Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image

PubMed Central

El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-01-01

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick’s texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm. PMID:28773080

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

Classification of CT examinations for COPD visual severity analysis

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

2012-03-01

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

Computerized Classification of Pneumoconiosis on Digital Chest Radiography Artificial Neural Network with Three Stages.

PubMed

Okumura, Eiichiro; Kawashita, Ikuo; Ishida, Takayuki

2017-08-01

It is difficult for radiologists to classify pneumoconiosis from category 0 to category 3 on chest radiographs. Therefore, we have developed a computer-aided diagnosis (CAD) system based on a three-stage artificial neural network (ANN) method for classification based on four texture features. The image database consists of 36 chest radiographs classified as category 0 to category 3. Regions of interest (ROIs) with a matrix size of 32 × 32 were selected from chest radiographs. We obtained a gray-level histogram, histogram of gray-level difference, gray-level run-length matrix (GLRLM) feature image, and gray-level co-occurrence matrix (GLCOM) feature image in each ROI. For ROI-based classification, the first ANN was trained with each texture feature. Next, the second ANN was trained with output patterns obtained from the first ANN. Finally, we obtained a case-based classification for distinguishing among four categories with the third ANN method. We determined the performance of the third ANN by receiver operating characteristic (ROC) analysis. The areas under the ROC curve (AUC) of the highest category (severe pneumoconiosis) case and the lowest category (early pneumoconiosis) case were 0.89 ± 0.09 and 0.84 ± 0.12, respectively. The three-stage ANN with four texture features showed the highest performance for classification among the four categories. Our CAD system would be useful for assisting radiologists in classification of pneumoconiosis from category 0 to category 3.

Research on Optimization of GLCM Parameter in Cell Classification

NASA Astrophysics Data System (ADS)

Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

2016-05-01

Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

Cloud field classification based upon high spatial resolution textural features. I - Gray level co-occurrence matrix approach

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1988-01-01

Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.

General Approach for Rock Classification Based on Digital Image Analysis of Electrical Borehole Wall Images

NASA Astrophysics Data System (ADS)

Linek, M.; Jungmann, M.; Berlage, T.; Clauser, C.

2005-12-01

Within the Ocean Drilling Program (ODP), image logging tools have been routinely deployed such as the Formation MicroScanner (FMS) or the Resistivity-At-Bit (RAB) tools. Both logging methods are based on resistivity measurements at the borehole wall and therefore are sensitive to conductivity contrasts, which are mapped in color scale images. These images are commonly used to study the structure of the sedimentary rocks and the oceanic crust (petrologic fabric, fractures, veins, etc.). So far, mapping of lithology from electrical images is purely based on visual inspection and subjective interpretation. We apply digital image analysis on electrical borehole wall images in order to develop a method, which augments objective rock identification. We focus on supervised textural pattern recognition which studies the spatial gray level distribution with respect to certain rock types. FMS image intervals of rock classes known from core data are taken in order to train textural characteristics for each class. A so-called gray level co-occurrence matrix is computed by counting the occurrence of a pair of gray levels that are a certain distant apart. Once the matrix for an image interval is computed, we calculate the image contrast, homogeneity, energy, and entropy. We assign characteristic textural features to different rock types by reducing the image information into a small set of descriptive features. Once a discriminating set of texture features for each rock type is found, we are able to discriminate the entire FMS images regarding the trained rock type classification. A rock classification based on texture features enables quantitative lithology mapping and is characterized by a high repeatability, in contrast to a purely visual subjective image interpretation. We show examples for the rock classification between breccias, pillows, massive units, and horizontally bedded tuffs based on ODP image data.

Application of texture analysis method for mammogram density classification

NASA Astrophysics Data System (ADS)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Blaschke, Thomas; Tiede, Dirk; Moghaddam, Mohammad Hossein Rezaei

2017-09-01

This article presents a method of object-based image analysis (OBIA) for landslide delineation and landslide-related change detection from multi-temporal satellite images. It uses both spatial and spectral information on landslides, through spectral analysis, shape analysis, textural measurements using a gray-level co-occurrence matrix (GLCM), and fuzzy logic membership functionality. Following an initial segmentation step, particular combinations of various information layers were investigated to generate objects. This was achieved by applying multi-resolution segmentation to IRS-1D, SPOT-5, and ALOS satellite imagery in sequential steps of feature selection and object classification, and using slope and flow direction derivatives from a digital elevation model together with topographically-oriented gray level co-occurrence matrices. Fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data. Six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared. A Fuzzy Synthetic Evaluation (FSE) approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database. The FSE approach revealed that the AND operator performed best with an accuracy of 93.87% for 2005 and 94.74% for 2011, closely followed by the MEAN Arithmetic operator, while the OR and AND (*) operators yielded relatively low accuracies. An object-based change detection was then applied to monitor landslide-related changes that occurred in northern Iran between 2005 and 2011. Knowledge rules to detect possible landslide-related changes were developed by evaluating all possible landslide-related objects for both time steps.

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Diagnostic analysis of liver B ultrasonic texture features based on LM neural network

NASA Astrophysics Data System (ADS)

Chi, Qingyun; Hua, Hu; Liu, Menglin; Jiang, Xiuying

2017-03-01

In this study, B ultrasound images of 124 benign and malignant patients were randomly selected as the study objects. The B ultrasound images of the liver were treated by enhanced de-noising. By constructing the gray level co-occurrence matrix which reflects the information of each angle, Principal Component Analysis of 22 texture features were extracted and combined with LM neural network for diagnosis and classification. Experimental results show that this method is a rapid and effective diagnostic method for liver imaging, which provides a quantitative basis for clinical diagnosis of liver diseases.

Predicting neo-adjuvant chemotherapy response and progression-free survival of locally advanced breast cancer using textural features of intratumoral heterogeneity on F-18 FDG PET/CT and diffusion-weighted MR imaging.

PubMed

Yoon, Hai-Jeon; Kim, Yemi; Chung, Jin; Kim, Bom Sahn

2018-03-30

Predicting response to neo-adjuvant chemotherapy (NAC) and survival in locally advanced breast cancer (LABC) is important. This study investigated the prognostic value of tumor heterogeneity evaluated with textural analysis through F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and diffusion-weighted imaging (DWI). We enrolled 83 patients with LABC who had completed NAC and curative surgery. Tumor texture indices from pretreatment FDG PET and DWI were extracted from histogram analysis and 7 different parent matrices: co-occurrence matrix, the voxel-alignment matrix, neighborhood intensity difference matrix, intensity size-zone matrix (ISZM), normalized gray-level co-occurrence matrix (NGLCM), neighboring gray-level dependence matrix (NGLDM), and texture spectrum matrix. The predictive values of textural features were tested regarding both pathologic NAC response and progression-free survival. Among 83 patients, 46 were pathologic responders, while 37 were nonresponders. The PET texture indices from 7 parent matrices, DWI texture indices from histogram, and 1 parent matrix (NGLCM) showed significant differences according to NAC response. On multivariable analysis, number nonuniformity of PET extracted from the NGLDM was an independent predictor of pathologic response (P = .009). During a median follow-up period of 17.3 months, 14 patients experienced recurrence. High-intensity zone emphasis (HIZE) and high-intensity short-zone emphasis (HISZE) from PET extracted from ISZM were significant textural predictors (P = .011 and P = .033). On Cox regression analysis, only HIZE was a significant predictor of recurrence (P = .027), while HISZE showed borderline significance (P = .107). Tumor texture indices are useful for NAC response prediction in LABC. Moreover, PET texture indices can help to predict disease recurrence. © 2018 Wiley Periodicals, Inc.

Recognition of Roasted Coffee Bean Levels using Image Processing and Neural Network

NASA Astrophysics Data System (ADS)

Nasution, T. H.; Andayani, U.

2017-03-01

The coffee beans roast levels have some characteristics. However, some people cannot recognize the coffee beans roast level. In this research, we propose to design a method to recognize the coffee beans roast level of images digital by processing the image and classifying with backpropagation neural network. The steps consist of how to collect the images data with image acquisition, pre-processing, feature extraction using Gray Level Co-occurrence Matrix (GLCM) method and finally normalization of data extraction using decimal scaling features. The values of decimal scaling features become an input of classifying in backpropagation neural network. We use the method of backpropagation to recognize the coffee beans roast levels. The results showed that the proposed method is able to identify the coffee roasts beans level with an accuracy of 97.5%.

Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

NASA Astrophysics Data System (ADS)

Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

2016-03-01

This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.

Spoofing detection on facial images recognition using LBP and GLCM combination

NASA Astrophysics Data System (ADS)

Sthevanie, F.; Ramadhani, K. N.

2018-03-01

The challenge for the facial based security system is how to detect facial image falsification such as facial image spoofing. Spoofing occurs when someone try to pretend as a registered user to obtain illegal access and gain advantage from the protected system. This research implements facial image spoofing detection method by analyzing image texture. The proposed method for texture analysis combines the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) method. The experimental results show that spoofing detection using LBP and GLCM combination achieves high detection rate compared to that of using only LBP feature or GLCM feature.

A study on using texture analysis methods for identifying lobar fissure regions in isotropic CT images.

PubMed

Wei, Q; Hu, Y

2009-01-01

The major hurdle for segmenting lung lobes in computed tomographic (CT) images is to identify fissure regions, which encase lobar fissures. Accurate identification of these regions is difficult due to the variable shape and appearance of the fissures, along with the low contrast and high noise associated with CT images. This paper studies the effectiveness of two texture analysis methods - the gray level co-occurrence matrix (GLCM) and the gray level run length matrix (GLRLM) - in identifying fissure regions from isotropic CT image stacks. To classify GLCM and GLRLM texture features, we applied a feed-forward back-propagation neural network and achieved the best classification accuracy utilizing 16 quantized levels for computing the GLCM and GLRLM texture features and 64 neurons in the input/hidden layers of the neural network. Tested on isotropic CT image stacks of 24 patients with the pathologic lungs, we obtained accuracies of 86% and 87% for identifying fissure regions using the GLCM and GLRLM methods, respectively. These accuracies compare favorably with surgeons/radiologists' accuracy of 80% for identifying fissure regions in clinical settings. This shows promising potential for segmenting lung lobes using the GLCM and GLRLM methods.

SU-F-R-36: Validating Quantitative Radiomic Texture Features for Oncologic PET: A Digital Phantom Study

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

Yang, F; Yang, Y; Young, L

Purpose: Radiomic texture features derived from the oncologic PET have recently been brought under intense investigation within the context of patient stratification and treatment outcome prediction in a variety of cancer types; however, their validity has not yet been examined. This work is aimed to validate radiomic PET texture metrics through the use of realistic simulations in the ground truth setting. Methods: Simulation of FDG-PET was conducted by applying the Zubal phantom as an attenuation map to the SimSET software package that employs Monte Carlo techniques to model the physical process of emission imaging. A total of 15 irregularly-shaped lesionsmore » featuring heterogeneous activity distribution were simulated. For each simulated lesion, 28 texture features in relation to the intensity histograms (GLIH), grey-level co-occurrence matrices (GLCOM), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated and compared with their respective values extracted from the ground truth activity map. Results: In reference to the values from the ground truth images, texture parameters appearing on the simulated data varied with a range of 0.73–3026.2% for GLIH-based, 0.02–100.1% for GLCOM-based, 1.11–173.8% for GLNDM-based, and 0.35–66.3% for GLZSM-based. For majority of the examined texture metrics (16/28), their values on the simulated data differed significantly from those from the ground truth images (P-value ranges from <0.0001 to 0.04). Features not exhibiting significant difference comprised of GLIH-based standard deviation, GLCO-based energy and entropy, GLND-based coarseness and contrast, and GLZS-based low gray-level zone emphasis, high gray-level zone emphasis, short zone low gray-level emphasis, long zone low gray-level emphasis, long zone high gray-level emphasis, and zone size nonuniformity. Conclusion: The extent to which PET imaging disturbs texture appearance is feature-dependent and could be substantial. It is thus advised that use of PET texture parameters for predictive and prognostic measurements in oncologic setting awaits further systematic and critical evaluation.« less

Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC?

PubMed

Karacavus, Seyhan; Yılmaz, Bülent; Tasdemir, Arzu; Kayaaltı, Ömer; Kaya, Eser; İçer, Semra; Ayyıldız, Oguzhan

2018-04-01

We investigated the association between the textural features obtained from 18 F-FDG images, metabolic parameters (SUVmax , SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC). The FDG-PET images of 67 patients with NSCLC were evaluated. MATLAB technical computing language was employed in the extraction of 137 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), and Laws' texture filters. Textural features and metabolic parameters were statistically analyzed in terms of good discrimination power between tumor stages, and selected features/parameters were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). We showed that one textural feature (gray-level nonuniformity, GLN) obtained using GLRLM approach and nine textural features using Laws' approach were successful in discriminating all tumor stages, unlike metabolic parameters. There were significant correlations between Ki-67 index and some of the textural features computed using Laws' method (r = 0.6, p = 0.013). In terms of automatic classification of tumor stage, the accuracy was approximately 84% with k-NN classifier (k = 3) and SVM, using selected five features. Texture analysis of FDG-PET images has a potential to be an objective tool to assess tumor histopathological characteristics. The textural features obtained using Laws' approach could be useful in the discrimination of tumor stage.

An Appraisal of the Occurrence of the More Serious Tree Pests and Infectious Diseases in Poland in 1980 and a Forecast of Their Appearance in 1981,

DTIC Science & Technology

1982-10-28

122 2. Verticillium deciduous tree wilt (Verticillium alboatrum) ...... 124 3. Gray mold rot of conifer seedlings ( Botrytis cinerea ...or Botrytis cinerea . The overall occurrence of seedling wilt disease in young forest tree nur- series is shown in Table 53. Parasitic seedling wilt...successive years. 3. Gray mold rot of conifer seedlings ( Botrytis cinerea ) The occurrence of conifer seedling gray mold rot was confirmed on black pine

Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

NASA Astrophysics Data System (ADS)

Wutsqa, D. U.; Marwah, M.

2017-06-01

In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

Feature detection in satellite images using neural network technology

NASA Technical Reports Server (NTRS)

Augusteijn, Marijke F.; Dimalanta, Arturo S.

1992-01-01

A feasibility study of automated classification of satellite images is described. Satellite images were characterized by the textures they contain. In particular, the detection of cloud textures was investigated. The method of second-order gray level statistics, using co-occurrence matrices, was applied to extract feature vectors from image segments. Neural network technology was employed to classify these feature vectors. The cascade-correlation architecture was successfully used as a classifier. The use of a Kohonen network was also investigated but this architecture could not reliably classify the feature vectors due to the complicated structure of the classification problem. The best results were obtained when data from different spectral bands were fused.

Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.

PubMed

Altazi, Baderaldeen A; Zhang, Geoffrey G; Fernandez, Daniel C; Montejo, Michael E; Hunt, Dylan; Werner, Joan; Biagioli, Matthew C; Moros, Eduardo G

2017-11-01

Site-specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18 Flourine-fluorodeoxyglucose ( 18 F-FDG) PET images for three parameters: manual versus computer-aided segmentation methods, gray-level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board-certified radiation oncologists manually segmented the metabolic tumor volume (MTV 1 and MTV 2 ) for each patient. For comparison, we used a graphical-based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down-sampled the tumor volumes into three gray-levels: 32, 64, and 128 from the original gray-level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D-reconstruction algorithms: maximum likelihood-ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning-ML-OSEM (FOREIR), FORE-filtered back projection (FOREFBP), and 3D-Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray-levels of down-sampled volumes, and PET reconstruction algorithms. The features were extracted using gray-level co-occurrence matrices (GLCM), gray-level size zone matrices (GLSZM), gray-level run-length matrices (GLRLM), neighborhood gray-tone difference matrices (NGTDM), shape-based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV 1 -MTV 2 , MTV 1 -GBSV, MTV 2 -GBSV; gray-levels: 64-32, 64-128, and 64-256; reconstruction algorithms: OSEM-FORE-OSEM, OSEM-FOREFBP, and OSEM-3DRP). We used |d¯| as a measure of radiomic feature reproducibility level, where any feature scored |d¯| ±SD ≤ |25|% ± 35% was considered reproducible. We used Bland-Altman analysis to evaluate the mean, standard deviation (SD), and upper/lower reproducibility limits (U/LRL) for radiomic features in response to variation in each testing parameter. Furthermore, we proposed U/LRL as a method to classify the level of reproducibility: High- ±1% ≤ U/LRL ≤ ±30%; Intermediate- ±30% < U/LRL ≤ ±45%; Low- ±45 < U/LRL ≤ ±50%. We considered any feature below the low level as nonreproducible (NR). Finally, we calculated the interclass correlation coefficient (ICC) to evaluate the reliability of radiomic feature measurements for each parameter. The segmented volumes of 65 patients (81.3%) scored Dice coefficient >0.75 for all three volumes. The result outcomes revealed a tendency of higher radiomic feature reproducibility among segmentation pair MTV 1 -GBSV than MTV 2 -GBSV, gray-level pairs of 64-32 and 64-128 than 64-256, and reconstruction algorithm pairs of OSEM-FOREIR and OSEM-FOREFBP than OSEM-3DRP. Although the choice of cervical tumor segmentation method, gray-level value, and reconstruction algorithm may affect radiomic features, some features were characterized by high reproducibility through all testing parameters. The number of radiomic features that showed insensitivity to variations in segmentation methods, gray-level discretization, and reconstruction algorithms was 10 (13%), 4 (5%), and 1 (1%), respectively. These results suggest that a careful analysis of the effects of these parameters is essential prior to any radiomics clinical application. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Influence of temperature variations on the entropy and correlation of the Grey-Level Co-occurrence Matrix from B-Mode images.

PubMed

Alvarenga, André V; Teixeira, César A; Ruano, Maria Graça; Pereira, Wagner C A

2010-02-01

In this work, the feasibility of texture parameters extracted from B-Mode images were explored in quantifying medium temperature variation. The goal is to understand how parameters obtained from the gray-level content can be used to improve the actual state-of-the-art methods for non-invasive temperature estimation (NITE). B-Mode images were collected from a tissue mimic phantom heated in a water bath. The phantom is a mixture of water, glycerin, agar-agar and graphite powder. This mixture aims to have similar acoustical properties to in vivo muscle. Images from the phantom were collected using an ultrasound system that has a mechanical sector transducer working at 3.5 MHz. Three temperature curves were collected, and variations between 27 and 44 degrees C during 60 min were allowed. Two parameters (correlation and entropy) were determined from Grey-Level Co-occurrence Matrix (GLCM) extracted from image, and then assessed for non-invasive temperature estimation. Entropy values were capable of identifying variations of 2.0 degrees C. Besides, it was possible to quantify variations from normal human body temperature (37 degrees C) to critical values, as 41 degrees C. In contrast, despite correlation parameter values (obtained from GLCM) presented a correlation coefficient of 0.84 with temperature variation, the high dispersion of values limited the temperature assessment.

Marine Stratocumulus Cloud Fields off the Coast of Southern California Observed Using LANDSAT Imagery. Part II: Textural Analysis.

NASA Astrophysics Data System (ADS)

Welch, R. M.; Sengupta, S. K.; Kuo, K. S.

1988-04-01

Statistical measures of the spatial distributions of gray levels (cloud reflectivities) are determined for LANDSAT Multispectral Scanner digital data. Textural properties for twelve stratocumulus cloud fields, seven cumulus fields, and two cirrus fields are examined using the Spatial Gray Level Co-Occurrence Matrix method. The co-occurrence statistics are computed for pixel separations ranging from 57 m to 29 km and at angles of 0°, 45°, 90° and 135°. Nine different textual measures are used to define the cloud field spatial relationships. However, the measures of contrast and correlation appear to be most useful in distinguishing cloud structure.Cloud field macrotexture describes general cloud field characteristics at distances greater than the size of typical cloud elements. It is determined from the spatial asymptotic values of the texture measures. The slope of the texture curves at small distances provides a measure of the microtexture of individual cloud cells. Cloud fields composed primarily of small cells have very steep slopes and reach their asymptotic values at short distances from the origin. As the cells composing the cloud field grow larger, the slope becomes more gradual and the asymptotic distance increases accordingly. Low asymptotic values of correlation show that stratocumulus cloud fields have no large scale organized structure.Besides the ability to distinguish cloud field structure, texture appears to be a potentially valuable tool in cloud classification. Stratocumulus clouds are characterized by low values of angular second moment and large values of entropy. Cirrus clouds appear to have extremely low values of contrast, low values of entropy, and very large values of correlation.Finally, we propose that sampled high spatial resolution satellite data be used in conjunction with coarser resolution operational satellite data to detect and identify cloud field structure and directionality and to locate regions of subresolution scale cloud contamination.

Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer.

PubMed

Garcia-Vicente, Ana María; Molina, David; Pérez-Beteta, Julián; Amo-Salas, Mariano; Martínez-González, Alicia; Bueno, Gloria; Tello-Galán, María Jesús; Soriano-Castrejón, Ángel

2017-12-01

To study the influence of dual time point 18F-FDG PET/CT in textural features and SUV-based variables and their relation among them. Fifty-six patients with locally advanced breast cancer (LABC) were prospectively included. All of them underwent a standard 18F-FDG PET/CT (PET-1) and a delayed acquisition (PET-2). After segmentation, SUV variables (SUVmax, SUVmean, and SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained. Eighteen three-dimensional (3D) textural measures were computed including: run-length matrices (RLM) features, co-occurrence matrices (CM) features, and energies. Differences between all PET-derived variables obtained in PET-1 and PET-2 were studied. Significant differences were found between the SUV-based parameters and MTV obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1. In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run emphasis, gray-level non-uniformity, homogeneity, and dissimilarity. Textural variables showed relations with MTV and TLG. Significant differences of textural features were found in dual time point 18F-FDG PET/CT. Thus, a dynamic behavior of metabolic characteristics should be expected, with higher heterogeneity in delayed PET acquisition compared with the standard PET. A greater heterogeneity was found in bigger tumors.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

PubMed

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

Fingerprint recognition of alien invasive weeds based on the texture character and machine learning

NASA Astrophysics Data System (ADS)

Yu, Jia-Jia; Li, Xiao-Li; He, Yong; Xu, Zheng-Hao

2008-11-01

Multi-spectral imaging technique based on texture analysis and machine learning was proposed to discriminate alien invasive weeds with similar outline but different categories. The objectives of this study were to investigate the feasibility of using Multi-spectral imaging, especially the near-infrared (NIR) channel (800 nm+/-10 nm) to find the weeds' fingerprints, and validate the performance with specific eigenvalues by co-occurrence matrix. Veronica polita Pries, Veronica persica Poir, longtube ground ivy, Laminum amplexicaule Linn. were selected in this study, which perform different effect in field, and are alien invasive species in China. 307 weed leaves' images were randomly selected for the calibration set, while the remaining 207 samples for the prediction set. All images were pretreated by Wallis filter to adjust the noise by uneven lighting. Gray level co-occurrence matrix was applied to extract the texture character, which shows density, randomness correlation, contrast and homogeneity of texture with different algorithms. Three channels (green channel by 550 nm+/-10 nm, red channel by 650 nm+/-10 nm and NIR channel by 800 nm+/-10 nm) were respectively calculated to get the eigenvalues.Least-squares support vector machines (LS-SVM) was applied to discriminate the categories of weeds by the eigenvalues from co-occurrence matrix. Finally, recognition ratio of 83.35% by NIR channel was obtained, better than the results by green channel (76.67%) and red channel (69.46%). The prediction results of 81.35% indicated that the selected eigenvalues reflected the main characteristics of weeds' fingerprint based on multi-spectral (especially by NIR channel) and LS-SVM model.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Sensitive indicators of Stipa bungeana response to precipitation under ambient and elevated CO2 concentration

NASA Astrophysics Data System (ADS)

Shi, Yaohui; Zhou, Guangsheng; Jiang, Yanling; Wang, Hui; Xu, Zhenzhu

2018-02-01

Precipitation is a primary environmental factor in the semiarid grasslands of northern China. With increased concentrations of atmospheric greenhouse gases, precipitation regimes will change, and high-impact weather events may be more common. Currently, many ecophysiological indicators are known to reflect drought conditions, but these indicators vary greatly among species, and few studies focus on the applicability of these drought indicators under high CO2 conditions. In this study, five precipitation levels (- 30%, - 15%, control, + 15%, and + 30%) were used to simulate the effects of precipitation change on 18 ecophysiological characteristics in Stipa bungeana, including leaf area, plant height, leaf nitrogen (N), and chlorophyll content, among others. Two levels of CO2 concentration (ambient, 390 ppm; 550 ppm) were used to simulate the effects of elevated CO2 on these drought indicators. Using gray relational analysis and phenotypic plasticity analysis, we found that total leaf area or leaf number (morphology), leaf water potential or leaf water content (physiology), and aboveground biomass better reflected the water status of S. bungeana under ambient and elevated CO2 than the 13 other analyzed variables. The sensitivity of drought indicators changed under the elevated CO2 condition. By quantifying the relationship between precipitation and the five most sensitive indicators, we found that the thresholds of precipitation decreased under elevated CO2 concentration. These results will be useful for objective monitoring and assessment of the occurrence and development of drought events in S. bungeana grasslands.

Shell feature: a new radiomics descriptor for predicting distant failure after radiotherapy in non-small cell lung cancer and cervix cancer

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Li, Shulong; Maquilan, Genevieve; Folkert, Michael R.; Iyengar, Puneeth; Westover, Kenneth D.; Albuquerque, Kevin; Liu, Fang; Choy, Hak; Timmerman, Robert; Yang, Lin; Wang, Jing

2018-05-01

Distant failure is the main cause of human cancer-related mortalities. To develop a model for predicting distant failure in non-small cell lung cancer (NSCLC) and cervix cancer (CC) patients, a shell feature, consisting of outer voxels around the tumor boundary, was constructed using pre-treatment positron emission tomography (PET) images from 48 NSCLC patients received stereotactic body radiation therapy and 52 CC patients underwent external beam radiation therapy and concurrent chemotherapy followed with high-dose-rate intracavitary brachytherapy. The hypothesis behind this feature is that non-invasive and invasive tumors may have different morphologic patterns in the tumor periphery, in turn reflecting the differences in radiological presentations in the PET images. The utility of the shell was evaluated by the support vector machine classifier in comparison with intensity, geometry, gray level co-occurrence matrix-based texture, neighborhood gray tone difference matrix-based texture, and a combination of these four features. The results were assessed in terms of accuracy, sensitivity, specificity, and AUC. Collectively, the shell feature showed better predictive performance than all the other features for distant failure prediction in both NSCLC and CC cohorts.

Demonstrating microbial co-occurrence pattern analyses within and between ecosystems

PubMed Central

Williams, Ryan J.; Howe, Adina; Hofmockel, Kirsten S.

2014-01-01

Co-occurrence patterns are used in ecology to explore interactions between organisms and environmental effects on coexistence within biological communities. Analysis of co-occurrence patterns among microbial communities has ranged from simple pairwise comparisons between all community members to direct hypothesis testing between focal species. However, co-occurrence patterns are rarely studied across multiple ecosystems or multiple scales of biological organization within the same study. Here we outline an approach to produce co-occurrence analyses that are focused at three different scales: co-occurrence patterns between ecosystems at the community scale, modules of co-occurring microorganisms within communities, and co-occurring pairs within modules that are nested within microbial communities. To demonstrate our co-occurrence analysis approach, we gathered publicly available 16S rRNA amplicon datasets to compare and contrast microbial co-occurrence at different taxonomic levels across different ecosystems. We found differences in community composition and co-occurrence that reflect environmental filtering at the community scale and consistent pairwise occurrences that may be used to infer ecological traits about poorly understood microbial taxa. However, we also found that conclusions derived from applying network statistics to microbial relationships can vary depending on the taxonomic level chosen and criteria used to build co-occurrence networks. We present our statistical analysis and code for public use in analysis of co-occurrence patterns across microbial communities. PMID:25101065

Overlaid caption extraction in news video based on SVM

NASA Astrophysics Data System (ADS)

Liu, Manman; Su, Yuting; Ji, Zhong

2007-11-01

Overlaid caption in news video often carries condensed semantic information which is key cues for content-based video indexing and retrieval. However, it is still a challenging work to extract caption from video because of its complex background and low resolution. In this paper, we propose an effective overlaid caption extraction approach for news video. We first scan the video key frames using a small window, and then classify the blocks into the text and non-text ones via support vector machine (SVM), with statistical features extracted from the gray level co-occurrence matrices, the LH and HL sub-bands wavelet coefficients and the orientated edge intensity ratios. Finally morphological filtering and projection profile analysis are employed to localize and refine the candidate caption regions. Experiments show its high performance on four 30-minute news video programs.

Tropical Timber Identification using Backpropagation Neural Network

NASA Astrophysics Data System (ADS)

Siregar, B.; Andayani, U.; Fatihah, N.; Hakim, L.; Fahmi, F.

2017-01-01

Each and every type of wood has different characteristics. Identifying the type of wood properly is important, especially for industries that need to know the type of timber specifically. However, it requires expertise in identifying the type of wood and only limited experts available. In addition, the manual identification even by experts is rather inefficient because it requires a lot of time and possibility of human errors. To overcome these problems, a digital image based method to identify the type of timber automatically is needed. In this study, backpropagation neural network is used as artificial intelligence component. Several stages were developed: a microscope image acquisition, pre-processing, feature extraction using gray level co-occurrence matrix and normalization of data extraction using decimal scaling features. The results showed that the proposed method was able to identify the timber with an accuracy of 94%.

Efficient video-equipped fire detection approach for automatic fire alarm systems

NASA Astrophysics Data System (ADS)

Kang, Myeongsu; Tung, Truong Xuan; Kim, Jong-Myon

2013-01-01

This paper proposes an efficient four-stage approach that automatically detects fire using video capabilities. In the first stage, an approximate median method is used to detect video frame regions involving motion. In the second stage, a fuzzy c-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and nonfire. Experimental results indicate that the proposed four-stage approach outperforms other fire detection algorithms in terms of consistently increasing the accuracy of fire detection in both indoor and outdoor test videos.

SU-E-E-16: The Application of Texture Analysis for Differentiation of Central Cancer From Atelectasis

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

Gao, M; Fan, T; Duan, J

2015-06-15

Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET-CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET-CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co-occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05).more » Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.« less

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

The Effects of Daily Co-Occurrence of Affect on Older Adults’ Reactivity to Health Stressors

PubMed Central

Ramsey, Jennifer L.; Neupert, Shevaun D.; Mroczek, Daniel K.; Spiro, Avron

2015-01-01

Objectives The present study examined age differences among older adults in the daily co-occurrence of affect and its potential role in buffering the negative effects of health stressors. Design Participants were from the Veterans Affairs Normative Aging Study (NAS) and included 249 young-old adults (age = 60–79 years, M=71.6) and 64 old-old adults (age = 80–89, M = 82.9) who completed questionnaires assessing stressors, physical health symptoms, and positive and negative affect on eight consecutive days. Results An independent samples t-test showed young-old and old-old adults did not significantly differ in their mean levels of daily co-occurrence of affect. The between-person relationships among stressors, health, and daily co-occurrence of affect revealed that neither stressors nor health were significantly related to daily co-occurrence of affect. However, results from a multilevel model revealed a three-way cross-level interaction (Health Stressor X Age Group X Co-Occurrence of Affect) where old-old adults with higher levels of co-occurrence of affect were less emotionally reactive to health stressors than young-old adults. Conclusion These findings provide support for the assertion that co-occurrence of affect functions in an adaptive capacity and highlight the importance of examining domain specific stressors. PMID:26518259

The effects of daily co-occurrence of affect on older adults' reactivity to health stressors.

PubMed

Ramsey, Jennifer L; Neupert, Shevaun D; Mroczek, Daniel K; Spiro, Avron

2016-01-01

The present study examined age differences among older adults in the daily co-occurrence of affect and its potential role in buffering the negative effects of health stressors. Participants were from the Veterans Affairs Normative Aging Study and included 249 young-old adults (age = 60-79 years, M = 71.6) and 64 old-old adults (age = 80-89, M = 82.9) who completed questionnaires assessing stressors, physical health symptoms, and positive and negative affect for eight consecutive days. An independent samples t-test showed young-old and old-old adults did not significantly differ in their mean levels of daily co-occurrence of affect. The between-person relationships among stressors, health and daily co-occurrence of affect revealed that neither stressors nor health were significantly related to daily co-occurrence of affect. However, results from a multilevel model revealed a three-way cross-level interaction (health stressor × age group × co-occurrence of affect) where old-old adults with higher levels of co-occurrence of affect were less emotionally reactive to health stressors than young-old adults. These findings provide support for the assertion that co-occurrence of affect functions in an adaptive capacity and highlight the importance of examining domain-specific stressors.

Measurement of Vibrated Bulk Density of Coke Particle Blends Using Image Texture Analysis

NASA Astrophysics Data System (ADS)

Azari, Kamran; Bogoya-Forero, Wilinthon; Duchesne, Carl; Tessier, Jayson

2017-09-01

A rapid and nondestructive machine vision sensor was developed for predicting the vibrated bulk density (VBD) of petroleum coke particles based on image texture analysis. It could be used for making corrective adjustments to a paste plant operation to reduce green anode variability (e.g., changes in binder demand). Wavelet texture analysis (WTA) and gray level co-occurrence matrix (GLCM) algorithms were used jointly for extracting the surface textural features of coke aggregates from images. These were correlated with the VBD using partial least-squares (PLS) regression. Coke samples of several sizes and from different sources were used to test the sensor. Variations in the coke surface texture introduced by coke size and source allowed for making good predictions of the VBD of individual coke samples and mixtures of them (blends involving two sources and different sizes). Promising results were also obtained for coke blends collected from an industrial-baked carbon anode manufacturer.

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

PubMed Central

Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

2014-01-01

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM). PMID:24940551

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images.

PubMed

Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

2014-06-01

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM).

Comparing the role of shape and texture on staging hepatic fibrosis from medical imaging

NASA Astrophysics Data System (ADS)

Zhang, Xuejun; Louie, Ryan; Liu, Brent J.; Gao, Xin; Tan, Xiaomin; Qu, Xianghe; Long, Liling

2016-03-01

The purpose of this study is to investigate the role of shape and texture in the classification of hepatic fibrosis by selecting the optimal parameters for a better Computer-aided diagnosis (CAD) system. 10 surface shape features are extracted from a standardized profile of liver; while15 texture features calculated from gray level co-occurrence matrix (GLCM) are extracted within an ROI in liver. Each combination of these input subsets is checked by using support vector machine (SVM) with leave-one-case-out method to differentiate fibrosis into two groups: normal or abnormal. The accurate rate value of all 10/15 types number of features is 66.83% by texture, while 85.74% by shape features, respectively. The irregularity of liver shape can demonstrate fibrotic grade efficiently and texture feature of CT image is not recommended to use with shape feature for interpretation of cirrhosis.

Monitoring Progression of Amyotrophic Lateral Sclerosis Using Ultrasound Morpho-Textural Muscle Biomarkers: A Pilot Study.

PubMed

Martínez-Payá, Jacinto J; Ríos-Díaz, José; Medina-Mirapeix, Francesc; Vázquez-Costa, Juan F; Del Baño-Aledo, María Elena

2018-01-01

The need is increasing for progression biomarkers that allow the loss of motor neurons in amyotrophic lateral sclerosis (ALS) to be monitored in clinical trials. In this prospective longitudinal study, muscle thickness, echointensity, echovariation and gray level co-occurrence matrix textural features are examined as possible progression ultrasound biomarkers in ALS patients during a 5-mo follow-up period. We subjected 13 patients to 3 measurements for 20 wk. They showed a significant loss of muscle, an evident tendency to loss of thickness and increased echointensity and echovariation. In regard to textural parameters, muscle heterogeneity tended to increase as a result of the neoformation of non-contractile tissue through denervation. Considering some limitations of the study, the quantitative muscle ultrasound biomarkers evaluated showed a promising ability to monitor patients affected by ALS. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Rapid extraction of image texture by co-occurrence using a hybrid data structure

NASA Astrophysics Data System (ADS)

Clausi, David A.; Zhao, Yongping

2002-07-01

Calculation of co-occurrence probabilities is a popular method for determining texture features within remotely sensed digital imagery. Typically, the co-occurrence features are calculated by using a grey level co-occurrence matrix (GLCM) to store the co-occurring probabilities. Statistics are applied to the probabilities in the GLCM to generate the texture features. This method is computationally intensive since the matrix is usually sparse leading to many unnecessary calculations involving zero probabilities when applying the statistics. An improvement on the GLCM method is to utilize a grey level co-occurrence linked list (GLCLL) to store only the non-zero co-occurring probabilities. The GLCLL suffers since, to achieve preferred computational speeds, the list should be sorted. An improvement on the GLCLL is to utilize a grey level co-occurrence hybrid structure (GLCHS) based on an integrated hash table and linked list approach. Texture features obtained using this technique are identical to those obtained using the GLCM and GLCLL. The GLCHS method is implemented using the C language in a Unix environment. Based on a Brodatz test image, the GLCHS method is demonstrated to be a superior technique when compared across various window sizes and grey level quantizations. The GLCHS method required, on average, 33.4% ( σ=3.08%) of the computational time required by the GLCLL. Significant computational gains are made using the GLCHS method.

Quantifying neighbourhood socioeconomic effects in clustering of behaviour-related risk factors: a multilevel analysis.

PubMed

Halonen, Jaana I; Kivimäki, Mika; Pentti, Jaana; Kawachi, Ichiro; Virtanen, Marianna; Martikainen, Pekka; Subramanian, S V; Vahtera, Jussi

2012-01-01

The extent to which neighbourhood characteristics explain accumulation of health behaviours is poorly understood. We examined whether neighbourhood disadvantage was associated with co-occurrence of behaviour-related risk factors, and how much of the neighbourhood differences in the co-occurrence can be explained by individual and neighbourhood level covariates. The study population consisted of 60 694 Finnish Public Sector Study participants in 2004 and 2008. Neighbourhood disadvantage was determined using small-area level information on household income, education attainment, and unemployment rate, and linked with individual data using Global Positioning System-coordinates. Associations between neighbourhood disadvantage and co-occurrence of three behaviour-related risk factors (smoking, heavy alcohol use, and physical inactivity), and the extent to which individual and neighbourhood level covariates explain neighbourhood differences in co-occurrence of risk factors were determined with multilevel cumulative logistic regression. After adjusting for age, sex, marital status, and population density we found a dose-response relationship between neighbourhood disadvantage and co-occurrence of risk factors within each level of individual socioeconomic status. The cumulative odds ratios for the sum of health risks comparing the most to the least disadvantaged neighbourhoods ranged between 1.13 (95% confidence interval (CI): 1.03-1.24) and 1.75 (95% CI, 1.54-1.98). Individual socioeconomic characteristics explained 35%, and neighbourhood disadvantage and population density 17% of the neighbourhood differences in the co-occurrence of risk factors. Co-occurrence of poor health behaviours associated with neighbourhood disadvantage over and above individual's own socioeconomic status. Neighbourhood differences cannot be captured using individual socioeconomic factors alone, but neighbourhood level characteristics should also be considered.

Differentiation of the drying time of adhesives on plywoods through the dynamic speckle technique

NASA Astrophysics Data System (ADS)

Kumari, S.; Nirala, A. K.

2018-02-01

The drying time of adhesives such as Fevicol SH, Fevicol MR, Dendrite white and Bulbond after coating separately on the three plywoods, namely Archidply, Centuryply and Greenply, has been studied non-destructively using the dynamic speckle technique. The time history of the speckle pattern, the co-occurrence matrix, 3D graphs and line profiles of images from the time history of the speckle pattern along with 3D trajectory plots have been used for qualitative analysis whereas the inertia moment, absolute value difference, SM index and autocovariance have been used for quantitative analysis. The gray-level co-occurrence matrix has been used for the first time to study the textual parameters of adhesive coated on plywoods during drying. The average drying time of adhesive is a maximum for Bulbond on Archidply (357.25  ±  1.49 min) and a minimum for Dendrite white on Greenply (90.75  ±  2.36 min). Comparative studies among the results obtained for all the four adhesives on the three plywoods reveal that Dendrite white adhesive is the best among the adhesives because it takes the shortest time to dry on all the plywoods, and Greenply is the best among all the plywoods because drying is fastest on it for all the adhesives. Furthermore, it is also concluded that the best plywood and the best adhesive may be decided by knowing the remnant activity.

Gray Matter-White Matter De-Differentiation on Brain Computed Tomography Predicts Brain Death Occurrence.

PubMed

Vigneron, C; Labeye, V; Cour, M; Hannoun, S; Grember, A; Rampon, F; Cotton, F

2016-01-01

Previous studies have shown that a loss of distinction between gray matter (GM) and white matter (WM) on unenhanced CT scans was predictive of poor outcome after cardiac arrest. The aim of this study was to identify a marker/predictor of imminent brain death. In this retrospective study, 15 brain-dead patients after anoxia and cardiac arrest were included. Patients were paired (1:1) with normal control subjects. Only patients' unenhanced CT scans performed before brain death and during the 24 hours after initial signs were analyzed. WM and GM densities were measured in predefined regions of interest (basal ganglia level, centrum semi-ovale level, high convexity level, brainstem level). At each level, GM and WM density and GM/WM ratio for brain-dead patients and normal control subjects were compared using the Wilcoxon signed-rank test. At each level, a lower GM/WM ratio and decreased GM and WM densities were observed in brain-dead patients' CT scans when compared with normal control subject CT scans. A cut-off value of 1.21 at the basal ganglia level was identified, below which brain death systematically occurred. GM/WM dedifferentiation on unenhanced CT scan is measurable before the occurrence of brain death, highlighting its importance in brain death prediction. The mechanism of GM/WM differentiation loss could be explained by the lack of oxygen caused by ischemia initially affecting the mitochondrial system. Copyright © 2016 Elsevier Inc. All rights reserved.

Correction method for stripe nonuniformity.

PubMed

Qian, Weixian; Chen, Qian; Gu, Guohua; Guan, Zhiqiang

2010-04-01

Stripe nonuniformity is very typical in line infrared focal plane arrays (IR-FPA) and uncooled staring IR-FPA. In this paper, the mechanism of the stripe nonuniformity is analyzed, and the gray-scale co-occurrence matrix theory and optimization theory are studied. Through these efforts, the stripe nonuniformity correction problem is translated into the optimization problem. The goal of the optimization is to find the minimal energy of the image's line gradient. After solving the constrained nonlinear optimization equation, the parameters of the stripe nonuniformity correction are obtained and the stripe nonuniformity correction is achieved. The experiments indicate that this algorithm is effective and efficient.

