, Guang-Guo

2015-06-15

In this study, the occurrence and spatial distribution of 38 antibiotics in surface water and sediment samples of the Hailing Bay region, South China Sea, were investigated. Twenty-one, 16 and 15 of 38 antibiotics were detected with the concentrations ranging from <0.08 (clarithromycin) to 15,163ng/L (oxytetracycline), 2.12 (methacycline) to 1318ng/L (erythromycin-H2O), <1.95 (ciprofloxacin) to 184ng/g (chlortetracycline) in the seawater, discharged effluent and sediment samples, respectively. The concentrations of antibiotics in the water phase were correlated positively with chemical oxygen demand and nitrate. The source analysis indicated that untreated domestic sewage was the primary source of antibiotics in the study region. Fluoroquinolones showed strong sorption capacity onto sediments due to their high pseudo-partitioning coefficients. Risk assessment indicated that oxytetracycline, norfloxacin and erythromycin-H2O posed high risks to aquatic organisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

NASA Astrophysics Data System (ADS)

Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán

2014-11-01

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.

Noise assisted pattern fabrication

NASA Astrophysics Data System (ADS)

Roy, Tanushree; Agarwal, V.; Singh, B. P.; Parmananda, P.

2018-04-01

Pre-selected patterns on an n-type Si surface are fabricated by electrochemical etching in the presence of a weak optical signal. The constructive role of noise, namely, stochastic resonance (SR), is exploited for these purposes. SR is a nonlinear phenomenon wherein at an optimal amplitude of noise, the information transfer from weak input sub-threshold signals to the system output is maximal. In the present work, the amplitude of internal noise was systematically regulated by varying the molar concentration of hydrofluoric acid (HF) in the electrolyte. Pattern formation on the substrate for two different amplitudes (25 ± 2 and 11 ± 1 mW) of the optical template (sub-threshold signal) was considered. To quantify the fidelity/quality of pattern formation, the spatial cross-correlation coefficient (CCC) between the constructed pattern and the template of the applied signal was calculated. The maximum CCC is obtained for the pattern formed at an optimal HF concentration, indicating SR. Simulations, albeit using external noise, on a spatial array of coupled FitzHugh-Nagumo oscillators revealed similar results.

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

NASA Technical Reports Server (NTRS)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

Family Reintegration Experiences of Soldiers with Mild Traumatic Brain Injury

DTIC Science & Technology

2014-02-26

depression scores in the spouse. Weak within-couple correlation were indicated on the other measures. Table 3 presents the Spearman correlation matrix...separately. Table 2: Spearman Correlation Coefficients for Couples Spouse MAT Spouse Depression Spouse...Anxiety Soldier MAT -0.06 Soldier Depression -0.61 Soldier Anxiety -0.12 Table 3: Spearman Correlation Coefficients for Soldiers and

Applying complex networks to evaluate precipitation patterns over South America

NASA Astrophysics Data System (ADS)

Ciemer, Catrin; Boers, Niklas; Barbosa, Henrique; Kurths, Jürgen; Rammig, Anja

2016-04-01

The climate of South America exhibits pronounced differences between the wet- and the dry-season, which are accompanied by specific synoptic events like changes in the location of the South American Low Level Jet (SALLJ) and the establishment of the South American Convergence Zone (SACZ). The onset of these events can be related to the presence of typical large-scale precipitation patterns over South America, as previous studies have shown[1,2]. The application of complex network methods to precipitation data recently received increased scientific attention for the special case of extreme events, as it is possible with such methods to analyze the spatiotemporal correlation structure as well as possible teleconnections of these events[3,4]. In these approaches the correlation between precipitation datasets is calculated by means of Event Synchronization which restricts their applicability to extreme precipitation events. In this work, we propose a method which is able to consider not only extreme precipitation but complete time series. A direct application of standard similarity measures in order to correlate precipitation time series is impossible due to their intricate statistical properties as the large amount of zeros. Therefore, we introduced and evaluated a suitable modification of Pearson's correlation coefficient to construct spatial correlation networks of precipitation. By analyzing the characteristics of spatial correlation networks constructed on the basis of this new measure, we are able to determine coherent areas of similar precipitation patterns, spot teleconnections of correlated areas, and detect central regions for precipitation correlation. By analyzing the change of the network over the year[5], we are also able to determine local and global changes in precipitation correlation patterns. Additionally, global network characteristics as the network connectivity yield indications for beginning and end of wet- and dry season. In order to identify large-scale synoptic events like the SACZ and SALLJ onset, detecting the changes of correlation over time between certain regions is of significant relevance. [1] Nieto-Ferreira et al. Quarterly Journal of the Royal Meteorological Society (2011) [2] Vera et al. Bulletin of the American Meteorological Society (2006) [3] Quiroga et al. Physical review E (2002) [4] Boers et al. nature communications (2014) [5] Radebach et al. Physical review E (2013)

Correlation tests of the engine performance parameter by using the detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Gao, You; Jing, Liming

2015-02-01

The presence of cross-correlation in complex systems has long been noted and studied in a broad range of physical applications. We here focus on an aero-engine system as an example of a complex system. By applying the detrended cross-correlation (DCCA) coefficient method to aero-engine time series, we investigate the effects of the data length and the time scale on the detrended cross-correlation coefficients ρ DCCA ( T, s). We then show, for a twin-engine aircraft, that the engine fuel flow time series derived from the left engine and the right engine exhibit much stronger cross-correlations than the engine exhaust-gas temperature series derived from the left engine and the right engine do.

Multiple paternity and sporophytic inbreeding depression in a dioicous moss species.

PubMed

Szövényi, P; Ricca, M; Shaw, A J

2009-11-01

Multiple paternity (polyandry) frequently occurs in flowering plants and animals and is assumed to have an important function in the evolution of reproductive traits. Polyandry in bryophytes may occur among multiple sporophytes of a female gametophyte; however, its occurrence and extent is unknown. In this study we investigate the occurrence and extent of multiple paternity, spatial genetic structure, and sporophytic inbreeding depression in natural populations of a dioicous bryophyte species, Sphagnum lescurii, using microsatellite markers. Multiple paternity is prevalent among sporophytes of a female gametophyte and male genotypes exhibit significant skew in paternity. Despite significant spatial genetic structure in the population, suggesting frequent inbreeding, the number of inbred and outbred sporophytes was balanced, resulting in an average fixation coefficient and population level selfing rate of zero. In line with the prediction of sporophytic inbreeding depression sporophyte size was significantly correlated with the level of heterozygosity. Furthermore, female gametophytes preferentially supported sporophytes with higher heterozygosity. These results indicate that polyandry provides the opportunity for postfertilization selection in bryophytes having short fertilization distances and spatially structured populations facilitating inbreeding. Preferential maternal support of the more heterozygous sporophytes suggests active inbreeding avoidance that may have significant implications for mating system evolution in bryophytes.

Roles of climate, vegetation and soil in regulating the spatial variations in ecosystem carbon dioxide fluxes in the Northern Hemisphere.

PubMed

Chen, Zhi; Yu, Guirui; Ge, Jianping; Wang, Qiufeng; Zhu, Xianjin; Xu, Zhiwei

2015-01-01

Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60% and 58% of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45-47% of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75%. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary.