Quantitative evaluation methods of skin condition based on texture feature parameters.

PubMed

Pang, Hui; Chen, Tianhua; Wang, Xiaoyi; Chang, Zhineng; Shao, Siqi; Zhao, Jing

2017-03-01

In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM) is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Hall, Lawrence O.; Goldgof, Dmitry B.; Gatenby, Robert A.; Gillies, Robert; Drukteinis, Jennifer S.

2014-03-01

Magnetic Resonance Imaging (MRI) of breast cancer typically shows that tumors are heterogeneous with spatial variations in blood flow and cell density. Here, we examine the potential link between clinical tumor imaging and the underlying evolutionary dynamics behind heterogeneity in the cellular expression of estrogen receptors (ER) in breast cancer. We assume, in an evolutionary environment, that ER expression will only occur in the presence of significant concentrations of estrogen, which is delivered via the blood stream. Thus, we hypothesize, the expression of ER in breast cancer cells will correlate with blood flow on gadolinium enhanced breast MRI. To test this hypothesis, we performed quantitative analysis of blood flow on dynamic contrast enhanced MRI (DCE-MRI) and correlated it with the ER status of the tumor. Here we present our analytic methods, which utilize a novel algorithm to analyze 20 volumetric DCE-MRI breast cancer tumors. The algorithm generates post initial enhancement (PIE) maps from DCE-MRI and then performs texture features extraction from the PIE map, feature selection, and finally classification of tumors into ER positive and ER negative status. The combined gray level co-occurrence matrices, gray level run length matrices and local binary pattern histogram features allow quantification of breast tumor heterogeneity. The algorithm predicted ER expression with an accuracy of 85% using a Naive Bayes classifier in leave-one-out cross-validation. Hence, we conclude that our data supports the hypothesis that imaging characteristics can, through application of evolutionary principles, provide insights into the cellular and molecular properties of cancer cells.

The co-occurrence of autistic traits and borderline personality disorder traits is associated to increased suicidal ideation in nonclinical young adults.

PubMed

Chabrol, Henri; Raynal, Patrick

2018-04-01

The co-occurrence of Autism Spectrum Disorder (ASD) and Borderline Personality Disorder (BPD) is not rare and has been linked to increased suicidality. Despite this significant comorbidity between ASD and BPD, no study had examined the co-occurrence of autistic traits and borderline personality disorder traits in the general population. The aim of the present study was to examine the co-occurrence of autistic and borderline traits in a non-clinical sample of young adults and its influence on the levels of suicidal ideation and depressive symptomatology. Participants were 474 college students who completed self-report questionnaires. Data were analysed using correlation and cluster analyses. Borderline personality traits and autistic traits were weakly correlated. However, cluster analysis yielded four groups: a low traits group, a borderline traits group, an autistic traits group, and a group characterized by high levels of both traits. Cluster analysis revealed that autistic and borderline traits can co-occur in a significant proportion of young adults. The high autistic and borderline traits group constituted 17% of the total sample and had higher level of suicidal ideation than the borderline traits group, despite similar levels of depressive symptoms. This result suggests that the higher suicidality observed in patients with comorbid ASD and BPD may extent to non-clinical individuals with high levels of co-occurrent autistic and borderline traits. Copyright © 2018 Elsevier Inc. All rights reserved.

Profiling pleural effusion cells by a diffraction imaging method

NASA Astrophysics Data System (ADS)

Al-Qaysi, Safaa; Hong, Heng; Wen, Yuhua; Lu, Jun Q.; Feng, Yuanming; Hu, Xin-Hua

2018-02-01

Assay of cells in pleural effusion (PE) is an important means of disease diagnosis. Conventional cytology of effusion samples, however, has low sensitivity and depends heavily on the expertise of cytopathologists. We applied a polarization diffraction imaging flow cytometry method on effusion cells to investigate their features. Diffraction imaging of the PE cell samples has been performed on 6000 to 12000 cells for each effusion cell sample of three patients. After prescreening to remove images by cellular debris and aggregated non-cellular particles, the image textures were extracted with a gray level co-occurrence matrix (GLCM) algorithm. The distribution of the imaged cells in the GLCM parameters space was analyzed by a Gaussian Mixture Model (GMM) to determine the number of clusters among the effusion cells. These results yield insight on textural features of diffraction images and related cellular morphology in effusion samples and can be used toward the development of a label-free method for effusion cells assay.

CAD scheme for detection of hemorrhages and exudates in ocular fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Mizukusa, Yutaka; Fujita, Akihiro; Kakogawa, Masakatsu; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2007-03-01

This paper describes a method for detecting hemorrhages and exudates in ocular fundus images. The detection of hemorrhages and exudates is important in order to diagnose diabetic retinopathy. Diabetic retinopathy is one of the most significant factors contributing to blindness, and early detection and treatment are important. In this study, hemorrhages and exudates were automatically detected in fundus images without using fluorescein angiograms. Subsequently, the blood vessel regions incorrectly detected as hemorrhages were eliminated by first examining the structure of the blood vessels and then evaluating the length-to-width ratio. Finally, the false positives were eliminated by checking the following features extracted from candidate images: the number of pixels, contrast, 13 features calculated from the co-occurrence matrix, two features based on gray-level difference statistics, and two features calculated from the extrema method. The sensitivity of detecting hemorrhages in the fundus images was 85% and that of detecting exudates was 77%. Our fully automated scheme could accurately detect hemorrhages and exudates.

Textural content in 3T MR: an image-based marker for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Bharath Kumar, S. V.; Mullick, Rakesh; Patil, Uday

2005-04-01

In this paper, we propose a study, which investigates the first-order and second-order distributions of T2 images from a magnetic resonance (MR) scan for an age-matched data set of 24 Alzheimer's disease and 17 normal patients. The study is motivated by the desire to analyze the brain iron uptake in the hippocampus of Alzheimer's patients, which is captured by low T2 values. Since, excess iron deposition occurs locally in certain regions of the brain, we are motivated to investigate the spatial distribution of T2, which is captured by higher-order statistics. Based on the first-order and second-order distributions (involving gray level co-occurrence matrix) of T2, we show that the second-order statistics provide features with sensitivity >90% (at 80% specificity), which in turn capture the textural content in T2 data. Hence, we argue that different texture characteristics of T2 in the hippocampus for Alzheimer's and normal patients could be used as an early indicator of Alzheimer's disease.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

PubMed

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

Non-destructive assessment of instrumental and sensory tenderness of lamb meat using NIR hyperspectral imaging.

PubMed

Kamruzzaman, Mohammed; Elmasry, Gamal; Sun, Da-Wen; Allen, Paul

2013-11-01

The purpose of this study was to develop and test a hyperspectral imaging system (900-1700 nm) to predict instrumental and sensory tenderness of lamb meat. Warner-Bratzler shear force (WBSF) values and sensory scores by trained panellists were collected as the indicator of instrumental and sensory tenderness, respectively. Partial least squares regression models were developed for predicting instrumental and sensory tenderness with reasonable accuracy (Rcv=0.84 for WBSF and 0.69 for sensory tenderness). Overall, the results confirmed that the spectral data could become an interesting screening tool to quickly categorise lamb steaks in good (i.e. tender) and bad (i.e. tough) based on WBSF values and sensory scores with overall accuracy of about 94.51% and 91%, respectively. Successive projections algorithm (SPA) was used to select the most important wavelengths for WBSF prediction. Additionally, textural features from Gray Level Co-occurrence Matrix (GLCM) were extracted to determine the correlation between textural features and WBSF values. Copyright © 2013 Elsevier Ltd. All rights reserved.

An authentic record of Eutropis bibronii (Gray, 1838) (Reptilia: Scincidae) from Sri Lanka.

PubMed

Silva, Anslem DE; Sandaruwan, W M J; Zoysa, H K Sameera DE; Ukuwela, Kanishka D B

2017-10-03

Among the eight species of Eutropis Fitzinger currently known from Sri Lanka, Eutropis bibronii (Gray, 1838) is among the least known. Hence, the occurrence of this species in Sri Lanka has been doubted by some authors since there were no confirmed records from live specimens for the past 70 years. The species has been previously reported mostly from northern regions of Sri Lanka. Here, we report the collection of a live Eutropis bibronii from the Chundikulam National Park in the Northern Province of Sri Lanka confirming its occurrence in the country.

Automatic histologically-closer classification of skin lesions.

PubMed

Rebouças Filho, Pedro Pedrosa; Peixoto, Solon Alves; Medeiros da Nóbrega, Raul Victor; Hemanth, D Jude; Medeiros, Aldisio Gonçalves; Sangaiah, Arun Kumar; de Albuquerque, Victor Hugo C

2018-06-04

According to the American Cancer Society, melanoma is one of the most common types of cancer in the world. In 2017, approximately 87,110 new cases of skin cancer were diagnosed in the United States alone. A dermatoscope is a tool that captures lesion images with high resolution and is one of the main clinical tools to diagnose, evaluate and monitor this disease. This paper presents a new approach to classify melanoma automatically using structural co-occurrence matrix (SCM) of main frequencies extracted from dermoscopy images. The main advantage of this approach consists in transform the SCM in an adaptive feature extractor improving his power of discrimination using only the image as parameter. The images were collected from the International Skin Imaging Collaboration (ISIC) 2016, 2017 and Pedro Hispano Hospital (PH2) datasets. Specificity (Spe), sensitivity (Sen), positive predictive value, F Score, Harmonic Mean, accuracy (Acc) and area under the curve (AUC) were used to verify the efficiency of the SCM. The results show that the SCM in the frequency domain work automatically, where it obtained better results in comparison with local binary patterns, gray-level co-occurrence matrix and invariant moments of Hu as well as compared with recent works with the same datasets. The results of the proposed approach were: Spe 95.23%, 92.15% and 99.4%, Sen 94.57%, 89.9% and 99.2%, Acc 94.5%, 89.93% and 99%, and AUC 92%, 90% and 99% in ISIC 2016, 2017 and PH2 datasets, respectively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Intermediate hepatobiliary cells predict an increased risk of hepatocarcinogenesis in patients with hepatitis C virus-related cirrhosis.

PubMed

Ziol, Marianne; Nault, Jean-Charles; Aout, Mounir; Barget, Nathalie; Tepper, Maryline; Martin, Antoine; Trinchet, Jean-Claude; Ganne-Carrié, Nathalie; Vicaut, Eric; Beaugrand, Michel; N'Kontchou, Gisele

2010-07-01

The expression of biliary lineage markers such as cytokeratin (K) 7 by hepatocytes is thought to reflect an altered regeneration pathway recruiting a stem cell compartment, more prone to carcinogenesis. We aimed to investigate the presence of these so-called intermediate hepatobiliary cells (IHC) in liver biopsies of patients with hepatitis C-related cirrhosis and their potential influence on the subsequent occurrence of hepatocellular carcinoma (HCC). From a cohort of patients with hepatitis C-related cirrhosis, prospectively screened for HCC, we retrospectively selected those with a liver biopsy performed for the initial diagnosis of cirrhosis. Presence of IHC was recorded when foci of K7-positive, intermediate-sized hepatocytes were detected. A total of 150 patients were included (87 men; mean age, 57 y; range, 19-84 y; body mass index, 25 kg/m(2)). After a median follow-up period of 4.85 years, HCC was diagnosed in 36 patients (24%). Baseline liver biopsy showed intermediate hepatobiliary cell foci in 61 patients (41%). Intermediate cells co-expressed both hepatocytes markers and the progenitor cell markers Ep-CAM and K19. The presence of intermediate hepatobiliary cells was associated independently with HCC occurrence (Fine and Gray model; hazard ratio, 2.48; 95% confidence interval, 1.24-4.96; P = .01). Other predictors of HCC were diabetes and low platelet count. The HCC annual incidence rate was significantly higher in patients with IHC compared with patients without (8.14% vs 3.12%, Gray's test, P = .003). The aberrant expression of biliary K by hepatocytes in patients with hepatitis C virus-related cirrhosis is related independently to HCC occurrence. Copyright 2010 AGA Institute. Published by Elsevier Inc. All rights reserved.

SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

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

Li, Dengwang; Wang, Qinfen; Li, H

Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contourmore » structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity differences between primary and lymphoma tumor by multi-scale image texture analysis. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)« less

SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

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

Mahon, R; Weiss, E; Karki, K

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from themore » delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use in specific applications such as tissue classification and changes during radiation therapy utilizing a standard imaging protocol. Authors have the following disclosures: a research agreement with Philips Medical systems (Hugo, Weiss), a license agreement with Varian Medical Systems (Hugo, Weiss), research grants from the National Institute of Health (Hugo, Weiss), UpToDate royalties (Weiss), and none(Mahon, Ford, Karki). Authors have no potential conflicts of interest to disclose.« less

Color image processing and vision system for an automated laser paint-stripping system

NASA Astrophysics Data System (ADS)

Hickey, John M., III; Hise, Lawson

1994-10-01

Color image processing in machine vision systems has not gained general acceptance. Most machine vision systems use images that are shades of gray. The Laser Automated Decoating System (LADS) required a vision system which could discriminate between substrates of various colors and textures and paints ranging from semi-gloss grays to high gloss red, white and blue (Air Force Thunderbirds). The changing lighting levels produced by the pulsed CO2 laser mandated a vision system that did not require a constant color temperature lighting for reliable image analysis.

Artificial neural network in breast lesions from fine-needle aspiration cytology smear.

PubMed

Subbaiah, R M; Dey, Pranab; Nijhawan, Raje

2014-03-01

Artificial neural networks (ANNs) are applied in engineering and certain medical fields. ANN has immense potential and is rarely been used in breast lesions. In this present study, we attempted to build up a complete robust back propagation ANN model based on cytomorphological data, morphometric data, nuclear densitometric data, and gray level co-occurrence matrix (GLCM) of ductal carcinoma and fibroadenomas of breast cases diagnosed on fine-needle aspiration cytology (FNAC). We selected 52 cases of fibroadenomas and 60 cases of infiltrating ductal carcinoma of breast diagnosed on FNAC by two cytologists. Essential cytological data was quantitated by two independent cytologists (SRM, PD). With the help of Image J software, nuclear morphomeric, densitometric, and GLCM features were measured in all the cases on hematoxylin and eosin-stained smears. With the available data, an ANN model was built up with the help of Neurointelligence software. The network was designed as 41-20-1 (41 input nodes, 20 hidden nodes, 1 output node). The network was trained by the online back propagation algorithm and 500 iterations were done. Learning was adjusted after every iteration. ANN model correctly identified all cases of fibroadenomas and infiltrating carcinomas in the test set. This is one of the first successful composite ANN models of breast carcinomas. This basic model can be used to diagnose the gray zone area of the breast lesions on FNAC. We assume that this model may have far-reaching implications in future. Copyright © 2013 Wiley Periodicals, Inc.

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

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

Klawikowski, S; Christian, J; Schott, D

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each dailymore » CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.« less

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Characterization of coronary plaque regions in intravascular ultrasound images using a hybrid ensemble classifier.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Shin, Eun Seok; Kim, Sung Min

2018-01-01

The purpose of this study was to propose a hybrid ensemble classifier to characterize coronary plaque regions in intravascular ultrasound (IVUS) images. Pixels were allocated to one of four tissues (fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), and dense calcium (DC)) through processes of border segmentation, feature extraction, feature selection, and classification. Grayscale IVUS images and their corresponding virtual histology images were acquired from 11 patients with known or suspected coronary artery disease using 20 MHz catheter. A total of 102 hybrid textural features including first order statistics (FOS), gray level co-occurrence matrix (GLCM), extended gray level run-length matrix (GLRLM), Laws, local binary pattern (LBP), intensity, and discrete wavelet features (DWF) were extracted from IVUS images. To select optimal feature sets, genetic algorithm was implemented. A hybrid ensemble classifier based on histogram and texture information was then used for plaque characterization in this study. The optimal feature set was used as input of this ensemble classifier. After tissue characterization, parameters including sensitivity, specificity, and accuracy were calculated to validate the proposed approach. A ten-fold cross validation approach was used to determine the statistical significance of the proposed method. Our experimental results showed that the proposed method had reliable performance for tissue characterization in IVUS images. The hybrid ensemble classification method outperformed other existing methods by achieving characterization accuracy of 81% for FFT and 75% for NC. In addition, this study showed that Laws features (SSV and SAV) were key indicators for coronary tissue characterization. The proposed method had high clinical applicability for image-based tissue characterization. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating image processing and classification technology into automated polarizing film defect inspection

NASA Astrophysics Data System (ADS)

Kuo, Chung-Feng Jeffrey; Lai, Chun-Yu; Kao, Chih-Hsiang; Chiu, Chin-Hsun

2018-05-01

In order to improve the current manual inspection and classification process for polarizing film on production lines, this study proposes a high precision automated inspection and classification system for polarizing film, which is used for recognition and classification of four common defects: dent, foreign material, bright spot, and scratch. First, the median filter is used to remove the impulse noise in the defect image of polarizing film. The random noise in the background is smoothed by the improved anisotropic diffusion, while the edge detail of the defect region is sharpened. Next, the defect image is transformed by Fourier transform to the frequency domain, combined with a Butterworth high pass filter to sharpen the edge detail of the defect region, and brought back by inverse Fourier transform to the spatial domain to complete the image enhancement process. For image segmentation, the edge of the defect region is found by Canny edge detector, and then the complete defect region is obtained by two-stage morphology processing. For defect classification, the feature values, including maximum gray level, eccentricity, the contrast, and homogeneity of gray level co-occurrence matrix (GLCM) extracted from the images, are used as the input of the radial basis function neural network (RBFNN) and back-propagation neural network (BPNN) classifier, 96 defect images are then used as training samples, and 84 defect images are used as testing samples to validate the classification effect. The result shows that the classification accuracy by using RBFNN is 98.9%. Thus, our proposed system can be used by manufacturing companies for a higher yield rate and lower cost. The processing time of one single image is 2.57 seconds, thus meeting the practical application requirement of an industrial production line.

Can we trust the calculation of texture indices of CT images? A phantom study.

PubMed

Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie

2018-04-01

Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.

In vivo placental MRI shape and textural features predict fetal growth restriction and postnatal outcome.

PubMed

Dahdouh, Sonia; Andescavage, Nickie; Yewale, Sayali; Yarish, Alexa; Lanham, Diane; Bulas, Dorothy; du Plessis, Adre J; Limperopoulos, Catherine

2018-02-01

To investigate the ability of three-dimensional (3D) MRI placental shape and textural features to predict fetal growth restriction (FGR) and birth weight (BW) for both healthy and FGR fetuses. We recruited two groups of pregnant volunteers between 18 and 39 weeks of gestation; 46 healthy subjects and 34 FGR. Both groups underwent fetal MR imaging on a 1.5 Tesla GE scanner using an eight-channel receiver coil. We acquired T2-weighted images on either the coronal or the axial plane to obtain MR volumes with a slice thickness of either 4 or 8 mm covering the full placenta. Placental shape features (volume, thickness, elongation) were combined with textural features; first order textural features (mean, variance, kurtosis, and skewness of placental gray levels), as well as, textural features computed on the gray level co-occurrence and run-length matrices characterizing placental homogeneity, symmetry, and coarseness. The features were used in two machine learning frameworks to predict FGR and BW. The proposed machine-learning based method using shape and textural features identified FGR pregnancies with 86% accuracy, 77% precision and 86% recall. BW estimations were 0.3 ± 13.4% (mean percentage error ± standard error) for healthy fetuses and -2.6 ± 15.9% for FGR. The proposed FGR identification and BW estimation methods using in utero placental shape and textural features computed on 3D MR images demonstrated high accuracy in our healthy and high-risk cohorts. Future studies to assess the evolution of each feature with regard to placental development are currently underway. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:449-458. © 2017 International Society for Magnetic Resonance in Medicine.

[18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type.

PubMed

Shen, Wei-Chih; Chen, Shang-Wen; Liang, Ji-An; Hsieh, Te-Chun; Yen, Kuo-Yang; Kao, Chia-Hung

2017-09-01

In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography. We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV max ), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann-Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis. Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV max , the risk of pelvic LN metastasis can be scored accordingly. The TLG mean was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM). This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG mean, respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology.

The occurrence of hepatozoon in the gray squirrel (Sciurus carolinensis)

USGS Publications Warehouse

Herman, C.M.; Price, D.L.

1955-01-01

Hepatozoon sciuri (Coles, 1914) is reported from gray squirrels (Sciurus carolinensis) in Washington, D.C. and Maryland. Blood smears stained with Giemsa's stain revealed a parasitemia in 16 to 71% of the squirrels examined. A technique for laking the red cells and concentrating the white cells in blood samples demonstrated this protozoon to be present in every squirrel so tested.

A gene encoding maize caffeoyl-CoA O-methyltransferase confers quantitative resistance to multiple pathogens.

PubMed

Yang, Qin; He, Yijian; Kabahuma, Mercy; Chaya, Timothy; Kelly, Amy; Borrego, Eli; Bian, Yang; El Kasmi, Farid; Yang, Li; Teixeira, Paulo; Kolkman, Judith; Nelson, Rebecca; Kolomiets, Michael; L Dangl, Jeffery; Wisser, Randall; Caplan, Jeffrey; Li, Xu; Lauter, Nick; Balint-Kurti, Peter

2017-09-01

Alleles that confer multiple disease resistance (MDR) are valuable in crop improvement, although the molecular mechanisms underlying their functions remain largely unknown. A quantitative trait locus, qMdr 9.02 , associated with resistance to three important foliar maize diseases-southern leaf blight, gray leaf spot and northern leaf blight-has been identified on maize chromosome 9. Through fine-mapping, association analysis, expression analysis, insertional mutagenesis and transgenic validation, we demonstrate that ZmCCoAOMT2, which encodes a caffeoyl-CoA O-methyltransferase associated with the phenylpropanoid pathway and lignin production, is the gene within qMdr 9.02 conferring quantitative resistance to both southern leaf blight and gray leaf spot. We suggest that resistance might be caused by allelic variation at the level of both gene expression and amino acid sequence, thus resulting in differences in levels of lignin and other metabolites of the phenylpropanoid pathway and regulation of programmed cell death.

Emerging factors associated with the decline of a gray fox population and multi-scale land cover associations of mesopredators in the Chicago metropolitan area.

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

Willingham, Alison N.; /Ohio State U.

Statewide surveys of furbearers in Illinois indicate gray (Urocyon cinereoargenteus) and red (Vulpes vulpes) foxes have experienced substantial declines in relative abundance, whereas other species such as raccoons (Procyon lotor) and coyotes (Canis latrans) have exhibited dramatic increases during the same time period. The cause of the declines of gray and red foxes has not been identified, and the current status of gray foxes remains uncertain. Therefore, I conducted a large-scale predator survey and tracked radiocollared gray foxes from 2004 to 2007 in order to determine the distribution, survival, cause-specific mortality sources and land cover associations of gray foxes inmore » an urbanized region of northeastern Illinois, and examined the relationships between the occurrence of gray fox and the presence other species of mesopredators, specifically coyotes and raccoons. Although generalist mesopredators are common and can reach high densities in many urban areas their urban ecology is poorly understood due to their secretive nature and wariness of humans. Understanding how mesopredators utilize urbanized landscapes can be useful in the management and control of disease outbreaks, mitigation of nuisance wildlife issues, and gaining insight into how mesopredators shape wildlife communities in highly fragmented areas. I examined habitat associations of raccoons, opossums (Didelphis virginiana), domestic cats (Felis catus), coyotes, foxes (gray and red), and striped skunks (Mephitis mephitis) at multiple spatial scales in an urban environment. Gray fox occurrence was rare and widely dispersed, and survival estimates were similar to other studies. Gray fox occurrence was negatively associated with natural and semi-natural land cover types. Fox home range size increased with increasing urban development suggesting that foxes may be negatively influenced by urbanization. Gray fox occurrence was not associated with coyote or raccoon presence. However, spatial avoidance and mortality due to coyote predation was documented and disease was a major mortality source for foxes. The declining relative abundance of gray fox in Illinois is likely a result of a combination of factors. Assessment of habitat associations indicated that urban mesopredators, particularly coyotes and foxes, perceived the landscape as relatively homogeneous and that urban mesopredators interacted with the environment at scales larger than that accommodated by remnant habitat patches. Coyote and fox presence was found to be associated with a high degree of urban development at large and intermediate spatial scales. However, at a small spatial scale fox presence was associated with high density urban land cover whereas coyote presence was associated with urban development with increased forest cover. Urban habitats can offer a diversity of prey items and anthropogenic resources and natural land cover could offer coyotes daytime resting opportunities in urban areas where they may not be as tolerated as smaller foxes. Raccoons and opossums were found to utilize moderately developed landscapes with interspersed natural and semi-natural land covers at a large spatial scale, which may facilitate dispersal movements. At intermediate and small spatial scales, both species were found to utilize areas that were moderately developed and included forested land cover. These results indicated that raccoons and opossums used natural areas in proximity to anthropogenic resources. At a large spatial scale, skunk presence was associated with highly developed landscapes with interspersed natural and semi-natural land covers. This may indicate that skunks perceived the urban matrix as more homogeneous than raccoons or opossums. At an intermediate spatial scale skunks were associated with moderate levels of development and increased forest cover, which indicated that they might utilize natural land cover in proximity to human-dominated land cover. At the smallest spatial scale skunk presence was associated with forested land cover surrounded by a suburban matrix. Compared to raccoons and opossums, skunks may not be tolerated in close proximity to human development in urban areas. Domestic cat presence was positively associated with increasingly urbanized and less diverse landscapes with decreased amounts of forest and urban open space at the largest spatial scale. At an intermediate spatial scale, cat presence was associated with a moderate degree of urban development characterized by increased forest cover, and at a small spatial scale cat presence was associated with a high degree of urbanization. Free-ranging domestic cats are often associated with human-dominated landscapes and likely utilize remnant natural habitat patches for hunting purposes, which may have implications for native predator and prey species existing in fragmented habitat patches in proximity to human development.« less

Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

PubMed

Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

2015-12-01

The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

A single high dose of dexamethasone increases GAP-43 and synaptophysin in the hippocampus of aged rats.

PubMed

Tesic, Vesna; Perovic, Milka; Zaletel, Ivan; Jovanovic, Mirna; Puskas, Nela; Ruzdijic, Sabera; Kanazir, Selma

2017-11-01

The administration of dexamethasone, a synthetic glucocorticoid receptor agonist, has been reported to modulate cognitive performance in both animals and humans. In the present study, we demonstrate the effects of a single high dose of dexamethasone on the expression and distribution of synaptic plasticity-related proteins, growth-associated protein-43 (GAP-43) and synaptophysin, in the hippocampus of 6-, 12-, 18- and 24-month-old rats. Acute dexamethasone treatment significantly altered the expression of GAP-43 at the posttranslational level by modulating the levels of phosphorylated GAP-43 and proteolytic GAP-43-3 fragment. The effect was the most pronounced in the hippocampi of the aged animals. The total GAP-43 protein was increased only in 24-month-old dexamethasone-treated animals, and was concomitant with a decrease in calpain-mediated proteolysis. Moreover, by introducing the gray level co-occurrence matrix method, a form of texture analysis, we were able to reveal the subtle differences in the expression pattern of both GAP-43 and synaptophysin in the hippocampal subfields that were not detected by Western blot analysis alone. Therefore, the current study demonstrates, through a novel combined approach, that dexamethasone treatment significantly affects both GAP-43 and synaptophysin protein expression in the hippocampus of aged rats. Copyright © 2017 Elsevier Inc. All rights reserved.

A Novel Hyperspectral Microscopic Imaging System for Evaluating Fresh Degree of Pork.

PubMed

Xu, Yi; Chen, Quansheng; Liu, Yan; Sun, Xin; Huang, Qiping; Ouyang, Qin; Zhao, Jiewen

2018-04-01

This study proposed a rapid microscopic examination method for pork freshness evaluation by using the self-assembled hyperspectral microscopic imaging (HMI) system with the help of feature extraction algorithm and pattern recognition methods. Pork samples were stored for different days ranging from 0 to 5 days and the freshness of samples was divided into three levels which were determined by total volatile basic nitrogen (TVB-N) content. Meanwhile, hyperspectral microscopic images of samples were acquired by HMI system and processed by the following steps for the further analysis. Firstly, characteristic hyperspectral microscopic images were extracted by using principal component analysis (PCA) and then texture features were selected based on the gray level co-occurrence matrix (GLCM). Next, features data were reduced dimensionality by fisher discriminant analysis (FDA) for further building classification model. Finally, compared with linear discriminant analysis (LDA) model and support vector machine (SVM) model, good back propagation artificial neural network (BP-ANN) model obtained the best freshness classification with a 100 % accuracy rating based on the extracted data. The results confirm that the fabricated HMI system combined with multivariate algorithms has ability to evaluate the fresh degree of pork accurately in the microscopic level, which plays an important role in animal food quality control.

A Novel Hyperspectral Microscopic Imaging System for Evaluating Fresh Degree of Pork

PubMed Central

Xu, Yi; Chen, Quansheng; Liu, Yan; Sun, Xin; Huang, Qiping; Ouyang, Qin; Zhao, Jiewen

2018-01-01

Abstract This study proposed a rapid microscopic examination method for pork freshness evaluation by using the self-assembled hyperspectral microscopic imaging (HMI) system with the help of feature extraction algorithm and pattern recognition methods. Pork samples were stored for different days ranging from 0 to 5 days and the freshness of samples was divided into three levels which were determined by total volatile basic nitrogen (TVB-N) content. Meanwhile, hyperspectral microscopic images of samples were acquired by HMI system and processed by the following steps for the further analysis. Firstly, characteristic hyperspectral microscopic images were extracted by using principal component analysis (PCA) and then texture features were selected based on the gray level co-occurrence matrix (GLCM). Next, features data were reduced dimensionality by fisher discriminant analysis (FDA) for further building classification model. Finally, compared with linear discriminant analysis (LDA) model and support vector machine (SVM) model, good back propagation artificial neural network (BP-ANN) model obtained the best freshness classification with a 100 % accuracy rating based on the extracted data. The results confirm that the fabricated HMI system combined with multivariate algorithms has ability to evaluate the fresh degree of pork accurately in the microscopic level, which plays an important role in animal food quality control. PMID:29805285

Land use and land cover classification for rural residential areas in China using soft-probability cascading of multifeatures

NASA Astrophysics Data System (ADS)

Zhang, Bin; Liu, Yueyan; Zhang, Zuyu; Shen, Yonglin

2017-10-01

A multifeature soft-probability cascading scheme to solve the problem of land use and land cover (LULC) classification using high-spatial-resolution images to map rural residential areas in China is proposed. The proposed method is used to build midlevel LULC features. Local features are frequently considered as low-level feature descriptors in a midlevel feature learning method. However, spectral and textural features, which are very effective low-level features, are neglected. The acquisition of the dictionary of sparse coding is unsupervised, and this phenomenon reduces the discriminative power of the midlevel feature. Thus, we propose to learn supervised features based on sparse coding, a support vector machine (SVM) classifier, and a conditional random field (CRF) model to utilize the different effective low-level features and improve the discriminability of midlevel feature descriptors. First, three kinds of typical low-level features, namely, dense scale-invariant feature transform, gray-level co-occurrence matrix, and spectral features, are extracted separately. Second, combined with sparse coding and the SVM classifier, the probabilities of the different LULC classes are inferred to build supervised feature descriptors. Finally, the CRF model, which consists of two parts: unary potential and pairwise potential, is employed to construct an LULC classification map. Experimental results show that the proposed classification scheme can achieve impressive performance when the total accuracy reached about 87%.

The direct biologic effects of radioactive 125I seeds on pancreatic cancer cells PANC-1, at continuous low-dose rates.

PubMed

Wang, Jidong; Wang, Junjie; Liao, Anyan; Zhuang, Hongqing; Zhao, Yong

2009-08-01

The relative biologic effectiveness of model 6711 125I seeds (Ningbo Junan Pharmaceutical Technology Company,Ningbo, China) and their effects on growth, cell cycle, and apoptosis in human pancreatic cancer cell line PANC-1 were examined in the present study. PANC-1 cells were exposed to the absorbed doses of 1, 2, 4, 6, 8, and 10 Gyeither with 125I seeds (initial dose rate, 2.59 cGy=h) or with 60Co g-ray irradiation (dose rate, 221 cGy=min),respectively. Significantly greater numbers of apoptotic PANC-1 cells were detected following the continuouslow-dose-rate (CLDR) irradiation of 125I seeds, compared with cells irradiated with identical doses of 60Co g-ray. The D(0) for 60Co g-ray and 125I seed irradiation were 2.30 and 1.66, respectively. The survival fraction after 125Iseed irradiation was significantly lower than that of 60Co g-ray, with a relative biologic effectiveness of 1.39.PANC-1 cells were dose dependently arrested in the S-phase by 60Co g-rays and in the G2=M phase by 125I seeds,24 hour after irradiation. CLDR irradiation by 125I seeds was more effective in inducing cell apoptosis in PANC-1cells than acute high-dose-rate 60Co g irradiation. Interestingly, CLDR irradiation by 125I seeds can cause PANC-1cell-cycle arrest at the G2=M phase and induce apoptosis, which may be an important mechanism underlying 125Iseed-induced PANC-1 cell inhibition.

Division within the North American boreal forest: Ecological niche divergence between the Bicknell's Thrush (Catharus bicknelli) and Gray-cheeked Thrush (C. minimus).

PubMed

FitzGerald, Alyssa M

2017-07-01

Sister species that diverged in allopatry in similar environments are expected to exhibit niche conservatism. Using ecological niche modeling and a multivariate analysis of climate and habitat data, I test the hypothesis that the Bicknell's Thrush ( Catharus bicknelli ) and Gray-cheeked Thrush ( C. mimimus ), sister species that breed in the North American boreal forest, show niche conservatism. Three tree species that are important components of breeding territories of both thrush species were combined with climatic variables to create niche models consisting of abiotic and biotic components. Abiotic-only, abiotic+biotic, and biotic-only models were evaluated using the area under the curve (AUC) criterion. Abiotic+biotic models had higher AUC scores and did not over-project thrush distributions compared to abiotic-only or biotic-only models. From the abiotic+biotic models, I tested for niche conservatism or divergence by accounting for the differences in the availability of niche components by calculating (1) niche overlap from ecological niche models and (2) mean niche differences of environmental values at occurrence points. Niche background similarity tests revealed significant niche divergence in 10 of 12 comparisons, and multivariate tests revealed niche divergence along 2 of 3 niche axes. The Bicknell's Thrush breeds in warmer and wetter regions with a high abundance of balsam fir ( Abies balsamea ), whereas Gray-cheeked Thrush often co-occurs with black spruce ( Picea mariana ). Niche divergence, rather than conservatism, was the predominant pattern for these species, suggesting that ecological divergence has played a role in the speciation of the Bicknell's Thrush and Gray-cheeked Thrush. Furthermore, because niche models were improved by the incorporation of biotic variables, this study validates the inclusion of relevant biotic factors in ecological niche modeling to increase model accuracy.

Geographical classification of apple based on hyperspectral imaging

NASA Astrophysics Data System (ADS)

Guo, Zhiming; Huang, Wenqian; Chen, Liping; Zhao, Chunjiang; Peng, Yankun

2013-05-01

Attribute of apple according to geographical origin is often recognized and appreciated by the consumers. It is usually an important factor to determine the price of a commercial product. Hyperspectral imaging technology and supervised pattern recognition was attempted to discriminate apple according to geographical origins in this work. Hyperspectral images of 207 Fuji apple samples were collected by hyperspectral camera (400-1000nm). Principal component analysis (PCA) was performed on hyperspectral imaging data to determine main efficient wavelength images, and then characteristic variables were extracted by texture analysis based on gray level co-occurrence matrix (GLCM) from dominant waveband image. All characteristic variables were obtained by fusing the data of images in efficient spectra. Support vector machine (SVM) was used to construct the classification model, and showed excellent performance in classification results. The total classification rate had the high classify accuracy of 92.75% in the training set and 89.86% in the prediction sets, respectively. The overall results demonstrated that the hyperspectral imaging technique coupled with SVM classifier can be efficiently utilized to discriminate Fuji apple according to geographical origins.

[Identification of green tea brand based on hyperspectra imaging technology].

PubMed

Zhang, Hai-Liang; Liu, Xiao-Li; Zhu, Feng-Le; He, Yong

2014-05-01

Hyperspectral imaging technology was developed to identify different brand famous green tea based on PCA information and image information fusion. First 512 spectral images of six brands of famous green tea in the 380 approximately 1 023 nm wavelength range were collected and principal component analysis (PCA) was performed with the goal of selecting two characteristic bands (545 and 611 nm) that could potentially be used for classification system. Then, 12 gray level co-occurrence matrix (GLCM) features (i. e., mean, covariance, homogeneity, energy, contrast, correlation, entropy, inverse gap, contrast, difference from the second-order and autocorrelation) based on the statistical moment were extracted from each characteristic band image. Finally, integration of the 12 texture features and three PCA spectral characteristics for each green tea sample were extracted as the input of LS-SVM. Experimental results showed that discriminating rate was 100% in the prediction set. The receiver operating characteristic curve (ROC) assessment methods were used to evaluate the LS-SVM classification algorithm. Overall results sufficiently demonstrate that hyperspectral imaging technology can be used to perform classification of green tea.

Scanning electron microscopy combined with image processing technique: Analysis of microstructure, texture and tenderness in Semitendinous and Gluteus Medius bovine muscles.

PubMed

Pieniazek, Facundo; Messina, Valeria

2016-11-01

In this study the effect of freeze drying on the microstructure, texture, and tenderness of Semitendinous and Gluteus Medius bovine muscles were analyzed applying Scanning Electron Microscopy combined with image analysis. Samples were analyzed by Scanning Electron Microscopy at different magnifications (250, 500, and 1,000×). Texture parameters were analyzed by Texture analyzer and by image analysis. Tenderness by Warner-Bratzler shear force. Significant differences (p < 0.05) were obtained for image and instrumental texture features. A linear trend with a linear correlation was applied for instrumental and image features. Image texture features calculated from Gray Level Co-occurrence Matrix (homogeneity, contrast, entropy, correlation and energy) at 1,000× in both muscles had high correlations with instrumental features (chewiness, hardness, cohesiveness, and springiness). Tenderness showed a positive correlation in both muscles with image features (energy and homogeneity). Combing Scanning Electron Microscopy with image analysis can be a useful tool to analyze quality parameters in meat.Summary SCANNING 38:727-734, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Electroencephalogram Signal Classification for Automated Epileptic Seizure Detection Using Genetic Algorithm

PubMed Central

Nanthini, B. Suguna; Santhi, B.

2017-01-01

Background: Epilepsy causes when the repeated seizure occurs in the brain. Electroencephalogram (EEG) test provides valuable information about the brain functions and can be useful to detect brain disorder, especially for epilepsy. In this study, application for an automated seizure detection model has been introduced successfully. Materials and Methods: The EEG signals are decomposed into sub-bands by discrete wavelet transform using db2 (daubechies) wavelet. The eight statistical features, the four gray level co-occurrence matrix and Renyi entropy estimation with four different degrees of order, are extracted from the raw EEG and its sub-bands. Genetic algorithm (GA) is used to select eight relevant features from the 16 dimension features. The model has been trained and tested using support vector machine (SVM) classifier successfully for EEG signals. The performance of the SVM classifier is evaluated for two different databases. Results: The study has been experimented through two different analyses and achieved satisfactory performance for automated seizure detection using relevant features as the input to the SVM classifier. Conclusion: Relevant features using GA give better accuracy performance for seizure detection. PMID:28781480

Neurostructural impact of co-occurring anxiety in pediatric patients with major depressive disorder: a voxel-based morphometry study.

PubMed

Wehry, Anna M; McNamara, Robert K; Adler, Caleb M; Eliassen, James C; Croarkin, Paul; Cerullo, Michael A; DelBello, Melissa P; Strawn, Jeffrey R

2015-01-15

Depressive and anxiety disorders are among the most frequently occurring psychiatric conditions in children and adolescents and commonly present occur together. Co-occurring depression and anxiety is associated with increased functional impairment and suicidality compared to depression alone. Despite this, little is known regarding the neurostructural differences between anxiety disorders and major depressive disorder (MDD). Moreover, the neurophysiologic impact of the presence of anxiety in adolescents with MDD is unknown. Using voxel-based morphometry, gray matter volumes were compared among adolescents with MDD (and no co-morbid anxiety disorders, n=14), adolescents with MDD and co-morbid anxiety ("anxious depression," n=12), and healthy comparison subjects (n=41). Patients with anxious depression exhibited decreased gray matter volumes in the dorsolateral prefrontal cortex (DLPFC) compared to patients with MDD alone. Compared to healthy subjects, adolescents with anxious depression had increased gray matter volumes in the pre- and post-central gyri. The current sample size was small and precluded an analysis of multiple covariates which may influence GMV. Gray matter deficits in the DLPFC in youth with anxious depression compared to patients with MDD and no co-occurring anxiety may reflect the more severe psychopathology in these patients. Additionally, the distinct gray matter fingerprints of MDD and anxious depression (compared to healthy subjects) suggest differing neurophysiologic substrates for these conditions, though the etiology and longitudinal trajectory of the differences remain to be determined. Copyright © 2014 Elsevier B.V. All rights reserved.

Association between background parenchymal enhancement of breast MRI and BIRADS rating change in the subsequent screening

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-03-01

Although breast magnetic resonance imaging (MRI) has been used as a breast cancer screening modality for high-risk women, its cancer detection yield remains low (i.e., <= 3%). Thus, increasing breast MRI screening efficacy and cancer detection yield is an important clinical issue in breast cancer screening. In this study, we investigated association between the background parenchymal enhancement (BPE) of breast MRI and the change of diagnostic (BIRADS) status in the next subsequent breast MRI screening. A dataset with 65 breast MRI screening cases was retrospectively assembled. All cases were rated BIRADS-2 (benign findings). In the subsequent screening, 4 cases were malignant (BIRADS-6), 48 remained BIRADS-2 and 13 were downgraded to negative (BIRADS-1). A computer-aided detection scheme was applied to process images of the first set of breast MRI screening. Total of 33 features were computed including texture feature and global BPE features. Texture features were computed from either a gray-level co-occurrence matrix or a gray level run length matrix. Ten global BPE features were also initially computed from two breast regions and bilateral difference between the left and right breasts. Box-plot based analysis shows positive association between texture features and BIRADS rating levels in the second screening. Furthermore, a logistic regression model was built using optimal features selected by a CFS based feature selection method. Using a leave-one-case-out based cross-validation method, classification yielded an overall 75% accuracy in predicting the improvement (or downgrade) of diagnostic status (to BIRAD-1) in the subsequent breast MRI screening. This study demonstrated potential of developing a new quantitative imaging marker to predict diagnostic status change in the short-term, which may help eliminate a high fraction of unnecessary repeated breast MRI screenings and increase the cancer detection yield.