Roles of Climate, Vegetation and Soil in Regulating the Spatial Variations in Ecosystem Carbon Dioxide Fluxes in the Northern Hemisphere

PubMed Central

Chen, Zhi; Yu, Guirui; Ge, Jianping; Wang, Qiufeng; Zhu, Xianjin; Xu, Zhiwei

2015-01-01

Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60 % and 58 % of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45 - 47 % of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75 %. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary. PMID:25928452

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

A Practical Theory of Micro-Solar Power Sensor Networks

DTIC Science & Technology

2009-04-20

Simulation Platform TOSSIM [LLWC03] ns-2 Matlab C++ AVRORA [TLP05] Reference Hardware Mica2 WINS, Medusa Mica Mica2, Medusa Mica2 Simulated Power Power...scale. From this raw data, we can 162 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 2 4 Correlation coefficient F re qu en cy Histogram of correlation...0.5 0.6 0.7 0.8 0.9 1 0 1 2 Correlation coefficient F re qu en cy Histogram of correlation coefficient with solar radiation measurement (Turbidity at

Quasi-Likelihood Techniques in a Logistic Regression Equation for Identifying Simulium damnosum s.l. Larval Habitats Intra-cluster Covariates in Togo.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R

2012-01-01

The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.

Functional CAR models for large spatially correlated functional datasets.

PubMed

Zhang, Lin; Baladandayuthapani, Veerabhadran; Zhu, Hongxiao; Baggerly, Keith A; Majewski, Tadeusz; Czerniak, Bogdan A; Morris, Jeffrey S

2016-01-01

We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on functions defined on higher dimensional domains such as images. Through simulation studies, we demonstrate that accounting for the spatial correlation in our modeling leads to improved functional regression performance. Applied to a high-throughput spatially correlated copy number dataset, the model identifies genetic markers not identified by comparable methods that ignore spatial correlations.

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Lipschitz stability for an inverse hyperbolic problem of determining two coefficients by a finite number of observations

NASA Astrophysics Data System (ADS)

Beilina, L.; Cristofol, M.; Li, S.; Yamamoto, M.

2018-01-01

We consider an inverse problem of reconstructing two spatially varying coefficients in an acoustic equation of hyperbolic type using interior data of solutions with suitable choices of initial condition. Using a Carleman estimate, we prove Lipschitz stability estimates which ensure unique reconstruction of both coefficients. Our theoretical results are justified by numerical studies on the reconstruction of two unknown coefficients using noisy backscattered data.

Repeatability of chemical-shift-encoded water-fat MRI and diffusion-tensor imaging in lower extremity muscles in children.

PubMed

Ponrartana, Skorn; Andrade, Kristine E; Wren, Tishya A L; Ramos-Platt, Leigh; Hu, Houchun H; Bluml, Stefan; Gilsanz, Vicente

2014-06-01

The purpose of this study was to assess the repeatability of water-fat MRI and diffusion-tensor imaging (DTI) as quantitative biomarkers of pediatric lower extremity skeletal muscle. MRI at 3 T of a randomly selected thigh and lower leg of seven healthy children was studied using water-fat separation and DTI techniques. Muscle-fat fraction, apparent diffusion coefficient (ADC), and fractional anisotropy (FA) values were calculated. Test-retest and interrater repeatability were assessed by calculating the Pearson correlation coefficient, intraclass correlation coefficient, and Bland-Altman analysis. Bland-Altman plots show that the mean difference between test-retest and interrater measurements of muscle-fat fraction, ADC, and FA was near 0. The correlation coefficients and intraclass correlation coefficients were all between 0.88 and 0.99 (p < 0.05), suggesting excellent reliability of the measurements. Muscle-fat fraction measurements from water-fat MRI exhibited the highest intraclass correlation coefficient. Interrater agreement was consistently better than test-retest comparisons. Water-fat MRI and DTI measurements in lower extremity skeletal muscles are objective repeatable biomarkers in children. This knowledge should aid in the understanding of the number of participants needed in clinical trials when using these determinations as an outcome measure to noninvasively monitor neuromuscular disease.

Regional vulnerability of longitudinal cortical association connectivity: Associated with structural network topology alterations in preterm children with cerebral palsy.

PubMed

Ceschin, Rafael; Lee, Vince K; Schmithorst, Vince; Panigrahy, Ashok

2015-01-01

Preterm born children with spastic diplegia type of cerebral palsy and white matter injury or periventricular leukomalacia (PVL), are known to have motor, visual and cognitive impairments. Most diffusion tensor imaging (DTI) studies performed in this group have demonstrated widespread abnormalities using averaged deterministic tractography and voxel-based DTI measurements. Little is known about structural network correlates of white matter topography and reorganization in preterm cerebral palsy, despite the availability of new therapies and the need for brain imaging biomarkers. Here, we combined novel post-processing methodology of probabilistic tractography data in this preterm cohort to improve spatial and regional delineation of longitudinal cortical association tract abnormalities using an along-tract approach, and compared these data to structural DTI cortical network topology analysis. DTI images were acquired on 16 preterm children with cerebral palsy (mean age 5.6 ± 4) and 75 healthy controls (mean age 5.7 ± 3.4). Despite mean tract analysis, Tract-Based Spatial Statistics (TBSS) and voxel-based morphometry (VBM) demonstrating diffusely reduced fractional anisotropy (FA) reduction in all white matter tracts, the along-tract analysis improved the detection of regional tract vulnerability. The along-tract map-structural network topology correlates revealed two associations: (1) reduced regional posterior-anterior gradient in FA of the longitudinal visual cortical association tracts (inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiation, posterior thalamic radiation) correlated with reduced posterior-anterior gradient of intra-regional (nodal efficiency) metrics with relative sparing of frontal and temporal regions; and (2) reduced regional FA within frontal-thalamic-striatal white matter pathways (anterior limb/anterior thalamic radiation, superior longitudinal fasciculus and cortical spinal tract) correlated with alteration in eigenvector centrality, clustering coefficient (inter-regional) and participation co-efficient (inter-modular) alterations of frontal-striatal and fronto-limbic nodes suggesting re-organization of these pathways. Both along tract and structural topology network measurements correlated strongly with motor and visual clinical outcome scores. This study shows the value of combining along-tract analysis and structural network topology in depicting not only selective parietal occipital regional vulnerability but also reorganization of frontal-striatal and frontal-limbic pathways in preterm children with cerebral palsy. These finding also support the concept that widespread, but selective posterior-anterior neural network connectivity alterations in preterm children with cerebral palsy likely contribute to the pathogenesis of neurosensory and cognitive impairment in this group.

Joint transform correlators with spatially incoherent illumination

NASA Astrophysics Data System (ADS)

Bykovsky, Yuri A.; Karpiouk, Andrey B.; Markilov, Anatoly A.; Rodin, Vladislav G.; Starikov, Sergey N.

1997-03-01

Two variants of joint transform correlators with monochromatic spatially incoherent illumination are considered. The Fourier-holograms of the reference and recognized images are recorded simultaneously or apart in a time on the same spatial light modulator directly by monochromatic spatially incoherent light. To create the signal of mutual correlation of the images it is necessary to execute nonlinear transformation when the hologram is illuminated by coherent light. In the first scheme of the correlator this aim was achieved by using double pas of a restoring coherent wave through the hologram. In the second variant of the correlator the non-linearity of the characteristic of the spatial light modulator for hologram recording was used. Experimental schemes and results on processing teste images by both variants of joint transform correlators with monochromatic spatially incoherent illumination. The use of spatially incoherent light on the input of joint transform correlators permits to reduce the requirements to optical quality of elements, to reduce accuracy requirements on elements positioning and to expand a number of devices suitable to input images in correlators.

Observations of copolar correlation coefficient through a bright band at vertical incidence

NASA Technical Reports Server (NTRS)

Zrnic, D. S.; Raghavan, R.; Chandrasekar, V.

1994-01-01

This paper discusses an application of polarimetric measurements at vertical incidence. In particular, the correlation coefficients between linear copolar components are examined, and measurements obtained with the National Severe Storms Laboratory (NSSL)'s and National Center for Atmospheric Research (NCAR)'s polarimetric radars are presented. The data are from two well-defined bright bands. A sharp decrease of the correlation coefficient, confined to a height interval of a few hundred meters, marks the bottom of the bright band.

Properties of a new small-world network with spatially biased random shortcuts

NASA Astrophysics Data System (ADS)

Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko

2017-11-01

This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.

Relationship of body mass index to percent body fat and waist circumference among schoolchildren in Japan--the influence of gender and obesity: a population-based cross-sectional study.

PubMed

Ochiai, Hirotaka; Shirasawa, Takako; Nishimura, Rimei; Morimoto, Aya; Shimada, Naoki; Ohtsu, Tadahiro; Kujirai, Emiko; Hoshino, Hiromi; Tajima, Naoko; Kokaze, Akatsuki

2010-08-18

Although the correlation coefficient between body mass index (BMI) and percent body fat (%BF) or waist circumference (WC) has been reported, studies conducted among population-based schoolchildren to date have been limited in Japan, where %BF and WC are not usually measured in annual health examinations at elementary schools or junior high schools. The aim of the present study was to investigate the relationship of BMI to %BF and WC and to examine the influence of gender and obesity on these relationships among Japanese schoolchildren. Subjects included 3,750 schoolchildren from the fourth and seventh grade in Ina-town, Saitama Prefecture, Japan between 2004 and 2008. Information about subject's age, sex, height, weight, %BF, and WC was collected from annual physical examinations. %BF was measured with a bipedal biometrical impedance analysis device. Obesity was defined by the following two criteria: the obese definition of the Centers for Disease Control and Prevention, and the definition of obesity for Japanese children. Pearson's correlation coefficients between BMI and %BF or WC were calculated separately for sex. Among fourth graders, the correlation coefficients between BMI and %BF were 0.74 for boys and 0.97 for girls, whereas those between BMI and WC were 0.94 for boys and 0.90 for girls. Similar results were observed in the analysis of seventh graders. The correlation coefficient between BMI and %BF varied by physique (obese or non-obese), with weaker correlations among the obese regardless of the definition of obesity; most correlation coefficients among obese boys were less than 0.5, whereas most correlations among obese girls were more than 0.7. On the other hand, the correlation coefficients between BMI and WC were more than 0.8 among boys and almost all coefficients were more than 0.7 among girls, regardless of physique. BMI was positively correlated with %BF and WC among Japanese schoolchildren. The correlations could be influenced by obesity as well as by gender. Accordingly, it is essential to consider gender and obesity when using BMI as a surrogate for %BF and WC for epidemiological use.

Hyperspectral imaging-based spatially-resolved technique for accurate measurement of the optical properties of horticultural products

NASA Astrophysics Data System (ADS)

Cen, Haiyan

Hyperspectral imaging-based spatially-resolved technique is promising for determining the optical properties and quality attributes of horticultural and food products. However, considerable challenges still exist for accurate determination of spectral absorption and scattering properties from intact horticultural products. The objective of this research was, therefore, to develop and optimize hyperspectral imaging-based spatially-resolved technique for accurate measurement of the optical properties of horticultural products. Monte Carlo simulations and experiments for model samples of known optical properties were performed to optimize the inverse algorithm of a single-layer diffusion model and the optical designs, for extracting the absorption (micro a) and reduced scattering (micros') coefficients from spatially-resolved reflectance profiles. The logarithm and integral data transformation and the relative weighting methods were found to greatly improve the parameter estimation accuracy with the relative errors of 10.4%, 10.7%, and 11.4% for micro a, and 6.6%, 7.0%, and 7.1% for micros', respectively. More accurate measurements of optical properties were obtained when the light beam was of Gaussian type with the diameter of less than 1 mm, and the minimum and maximum source-detector distances were 1.5 mm and 10--20 transport mean free paths, respectively. An optical property measuring prototype was built, based on the optimization results, and evaluated for automatic measurement of absorption and reduced scattering coefficients for the wavelengths of 500--1,000 nm. The instrument was used to measure the optical properties, and assess quality/maturity, of 500 'Redstar' peaches and 1039 'Golden Delicious' (GD) and 1040 'Delicious' (RD) apples. A separate study was also conducted on confocal laser scanning and scanning electron microscopic image analysis and compression test of fruit tissue specimens to measure the structural and mechanical properties of 'Golden Delicious' and 'Granny Smith' (GS) apples under accelerated softening at high temperature (22 ºC)/high humidity (95%) for up to 30 days. The absorption spectra of peach and apple fruit were featured with the absorption peaks of major pigments (i.e., chlorophylls and anthocyanin) and water, while the reduced scattering coefficient generally decreased with the increase of wavelength. Partial least squares regression resulted in various levels of correlation of microa and micros' with the firmness, soluble solids content, and skin and flesh color parameters of peaches (r = 0.204--0.855) and apples (r = 0.460--0.885), and the combination of the two optical parameters generally gave higher correlations (up to 0.893). The mean value of microa and micros' for GD and GS apples for each storage date was positively correlated with acoustic/impact firmness, Young's modulus, and cell parameters (r = 0.585--0.948 for GD and r = 0.292--0.993 for GS). A two-layer diffusion model for determining the optical properties of fruit skin and flesh was further investigated through solid model samples. The average errors of determining two and four optical parameters were 6.8% and 15.3%, respectively, for the Monte Carlo reflectance data. The errors of determining the first or surface layer of the model samples were approximately 23.0% for microa and 18.4% for micros', indicating the difficulty and also potential in applying the two-layer diffusion model for fruit. This research has demonstrated the usefulness of hyperspectral imaging-based spatially-resolved technique for determining the optical properties and maturity/quality of fruits. However, further research is needed to reduce measurement variability or error caused by irregular or rough surface of fruit and the presence of fruit skin, and apply the technique to other foods and biological materials.

Cross multivariate correlation coefficients as screening tool for analysis of concurrent EEG-fMRI recordings.