Cannabis, Cigarettes, and Their Co-Occurring Use: Disentangling Differences in Gray Matter Volume

PubMed Central

Jagannathan, Kanchana; Hager, Nathan; Childress, Anna Rose; Rao, Hengyi; Franklin, Teresa R.

2015-01-01

Background: Structural magnetic resonance imaging techniques are powerful tools for examining the effects of drug use on the brain. The nicotine and cannabis literature has demonstrated differences between nicotine cigarette smokers and cannabis users compared to controls in brain structure; however, less is known about the effects of co-occurring cannabis and tobacco use. Methods: We used voxel-based morphometry to examine gray matter volume differences between four groups: (1) cannabis-dependent individuals who do not smoke tobacco (Cs); (2) cannabis-dependent individuals who smoke tobacco (CTs); (3) cannabis-naïve, nicotine-dependent individuals who smoke tobacco (Ts); and (4) healthy controls (HCs). We also explored associations between gray matter volume and measures of cannabis and tobacco use. Results: A significant group effect was observed in the left putamen, thalamus, right precentral gyrus, and left cerebellum. Compared to HCs, the Cs, CTs, and Ts exhibited larger gray matter volumes in the left putamen. Cs also had larger gray matter volume than HCs in the right precentral gyrus. Cs and CTs exhibited smaller gray matter volume than HCs in the thalamus, and CTs and Ts had smaller left cerebellar gray matter volume than HCs. Conclusions: This study extends previous research that independently examined the effects of cannabis or tobacco use on brain structure by including an examination of co-occurring cannabis and tobacco use, and provides evidence that cannabis and tobacco exposure are associated with alterations in brain regions associated with addiction. PMID:26045474

Analysis of co-occurrence toponyms in web pages based on complex networks

NASA Astrophysics Data System (ADS)

Zhong, Xiang; Liu, Jiajun; Gao, Yong; Wu, Lun

2017-01-01

A large number of geographical toponyms exist in web pages and other documents, providing abundant geographical resources for GIS. It is very common for toponyms to co-occur in the same documents. To investigate these relations associated with geographic entities, a novel complex network model for co-occurrence toponyms is proposed. Then, 12 toponym co-occurrence networks are constructed from the toponym sets extracted from the People's Daily Paper documents of 2010. It is found that two toponyms have a high co-occurrence probability if they are at the same administrative level or if they possess a part-whole relationship. By applying complex network analysis methods to toponym co-occurrence networks, we find the following characteristics. (1) The navigation vertices of the co-occurrence networks can be found by degree centrality analysis. (2) The networks express strong cluster characteristics, and it takes only several steps to reach one vertex from another one, implying that the networks are small-world graphs. (3) The degree distribution satisfies the power law with an exponent of 1.7, so the networks are free-scale. (4) The networks are disassortative and have similar assortative modes, with assortative exponents of approximately 0.18 and assortative indexes less than 0. (5) The frequency of toponym co-occurrence is weakly negatively correlated with geographic distance, but more strongly negatively correlated with administrative hierarchical distance. Considering the toponym frequencies and co-occurrence relationships, a novel method based on link analysis is presented to extract the core toponyms from web pages. This method is suitable and effective for geographical information retrieval.

Application of the Spectral Neighborhood of Soil Line Technique to Analyze the Intensity of Soil Use in 1985-2014 (by the Example of Three Districts of Tula Oblast)

NASA Astrophysics Data System (ADS)

Rukhovich, D. I.; Rukhovich, A. D.; Rukhovich, D. D.; Simakova, M. S.; Kulyanitsa, A. L.; Koroleva, P. V.

2018-03-01

The technique of separation of the spectral neighborhood of soil line (SNSL) makes it possible to perform quantitative estimates of the intensity of agricultural land use. This is achieved via calculation of the frequency of occurrence of bare soil surface (BSS). It is shown that the frequency of occurrence of BSS in 1984-1994 was linearly related to the soil type within the sequence of soddy strongly podzolic, soddy moderately podzolic, soddy slightly podzolic (Eutric Albic Glossic Retisols (Loamic, Aric, Cutanic, Differentic, Ochric)); light gray forest (Eutric Retisols (Loamic, Aric, Cutanic, Differentic, Ochric)), gray forest (Eutric Retisols (Loamic, Aric, Cutanic, Ochric)), and dark gray forest soils (Luvic Retic Greyzemic Phaeozems (Loamic, Aric)); podzolized chernozems (Luvic Greyzemic Chernic Phaeozems (Loamic, Aric, Pachic)) and leached chernozems (Luvic Chernic Phaeozems (Loamic, Aric, Pachic)). The intensity of exploitation of the least and most fertile soils in this sequence comprised 28 and 48%, respectively. In the next decade (1995-2004) the relationship between the type of soil and the intensity of its exploitation drastically changed; the intensity of exploitation of the leas and most fertile soils comprised 14 and 43%, respectively. Nearly a half of agricultural lands in the zones of soddy-podzolic and gray forest soils were abandoned, because the cultivation of the soils with the natural fertility below that in the podzolized chernozems became economically unfeasible under conditions of the economic crisis of the 1990s. The spatiotemporal relationships between the character of the soil cover and the intensity of exploitation of the agricultural lands manifest themselves by the decreasing frequency of occurrence of BSS from leached chernozems to soddy strongly podzolic soils and from 1985 to 2014.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain.

PubMed

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain

PubMed Central

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L.; Aziz, Tipu Z.; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations. PMID:29695951

Effect of multiphase radiation on coal combustion in a pulverized coal jet flame

NASA Astrophysics Data System (ADS)

Wu, Bifen; Roy, Somesh P.; Zhao, Xinyu; Modest, Michael F.

2017-08-01

The accurate modeling of coal combustion requires detailed radiative heat transfer models for both gaseous combustion products and solid coal particles. A multiphase Monte Carlo ray tracing (MCRT) radiation solver is developed in this work to simulate a laboratory-scale pulverized coal flame. The MCRT solver considers radiative interactions between coal particles and three major combustion products (CO2, H2O, and CO). A line-by-line spectral database for the gas phase and a size-dependent nongray correlation for the solid phase are employed to account for the nongray effects. The flame structure is significantly altered by considering nongray radiation and the lift-off height of the flame increases by approximately 35%, compared to the simulation without radiation. Radiation is also found to affect the evolution of coal particles considerably as it takes over as the dominant mode of heat transfer for medium-to-large coal particles downstream of the flame. To investigate the respective effects of spectral models for the gas and solid phases, a Planck-mean-based gray gas model and a size-independent gray particle model are applied in a frozen-field analysis of a steady-state snapshot of the flame. The gray gas approximation considerably underestimates the radiative source terms for both the gas phase and the solid phase. The gray coal approximation also leads to under-prediction of the particle emission and absorption. However, the level of under-prediction is not as significant as that resulting from the employment of the gray gas model. Finally, the effect of the spectral property of ash on radiation is also investigated and found to be insignificant for the present target flame.

BSW and MSW Students' Opinions about and Responses to the Death of Freddie Gray and the Ensuing Riots: Implications for the Social Justice Emphasis in Social Work Education

ERIC Educational Resources Information Center

Knight, Carolyn

2017-01-01

In April 2015, a Black man, Freddie Gray, died in police custody in Baltimore, Maryland. A day of rioting followed. These events provided the researcher with the opportunity to ascertain social work students' opinions about and actions in response to these occurrences and their implications for the social justice mission of the social work…

North Pacific Tropical Cyclones and Teleconnections

DTIC Science & Technology

2005-03-01

variance may be significantly explained by the stratospheric Quasi-biennial Oscillation ( QBO ). 3 Investigators of Atlantic basin TC frequency know that Gray...1984) has linked TC frequency in this region to the QBO . Gray et al. (1992) found that intense hurricane occurrence was almost three times more...likely during the westerly phase of the QBO as that of the easterly phase (Chan 2004). Zhang et al. (1994) examined TC frequency in the WNP from 1884-1988

Cannabis, Cigarettes, and Their Co-Occurring Use: Disentangling Differences in Gray Matter Volume.

PubMed

Wetherill, Reagan R; Jagannathan, Kanchana; Hager, Nathan; Childress, Anna Rose; Rao, Hengyi; Franklin, Teresa R

2015-06-04

Structural magnetic resonance imaging techniques are powerful tools for examining the effects of drug use on the brain. The nicotine and cannabis literature has demonstrated differences between nicotine cigarette smokers and cannabis users compared to controls in brain structure; however, less is known about the effects of co-occurring cannabis and tobacco use. We used voxel-based morphometry to examine gray matter volume differences between four groups: (1) cannabis-dependent individuals who do not smoke tobacco (Cs); (2) cannabis-dependent individuals who smoke tobacco (CTs); (3) cannabis-naïve, nicotine-dependent individuals who smoke tobacco (Ts); and (4) healthy controls (HCs). We also explored associations between gray matter volume and measures of cannabis and tobacco use. A significant group effect was observed in the left putamen, thalamus, right precentral gyrus, and left cerebellum. Compared to HCs, the Cs, CTs, and Ts exhibited larger gray matter volumes in the left putamen. Cs also had larger gray matter volume than HCs in the right precentral gyrus. Cs and CTs exhibited smaller gray matter volume than HCs in the thalamus, and CTs and Ts had smaller left cerebellar gray matter volume than HCs. This study extends previous research that independently examined the effects of cannabis or tobacco use on brain structure by including an examination of co-occurring cannabis and tobacco use, and provides evidence that cannabis and tobacco exposure are associated with alterations in brain regions associated with addiction. © The Author 2015. Published by Oxford University Press on behalf of CINP.

11. VIEW OF HORIZONTAL MIXER (GedgeGray Co., Lockland, Ohio), LOCATED ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

11. VIEW OF HORIZONTAL MIXER (Gedge-Gray Co., Lockland, Ohio), LOCATED IN THE BASEMENT, MIXED ANIMAL FEED TO ORDER. THE WATER-POWERED MIXER WAS SUPERSEDED BY TWO ELECTRIC-POWERED VERTICAL MIXERS, ADDED IN THE 1940S. Photographer: Louise Taft Cawood, July 1986 - Alexander's Grist Mill, Lock 37 on Ohio & Erie Canal, South of Cleveland, Valley View, Cuyahoga County, OH

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

NASA Astrophysics Data System (ADS)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Gender differences in co-occurrence of depressive and anger symptoms among adolescents in five Nordic countries.

PubMed

Asgeirsdottir, Bryndis Bjork; Sigfusdottir, Inga Dora

2015-03-01

The aim of this study was to carry out a comparative examination on gender differences in depressive and anger symptoms and their co-occurrence, using comparative self-report survey data from 16-19-year-old students in five Nordic countries. In total, 8038 adolescents participated in the study, 4183 females (52%) and 3855 males (48%) with an average age of 17.1 years. Analysis of Covariance (ANCOVA) was used to test for gender differences in symptoms for the sample as a whole and also for each country. Furthermore, partial bivariate correlation was carried out and followed up by ANCOVA to test for gender differences in the co-occurrence of depressive and anger symptoms in the five countries. The results indicated that, on average, adolescent females reported higher levels of depressive symptoms than males in all the countries under study and higher levels of anger symptoms in four out of five countries. The relationship between depressive and anger symptoms turned out to be stronger for females than males for all the countries under study, demonstrating higher co-occurrence of depressive and anger symptoms on average among females than males. The findings underline the need for attending to both depressive and anger symptoms among adolescents when designing mental health interventions and treatments as co-occurrence of both types of symptoms is common, particularly among females. © 2014 the Nordic Societies of Public Health.

Analysis of second-harmonic-generation microscopy in a mouse model of ovarian carcinoma

NASA Astrophysics Data System (ADS)

Watson, Jennifer M.; Rice, Photini F.; Marion, Samuel L.; Brewer, Molly A.; Davis, John R.; Rodriguez, Jeffrey J.; Utzinger, Urs; Hoyer, Patricia B.; Barton, Jennifer K.

2012-07-01

Second-harmonic-generation (SHG) imaging of mouse ovaries ex vivo was used to detect collagen structure changes accompanying ovarian cancer development. Dosing with 4-vinylcyclohexene diepoxide and 7,12-dimethylbenz[a]anthracene resulted in histologically confirmed cases of normal, benign abnormality, dysplasia, and carcinoma. Parameters for each SHG image were calculated using the Fourier transform matrix and gray-level co-occurrence matrix (GLCM). Cancer versus normal and cancer versus all other diagnoses showed the greatest separation using the parameters derived from power in the highest-frequency region and GLCM energy. Mixed effects models showed that these parameters were significantly different between cancer and normal (P<0.008). Images were classified with a support vector machine, using 25% of the data for training and 75% for testing. Utilizing all images with signal greater than the noise level, cancer versus not-cancer specimens were classified with 81.2% sensitivity and 80.0% specificity, and cancer versus normal specimens were classified with 77.8% sensitivity and 79.3% specificity. Utilizing only images with greater than of 75% of the field of view containing signal improved sensitivity and specificity for cancer versus normal to 81.5% and 81.1%. These results suggest that using SHG to visualize collagen structure in ovaries could help with early cancer detection.

Mammogram segmentation using maximal cell strength updation in cellular automata.

PubMed

Anitha, J; Peter, J Dinesh

2015-08-01

Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.

Evaluating land use and aboveground biomass dynamics in an oil palm-dominated landscape in Borneo using optical remote sensing

NASA Astrophysics Data System (ADS)

Singh, Minerva; Malhi, Yadvinder; Bhagwat, Shonil

2014-01-01

The focus of this study is to assess the efficacy of using optical remote sensing (RS) in evaluating disparities in forest composition and aboveground biomass (AGB). The research was carried out in the East Sabah region, Malaysia, which constitutes a disturbance gradient ranging from pristine old growth forests to forests that have experienced varying levels of disturbances. Additionally, a significant proportion of the area consists of oil palm plantations. In accordance with local laws, riparian forest (RF) zones have been retained within oil palm plantations and other forest types. The RS imagery was used to assess forest stand structure and AGB. Band reflectance, vegetation indicators, and gray-level co-occurrence matrix (GLCM) consistency features were used as predictor variables in regression analysis. Results indicate that the spectral variables were limited in their effectiveness in differentiating between forest types and in calculating biomass. However, GLCM based variables illustrated strong correlations with the forest stand structures as well as with the biomass of the various forest types in the study area. The present study provides new insights into the efficacy of texture examination methods in differentiating between various land-use types (including small, isolated forest zones such as RFs) as well as their AGB stocks.

Flood monitoring in a semi-arid environment using spatially high resolution radar and optical data.

PubMed

Seiler, Ralf; Schmidt, Jana; Diallo, Ousmane; Csaplovics, Elmar

2009-05-01

The geographic term "Niger Inland Delta" stands for a vast plain of approximately 40,000 km(2), which is situated in the western Sahel (Republic of Mali). The Inland Delta is affected by yearly inundation through the variable water levels of the Niger-Bani river system. Due to a good availability of (surface) water, the ecosystem at the Niger Inland Delta serves as resting place stop-over for many migrating birds and other wildlife species as well as economic base for farmers and pastoral people. To foster the sustainable usage of its natural resources and to protect this natural heritage, the entire Niger Inland Delta became RAMSAR site in 2004. This paper aims to test to which extent texture analysis can improve the quality of flood monitoring in a semi-arid environment using spatially high resolution ASAR imaging mode data. We found the Gray Level Dependence Method (GLDM) was most suitable proceeding for our data. Several statistical parameters were calculated via co-occurrence matrices and were used to classify the images in different gradation of soil moisture classes. In a second step we used additional information from spatially high resolution optical data (ASTER) to improve the separability of open water areas from moisture/vegetated areas.

Workplace social capital and co-occurrence of lifestyle risk factors: the Finnish Public Sector Study.

PubMed

Väänänen, A; Kouvonen, A; Kivimäki, M; Oksanen, T; Elovainio, M; Virtanen, M; Pentti, J; Vahtera, J

2009-07-01

The aim of this prospective study was to examine the link between individual and ecological workplace social capital and the co-occurrence of adverse lifestyle risk factors such as smoking, heavy drinking, physical inactivity and overweight. Data on 25 897 female and 5476 male public sector employees were analysed. Questionnaire surveys conducted in 2000-2002 (baseline) and 2004-2005 (follow-up) were used to assess workplace social capital, lifestyle risk factors and other characteristics. Multilevel multinomial logistic regression analysis was used to examine associations between individual and ecological social capital and the co-occurrence of lifestyle risk factors. In the cross-sectional analysis adjusted for age, sex, marital status and employer, low social capital at work at both the individual and ecological level was associated with at least a 1.3 times higher odds of having more than two lifestyle risk factors versus having no risk factors. Similar associations were found in the prospective setting. However, additional adjustment for the co-occurrence of risk factors and socioeconomic status at baseline attenuated the result to non-significant. Social capital at work seems to be associated with a lowered risk of co-occurrence of multiple lifestyle risk factors but does not clearly predict the future risk of this co-occurrence.

Computed gray levels in multislice and cone-beam computed tomography.

PubMed

Azeredo, Fabiane; de Menezes, Luciane Macedo; Enciso, Reyes; Weissheimer, Andre; de Oliveira, Rogério Belle

2013-07-01

Gray level is the range of shades of gray in the pixels, representing the x-ray attenuation coefficient that allows for tissue density assessments in computed tomography (CT). An in-vitro study was performed to investigate the relationship between computed gray levels in 3 cone-beam CT (CBCT) scanners and 1 multislice spiral CT device using 5 software programs. Six materials (air, water, wax, acrylic, plaster, and gutta-percha) were scanned with the CBCT and CT scanners, and the computed gray levels for each material at predetermined points were measured with OsiriX Medical Imaging software (Geneva, Switzerland), OnDemand3D (CyberMed International, Seoul, Korea), E-Film (Merge Healthcare, Milwaukee, Wis), Dolphin Imaging (Dolphin Imaging & Management Solutions, Chatsworth, Calif), and InVivo Dental Software (Anatomage, San Jose, Calif). The repeatability of these measurements was calculated with intraclass correlation coefficients, and the gray levels were averaged to represent each material. Repeated analysis of variance tests were used to assess the differences in gray levels among scanners and materials. There were no differences in mean gray levels with the different software programs. There were significant differences in gray levels between scanners for each material evaluated (P <0.001). The software programs were reliable and had no influence on the CT and CBCT gray level measurements. However, the gray levels might have discrepancies when different CT and CBCT scanners are used. Therefore, caution is essential when interpreting or evaluating CBCT images because of the significant differences in gray levels between different CBCT scanners, and between CBCT and CT values. Copyright © 2013 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Results of a conservation agreement and strategy for Rabbit Valley gilia (Gilia caespitosa)

Treesearch

L. A. Armstrong; T. O. Clark; R. B. Campbell

2001-01-01

Gilia caespitosa Gray (Rabbit Valley gilia) is a rare species restricted to scattered occurrences from the northern Waterpocket Fold to Thousand Lakes Mountain and Rabbit Valley in Wayne County, Utah. This species is a very narrow endemic, known only from unstable and faulting soils of detrital Navajo Sandstone. Species occurrences are often found with limited numbers...

Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

NASA Astrophysics Data System (ADS)

Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

2016-05-01

Keeping abreast of trends in the articles and rapidly grasping a body of article's key points and relationship from a holistic perspective is a new challenge in both literature research and text mining. As the important component, keywords can present the core idea of the academic article. Usually, articles on a single theme or area could share one or some same keywords, and we can analyze topological features and evolution of the articles co-keyword networks and keywords co-occurrence networks to realize the in-depth analysis of the articles. This paper seeks to integrate statistics, text mining, complex networks and visualization to analyze all of the academic articles on one given theme, complex network(s). All 5944 ;complex networks; articles that were published between 1990 and 2013 and are available on the Web of Science are extracted. Based on the two-mode affiliation network theory, a new frontier of complex networks, we constructed two different networks, one taking the articles as nodes, the co-keyword relationships as edges and the quantity of co-keywords as the weight to construct articles co-keyword network, and another taking the articles' keywords as nodes, the co-occurrence relationships as edges and the quantity of simultaneous co-occurrences as the weight to construct keyword co-occurrence network. An integrated method for analyzing the topological features and evolution of the articles co-keyword network and keywords co-occurrence networks is proposed, and we also defined a new function to measure the innovation coefficient of the articles in annual level. This paper provides a useful tool and process for successfully achieving in-depth analysis and rapid understanding of the trends and relationships of articles in a holistic perspective.

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

Mateos, M-J; Brandan, M-E; Gastelum, A

Purpose: To evaluate the time evolution of texture parameters, based on the gray level co-occurrence matrix (GLCM), in subtracted images of 17 patients (10 malignant and 7 benign) subjected to contrast-enhanced digital mammography (CEDM). The goal is to determine the sensitivity of texture to iodine uptake at the lesion, and its correlation (or lack of) with mean-pixel-value (MPV). Methods: Acquisition of clinical images followed a single-energy CEDM protocol using Rh/Rh/48 kV plus external 0.5 cm Al from a Senographe DS unit. Prior to the iodine-based contrast medium (CM) administration a mask image was acquired; four CM images were obtained 1,more » 2, 3, and 5 minutes after CM injection. Temporal series were obtained by logarithmic subtraction of registered CM minus mask images.Regions of interest (ROI) for the lesion were drawn by a radiologist and the texture was analyzed. GLCM was evaluated at a 3 pixel distance, 0° angle, and 64 gray-levels. Pixels identified as registration errors were excluded from the computation. 17 texture parameters were chosen, classified according to similarity into 7 groups, and analyzed. Results: In all cases the texture parameters within a group have similar dynamic behavior. Two texture groups (associated to cluster and sum mean) show a strong correlation with MPV; their average correlation coefficient (ACC) is r{sup 2}=0.90. Other two groups (contrast, homogeneity) remain constant with time, that is, a low-sensitivity to CM uptake. Three groups (regularity, lacunarity and diagonal moment) are sensitive to CM uptake but less correlated with MPV; their ACC is r{sup 2}=0.78. Conclusion: This analysis has shown that, at least groups associated to regularity, lacunarity and diagonal moment offer dynamical information additional to the mean pixel value due to the presence of CM at the lesion. The next step will be the analysis in terms of the lesion pathology. Authors thank PAPIIT-IN105813 for support. Consejo Nacional de Ciencia Y Tecnologia, PAPIIT-IN105813.« less

SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom

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

Xie, Y; Wang, J; Wang, C

Purpose: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. Methods: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were keptmore » as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. Results: For different NEX, 31 out of 32 texture features’ range are within 10%. For different phase encoding steps, 31 out of 32 texture features’ range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features’ range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features’ range are within 10%. Conclusion: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.« less

SU-E-J-265: Feasibility Study of Texture Analysis for Prognosis of Local Tumor Recurrence Within 5-Years for Pharyngeal-Laryngeal Carcinoma Patients Received Radiotherapy Treatment

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

Huang, W; Tu, S

Purpose: Pharyngeal and laryngeal carcinomas (PLC) are among the top leading cancers in Asian populations. Typically the tumor may recur and progress in a short period of time if radiotherapy fails to deliver a successful treatment. Here we used image texture features extracted from images of computed tomography (CT) planning and conducted a retrospective study to evaluate whether texture analysis is a feasible approach to predict local tumor recurrence for PLC patients received radiotherapy treatment. Methods: CT planning images of 100 patients with PLC treated by radiotherapy at our facility between 2001 and 2010 are collected. These patients were receivedmore » two separate CT scans, before and mid-course of the treatment delivery. Before the radiotherapy, a CT scanning was used for the first treatment planning. A total of 30 fractions were used in the treatment and patients were scanned with a second CT around the end of the fifteenth delivery for an adaptive treatment planning. Only patients who were treated with intensity modulated radiation therapy and RapidArc were selected. Treatment planning software of Eclipse was used. The changes of texture parameters between two CT acquisitions were computed to determine whether they were correlated to the local tumor recurrence. The following texture parameters were used in the preliminary assessment: mean, variance, standard deviation, skewness, kurtosis, energy, entropy, inverse difference moment, cluster shade, inertia, cluster prominence, gray-level co-occurrence matrix, and gray-level run-length matrix. The study was reviewed and approved by the committee of our institutional review board. Results: Our calculations suggested the following texture parameters were correlated with the local tumor recurrence: skewness, kurtosis, entropy, and inertia (p<0.0.05). Conclusion: The preliminary results were positive. However some works remain crucial to be completed, including addition of texture parameters for different image features, sensitivity of tumor segmentation variations, and effect of image filtering.« less

[A voxel-based morphometric analysis of brain gray matter in online game addicts].

PubMed

Weng, Chuan-bo; Qian, Ruo-bing; Fu, Xian-ming; Lin, Bin; Ji, Xue-bing; Niu, Chao-shi; Wang, Ye-han

2012-12-04

To explore the possible brain mechanism of online game addiction (OGA) in terms of brain morphology through voxel-based morphometric (VBM) analysis. Seventeen subjects with OGA and 17 age- and gender-matched healthy controls (HC group) were recruited from Department of Psychology at our hospital during February-December 2011. The internet addiction scale (IAS) was used to measure the degree of OGA tendency. Magnetic resonance imaging (MRI) scans were performed to acquire 3-dimensional T1-weighted images. And FSL 4.1 software was employed to confirm regional gray matter volume changes. For the regions where OGA subjects showed significantly different gray matter volumes from the controls, the gray matter volumes of these areas were extracted, averaged and regressed against the scores of IAS. The OGA group had lower gray matter volume in left orbitofrontal cortex (OFC), left medial prefrontal cortex (mPFC), bilateral insula (INS), left posterior cingulate cortex (PCC) and left supplementary motor area (SMA). Gray matter volumes of left OFC and bilateral INS showed a negative correlation with the scores of IAS (r = -0.65, r = -0.78, P < 0.05). Gray matter volume changes are present in online game addicts and they may be correlated with the occurrence and maintenance of OGA.

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.

PubMed

Milenković, Jana; Dalmış, Mehmet Ufuk; Žgajnar, Janez; Platel, Bram

2017-09-01

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI. The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate. The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively, compared to AUC values of previous approach of 0.8562 and 0.8311, respectively. The proposed approach based on 2D textural features quantifying spatiotemporal changes of the contrast-agent uptake significantly outperforms the previous approach based on 3D morphology and dynamic analysis in differentiating the malignant and benign breast lesions, showing its potential to aid clinical decision making. © 2017 American Association of Physicists in Medicine.

Urinary bladder cancer T-staging from T2-weighted MR images using an optimal biomarker approach

NASA Astrophysics Data System (ADS)

Wang, Chuang; Udupa, Jayaram K.; Tong, Yubing; Chen, Jerry; Venigalla, Sriram; Odhner, Dewey; Guzzo, Thomas J.; Christodouleas, John; Torigian, Drew A.

2018-02-01

Magnetic resonance imaging (MRI) is often used in clinical practice to stage patients with bladder cancer to help plan treatment. However, qualitative assessment of MR images is prone to inaccuracies, adversely affecting patient outcomes. In this paper, T2-weighted MR image-based quantitative features were extracted from the bladder wall in 65 patients with bladder cancer to classify them into two primary tumor (T) stage groups: group 1 - T stage < T2, with primary tumor locally confined to the bladder, and group 2 - T stage < T2, with primary tumor locally extending beyond the bladder. The bladder was divided into 8 sectors in the axial plane, where each sector has a corresponding reference standard T stage that is based on expert radiology qualitative MR image review and histopathologic results. The performance of the classification for correct assignment of T stage grouping was then evaluated at both the patient level and the sector level. Each bladder sector was divided into 3 shells (inner, middle, and outer), and 15,834 features including intensity features and texture features from local binary pattern and gray-level co-occurrence matrix were extracted from the 3 shells of each sector. An optimal feature set was selected from all features using an optimal biomarker approach. Nine optimal biomarker features were derived based on texture properties from the middle shell, with an area under the ROC curve of AUC value at the sector and patient level of 0.813 and 0.806, respectively.

An iris recognition algorithm based on DCT and GLCM

NASA Astrophysics Data System (ADS)

Feng, G.; Wu, Ye-qing

2008-04-01

With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and more important. So many different techniques for person's status identity were proposed for this practical usage. Conventional person's status identity methods like password and identification card are not always reliable. A wide variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot research point in the past several years. This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that the algorithm is effective and feasible with iris recognition.

Ant-cuckoo colony optimization for feature selection in digital mammogram.

PubMed

Jona, J B; Nagaveni, N

2014-01-15

Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques.

Feasibility study of stain-free classification of cell apoptosis based on diffraction imaging flow cytometry and supervised machine learning techniques.

PubMed

Feng, Jingwen; Feng, Tong; Yang, Chengwen; Wang, Wei; Sa, Yu; Feng, Yuanming

2018-06-01

This study was to explore the feasibility of prediction and classification of cells in different stages of apoptosis with a stain-free method based on diffraction images and supervised machine learning. Apoptosis was induced in human chronic myelogenous leukemia K562 cells by cis-platinum (DDP). A newly developed technique of polarization diffraction imaging flow cytometry (p-DIFC) was performed to acquire diffraction images of the cells in three different statuses (viable, early apoptotic and late apoptotic/necrotic) after cell separation through fluorescence activated cell sorting with Annexin V-PE and SYTOX® Green double staining. The texture features of the diffraction images were extracted with in-house software based on the Gray-level co-occurrence matrix algorithm to generate datasets for cell classification with supervised machine learning method. Therefore, this new method has been verified in hydrogen peroxide induced apoptosis model of HL-60. Results show that accuracy of higher than 90% was achieved respectively in independent test datasets from each cell type based on logistic regression with ridge estimators, which indicated that p-DIFC system has a great potential in predicting and classifying cells in different stages of apoptosis.

Medical image retrieval system using multiple features from 3D ROIs

NASA Astrophysics Data System (ADS)

Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

2012-02-01

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

Recognition of skin melanoma through dermoscopic image analysis

NASA Astrophysics Data System (ADS)

Gómez, Catalina; Herrera, Diana Sofia

2017-11-01

Melanoma skin cancer diagnosis can be challenging due to the similarities of the early stage symptoms with regular moles. Standardized visual parameters can be determined and characterized to suspect a melanoma cancer type. The automation of this diagnosis could have an impact in the medical field by providing a tool to support the specialists with high accuracy. The objective of this study is to develop an algorithm trained to distinguish a highly probable melanoma from a non-dangerous mole by the segmentation and classification of dermoscopic mole images. We evaluate our approach on the dataset provided by the International Skin Imaging Collaboration used in the International Challenge Skin Lesion Analysis Towards Melanoma Detection. For the segmentation task, we apply a preprocessing algorithm and use Otsu's thresholding in the best performing color space; the average Jaccard Index in the test dataset is 70.05%. For the subsequent classification stage, we use joint histograms in the YCbCr color space, a RBF Gaussian SVM trained with five features concerning circularity and irregularity of the segmented lesion, and the Gray Level Co-occurrence matrix features for texture analysis. These features are combined to obtain an Average Classification Accuracy of 63.3% in the test dataset.

Texture Analysis and Synthesis of Malignant and Benign Mediastinal Lymph Nodes in Patients with Lung Cancer on Computed Tomography

NASA Astrophysics Data System (ADS)

Pham, Tuan D.; Watanabe, Yuzuru; Higuchi, Mitsunori; Suzuki, Hiroyuki

2017-02-01

Texture analysis of computed tomography (CT) imaging has been found useful to distinguish subtle differences, which are in- visible to human eyes, between malignant and benign tissues in cancer patients. This study implemented two complementary methods of texture analysis, known as the gray-level co-occurrence matrix (GLCM) and the experimental semivariogram (SV) with an aim to improve the predictive value of evaluating mediastinal lymph nodes in lung cancer. The GLCM was explored with the use of a rich set of its derived features, whereas the SV feature was extracted on real and synthesized CT samples of benign and malignant lymph nodes. A distinct advantage of the computer methodology presented herein is the alleviation of the need for an automated precise segmentation of the lymph nodes. Using the logistic regression model, a sensitivity of 75%, specificity of 90%, and area under curve of 0.89 were obtained in the test population. A tenfold cross-validation of 70% accuracy of classifying between benign and malignant lymph nodes was obtained using the support vector machines as a pattern classifier. These results are higher than those recently reported in literature with similar studies.

Wood texture classification by fuzzy neural networks

NASA Astrophysics Data System (ADS)

Gonzaga, Adilson; de Franca, Celso A.; Frere, Annie F.

1999-03-01

The majority of scientific papers focusing on wood classification for pencil manufacturing take into account defects and visual appearance. Traditional methodologies are base don texture analysis by co-occurrence matrix, by image modeling, or by tonal measures over the plate surface. In this work, we propose to classify plates of wood without biological defects like insect holes, nodes, and cracks, by analyzing their texture. By this methodology we divide the plate image in several rectangular windows or local areas and reduce the number of gray levels. From each local area, we compute the histogram of difference sand extract texture features, given them as input to a Local Neuro-Fuzzy Network. Those features are from the histogram of differences instead of the image pixels due to their better performance and illumination independence. Among several features like media, contrast, second moment, entropy, and IDN, the last three ones have showed better results for network training. Each LNN output is taken as input to a Partial Neuro-Fuzzy Network (PNFN) classifying a pencil region on the plate. At last, the outputs from the PNFN are taken as input to a Global Fuzzy Logic doing the plate classification. Each pencil classification within the plate is done taking into account each quality index.

Image processing analysis of geospatial uav orthophotos for palm oil plantation monitoring

NASA Astrophysics Data System (ADS)

Fahmi, F.; Trianda, D.; Andayani, U.; Siregar, B.

2018-03-01

Unmanned Aerial Vehicle (UAV) is one of the tools that can be used to monitor palm oil plantation remotely. With the geospatial orthophotos, it is possible to identify which part of the plantation land is fertile for planted crops, means to grow perfectly. It is also possible furthermore to identify less fertile in terms of growth but not perfect, and also part of plantation field that is not growing at all. This information can be easily known quickly with the use of UAV photos. In this study, we utilized image processing algorithm to process the orthophotos for more accurate and faster analysis. The resulting orthophotos image were processed using Matlab including classification of fertile, infertile, and dead palm oil plants by using Gray Level Co-Occurrence Matrix (GLCM) method. The GLCM method was developed based on four direction parameters with specific degrees 0°, 45°, 90°, and 135°. From the results of research conducted with 30 image samples, it was found that the accuracy of the system can be reached by using the features extracted from the matrix as parameters Contras, Correlation, Energy, and Homogeneity.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Computer-aided diagnosis in phase contrast imaging X-ray computed tomography for quantitative characterization of ex vivo human patellar cartilage.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismuller, Axel

2013-10-01

Visualization of ex vivo human patellar cartilage matrix through the phase contrast imaging X-ray computed tomography (PCI-CT) has been previously demonstrated. Such studies revealed osteoarthritis-induced changes to chondrocyte organization in the radial zone. This study investigates the application of texture analysis to characterizing such chondrocyte patterns in the presence and absence of osteoarthritic damage. Texture features derived from Minkowski functionals (MF) and gray-level co-occurrence matrices (GLCM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These texture features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). The best classification performance was observed with the MF features perimeter (AUC: 0.94 ±0.08 ) and "Euler characteristic" (AUC: 0.94 ±0.07 ), and GLCM-derived feature "Correlation" (AUC: 0.93 ±0.07). These results suggest that such texture features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix, enabling classification of cartilage as healthy or osteoarthritic with high accuracy.

Assessing clutter reduction in parallel coordinates using image processing techniques

NASA Astrophysics Data System (ADS)

Alhamaydh, Heba; Alzoubi, Hussein; Almasaeid, Hisham

2018-01-01

Information visualization has appeared as an important research field for multidimensional data and correlation analysis in recent years. Parallel coordinates (PCs) are one of the popular techniques to visual high-dimensional data. A problem with the PCs technique is that it suffers from crowding, a clutter which hides important data and obfuscates the information. Earlier research has been conducted to reduce clutter without loss in data content. We introduce the use of image processing techniques as an approach for assessing the performance of clutter reduction techniques in PC. We use histogram analysis as our first measure, where the mean feature of the color histograms of the possible alternative orderings of coordinates for the PC images is calculated and compared. The second measure is the extracted contrast feature from the texture of PC images based on gray-level co-occurrence matrices. The results show that the best PC image is the one that has the minimal mean value of the color histogram feature and the maximal contrast value of the texture feature. In addition to its simplicity, the proposed assessment method has the advantage of objectively assessing alternative ordering of PC visualization.

Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Jiang, Yuan Yuan; Kim, Sung Min

2015-01-01

This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangiomas, and 33 malignancies. A total of 42 hybrid textural features that composed of 5 first order statistics, 18 gray level co-occurrence matrices, 18 Law's, and echogenicity were extracted. A total of 29 key features that were selected by principal component analysis were used as a set of inputs for a feed-forward neural network. For each lesion, the performance of the diagnosis was evaluated by using the positive predictive value, negative predictive value, sensitivity, specificity, and accuracy. The results of the experiment indicate that the proposed method exhibits great performance, a high diagnosis accuracy of over 96% among all focal liver lesion groups (cyst vs. hemangioma, cyst vs. malignant, and hemangioma vs. malignant) on ultrasound images. The accuracy was slightly increased when echogenicity was included in the optimal feature set. These results indicate that it is possible for the proposed method to be applied clinically.

Changing contributions of stochastic and deterministic processes in community assembly over a successional gradient.

PubMed

Måren, Inger Elisabeth; Kapfer, Jutta; Aarrestad, Per Arild; Grytnes, John-Arvid; Vandvik, Vigdis

2018-01-01

Successional dynamics in plant community assembly may result from both deterministic and stochastic ecological processes. The relative importance of different ecological processes is expected to vary over the successional sequence, between different plant functional groups, and with the disturbance levels and land-use management regimes of the successional systems. We evaluate the relative importance of stochastic and deterministic processes in bryophyte and vascular plant community assembly after fire in grazed and ungrazed anthropogenic coastal heathlands in Northern Europe. A replicated series of post-fire successions (n = 12) were initiated under grazed and ungrazed conditions, and vegetation data were recorded in permanent plots over 13 years. We used redundancy analysis (RDA) to test for deterministic successional patterns in species composition repeated across the replicate successional series and analyses of co-occurrence to evaluate to what extent species respond synchronously along the successional gradient. Change in species co-occurrences over succession indicates stochastic successional dynamics at the species level (i.e., species equivalence), whereas constancy in co-occurrence indicates deterministic dynamics (successional niche differentiation). The RDA shows high and deterministic vascular plant community compositional change, especially early in succession. Co-occurrence analyses indicate stochastic species-level dynamics the first two years, which then give way to more deterministic replacements. Grazed and ungrazed successions are similar, but the early stage stochasticity is higher in ungrazed areas. Bryophyte communities in ungrazed successions resemble vascular plant communities. In contrast, bryophytes in grazed successions showed consistently high stochasticity and low determinism in both community composition and species co-occurrence. In conclusion, stochastic and individualistic species responses early in succession give way to more niche-driven dynamics in later successional stages. Grazing reduces predictability in both successional trends and species-level dynamics, especially in plant functional groups that are not well adapted to disturbance. © 2017 The Authors. Ecology, published by Wiley Periodicals, Inc., on behalf of the Ecological Society of America.

Theoretical foundations of spatially-variant mathematical morphology part ii: gray-level images.

PubMed

Bouaynaya, Nidhal; Schonfeld, Dan

2008-05-01

In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the Euclidean space. The proposed theory preserves the geometrical concept of the structuring function, which provides the foundation of classical morphology and is essential in signal and image processing applications. We define the basic SV gray-level morphological operators (i.e., SV gray-level erosion, dilation, opening, and closing) and investigate their properties. We demonstrate the ubiquity of SV gray-level morphological systems by deriving a kernel representation for a large class of systems, called V-systems, in terms of the basic SV graylevel morphological operators. A V-system is defined to be a gray-level operator, which is invariant under gray-level (vertical) translations. Particular attention is focused on the class of SV flat gray-level operators. The kernel representation for increasing V-systems is a generalization of Maragos' kernel representation for increasing and translation-invariant function-processing systems. A representation of V-systems in terms of their kernel elements is established for increasing and upper-semi-continuous V-systems. This representation unifies a large class of spatially-variant linear and non-linear systems under the same mathematical framework. Finally, simulation results show the potential power of the general theory of gray-level spatially-variant mathematical morphology in several image analysis and computer vision applications.

P04.19 Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization.

PubMed Central

Molina, D.; Pérez-Beteta, J.; Martínez-González, A.; Velásquez, C.; Martino, J.; Luque, B.; Revert, A.; Herruzo, I.; Arana, E.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Textural analysis refers to a variety of mathematical methods used to quantify the spatial variations in grey levels within images. In brain tumors, textural features have a great potential as imaging biomarkers having been shown to correlate with survival, tumor grade, tumor type, etc. However, these measures should be reproducible under dynamic range and matrix size changes for their clinical use. Our aim is to study this robustness in brain tumors with 3D magnetic resonance imaging, not previously reported in the literature. Materials and methods: 3D T1-weighted images of 20 patients with glioblastoma (64.80 ± 9.12 years-old) obtained from a 3T scanner were analyzed. Tumors were segmented using an in-house semi-automatic 3D procedure. A set of 16 3D textural features of the most common types (co-occurrence and run-length matrices) were selected, providing regional (run-length based measures) and local information (co-ocurrence matrices) on the tumor heterogeneity. Feature robustness was assessed by means of the coefficient of variation (CV) under both dynamic range (16, 32 and 64 gray levels) and/or matrix size (256x256 and 432x432) changes. Results: None of the textural features considered were robust under dynamic range changes. The textural co-occurrence matrix feature Entropy was the only textural feature robust (CV < 10%) under spatial resolution changes. Conclusions: In general, textural measures of three-dimensional brain tumor images are neither robust under dynamic range nor under matrix size changes. Thus, it becomes mandatory to fix standards for image rescaling after acquisition before the textural features are computed if they are to be used as imaging biomarkers. For T1-weighted images a dynamic range of 16 grey levels and a matrix size of 256x256 (and isotropic voxel) is found to provide reliable and comparable results and is feasible with current MRI scanners. The implications of this work go beyond the specific tumor type and MRI sequence studied here and pose the need for standardization in textural feature calculation of oncological images. FUNDING: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

PubMed

Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

2013-01-01

The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumor grading.

Plasma-Sprayed High Entropy Alloys: Microstructure and Properties of AlCoCrFeNi and MnCoCrFeNi

NASA Astrophysics Data System (ADS)

Ang, Andrew Siao Ming; Berndt, Christopher C.; Sesso, Mitchell L.; Anupam, Ameey; S, Praveen; Kottada, Ravi Sankar; Murty, B. S.

2015-02-01

High entropy alloys (HEAs) represent a new class of materials that present novel phase structures and properties. Apart from bulk material consolidation methods such as casting and sintering, HEAs can also be deposited as a surface coating. In this work, thermal sprayed HEA coatings are investigated that may be used as an alternative bond coat material for a thermal barrier coating system. Nanostructured HEAs that were based on AlCoCrFeNi and MnCoCrFeNi were prepared by ball milling and then plasma sprayed. Splat studies were assessed to optimise the appropriate thermal spray parameters and spray deposits were prepared. After mechanical alloying, aluminum-based and manganese-based HEA powders revealed contrary prominences of BCC and FCC phases in their X-ray diffraction patterns. However, FCC phase was observed as the major phase present in both of the plasma-sprayed AlCoCrFeNi and MnCoCrFeNi coatings. There were also minor oxide peaks detected, which can be attributed to the high temperature processing. The measured porosity levels for AlCoCrFeNi and MnCoCrFeNi coatings were 9.5 ± 2.3 and 7.4 ± 1.3 pct, respectively. Three distinct phase contrasts, dark gray, light gray and white, were observed in the SEM images, with the white regions corresponding to retained multicomponent HEAs. The Vickers hardness (HV0.3kgf) was 4.13 ± 0.43 and 4.42 ± 0.60 GPa for AlCoCrFeNi and MnCoCrFeNi, respectively. Both type of HEAs coatings exhibited anisotropic mechanical behavior due to their lamellar, composite-type microstructure.

Estimating local scaling properties for the classification of interstitial lung disease patterns

NASA Astrophysics Data System (ADS)

Huber, Markus B.; Nagarajan, Mahesh B.; Leinsinger, Gerda; Ray, Lawrence A.; Wismueller, Axel

2011-03-01

Local scaling properties of texture regions were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honeycombing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and the estimation of local scaling properties with Scaling Index Method (SIM). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions including the Bonferroni correction. The best classification results were obtained by the set of SIM features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers with the highest accuracy (94.1%, 93.7%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced texture features using local scaling properties can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

The co-occurrence of aggression and self-harm: systematic literature review.

PubMed

O'Donnell, Orla; House, Allan; Waterman, Mitch

2015-04-01

Epidemiological research supports an association between aggression and self-harm through data on the frequency with which individuals exhibit both behaviours. Unbiased evidence, however, is needed to draw conclusions about the nature and extent of co-occurrence. Systematic review of published studies was undertaken to evaluate whether or not the frequency with which aggression and self-harm co-occur is beyond that which would be expected by chance. Outcome measures included: (a) between-group differences on a standardised aggression/self-harm measure - the groups defined by scores on a measure of the other behaviour; (b) correlations between the two behaviours; (c) co-occurrence rates in populations defined by the presence of either behaviour; (d) co-occurrence rates in populations not defined by either behaviour. Odds ratios were calculated for studies presenting complete frequency data. 123 studies, some yielding more than one type of result, met the inclusion criteria. Most case-control studies found elevated levels of aggression in self-harming populations (or self-harm in aggressive populations) compared to controls. The majority of correlational, co-occurrence rate, and odds ratio data found aggression and self-harm to be associated. Results were subject to descriptive synthesis only and thus, unable to report an overall effect size. Evidence suggests that aggression and self-harm frequently co-occur. Such evidence necessitates more theoretical discussion and associated research on the source and nature of co-occurrence. Nonetheless, individuals who present with one behaviour may be considered an 'at-risk' group in terms of exhibiting the other. Such evidence holds implications for practice (e.g. risk assessment). Copyright © 2015. Published by Elsevier B.V.

Grays Harbor and Chehalis River Improvements to Navigation Environmental Studies. Wildlife Studies at Proposed Disposal Sites in Grays Harbor, Washington,

DTIC Science & Technology

1982-01-01

sltand. T 𔃼~P i’ W 210 three times VtwCerI November IOC’C -nd ~co l.Etls ~ ec!,!zervc-o betxwe H -gF 12 Th -ind hl rway u- 7Plie Sicuobh. E. Cumin -s 1... stress imposed by dredge dsosal ;ictivities on these species. It is difficult to rredict the effects of establishing a salt marsh in Grays Harbor on

Effort-reward imbalance at work and the co-occurrence of lifestyle risk factors: cross-sectional survey in a sample of 36,127 public sector employees

PubMed Central

Kouvonen, Anne; Kivimäki, Mika; Virtanen, Marianna; Heponiemi, Tarja; Elovainio, Marko; Pentti, Jaana; Linna, Anne; Vahtera, Jussi

2006-01-01

Background In occupational life, a mismatch between high expenditure of effort and receiving few rewards may promote the co-occurrence of lifestyle risk factors, however, there is insufficient evidence to support or refute this hypothesis. The aim of this study is to examine the extent to which the dimensions of the Effort-Reward Imbalance (ERI) model – effort, rewards and ERI – are associated with the co-occurrence of lifestyle risk factors. Methods Based on data from the Finnish Public Sector Study, cross-sectional analyses were performed for 28,894 women and 7233 men. ERI was conceptualized as a ratio of effort and rewards. To control for individual differences in response styles, such as a personal disposition to answer negatively to questionnaires, occupational and organizational -level ecological ERI scores were constructed in addition to individual-level ERI scores. Risk factors included current smoking, heavy drinking, body mass index ≥25 kg/m2, and physical inactivity. Multinomial logistic regression models were used to estimate the likelihood of having one risk factor, two risk factors, and three or four risk factors. The associations between ERI and single risk factors were explored using binary logistic regression models. Results After adjustment for age, socioeconomic position, marital status, and type of job contract, women and men with high ecological ERI were 40% more likely to have simultaneously ≥3 lifestyle risk factors (vs. 0 risk factors) compared with their counterparts with low ERI. When examined separately, both low ecological effort and low ecological rewards were also associated with an elevated prevalence of risk factor co-occurrence. The results obtained with the individual-level scores were in the same direction. The associations of ecological ERI with single risk factors were generally less marked than the associations with the co-occurrence of risk factors. Conclusion This study suggests that a high ratio of occupational efforts relative to rewards may be associated with an elevated risk of having multiple lifestyle risk factors. However, an unexpected association between low effort and a higher likelihood of risk factor co-occurrence as well as the absence of data on overcommitment (and thereby a lack of full test of the ERI model) warrant caution in regard to the extent to which the entire ERI model is supported by our evidence. PMID:16464262

Effort-reward imbalance at work and the co-occurrence of lifestyle risk factors: cross-sectional survey in a sample of 36,127 public sector employees.

PubMed

Kouvonen, Anne; Kivimäki, Mika; Virtanen, Marianna; Heponiemi, Tarja; Elovainio, Marko; Pentti, Jaana; Linna, Anne; Vahtera, Jussi

2006-02-07

In occupational life, a mismatch between high expenditure of effort and receiving few rewards may promote the co-occurrence of lifestyle risk factors, however, there is insufficient evidence to support or refute this hypothesis. The aim of this study is to examine the extent to which the dimensions of the Effort-Reward Imbalance (ERI) model--effort, rewards and ERI--are associated with the co-occurrence of lifestyle risk factors. Based on data from the Finnish Public Sector Study, cross-sectional analyses were performed for 28,894 women and 7233 men. ERI was conceptualized as a ratio of effort and rewards. To control for individual differences in response styles, such as a personal disposition to answer negatively to questionnaires, occupational and organizational-level ecological ERI scores were constructed in addition to individual-level ERI scores. Risk factors included current smoking, heavy drinking, body mass index > or =25 kg/m2, and physical inactivity. Multinomial logistic regression models were used to estimate the likelihood of having one risk factor, two risk factors, and three or four risk factors. The associations between ERI and single risk factors were explored using binary logistic regression models. After adjustment for age, socioeconomic position, marital status, and type of job contract, women and men with high ecological ERI were 40% more likely to have simultaneously > or =3 lifestyle risk factors (vs. 0 risk factors) compared with their counterparts with low ERI. When examined separately, both low ecological effort and low ecological rewards were also associated with an elevated prevalence of risk factor co-occurrence. The results obtained with the individual-level scores were in the same direction. The associations of ecological ERI with single risk factors were generally less marked than the associations with the co-occurrence of risk factors. This study suggests that a high ratio of occupational efforts relative to rewards may be associated with an elevated risk of having multiple lifestyle risk factors. However, an unexpected association between low effort and a higher likelihood of risk factor co-occurrence as well as the absence of data on overcommitment (and thereby a lack of full test of the ERI model) warrant caution in regard to the extent to which the entire ERI model is supported by our evidence.

Genetic Correlation and Gene–Environment Interaction Between Alcohol Problems and Educational Level in Young Adulthood*

PubMed Central

Latvala, Antti; Dick, Danielle M.; Tuulio-Henriksson, Annamari; Suvisaari, Jaana; Viken, Richard J.; Rose, Richard J.; Kaprio, Jaakko

2011-01-01

Objective: A lower level of education often co-occurs with alcohol problems, but factors underlying this co-occurrence are not well understood. Specifically, whether these outcomes share part of their underlying genetic influences has not been widely studied. Educational level also reflects various environmental influences that may moderate the genetic etiology of alcohol problems, but gene–environment interactions between educational attainment and alcohol problems are unknown. Method: We studied the two nonmutually exclusive possibilities of common genetic influences and gene–environment interaction between alcohol problems and low education using a population-based sample (n = 4,858) of Finnish young adult twins (Mage = 24.5 years, range: 22.8–28.6 years). Alcohol problems were assessed with the Rutgers Alcohol Problem Index and self-reported maximum number of drinks consumed in a 24-hour period. Years of education, based on completed and ongo-ing studies, represented educational level. Results: Educational level was inversely associated with alcohol problems in young adulthood, and this association was most parsimoniously explained by overlapping genetic influences. Independent of this co-occurrence, higher education was associated with increased relative importance of genetic influences on alcohol problems, whereas environmental factors had a greater effect among twins with lower education. Conclusions: Our findings suggest a complex relationship between educational level and alcohol problems in young adulthood. Lower education is related to higher levels of alcohol problems, and this co-occurrence is influenced by genetic factors affecting both phenotypes. In addition, educational level moderates the importance of genetic and environmental influences on alcohol problems, possibly reflecting differences in social-control mechanisms related to educational level. PMID:21388594

Effects of urbanization on carnivore species distribution and richness

USGS Publications Warehouse

Ordenana, Miguel A.; Crooks, Kevin R.; Boydston, Erin E.; Fisher, Robert N.; Lyren, Lisa M.; Siudyla, Shalene; Haas, Christopher D.; Harris, Sierra; Hathaway, Stacie A.; Turschak, Greta M.; Miles, A. Keith; Van Vuren, Dirk H.

2010-01-01

Urban development can have multiple effects on mammalian carnivore communities. We conducted a meta-analysis of 7,929 photographs from 217 localities in 11 camera-trap studies across coastal southern California to describe habitat use and determine the effects of urban proximity (distance to urban edge) and intensity (percentage of area urbanized) on carnivore occurrence and species richness in natural habitats close to the urban boundary. Coyotes (Canis latrans) and bobcats (Lynx rufus) were distributed widely across the region. Domestic dogs (Canis lupus familiaris), striped skunks (Mephitis mephitis), raccoons (Procyon lotor), gray foxes (Urocyon cinereoargenteus), mountain lions (Puma concolor), and Virginia opossums (Didelphis virginiana) were detected less frequently, and long-tailed weasels (Mustela frenata), American badgers (Taxidea taxus), western spotted skunks (Spilogale gracilis), and domestic cats (Felis catus) were detected rarely. Habitat use generally reflected availability for most species. Coyote and raccoon occurrence increased with both proximity to and intensity of urbanization, whereas bobcat, gray fox, and mountain lion occurrence decreased with urban proximity and intensity. Domestic dogs and Virginia opossums exhibited positive and weak negative relationships, respectively, with urban intensity but were unaffected by urban proximity. Striped skunk occurrence increased with urban proximity but decreased with urban intensity. Native species richness was negatively associated with urban intensity but not urban proximity, probably because of the stronger negative response of individual species to urban intensity.

Environmental heterogeneity, dispersal mode, and co-occurrence in stream macroinvertebrates

PubMed Central

Heino, Jani

2013-01-01

Both environmental heterogeneity and mode of dispersal may affect species co-occurrence in metacommunities. Aquatic invertebrates were sampled in 20–30 streams in each of three drainage basins, differing considerably in environmental heterogeneity. Each drainage basin was further divided into two equally sized sets of sites, again differing profoundly in environmental heterogeneity. Benthic invertebrate data were divided into three groups of taxa based on overland dispersal modes: passive dispersers with aquatic adults, passive dispersers with terrestrial winged adults, and active dispersers with terrestrial winged adults. The co-occurrence of taxa in each dispersal mode group, drainage basin, and heterogeneity site subset was measured using the C-score and its standardized effect size. The probability of finding high levels of species segregation tended to increase with environmental heterogeneity across the drainage basins. These patterns were, however, contingent on both dispersal mode and drainage basin. It thus appears that environmental heterogeneity and dispersal mode interact in affecting co-occurrence in metacommunities, with passive dispersers with aquatic adults showing random patterns irrespective of environmental heterogeneity, and active dispersers with terrestrial winged adults showing increasing segregation with increasing environmental heterogeneity. PMID:23467653

Integrated stratigraphy of a shallow marine Paleocene-Eocene boundary section, MCBR cores, Maryland (USA)

NASA Astrophysics Data System (ADS)

Self-Trail, J. M.; Robinson, M. M.; Edwards, L. E.; Powars, D. S.; Wandless, G. A.; Willard, D. A.

2013-12-01

An exceptional Paleocene-Eocene boundary section occurs in a cluster of six short (<15m) coreholes (MCBR 1 through 6) drilled near Mattawoman Creek in western Charles County, Maryland. The sediments consist of glauconite-rich sand of the upper Paleocene Aquia Formation and silty clay of the lower Eocene Marlboro Clay. Sediment samples were analyzed for carbon and oxygen isotopes, percent calcium carbonate, calcareous nannofossils, planktic and benthic foraminifera, dinoflagellates, pollen, and lithology. A well-defined carbon isotope excursion (CIE) documents a gradual negative shift in δ13C values that starts below the lithologic break between the Aquia Formation and the Marlboro Clay. A benthic foraminifer extinction event, reduction of calcareous nannofossil assemblages, and change in core color from gray to alternating gray and pink also occurs within the CIE transition. These alternating changes in color coincide with cyclic peaks in the carbon isotope and percent calcium carbonate curves, where gray color corresponds to a positive shift in carbon isotope values and to a corresponding increase in percent benthic and planktic foraminifera. The upper third of the Marlboro Clay is barren of all calcareous microfossil material, although the presence of foraminiferal molds and linings proves that deposition occurred in a marine environment. Co-occurrence of the dinoflagellates Apectodinium augustum and Phthanoperidinium crenulatum at the top of the Marlboro Clay suggests that the Marlboro Clay at Mattawoman Creek is truncated. This is corroborated by the absence in the Marlboro of specimens of the calcareous nannofossil Rhomboaster-Discoaster assemblage, which is restricted to early Eocene Zone NP9b. Based on planktic/benthic foraminifera ratios, deposition of sediments at Mattawoman Creek occurred predominantly in an inner neritic environment, at water depths between 25-50 m. Occasional deepening to approximately 75m (middle neritic environment) occurred in the early Eocene, as represented by the basal Marlboro Clay. The planktic/benthic ratio, however, could also be affected by surface productivity and/or river runoff. The gradual shift up-section in core color from gray to alternating gray and red, to dark red, coupled with dissolution of calcareous microfossil assemblages, is possibly secondary and may represent lysocline shoaling in a nearshore environment. This would suggest that lysocline shoaling continued after the CIE and well into the early Eocene.

Edge co-occurrences can account for rapid categorization of natural versus animal images

NASA Astrophysics Data System (ADS)

Perrinet, Laurent U.; Bednar, James A.

2015-06-01

Making a judgment about the semantic category of a visual scene, such as whether it contains an animal, is typically assumed to involve high-level associative brain areas. Previous explanations require progressively analyzing the scene hierarchically at increasing levels of abstraction, from edge extraction to mid-level object recognition and then object categorization. Here we show that the statistics of edge co-occurrences alone are sufficient to perform a rough yet robust (translation, scale, and rotation invariant) scene categorization. We first extracted the edges from images using a scale-space analysis coupled with a sparse coding algorithm. We then computed the “association field” for different categories (natural, man-made, or containing an animal) by computing the statistics of edge co-occurrences. These differed strongly, with animal images having more curved configurations. We show that this geometry alone is sufficient for categorization, and that the pattern of errors made by humans is consistent with this procedure. Because these statistics could be measured as early as the primary visual cortex, the results challenge widely held assumptions about the flow of computations in the visual system. The results also suggest new algorithms for image classification and signal processing that exploit correlations between low-level structure and the underlying semantic category.

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices.

PubMed

Keller, Brad M; Oustimov, Andrew; Wang, Yan; Chen, Jinbo; Acciavatti, Raymond J; Zheng, Yuanjie; Ray, Shonket; Gee, James C; Maidment, Andrew D A; Kontos, Despina

2015-04-01

An analytical framework is presented for evaluating the equivalence of parenchymal texture features across different full-field digital mammography (FFDM) systems using a physical breast phantom. Phantom images (FOR PROCESSING) are acquired from three FFDM systems using their automated exposure control setting. A panel of texture features, including gray-level histogram, co-occurrence, run length, and structural descriptors, are extracted. To identify features that are robust across imaging systems, a series of equivalence tests are performed on the feature distributions, in which the extent of their intersystem variation is compared to their intrasystem variation via the Hodges-Lehmann test statistic. Overall, histogram and structural features tend to be most robust across all systems, and certain features, such as edge enhancement, tend to be more robust to intergenerational differences between detectors of a single vendor than to intervendor differences. Texture features extracted from larger regions of interest (i.e., [Formula: see text]) and with a larger offset length (i.e., [Formula: see text]), when applicable, also appear to be more robust across imaging systems. This framework and observations from our experiments may benefit applications utilizing mammographic texture analysis on images acquired in multivendor settings, such as in multicenter studies of computer-aided detection and breast cancer risk assessment.

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping

PubMed Central

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-01-01

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply. PMID:27128915

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

PubMed

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-04-26

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply.

In vivo Quantification of the Structural Changes of Collagens in a Melanoma Microenvironment with Second and Third Harmonic Generation Microscopy

NASA Astrophysics Data System (ADS)

Wu, Pei-Chun; Hsieh, Tsung-Yuan; Tsai, Zen-Uong; Liu, Tzu-Ming

2015-03-01

Using in vivo second harmonic generation (SHG) and third harmonic generation (THG) microscopies, we tracked the course of collagen remodeling over time in the same melanoma microenvironment within an individual mouse. The corresponding structural and morphological changes were quantitatively analyzed without labeling using an orientation index (OI), the gray level co-occurrence matrix (GLCM) method, and the intensity ratio of THG to SHG (RTHG/SHG). In the early stage of melanoma development, we found that collagen fibers adjacent to a melanoma have increased OI values and SHG intensities. In the late stages, these collagen networks have more directionality and less homogeneity. The corresponding GLCM traces showed oscillation features and the sum of squared fluctuation VarGLCM increased with the tumor sizes. In addition, the THG intensities of the extracellular matrices increased, indicating an enhanced optical inhomogeneity. Multiplying OI, VarGLCM, and RTHG/SHG together, the combinational collagen remodeling (CR) index at 4 weeks post melanoma implantation showed a 400-times higher value than normal ones. These results validate that our quantitative indices of SHG and THG microscopies are sensitive enough to diagnose the collagen remodeling in vivo. We believe these indices have the potential to help the diagnosis of skin cancers in clinical practice.

Automatic system for radar echoes filtering based on textural features and artificial intelligence

NASA Astrophysics Data System (ADS)

Hedir, Mehdia; Haddad, Boualem

2017-10-01

Among the very popular Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been retained to process Ground Echoes (GE) on meteorological radar images taken from Setif (Algeria) and Bordeaux (France) with different climates and topologies. To achieve this task, AI techniques were associated with textural approaches. We used Gray Level Co-occurrence Matrix (GLCM) and Completed Local Binary Pattern (CLBP); both methods were largely used in image analysis. The obtained results show the efficiency of texture to preserve precipitations forecast on both sites with the accuracy of 98% on Bordeaux and 95% on Setif despite the AI technique used. 98% of GE are suppressed with SVM, this rate is outperforming ANN skills. CLBP approach associated to SVM eliminates 98% of GE and preserves precipitations forecast on Bordeaux site better than on Setif's, while it exhibits lower accuracy with ANN. SVM classifier is well adapted to the proposed application since the average filtering rate is 95-98% with texture and 92-93% with CLBP. These approaches allow removing Anomalous Propagations (APs) too with a better accuracy of 97.15% with texture and SVM. In fact, textural features associated to AI techniques are an efficient tool for incoherent radars to surpass spurious echoes.

An effective method for cirrhosis recognition based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Chen, Yameng; Sun, Gengxin; Lei, Yiming; Zhang, Jinpeng

2018-04-01

Liver disease is one of the main causes of human healthy problem. Cirrhosis, of course, is the critical phase during the development of liver lesion, especially the hepatoma. Many clinical cases are still influenced by the subjectivity of physicians in some degree, and some objective factors such as illumination, scale, edge blurring will affect the judgment of clinicians. Then the subjectivity will affect the accuracy of diagnosis and the treatment of patients. In order to solve the difficulty above and improve the recognition rate of liver cirrhosis, we propose a method of multi-feature fusion to obtain more robust representations of texture in ultrasound liver images, the texture features we extract include local binary pattern(LBP), gray level co-occurrence matrix(GLCM) and histogram of oriented gradient(HOG). In this paper, we firstly make a fusion of multi-feature to recognize cirrhosis and normal liver based on parallel combination concept, and the experimental results shows that the classifier is effective for cirrhosis recognition which is evaluated by the satisfying classification rate, sensitivity and specificity of receiver operating characteristic(ROC), and cost time. Through the method we proposed, it will be helpful to improve the accuracy of diagnosis of cirrhosis and prevent the development of liver lesion towards hepatoma.

Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification.

PubMed

Hu, Zhihong; Medioni, Gerard G; Hernandez, Matthias; Sadda, Srinivas R

2015-01-01

Geographic atrophy (GA) is a manifestation of the advanced or late stage of age-related macular degeneration (AMD). AMD is the leading cause of blindness in people over the age of 65 in the western world. The purpose of this study is to develop a fully automated supervised pixel classification approach for segmenting GA, including uni- and multifocal patches in fundus autofluorescene (FAF) images. The image features include region-wise intensity measures, gray-level co-occurrence matrix measures, and Gaussian filter banks. A [Formula: see text]-nearest-neighbor pixel classifier is applied to obtain a GA probability map, representing the likelihood that the image pixel belongs to GA. Sixteen randomly chosen FAF images were obtained from 16 subjects with GA. The algorithm-defined GA regions are compared with manual delineation performed by a certified image reading center grader. Eight-fold cross-validation is applied to evaluate the algorithm performance. The mean overlap ratio (OR), area correlation (Pearson's [Formula: see text]), accuracy (ACC), true positive rate (TPR), specificity (SPC), positive predictive value (PPV), and false discovery rate (FDR) between the algorithm- and manually defined GA regions are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], respectively.

Assessing the performance of multiple spectral-spatial features of a hyperspectral image for classification of urban land cover classes using support vector machines and artificial neural network

NASA Astrophysics Data System (ADS)

Pullanagari, Reddy; Kereszturi, Gábor; Yule, Ian J.; Ghamisi, Pedram

2017-04-01

Accurate and spatially detailed mapping of complex urban environments is essential for land managers. Classifying high spectral and spatial resolution hyperspectral images is a challenging task because of its data abundance and computational complexity. Approaches with a combination of spectral and spatial information in a single classification framework have attracted special attention because of their potential to improve the classification accuracy. We extracted multiple features from spectral and spatial domains of hyperspectral images and evaluated them with two supervised classification algorithms; support vector machines (SVM) and an artificial neural network. The spatial features considered are produced by a gray level co-occurrence matrix and extended multiattribute profiles. All of these features were stacked, and the most informative features were selected using a genetic algorithm-based SVM. After selecting the most informative features, the classification model was integrated with a segmentation map derived using a hidden Markov random field. We tested the proposed method on a real application of a hyperspectral image acquired from AisaFENIX and on widely used hyperspectral images. From the results, it can be concluded that the proposed framework significantly improves the results with different spectral and spatial resolutions over different instrumentation.

Fast segmentation of industrial quality pavement images using Laws texture energy measures and k -means clustering

NASA Astrophysics Data System (ADS)

Mathavan, Senthan; Kumar, Akash; Kamal, Khurram; Nieminen, Michael; Shah, Hitesh; Rahman, Mujib

2016-09-01

Thousands of pavement images are collected by road authorities daily for condition monitoring surveys. These images typically have intensity variations and texture nonuniformities that make their segmentation challenging. The automated segmentation of such pavement images is crucial for accurate, thorough, and expedited health monitoring of roads. In the pavement monitoring area, well-known texture descriptors, such as gray-level co-occurrence matrices and local binary patterns, are often used for surface segmentation and identification. These, despite being the established methods for texture discrimination, are inherently slow. This work evaluates Laws texture energy measures as a viable alternative for pavement images for the first time. k-means clustering is used to partition the feature space, limiting the human subjectivity in the process. Data classification, hence image segmentation, is performed by the k-nearest neighbor method. Laws texture energy masks are shown to perform well with resulting accuracy and precision values of more than 80%. The implementations of the algorithm, in both MATLAB® and OpenCV/C++, are extensively compared against the state of the art for execution speed, clearly showing the advantages of the proposed method. Furthermore, the OpenCV-based segmentation shows a 100% increase in processing speed when compared to the fastest algorithm available in literature.

Quantitative second-harmonic generation imaging to detect osteogenesis imperfecta in human skin samples

NASA Astrophysics Data System (ADS)

Adur, J.; Ferreira, A. E.; D'Souza-Li, L.; Pelegati, V. B.; de Thomaz, A. A.; Almeida, D. B.; Baratti, M. O.; Carvalho, H. F.; Cesar, C. L.

2012-03-01

Osteogenesis Imperfecta (OI) is a genetic disorder that leads to bone fractures due to mutations in the Col1A1 or Col1A2 genes that affect the primary structure of the collagen I chain with the ultimate outcome in collagen I fibrils that are either reduced in quantity or abnormally organized in the whole body. A quick test screening of the patients would largely reduce the sample number to be studied by the time consuming molecular genetics techniques. For this reason an assessment of the human skin collagen structure by Second Harmonic Generation (SHG) can be used as a screening technique to speed up the correlation of genetics/phenotype/OI types understanding. In the present work we have used quantitative second harmonic generation (SHG) imaging microscopy to investigate the collagen matrix organization of the OI human skin samples comparing with normal control patients. By comparing fibril collagen distribution and spatial organization, we calculated the anisotropy and texture patterns of this structural protein. The analysis of the anisotropy was performed by means of the two-dimensional Discrete Fourier Transform and image pattern analysis with Gray-Level Co-occurrence Matrix (GLCM). From these results, we show that statistically different results are obtained for the normal and disease states of OI.

Variations in algorithm implementation among quantitative texture analysis software packages

NASA Astrophysics Data System (ADS)

Foy, Joseph J.; Mitta, Prerana; Nowosatka, Lauren R.; Mendel, Kayla R.; Li, Hui; Giger, Maryellen L.; Al-Hallaq, Hania; Armato, Samuel G.

2018-02-01

Open-source texture analysis software allows for the advancement of radiomics research. Variations in texture features, however, result from discrepancies in algorithm implementation. Anatomically matched regions of interest (ROIs) that captured normal breast parenchyma were placed in the magnetic resonance images (MRI) of 20 patients at two time points. Six first-order features and six gray-level co-occurrence matrix (GLCM) features were calculated for each ROI using four texture analysis packages. Features were extracted using package-specific default GLCM parameters and using GLCM parameters modified to yield the greatest consistency among packages. Relative change in the value of each feature between time points was calculated for each ROI. Distributions of relative feature value differences were compared across packages. Absolute agreement among feature values was quantified by the intra-class correlation coefficient. Among first-order features, significant differences were found for max, range, and mean, and only kurtosis showed poor agreement. All six second-order features showed significant differences using package-specific default GLCM parameters, and five second-order features showed poor agreement; with modified GLCM parameters, no significant differences among second-order features were found, and all second-order features showed poor agreement. While relative texture change discrepancies existed across packages, these differences were not significant when consistent parameters were used.

Application of Hyperspectral Imaging and Chemometric Calibrations for Variety Discrimination of Maize Seeds

PubMed Central

Zhang, Xiaolei; Liu, Fei; He, Yong; Li, Xiaoli

2012-01-01

Hyperspectral imaging in the visible and near infrared (VIS-NIR) region was used to develop a novel method for discriminating different varieties of commodity maize seeds. Firstly, hyperspectral images of 330 samples of six varieties of maize seeds were acquired using a hyperspectral imaging system in the 380–1,030 nm wavelength range. Secondly, principal component analysis (PCA) and kernel principal component analysis (KPCA) were used to explore the internal structure of the spectral data. Thirdly, three optimal wavelengths (523, 579 and 863 nm) were selected by implementing PCA directly on each image. Then four textural variables including contrast, homogeneity, energy and correlation were extracted from gray level co-occurrence matrix (GLCM) of each monochromatic image based on the optimal wavelengths. Finally, several models for maize seeds identification were established by least squares-support vector machine (LS-SVM) and back propagation neural network (BPNN) using four different combinations of principal components (PCs), kernel principal components (KPCs) and textural features as input variables, respectively. The recognition accuracy achieved in the PCA-GLCM-LS-SVM model (98.89%) was the most satisfactory one. We conclude that hyperspectral imaging combined with texture analysis can be implemented for fast classification of different varieties of maize seeds. PMID:23235456

In vivo Quantification of the Structural Changes of Collagens in a Melanoma Microenvironment with Second and Third Harmonic Generation Microscopy

PubMed Central

Wu, Pei-Chun; Hsieh, Tsung-Yuan; Tsai, Zen-Uong; Liu, Tzu-Ming

2015-01-01

Using in vivo second harmonic generation (SHG) and third harmonic generation (THG) microscopies, we tracked the course of collagen remodeling over time in the same melanoma microenvironment within an individual mouse. The corresponding structural and morphological changes were quantitatively analyzed without labeling using an orientation index (OI), the gray level co-occurrence matrix (GLCM) method, and the intensity ratio of THG to SHG (RTHG/SHG). In the early stage of melanoma development, we found that collagen fibers adjacent to a melanoma have increased OI values and SHG intensities. In the late stages, these collagen networks have more directionality and less homogeneity. The corresponding GLCM traces showed oscillation features and the sum of squared fluctuation VarGLCM increased with the tumor sizes. In addition, the THG intensities of the extracellular matrices increased, indicating an enhanced optical inhomogeneity. Multiplying OI, VarGLCM, and RTHG/SHG together, the combinational collagen remodeling (CR) index at 4 weeks post melanoma implantation showed a 400-times higher value than normal ones. These results validate that our quantitative indices of SHG and THG microscopies are sensitive enough to diagnose the collagen remodeling in vivo. We believe these indices have the potential to help the diagnosis of skin cancers in clinical practice. PMID:25748390

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards

PubMed Central

Nyflot, Matthew J.; Yang, Fei; Byrd, Darrin; Bowen, Stephen R.; Sandison, George A.; Kinahan, Paul E.

2015-01-01

Abstract. Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes. PMID:26251842

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards.

PubMed

Nyflot, Matthew J; Yang, Fei; Byrd, Darrin; Bowen, Stephen R; Sandison, George A; Kinahan, Paul E

2015-10-01

Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes.

Using a high-dimensional graph of semantic space to model relationships among words

PubMed Central

Jackson, Alice F.; Bolger, Donald J.

2014-01-01

The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD). PMID:24860525

Using a high-dimensional graph of semantic space to model relationships among words.

PubMed

Jackson, Alice F; Bolger, Donald J

2014-01-01

The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD).

Outbreak of Tinea capitis and corporis in a primary school in Antananarivo, Madagascar.

PubMed

Carod, Jean-François; Ratsitorahina, Mahery; Raherimandimby, Hasina; Hincky Vitrat, Virginie; Ravaolimalala Andrianaja, Vololomboahangy; Contet-Audonneau, Nelly

2011-10-13

Tinea capitis is common among schoolchildren in developing countries but underreported in Madagascar. We report the occurrence of an outbreak of gray patch tinea capitis due to Microsporum langeronii in a public primary school of Antananarivo, the capital city of Madagascar. Forty-two children were included, 27 (64%) of them presenting with tinea capitis and 32 (76%) with Tinea corporis. Patients were treated with griseofulvin 500 mg and Povidone-iodine 4% and followed up for four weeks. Twenty-five (93%) of the 27 children with tinea capitis presented a gray patch as the main clinical feature. All these cases were fluorescent under Wood's UV light and positive in cultures for M. langeronii. All 27 children reported a contact with infected classmates, and 19 (70%) reported to have infected brothers and sisters at home. After four weeks of treatment, all patients recovered. Appropriate treatment and improved hygienic practices reduced the occurrence of tinea in the studied school and no more cases of tinea capitis or corporis occurred after the outbreak.

Investigation of varying gray scale levels for remote manipulation

NASA Technical Reports Server (NTRS)

Bierschwale, John M.; Stuart, Mark A.; Sampaio, Carlos E.

1991-01-01

A study was conducted to investigate the effects of variant monitor gray scale levels and workplace illumination levels on operators' ability to discriminate between different colors on a monochrome monitor. It was determined that 8-gray scale viewing resulted in significantly worse discrimination performance compared to 16- and 32-gray scale viewing and that there was only a negligible difference found between 16 and 32 shades of gray. Therefore, it is recommended that monitors used while performing remote manipulation tasks have 16 or above shades of gray since this evaluation has found levels lower than this to be unacceptable for color discrimination task. There was no significant performance difference found between a high and a low workplace illumination condition. Further analysis was conducted to determine which specific combinations of colors can be used in conjunction with each other to ensure errorfree color coding/brightness discrimination performance while viewing a monochrome monitor. It was found that 92 three-color combination and 9 four-color combinations could be used with 100 percent accuracy. The results can help to determine which gray scale levels should be provided on monochrome monitors as well as which colors to use to ensure the maximal performance of remotely-viewed color discrimination/coding tasks.

Fast algorithm of low power image reformation for OLED display

NASA Astrophysics Data System (ADS)

Lee, Myungwoo; Kim, Taewhan

2014-04-01

We propose a fast algorithm of low-power image reformation for organic light-emitting diode (OLED) display. The proposed algorithm scales the image histogram in a way to reduce power consumption in OLED display by remapping the gray levels of the pixels in the image based on the fast analysis of the histogram of the input image while maintaining contrast of the image. The key idea is that a large number of gray levels are never used in the images and these gray levels can be effectively exploited to reduce power consumption. On the other hand, to maintain the image contrast the gray level remapping is performed by taking into account the object size in the image to which each gray level is applied, that is, reforming little for the gray levels in the objects of large size. Through experiments with 24 Kodak images, it is shown that our proposed algorithm is able to reduce the power consumption by 10% even with 9% contrast enhancement. Our algorithm runs in a linear time so that it can be applied to moving pictures with high resolution.

The use of in vivo fluorescence image sequences to indicate the occurrence and propagation of transient focal depolarizations in cerebral ischemia.

PubMed

Strong, A J; Harland, S P; Meldrum, B S; Whittington, D J

1996-05-01

A method for the detection and tracking of propagated fluorescence transients as indicators of depolarizations in focal cerebral ischemia is described, together with initial results indicating the potential of the method. The cortex of the right cerebral hemisphere was exposed for nonrecovery experiments in five cats anesthetized with chloralose and subjected to permanent middle cerebral artery (MCA) occlusion. Fluorescence with 370-nm excitation (attributed to the degree of reduction of the NAD/H couple) was imaged with an intensified charge-coupled device camera and digitized. Sequences of images representing changes in gray level from a baseline image were examined, together with the time courses of mean gray levels in specified regions of interest. Spontaneous increases in fluorescence occurred, starting most commonly at the edge of areas of core ischemia; they propagated usually throughout the periinfarct zone and resolved to varying degrees and at varying rates, depending on proximity of the locus to the MCA input. When a fluorescence transient reached the anterior cerebral artery territory, its initial polarity reversed from an increase to a decrease in fluorescence. An initial increase in fluorescence in response to the arrival of a transient may characterize cortex that will become infarcted, if pathophysiological changes in the periinfarct zone are allowed to evolve naturally.

Affect and Health Behavior Co-Occurrence: The Emerging Roles of Transdiagnostic Factors and Sociocultural Factors.

PubMed

Zvolensky, Michael J; Leventhal, Adam M

2016-01-01

The majority of scientific work addressing relations among affective states and health correlates has focused primarily on their co-occurrence and a limited range of health conditions. We have developed a Special Issue to highlight recent advances in this emerging field of work that addresses the nature and interplay between affective states and disorders, in terms of their impact and consequences from health status and behavior. This Special Issue is organized into three parts classified as (a) co-occurrence and interplay between (b) transdiagnostic factors and (c) sociocultural factors. It is hoped that this issue will (a) alert readers to the significance of this work at different levels of analysis, (b) illustrate the many domains currently being explored via innovative approaches, and (c) identify fecund areas for future systematic study. © The Author(s) 2016.

Classification of interstitial lung disease patterns with topological texture features

NASA Astrophysics Data System (ADS)

Huber, Markus B.; Nagarajan, Mahesh; Leinsinger, Gerda; Ray, Lawrence A.; Wismüller, Axel

2010-03-01

Topological texture features were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honey-combing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. A set of 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions and the significance thresholds were adjusted for multiple comparisons by the Bonferroni correction. The best classification results were obtained by the MF features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers. The highest accuracy was found for MF.euler (97.5%, 96.6%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced topological texture features can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

TU-F-CAMPUS-J-02: Evaluation of Textural Feature Extraction for Radiotherapy Response Assessment of Early Stage Breast Cancer Patients Using Diffusion Weighted MRI and Dynamic Contrast Enhanced MRI

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

Xie, Y; Wang, C; Horton, J

Purpose: To investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment, we studied a unique cohort of early stage breast cancer patients with paired pre - and post-radiation Diffusion Weighted MRI (DWI-MRI) and Dynamic Contrast Enhanced MRI (DCE-MRI). Methods: 15 female patients from our prospective phase I trial evaluating preoperative radiotherapy were included in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b =more » 500 mm{sup 2} /s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T{sub 1}-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (K{sup trans} ) and k{sub ep} were analyzed using the two-compartment Tofts kinetic model. For DCE parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction. Results: For ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of K{sup trans} and 33 features of k{sub ep} changed significantly. Conclusion: Initial results indicate that those significantly changed classic texture features are sensitive to radiation-induced changes and can be used for assessment of radiotherapy response in breast cancer.« less

TU-AB-BRA-05: Repeatability of [F-18]-NaF PET Imaging Biomarkers for Bone Lesions: A Multicenter Study

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

Lin, C; Bradshaw, T; Perk, T

2015-06-15

Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative {sup 18}F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm{sup 3} were identified and automatically segmented using a SUV>15 threshold. From eachmore » lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm{sup 3} for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria for NaF PET-based treatment response assessment. Prostate Cancer Foundation (PCF)« less

Great gray owls (Strix nebulosa) in Yosemite National Park: on the importance of food, forest structure, and human disturbance

USGS Publications Warehouse

van Riper, Charles; Fontaine, Joseph J.; van Wagtendonk, Jan W.

2013-01-01

We studied great gray owls (Strix nebulosa Forster) in Yosemite National Park, California, measuring variables that could potentially influence patterns of occurrence and conservation of this stateendangered species. We found that owl presence was closely tied to habitat (red fir (Abies magnified A. Murray) and the abundance of meadows), prey, and snags across the landscape. We also found that indicators of human recreational activities negatively influenced owl distribution and habitat use. Great gray owls appear to prefer mid-elevation red fir forest with meadows that are drier and more productive in terms of small mammal populations. That these areas also have the highest human activity presents a paradox, both for individual owls and for the future conservation and management of this California endangered species. The extent to which human recreation in natural areas affects animal behavior, species distribution, and productivity is a growing issue in natural area management. We present information that will allow land managers to better understand how existing natural resources, coupled with human recreation, influence the distribution and habitat use of the great gray owl.

Investigating the nature of co-occurring depression and anxiety: Comparing diagnostic and dimensional research approaches.

PubMed

Kircanski, Katharina; LeMoult, Joelle; Ordaz, Sarah; Gotlib, Ian H

2017-07-01

Although approximately half of adults diagnosed with a depressive or anxiety disorder exhibit their simultaneous co-occurrence, traditional research has centered on single-target diagnoses, overlooking comorbidities within samples. In this article, we review and extend the literature that directly investigates co-occurring depression and anxiety, with the goal of shifting the focus from co-occurring diagnoses to symptom dimensions. First, we review studies that have directly compared psychobiological features (neural, neuroendocrine, autonomic) across depression, anxiety, and their co-occurrence, defined either categorically or dimensionally. Second, we analyze adults' diurnal cortisol secretion to examine the independent and interactive relations of continuously-assessed depressive and anxiety symptoms to neuroendocrine function. Previous findings on the psychobiology of diagnostic co-occurrence are mixed. While nascent, evidence from dimensionally focused studies suggests that co-occurring levels of depressive and anxiety symptoms can interact with one another, as reflected in a distinct psychobiological profile for individuals with high levels of both symptom dimensions. Results of our analyses support this formulation: we found that depressive and anxiety symptom dimensions interacted consistently in their relation to the measures of diurnal cortisol. The illustrative sample was relatively small and included only women; future research should examine generalizability of these findings. A dimensional approach to investigating the psychobiology of co-occurring depression and anxiety affords both conceptual and practical advantages. Simultaneously assessing depressive and anxiety symptom dimensions can efficiently capture their unique, shared, and interactive features, thereby identifying targets for intervention across a wide range of symptom presentations. Published by Elsevier B.V.