PubMed

Ji, Hong; Petro, Nathan M; Chen, Badong; Yuan, Zejian; Wang, Jianji; Zheng, Nanning; Keil, Andreas

2018-02-06

Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging. Here, we propose a novel screening approach that relies on a Cross Multivariate Correlation Coefficient (xMCC) framework. This approach accomplishes three tasks: (1) It provides a measure for testing multivariate correlation and multivariate uncorrelation of the two modalities; (2) it provides criterion for the selection of EEG features; (3) it performs a screening of relevant EEG information by grouping the EEG channels into clusters to improve efficiency and to reduce computational load when searching for the best predictors of the BOLD signal. The present report applies this approach to a data set with concurrent recordings of steady-state-visual evoked potentials (ssVEPs) and fMRI, recorded while observers viewed phase-reversing Gabor patches. We test the hypothesis that fluctuations in visuo-cortical mass potentials systematically covary with BOLD fluctuations not only in visual cortical, but also in anterior temporal and prefrontal areas. Results supported the hypothesis and showed that the xMCC-based analysis provides straightforward identification of neurophysiological plausible brain regions with EEG-fMRI covariance. Furthermore xMCC converged with other extant methods for EEG-fMRI analysis. © 2018 The Authors Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Remote sensing of soil organic matter of farmland with hyperspectral image

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Wang, Lei; Yang, Guijun; Zhang, Liyan

2017-10-01

Monitoring soil organic matter (SOM) of cultivated land quantitively and mastering its spatial change are helpful for fertility adjustment and sustainable development of agriculture. The study aimed to analyze the response between SOM and reflectivity of hyperspectral image with different pixel size and develop the optimal model of estimating SOM with imaging spectral technology. The wavelet transform method was used to analyze the correlation between the hyperspectral reflectivity and SOM. Then the optimal pixel size and sensitive wavelet feature scale were screened to develop the inversion model of SOM. Result showed that wavelet transform of soil hyperspectrum was help to improve the correlation between the wavelet features and SOM. In the visible wavelength range, the susceptible wavelet features of SOM mainly concentrated 460 603 nm. As the wavelength increased, the wavelet scale corresponding correlation coefficient increased maximum and then gradually decreased. In the near infrared wavelength range, the susceptible wavelet features of SOM mainly concentrated 762 882 nm. As the wavelength increased, the wavelet scale gradually decreased. The study developed multivariate model of continuous wavelet transforms by the method of stepwise linear regression (SLR). The CWT-SLR models reached higher accuracies than those of univariate models. With the resampling scale increasing, the accuracies of CWT-SLR models gradually increased, while the determination coefficients (R2) fluctuated from 0.52 to 0.59. The R2 of 5*5 scale reached highest (0.5954), while the RMSE reached lowest (2.41 g/kg). It indicated that multivariate model based on continuous wavelet transform had better ability for estimating SOM than univariate model.

A Method for Approximating the Bivariate Normal Correlation Coefficient.

ERIC Educational Resources Information Center

Kirk, David B.

Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

Semi-quantitative spectrographic analysis and rank correlation in geochemistry

USGS Publications Warehouse

Flanagan, F.J.

1957-01-01

The rank correlation coefficient, rs, which involves less computation than the product-moment correlation coefficient, r, can be used to indicate the degree of relationship between two elements. The method is applicable in situations where the assumptions underlying normal distribution correlation theory may not be satisfied. Semi-quantitative spectrographic analyses which are reported as grouped or partly ranked data can be used to calculate rank correlations between elements. ?? 1957.

Robust Approximations to the Non-Null Distribution of the Product Moment Correlation Coefficient I: The Phi Coefficient.

ERIC Educational Resources Information Center

Edwards, Lynne K.; Meyers, Sarah A.

Correlation coefficients are frequently reported in educational and psychological research. The robustness properties and optimality among practical approximations when phi does not equal 0 with moderate sample sizes are not well documented. Three major approximations and their variations are examined: (1) a normal approximation of Fisher's Z,…

Correcting Coefficient Alpha for Correlated Errors: Is [alpha][K]a Lower Bound to Reliability?

ERIC Educational Resources Information Center

Rae, Gordon

2006-01-01

When errors of measurement are positively correlated, coefficient alpha may overestimate the "true" reliability of a composite. To reduce this inflation bias, Komaroff (1997) has proposed an adjusted alpha coefficient, ak. This article shows that ak is only guaranteed to be a lower bound to reliability if the latter does not include correlated…

A Hydrodynamic Theory for Spatially Inhomogeneous Semiconductor Lasers: Microscopic Approach

NASA Technical Reports Server (NTRS)

Li, Jianzhong; Ning, C. Z.; Biegel, Bryan A. (Technical Monitor)

2001-01-01

Starting from the microscopic semiconductor Bloch equations (SBEs) including the Boltzmann transport terms in the distribution function equations for electrons and holes, we derived a closed set of diffusion equations for carrier densities and temperatures with self-consistent coupling to Maxwell's equation and to an effective optical polarization equation. The coherent many-body effects are included within the screened Hartree-Fock approximation, while scatterings are treated within the second Born approximation including both the in- and out-scatterings. Microscopic expressions for electron-hole (e-h) and carrier-LO (c-LO) phonon scatterings are directly used to derive the momentum and energy relaxation rates. These rates expressed as functions of temperatures and densities lead to microscopic expressions for self- and mutual-diffusion coefficients in the coupled density-temperature diffusion equations. Approximations for reducing the general two-component description of the electron-hole plasma (EHP) to a single-component one are discussed. In particular, we show that a special single-component reduction is possible when e-h scattering dominates over c-LO phonon scattering. The ambipolar diffusion approximation is also discussed and we show that the ambipolar diffusion coefficients are independent of e-h scattering, even though the diffusion coefficients of individual components depend sensitively on the e-h scattering rates. Our discussions lead to new perspectives into the roles played in the single-component reduction by the electron-hole correlation in momentum space induced by scatterings and the electron-hole correlation in real space via internal static electrical field. Finally, the theory is completed by coupling the diffusion equations to the lattice temperature equation and to the effective optical polarization which in turn couples to the laser field.

Scaling relations between trabecular bone volume fraction and microstructure at different skeletal sites.

PubMed

Räth, Christoph; Baum, Thomas; Monetti, Roberto; Sidorenko, Irina; Wolf, Petra; Eckstein, Felix; Matsuura, Maiko; Lochmüller, Eva-Maria; Zysset, Philippe K; Rummeny, Ernst J; Link, Thomas M; Bauer, Jan S

2013-12-01

In this study, we investigated the scaling relations between trabecular bone volume fraction (BV/TV) and parameters of the trabecular microstructure at different skeletal sites. Cylindrical bone samples with a diameter of 8mm were harvested from different skeletal sites of 154 human donors in vitro: 87 from the distal radius, 59/69 from the thoracic/lumbar spine, 51 from the femoral neck, and 83 from the greater trochanter. μCT images were obtained with an isotropic spatial resolution of 26μm. BV/TV and trabecular microstructure parameters (TbN, TbTh, TbSp, scaling indices (< > and σ of α and αz), and Minkowski Functionals (Surface, Curvature, Euler)) were computed for each sample. The regression coefficient β was determined for each skeletal site as the slope of a linear fit in the double-logarithmic representations of the correlations of BV/TV versus the respective microstructure parameter. Statistically significant correlation coefficients ranging from r=0.36 to r=0.97 were observed for BV/TV versus microstructure parameters, except for Curvature and Euler. The regression coefficients β were 0.19 to 0.23 (TbN), 0.21 to 0.30 (TbTh), -0.28 to -0.24 (TbSp), 0.58 to 0.71 (Surface) and 0.12 to 0.16 (<α>), 0.07 to 0.11 (<αz>), -0.44 to -0.30 (σ(α)), and -0.39 to -0.14 (σ(αz)) at the different skeletal sites. The 95% confidence intervals of β overlapped for almost all microstructure parameters at the different skeletal sites. The scaling relations were independent of vertebral fracture status and similar for subjects aged 60-69, 70-79, and >79years. In conclusion, the bone volume fraction-microstructure scaling relations showed a rather universal character. © 2013.