The origin and determination of silica types in the silica occurrences from Altintaş region (Uşak-Western Anatolia) using multianalytical techniques

NASA Astrophysics Data System (ADS)

Koralay, Tamer; Kadıoğlu, Yusuf Kağan

2015-02-01

The studied area is located in Western Anatolia and situated on the NE-SW directed Uşak-Güre cross-graben that developed under a crustal extensional regime during the Late Miocene-Pliocene. Silica occurrences have been mostly found as mushroom-shaped big caps. They also show sedimentary structures such as stratification. Silica occurrences are milky white, yellowish white, yellow to chocolate brown and rarely pale blue, bluish gray in color and have no crystal forms in hand specimen. Some of the silica samples show conchoidal fracture. Silica minerals are mostly chalcedony, low-quartz (α-quartz) and sporadically opal-CT in spectras, according to confocal Raman spectrometry. The silica samples have enrichment of Fe (1000-24,600 ppm), Ca (100-10,200 ppm), P (4-3950 ppm) and Mn (8-3020 ppm). Other striking elements in fewer amounts are Ba (0.9-609.6 ppm), Ni (15.7-182.3 ppm) and Co (18.6-343.1 ppm). In chondrite-normalized spider diagram, silica samples display partial enrichment in LIL elements (Rb, Ba, Th). The δ18O (‰ V-SMOW) values for silica samples vary from 18.4‰ to 22.8‰ and are similar to low temperature hydrothermal silica. Confocal Raman spectrometry and oxygen isotope indicate that the silica minerals may precipitate from host fluid which is relatively has low temperatures hydrothermal solutions derived from the residual melt of basaltic magma.

Application of gray level mapping in computed tomographic colonography: a pilot study to compare with traditional surface rendering method for identification and differentiation of endoluminal lesions

PubMed Central

Chen, Lih-Shyang; Hsu, Ta-Wen; Chang, Shu-Han; Lin, Chih-Wen; Chen, Yu-Ruei; Hsieh, Chin-Chiang; Han, Shu-Chen; Chang, Ku-Yaw; Hou, Chun-Ju

2017-01-01

Objective: In traditional surface rendering (SR) computed tomographic endoscopy, only the shape of endoluminal lesion is depicted without gray-level information unless the volume rendering technique is used. However, volume rendering technique is relatively slow and complex in terms of computation time and parameter setting. We use computed tomographic colonography (CTC) images as examples and report a new visualization technique by three-dimensional gray level mapping (GM) to better identify and differentiate endoluminal lesions. Methods: There are 33 various endoluminal cases from 30 patients evaluated in this clinical study. These cases were segmented using gray-level threshold. The marching cube algorithm was used to detect isosurfaces in volumetric data sets. GM is applied using the surface gray level of CTC. Radiologists conducted the clinical evaluation of the SR and GM images. The Wilcoxon signed-rank test was used for data analysis. Results: Clinical evaluation confirms GM is significantly superior to SR in terms of gray-level pattern and spatial shape presentation of endoluminal cases (p < 0.01) and improves the confidence of identification and clinical classification of endoluminal lesions significantly (p < 0.01). The specificity and diagnostic accuracy of GM is significantly better than those of SR in diagnostic performance evaluation (p < 0.01). Conclusion: GM can reduce confusion in three-dimensional CTC and well correlate CTC with sectional images by the location as well as gray-level value. Hence, GM increases identification and differentiation of endoluminal lesions, and facilitates diagnostic process. Advances in knowledge: GM significantly improves the traditional SR method by providing reliable gray-level information for the surface points and is helpful in identification and differentiation of endoluminal lesions according to their shape and density. PMID:27925483

Pixel-based image fusion with false color mapping

NASA Astrophysics Data System (ADS)

Zhao, Wei; Mao, Shiyi

2003-06-01

In this paper, we propose a pixel-based image fusion algorithm that combines the gray-level image fusion method with the false color mapping. This algorithm integrates two gray-level images presenting different sensor modalities or at different frequencies and produces a fused false-color image. The resulting image has higher information content than each of the original images. The objects in the fused color image are easy to be recognized. This algorithm has three steps: first, obtaining the fused gray-level image of two original images; second, giving the generalized high-boost filtering images between fused gray-level image and two source images respectively; third, generating the fused false-color image. We use the hybrid averaging and selection fusion method to obtain the fused gray-level image. The fused gray-level image will provide better details than two original images and reduce noise at the same time. But the fused gray-level image can't contain all detail information in two source images. At the same time, the details in gray-level image cannot be discerned as easy as in a color image. So a color fused image is necessary. In order to create color variation and enhance details in the final fusion image, we produce three generalized high-boost filtering images. These three images are displayed through red, green and blue channel respectively. A fused color image is produced finally. This method is used to fuse two SAR images acquired on the San Francisco area (California, USA). The result shows that fused false-color image enhances the visibility of certain details. The resolution of the final false-color image is the same as the resolution of the input images.

The collection of images of an insulator taken outdoors in varying lighting conditions with additional laser spots.

PubMed

Tomaszewski, Michał; Ruszczak, Bogdan; Michalski, Paweł

2018-06-01

Electrical insulators are elements of power lines that require periodical diagnostics. Due to their location on the components of high-voltage power lines, their imaging can be cumbersome and time-consuming, especially under varying lighting conditions. Insulator diagnostics with the use of visual methods may require localizing insulators in the scene. Studies focused on insulator localization in the scene apply a number of methods, including: texture analysis, MRF (Markov Random Field), Gabor filters or GLCM (Gray Level Co-Occurrence Matrix) [1], [2]. Some methods, e.g. those which localize insulators based on colour analysis [3], rely on object and scene illumination, which is why the images from the dataset are taken under varying lighting conditions. The dataset may also be used to compare the effectiveness of different methods of localizing insulators in images. This article presents high-resolution images depicting a long rod electrical insulator under varying lighting conditions and against different backgrounds: crops, forest and grass. The dataset contains images with visible laser spots (generated by a device emitting light at the wavelength of 532 nm) and images without such spots, as well as complementary data concerning the illumination level and insulator position in the scene, the number of registered laser spots, and their coordinates in the image. The laser spots may be used to support object-localizing algorithms, while the images without spots may serve as a source of information for those algorithms which do not need spots to localize an insulator.

Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

PubMed

Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

2016-01-01

To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

Microbial activity in the profiles of gray forest soil and chernozems

NASA Astrophysics Data System (ADS)

Susyan, E. A.; Rybyanets, D. S.; Ananyeva, N. D.

2006-08-01

Soil samples were taken from the profiles of a gray forest soil (under a forest) and southern chernozems of different textures under meadow vegetation. The microbial biomass (MB) was determined by the method of substrate-induced respiration; the basal respiration (BR) and the population density of microorganisms on nutrient media of different composition were also determined in the samples. The microbial metabolic quotient ( qCO2 = BR/MB) and the portion of microbial carbon (C mic) in C org were calculated. The MB and BR values were shown to decrease down the soil profiles. About 57% of the total MB in the entire soil profile was concentrated in the layer of 0-24 cm of the gray forest soil. The MB in the C horizon of chernozems was approximately two times lower than the MB in the A horizon of these soils. The correlation was found between the MB and the C org ( r = 0.99) and between the MB and the clay content ( r = 0.89) in the profile of the gray forest soil. The C mic/C org ratio in the gray forest soil and in the chernozems comprised 2.3-6.6 and 1.2-9.6%, respectively. The qCO2 value increased with the depth. The microbial community in the lower layers of the gray forest soil was dominated (88-96%) by oligotrophic microorganisms (grown on soil agar); in the upper 5 cm, these microorganisms comprised only 50% of the total amount of microorganisms grown on three media.

Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo)

USGS Publications Warehouse

Strona, Giovanni; Lafferty, Kevin D.

2013-01-01

Fish pathologists are often interested in which parasites would likely be present in a particular host. Parasite Co-occurrence Modeler (PaCo) is a tool for identifying a list of parasites known from fish species that are similar ecologically, phylogenetically, and geographically to the host of interest. PaCo uses data from FishBase (maximum length, growth rate, life span, age at maturity, trophic level, phylogeny, and biogeography) to estimate compatibility between a target host and parasite species–genera from the major helminth groups (Acanthocephala, Cestoda, Monogenea, Nematoda, and Trematoda). Users can include any combination of host attributes in a model. These unique features make PaCo an innovative tool for addressing both theoretical and applied questions in parasitology. In addition to predicting the occurrence of parasites, PaCo can be used to investigate how host characteristics shape parasite communities. To test the performance of the PaCo algorithm, we created 12,400 parasite lists by applying any possible combination of model parameters (248) to 50 fish hosts. We then measured the relative importance of each parameter by assessing their frequency in the best models for each host. Host phylogeny and host geography were identified as the most important factors, with both present in 88% of the best models. Habitat (64%) was identified in more than half of the best models. Among ecological parameters, trophic level (41%) was the most relevant while life span (34%), growth rate (32%), maximum length (28%), and age at maturity (20%) were less commonly linked to best models. PaCo is free to use at www.purl.oclc.org/fishpest.

Temporal Trends of NO2, CO and their Relation to the Fire Occurrences over the Indo-Gangetic Plain

NASA Astrophysics Data System (ADS)

Pandey, A. K.; Kumar, K.

2016-12-01

Air pollution is an environmental issue that has a gigantic impact on human health, and it is a major problem in the densely populated regions throughout the world. Situated in the foothills of the great Himalayas Indo-Gangetic Plain (IGP) is among one of the most densely populated regions of the earth. NO2 and CO are among major air pollutants which affect the air quality of IGP predominantly. In the present study, we studied the temporal trends of NO2, CO and fire count over the IGP region. Further, we investigated the role of the fire occurrences in the ambient NO2 and CO levels. We used MODIS instrument (Aqua satellite), OMI sensor and AIRS instrument data for fire count, Nitrogen Dioxide (NO2) tropospheric column and Carbon monoxide (CO) column study respectively. The IGP is divided into three part geographically i.e. Eastern (E-IGP), Central (C-IGP) and Western (W-IGP). A higher columnar CO concentration is observed in the E-IGP whereas NO2 concentration is highest in the W-IGP. A higher NO2 concentration is obtained in winter followed by summer and a minimum in monsoon months throughout the IGP. Columnar CO concentration is higher in the E-IGP and its concentration is maximum in pre-monsoon months and minimum in the monsoon months. Fire pixel count is highest in the W-IGP with peak twice every year i.e. in the April - May and October - November corresponding to the harvest period in the Rabi-Kharif cropping system. We also obtained a significant positive correlation between fire occurrences and columnar NO2 & CO levels over the IGP which shows the biomass burning practices associated with the agriculture influences the NO2 and CO concentration in the atmosphere.

Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo).

PubMed

Strona, Giovanni; Lafferty, Kevin D

2013-02-01

Fish pathologists are often interested in which parasites would likely be present in a particular host. Parasite Co-occurrence Modeler (PaCo) is a tool for identifying a list of parasites known from fish species that are similar ecologically, phylogenetically, and geographically to the host of interest. PaCo uses data from FishBase (maximum length, growth rate, life span, age at maturity, trophic level, phylogeny, and biogeography) to estimate compatibility between a target host and parasite species-genera from the major helminth groups (Acanthocephala, Cestoda, Monogenea, Nematoda, and Trematoda). Users can include any combination of host attributes in a model. These unique features make PaCo an innovative tool for addressing both theoretical and applied questions in parasitology. In addition to predicting the occurrence of parasites, PaCo can be used to investigate how host characteristics shape parasite communities. To test the performance of the PaCo algorithm, we created 12,400 parasite lists by applying any possible combination of model parameters (248) to 50 fish hosts. We then measured the relative importance of each parameter by assessing their frequency in the best models for each host. Host phylogeny and host geography were identified as the most important factors, with both present in 88% of the best models. Habitat (64%) was identified in more than half of the best models. Among ecological parameters, trophic level (41%) was the most relevant while life span (34%), growth rate (32%), maximum length (28%), and age at maturity (20%) were less commonly linked to best models. PaCo is free to use at www.purl.oclc.org/fishpest.

The Co-Occurrence of Obesity, Elevated Blood Pressure and Acanthosis Nigricans among American Indian School-children: Identifying Individual Heritage and Environment-level Correlates

PubMed Central

Hearst, Mary O.; Laska, Melissa Nelson; Himes, John H.; Butterbrodt, Mark; Sinaiko, Alan; Cloud, Richard Iron; Tobacco, Mary; Story, Mary

2011-01-01

Objective To estimate the prevalence and explore the social and cultural etiologic roots of weight status, blood pressure and acanthosis nigricans among American Indian children on a reservation in South Dakota. Methods This observational study was conducted in 26 schools from 1998–2002 and included 5,422 observations representing 3,841 children, ages 3–19. Trained staff measured height, weight, blood pressure and assessed the presence of acanthosis nigricans (AN). Percent Indian heritage (PIH) was abstracted from tribal records. Sociodemographic environment (SDE) was calculated using the 2000 Census at the city/town level. Descriptive analyses were conducted using one measurement time point, including tests for trend and co-occurrence of risk factors using the kappa statistic. Hierarchical, multivariate logistic regression estimated associations with overweight/obesity status, accounting for multiple measures on individuals and SDE. Results The overall prevalence of overweight/obesity was 46%, of hypertension 9%, and of AN 14%. The co-occurrence of risk factors was moderate to high. PIH and AN were positively associated in unadjusted analysis. Controlling for sex, age, and SDE, higher PIH was a significant correlate of overweight/obesity, although when hypertension (OR=5.92, CI=3.27–10.72), pre-hypertension (OR=3.80, CI=1.99–7.26) and AN (OR=16.20, CI=8.08–32.48) were included in the model PIH was no longer significant. SDE was not significantly associated with overweight/obesity. Conclusion PIH appeared to be an important correlate of overweight and obesity, except when adjusted for the co-occurrence of high blood pressure and AN. Overall, the prevalence and co-occurrence of various risk factors in this population was high. Obesity prevention initiatives targeting families and communities are needed, as well as access to screening and treatment services. PMID:21445934

Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders.

PubMed

He, Hao; Sui, Jing; Du, Yuhui; Yu, Qingbao; Lin, Dongdong; Drevets, Wayne C; Savitz, Jonathan B; Yang, Jian; Victor, Teresa A; Calhoun, Vince D

2017-12-01

Bipolar disorder (BD) and major depressive disorder (MDD) share similar clinical characteristics that often obscure the diagnostic distinctions between their depressive conditions. Both functional and structural brain abnormalities have been reported in these two disorders. However, the direct link between altered functioning and structure in these two diseases is unknown. To elucidate this relationship, we conducted a multimodal fusion analysis on the functional network connectivity (FNC) and gray matter density from MRI data from 13 BD, 40 MDD, and 33 matched healthy controls (HC). A data-driven fusion method called mCCA+jICA was used to identify the co-altered FNC and gray matter components. Comparing to HC, BD exhibited reduced gray matter density in the parietal and occipital cortices, which correlated with attenuated functional connectivity within sensory and motor networks, as well as hyper-connectivity in regions that are putatively engaged in cognitive control. In addition, lower gray matter density was found in MDD in the amygdala and cerebellum. High accuracy in discriminating across groups was also achieved by trained classification models, implying that features extracted from the fusion analysis hold the potential to ultimately serve as diagnostic biomarkers for mood disorders.

Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor.

PubMed

Prasanna, Prateek; Tiwari, Pallavi; Madabhushi, Anant

2016-11-22

In this paper, we introduce a new radiomic descriptor, Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe) for capturing subtle differences between benign and pathologic phenotypes which may be visually indistinguishable on routine anatomic imaging. CoLlAGe seeks to capture and exploit local anisotropic differences in voxel-level gradient orientations to distinguish similar appearing phenotypes. CoLlAGe involves assigning every image voxel an entropy value associated with the co-occurrence matrix of gradient orientations computed around every voxel. The hypothesis behind CoLlAGe is that benign and pathologic phenotypes even though they may appear similar on anatomic imaging, will differ in their local entropy patterns, in turn reflecting subtle local differences in tissue microarchitecture. We demonstrate CoLlAGe's utility in three clinically challenging classification problems: distinguishing (1) radiation necrosis, a benign yet confounding effect of radiation treatment, from recurrent tumors on T1-w MRI in 42 brain tumor patients, (2) different molecular sub-types of breast cancer on DCE-MRI in 65 studies and (3) non-small cell lung cancer (adenocarcinomas) from benign fungal infection (granulomas) on 120 non-contrast CT studies. For each of these classification problems, CoLlAGE in conjunction with a random forest classifier outperformed state of the art radiomic descriptors (Haralick, Gabor, Histogram of Gradient Orientations).

Optimal scan strategy for mega-pixel and kilo-gray-level OLED-on-silicon microdisplay.

PubMed

Ji, Yuan; Ran, Feng; Ji, Weigui; Xu, Meihua; Chen, Zhangjing; Jiang, Yuxi; Shen, Weixin

2012-06-10

The digital pixel driving scheme makes the organic light-emitting diode (OLED) microdisplays more immune to the pixel luminance variations and simplifies the circuit architecture and design flow compared to the analog pixel driving scheme. Additionally, it is easily applied in full digital systems. However, the data bottleneck becomes a notable problem as the number of pixels and gray levels grow dramatically. This paper will discuss the digital driving ability to achieve kilogray-levels for megapixel displays. The optimal scan strategy is proposed for creating ultra high gray levels and increasing light efficiency and contrast ratio. Two correction schemes are discussed to improve the gray level linearity. A 1280×1024×3 OLED-on-silicon microdisplay, with 4096 gray levels, is designed based on the optimal scan strategy. The circuit driver is integrated in the silicon backplane chip in the 0.35 μm 3.3 V-6 V dual voltage one polysilicon layer, four metal layers (1P4M) complementary metal-oxide semiconductor (CMOS) process with custom top metal. The design aspects of the optimal scan controller are also discussed. The test results show the gray level linearity of the correction schemes for the optimal scan strategy is acceptable by the human eye.

Gray matter alterations and correlation of nutritional intake with the gray matter volume in prediabetes

PubMed Central

Hou, Yi-Cheng; Lai, Chien-Han; Wu, Yu-Te; Yang, Shwu-Huey

2016-01-01

Abstract The neurophysiology of prediabetes plays an important role in preventive medicine. The dysregulation of glucose metabolism is likely linked to changes in neuron-related gray matter. Therefore, we designed this study to investigate gray matter alterations in medication-naive prediabetic patients. We expected to find alterations in the gray matter of prediabetic patients. A total of 64 prediabetic patients and 54 controls were enrolled. All subjects received T1 scans using a 3-T magnetic resonance imaging machine. Subjects also completed nutritional intake records at the 24-hour and 3-day time points to determine their carbohydrate, protein, fat, and total calorie intake. We utilized optimized voxel-based morphometry to estimate the gray matter differences between the patients and controls. In addition, the preprandial serum glucose level and the carbohydrate, protein, fat, and total calorie intake levels were tested to determine whether these parameters were correlated with the gray matter volume. Prediabetic patients had lower gray matter volumes than controls in the right anterior cingulate gyrus, right posterior cingulate gyrus, left insula, left super temporal gyrus, and left middle temporal gyrus (corrected P < 0.05; voxel threshold: 33). Gray matter volume in the right anterior cingulate was also negatively correlated with the preprandial serum glucose level gyrus in a voxel-dependent manner (r = –0.501; 2-tailed P = 0.001). The cingulo-temporal and insula gray matter alterations may be associated with the glucose dysregulation in prediabetic patients. PMID:27336893

Histogram contrast analysis and the visual segregation of IID textures.

PubMed

Chubb, C; Econopouly, J; Landy, M S

1994-09-01

A new psychophysical methodology is introduced, histogram contrast analysis, that allows one to measure stimulus transformations, f, used by the visual system to draw distinctions between different image regions. The method involves the discrimination of images constructed by selecting texture micropatterns randomly and independently (across locations) on the basis of a given micropattern histogram. Different components of f are measured by use of different component functions to modulate the micropattern histogram until the resulting textures are discriminable. When no discrimination threshold can be obtained for a given modulating component function, a second titration technique may be used to measure the contribution of that component to f. The method includes several strong tests of its own assumptions. An example is given of the method applied to visual textures composed of small, uniform squares with randomly chosen gray levels. In particular, for a fixed mean gray level mu and a fixed gray-level variance sigma 2, histogram contrast analysis is used to establish that the class S of all textures composed of small squares with jointly independent, identically distributed gray levels with mean mu and variance sigma 2 is perceptually elementary in the following sense: there exists a single, real-valued function f S of gray level, such that two textures I and J in S are discriminable only if the average value of f S applied to the gray levels in I is significantly different from the average value of f S applied to the gray levels in J. Finally, histogram contrast analysis is used to obtain a seventh-order polynomial approximation of f S.

Non-gray gas radiation effect on mixed convection in lid driven square cavity

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

Cherifi, Mohammed, E-mail: production1998@yahoo.fr; Benbrik, Abderrahmane, E-mail: abenbrik@umbb.dz; Laouar-Meftah, Siham, E-mail: laouarmeftah@gmail.com

A numerical study is performed to investigate the effect of non-gray radiation on mixed convection in a vertical two sided lid driven square cavity filled with air-H{sub 2}O-CO{sub 2} gas mixture. The vertical moving walls of the enclosure are maintained at two different but uniform temperatures. The horizontal walls are thermally insulated and considered as adiabatic walls. The governing differential equations are solved by a finite-volume method and the SIMPLE algorithm was adopted to solve the pressure–velocity coupling. The radiative transfer equation (RTE) is solved by the discrete ordinates method (DOM). The spectral line weighted sum of gray gases modelmore » (SLW) is used to account for non-gray radiation properties. Simulations are performed in configurations where thermal and shear forces induce cooperating buoyancy forces. Streamlines, isotherms, and Nusselt number are analyzed for three different values of Richardson’s number (from 0.1 to 10) and by considering three different medium (transparent medium, gray medium using the Planck mean absorption coefficient, and non-gray medium assumption).« less

Determination of fungicide resistance in Botrytis cinerea from strawberry in the Central Coast Region of California

USDA-ARS?s Scientific Manuscript database

A study was conducted in 2013 to investigate the occurrence of fungicide resistance in Botrytis cinerea populations in California’s northern strawberry growing region; specifically in Watsonville and Salinas. In mid-May, 59 samples consisting of a single diseased fruit or plant part with gray mold s...

Treatment of co-occurring anxiety disorders and substance use disorders.

PubMed

McHugh, R Kathryn

2015-01-01

Anxiety disorders commonly co-occur with substance use disorders both in the general population and in treatment-seeking samples. This co-occurrence is associated with greater symptom severity, higher levels of disability, and poorer course of illness relative to either disorder alone. Little research has been conducted, however, on the treatment of these co-occurring disorders. This gap may not only leave anxiety untreated or undertreated but also increase the risk for relapse and poor substance use outcomes. The aim of this article is to review the current state of the literature on treating co-occurring anxiety and substance use disorders. In addition to presenting a brief overview of the epidemiology of this co-occurrence, the article discusses the challenges in assessing anxiety in the context of a substance use disorder, the evidence for various treatment approaches, and recent advances and future directions in this understudied area. Also highlighted is the need for future research to identify optimal behavioral and pharmacologic treatments for co-occurring anxiety and substance use disorders.

Gray-level transformations for interactive image enhancement. M.S. Thesis. Final Technical Report

NASA Technical Reports Server (NTRS)

Fittes, B. A.

1975-01-01

A gray-level transformation method suitable for interactive image enhancement was presented. It is shown that the well-known histogram equalization approach is a special case of this method. A technique for improving the uniformity of a histogram is also developed. Experimental results which illustrate the capabilities of both algorithms are described. Two proposals for implementing gray-level transformations in a real-time interactive image enhancement system are also presented.

Texture analysis of ultrahigh field T2*-weighted MR images of the brain: application to Huntington's disease.

PubMed

Doan, Nhat Trung; van den Bogaard, Simon J A; Dumas, Eve M; Webb, Andrew G; van Buchem, Mark A; Roos, Raymund A C; van der Grond, Jeroen; Reiber, Johan H C; Milles, Julien

2014-03-01

To develop a framework for quantitative detection of between-group textural differences in ultrahigh field T2*-weighted MR images of the brain. MR images were acquired using a three-dimensional (3D) T2*-weighted gradient echo sequence on a 7 Tesla MRI system. The phase images were high-pass filtered to remove phase wraps. Thirteen textural features were computed for both the magnitude and phase images of a region of interest based on 3D Gray-Level Co-occurrence Matrix, and subsequently evaluated to detect between-group differences using a Mann-Whitney U-test. We applied the framework to study textural differences in subcortical structures between premanifest Huntington's disease (HD), manifest HD patients, and controls. In premanifest HD, four phase-based features showed a difference in the caudate nucleus. In manifest HD, 7 magnitude-based features showed a difference in the pallidum, 6 phase-based features in the caudate nucleus, and 10 phase-based features in the putamen. After multiple comparison correction, significant differences were shown in the putamen in manifest HD by two phase-based features (both adjusted P values=0.04). This study provides the first evidence of textural heterogeneity of subcortical structures in HD. Texture analysis of ultrahigh field T2*-weighted MR images can be useful for noninvasive monitoring of neurodegenerative diseases. Copyright © 2013 Wiley Periodicals, Inc.

Germinal center texture entropy as possible indicator of humoral immune response: immunophysiology viewpoint.

PubMed

Pantic, Igor; Pantic, Senka

2012-10-01

In this article, we present the results indicating that spleen germinal center (GC) texture entropy determined by gray-level co-occurrence matrix (GLCM) method is related to humoral immune response. Spleen tissue was obtained from eight outbred male short-haired guinea pigs previously immunized by sheep red blood cells (SRBC). A total of 312 images from 39 germinal centers (156 GC light zone images and 156 GC dark zone images) were acquired and analyzed by GLCM method. Angular second moment, contrast, correlation, entropy, and inverse difference moment were calculated for each image. Humoral immune response to SRBC was measured using T cell-dependent antibody response (TDAR) assay. Statistically highly significant negative correlation was detected between light zone entropy and the number of TDAR plaque-forming cells (r (s) = -0.86, p < 0.01). The entropy decreased as the plaque-forming cells increased and vice versa. A statistically significant negative correlation was also detected between dark zone entropy values and the number of plaque-forming cells (r (s) = -0.69, p < 0.05). Germinal center texture entropy may be a powerful indicator of humoral immune response. This study is one of the first to point out the potential scientific value of GLCM image texture analysis in lymphoid tissue cytoarchitecture evaluation. Lymphoid tissue texture analysis could become an important and affordable addition to the conventional immunophysiology techniques.

Thermography based diagnosis of ruptured anterior cruciate ligament (ACL) in canines

NASA Astrophysics Data System (ADS)

Lama, Norsang; Umbaugh, Scott E.; Mishra, Deependra; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

Anterior cruciate ligament (ACL) rupture in canines is a common orthopedic injury in veterinary medicine. Veterinarians use both imaging and non-imaging methods to diagnose the disease. Common imaging methods such as radiography, computed tomography (CT scan) and magnetic resonance imaging (MRI) have some disadvantages: expensive setup, high dose of radiation, and time-consuming. In this paper, we present an alternative diagnostic method based on feature extraction and pattern classification (FEPC) to diagnose abnormal patterns in ACL thermograms. The proposed method was experimented with a total of 30 thermograms for each camera view (anterior, lateral and posterior) including 14 disease and 16 non-disease cases provided from Long Island Veterinary Specialists. The normal and abnormal patterns in thermograms are analyzed in two steps: feature extraction and pattern classification. Texture features based on gray level co-occurrence matrices (GLCM), histogram features and spectral features are extracted from the color normalized thermograms and the computed feature vectors are applied to Nearest Neighbor (NN) classifier, K-Nearest Neighbor (KNN) classifier and Support Vector Machine (SVM) classifier with leave-one-out validation method. The algorithm gives the best classification success rate of 86.67% with a sensitivity of 85.71% and a specificity of 87.5% in ACL rupture detection using NN classifier for the lateral view and Norm-RGB-Lum color normalization method. Our results show that the proposed method has the potential to detect ACL rupture in canines.

Computer-aided screening system for cervical precancerous cells based on field emission scanning electron microscopy and energy dispersive x-ray images and spectra

NASA Astrophysics Data System (ADS)

Jusman, Yessi; Ng, Siew-Cheok; Hasikin, Khairunnisa; Kurnia, Rahmadi; Osman, Noor Azuan Bin Abu; Teoh, Kean Hooi

2016-10-01

The capability of field emission scanning electron microscopy and energy dispersive x-ray spectroscopy (FE-SEM/EDX) to scan material structures at the microlevel and characterize the material with its elemental properties has inspired this research, which has developed an FE-SEM/EDX-based cervical cancer screening system. The developed computer-aided screening system consisted of two parts, which were the automatic features of extraction and classification. For the automatic features extraction algorithm, the image and spectra of cervical cells features extraction algorithm for extracting the discriminant features of FE-SEM/EDX data was introduced. The system automatically extracted two types of features based on FE-SEM/EDX images and FE-SEM/EDX spectra. Textural features were extracted from the FE-SEM/EDX image using a gray level co-occurrence matrix technique, while the FE-SEM/EDX spectra features were calculated based on peak heights and corrected area under the peaks using an algorithm. A discriminant analysis technique was employed to predict the cervical precancerous stage into three classes: normal, low-grade intraepithelial squamous lesion (LSIL), and high-grade intraepithelial squamous lesion (HSIL). The capability of the developed screening system was tested using 700 FE-SEM/EDX spectra (300 normal, 200 LSIL, and 200 HSIL cases). The accuracy, sensitivity, and specificity performances were 98.2%, 99.0%, and 98.0%, respectively.

Volumetric characterization of human patellar cartilage matrix on phase contrast x-ray computed tomography

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Nagarajan, Mahesh B.; Checefsky, Walter A.; Coan, Paola; Diemoz, Paul C.; Hobbs, Susan K.; Huber, Markus B.; Wismüller, Axel

2015-03-01

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 +/- 0.06) and homogeneity (AUC = 0.82 +/- 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

PubMed Central

Chaddad, Ahmad; Desrosiers, Christian; Bouridane, Ahmed; Toews, Matthew; Hassan, Lama; Tanougast, Camel

2016-01-01

Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT) are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma. Materials and Methods In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG) filter, discrete wavelets (DW) and gray level co-occurrence matrices (GLCM). To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models. Results Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01). Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%. Conclusions These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images. PMID:26901134

Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.

PubMed

Li, Zhiming; Yu, Lan; Wang, Xin; Yu, Haiyang; Gao, Yuanxiang; Ren, Yande; Wang, Gang; Zhou, Xiaoming

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P < .05). The area under the ROC (AUROC) of histogram, GLCM, and RLM were 0.800, 0.787, and 0.761, with no differences between them (P > .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P < .05). Mammographic texture analysis is a reliable technique for differential diagnosis of benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

The effects of TIS and MI on the texture features in ultrasonic fatty liver images

NASA Astrophysics Data System (ADS)

Zhao, Yuan; Cheng, Xinyao; Ding, Mingyue

2017-03-01

Nonalcoholic fatty liver disease (NAFLD) is prevalent and has a worldwide distribution now. Although ultrasound imaging technology has been deemed as the common method to diagnose fatty liver, it is not able to detect NAFLD in its early stage and limited by the diagnostic instruments and some other factors. B-scan image feature extraction of fatty liver can assist doctor to analyze the patient's situation and enhance the efficiency and accuracy of clinical diagnoses. However, some uncertain factors in ultrasonic diagnoses are often been ignored during feature extraction. In this study, the nonalcoholic fatty liver rabbit model was made and its liver ultrasound images were collected by setting different Thermal index of soft tissue (TIS) and mechanical index (MI). Then, texture features were calculated based on gray level co-occurrence matrix (GLCM) and the impacts of TIS and MI on these features were analyzed and discussed. Furthermore, the receiver operating characteristic (ROC) curve was used to evaluate whether each feature was effective or not when TIS and MI were given. The results showed that TIS and MI do affect the features extracted from the healthy liver, while the texture features of fatty liver are relatively stable. In addition, TIS set to 0.3 and MI equal to 0.9 might be a better choice when using a computer aided diagnosis (CAD) method for fatty liver recognition.

MRI textures as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma

NASA Astrophysics Data System (ADS)

Langenhuizen, P. P. J. H.; Legters, M. J. W.; Zinger, S.; Verheul, H. B.; Leenstra, S.; de With, P. H. N.

2018-02-01

Vestibular schwannomas (VS) are benign brain tumors that can be treated with high-precision focused radiation with the Gamma Knife in order to stop tumor growth. Outcome prediction of Gamma Knife radiosurgery (GKRS) treatment can help in determining whether GKRS will be effective on an individual patient basis. However, at present, prognostic factors of tumor control after GKRS for VS are largely unknown, and only clinical factors, such as size of the tumor at treatment and pre-treatment growth rate of the tumor, have been considered thus far. This research aims at outcome prediction of GKRS by means of quantitative texture feature analysis on conventional MRI scans. We compute first-order statistics and features based on gray-level co- occurrence (GLCM) and run-length matrices (RLM), and employ support vector machines and decision trees for classification. In a clinical dataset, consisting of 20 tumors showing treatment failure and 20 tumors exhibiting treatment success, we have discovered that the second-order statistical metrics distilled from GLCM and RLM are suitable for describing texture, but are slightly outperformed by simple first-order statistics, like mean, standard deviation and median. The obtained prediction accuracy is about 85%, but a final choice of the best feature can only be made after performing more extensive analyses on larger datasets. In any case, this work provides suitable texture measures for successful prediction of GKRS treatment outcome for VS.

An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

NASA Astrophysics Data System (ADS)

Zhongqin, G.; Chen, Y.

2017-12-01

Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

Geomorphological diversity of Dong-Sha Atoll based on spectrum and texture analysis in high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Chen, Jianyu; Mao, Zhihua; He, Xianqiang

2009-01-01

Coral reefs are complex marine ecosystems that are constructed and maintained by biological communities that thrive in tropical oceans. The Dong-Sha Atoll is located at the northern continental margin of the South China Sea. It has being abused by destructive activity of human being and natural event during recent decades. Remote sensing offers a powerful tool for studying coral reef geomorphology and is the most cost-effective approach for large-scale reef survey. In this paper, the high-resolution Quickbird2 imageries which covered the full atoll are used to categorize the current distribution of coral reefs geomorphological structure therein with the auxiliary SPOT5 and ASTER imageries. Spectral and texture analysis are used to distinguish the geomorphological diversity during data processing. The Gray Level Co-occurrence Matrices is adopted for texture feature extraction and atoll geomorphology mapping in the high-resolution pan-color image of Quickbird2. Quickbird2 is considered as the most appropriate image source for coral reefs studies. In the Dong-Sha Atoll, various dynamical geomorphologic units are developed according to wave energy zones. There the reef frame types are classified to 3 different types according as its diversity at the image. The radial structure system is the most characteristic and from high resolution imagery we can distinguish the discrepancy between them.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging.

PubMed

Banerjee, Imon; Malladi, Sadhika; Lee, Daniela; Depeursinge, Adrien; Telli, Melinda; Lipson, Jafi; Golden, Daniel; Rubin, Daniel L

2018-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.

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

The origin and determination of silica types in the silica occurrences from Altintaş region (Uşak-Western Anatolia) using multianalytical techniques.

PubMed

Koralay, Tamer; Kadıoğlu, Yusuf Kağan

2015-02-25

The studied area is located in Western Anatolia and situated on the NE-SW directed Uşak-Güre cross-graben that developed under a crustal extensional regime during the Late Miocene-Pliocene. Silica occurrences have been mostly found as mushroom-shaped big caps. They also show sedimentary structures such as stratification. Silica occurrences are milky white, yellowish white, yellow to chocolate brown and rarely pale blue, bluish gray in color and have no crystal forms in hand specimen. Some of the silica samples show conchoidal fracture. Silica minerals are mostly chalcedony, low-quartz (α-quartz) and sporadically opal-CT in spectras, according to confocal Raman spectrometry. The silica samples have enrichment of Fe (1000-24,600 ppm), Ca (100-10,200 ppm), P (4-3950 ppm) and Mn (8-3020 ppm). Other striking elements in fewer amounts are Ba (0.9-609.6 ppm), Ni (15.7-182.3 ppm) and Co (18.6-343.1 ppm). In chondrite-normalized spider diagram, silica samples display partial enrichment in LIL elements (Rb, Ba, Th). The δ(18)O (‰ V-SMOW) values for silica samples vary from 18.4‰ to 22.8‰ and are similar to low temperature hydrothermal silica. Confocal Raman spectrometry and oxygen isotope indicate that the silica minerals may precipitate from host fluid which is relatively has low temperatures hydrothermal solutions derived from the residual melt of basaltic magma. Copyright © 2014 Elsevier B.V. All rights reserved.

The co-occurrence of childhood sexual abuse, adult sexual assault, intimate partner violence, and sexual harassment: a mediational model of posttraumatic stress disorder and physical health outcomes.

PubMed

Campbell, Rebecca; Greeson, Megan R; Bybee, Deborah; Raja, Sheela

2008-04-01

This study examined the co-occurrence of childhood sexual abuse, adult sexual assault, intimate partner violence, and sexual harassment in a predominantly African American sample of 268 female veterans, randomly sampled from an urban Veterans Affairs hospital women's clinic. A combination of hierarchical and iterative cluster analysis was used to identify 4 patterns of women's lifetime experiences of violence co-occurrence. The 1st cluster experienced relatively low levels of all 4 forms of violence; the 2nd group, high levels of all 4 forms; the 3rd, sexual revictimization across the lifespan with adult sexual harassment; and the 4th, high intimate partner violence with sexual harassment. This cluster solution was validated in a theoretically driven model that examined the role of posttraumatic stress disorder (PTSD) as a mediator of physical health symptomatology. Structural equation modeling analyses revealed that PTSD fully mediated the relationship between violence and physical health symptomatology. Consistent with a bio-psycho-immunologic theoretical model, PTSD levels more strongly predicted pain-related physical health symptoms compared to nonpain health problems. Implications for clinical interventions to prevent PTSD and to screen women for histories of violence in health care settings are discussed. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Getting connected: Both associative and semantic links structure semantic memory for newly learned persons.

PubMed

Wiese, Holger; Schweinberger, Stefan R

2015-01-01

The present study examined whether semantic memory for newly learned people is structured by visual co-occurrence, shared semantics, or both. Participants were trained with pairs of simultaneously presented (i.e., co-occurring) preexperimentally unfamiliar faces, which either did or did not share additionally provided semantic information (occupation, place of living, etc.). Semantic information could also be shared between faces that did not co-occur. A subsequent priming experiment revealed faster responses for both co-occurrence/no shared semantics and no co-occurrence/shared semantics conditions, than for an unrelated condition. Strikingly, priming was strongest in the co-occurrence/shared semantics condition, suggesting additive effects of these factors. Additional analysis of event-related brain potentials yielded priming in the N400 component only for combined effects of visual co-occurrence and shared semantics, with more positive amplitudes in this than in the unrelated condition. Overall, these findings suggest that both semantic relatedness and visual co-occurrence are important when novel information is integrated into person-related semantic memory.

Gray and white matter volume abnormalities in monozygotic and same-gender dizygotic twins discordant for schizophrenia.

PubMed

Hulshoff Pol, Hilleke E; Brans, Rachel G H; van Haren, Neeltje E M; Schnack, Hugo G; Langen, Marieke; Baaré, Wim F C; van Oel, Clarine J; Kahn, René S

2004-01-15

Whole brain tissue volume decreases in schizophrenia have been related to both genetic risk factors and disease-related (possibly nongenetic) factors; however, whether genetic and environmental risk factors in the brains of patients with schizophrenia are differentially reflected in gray or white matter volume change is not known. Magnetic resonance imaging (1.5 T) brain scans of 11 monozygotic and 11 same-gender dizygotic twin pairs discordant for schizophrenia were acquired and compared with 11 monozygotic and 11 same-gender dizygotic healthy control twin pairs. Repeated-measures volume analysis of covariance revealed decreased whole brain volume in the patients with schizophrenia as compared with their co-twins and with healthy twin pairs. Decreased white matter volume was found in discordant twin pairs compared with healthy twin pairs, particularly in the monozygotic twin pairs. A decrease in gray matter was found in the patients compared with their co-twins and compared with the healthy twins. The results suggest that the decreases in white matter volume reflect the increased genetic risk to develop schizophrenia, whereas the decreases in gray matter volume are related to environmental risk factors. Study of genes involved in the (maintenance) of white matter structures may be particularly fruitful in schizophrenia.

Biogeographical Analysis of Chemical Co-Occurrence Data to ...