Prediction of stream volatilization coefficients

USGS Publications Warehouse

Rathbun, Ronald E.

1990-01-01

Equations are developed for predicting the liquid-film and gas-film reference-substance parameters for quantifying volatilization of organic solutes from streams. Molecular weight and molecular-diffusion coefficients of the solute are used as correlating parameters. Equations for predicting molecular-diffusion coefficients of organic solutes in water and air are developed, with molecular weight and molal volume as parameters. Mean absolute errors of prediction for diffusion coefficients in water are 9.97% for the molecular-weight equation, 6.45% for the molal-volume equation. The mean absolute error for the diffusion coefficient in air is 5.79% for the molal-volume equation. Molecular weight is not a satisfactory correlating parameter for diffusion in air because two equations are necessary to describe the values in the data set. The best predictive equation for the liquid-film reference-substance parameter has a mean absolute error of 5.74%, with molal volume as the correlating parameter. The best equation for the gas-film parameter has a mean absolute error of 7.80%, with molecular weight as the correlating parameter.

Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

NASA Astrophysics Data System (ADS)

Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

2010-09-01

In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional ground cover. Thermal-based energy balance models are more suitable than the FAO-Kc model for estimating crop ET, especially under moisture stress conditions, but they require many inputs and detailed theoretical background knowledge; so they can be only used in regions where high quality, hourly agricultural weather data are readily available providing instantaneous values of heat fluxes corresponding to the time of the satellite overpass. Thus, FAO-Kc approach is widely used in research activities and real-time irrigation scheduling for several water applications since it does not require temporal upscaling for obtaining daily values and satellite imagery in the reflective bands used for vegetation index computation are more readily available at higher spatial resolution than thermal band data. There is no simple way to compute crop coefficients because they depend on climate, soil type, crop and its varieties, irrigation method, soil water, nutrient content and plant phenology. Consequently, specific calibrations of crop coefficient are required in various climatic regions. Many authors suggested a linear relationship between Kc and vegetation indices, but non-linear relationships have been proposed too. However, according to the radiative transfer theory, the nature of such relationships depends on the crop architecture and the definition of the adopted vegetation index, but the linear assumption can be adopted as first. Such studies, mainly investigated the possibility to use high resolution satellite data, such as Quickbird, Ikonos, TM, which are not suitable for operational purposes since in spite of the high spatial sampling they have an inadequate revisiting time over a given area. To obtain adequate temporal sampling, some authors proposed the use of a virtual constellation made by all currently available high-resolution satellites (e.g., DEMETER project). However the joint use of data from different satellites requires a carefully inter-satellite cross-calibration and co-registration. In order to avoid such problems and to generate spatially distributed values of Kc capturing field-specific crop development, the employment of vegetation indices derived from medium resolution MODIS data having a higher temporal sampling has been investigated. The spatial and temporal correlation between NDVI (Normalized Difference Vegetation Index) and crop coefficients for different herbaceous and arboreal cultivations has been investigated to define their relationships. Through this approach site-specific crop coefficients were derived taking into account the effective ground coverage and status. The analysis has been applied on the 2005-2008 time series for the Basilicata region, Southern Italy.

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

PubMed Central

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-01-01

Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data. PMID:27621916

A model relating Eulerian spatial and temporal velocity correlations

NASA Astrophysics Data System (ADS)

Cholemari, Murali R.; Arakeri, Jaywant H.

2006-03-01

In this paper we propose a model to relate Eulerian spatial and temporal velocity autocorrelations in homogeneous, isotropic and stationary turbulence. We model the decorrelation as the eddies of various scales becoming decorrelated. This enables us to connect the spatial and temporal separations required for a certain decorrelation through the ‘eddy scale’. Given either the spatial or the temporal velocity correlation, we obtain the ‘eddy scale’ and the rate at which the decorrelation proceeds. This leads to a spatial separation from the temporal correlation and a temporal separation from the spatial correlation, at any given value of the correlation relating the two correlations. We test the model using experimental data from a stationary axisymmetric turbulent flow with homogeneity along the axis.

Python Waveform Cross-Correlation

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

Templeton, Dennise

PyWCC is a tool to compute seismic waveform cross-correlation coefficients on single-component or multiple-component seismic data across a network of seismic sensors. PyWCC compares waveform data templates with continuous seismic data, associates the resulting detections, identifies the template with the highest cross-correlation coefficient, and outputs a catalog of detections above a user-defined absolute cross-correlation threshold value.

Hadamard multimode optical imaging transceiver

DOEpatents

Cooke, Bradly J; Guenther, David C; Tiee, Joe J; Kellum, Mervyn J; Olivas, Nicholas L; Weisse-Bernstein, Nina R; Judd, Stephen L; Braun, Thomas R

2012-10-30

Disclosed is a method and system for simultaneously acquiring and producing results for multiple image modes using a common sensor without optical filtering, scanning, or other moving parts. The system and method utilize the Walsh-Hadamard correlation detection process (e.g., functions/matrix) to provide an all-binary structure that permits seamless bridging between analog and digital domains. An embodiment may capture an incoming optical signal at an optical aperture, convert the optical signal to an electrical signal, pass the electrical signal through a Low-Noise Amplifier (LNA) to create an LNA signal, pass the LNA signal through one or more correlators where each correlator has a corresponding Walsh-Hadamard (WH) binary basis function, calculate a correlation output coefficient for each correlator as a function of the corresponding WH binary basis function in accordance with Walsh-Hadamard mathematical principles, digitize each of the correlation output coefficient by passing each correlation output coefficient through an Analog-to-Digital Converter (ADC), and performing image mode processing on the digitized correlation output coefficients as desired to produce one or more image modes. Some, but not all, potential image modes include: multi-channel access, temporal, range, three-dimensional, and synthetic aperture.

Relative validity of an FFQ to estimate daily food and nutrient intakes for Chilean adults.

PubMed

Dehghan, Mahshid; Martinez, Solange; Zhang, Xiaohe; Seron, Pamela; Lanas, Fernando; Islam, Shofiqul; Merchant, Anwar T

2013-10-01

FFQ are commonly used to rank individuals by their food and nutrient intakes in large epidemiological studies. The purpose of the present study was to develop and validate an FFQ to rank individuals participating in an ongoing Prospective Urban and Rural Epidemiological (PURE) study in Chile. An FFQ and four 24 h dietary recalls were completed over 1 year. Pearson correlation coefficients, energy-adjusted and de-attenuated correlations and weighted kappa were computed between the dietary recalls and the FFQ. The level of agreement between the two dietary assessment methods was evaluated by Bland-Altman analysis. Temuco, Chile. Overall, 166 women and men enrolled in the present study. One hundred men and women participated in FFQ development and sixty-six individuals participated in FFQ validation. The FFQ consisted of 109 food items. For nutrients, the crude correlation coefficients between the dietary recalls and FFQ varied from 0.14 (protein) to 0.44 (fat). Energy adjustment and de-attenuation improved correlation coefficients and almost all correlation coefficients exceeded 0.40. Similar correlation coefficients were observed for food groups; the highest de-attenuated energy adjusted correlation coefficient was found for margarine and butter (0.75) and the lowest for potatoes (0.12). The FFQ showed moderate to high agreement for most nutrients and food groups, and can be used to rank individuals based on energy, nutrient and food intakes. The validation study was conducted in a unique setting and indicated that the tool is valid for use by adults in Chile.