EPA Pesticide Factsheets

A challenge with multiple chemical risk assessment is the need to consider the joint behavior of chemicals in mixtures. To address this need, pharmacologists and toxicologists have developed methods over the years to evaluate and test chemical interaction. In practice, however, testing of chemical interaction more often comprises ad hoc binary combinations and rarely examines higher order combinations. One explanation for this practice is the belief that there are simply too many possible combinations of chemicals to consider. Indeed, under stochastic conditions the possible number of chemical combinations scales geometrically as the pool of chemicals increases. However, the occurrence of chemicals in the environment is determined by factors, economic in part, which favor some chemicals over others. We investigate methods from the field of biogeography, originally developed to study avian species co-occurrence patterns, and adapt these approaches to examine chemical co-occurrence. These methods were applied to a national survey of pesticide residues in 168 child care centers from across the country. Our findings show that pesticide co-occurrence in the child care center was not random but highly structured, leading to the co-occurrence of specific pesticide combinations. Thus, ecological studies of species co-occurrence parallel the issue of chemical co-occurrence at specific locations. Both are driven by processes that introduce structure in the pattern of co-o

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

Altazi, B; Fernandez, D; Zhang, G

Purpose: Site-specific investigations of the role of Radiomics in cancer diagnosis and therapy are needed. We report of the reproducibility of quantitative image features over different discrete voxel levels in PET/CT images of cervical cancer. Methods: Our dataset consisted of the pretreatment PET/CT scans from a cohort of 76 patients diagnosed with cervical cancer, FIGO stage IB-IVA, age range 31–76 years, treated with external beam radiation therapy to a dose range between 45–50.4 Gy (median dose: 45 Gy), concurrent cisplatin chemotherapy and MRI-based Brachytherapy to a dose of 20–30 Gy (median total dose: 28 Gy). Two board certified radiation oncologistsmore » delineated Metabolic Tumor volume (MTV) for each patient. Radiomics features were extracted based on 32, 64, 128 and 256 discretization levels (DL). The 64 level was chosen to be the reference DL. Features were calculated based on Co-occurrence (COM), Gray Level Size Zone (GLSZM) and Run-Length (RLM) matrices. Mean Percentage Differences (Δ) of features for discrete levels were determined. Normality distribution of Δ was tested using Kolomogorov - Smirnov test. Bland-Altman test was used to investigate differences between feature values measured on different DL. The mean, standard deviation and upper/lower value limits for each pair of DL were calculated. Interclass Correlation Coefficient (ICC) analysis was performed to examine the reliability of repeated measures within the context of the test re-test format. Results: 3 global and 5 regional features out of 48 features showed distribution not significantly different from a normal one. The reproducible features passed the normality test. Only 5 reproducible results were reliable, ICC range 0.7 – 0.99. Conclusion: Most of the radiomics features tested showed sensitivity to voxel level discretization between (32 – 256). Only 4 GLSZM, 3 COM and 1 RLM showed insensitivity towards mentioned discrete levels.« less

Efficiency of quantitative echogenicity for investigating supraspinatus tendinopathy by the gray-level histogram of two ultrasound devices.

PubMed

Hsu, Jiun-Cheng; Chen, Po-Han; Huang, Kuo-Chin; Tsai, Yao-Hung; Hsu, Wei-Hsiu

2017-10-01

The gray-level histogram of ultrasound is a promising tool for scanning the hypoechogenic appearance of supraspinatus tendinopathy, and the aim of this study was to test the hypothesis that the gray-level value of the supraspinatus tendon in the painful shoulder has a lower value on B-mode images even though in different ultrasound devices. Sixty-seven patients who had unilateral shoulder pain with rotator cuff tendinopathy underwent bilateral shoulder ultrasonography, and we compared the mean gray-level values of painful shoulders and contralateral shoulders without any pain in each patient using two ultrasound devices. The echogenicity ratio (symptomatic/asymptomatic side) of two ultrasound devices was compared. A significant difference existed between the symptomatic shoulder and contralateral asymptomatic shoulder (p < 0.001) on the mean gray-level value measurements of each device. The symptomatic-to-asymptomatic tendon echogenicity ratio of device A was 0.919 ± 0.090 in the transverse plane and 0.937 ± 0.081 in the longitudinal plane, and the echogenicity ratio of device B was 0.899 ± 0.113 in the transverse plane and 0.940 ± 0.113 in the longitudinal plane. The decline of the mean gray-level value and the echogenicity ratio of the supraspinatus tendon in the painful shoulder may be utilized as a useful sonographic reference of unilateral rotator cuff lesions. Diagnostic level III.

Co-occurrence of Victimization from Five Subtypes of Bullying: Physical, Verbal, Social Exclusion, Spreading Rumors, and Cyber

PubMed Central

Iannotti, Ronald J.; Luk, Jeremy W.; Nansel, Tonja R.

2010-01-01

Objective To examine co-occurrence of five subtypes of peer victimization. Methods Data were obtained from a national sample of 7,475 US adolescents in grades 6 through 10 in the 2005/2006 Health Behavior in School-Aged Children (HBSC) study. Latent class analyses (LCA) were conducted on victimization by physical, verbal, social exclusion, spreading rumors, and cyber bullying. Results Three latent classes were identified, including an all-types victims class (9.7% of males and 6.2% of females), a verbal/relational victims class (28.1% of males and 35.1% of females), and a nonvictim class (62.2% of males and 58.7% of females). Males were more likely to be all-type victims. There was a graded relationship between the three latent classes and level of depression, frequency of medically attended injuries, and medicine use, especially among females. Conclusions  Increased co-occurrence of victimization types put adolescents at greater risks for poorer physical and psychological outcomes. PMID:20488883

Children with co-occurring anxiety and externalizing disorders: family risks and implications for competence.

PubMed

Yoo, Joan P; Brown, Pamela J; Luthar, Suniya S

2009-10-01

This study used data from 340 mother-child dyads to examine characteristics of children with co-occurring diagnoses of anxiety and externalizing disorders and compared them with children with a sole diagnosis or no diagnosis. Comparisons were made using 4 child-diagnostic groups: anxiety-only, externalizing-only, co-occurrence, and no-problem groups. Most mothers were characterized by low income and histories of psychiatric diagnoses during the child's lifetime. Analyses using multinomial logistic regressions found the incidence of co-occurring childhood disorders to be significantly linked with maternal affective/anxiety disorders during the child's lifetime. In exploring implications for developmental competence, we found the co-occurrence group to have the lowest level of adaptive functioning among the 4 groups, faring significantly worse than the no-problem group on both academic achievement and intelligence as assessed by standardized tests. Findings underscore the importance of considering co-occurring behavior problems as a distinct phenomenon when examining children's developmental outcomes. (c) 2009 APA, all rights reserved.

Modulation of the activity of midbrain central gray substance neurons by calcium channel agonists and antagonists in vitro.

PubMed

Yakhnitsa, V A; Pilyavskii, A I; Limansky, Y P; Bulgakova, N V

1996-01-01

Changes in the background impulse activity of midbrain central gray substance neurons have been studied on slice preparations from the rat midbrain upon application of calcium-free solution, an activator of calcium channels, BAY-K 8644 (10 nM), organic (verapamil, 40 microM; D600, 10 microM; nifedipine, 1-10 microM; amiloride, 1 microM) and inorganic (Co2+, 1.5 mM) calcium channel blockers. Besides BAY-K 8644, all the substances inhibited most of the neurons studied. Verapamil, BAY-K 8644 and Co2+ also revealed facilitatory effects. Facilitatory action of BAY-K was most effective in silent neurons and in those previously inhibited by amiloride. Latent period values of inhibition in calcium-free solution and upon application of organic and inorganic blockers have the following sequence: D600 > amiloride > verapamil > Co2+ > nifedipine > calcium-free solution. Maximum rise time had the following order: amiloride > D600 > nifedipine > verapamil > Co2+ > calcium-free solution. Complete suppression of the neuronal activity induced by amiloride lasted twice as long as that induced by calcium-free solution, Co2+ and nifedipine, and six times as long as verapamil-induced suppression. Preliminary application of calcium channel blockers reduced facilitatory and increased inhibitory effects of serotonin and substance P. Data obtained are discussed with the supposition in mind that inhibition of the function of calcium channels in central gray substance neurons could be one of the mechanisms underlying the analgesic effect of a series of neurotropic agents after their introduction into this structure.

Design and testing of a new radio-tag for instrumenting large whales. Final report

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

Follmann, E.H.; Miller, G.O.

1981-03-01

In 1978, Project Whales was initiated to investigate the occurrence, ecology, and biology of bowhead and gray whales in areas of the Beaufort Sea under consideration for offshore oil and gas leasing. One aspect of the study was to develop radio tags to monitor the movement and behavior of whales. It was considered important to test the radio tag design in more favorable environments than arctic waters. The test called for tagging of gray whales in Mexico with the objective to determine (1) effectiveness of the attachment procedure for tagging large whales (2) length of time the radio tag willmore » remain attached to a whale, and (3) range of reception from tagged whales.« less

Co-occurrence dynamics of endangered Lower Keys marsh rabbits and free-ranging domestic cats: Prey responses to an exotic predator removal program.

PubMed

Cove, Michael V; Gardner, Beth; Simons, Theodore R; O'Connell, Allan F

2018-04-01

The Lower Keys marsh rabbit ( Sylvilagus palustris hefneri ) is one of many endangered endemic species of the Florida Keys. The main threats are habitat loss and fragmentation from sea-level rise, development, and habitat succession. Exotic predators such as free-ranging domestic cats ( Felis catus ) pose an additional threat to these endangered small mammals. Management strategies have focused on habitat restoration and exotic predator control. However, the effectiveness of predator removal and the effects of anthropogenic habitat modifications and restoration have not been evaluated. Between 2013 and 2015, we used camera traps to survey marsh rabbits and free-ranging cats at 84 sites in the National Key Deer Refuge, Big Pine Key, Florida, USA. We used dynamic occupancy models to determine factors associated with marsh rabbit occurrence, colonization, extinction, and the co-occurrence of marsh rabbits and cats during a period of predator removal. Rabbit occurrence was positively related to freshwater habitat and patch size, but was negatively related to the number of individual cats detected at each site. Furthermore, marsh rabbit colonization was negatively associated with relative increases in the number of individual cats at each site between survey years. Cat occurrence was negatively associated with increasing distance from human developments. The probability of cat site extinction was positively related to a 2-year trapping effort, indicating that predator removal reduced the cat population. Dynamic co-occurrence models suggested that cats and marsh rabbits co-occur less frequently than expected under random conditions, whereas co-detections were site and survey-specific. Rabbit site extinction and colonization were not strongly conditional on cat presence, but corresponded with a negative association. Our results suggest that while rabbits can colonize and persist at sites where cats occur, it is the number of individual cats at a site that more strongly influences rabbit occupancy and colonization. These findings indicate that continued predator management would likely benefit endangered small mammals as they recolonize restored habitats.

Gray matter network disruptions and amyloid beta in cognitively normal adults.

PubMed

Tijms, Betty M; Kate, Mara Ten; Wink, Alle Meije; Visser, Pieter Jelle; Ecay, Mirian; Clerigue, Montserrat; Estanga, Ainara; Garcia Sebastian, Maite; Izagirre, Andrea; Villanua, Jorge; Martinez Lage, Pablo; van der Flier, Wiesje M; Scheltens, Philip; Sanz Arigita, Ernesto; Barkhof, Frederik

2016-01-01

Gray matter networks are disrupted in Alzheimer's disease (AD). It is unclear when these disruptions start during the development of AD. Amyloid beta 1-42 (Aβ42) is among the earliest changes in AD. We studied, in cognitively healthy adults, the relationship between Aβ42 levels in cerebrospinal fluid (CSF) and single-subject cortical gray matter network measures. Single-subject gray matter networks were extracted from structural magnetic resonance imaging scans in a sample of cognitively healthy adults (N = 185; age range 39-79, mini-mental state examination >25, N = 12 showed abnormal Aβ42 < 550 pg/mL). Degree, clustering coefficient, and path length were computed at whole brain level and for 90 anatomical areas. Associations between continuous Aβ42 CSF levels and single-subject cortical gray matter network measures were tested. Smoothing splines were used to determine whether a linear or nonlinear relationship gave a better fit to the data. Lower Aβ42 CSF levels were linearly associated at whole brain level with lower connectivity density, and nonlinearly with lower clustering values and higher path length values, which is indicative of a less-efficient network organization. These relationships were specific to medial temporal areas, precuneus, and the middle frontal gyrus (all p < 0.05). These results suggest that mostly within the normal spectrum of amyloid, lower Aβ42 levels can be related to gray matter networks disruptions. Copyright © 2016 Elsevier Inc. All rights reserved.

How does language change as a lexical network? An investigation based on written Chinese word co-occurrence networks

PubMed Central

Chen, Heng; Chen, Xinying

2018-01-01

Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system. PMID:29489837

How does language change as a lexical network? An investigation based on written Chinese word co-occurrence networks.

PubMed

Chen, Heng; Chen, Xinying; Liu, Haitao

2018-01-01

Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system.

Discordance in CD4+T-Cell Levels and Viral Loads with Co-Occurrence of Elevated Peripheral TNF-α and IL-4 in Newly Diagnosed HIV-TB Co-Infected Cases

PubMed Central

Benjamin, Ronald; Banerjee, Atoshi; Sunder, Sharada Ramaseri; Gaddam, Sumanlatha; Valluri, Vijaya Lakshmi; Banerjee, Sharmistha

2013-01-01

Background Cytokines are the hallmark of immune response to different pathogens and often dictate the disease outcome. HIV infection and tuberculosis (TB) are more destructive when confronted together than either alone. Clinical data related to the immune status of HIV-TB patients before the initiation of any drug therapy is not well documented. This study aimed to collect the baseline information pertaining to the immune status of HIV-TB co-infected patients and correlate the same with CD4+T cell levels and viral loads at the time of diagnosis prior to any drug therapy. Methodology/Principal Findings We analyzed the cytokines, CD4+T cell levels and viral loads to determine the immune environment in HIV-TB co-infection. The study involved four categories namely, Healthy controls (n = 57), TB infected (n = 57), HIV infected (n = 59) and HIV-TB co-infected (n = 57) patients. The multi-partite comparison and correlation between cytokines, CD4+T-cell levels and viral loads prior to drug therapy, showed an altered TH1 and TH2 response, as indicated by the cytokine profiles and skewed IFN-γ/IL-10 ratio. Inadequate CD4+T cell counts in HIV-TB patients did not correlate with high viral loads and vice-versa. When compared to HIV category, 34% of HIV-TB patients had concurrent high plasma levels of IL-4 and TNF-α at the time of diagnosis. TB relapse was observed in 5 of these HIV-TB co-infected patients who also displayed high IFN-γ/IL-10 ratio. Conclusion/Significance With these studies, we infer (i) CD4+T-cell levels as baseline criteria to report the disease progression in terms of viral load in HIV-TB co-infected patients can be misleading and (ii) co-occurrence of high TNF-α and IL-4 levels along with a high ratio of IFN-γ/IL-10, prior to drug therapy, may increase the susceptibility of HIV-TB co-infected patients to hyper-inflammation and TB relapse. PMID:23936398

The co-occurrence of mental disorders in children and adolescents with intellectual disability/intellectual developmental disorder

PubMed Central

Munir, Kerim M.

2016-01-01

Purpose of review The study summarizes supportive epidemiological data regarding the true co-occurrence (comorbidity) and course of mental disorders in children with intellectual disability/intellectual developmental disorders (ID/IDD) across the lifespan. Recent findings Published studies involving representative populations of children and adolescents with ID/IDD have demonstrated a three to four-fold increase in prevalence of co-occurring mental disorders. The effect of age, sex, and severity (mild, moderate, severe, and profound) and socioeconomic status on prevalence is currently not clearly understood. To date there are no prevalence estimates of co-occurring mental disorders in youth identified using the new DSM-5 (and proposed ICD-11) definition of ID/IDD using measures of intellectual functions and deficits in adaptive functioning with various severity levels defined on the basis of adaptive functioning, and not intellectual quotient scores. Summary The true relationship between two forms of morbidity remains complex and causal relationships that may be true for one disorder may not apply to another. The new conceptualization of ID/IDD offers a developmentally better informed psychobiological approach that can help distinguish co-occurrence of mental disorders within the neurodevelopmental section with onset during the developmental period as well as the later onset of other mental disorders. PMID:26779862

The co-occurrence of mental disorders in children and adolescents with intellectual disability/intellectual developmental disorder.

PubMed

Munir, Kerim M

2016-03-01

The study summarizes supportive epidemiological data regarding the true co-occurrence (comorbidity) and course of mental disorders in children with intellectual disability/intellectual developmental disorders (ID/IDD) across the lifespan. Published studies involving representative populations of children and adolescents with ID/IDD have demonstrated a three to four-fold increase in prevalence of co-occurring mental disorders. The effect of age, sex, and severity (mild, moderate, severe, and profound) and socioeconomic status on prevalence is currently not clearly understood. To date there are no prevalence estimates of co-occurring mental disorders in youth identified using the new DSM-5 (and proposed ICD-11) definition of ID/IDD using measures of intellectual functions and deficits in adaptive functioning with various severity levels defined on the basis of adaptive functioning, and not intellectual quotient scores. The true relationship between two forms of morbidity remains complex and causal relationships that may be true for one disorder may not apply to another. The new conceptualization of ID/IDD offers a developmentally better informed psychobiological approach that can help distinguish co-occurrence of mental disorders within the neurodevelopmental section with onset during the developmental period as well as the later onset of other mental disorders.

LIFETIME AND TEMPORAL OCCURRENCE OF ECTOMYCORRHIZAE ON PONDEROSA PINE (PINUS PONDEROSA LAWS.) SEEDLINGS GROWN UNDER VARIED ATMOSPHERIC CO-2 AND NITROGEN LEVELS

EPA Science Inventory

Climate change(elevated atmospheric CO-2,and altered air temperatures,precipitation amounts and seasonal patterns)may affect ecosystem processes by altering carbon allocation in plants,and carbon flux from plants to soil.Mycorrhizal fungi,as carbon sinks, are among the first soil...

Current Situation of Mycotoxin Contamination and Co-occurrence in Animal Feed—Focus on Europe

PubMed Central

Streit, Elisabeth; Schatzmayr, Gerd; Tassis, Panagiotis; Tzika, Eleni; Marin, Daniela; Taranu, Ionelia; Tabuc, Cristina; Nicolau, Anca; Aprodu, Iuliana; Puel, Olivier; Oswald, Isabelle P.

2012-01-01

Mycotoxins are secondary metabolites produced by fungi especially those belonging to the genus Aspergillus, Penicillum and Fusarium. Mycotoxin contamination can occur in all agricultural commodities in the field and/or during storage, if conditions are favourable to fungal growth. Regarding animal feed, five mycotoxins (aflatoxins, deoxynivalenol, zearalenone, fumonisins and ochratoxin A) are covered by EU legislation (regulation or recommendation). Transgressions of these limits are rarely observed in official monitoring programs. However, low level contamination by Fusarium toxins is very common (e.g., deoxynivalenol (DON) is typically found in more than 50% of the samples) and co-contamination is frequently observed. Multi-mycotoxin studies reported 75%–100% of the samples to contain more than one mycotoxin which could impact animal health at already low doses. Co-occurrence of mycotoxins is likely to arise for at least three different reasons (i) most fungi are able to simultaneously produce a number of mycotoxins, (ii) commodities can be contaminated by several fungi, and (iii) completed feed is made from various commodities. In the present paper, we reviewed the data published since 2004 concerning the contamination of animal feed with single or combinations of mycotoxins and highlighted the occurrence of these co-contaminations. PMID:23162698

Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies

PubMed Central

Kober, Hedy; Barrett, Lisa Feldman; Joseph, Josh; Bliss-Moreau, Eliza; Lindquist, Kristen; Wager, Tor D.

2009-01-01

We performed an updated quantitative meta-analysis of 162 neuroimaging studies of emotion using a novel multi-level kernel-based approach, focusing on locating brain regions consistently activated in emotional tasks and their functional organization into distributed functional groups, independent of semantically defined emotion category labels (e.g., “anger,” “fear”). Such brain-based analyses are critical if our ways of labeling emotions are to be evaluated and revised based on consistency with brain data. Consistent activations were limited to specific cortical sub-regions, including multiple functional areas within medial, orbital, and inferior lateral frontal cortices. Consistent with a wealth of animal literature, multiple subcortical activations were identified, including amygdala, ventral striatum, thalamus, hypothalamus, and periaqueductal gray. We used multivariate parcellation and clustering techniques to identify groups of co-activated brain regions across studies. These analyses identified six distributed functional groups, including medial and lateral frontal groups, two posterior cortical groups, and paralimbic and core limbic/brainstem groups. These functional groups provide information on potential organization of brain regions into large-scale networks. Specific follow-up analyses focused on amygdala, periaqueductal gray (PAG), and hypothalamic (Hy) activations, and identified frontal cortical areas co-activated with these core limbic structures. While multiple areas of frontal cortex co-activated with amygdala sub-regions, a specific region of dorsomedial prefrontal cortex (dmPFC, Brodmann’s Area 9/32) was the only area co-activated with both PAG and Hy. Subsequent mediation analyses were consistent with a pathway from dmPFC through PAG to Hy. These results suggest that medial frontal areas are more closely associated with core limbic activation than their lateral counterparts, and that dmPFC may play a particularly important role in the cognitive generation of emotional states. PMID:18579414

Deciphering microbial interactions and detecting keystone species with co-occurrence networks.

PubMed

Berry, David; Widder, Stefanie

2014-01-01

Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

2004-01-01

Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative measures used in this study will in combination attempt to determine which texture characterization models best capture the correct statistical and radiometric attributes of the corresponding real image textures in both the spatial and spectral domains. The motivation for this work is to refine our understanding of the complexities of texture phenomena so that an optimal texture characterization model that can accurately account for these complexities can be eventually implemented into a synthetic image generation (SIG) model. Further, conclusions will be drawn regarding which of the candidate texture models are able to achieve realistic levels of spatial and spectral clutter, thereby permitting more effective and robust testing of hyperspectral algorithms in synthetic imagery.

Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

2003-12-01

Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative measures used in this study will in combination attempt to determine which texture characterization models best capture the correct statistical and radiometric attributes of the corresponding real image textures in both the spatial and spectral domains. The motivation for this work is to refine our understanding of the complexities of texture phenomena so that an optimal texture characterization model that can accurately account for these complexities can be eventually implemented into a synthetic image generation (SIG) model. Further, conclusions will be drawn regarding which of the candidate texture models are able to achieve realistic levels of spatial and spectral clutter, thereby permitting more effective and robust testing of hyperspectral algorithms in synthetic imagery.

Species co-occurrence analysis predicts management outcomes for multiple threats.

PubMed

Tulloch, Ayesha I T; Chadès, Iadine; Lindenmayer, David B

2018-03-01

Mitigating the impacts of global anthropogenic change on species is conservation's greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species' responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery.

Age, stress, and emotional complexity: results from two studies of daily experiences.

PubMed

Scott, Stacey B; Sliwinski, Martin J; Mogle, Jacqueline A; Almeida, David M

2014-09-01

Experiencing positive and negative emotions together (i.e., co-occurrence) has been described as a marker of positive adaptation during stress and a strength of socioemotional aging. Using data from daily diary (N = 2,022; ages 33-84) and ecological momentary assessment (N = 190; ages 20-80) studies, we evaluate the utility of a common operationalization of co-occurrence, the within-person correlation between positive affect (PA) and negative affect (NA). Then we test competing predictions regarding when co-occurrence will be observed and whether age differences will be present. Results indicate that the correlation is not an informative indicator of co-occurrence. Although correlations were stronger and more negative when stressors occurred (typically interpreted as lower co-occurrence), objective counts of emotion reports indicated that positive and negative emotions were 3 to 4 times more likely to co-occur when stressors were reported. This suggests that co-occurrence reflects the extent to which negative emotions intrude on typically positive emotional states, rather than the extent to which people maintain positive emotions during stress. The variances of both PA and NA increased at stressor reports, indicating that individuals reported a broader not narrower range of emotion during stress. Finally, older age was associated with less variability in NA and a lower likelihood of co-occurring positive and negative emotions. In sum, these findings cast doubt on the utility of the PA-NA correlation as an index of emotional co-occurrence, and question notion that greater emotional co-occurrence represents either a typical or adaptive emotional state in adults. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Modifications of resting state networks in spinocerebellar ataxia type 2.

PubMed

Cocozza, Sirio; Saccà, Francesco; Cervo, Amedeo; Marsili, Angela; Russo, Cinzia Valeria; Giorgio, Sara Maria Delle Acque; De Michele, Giuseppe; Filla, Alessandro; Brunetti, Arturo; Quarantelli, Mario

2015-09-01

We aimed to investigate the integrity of the Resting State Networks in spinocerebellar ataxia type 2 (SCA2) and the correlations between the modification of these networks and clinical variables. Resting-state functional magnetic resonance imaging (RS-fMRI) data from 19 SCA2 patients and 29 healthy controls were analyzed using an independent component analysis and dual regression, controlling at voxel level for the effect of atrophy by co-varying for gray matter volume. Correlations between the resting state networks alterations and disease duration, age at onset, number of triplets, and clinical score were assessed by Spearman's coefficient, for each cluster which was significantly different in SCA2 patients compared with healthy controls. In SCA2 patients, disruption of the cerebellar components of all major resting state networks was present, with supratentorial involvement only for the default mode network. When controlling at voxel level for gray matter volume, the reduction in functional connectivity in supratentorial regions of the default mode network, and in cerebellar regions within the default mode, executive and right fronto-parietal networks, was still significant. No correlations with clinical variables were found for any of the investigated resting state networks. The SCA2 patients show significant alterations of the resting state networks, only partly explained by the atrophy. The default mode network is the only resting state network that shows also supratentorial changes, which appear unrelated to the cortical gray matter volume. Further studies are needed to assess the clinical significance of these changes. © 2015 International Parkinson and Movement Disorder Society.

The Co-Occurrence of Reading Disorder and ADHD: Epidemiology, Treatment, Psychosocial Impact, and Economic Burden

ERIC Educational Resources Information Center

Sexton, Chris C.; Gelhorn, Heather L.; Bell, Jill A.; Classi, Peter M.

2012-01-01

The co-occurrence of reading disorder (RD) and attention-deficit/hyperactivity disorder (ADHD) has received increasing attention. This review summarizes the epidemiology, treatment strategies, psychosocial impact, and economic burden associated with the co-occurrence of these conditions. Common genetic and neuropsychological deficits may partially…

Factors mediating co-occurrence of an economically valuable introduced fish and its native frog prey.

PubMed

Hartman, Rosemary; Pope, Karen; Lawler, Sharon

2014-06-01

Habitat characteristics mediate predator-prey coexistence in many ecological systems but are seldom considered in species introductions. When economically important introduced predators are stocked despite known negative impacts on native species, understanding the role of refuges, landscape configurations, and community interactions can inform habitat management plans. We measured these factors in basins with introduced trout (Salmonidae) and the Cascades frog (Rana cascadae) to determine, which are responsible for observed patterns of co-occurrence of this economically important predator and its native prey. Large, vegetated shallows were strongly correlated to co-occurrence, and R. cascadae larvae occur in shallower water when fish are present, presumably to escape predation. The number of nearby breeding sites of R. cascadae was also correlated to co-occurrence, but only when the western toad (Anaxyrus boreas) was present. Because A. boreas larvae are unpalatable to fish and resemble R. cascadae, they may provide protection from trout via Batesian mimicry. Although rescue-effect dispersal from nearby populations may maintain co-occurrence, within-lake factors proved more important for predicting co-occurrence. Learning which factors allow co-occurrence between economically important introduced species and their native prey enables managers to make better-informed stocking decisions. © 2013 Society for Conservation Biology.

Opto-acoustic breast imaging with co-registered ultrasound

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Herzog, Don; Miller, Tom; Stavros, A. Thomas; Oraevsky, Alexander; Kist, Kenneth; Dornbluth, N. Carol; Otto, Pamela

2014-03-01

We present results from a recent study involving the ImagioTM breast imaging system, which produces fused real-time two-dimensional color-coded opto-acoustic (OA) images that are co-registered and temporally inter- leaved with real-time gray scale ultrasound using a specialized duplex handheld probe. The use of dual optical wavelengths provides functional blood map images of breast tissue and tumors displayed with high contrast based on total hemoglobin and oxygen saturation of the blood. This provides functional diagnostic information pertaining to tumor metabolism. OA also shows morphologic information about tumor neo-vascularity that is complementary to the morphological information obtained with conventional gray scale ultrasound. This fusion technology conveniently enables real-time analysis of the functional opto-acoustic features of lesions detected by readers familiar with anatomical gray scale ultrasound. We demonstrate co-registered opto-acoustic and ultrasonic images of malignant and benign tumors from a recent clinical study that provide new insight into the function of tumors in-vivo. Results from the Feasibility Study show preliminary evidence that the technology may have the capability to improve characterization of benign and malignant breast masses over conventional diagnostic breast ultrasound alone and to improve overall accuracy of breast mass diagnosis. In particular, OA improved speci city over that of conventional diagnostic ultrasound, which could potentially reduce the number of negative biopsies performed without missing cancers.

Higher homocysteine associated with thinner cortical gray matter in 803 ADNI subjects

PubMed Central

Madsen, Sarah K.; Rajagopalan, Priya; Joshi, Shantanu H.; Toga, Arthur W.; Thompson, Paul M.

2014-01-01

A significant portion of our risk for dementia in old age is associated with lifestyle factors (diet, exercise, and cardiovascular health) that are modifiable, at least in principle. One such risk factor – high homocysteine levels in the blood – is known to increase risk for Alzheimer’s disease and vascular disorders. Here we set out to understand how homocysteine levels relate to 3D surface-based maps of cortical gray matter distribution (thickness, volume, surface area) computed from brain MRI in 803 elderly subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Individuals with higher plasma levels of homocysteine had lower gray matter thickness in bilateral frontal, parietal, occipital and right temporal regions; and lower gray matter volumes in left frontal, parietal, temporal, and occipital regions, after controlling for diagnosis, age, and sex, and after correcting for multiple comparisons. No significant within-group associations were found in cognitively healthy people, mild cognitive impairment, or Alzheimer’s disease. These regional differences in gray matter structure may be useful biomarkers to assess the effectiveness of interventions, such as vitamin B supplements, that aim to prevent homocysteine-related brain atrophy by normalizing homocysteine levels. PMID:25444607

Automatic image equalization and contrast enhancement using Gaussian mixture modeling.

PubMed

Celik, Turgay; Tjahjadi, Tardi

2012-01-01

In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels' gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval. To take account of the hypothesis that homogeneous regions in the image represent homogeneous silences (or set of Gaussian components) in the image histogram, the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the gray-level distribution is also used to weight the components in the mapping of the input interval to the output interval. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several state-of-the-art algorithms. Unlike the other algorithms, the proposed algorithm is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types.

Optimization of Maghemite (γ-Fe2O3) Nano-Powder Mixed micro-EDM of CoCrMo with Multiple Responses Using Gray Relational Analysis (GRA)

NASA Astrophysics Data System (ADS)

Mejid Elsiti, Nagwa; Noordin, M. Y.; Idris, Ani; Saed Majeed, Faraj

2017-10-01

This paper presents an optimization of process parameters of Micro-Electrical Discharge Machining (EDM) process with (γ-Fe2O3) nano-powder mixed dielectric using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on 2-Level factorial design combined with Grey Relational Analysis. The machining parameters such as peak current, gap voltage, and pulse on time were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool wear rate (TWR), Taper and Overcut. Experiments were conducted using electrolyte copper as the tool and CoCrMo as the workpiece. Experimental results have been improved through this approach.

Phylogenetic fields through time: temporal dynamics of geographical co-occurrence and phylogenetic structure within species ranges

PubMed Central

Carotenuto, Francesco; Diniz-Filho, José Alexandre F.

2016-01-01

Species co-occur with different sets of other species across their geographical distribution, which can be either closely or distantly related. Such co-occurrence patterns and their phylogenetic structure within individual species ranges represent what we call the species phylogenetic fields (PFs). These PFs allow investigation of the role of historical processes—speciation, extinction and dispersal—in shaping species co-occurrence patterns, in both extinct and extant species. Here, we investigate PFs of large mammalian species during the last 3 Myr, and how these correlate with trends in diversification rates. Using the fossil record, we evaluate species' distributional and co-occurrence patterns along with their phylogenetic structure. We apply a novel Bayesian framework on fossil occurrences to estimate diversification rates through time. Our findings highlight the effect of evolutionary processes and past climatic changes on species' distributions and co-occurrences. From the Late Pliocene to the Recent, mammal species seem to have responded in an individualistic manner to climate changes and diversification dynamics, co-occurring with different sets of species from different lineages across their geographical ranges. These findings stress the difficulty of forecasting potential effects of future climate changes on biodiversity. PMID:26977061

Phylogenetic fields through time: temporal dynamics of geographical co-occurrence and phylogenetic structure within species ranges.

PubMed

Villalobos, Fabricio; Carotenuto, Francesco; Raia, Pasquale; Diniz-Filho, José Alexandre F

2016-04-05

Species co-occur with different sets of other species across their geographical distribution, which can be either closely or distantly related. Such co-occurrence patterns and their phylogenetic structure within individual species ranges represent what we call the species phylogenetic fields (PFs). These PFs allow investigation of the role of historical processes--speciation, extinction and dispersal--in shaping species co-occurrence patterns, in both extinct and extant species. Here, we investigate PFs of large mammalian species during the last 3 Myr, and how these correlate with trends in diversification rates. Using the fossil record, we evaluate species' distributional and co-occurrence patterns along with their phylogenetic structure. We apply a novel Bayesian framework on fossil occurrences to estimate diversification rates through time. Our findings highlight the effect of evolutionary processes and past climatic changes on species' distributions and co-occurrences. From the Late Pliocene to the Recent, mammal species seem to have responded in an individualistic manner to climate changes and diversification dynamics, co-occurring with different sets of species from different lineages across their geographical ranges. These findings stress the difficulty of forecasting potential effects of future climate changes on biodiversity. © 2016 The Author(s).

Co-Occurrence of Linguistic and Behavioural Difficulties in Early Childhood: A Developmental Psychopathology Perspective

ERIC Educational Resources Information Center

Carpenter, Johanna L.; Drabick, Deborah A. G.

2011-01-01

Three hypotheses have been posited as competing explanations for the comorbidity or co-occurrence of language difficulties and behavioural problems among children: (1) language difficulties confer risk for behaviour problems, (2) behaviour problems confer risk for language difficulties, and (3) shared risk factors account for their co-occurrence.…

Deciphering microbial interactions and detecting keystone species with co-occurrence networks

PubMed Central

Berry, David; Widder, Stefanie

2014-01-01

Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets. PMID:24904535

Quantifying receptor trafficking and colocalization with confocal microscopy.

PubMed

Pike, Jeremy A; Styles, Iain B; Rappoport, Joshua Z; Heath, John K

2017-02-15

Confocal microscopy is a powerful tool for the study of cellular receptor trafficking and endocytosis. Unbiased and robust image analysis workflows are required for the identification, and study, of aberrant trafficking. After a brief review of related strategies, identifying both good and bad practice, custom workflows for the analysis of live cell 3D time-lapse data are presented. Strategies for data pre-processing, including denoising and background subtraction are considered. We use a 3D level set protocol to accurately segment cells using only the signal from fluorescently labelled receptor. A protocol for the quantification of changes to subcellular receptor distribution over time is then presented. As an example, ligand stimulated trafficking of epidermal growth factor receptor (EGFR) is shown to be significantly reduced in both AG1478 and Dynasore treated cells. Protocols for the quantitative analysis of colocalization between receptor and endosomes are also introduced, including strategies for signal isolation and statistical testing. By calculating the Manders and Pearson coefficients, both co-occurrence and correlation can be assessed. A statistically significant decrease in the level of ligand induced co-occurrence between EGFR and rab5 positive endosomes is demonstrated for both the AG1478 and Dynasore treated cells relative to a control. Finally, a strategy for the visualisation of co-occurrence is presented, which provides an unbiased alternative to colour overlays. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Pesticide contamination of endangered gray bats and their food base in Boone County, Missouri, 1982

USGS Publications Warehouse

Clawson, R.L.; Clark, D.R.

1989-01-01

Gray bat guano from Devil's Icebox and Hunters Caves contained dieldrin at levels previously associated with gray bat mortality. Two of four gray bats found dead in Holton Cave had lethal brain concentrations of dieldrin. Twenty-five of 28 (86%) insect samples from bat foraging areas contained measurable dieldrin, heptachlor epoxide or both. Beetle samples were most heavily contaminated containing up to 2.2 ppm and 1.1 ppm heptachlor epoxide. The addition of Holton Cave brings to five the number of Missouri caves where gray bats have died of food chain pesticide poisoning.

Optimal Non-Invasive Fault Classification Model for Packaged Ceramic Tile Quality Monitoring Using MMW Imaging

NASA Astrophysics Data System (ADS)

Agarwal, Smriti; Singh, Dharmendra

2016-04-01

Millimeter wave (MMW) frequency has emerged as an efficient tool for different stand-off imaging applications. In this paper, we have dealt with a novel MMW imaging application, i.e., non-invasive packaged goods quality estimation for industrial quality monitoring applications. An active MMW imaging radar operating at 60 GHz has been ingeniously designed for concealed fault estimation. Ceramic tiles covered with commonly used packaging cardboard were used as concealed targets for undercover fault classification. A comparison of computer vision-based state-of-the-art feature extraction techniques, viz, discrete Fourier transform (DFT), wavelet transform (WT), principal component analysis (PCA), gray level co-occurrence texture (GLCM), and histogram of oriented gradient (HOG) has been done with respect to their efficient and differentiable feature vector generation capability for undercover target fault classification. An extensive number of experiments were performed with different ceramic tile fault configurations, viz., vertical crack, horizontal crack, random crack, diagonal crack along with the non-faulty tiles. Further, an independent algorithm validation was done demonstrating classification accuracy: 80, 86.67, 73.33, and 93.33 % for DFT, WT, PCA, GLCM, and HOG feature-based artificial neural network (ANN) classifier models, respectively. Classification results show good capability for HOG feature extraction technique towards non-destructive quality inspection with appreciably low false alarm as compared to other techniques. Thereby, a robust and optimal image feature-based neural network classification model has been proposed for non-invasive, automatic fault monitoring for a financially and commercially competent industrial growth.

The Effects of Betaine on the Nuclear Fractal Dimension, Chromatin Texture, and Proliferative Activity in Hepatocytes in Mouse Model of Nonalcoholic Fatty Liver Disease.

PubMed

Vesković, Milena; Labudović-Borović, Milica; Zaletel, Ivan; Rakočević, Jelena; Mladenović, Dušan; Jorgačević, Bojan; Vučević, Danijela; Radosavljević, Tatjana

2018-04-01

The effects of betaine on hepatocytes chromatin architecture changes were examined by using fractal and gray-level co-occurrence matrix (GLCM) analysis in methionine/choline-deficient (MCD) diet-induced, nonalcoholic fatty liver disease (NAFLD). Male C57BL/6 mice were divided into groups: (1) Control: standard diet; (2) BET: standard diet and betaine supplementation through drinking water (solution 1.5%); (3) MCD group: MCD diet for 6 weeks; (4) MCD+BET: fed with MCD diet + betaine for 6 weeks. Liver tissue was collected for histopathology, immunohistochemistry, and determination of fractal dimension and GLCM parameters. MCD diet induced diffuse micro- and macrovesicular steatosis accompanied with increased Ki67-positive hepatocyte nuclei. Steatosis and Ki67 immunopositivity were less prominent in the MCD+BET group compared with the MCD group. Angular second moment (ASM) and inverse difference moment (IDM) (textural homogeneity markers) were significantly increased in the MCD+BET group versus the MCD group (p<0.001), even though no difference between the MCD and the control group was evident. Heterogeneity parameters, contrast, and correlation were significantly increased in the MCD group versus the control (p<0.001). On the other hand, betaine treatment significantly reduced correlation, contrast, and entropy compared with the MCD group (p<0.001). Betaine attenuated MCD diet-induced NAFLD by reducing fat accumulation and inhibiting hepatocyte proliferation. Betaine supplementation increased nuclear homogeneity and chromatin complexity with reduction of entropy, contrast, and correlation.

Feasibility of opportunistic osteoporosis screening in routine contrast-enhanced multi detector computed tomography (MDCT) using texture analysis.

PubMed

Mookiah, M R K; Rohrmeier, A; Dieckmeyer, M; Mei, K; Kopp, F K; Noel, P B; Kirschke, J S; Baum, T; Subburaj, K

2018-04-01

This study investigated the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. The results showed an acceptable reproducibility of texture features, and these features could discriminate healthy/osteoporotic fracture cohort with an accuracy of 83%. This aim of this study is to investigate the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. We performed texture analysis at the spine in routine MDCT exams and investigated the effect of intravenous contrast medium (IVCM) (n = 7), slice thickness (n = 7), the long-term reproducibility (n = 9), and the ability to differentiate healthy/osteoporotic fracture cohort (n = 9 age and gender matched pairs). Eight texture features were extracted using gray level co-occurrence matrix (GLCM). The independent sample t test was used to rank the features of healthy/fracture cohort and classification was performed using support vector machine (SVM). The results revealed significant correlations between texture parameters derived from MDCT scans with and without IVCM (r up to 0.91) slice thickness of 1 mm versus 2 and 3 mm (r up to 0.96) and scan-rescan (r up to 0.59). The performance of the SVM classifier was evaluated using 10-fold cross-validation and revealed an average classification accuracy of 83%. Opportunistic osteoporosis screening at the spine using specific texture parameters (energy, entropy, and homogeneity) and SVM can be performed in routine contrast-enhanced MDCT exams.

Texture classification of vegetation cover in high altitude wetlands zone

NASA Astrophysics Data System (ADS)

Wentao, Zou; Bingfang, Wu; Hongbo, Ju; Hua, Liu

2014-03-01

The aim of this study was to investigate the utility of datasets composed of texture measures and other features for the classification of vegetation cover, specifically wetlands. QUEST decision tree classifier was applied to a SPOT-5 image sub-scene covering the typical wetlands area in Three River Sources region in Qinghai province, China. The dataset used for the classification comprised of: (1) spectral data and the components of principal component analysis; (2) texture measures derived from pixel basis; (3) DEM and other ancillary data covering the research area. Image textures is an important characteristic of remote sensing images; it can represent spatial variations with spectral brightness in digital numbers. When the spectral information is not enough to separate the different land covers, the texture information can be used to increase the classification accuracy. The texture measures used in this study were calculated from GLCM (Gray level Co-occurrence Matrix); eight frequently used measures were chosen to conduct the classification procedure. The results showed that variance, mean and entropy calculated by GLCM with a 9*9 size window were effective in distinguishing different vegetation types in wetlands zone. The overall accuracy of this method was 84.19% and the Kappa coefficient was 0.8261. The result indicated that the introduction of texture measures can improve the overall accuracy by 12.05% and the overall kappa coefficient by 0.1407 compared with the result using spectral and ancillary data.

Estimation of leaf nitrogen concentration on winter wheat by multispectral imaging

NASA Astrophysics Data System (ADS)

Leemans, Vincent; Marlier, Guillaume; Destain, Marie-France; Dumont, Benjamin; Mercatoris, Benoit

2017-04-01

Precision agriculture can be considered as one of the solutions to optimize agricultural practice such as nitrogen fertilization. Nitrogen deficiency is a major limitation to crop production worldwide whereas excess leads to environmental pollution. In this context, some devices were developed as reflectance spot sensors for on-the-go applications to detect leaves nitrogen concentration deduced from chlorophyll concentration. However, such measurements suffer from interferences with the crop growth stage and the water content of plants. The aim of this contribution is to evaluate the nitrogen status in winter wheat by using multispectral imaging. The proposed system is composed of a CMOS camera and a set of filters ranged from 450 nm to 950 nm and mounted on a wheel which moves due to a stepper motor. To avoid the natural irradiance variability, a white reference is used to adjust the integration time. The segmentation of Photosynthetically Active Leaves is performed by using Bayes theorem to extract their mean reflectance. In order to introduce information related to the canopy architecture, i.e. the crop growth stage, textural attributes are also extracted from raw images at different wavelength ranges. Nc was estimated by partial least squares regression (R² = 0.94). The best attribute was homogeneity extracted from the gray level co-occurrence matrix (R² = 0.91). In order to select in limited number of filters, best subset selection was performed. Nc could be estimated by four filters (450 +/- 40 nm, 500 +/- 20 nm, 650 +/- 40 nm, 800 +/- 50 nm) (R² = 0.91).

Bag-of-features approach for improvement of lung tissue classification in diffuse lung disease

NASA Astrophysics Data System (ADS)

Kato, Noriji; Fukui, Motofumi; Isozaki, Takashi

2009-02-01

Many automated techniques have been proposed to classify diffuse lung disease patterns. Most of the techniques utilize texture analysis approaches with second and higher order statistics, and show successful classification result among various lung tissue patterns. However, the approaches do not work well for the patterns with inhomogeneous texture distribution within a region of interest (ROI), such as reticular and honeycombing patterns, because the statistics can only capture averaged feature over the ROI. In this work, we have introduced the bag-of-features approach to overcome this difficulty. In the approach, texture images are represented as histograms or distributions of a few basic primitives, which are obtained by clustering local image features. The intensity descriptor and the Scale Invariant Feature Transformation (SIFT) descriptor are utilized to extract the local features, which have significant discriminatory power due to their specificity to a particular image class. In contrast, the drawback of the local features is lack of invariance under translation and rotation. We improved the invariance by sampling many local regions so that the distribution of the local features is unchanged. We evaluated the performance of our system in the classification task with 5 image classes (ground glass, reticular, honeycombing, emphysema, and normal) using 1109 ROIs from 211 patients. Our system achieved high classification accuracy of 92.8%, which is superior to that of the conventional system with the gray level co-occurrence matrix (GLCM) feature especially for inhomogeneous texture patterns.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Computer-aided diagnosis of malignant mammograms using Zernike moments and SVM.

PubMed

Sharma, Shubhi; Khanna, Pritee

2015-02-01

This work is directed toward the development of a computer-aided diagnosis (CAD) system to detect abnormalities or suspicious areas in digital mammograms and classify them as malignant or nonmalignant. Original mammogram is preprocessed to separate the breast region from its background. To work on the suspicious area of the breast, region of interest (ROI) patches of a fixed size of 128×128 are extracted from the original large-sized digital mammograms. For training, patches are extracted manually from a preprocessed mammogram. For testing, patches are extracted from a highly dense area identified by clustering technique. For all extracted patches corresponding to a mammogram, Zernike moments of different orders are computed and stored as a feature vector. A support vector machine (SVM) is used to classify extracted ROI patches. The experimental study shows that the use of Zernike moments with order 20 and SVM classifier gives better results among other studies. The proposed system is tested on Image Retrieval In Medical Application (IRMA) reference dataset and Digital Database for Screening Mammography (DDSM) mammogram database. On IRMA reference dataset, it attains 99% sensitivity and 99% specificity, and on DDSM mammogram database, it obtained 97% sensitivity and 96% specificity. To verify the applicability of Zernike moments as a fitting texture descriptor, the performance of the proposed CAD system is compared with the other well-known texture descriptors namely gray-level co-occurrence matrix (GLCM) and discrete cosine transform (DCT).

Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismüller, Axel

2014-02-01

Phase-contrast computed tomography (PCI-CT) has shown tremendous potential as an imaging modality for visualizing human cartilage with high spatial resolution. Previous studies have demonstrated the ability of PCI-CT to visualize (1) structural details of the human patellar cartilage matrix and (2) changes to chondrocyte organization induced by osteoarthritis. This study investigates the use of high-dimensional geometric features in characterizing such chondrocyte patterns in the presence or absence of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and statistical features derived from gray-level co-occurrence matrices were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic curve (AUC). SIM-derived geometrical features exhibited the best classification performance (AUC, 0.95 ± 0.06) and were most robust to changes in ROI size. These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated and non-subjective manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

SU-F-R-45: The Prognostic Value of Radiotherapy Based On the Changes of Texture Features Between Pre-Treatment and Post-Treatment FDG PET Image for NSCLC Patients

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

Ma, C; Yin, Y

Purpose: The purpose of this research is investigating which texture features extracted from FDG-PET images by gray-level co-occurrence matrix(GLCM) have a higher prognostic value than the other texture features. Methods: 21 non-small cell lung cancer(NSCLC) patients were approved in the study. Patients underwent 18F-FDG PET/CT scans with both pre-treatment and post-treatment. Firstly, the tumors were extracted by our house developed software. Secondly, the clinical features including the maximum SUV and tumor volume were extracted by MIM vista software, and texture features including angular second moment, contrast, inverse different moment, entropy and correlation were extracted using MATLAB.The differences can be calculatedmore » by using post-treatment features to subtract pre-treatment features. Finally, the SPSS software was used to get the Pearson correlation coefficients and Spearman rank correlation coefficients between the change ratios of texture features and change ratios of clinical features. Results: The Pearson and Spearman rank correlation coefficient between contrast and SUV maximum is 0.785 and 0.709. The P and S value between inverse difference moment and tumor volume is 0.953 and 0.942. Conclusion: This preliminary study showed that the relationships between different texture features and the same clinical feature are different. Finding the prognostic value of contrast and inverse difference moment were higher than the other three textures extracted by GLCM.« less

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gray water recycle: Effect of pretreatment technologies on low pressure reverse osmosis treatment

USDA-ARS?s Scientific Manuscript database

Gray water can be a valuable source of water when properly treated to reduce the risks associated with chemical and microbial contamination to acceptable levels for the intended reuse application. In this study, the treatment of gray water using low pressure reverse osmosis (RO) filtration after pre...

Discovering multi-scale co-occurrence patterns of asthma and influenza with the Oak Ridge bio-surveillance toolkit

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

Ramanathan, Arvind; Pullum, Laura L.; Hobson, Tanner C.

Here, we describe a data-driven unsupervised machine learning approach to extract geo-temporal co-occurrence patterns of asthma and the flu from large-scale electronic healthcare reimbursement claims (eHRC) datasets. Specifically, we examine the eHRC data from 2009 to 2010 pandemic H1N1 influenza season and analyze whether different geographic regions within the United States (US) showed an increase in co-occurrence patterns of the flu and asthma. Our analyses reveal that the temporal patterns extracted from the eHRC data show a distinct lag time between the peak incidence of the asthma and the flu. While the increased occurrence of asthma contributed to increased flumore » incidence during the pandemic, this co-occurrence is predominant for female patients. The geo-temporal patterns reveal that the co-occurrence of the flu and asthma are typically concentrated within the south-east US. Further, in agreement with previous studies, large urban areas (such as New York, Miami, and Los Angeles) exhibit co-occurrence patterns that suggest a peak incidence of asthma and flu significantly early in the spring and winter seasons. Together, our data-analytic approach, integrated within the Oak Ridge Bio-surveillance Toolkit platform, demonstrates how eHRC data can provide novel insights into co-occurring disease patterns.« less

Discovering multi-scale co-occurrence patterns of asthma and influenza with the Oak Ridge bio-surveillance toolkit

DOE PAGES

Ramanathan, Arvind; Pullum, Laura L.; Hobson, Tanner C.; ...

2015-08-03

Here, we describe a data-driven unsupervised machine learning approach to extract geo-temporal co-occurrence patterns of asthma and the flu from large-scale electronic healthcare reimbursement claims (eHRC) datasets. Specifically, we examine the eHRC data from 2009 to 2010 pandemic H1N1 influenza season and analyze whether different geographic regions within the United States (US) showed an increase in co-occurrence patterns of the flu and asthma. Our analyses reveal that the temporal patterns extracted from the eHRC data show a distinct lag time between the peak incidence of the asthma and the flu. While the increased occurrence of asthma contributed to increased flumore » incidence during the pandemic, this co-occurrence is predominant for female patients. The geo-temporal patterns reveal that the co-occurrence of the flu and asthma are typically concentrated within the south-east US. Further, in agreement with previous studies, large urban areas (such as New York, Miami, and Los Angeles) exhibit co-occurrence patterns that suggest a peak incidence of asthma and flu significantly early in the spring and winter seasons. Together, our data-analytic approach, integrated within the Oak Ridge Bio-surveillance Toolkit platform, demonstrates how eHRC data can provide novel insights into co-occurring disease patterns.« less

Age, Stress, and Emotional Complexity: Results from Two Studies of Daily Experiences

PubMed Central

Scott, Stacey B.; Sliwinski, Martin J.; Mogle, Jacqueline A.; Almeida, David M.

2014-01-01

Experiencing positive and negative emotions together (i.e., co-occurrence) has been described as a marker of positive adaptation during stress and a strength of socio-emotional aging. Using data from daily diary (N=2,022; ages 33-84) and ecological momentary assessment (N=190; ages 20-80) studies, we evaluate the utility of a common operationalization of co-occurrence, the within-person correlation between positive affect (PA) and negative affect (NA). Then we test competing predictions regarding when co-occurrence will be observed and whether age differences will be present. Results indicate that the correlation is not an informative indicator of co-occurrence. Although correlations were stronger and more negative when stressors occurred (typically interpreted as lower co-occurrence), objective counts of emotion reports indicated that positive and negative emotions were more 3 to 4 times likely to co-occur when stressors were reported. This suggests that co-occurrence reflects the extent to which negative emotions intrude on typically positive emotional states, rather than the extent to which people maintain positive emotions during stress. The variances of both PA and NA increased at stressor reports, indicating that individuals reported a broader not narrower range of emotion during stress. Finally, older age was associated with less variability in NA and a lower likelihood of co-occurring positive and negative emotions. In sum, these findings cast doubt on the utility of the PA-NA correlation as an index of emotional co-occurrence, and question notion that greater emotional cooccurrence represents either a typical or adaptive emotional state in adults. PMID:25244477

Late Quaternary sediment deposition of core MA01 in the Mendeleev Ridge, the western Arctic Ocean: Preliminary results

NASA Astrophysics Data System (ADS)

Park, Kwang-Kyu; Kim, Sunghan; Khim, Boo-Keun; Xiao, Wenshen; Wang, Rujian

2014-05-01

Late Quaternary deep marine sediments in the Arctic Ocean are characterized by brown layers intercalated with yellowish to olive gray layers (Poore et al., 1999; Polyak et al., 2004). Previous studies reported that the brown and gray layers were deposited during interglacial (or interstadial) and glacial (or stadial) periods, respectively. A 5.5-m long gravity core MA01 was obtained from the Mendeleev Ridge in the western Arctic Ocean by R/V Xue Long during scientific cruise CHINARE-V. Age (~450 ka) of core MA01 was tentatively estimated by correlation of brown layers with an adjacent core HLY0503-8JPC (Adler et al., 2009). A total of 22 brown layers characterized by low L* and b*, high Mn concentration, and abundant foraminifera were identified. Corresponding gray layers are characterized by high L* and b*, low Mn concentration, and few foraminiferal tests. Foraminifera abundance peaks are not well correlated to CaCO3 peaks which occurred with the coarse-grained (>0.063 mm) fractions (i.e., IRD) both in brown and gray layers. IRDs are transported presumably by sea ice for the deposition of brown layers and by iceberg for the deposition of gray layers (Polyak et al., 2004). A strong correlation coefficient (r2=0.89) between TOC content and C/N ratio indicates that the major source of organic matter is terrestrial. The good correlations of CaCO3 content to TOC (r2=0.56) and C/N ratio (r2=0.69) imply that IRDs contain detrital CaCO3 which mainly originated from the Canadian Arctic Archipelago. In addition, high kaolinite/chlorite (K/C) ratios mostly correspond to CaCO3 peaks, which suggests that the fine-grained particles in the Mendeleev Ridge are transported from the north coast Alaska and Canada where Mesozoic and Cenozoic strata are widely distributed. Thus, the Beaufort Gyre, the predominant surface current in the western Arctic Ocean, played an important role in the sediment delivery to the Mendeleev Ridge. It is worthy of note that the TOC and CaCO3 peaks are obviously distinct in the upper part of core MA01, whereas these peaks are reduced in the lower part of the core. More study on these contrasting features is in progress. References Adler, R.E., Polyak, L., Ortiz, J.D., Kaufman, D.S., Channell, J.E.T., Xuan, C., Grottoli, A.G., Sellén, E., and Crawford, K.A., 2009. Global and Planetary Change 68(1-2), 18-29. Polyak, L., Curry, W.B., Darby, D.A., Bischof, J., and Cronin, T.M., 2004. Palaeogeography, Palaeoclimatology, Palaeoecology 203, 73-93. Poore, R., Osterman, L., Curry, W., and Phillips, R., 1999. Geology 27, 759-762.

Serum creatine kinase (CK) activity following exposure to cadmium and/or /sup 60/CO gamma irradiation

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

Morgan, R.M.; Kundomal, Y.R.; Hupp, E.W.

1985-01-01

Two hundred and sixteen young adult male Sprague-Dawley rats were injected IP every 3 days for 29 days for a total of 9 injections with 0, 1.0, or 2.5 mg CdCl/sub 2//kg body weight. Total cumulative doses were 0, 9.0 or 22.5 mg CdCl/sub 2//kg body weight. Twenty-four hours after the last cadmium injection (day 30), each rat was irradiated with a total-body exposure of 0, 3.62, or 5.43 Gray of gamma (/sup 60/Co) radiation at a dose rate of 3.04 Gray/min. Eight rats from each of the 9 groups were sacrificed on day 1, 7, or 21. Highest levelsmore » of the creatine kinase enzyme were seen in radiation groups at day 1, indicating an immediate radiotoxic response. Enzyme levels decreased through day 21 indicating clearance of the enzyme from the plasma. Although statistically significant differences between the groups, cadmium, radiation, or days were not seen, cadmium did protect against radiation. This protective function is not explainable; however, it is speculated that different conformations of metal-induced metallothionein clusters exist to accommodate various metal ions. Further, that each kind of metal ion may have different and unique distribution patterns between the cluster centers which account for different functions.« less

Physical activity and inflammation: effects on gray-matter volume and cognitive decline in aging.

PubMed

Papenberg, Goran; Ferencz, Beata; Mangialasche, Francesca; Mecocci, Patrizia; Cecchetti, Roberta; Kalpouzos, Grégoria; Fratiglioni, Laura; Bäckman, Lars

2016-10-01

Physical activity has been positively associated with gray-matter integrity. In contrast, pro-inflammatory cytokines seem to have negative effects on the aging brain and have been related to dementia. It was investigated whether an inactive lifestyle and high levels of inflammation resulted in smaller gray-matter volumes and predicted cognitive decline across 6 years in a population-based study of older adults (n = 414). Self-reported physical activity (fitness-enhancing, health-enhancing, inadequate) was linked to gray-matter volume, such that individuals with inadequate physical activity had the least gray matter. There were no overall associations between different pro-and anti-inflammatory markers (IL-1β, IL-6, IL-10, IL-12p40, IL-12p70, G-CSF, and TNF-α) and gray-matter integrity. However, persons with inadequate activity and high levels of the pro-inflammatory marker IL-12p40 had smaller volumes of lateral prefrontal cortex and hippocampus and declined more on the Mini-Mental State Examination test over 6 years compared with physically inactive individuals with low levels of IL-12p40 and to more physically active persons, irrespective of their levels of IL-12p40. These patterns of data suggested that inflammation was particularly detrimental in inactive older adults and may exacerbate the negative effects of physical inactivity on brain and cognition in old age. Hum Brain Mapp 37:3462-3473, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A new species of Gulo from the Early Pliocene Gray Fossil Site (Eastern United States); rethinking the evolution of wolverines

PubMed Central

Bredehoeft, Keila E.; Wallace, Steven C.

2018-01-01

The wolverine (Gulo gulo) is the largest living terrestrial member of the Mustelidae; a versatile predator formerly distributed throughout boreal regions of North America and Eurasia. Though commonly recovered from Pleistocene sites across their range, pre-Pleistocene records of the genus are exceedingly rare. Here, we describe a new species of Gulo from the Gray Fossil Site in Tennessee. Based on biostratigraphy, a revised estimate of the age of the Gray Fossil Site is Early Pliocene, near the Hemphillian—Blancan transition, between 4.9 and 4.5 Ma. This represents the earliest known occurrence of a wolverine, more than one million years earlier than any other record. The new species of wolverine described here shares similarities with previously described species of Gulo, and with early fishers (Pekania). As the earliest records of both Gulo and Pekania are known from North America, this suggests the genus may have evolved in North America and dispersed to Eurasia later in the Pliocene. Both fauna and flora at the Gray Fossil Site are characteristic of warm/humid climates, which suggests wolverines may have become ‘cold-adapted’ relatively recently. Finally, detailed comparison indicates Plesiogulo, which has often been suggested to be ancestral to Gulo, is not likely closely related to gulonines, and instead may represent convergence on a similar niche. PMID:29682423

A survey of the awareness, knowledge and behavior of hair dye use in a korean population with gray hair.

PubMed

Kim, Jung Eun; Jung, Hee Dam; Kang, Hoon

2012-08-01

Gray hair naturally develops in the process of human aging. Many people with gray hair periodically dye their hair. Hair dyeing products are widely used and they can cause adverse effects. Therefore, the user's knowledge and recognition about hair dyeing and related side effects are important. The goal of this study was to lay the foundation for understanding, preventing and treating side effects caused by hair coloring products. We conducted a questionnaire survey for adult males and females aged over 20 who had gray hair. A total of 500 subjects were included in this study and statistical analysis was performed. Large numbers of the people who had experience with hair dye (233 out of 319 people, 73.0%) did not know about the exact brand name of the hair dye product that they were using. Of 319 hair dye users, 23.8% (76 out of 319) people stated that they experienced side effects. Despite the occurrence of side effects from hair dyeing products, it seems they did not realize the seriousness of the side effects or the need for treatment. It is advisable to introduce a system that enables users to become aware of the ingredients and side effects of hair coloring products and give opportunities for users to become aware of the side effects of hair coloring through education, publicity and publication of an informational booklet.

Patterns of volcanism, weathering, and climate history from high-resolution geochemistry of the BINGO core, Mono Lake, California, USA

NASA Astrophysics Data System (ADS)

Zimmerman, S. R.; Starratt, S.; Hemming, S. R.

2012-12-01

Mono Lake, California is a closed-basin lake on the east side of the Sierra Nevada, and inflow from snowmelt dominates the modern hydrology. Changes in wetness during the last glacial period (>12,000 years ago) and over the last 2,000 years have been extensively described, but are poorly known for the intervening period. We have recovered a 6.25 m-long core from ~3 m of water in the western embayment of Mono Lake, which is shown by initial radiocarbon dates to cover at least the last 10,000 years. The sediments of the core are variable, ranging from black to gray silts near the base, laminated olive-green silt through the center, to layers of peach-colored carbonate nodules interbedded with gray and olive silts and pea-green organic ooze. Volcanic tephras from <1 to 8 cm thick occur throughout. Results of 0.5 cm-resolution scanning-X-Ray fluoresence (XRF) analysis describe changes in lithology due to volcanism, erosion, and changing lake level and chemistry. Titanium (Ti) is chemically and biologically unreactive, and records the dominant input, from weathering of Sierra Nevada granite to the west and Miocene and Pliocene volcanic rocks of the Bodie and Adobe Hills to the north, east, and south. The rhyolitic tephras of the Mono-Inyo Craters are much lower in TiO2 than the bedrock (<0.1% vs. 1-2%), and are an unweathered source of K2O (3.5-5%), and thus form dramatic peaks in the K/Ti ratio. Calcium (Ca) and Sr are well correlated throughout the core, and normalization of both by K (detritus + tephra) corresponds with occurrence of carbonate-rich layers. These are a mixture of authigenic precipitates directly precipitated and eroded into the lake during periods of regression. The lowermost 1.5 m of the BINGO core contains the highest proportion of detrital input to Mono Lake over the last ~12,000 years, recorded by high Si, Ti, K, and Fe, in black to dark-gray, fine-grained silts above 10 cm of pure light gray silt. Based on radiocarbon dates of >10,000 calibrated years before present (cal yr BP) higher in the core, and significant disruption of the fine layers, this interval likely indicates a relatively deep lake persisting into the early Holocene, after the initial dramatic regression from late Pleistocene levels. The finely laminated olive-green silt of the period ~10,700 to ~7500 cal yr BP is very homogenous chemically, probably indicating a stable, stratified lake and a relatively wet climate. This section merits mm-scale scanning and petrographic examination in the future. The upper boundary of the laminated section shows rising Ca/K and decreasing Ti and Si/K, marking the appearance of authigenic carbonate layers. After ~7500 cal yr BP, the sediment in BINGO becomes highly variable, with increased occurrence of tephra layers and carbonate, indicating a lower and more variable lake level. A short interval of olive-green, laminated fine sand/silt just above a radiocarbon date of 3870 ± 360 cal yr BP may record the Dechambeau Ranch highstand of Stine (1990; PPP v. 78 pp 333-381), and is marked by a distinct low in Ca/K, lasting ~1000 years. The low terminates in a dramatic rise in Ca/K to some of the highest levels in the core, suggesting a period of ~1000 years of extremely dry climate, dwarfing all of the variability in Ca/K, and likely lake level, over the last 2000 years.

Individual, school-related and family characteristics distinguish co-occurrence of drinking and depressive symptoms in very young adolescents.

PubMed

Salom, Caroline L; Kelly, Adrian B; Alati, Rosa; Williams, Gail M; Patton, George C; Williams, Joanne W

2016-07-01

Alcohol misuse and depressed mood are common during early adolescence, and comorbidity of these conditions in adulthood is associated with poorer health and social outcomes, yet little research has examined the co-occurrence of these problems at early adolescence. This study assessed risky and protective characteristics of pre-teens with concurrent depressed mood/early alcohol use in a large school-based sample. School children aged 10-14 years (n = 7289) from late primary and early secondary school classes in government, Catholic and independent sectors participated with parental consent in the cross-sectional Healthy Neighbourhoods Study. Key measures included depressed mood, recent alcohol use, school mobility, family relationship quality, school engagement and coping style. Multinomial logistic regression analyses were used to identify school and family-related factors that distinguished those with co-occurring drinking and depressive symptoms from those with either single condition. Gender and school-level interactions for each factor were evaluated. Co-occurring conditions were reported by 5.7% of students [confidence interval (CI)95 5.19, 6.19]. Recent drinkers were more likely than non-drinkers to have symptoms consistent with depression (odds ratio 1.80; CI95 1.58, 2.03). Low school commitment was associated with co-occurring drinking/depressive symptoms (odds ratio 2.86; CI95 2.25, 3.65 compared with null condition). This association appeared to be weaker in the presence of adaptive stress-coping skills (odds ratio 0.18; CI95 0.14, 0.23). We have identified factors that distinguish pre-teens with very early co-occurrence of drinking and depressed mood, and protective factors with potential utility for school-based prevention programmes targeting these conditions. [Salom CL, Kelly AB, Alati R, Williams GM, Patton GC, Williams JW. Individual, school-related and family characteristics distinguish co-occurrence of drinking and depressive symptoms in very young adolescents. Drug Alcohol Rev 2016;35:387-396]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

SU-E-I-91: Quantitative Assessment of Early Hepatocellular Carcinoma and Cavernous Hemangioma of Live Using In-Line Phase-Contrast X-Ray Imaging

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

Duan, J

Purpose: To investigate the potential utility of in-line phase-contrast imaging (ILPCI) technique with synchrotron radiation in detecting early hepatocellular carcinoma and cavernous hemangioma of live using in vitro model system. Methods: Without contrast agents, three typical early hepatocellular carcinoma specimens and three typical cavernous hemangioma of live specimens were imaged using ILPCI. To quantitatively discriminate early hepatocellular carcinoma tissues and cavernous hemangioma tissues, the projection images texture feature based on gray level co-occurrence matrix (GLCM) were extracted. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, difference average, difference entropy and inverse difference moment, were obtained respectively.more » Results: In the ILPCI planar images of early hepatocellular carcinoma specimens, vessel trees were clearly visualized on the micrometer scale. Obvious distortion deformation was presented, and the vessel mostly appeared as a ‘dry stick’. Liver textures appeared not regularly. In the ILPCI planar images of cavernous hemangioma of live specimens, typical vessels had not been found compared with the early hepatocellular carcinoma planar images. The planar images of cavernous hemangioma of live specimens clearly displayed the dilated hepatic sinusoids with the diameter of less than 100 microns, but all of them were overlapped with each other. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, and difference average, showed a statistically significant between the two types specimens image (P<0.01), except the texture parameters of difference entropy and inverse difference moment(P>0.01). Conclusion: The results indicate that there are obvious changes in morphological levels including vessel structures and liver textures. The study proves that this imaging technique has a potential value in evaluating early hepatocellular carcinoma and cavernous hemangioma of live.« less

Inferring species roles in metacommunity structure from species co-occurrence networks

PubMed Central

Borthagaray, Ana I.; Arim, Matías; Marquet, Pablo A.

2014-01-01

A long-standing question in community ecology is what determines the identity of species that coexist across local communities or metacommunity assembly. To shed light upon this question, we used a network approach to analyse the drivers of species co-occurrence patterns. In particular, we focus on the potential roles of body size and trophic status as determinants of metacommunity cohesion because of their link to resource use and dispersal ability. Small-sized individuals at low-trophic levels, and with limited dispersal potential, are expected to form highly linked subgroups, whereas large-size individuals at higher trophic positions, and with good dispersal potential, will foster the spatial coupling of subgroups and the cohesion of the whole metacommunity. By using modularity analysis, we identified six modules of species with similar responses to ecological conditions and high co-occurrence across local communities. Most species either co-occur with species from a single module or are connectors of the whole network. Among the latter are carnivorous species of intermediate body size, which by virtue of their high incidence provide connectivity to otherwise isolated communities playing the role of spatial couplers. Our study also demonstrates that the incorporation of network tools to the analysis of metacommunity ecology can help unveil the mechanisms underlying patterns and processes in metacommunity assembly. PMID:25143039

Co-occurrence and clustering of health conditions at age 11: cross-sectional findings from the Millennium Cohort Study

PubMed Central

Hesketh, Kathryn R; Fagg, James; Muniz-Terrera, Graciela; Law, Catherine; Hope, Steven

2016-01-01

Objectives To identify patterns of co-occurrence and clustering of 6 common adverse health conditions in 11-year-old children and explore differences by sociodemographic factors. Design Nationally representative prospective cohort study. Setting Children born in the UK between 2000 and 2002. Participants 11 399 11-year-old singleton children for whom data on all 6 health conditions and sociodemographic information were available (complete cases). Main outcome measures Prevalence, co-occurrence and clustering of 6 common health conditions: wheeze; eczema; long-standing illness (excluding wheeze and eczema); injury; socioemotional difficulties (measured using Strengths and Difficulties Questionnaire) and unfavourable weight (thin/overweight/obese vs normal). Results 42.4% of children had 2 or more adverse health conditions (co-occurrence). Co-occurrence was more common in boys and children from lower income households. Latent class analysis identified 6 classes: ‘normative’ (57.4%): ‘atopic burdened’ (14.0%); ‘socioemotional burdened’ (11.0%); ‘unfavourable weight/injury’ (7.7%); ‘eczema/injury’ (6.0%) and ‘eczema/unfavourable weight’ (3.9%). As with co-occurrence, class membership differed by sociodemographic factors: boys, children of mothers with lower educational attainment and children from lower income households were more likely to be in the ‘socioemotional burdened’ class. Children of mothers with higher educational attainment were more likely to be in the ‘normative’ and ‘eczema/unfavourable weight’ classes. Conclusions Co-occurrence of adverse health conditions at age 11 is common and is associated with adverse socioeconomic circumstances. Holistic, child focused care, particularly in boys and those in lower income groups, may help to prevent and reduce co-occurrence in later childhood and adolescence. PMID:27881529

The Collaborative Longitudinal Personality Disorders Study: baseline Axis I/II and II/II diagnostic co-occurrence.

PubMed

McGlashan, T H; Grilo, C M; Skodol, A E; Gunderson, J G; Shea, M T; Morey, L C; Zanarini, M C; Stout, R L

2000-10-01

To describe baseline diagnostic co-occurrence in the Collaborative Longitudinal Personality Disorders Study. Six hundred and sixty-eight patients were reliably assessed with diagnostic interviews for DSM-IV Axis I and II disorders to create five groups: Schizotypal (STPD), Borderline (BPD), Avoidant (AVPD), Obsessive-Compulsive (OCPD) and Major Depressive Disorder (MDD) without personality disorder (PD). Mean number of Axis I lifetime diagnoses was 3.4; STPD and BPD groups had more diagnoses than AVPD, OCPD, and MDD groups. Significant Axis I co-occurrences emerged for Social Phobia/ AVPD, PTSD/BPD and Substance Use/BPD. Mean number of co-occurring PDs was 1.4; STPD had more than BPD group which had more than AVPD and OCPD groups. Significant PD co-occurrence emerged for: STPD/ Paranoid and Schizoid PDs, BPD with Antisocial and Dependent PDs, and lower frequency for OCPD/Antisocial PD. Diagnostic co-occurrences generally followed base rates, while significant departures resemble those of controlled literature.

Pathological worry, anxiety disorders and the impact of co-occurrence with depressive and other anxiety disorders.

PubMed

Starcevic, Vladan; Berle, David; Milicevic, Denise; Hannan, Anthony; Lamplugh, Claire; Eslick, Guy D

2007-01-01

The Penn State Worry Questionnaire (PSWQ) was administered to 123 outpatients with principal diagnoses of generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder with agoraphobia, and panic disorder without agoraphobia (PD) to examine the specificity of pathological worry for GAD. The mean PSWQ scores in patients with GAD and SAD were significantly higher than the mean PSWQ scores in patients with PD, while not differing significantly in the subgroups without any co-occurring depressive or anxiety disorders. Patients with any co-occurring depressive or anxiety disorder scored significantly higher on the PSWQ. In a logistic regression analysis, high PSWQ scores independently predicted only GAD and SAD diagnoses. The study suggests that pathological worry is specific not only for GAD, and indicates that a significant relationship exists between pathological worry, GAD and SAD, and that depressive and anxiety disorders co-occurrence increases levels of pathological worry in patients with anxiety disorders.

Effect of Contrasting Trophic Conditions on the Priming Effect in Gray Forest Soils

NASA Astrophysics Data System (ADS)

Zhuravleva, A. I.; Alifanov, V. M.; Blagodatskaya, E. V.

2018-02-01

Priming effects initiated by the addition of 14C glucose have been compared for humus horizons of soils existing under continuous input of fresh organic substrates and for buried soil horizons, in which entering of organic matter has been essentially limited. The effect of microrelief on the manifestation of priming effect in the humus horizons of gray forest soil on microhigh and in microlow has been estimated. Humus horizon in soils on microhigh, not activated by glucose, produced two times more CO2 in comparison with soils of microlow. However, the introduction of glucose canceled the effect of microrelief on CO2 emission. The intensity of absolute priming effect correlated with the Corg pool, initial microbial biomass, and enzyme activity, decreasing from humus horizons to the buried ones, and did not depend on microrelief. The effect of microrelief was observed, when assessing the priming effect relative to control (soil not activated by glucose): the value of relative priming effect was 1.5 times greater in A horizon of gray forest soil in microlow in comparison with that on microhigh being the result of increasing activity of enzymes.

A Network-Based Method to Assess the Statistical Significance of Mild Co-Regulation Effects

PubMed Central

Horvát, Emőke-Ágnes; Zhang, Jitao David; Uhlmann, Stefan; Sahin, Özgür; Zweig, Katharina Anna

2013-01-01

Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis. PMID:24039936

Berkeley Lab Scientist Co-Leads Breast Cancer Dream Team

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

Gray, Joe

2009-05-19

An $16.5 million, three-year grant to develop new and more effective therapies to fight breast cancer was awarded today to a multi-institutional Dream Team of scientists and clinicians that is co-led by Joe Gray, a renowned cancer researcher with the U.S. Department of Energys Lawrence Berkeley National Laboratory. http://newscenter.lbl.gov/

Berkeley Lab Scientist Co-Leads Breast Cancer Dream Team

ScienceCinema

Gray, Joe

2017-12-27

An $16.5 million, three-year grant to develop new and more effective therapies to fight breast cancer was awarded today to a multi-institutional Dream Team of scientists and clinicians that is co-led by Joe Gray, a renowned cancer researcher with the U.S. Department of Energys Lawrence Berkeley National Laboratory. http://newscenter.lbl.gov/

Co-occurrence of alcohol use disorder and behavioral addictions: relevance of impulsivity and craving.

PubMed

Di Nicola, Marco; Tedeschi, Daniela; De Risio, Luisa; Pettorruso, Mauro; Martinotti, Giovanni; Ruggeri, Filippo; Swierkosz-Lenart, Kevin; Guglielmo, Riccardo; Callea, Antonino; Ruggeri, Giuseppe; Pozzi, Gino; Di Giannantonio, Massimo; Janiri, Luigi

2015-03-01

The aims of the study were to evaluate the occurrence of behavioral addictions (BAs) in alcohol use disorder (AUD) subjects and to investigate the role of impulsivity, personality dimensions and craving. 95 AUD outpatients (DSM-5) and 140 homogeneous controls were assessed with diagnostic criteria and specific tests for gambling disorder, compulsive buying, sexual, internet and physical exercise addictions, as well as with the Barratt Impulsiveness Scale (BIS-11) and Temperamental and Character Inventory-Revised (TCI-R). The Obsessive Compulsive Drinking Scale (OCDS) and Visual Analogue Scale for craving (VASc) were also administered to the AUD sample. 28.4% (n=27) of AUD subjects had at least one BA, as compared to 15% (n=21) of controls (χ(2)=6.27; p=.014). In AUD subjects, direct correlations between BIS-11 and Compulsive Buying Scale (CBS), Internet Addiction Disorder test (IAD), Exercise Addiction Inventory-Short Form (EAI-SF) scores (p<.01), between OCDS obsessive and CBS and VASc and CBS, IAD scores (p<.003), were found. BIS-11 (t=-2.36; p=.020), OCDS obsessive (Z=-4.13; p<.001), OCDS compulsive (Z=-2.12; p=.034) and VASc (Z=-4.94; p<.001) scores were higher in AUD subjects with co-occurring BAs. The occurrence of BAs was associated with higher impulsivity traits (BIS-11 scores; OR=1.08; p=.012) and higher craving levels (VASc scores; OR=2.48; p<.001). Our findings emphasize a significant rate of co-occurrence of BAs in AUD. High levels of impulsivity and craving for alcohol seem to be associated with other addictive behaviors. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Skeletonization of gray-scale images by gray weighted distance transform

NASA Astrophysics Data System (ADS)

Qian, Kai; Cao, Siqi; Bhattacharya, Prabir

1997-07-01

In pattern recognition, thinning algorithms are often a useful tool to represent a digital pattern by means of a skeletonized image, consisting of a set of one-pixel-width lines that highlight the significant features interest in applying thinning directly to gray-scale images, motivated by the desire of processing images characterized by meaningful information distributed over different levels of gray intensity. In this paper, a new algorithm is presented which can skeletonize both black-white and gray pictures. This algorithm is based on the gray distance transformation and can be used to process any non-well uniformly distributed gray-scale picture and can preserve the topology of original picture. This process includes a preliminary phase of investigation in the 'hollows' in the gray-scale image; these hollows are considered not as topological constrains for the skeleton structure depending on their statistically significant depth. This algorithm can also be executed on a parallel machine as all the operations are executed in local. Some examples are discussed to illustrate the algorithm.

Occurrence of Indoor VOCs in Nursery School - Case Study

NASA Astrophysics Data System (ADS)

Juhasova Senitkova, Ingrid

2017-10-01

Children’s exposure to air pollutants is an important public health challenge. Particular attention should be paid to preschools because younger children are more vulnerable to air pollution than higher grade children and spend more time indoors. The concentrations of volatile organic compounds (VOCs) as well as carbon dioxide (CO2) concentrations in younger and older children’s classrooms during the winter season were studied. An electronic nose based on gas chromatography was used for the analysis of individual VOCs and a photoionization detector with a UV lamp was used for the determination of total volatile organic compounds (TVOC) concentration. Continuous measurements of CO2 concentrations both inside classrooms and outside each building were performed using automatic portable monitors. Improving ventilation, decreasing the occupancy per room and completing cleaning activities following occupancy periods can contribute to alleviating high CO2 and VOCs occurrence levels.

2006 Progress Report on Acoustic and Visual Monitoring for Cetaceans along the Outer Washington Coast

DTIC Science & Technology

2007-08-01

Although Northern Resident killer whales have been extensively studied within Puget Sound and coastal British Columbia, they have been visually sighted... whales . Time series of vocalizations detected in acoustic recordings are presented for killer whales , white-sided dolphins, Risso’s dolphins...Pinniped sightings during visual surveys since August 2004. Seasonal occurrence of humpback and gray whales from visual surveys. Killer whale

Technical Note: Gray tracking in medical color displays-A report of Task Group 196.

PubMed

Badano, Aldo; Wang, Joel; Boynton, Paul; Le Callet, Patrick; Cheng, Wei-Chung; Deroo, Danny; Flynn, Michael J; Matsui, Takashi; Penczek, John; Revie, Craig; Samei, Ehsan; Steven, Peter M; Swiderski, Stan; Van Hoey, Gert; Yamaguchi, Matsuhiro; Hasegawa, Mikio; Nagy, Balázs Vince

2016-07-01

The authors discuss measurement methods and instrumentation useful for the characterization of the gray tracking performance of medical color monitors for diagnostic applications. The authors define gray tracking as the variability in the chromaticity of the gray levels in a color monitor. The authors present data regarding the capability of color measurement instruments with respect to their abilities to measure a target white point corresponding to the CIE Standard Illuminant D65 at different luminance values within the grayscale palette of a medical display. The authors then discuss evidence of significant differences in performance among color measurement instruments currently available for medical physicists to perform calibrations and image quality checks for the consistent representation of color in medical displays. In addition, the authors introduce two metrics for quantifying grayscale chromaticity consistency of gray tracking. The authors' findings show that there is an order of magnitude difference in the accuracy of field and reference instruments. The gray tracking metrics quantify how close the grayscale chromaticity is to the chromaticity of the full white point (equal amounts of red, green, and blue at maximum level) or to consecutive levels (equal values for red, green, and blue), with a lower value representing an improved grayscale tracking performance. An illustrative example of how to calculate and report the gray tracking performance according to the Task Group definitions is provided. The authors' proposed methodology for characterizing the grayscale degradation in chromaticity for color monitors that can be used to establish standards and procedures aiding in the quality control testing of color displays and color measurement instrumentation.

Statistics of co-occurring keywords in confined text messages on Twitter

NASA Astrophysics Data System (ADS)

Mathiesen, J.; Angheluta, L.; Jensen, M. H.

2014-09-01

Online social media such as the micro-blogging site Twitter has become a rich source of real-time data on online human behaviors. Here we analyze the occurrence and co-occurrence frequency of keywords in user posts on Twitter. From the occurrence rate of major international brand names, we provide examples of predictions of brand-user behaviors. From the co-occurrence rates, we further analyze the user-perceived relationships between international brand names and construct the corresponding relationship networks. In general the user activity on Twitter is highly intermittent and we show that the occurrence rate of brand names forms a highly correlated time signal.

An Integrative Account of Constraints on Cross-Situational Learning

PubMed Central

Yurovsky, Daniel; Frank, Michael C.

2015-01-01

Word-object co-occurrence statistics are a powerful information source for vocabulary learning, but there is considerable debate about how learners actually use them. While some theories hold that learners accumulate graded, statistical evidence about multiple referents for each word, others suggest that they track only a single candidate referent. In two large-scale experiments, we show that neither account is sufficient: Cross-situational learning involves elements of both. Further, the empirical data are captured by a computational model that formalizes how memory and attention interact with co-occurrence tracking. Together, the data and model unify opposing positions in a complex debate and underscore the value of understanding the interaction between computational and algorithmic levels of explanation. PMID:26302052

Ultrasonographic evaluation of equine tendons: a quantitative in vitro study of the effects of amplifier gain level, transducer-tilt, and transducer-displacement.

PubMed

van Schie, J T; Bakker, E M; van Weeren, P R

1999-01-01

The objective of the in vitro experiments described in this paper was to quantify the effects of some instrumental variables on the quantitative evaluation, by means of first-order gray-level statistics, of ultrasonographic images of equine tendons. The experiments were done on three isolated equine superficial digital flexor tendons that were mounted in a frame and submerged in a waterbath. Sections with either normal tendon tissue, an acute lesion, or a chronic scar, were selected. In these sections, the following experiments were done: 1) a gradual increase of total amplifier gain output subdivided in 12 equal steps; 2) a transducer tilt plus or minus 3 degrees from perpendicular, with steps of 1 degree; and 3) a transducer displacement along, and perpendicular to, the tendon long axis, with 16 steps of 0.25 mm each. Transverse ultrasonographic images were collected, and in the regions of interest (ROI) first-order gray-level statistics were calculated to quantify the effects of each experiment. Some important observations were: 1) the total amplifier gain output has a substantial influence on the ultrasonographic image; for example, in the case of an acute lesion, a low gain setting results in an almost completely black image; whereas, with higher gain settings, a marked "filling in" effect on the lesion can be observed; 2) the relative effects of the tilting of the transducer are substantial in normal tendon tissue (18%) and chronic scar (12%); whereas, in the event of an acute lesion, the effects on the mean gray level are dramatic (40%); and 3) the relative effects of displacement of the transducer are small in normal tendon tissue, but on the other hand, the mean gray-level changes 7% in chronic scar, and even 20% in an acute lesion. In general, slight variations in scanner settings and transducer handling can have considerable effects on the gray levels of the ultrasonographic image. Furthermore, there is a strong indication that this quantitative method, as far as based exclusively on the first-order gray-level statistics, may be not discriminative enough to accurately assess the integrity of the tendon. Therefore, the value of a quantitative evaluation of the first-order gray-level statistics for the assessment of the integrity of the equine tendon is questionable.