[Habitat suitability index of larval Japanese Halfbeak (Hyporhamphus sajori) in Bohai Sea based on geographically weighted regression.

PubMed

Zhao, Yang; Zhang, Xue Qing; Bian, Xiao Dong

2018-01-01

To investigate the early supplementary processes of fishre sources in the Bohai Sea, the geographically weighted regression (GWR) was introduced to the habitat suitability index (HSI) model. The Bohai Sea larval Japanese Halfbeak HSI GWR model was established with four environmental variables, including sea surface temperature (SST), sea surface salinity (SSS), water depth (DEP), and chlorophyll a concentration (Chl a). Results of the simulation showed that the four variables had different performances in August 2015. SST and Chl a were global variables, and had little impacts on HSI, with the regression coefficients of -0.027 and 0.006, respectively. SSS and DEP were local variables, and had larger impacts on HSI, while the average values of absolute values of their regression coefficients were 0.075 and 0.129, respectively. In the central Bohai Sea, SSS showed a negative correlation with HSI, and the most negative correlation coefficient was -0.3. In contrast, SSS was correlated positively but weakly with HSI in the three bays of Bohai Sea, and the largest correlation coefficient was 0.1. In particular, DEP and HSI were negatively correlated in the entire Bohai Sea, while they were more negatively correlated in the three bays of Bohai than in the central Bohai Sea, and the most negative correlation coefficient was -0.16 in the three bays. The Poisson regression coefficient of the HSI GWR model was 0.705, consistent with field measurements. Therefore, it could provide a new method for the research on fish habitats in the future.

Psychometric properties of the modified RESIDE physical activity questionnaire among low-income overweight women.

PubMed

Jones, Sydney A; Evenson, Kelly R; Johnston, Larry F; Trost, Stewart G; Samuel-Hodge, Carmen; Jewell, David A; Kraschnewski, Jennifer L; Keyserling, Thomas C

2015-01-01

This study explored the criterion-related validity and test-retest reliability of the modified RESIDential Environment physical activity questionnaire and whether the instrument's validity varied by body mass index, education, race/ethnicity, or employment status. Validation study using baseline data collected for randomized trial of a weight loss intervention. Participants recruited from health departments wore an ActiGraph accelerometer and self-reported non-occupational walking, moderate and vigorous physical activity on the modified RESIDential Environment questionnaire. We assessed validity (n=152) using Spearman correlation coefficients, and reliability (n=57) using intraclass correlation coefficients. When compared to steps, moderate physical activity, and bouts of moderate/vigorous physical activity measured by accelerometer, these questionnaire measures showed fair evidence for validity: recreational walking (Spearman correlation coefficients 0.23-0.36), total walking (Spearman correlation coefficients 0.24-0.37), and total moderate physical activity (Spearman correlation coefficients 0.18-0.36). Correlations for self-reported walking and moderate physical activity were higher among unemployed participants and women with lower body mass indices. Generally no other variability in the validity of the instrument was found. Evidence for reliability of RESIDential Environment measures of recreational walking, total walking, and total moderate physical activity was substantial (intraclass correlation coefficients 0.56-0.68). Evidence for questionnaire validity and reliability varied by activity domain and was strongest for walking measures. The questionnaire may capture physical activity less accurately among women with higher body mass indices and employed participants. Capturing occupational activity, specifically walking at work, may improve questionnaire validity. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

In vivo macular pigment measurements: a comparison of resonance Raman spectroscopy and heterochromatic flicker photometry

PubMed Central

Hogg, R E; Anderson, R S; Stevenson, M R; Zlatkova, M B; Chakravarthy, U

2007-01-01

Aim To investigate whether two methods of measuring macular pigment—namely, heterochromatic flicker photometry (HFP) and resonance Raman spectroscopy (RRS)—yield comparable data. Methods Macular pigment was measured using HFP and RRS in the right eye of 107 participants aged 20–79 years. Correlations between methods were sought and regression models generated. RRS was recorded as Raman counts and HFP as macular pigment optical density (MPOD). The average of the top three of five Raman counts was compared with MPOD obtained at 0.5° eccentricity, and an integrated measure (spatial profile; MPODsp) computed from four stimulus sizes on HFP. Results The coefficient of variation was 12.0% for MPODsp and 13.5% for Raman counts. MPODsp exhibited significant correlations with Raman counts (r = 0.260, p = 0.012), whereas MPOD at 0.5° did not correlate significantly (r = 0.163, p = 0.118). MPODsp was not significantly correlated with age (p = 0.062), whereas MPOD at 0.5° was positively correlated (p = 0.011). Raman counts showed a significant decrease with age (p = 0.002) and were significantly lower when pupil size was smaller (p = 0.015). Conclusions Despite a statistically significant correlation, the correlations were weak, with those in excess of 90% of the variance between MPODsp and Raman counts remaining unexplained, meriting further research. PMID:16825281

Nonlinearity of the forward-backward correlation function in the model with string fusion

NASA Astrophysics Data System (ADS)

Vechernin, Vladimir

2017-12-01

The behavior of the forward-backward correlation functions and the corresponding correlation coefficients between multiplicities and transverse momenta of particles produced in high energy hadronic interactions is analyzed by analytical and MC calculations in the models with and without string fusion. The string fusion is taking into account in simplified form by introducing the lattice in the transverse plane. The results obtained with two alternative definitions of the forward-backward correlation coefficient are compared. It is shown that the nonlinearity of correlation functions increases with the width of observation windows, leading at small string density to a strong dependence of correlation coefficient value on the definition. The results of the modeling enable qualitatively to explain the experimentally observed features in the behavior of the correlation functions between multiplicities and mean transverse momenta at small and large multiplicities.

Monitoring of land degradation from overgrazing using space-borne radar and optical imagery: a case study in Randi Forest, Cyprus

NASA Astrophysics Data System (ADS)

Papoutsa, C.; Kouhartsiouk, D.; Themistocleous, K.; Christoforou, M.; Hadjimitsis, D. G.

2016-10-01

This paper examines how radar and optical imagery combined can be employed for the study of land degradation. A case study was conducted in the Randi Forest, Cyprus, a known overgrazed area for the past 70 years. Satellite optical imagery was used for the calculation of the Normalised Difference Vegetation Index (NDVI) for the time period between December 2015 to July 2016 and C-Band Synthetic Aperture Radar imagery was used to derive correlative changes in backscatter intensity (σ0). The results are indicative of the overgrazing in the area with the temporal and spatial variations of grazing defined. Both the NDVI and the σ0 values demonstrate sudden shifts in vegetation cover following the start of the grazing period with the greatest shifts being evident in close proximity to the location of farms. NDVI and backscatter coefficient correlation was measured at 0.7 and 0.8 for the months of February and April respectively. Shifts in NDVI value by 0.1 correspond to a shift in σ0 by 4 db. VH cross-polarization showed greater sensitivity to changes in vegetation than VV. The paper also examines the capability of C-Band Synthetic Aperture Radar to measure changes in plant structure and vegetation fraction as the result of grazing. Depending on grazing intensity, backscatter coefficient varies according to vegetation density.

Gait consistency over a 7-day interval in people with Parkinson's disease.

PubMed

Urquhart, D M; Morris, M E; Iansek, R

1999-06-01

To evaluate the consistency of temporal and spatial parameters of the walking pattern in subjects with idiopathic Parkinson's disease (PD) over a 7-day interval during the "on" phase of the levodopa medication cycle. Walking patterns were measured on a 12-meter walkway at the Kingston Gait Laboratory, Cheltenham, using a computerized stride analyzer. Sixteen subjects (7 women, 9 men) with PD recruited from the Movement Disorders Clinic at Kingston Centre. Speed of walking, stride length, cadence, and the percentage of the walking cycle spent in the double limb support phase of gait were measured, together with the level of disability as indexed by the modified Webster scale. Product-moment correlation coefficients and intraclass correlation coefficients (ICC 2,1) for repeat measures over a 7-day interval were high for speed (r = .90; ICC = .93), cadence (r = .90; ICC = .86), and stride length (r = 1.00; ICC = .97) and moderate for double limb support duration after removal of outliers (r = .75; ICC = .73); 95% confidence intervals for the change scores were within clinically acceptable limits for all variables. The mean modified Webster score was 11.4 on the first day and 10.1 7 days later. The gait pattern and level of disability in subjects with PD without severe motor fluctuations remained stable over a 1-week period when optimal medication prevailed.

Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.

PubMed

Liang, Gaozhen; Dong, Chunwang; Hu, Bin; Zhu, Hongkai; Yuan, Haibo; Jiang, Yongwen; Hao, Guoshuang

2018-05-18

Withering is the first step in the processing of congou black tea. With respect to the deficiency of traditional water content detection methods, a machine vision based NDT (Non Destructive Testing) method was established to detect the moisture content of withered leaves. First, according to the time sequences using computer visual system collected visible light images of tea leaf surfaces, and color and texture characteristics are extracted through the spatial changes of colors. Then quantitative prediction models for moisture content detection of withered tea leaves was established through linear PLS (Partial Least Squares) and non-linear SVM (Support Vector Machine). The results showed correlation coefficients higher than 0.8 between the water contents and green component mean value (G), lightness component mean value (L * ) and uniformity (U), which means that the extracted characteristics have great potential to predict the water contents. The performance parameters as correlation coefficient of prediction set (Rp), root-mean-square error of prediction (RMSEP), and relative standard deviation (RPD) of the SVM prediction model are 0.9314, 0.0411 and 1.8004, respectively. The non-linear modeling method can better describe the quantitative analytical relations between the image and water content. With superior generalization and robustness, the method would provide a new train of thought and theoretical basis for the online water content monitoring technology of automated production of black tea.

The relationship between the managerial skills and results of "performance evaluation "tool among nursing managers in teaching hospitals of Iran University of Medical Science.

PubMed

Isfahani, Haleh Mousavi; Aryankhesal, Aidin; Haghani, Hamid

2014-09-25

Performance of different organizations, such as hospitals is mainly influenced by their managers' performance. Nursing managers have an important role in hospital performance and their managerial skills can improve the quality of the services. Hence, the present study was conducted in order to assess the relationship between the managerial skills and the results of their performance evaluation in Teaching Hospitals of Iran University of Medical Science in 2013. The research used the cross sectional method in 2013. It was done by distributing a managerial skills assessment questionnaire, with close-ended questions in 5 choice Likert scale, among 181 managers and head nurses of hospitals of Iran university of Medical Sciences; among which 131 answered the questions. Another data collection tools was a forms to record evaluation marks from the personnel records. We used Pearson and Spearman correlation tests and SPSS for analysis and description (frequency, mean and standard deviation). Results showed that the managerial skills of the nursing mangers were fair (2.57 out of 5) and the results of the performance evaluation were in a good condition (98.44). The mangers' evaluation results and the managerial skills scores were not in a meaningful correlation (r=0.047 np=0.856). The research showed no correlation between different domains of managerial skills and the performance evaluation marks: decision making skills (r=0.074 and p=0.399), leadership (correlation coefficient 0.028 and p=0.654), motivation (correlation coefficient 0.118 and p=0.163), communication  (correlation coefficient 0.116 and p=0.122), systematic thinking  (correlation coefficient 0.028 and p=0.828), time management (correlation coefficient 0.077 and p=0.401) and strategic thinking  (correlation coefficient 0.041 and p=0.756). Lack of any correlation and relation between managers' managerial skills and their performance evaluation results shows need to a fundamental revision at managers' performance evaluation form.

Does hemipelvis structure and position influence acetabulum orientation?

PubMed

Musielak, Bartosz; Jóźwiak, Marek; Rychlik, Michał; Chen, Brian Po-Jung; Idzior, Maciej; Grzegorzewski, Andrzej

2016-03-16

Although acetabulum orientation is well established anatomically and radiographically, its relation to the innominate bone has rarely been addressed. If explored, it could open the discussion on patomechanisms of such complex disorders as femoroacetabular impingement (FAI). We therefore evaluated the influence of pelvic bone position and structure on acetabular spatial orientation. We describe this relation and its clinical implications. This retrospective study was based on computed tomography scanning of three-dimensional models of 31 consecutive male pelvises (62 acetabulums). All measurements were based on CT spatial reconstruction with the use of highly specialized software (Rhinoceros). Relations between acetabular orientation (inclination, tilt, anteversion angles) and pelvic structure were evaluated. The following parameters were evaluated to assess the pelvic structure: iliac opening angle, iliac tilt angle, interspinous distance (ISD), intertuberous distance (ITD), height of the pelvis (HP), and the ISD/ITD/HP ratio. The linear and nonlinear dependence of the acetabular angles and hemipelvic measurements were examined with Pearson's product - moment correlation and Spearman's rank correlation coefficient. Correlations different from 0 with p < 0.05 were considered statistically significant. Comparison of the axis position with pelvis structure with orientation in the horizontal plane revealed a significant positive correlation between the acetabular anteversion angle and the iliac opening angle (p = 0.041 and 0.008, respectively). In the frontal plane, there was a positive correlation between the acetabular inclination angle and the iliac tilt angle (p = 0.025 and 0.014, respectively) and the acetabular inclination angle and the ISD/ITD/HP ratio (both p = 0.048). There is a significant correlation of the hemipelvic structure and acetabular orientation under anatomic conditions, especially in the frontal and horizontal planes. In the anteroposterior view, the more tilted-down innominate bone causes a more caudally oriented acetabulum axis, whereas in the horizontal view this relation is reversed. This study may serve as a basis for the discussion on the role of the pelvis in common disorders of the hip.

A novel approach to water polution monitoring by combining ion exchange resin and XRF-scanning technique

NASA Astrophysics Data System (ADS)

Huang, J. J.; Lin, S. C.; Löwemark, L.; Liou, Y. H.; Chang, Q. M.; Chang, T. K.; Wei, K. Y.; Croudace, I. W. C.

2017-12-01

Due to the rapid industrial expansion, environments are subject to irregular fluctuations and spatial distributions in pollutant concentrations. This study proposes to use ion exchange resin accompanied with the XRF-scanning technique to monitor environmental pollution. As a passive sampling sorbent, the use of ion exchange resin provides a rapid, low cost and simple method to detect episodic pollution signals with a high spatial sampling density. In order to digest large quantities of samples, the fast and non-destructive Itrax-XRF core scanner has been introduced to assess elemental concentrations in the resin samples. Although the XRF scanning results are often considered as a semi-quantitative measurement due to possible absorption or scattering caused by the physical variabilities of scanned materials, the use of resin can minimize such influences owing to the standarization of the sample matrix. In this study, 17 lab-prepared standard resin samples were scanned with the Itrax-XRF core scanner (at 100 s exposure time with the Mo-tube) and compared with the absolute elemental concentrations. Six elements generally used in pollution studies (Cr, Mn, Ni, Cu, Zn, and Pb) were selected, and their regression lines and correlation coefficients were determined. In addition, 5 standard resin samples were scanned at different exposure time settings (1 s, 5 s, 15 s, 30 s, 100 s) to address the influence of exposure time on the accuracy of the measurements. The results show that within the test range (from few ppm to thousands ppm), the correlation coefficients are higher than 0.97, even at the shortest exposure time (1 s). Furthermore, a pilot field survey with 30 resin samples has been conducted in a potentially polluted farm area in central Taiwan to demonstrate the feasibility of this novel approach. The polluted hot zones could be identified and the properties and sources of wastewater pollution can therefore be traced over large areas for the purposes of environmental monitoring and environmental forensics.

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

McCulloch, M; Polan, D; Feng, M

Purpose: Previous studies have shown that radiotherapy treatment for liver metastases causes marked liver hypertrophy in areas receiving low dose and atrophy/fibrosis in areas receiving high dose. The purpose of this work is to develop and evaluate a biomechanical model-based dose-response model to describe these liver responses to SBRT. Methods: In this retrospective study, a biomechanical model-based deformable registration algorithm, Morfeus, was expanded to include dose-based boundary conditions. Liver and tumor volumes were contoured on the planning images and CT/MR images three months post-RT and converted to finite element models. A thermal expansion-based relationship correlating the delivered dose and volumemore » response was generated from 22 patients previously treated. This coefficient, combined with the planned dose, was applied as an additional boundary condition to describe the volumetric response of the liver of an additional cohort of metastatic liver patients treated with SBRT. The accuracy of the model was evaluated based on overall volumetric liver comparisons and the target registration error (TRE) using the average deviations in positions of identified vascular bifurcations on each set of registered images, with a target accuracy of the 2.5mm isotropic dose grid (vector dimension 4.3mm). Results: The thermal expansion coefficient models the volumetric change of the liver to within 3%. The accuracy of Morfeus with dose-expansion boundary conditions a TRE of 5.7±2.8mm compared to 11.2±3.7mm using rigid registration and 8.9±0.28mm using Morfeus with only spatial boundary conditions. Conclusion: A biomechanical model has been developed to describe the volumetric and spatial response of the liver to SBRT. This work will enable the improvement of correlating functional imaging with delivered dose, the mapping of the delivered dose from one treatment onto the planning images for a subsequent treatment, and will further provide information to assist with the biological characterization of patients’ response to radiation.« less

Validating NO2 measurements in the vertical atmospheric column with the OMI instrument aboard the EOS Aura satellite against ground-based measurements at the Zvenigorod Scientific Station

NASA Astrophysics Data System (ADS)

Gruzdev, A. N.; Elokhov, A. S.

2009-08-01

Data on the NO2 content in the vertical column of the atmosphere obtained with the Ozone Monitoring Instrument (OMI) aboard the EOS Aura satellite (United States) in the period from October 2004 to October 2007 are compared with the results of ground-based measurements at the Zvenigorod Scientific Station (55.7° N, 36.8° E). The “unpolluted”; part of the total NO2 content in the atmospheric column, which mostly represents the stratosphere, and the NO2 contents in the vertical column of the troposphere, including the lower layer, which is subject to pollution, are included in the comparison. The correlation coefficient between the results of ground-based and satellite measurements of the “unpolluted” total NO2 content is ˜0.9. The content values measured with the OMI instrument are smaller than the results of ground-based measurements (on average, by (0.30 ± 0.03) × 1015 cm-2 or by (11 ± 1)%). Therms discrepancy between the satellite and ground-based data is 0.6 × 1015 cm-2. The NO2 content in the vertical column of the troposphere from the results of satellite measurements is, on average, (1.4 ± 0.5) × 1015 cm-2, (or about 35%) smaller than from the results of ground-based measurements, and the rms discrepancy between them is about 200%. The correlation coefficient between these data is ˜0.4. This considerable discrepancy is evidently caused by the strong spatial (horizontal) inhomogeneity and the temporal variability of the NO2 field during episodes of pollution, which leads to different (and often uncorrelated) estimates of the NO2 content in the lower troposphere due to different spatial resolutions of ground-based and satellite measurements.

Complementary studies of lipid membrane dynamics using iSCAT and super-resolved fluorescence correlation spectroscopy

NASA Astrophysics Data System (ADS)

Reina, Francesco; Galiani, Silvia; Shrestha, Dilip; Sezgin, Erdinc; de Wit, Gabrielle; Cole, Daniel; Lagerholm, B. Christoffer; Kukura, Philipp; Eggeling, Christian

2018-06-01

Observation techniques with high spatial and temporal resolution, such as single-particle tracking based on interferometric scattering (iSCAT) microscopy, and fluorescence correlation spectroscopy applied on a super-resolution STED microscope (STED-FCS), have revealed new insights of the molecular organization of membranes. While delivering complementary information, there are still distinct differences between these techniques, most prominently the use of fluorescent dye tagged probes for STED-FCS and a need for larger scattering gold nanoparticle tags for iSCAT. In this work, we have used lipid analogues tagged with a hybrid fluorescent tag–gold nanoparticle construct, to directly compare the results from STED-FCS and iSCAT measurements of phospholipid diffusion on a homogeneous supported lipid bilayer (SLB). These comparative measurements showed that while the mode of diffusion remained free, at least at the spatial (>40 nm) and temporal (50  ⩽  t  ⩽  100 ms) scales probed, the diffussion coefficient was reduced by 20- to 60-fold when tagging with 20 and 40 nm large gold particles as compared to when using dye tagged lipid analogues. These FCS measurements of hybrid fluorescent tag–gold nanoparticle labeled lipids also revealed that commercially supplied streptavidin-coated gold nanoparticles contain large quantities of free streptavidin. Finally, the values of apparent diffusion coefficients obtained by STED-FCS and iSCAT differed by a factor of 2–3 across the techniques, while relative differences in mobility between different species of lipid analogues considered were identical in both approaches. In conclusion, our experiments reveal that large and potentially cross-linking scattering tags introduce a significant slow-down in diffusion on SLBs but no additional bias, and our labeling approach creates a new way of exploiting complementary information from STED-FCS and iSCAT measurements.