Mapping invasive Fallopia japonica by combined spectral, spatial, and temporal analysis of digital orthophotos

NASA Astrophysics Data System (ADS)

Dorigo, Wouter; Lucieer, Arko; Podobnikar, Tomaž; Čarni, Andraž

2012-10-01

Japanese knotweed (Fallopia japonica) is listed among 100 of the World's worst invasive alien species and poses an increasing threat to ecosystems and agriculture in Northern America, Europe, and Oceania. This study proposes a remote sensing method to detect local occurrences of F. japonica from low-cost digital orthophotos taken in early spring and summer by concurrently exploring its temporal, spectral, and spatial characteristics. Temporal characteristics of the species are quantified by a band ratio calculated from the green and red spectral channels of both images. The normalized difference vegetation index was used to capture the high near-infrared (NIR) reflectance of F. japonica in summer while the characteristic texture of F. japonica is quantified by calculating gray level co-occurrence matrix (GLCM) measures. After establishing the optimum kernel size to quantify texture, the different input features (spectral, spatial, and texture) were stacked and used as input to the random forest (RF) classifier. The proposed method was tested for a built-up and semi-natural area in Slovenia. The spectral, spatial, and temporal provided an equally important contribution for differentiating F. japonica from other land cover types. The combination of all signatures resulted in a producer accuracy of 90.3% and a user accuracy of 98.1% for F. japonica when validation was based on independent regions of interest. A producer accuracy of 61.4% was obtained for F. japonica when comparing the classification result with all occurrences of F. japonica identified during a field validation campaign. This is an encouraging result given the very small patches in which the species usually occur and the high degree of intermingling with other plants. All hot spots were identified and even likely infestations of F. japonica that had remained undiscovered during the field campaign were detected. The probability images resulting from the RF classifier can be used to reduce the relatively large number of false alarms and may assist in targeted eradication measures. Classification skill only slightly reduced when NIR information was not considered, which is an important recognition with regard to transferability of the method to the most basic type of digital color orthophotos. The possibility to use orthophotos, which at most municipalities are commonly available and easily accessible, facilitates an immediate implementation of the approach in situations where intervention is urgent.

Physical activity, fitness, glucose homeostasis, and brain morphology in twins.

PubMed

Rottensteiner, Mirva; Leskinen, Tuija; Niskanen, Eini; Aaltonen, Sari; Mutikainen, Sara; Wikgren, Jan; Heikkilä, Kauko; Kovanen, Vuokko; Kainulainen, Heikki; Kaprio, Jaakko; Tarkka, Ina M; Kujala, Urho M

2015-03-01

The main aim of the present study (FITFATTWIN) was to investigate how physical activity level is associated with body composition, glucose homeostasis, and brain morphology in young adult male monozygotic twin pairs discordant for physical activity. From a population-based twin cohort, we systematically selected 10 young adult male monozygotic twin pairs (age range, 32-36 yr) discordant for leisure time physical activity during the past 3 yr. On the basis of interviews, we calculated a mean sum index for leisure time and commuting activity during the past 3 yr (3-yr LTMET index expressed as MET-hours per day). We conducted extensive measurements on body composition (including fat percentage measured by dual-energy x-ray absorptiometry), glucose homeostasis including homeostatic model assessment index and insulin sensitivity index (Matsuda index, calculated from glucose and insulin values from an oral glucose tolerance test), and whole brain magnetic resonance imaging for regional volumetric analyses. According to pairwise analysis, the active twins had lower body fat percentage (P = 0.029) and homeostatic model assessment index (P = 0.031) and higher Matsuda index (P = 0.021) compared with their inactive co-twins. Striatal and prefrontal cortex (subgyral and inferior frontal gyrus) brain gray matter volumes were larger in the nondominant hemisphere in active twins compared with those in inactive co-twins, with a statistical threshold of P < 0.001. Among healthy adult male twins in their mid-30s, a greater level of physical activity is associated with improved glucose homeostasis and modulation of striatum and prefrontal cortex gray matter volume, independent of genetic background. The findings may contribute to later reduced risk of type 2 diabetes and mobility limitations.

MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information.

PubMed

Milles, Julien; Zhu, Yue Min; Gimenez, Gérard; Guttmann, Charles R G; Magnin, Isabelle E

2007-03-01

A novel approach for correcting intensity nonuniformity in magnetic resonance imaging (MRI) is presented. This approach is based on the simultaneous use of spatial and gray-level histogram information. Spatial information about intensity nonuniformity is obtained using cubic B-spline smoothing. Gray-level histogram information of the image corrupted by intensity nonuniformity is exploited from a frequential point of view. The proposed correction method is illustrated using both physical phantom and human brain images. The results are consistent with theoretical prediction, and demonstrate a new way of dealing with intensity nonuniformity problems. They are all the more significant as the ground truth on intensity nonuniformity is unknown in clinical images.

TelCoVis: Visual Exploration of Co-occurrence in Urban Human Mobility Based on Telco Data.

PubMed

Wu, Wenchao; Xu, Jiayi; Zeng, Haipeng; Zheng, Yixian; Qu, Huamin; Ni, Bing; Yuan, Mingxuan; Ni, Lionel M

2016-01-01

Understanding co-occurrence in urban human mobility (i.e. people from two regions visit an urban place during the same time span) is of great value in a variety of applications, such as urban planning, business intelligence, social behavior analysis, as well as containing contagious diseases. In recent years, the widespread use of mobile phones brings an unprecedented opportunity to capture large-scale and fine-grained data to study co-occurrence in human mobility. However, due to the lack of systematic and efficient methods, it is challenging for analysts to carry out in-depth analyses and extract valuable information. In this paper, we present TelCoVis, an interactive visual analytics system, which helps analysts leverage their domain knowledge to gain insight into the co-occurrence in urban human mobility based on telco data. Our system integrates visualization techniques with new designs and combines them in a novel way to enhance analysts' perception for a comprehensive exploration. In addition, we propose to study the correlations in co-occurrence (i.e. people from multiple regions visit different places during the same time span) by means of biclustering techniques that allow analysts to better explore coordinated relationships among different regions and identify interesting patterns. The case studies based on a real-world dataset and interviews with domain experts have demonstrated the effectiveness of our system in gaining insights into co-occurrence and facilitating various analytical tasks.

Occurrence of dichloroacetamide herbicide safeners and co-applied herbicides in midwestern U.S. streams

USGS Publications Warehouse

Woodward, Emily; Hladik, Michelle; Kolpin, Dana W.

2018-01-01

Dichloroacetamide safeners (e.g., AD-67, benoxacor, dichlormid, and furilazole) are co-applied with chloroacetanilide herbicides to protect crops from herbicide toxicity. While such safeners have been used since the early 1970s, there are minimal data about safener usage, occurrence in streams, or potential ecological effects. This study focused on one of these research gaps, occurrence in streams. Seven Midwestern U.S. streams (five in Iowa and two in Illinois), with extensive row-crop agriculture, were sampled at varying frequencies from spring 2016 through summer 2017. All four safeners were detected at least once; furilazole was the most frequently detected (31%), followed by benoxacor (29%), dichlormid (15%), and AD-67 (2%). The maximum concentrations ranged from 42 to 190 ng/L. Stream detections and concentrations of safeners appear to be driven by a combination of timing of application (spring following herbicide application) and precipitation events. Detected concentrations were below known toxicity levels for aquatic organisms.

The Co-Occurrence of Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder Symptoms in Parents of Children with ASD or ASD with ADHD

ERIC Educational Resources Information Center

van Steijn, Daphne J.; Richards, Jennifer S.; Oerlemans, Anoek M.; de Ruiter, Saskia W.; van Aken, Marcel A. G.; Franke, Barbara; Buitelaar, Jan. K.; Rommelse, Nanda N. J.

2012-01-01

Background: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share about 50-72% of their genetic factors, which is the most likely explanation for their frequent co-occurrence within the same patient or family. An additional or alternative explanation for the co-occurrence may be (cross-)assortative mating, e.g.,…

The effect of evaluation on co-occurrence memory judgement.

PubMed

Bar-Anan, Yoav; Amzaleg-David, Efrat

2014-01-01

Three experiments tested the effect of an attitude towards an object on the memory judgement of whether this object co-occurred with positive versus negative stimuli. We induced positive or negative attitudes towards novel male stimuli, and paired each man with an equal number of positive and negative animals. In a memory test, participants reported more co-occurrences of same-valence man/animal pairs than opposite-valence pairs. This valence-compatibility effect occurred even when attitudes were induced after the pairing (Experiment 1), when participants knew that each man occurred with an equal number of positive and negative animals (Experiment 2), and in reports of clear memory of pairs that did not co-occur (Experiment 3). The present findings suggest that evaluation causes illusory correlation even when the co-occurring stimuli are not traits or behaviours attributed to the attitude object. The results question the validity of co-occurrence memory judgements as measures of co-occurrence awareness in evaluative conditioning (EC) research.

What Happened to Gray Whales during the Pleistocene? The Ecological Impact of Sea-Level Change on Benthic Feeding Areas in the North Pacific Ocean

PubMed Central

Pyenson, Nicholas D.; Lindberg, David R.

2011-01-01

Background Gray whales (Eschrichtius robustus) undertake long migrations, from Baja California to Alaska, to feed on seasonally productive benthos of the Bering and Chukchi seas. The invertebrates that form their primary prey are restricted to shallow water environments, but global sea-level changes during the Pleistocene eliminated or reduced this critical habitat multiple times. Because the fossil record of gray whales is coincident with the onset of Northern Hemisphere glaciation, gray whales survived these massive changes to their feeding habitat, but it is unclear how. Methodology/Principal Findings We reconstructed gray whale carrying capacity fluctuations during the past 120,000 years by quantifying gray whale feeding habitat availability using bathymetric data for the North Pacific Ocean, constrained by their maximum diving depth. We calculated carrying capacity based on modern estimates of metabolic demand, prey availability, and feeding duration; we also constrained our estimates to reflect current population size and account for glaciated and non-glaciated areas in the North Pacific. Our results show that key feeding areas eliminated by sea-level lowstands were not replaced by commensurate areas. Our reconstructions show that such reductions affected carrying capacity, and harmonic means of these fluctuations do not differ dramatically from genetic estimates of carrying capacity. Conclusions/Significance Assuming current carrying capacity estimates, Pleistocene glacial maxima may have created multiple, weak genetic bottlenecks, although the current temporal resolution of genetic datasets does not test for such signals. Our results do not, however, falsify molecular estimates of pre-whaling population size because those abundances would have been sufficient to survive the loss of major benthic feeding areas (i.e., the majority of the Bering Shelf) during glacial maxima. We propose that gray whales survived the disappearance of their primary feeding ground by employing generalist filter-feeding modes, similar to the resident gray whales found between northern Washington State and Vancouver Island. PMID:21754984

Visual performance with sport-tinted contact lenses in natural sunlight.

PubMed

Erickson, Graham B; Horn, Fraser C; Barney, Tyler; Pexton, Brett; Baird, Richard Y

2009-05-01

The use of tinted and clear contact lenses (CLs) in all aspects of life is becoming a more popular occurrence, particularly in athletic activities. This study broadens previous research regarding performance-tinted CLs and their effects on measures of visual performance. Thirty-three subjects (14 male, 19 female) were fitted with clear B&L Optima 38, 50% visible light transmission Amber and 36% visible light transmission Gray-Green Nike Maxsight CLs in an individualized randomized sequence. Subjects were dark-adapted with welding goggles before testing and in between subtests involving a Bailey-Lovie chart and the Haynes Distance Rock test. The sequence of testing was repeated for each lens modality. The Amber and Gray-Green lenses enabled subjects to recover vision faster in bright sunlight compared with clear lenses. Also, subjects were able to achieve better visual recognition in bright sunlight when compared with clear lenses. Additionally, the lenses allowed the subjects to alternate fixation between a bright and shaded target at a more rapid rate in bright sunlight as compared with clear lenses. Subjects preferred both the Amber and Gray-Green lenses over clear lenses in the bright and shadowed target conditions. The results of the current study show that Maxsight Amber and Gray-Green lenses provide better contrast discrimination in bright sunlight, better contrast discrimination when alternating between bright and shaded target conditions, better speed of visual recovery in bright sunlight, and better overall visual performance in bright and shaded target conditions compared with clear lenses.

Joint estimation of habitat dynamics and species interactions: Disturbance reduces co-occurrence of non-native predators with an endangered toad

USGS Publications Warehouse

Miller, David A.W.; Brehme, Cheryl S.; Hines, James E.; Nichols, James D.; Fisher, Robert N.

2012-01-01

1. Ecologists have long been interested in the processes that determine patterns of species occurrence and co-occurrence. Potential short-comings of many existing empirical approaches that address these questions include a reliance on patterns of occurrence at a single time point, failure to account properly for imperfect detection and treating the environment as a static variable.2. We fit detection and non-detection data collected from repeat visits using a dynamic site occupancy model that simultaneously accounts for the temporal dynamics of a focal prey species, its predators and its habitat. Our objective was to determine how disturbance and species interactions affect the co-occurrence probabilities of an endangered toad and recently introduced non-native predators in stream breeding habitats. For this, we determined statistical support for alternative processes that could affect co-occurrence frequency in the system.3. We collected occurrence data at stream segments in two watersheds where streams were largely ephemeral and one watershed dominated by perennial streams. Co-occurrence probabilities of toads with non-native predators were related to disturbance frequency, with low co-occurrence in the ephemeral watershed and high co-occurrence in the perennial watershed. This occurred because once predators were established at a site, they were rarely lost from the site except in cases when the site dried out. Once dry sites became suitable again, toads colonized them much more rapidly than predators, creating a period of predator-free space.4. We attribute the dynamics to a storage effect, where toads persisting outside the stream environment during periods of drought rapidly colonized sites when they become suitable again. Our results support that even in highly connected stream networks, temporal disturbance can structure frequencies with which breeding amphibians encounter non-native predators.5. Dynamic multi-state occupancy models are a powerful tool for rigorously examining hypotheses about inter-species and species–habitat interactions. In contrast to previous methods that infer dynamic processes based on static patterns in occupancy, the approach we took allows the dynamic processes that determine species–species and species–habitat interactions to be directly estimated.

Clinical feasibility study of combined opto-acoustic and ultrasonic imaging modality providing coregistered functional and anatomical maps of breast tumors

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Smith, Remie J.; Herzog, Don; Miller, Tom; Stavros, A. Thomas; Ermilov, Sergey; Conjusteau, André; Tsyboulski, Dmitri; Oraevsky, Alexander A.; Kist, Kenneth; Dornbluth, N. C.; Otto, Pamela

2013-03-01

We report on findings from the clinical feasibility study of the ImagioTM. Breast Imaging System, which acquires two-dimensional opto-acoustic (OA) images co-registered with conventional ultrasound using a specialized duplex hand-held probe. Dual-wavelength opto-acoustic technology is used to generate parametric maps based upon total hemoglobin and its oxygen saturation in breast tissues. This may provide functional diagnostic information pertaining to tumor metabolism and microvasculature, which is complementary to morphological information obtained with conventional gray-scale ultrasound. We present co-registered opto-acoustic and ultrasonic images of malignant and benign tumors from a recent clinical feasibility study. The clinical results illustrate that the technology may have the capability to improve the efficacy of breast tumor diagnosis. In doing so, it may have the potential to reduce biopsies and to characterize cancers that were not seen well with conventional gray-scale ultrasound alone.

Phase-only modulation of a twisted nematic liquid crystal TV by use of the eigenpolarization states

NASA Astrophysics Data System (ADS)

Pezzanaiti, J. L.; Chipman, R. A.

1993-09-01

Measured eigenpolarization states of an InFocus TVT-6000 liquid crystal television (LCTV) for 0-255 range gray levels are reported. It is shown that the eigenpolarization states remain nearly constant with dependence on gray level for several bias voltage settings. The LCTV eigenpolarization states were computed from Mueller matrix.

Rod stiffness as a risk factor of proximal junctional kyphosis after adult spinal deformity surgery: comparative study between cobalt chrome multiple-rod constructs and titanium alloy two-rod constructs.

PubMed

Han, Sanghyun; Hyun, Seung-Jae; Kim, Ki-Jeong; Jahng, Tae-Ahn; Lee, Subum; Rhim, Seung-Chul

2017-07-01

Little is known about the effect of rod stiffness as a risk factor of proximal junctional kyphosis (PJK) after adult spinal deformity (ASD) surgery. The aim of this study was to compare radiographic outcomes after the use of cobalt chrome multiple-rod constructs (CoCr MRCs) and titanium alloy two-rod constructs (Ti TRCs) for ASD surgery with a minimum 1-year follow-up. Retrospective case-control study in two institutes. We included 54 patients who underwent ASD surgery with fusion to the sacrum in two academic institutes between 2002 and 2015. Radiographic outcomes were measured on the standing lateral radiographs before surgery, 1 month postoperatively, and at ultimate follow-up. The outcome measures were composed of pre- and postoperative sagittal vertical axis (SVA), pre- and postoperative lumbar lordosis (LL), pre- and postoperative thoracic kyphosis (TK)+LL+pelvic incidence (PI), pre- and postoperative PI minus LL, level of uppermost instrumented vertebra (UIV), evaluation of fusion after surgery, the presence of PJK, and the occurrence of rod fracture. We reviewed the medical records of 54 patients who underwent ASD surgery. Of these, 20 patients had CoCr MRC and 34 patients had Ti TRC. Baseline data and radiographic measurements were compared between the two groups. The Mann-Whitney U test, the chi-square test, and the Fisher exact test were used to compare outcomes between the groups. The patients of the groups were similar in terms of age, gender, diagnosis, number of three-column osteotomy, levels fused, bone mineral density, preoperative TK, pre- and postoperative TK+LL+PI, SVA difference, LL change, pre- and postoperative PI minus LL, and location of UIV (upper or lower thoracic level). However, there were significant differences in the occurrence of PJK and rod breakage (PJK: CoCr MRC: 12 [60%] vs. Ti TRC: 9 [26.5%], p=.015; occurrence of rod breakage: CoCr MRC: 0 [0%] vs. Ti TRC: 11 [32.4%], p=.004). The time of PJK was less than 12 months after surgery in the CoCr MRC group. However, 55.5% (5/9) of PJK developed over 12 months after surgery in the Ti TRC group. Increasing the rod stiffness by the use of cobalt chrome rod and can prevent rod breakage but adversely affects the occurrence and the time of PJK. Copyright © 2017 Elsevier Inc. All rights reserved.

Computer-aided diagnosis for classifying benign versus malignant thyroid nodules based on ultrasound images: A comparison with radiologist-based assessments.

PubMed

Chang, Yongjun; Paul, Anjan Kumar; Kim, Namkug; Baek, Jung Hwan; Choi, Young Jun; Ha, Eun Ju; Lee, Kang Dae; Lee, Hyoung Shin; Shin, DaeSeock; Kim, Nakyoung

2016-01-01

To develop a semiautomated computer-aided diagnosis (cad) system for thyroid cancer using two-dimensional ultrasound images that can be used to yield a second opinion in the clinic to differentiate malignant and benign lesions. A total of 118 ultrasound images that included axial and longitudinal images from patients with biopsy-confirmed malignant (n = 30) and benign (n = 29) nodules were collected. Thyroid cad software was developed to extract quantitative features from these images based on thyroid nodule segmentation in which adaptive diffusion flow for active contours was used. Various features, including histogram, intensity differences, elliptical fit, gray-level co-occurrence matrixes, and gray-level run-length matrixes, were evaluated for each region imaged. Based on these imaging features, a support vector machine (SVM) classifier was used to differentiate benign and malignant nodules. Leave-one-out cross-validation with sequential forward feature selection was performed to evaluate the overall accuracy of this method. Additionally, analyses with contingency tables and receiver operating characteristic (ROC) curves were performed to compare the performance of cad with visual inspection by expert radiologists based on established gold standards. Most univariate features for this proposed cad system attained accuracies that ranged from 78.0% to 83.1%. When optimal SVM parameters that were established using a grid search method with features that radiologists use for visual inspection were employed, the authors could attain rates of accuracy that ranged from 72.9% to 84.7%. Using leave-one-out cross-validation results in a multivariate analysis of various features, the highest accuracy achieved using the proposed cad system was 98.3%, whereas visual inspection by radiologists reached 94.9% accuracy. To obtain the highest accuracies, "axial ratio" and "max probability" in axial images were most frequently included in the optimal feature sets for the authors' proposed cad system, while "shape" and "calcification" in longitudinal images were most frequently included in the optimal feature sets for visual inspection by radiologists. The computed areas under curves in the ROC analysis were 0.986 and 0.979 for the proposed cad system and visual inspection by radiologists, respectively; no significant difference was detected between these groups. The use of thyroid cad to differentiate malignant from benign lesions shows accuracy similar to that obtained via visual inspection by radiologists. Thyroid cad might be considered a viable way to generate a second opinion for radiologists in clinical practice.

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

Co-occurence of florid cemento-osseous dysplasia and simple bone cyst: a case report.

PubMed

Rao, Kumuda Arvind; Shetty, Shishir Ram; Babu, Subhas G; Castelino, Renita Lorina

2011-01-01

The purpose of this report is to present a rare case of co-occurrence of florid cemento-osseous dysplasia with simple bone cyst in a middle aged Asian woman. Most of the reported cases are isolated cases of simple bone cyst or florid cemento-osseous dysplasia, but co-occurrence of these two entities is extremely rare. The authors report a 41 year old female patient with co-occurrence of mandibular florid cemento-osseous dysplasia with simple bone cyst. A thorough clinical and radiological examination was carried out. It was diagnosed mandibular cyst with possible co-occurrence of florid cemento-osseous dysplasia. Surgical exploration of the multilocular lesion was applied. Since, the patient was symptomatic at the time of presentation utmost caution was taken during the surgical procedure as florid cemento-osseous dysplasia is associated with hypo-vascularity of the affected bone. Based on histopathological, as well as supporting clinico-radiological findings a confirmative diagnosis of florid cemento-osseous dysplasia co-occurring with simple bone cyst was made. Patient was followed-up for a period of six months and was reported to be asymptomatic. Timely diagnosis and well planned treatment is important to obtain a good prognosis when a rare co-occurrence of two or more bone lesions affects the jaws.

Co-infections of haemosporidian and trypanosome parasites in a North American songbird.

PubMed

Soares, Letícia; Ellis, Vincenzo A; Ricklefs, Robert E

2016-12-01

Hosts frequently harbour multiple parasite infections, yet patterns of parasite co-occurrence are poorly documented in nature. In this study, we asked whether two common avian blood parasites, one haemosporidian and one trypanosome, affect each other's occurrence in individuals of a single host species. We used molecular genotyping to survey protozoan parasites in the peripheral blood of yellow-breasted chats (Aves: Passeriformes [Parulidae]: Icteria virens) from the Ozarks of Southern Missouri. We also determined whether single and co-infections differently influence white blood cell and polychromatic erythrocyte counts, the latter being a measure of regenerative anaemia. We found a positive association between the haemosporidian and trypanosome parasites, such that infection by one increases the probability that an individual host is infected by the other. Adult individuals were more likely than juveniles to exhibit haemosporidian infection, but co-infections and single trypanosome infections were not age-related. We found evidence of pathogenicity of trypanosomes in that infected individuals exhibited similar levels of regenerative anaemia as birds infected with haemosporidian parasites of the genus Plasmodium. Counts of white blood cells did not differ with respect to infection status.

Nutritional status and physical activity level as risk factor for traumatic dental injuries occurrence: a systematic review.

PubMed

Goettems, Marília Leão; Schuch, Helena Silveira; Hallal, Pedro Curi; Torriani, Dione Dias; Demarco, Flávio Fernando

2014-08-01

To systematically review epidemiological articles assessing traumatic dental injuries (TDI) rates according to the physical activity habits and nutritional status. A search was conducted using PubMed, ISI, Scopus, SciELO, LILACS, and gray literature in Brazilian Theses Databank. We searched for dental trauma, traumatic dental injuries, tooth injuries, tooth fractures, physical activity, motor activity, exercise, sedentary lifestyle, sports, obesity, body mass index (BMI), overweight, and fatness. Databases were searched in duplicate from their earliest records until 2012. Additional studies were identified by searching bibliographies of the articles. Two reviewers performed data extraction and analyzed study procedural quality using the Newcastle-Ottawa scale. PRISMA guidelines for reporting systematic reviews were followed. We found 1159 articles, of whom 14 reports involving 13 studies were selected. One article was a birth cohort, one had a case-control design, and the others were cross-sectional. The quality of evidence varied across the studies and was high (9) in 3. Eleven of the studies included assessed influence of nutritional status: five show a positive association between dental trauma and overweight and six do not show any association. Regarding physical activity level, five studies assessed its effect on trauma occurrence: two detected that physical activity acts as a protective factor and two that physical active increases the risk of dental injuries, and one showed no differences in TDI occurrence. Physical activity estimated from questionnaires and BMI were the most frequently used measures, but methodological differences prevent the comparison of results. The results suggest that no truly causal relationship exists between dental trauma and physical activity and nutritional status. Due to the relatively low level of evidence currently present, studies with more robust design, for example, prospective cohort should address this question, especially in view of the epidemic of obesity. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Digital analysis of changes by Plasmodium vivax malaria in erythrocytes.

PubMed

Edison, Maombi; Jeeva, J B; Singh, Megha

2011-01-01

Blood samples of malaria patients (n = 30), selected based on the severity of parasitemia, were divided into low (LP), medium (MP) and high (HP) parasitemia, which represent increasing levels of the disease severity. Healthy subjects (n = 10) without any history of disease were selected as a control group. By processing of erythrocytes images their contours were obtained and from these the shape parameters area, perimeter and form factor were obtained. The gray level intensity was determined by scanning of erythrocyte along its largest diameter. A comparison of these with that of normal cells showed a significant change in shape parameters. The gray level intensity decreases with the increase of severity of the disease. The changes in shape parameters directly and gray level intensity variation inversely are correlated with the increase in parasite density due to the disease.

Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

USGS Publications Warehouse

Meier, E.S.; Edwards, T.C.; Kienast, Felix; Dobbertin, M.; Zimmermann, N.E.

2011-01-01

Aim During recent and future climate change, shifts in large-scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress-gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad-scale environmental data. We evaluated the variation of species co-occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates.Location Europe.Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co-occurrence patterns.Results Correlation analyses supported the stress-gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co-occurrence patterns may play a major role.Main conclusions Our results demonstrate the importance of species co-occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climate-induced spatial segregation of the major tree species could have ecological and economic consequences. ?? 2010 Blackwell Publishing Ltd.

Texture functions in image analysis: A computationally efficient solution

NASA Technical Reports Server (NTRS)

Cox, S. C.; Rose, J. F.

1983-01-01

A computationally efficient means for calculating texture measurements from digital images by use of the co-occurrence technique is presented. The calculation of the statistical descriptors of image texture and a solution that circumvents the need for calculating and storing a co-occurrence matrix are discussed. The results show that existing efficient algorithms for calculating sums, sums of squares, and cross products can be used to compute complex co-occurrence relationships directly from the digital image input.

[Co-occurrence of soil fauna communities with changes in altitude on the northern slope of Changbai Mountain].

PubMed

Tong, Fuchun; Jin, Zhedong; Wang, Qingli; Xiao, Yihua

2003-10-01

The co-occurrence of soil fauna communities at different altitudes may reflect at some extent the relationships among communities, their coexistence, and the replacement of species along the altitude gradient. The continuous or disjunctive distribution of different species along altitude gradient not only reflected the environment variation at altitude gradient, but also the biological and ecological spatiality as well as the adaptability of species. The northern slope of Changbai Moutain has not only a high diversity in soil fauna types and species, but also a high variation of diversity pattern along the altitude gradient, which is a perfect transect for the research of biodiversity and gradient patterns. From 550 m to 2,560 m on the northern slope of Changbai Mountain, twenty-two plots were investigated with an interval of 100 m in altitude. By using Jaccard index, the co-occurrence of soil fauna communities at different altitudes was analyzed. For the species of different life forms or for all the species as a whole, the co-occurrence of soil faunae between neighboring communities was the highest, except for that between different soil fauna types. The peak and valley values of the co-occurrence of soil fauna communities along altitude gradient were matched with their gradient patterns, and the co-occurrence of soil faunae at different layers or all of the soil fauna communities were decreased with increasing altitude difference.

Modality-Spanning Deficits in Attention-Deficit/Hyperactivity Disorder in Functional Networks, Gray Matter, and White Matter

PubMed Central

Kessler, Daniel; Angstadt, Michael; Welsh, Robert C.

2014-01-01

Previous neuroimaging investigations in attention-deficit/hyperactivity disorder (ADHD) have separately identified distributed structural and functional deficits, but interconnections between these deficits have not been explored. To unite these modalities in a common model, we used joint independent component analysis, a multivariate, multimodal method that identifies cohesive components that span modalities. Based on recent network models of ADHD, we hypothesized that altered relationships between large-scale networks, in particular, default mode network (DMN) and task-positive networks (TPNs), would co-occur with structural abnormalities in cognitive regulation regions. For 756 human participants in the ADHD-200 sample, we produced gray and white matter volume maps with voxel-based morphometry, as well as whole-brain functional connectomes. Joint independent component analysis was performed, and the resulting transmodal components were tested for differential expression in ADHD versus healthy controls. Four components showed greater expression in ADHD. Consistent with our a priori hypothesis, we observed reduced DMN-TPN segregation co-occurring with structural abnormalities in dorsolateral prefrontal cortex and anterior cingulate cortex, two important cognitive control regions. We also observed altered intranetwork connectivity in DMN, dorsal attention network, and visual network, with co-occurring distributed structural deficits. There was strong evidence of spatial correspondence across modalities: For all four components, the impact of the respective component on gray matter at a region strongly predicted the impact on functional connectivity at that region. Overall, our results demonstrate that ADHD involves multiple, cohesive modality spanning deficits, each one of which exhibits strong spatial overlap in the pattern of structural and functional alterations. PMID:25505309

Gray matter regions statistically mediating the cross-sectional association of eotaxin and set-shifting among older adults with major depressive disorder.

PubMed

Smagula, Stephen F; Karim, Helmet T; Lenze, Eric J; Butters, Meryl A; Wu, Gregory F; Mulsant, Benoit H; Reynolds, Charles F; Aizenstein, Howard J

2017-12-01

Eotaxin is a chemokine that exerts negative effects on neurogenesis. We recently showed that peripheral eotaxin levels correlate with both lower gray matter volume and poorer executive performance in older adults with major depressive disorder. These findings suggest that the relationship between eotaxin and set-shifting may be accounted for by lower gray matter volume in specific regions. Prior studies have identified specific gray matter regions that correlate with set-shifting performance, but have not examined whether these specific gray matter regions mediate the cross-sectional association between eotaxin and set-shifting. In 27 older adults (mean age: 68 ± 5.2 years) with major depressive disorder, we performed a whole brain (voxel-wise) analysis testing whether/where gray matter density statistically mediates the cross-sectional association of eotaxin and set-shifting performance. We found the association between eotaxin and set-shifting performance was fully statistically mediated by lower gray matter density in left middle cingulate, right pre-/post-central, lingual, inferior/superior frontal, cuneus, and middle temporal regions. The regions identified above may be both susceptible to a potential neurodegenerative effect of eotaxin, and critical to preserving set-shifting function. Longitudinal and intervention studies are needed to further evaluate whether targeting eotaxin levels will prevent neurodegeneration and executive impairment in older adults with depression. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Topical video object discovery from key frames by modeling word co-occurrence prior.

PubMed

Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

2015-12-01

A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

Wavelet Representation of the Corneal Pulse for Detecting Ocular Dicrotism

PubMed Central

Melcer, Tomasz; Danielewska, Monika E.; Iskander, D. Robert

2015-01-01

Purpose To develop a reliable and powerful method for detecting the ocular dicrotism from non-invasively acquired signals of corneal pulse without the knowledge of the underlying cardiopulmonary information present in signals of ocular blood pulse and the electrical heart activity. Methods Retrospective data from a study on glaucomatous and age-related changes in corneal pulsation [PLOS ONE 9(7),(2014):e102814] involving 261 subjects was used. Continuous wavelet representation of the signal derivative of the corneal pulse was considered with a complex Gaussian derivative function chosen as mother wavelet. Gray-level Co-occurrence Matrix has been applied to the image (heat-maps) of CWT to yield a set of parameters that can be used to devise the ocular dicrotic pulse detection schemes based on the Conditional Inference Tree and the Random Forest models. The detection scheme was first tested on synthetic signals resembling those of a dicrotic and a non-dicrotic ocular pulse before being used on all 261 real recordings. Results A detection scheme based on a single feature of the Continuous Wavelet Transform of the corneal pulse signal resulted in a low detection rate. Conglomeration of a set of features based on measures of texture (homogeneity, correlation, energy, and contrast) resulted in a high detection rate reaching 93%. Conclusion It is possible to reliably detect a dicrotic ocular pulse from the signals of corneal pulsation without the need of acquiring additional signals related to heart activity, which was the previous state-of-the-art. The proposed scheme can be applied to other non-stationary biomedical signals related to ocular dynamics. PMID:25906236

Performance assessment of automated tissue characterization for prostate H and E stained histopathology

NASA Astrophysics Data System (ADS)

DiFranco, Matthew D.; Reynolds, Hayley M.; Mitchell, Catherine; Williams, Scott; Allan, Prue; Haworth, Annette

2015-03-01

Reliable automated prostate tumor detection and characterization in whole-mount histology images is sought in many applications, including post-resection tumor staging and as ground-truth data for multi-parametric MRI interpretation. In this study, an ensemble-based supervised classification algorithm for high-resolution histology images was trained on tile-based image features including histogram and gray-level co-occurrence statistics. The algorithm was assessed using different combinations of H and E prostate slides from two separate medical centers and at two different magnifications (400x and 200x), with the aim of applying tumor classification models to new data. Slides from both datasets were annotated by expert pathologists in order to identify homogeneous cancerous and non-cancerous tissue regions of interest, which were then categorized as (1) low-grade tumor (LG-PCa), including Gleason 3 and high-grade prostatic intraepithelial neoplasia (HG-PIN), (2) high-grade tumor (HG-PCa), including various Gleason 4 and 5 patterns, or (3) non-cancerous, including benign stroma and benign prostatic hyperplasia (BPH). Classification models for both LG-PCa and HG-PCa were separately trained using a support vector machine (SVM) approach, and per-tile tumor prediction maps were generated from the resulting ensembles. Results showed high sensitivity for predicting HG-PCa with an AUC up to 0.822 using training data from both medical centres, while LG-PCa showed a lower sensitivity of 0.763 with the same training data. Visual inspection of cancer probability heatmaps from 9 patients showed that 17/19 tumors were detected, and HG-PCa generally reported less false positives than LG-PCa.

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

GBM heterogeneity characterization by radiomic analysis of phenotype anatomical planes

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

Glioblastoma multiforme (GBM) is the most common malignant primary tumor of the central nervous system, characterized among other traits by rapid metastatis. Three tissue phenotypes closely associated with GBMs, namely, necrosis (N), contrast enhancement (CE), and edema/invasion (E), exhibit characteristic patterns of texture heterogeneity in magnetic resonance images (MRI). In this study, we propose a novel model to characterize GBM tissue phenotypes using gray level co-occurrence matrices (GLCM) in three anatomical planes. The GLCM encodes local image patches in terms of informative, orientation-invariant texture descriptors, which are used here to sub-classify GBM tissue phenotypes. Experiments demonstrate the model on MRI data of 41 GBM patients, obtained from the cancer genome atlas (TCGA). Intensity-based automatic image registration is applied to align corresponding pairs of fixed T1˗weighted (T1˗WI) post-contrast and fluid attenuated inversion recovery (FLAIR) images. GBM tissue regions are then segmented using the 3D Slicer tool. Texture features are computed from 12 quantifier functions operating on GLCM descriptors, that are generated from MRI intensities within segmented GBM tissue regions. Various classifier models are used to evaluate the effectiveness of texture features for discriminating between GBM phenotypes. Results based on T1-WI scans showed a phenotype classification accuracy of over 88.14%, a sensitivity of 85.37% and a specificity of 96.1%, using the linear discriminant analysis (LDA) classifier. This model has the potential to provide important characteristics of tumors, which can be used for the sub-classification of GBM phenotypes.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

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

Wu, J; Gong, G; Cui, Y

Purpose: To predict early pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multi-region analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). Methods: In this institution review board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with a high-temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitativemore » Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Results: Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast wash-out were statistically significant (p< 0.05) after correcting for multiple testing, with area under the ROC curve or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (p = 0.002) in leave-one-out cross validation. This improved upon conventional imaging predictors such as tumor volume (AUC=0.53) and texture features based on whole-tumor analysis (AUC=0.65). Conclusion: The heterogeneity of the tumor subregion associated with fast wash-out on DCE-MRI predicted early pathological response to neoadjuvant chemotherapy in breast cancer.« less

Characterization of healthy and osteoarthritic chondrocyte cell patterns on phase contrast CT images of the knee cartilage matrix

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Yang, Chien-Chun; Glaser, Christian; Reiser, Maximilian F.; Wismüller, Axel

2012-03-01

The current approach to evaluating cartilage degeneration at the knee joint requires visualization of the joint space on radiographic images where indirect cues such as joint space narrowing serve as markers for osteoarthritis. A recent novel approach to visualizing the knee cartilage matrix using phase contrast CT imaging (PCI-CT) was shown to allow direct examination of chondrocyte cell patterns and their subsequent correlation to osteoarthritis. This study aims to characterize chondrocyte cell patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage through both gray-level co-occurrence matrix (GLCM) derived texture features as well as Minkowski Functionals (MF). Thirteen GLCM and three MF texture features were extracted from 404 regions of interest (ROI) annotated on PCI images of healthy and osteoarthritic specimens of knee cartilage. These texture features were then used in a machine learning task to classify ROIs as healthy or osteoarthritic. A fuzzy k-nearest neighbor classifier was used and its performance was evaluated using the area under the ROC curve (AUC). The best classification performance was observed with the MF features 'perimeter' and 'Euler characteristic' and with GLCM correlation features (f3 and f13). With the experimental conditions used in this study, both Minkowski Functionals and GLCM achieved a high classification performance (AUC value of 0.97) in the task of distinguishing between health and osteoarthritic ROIs. These results show that such quantitative analysis of chondrocyte patterns in the knee cartilage matrix can distinguish between healthy and osteoarthritic tissue with high accuracy.

3D Texture Analysis Reveals Imperceptible MRI Textural Alterations in the Thalamus and Putamen in Progressive Myoclonic Epilepsy Type 1, EPM1

PubMed Central

Suoranta, Sanna; Holli-Helenius, Kirsi; Koskenkorva, Päivi; Niskanen, Eini; Könönen, Mervi; Äikiä, Marja; Eskola, Hannu; Kälviäinen, Reetta; Vanninen, Ritva

2013-01-01

Progressive myoclonic epilepsy type 1 (EPM1) is an autosomal recessively inherited neurodegenerative disorder characterized by young onset age, myoclonus and tonic-clonic epileptic seizures. At the time of diagnosis, the visual assessment of the brain MRI is usually normal, with no major changes found later. Therefore, we utilized texture analysis (TA) to characterize and classify the underlying properties of the affected brain tissue by means of 3D texture features. Sixteen genetically verified patients with EPM1 and 16 healthy controls were included in the study. TA was performed upon 3D volumes of interest that were placed bilaterally in the thalamus, amygdala, hippocampus, caudate nucleus and putamen. Compared to the healthy controls, EPM1 patients had significant textural differences especially in the thalamus and right putamen. The most significantly differing texture features included parameters that measure the complexity and heterogeneity of the tissue, such as the co-occurrence matrix-based entropy and angular second moment, and also the run-length matrix-based parameters of gray-level non-uniformity, short run emphasis and long run emphasis. This study demonstrates the usability of 3D TA for extracting additional information from MR images. Textural alterations which suggest complex, coarse and heterogeneous appearance were found bilaterally in the thalamus, supporting the previous literature on thalamic pathology in EPM1. The observed putamenal involvement is a novel finding. Our results encourage further studies on the clinical applications, feasibility, reproducibility and reliability of 3D TA. PMID:23922849

Characterizing trabecular bone structure for assessing vertebral fracture risk on volumetric quantitative computed tomography

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Checefsky, Walter A.; Abidin, Anas Z.; Tsai, Halley; Wang, Xixi; Hobbs, Susan K.; Bauer, Jan S.; Baum, Thomas; Wismüller, Axel

2015-03-01

While the proximal femur is preferred for measuring bone mineral density (BMD) in fracture risk estimation, the introduction of volumetric quantitative computed tomography has revealed stronger associations between BMD and spinal fracture status. In this study, we propose to capture properties of trabecular bone structure in spinal vertebrae with advanced second-order statistical features for purposes of fracture risk assessment. For this purpose, axial multi-detector CT (MDCT) images were acquired from 28 spinal vertebrae specimens using a whole-body 256-row CT scanner with a dedicated calibration phantom. A semi-automated method was used to annotate the trabecular compartment in the central vertebral slice with a circular region of interest (ROI) to exclude cortical bone; pixels within were converted to values indicative of BMD. Six second-order statistical features derived from gray-level co-occurrence matrices (GLCM) and the mean BMD within the ROI were then extracted and used in conjunction with a generalized radial basis functions (GRBF) neural network to predict the failure load of the specimens; true failure load was measured through biomechanical testing. Prediction performance was evaluated with a root-mean-square error (RMSE) metric. The best prediction performance was observed with GLCM feature `correlation' (RMSE = 1.02 ± 0.18), which significantly outperformed all other GLCM features (p < 0.01). GLCM feature correlation also significantly outperformed MDCTmeasured mean BMD (RMSE = 1.11 ± 0.17) (p< 10-4). These results suggest that biomechanical strength prediction in spinal vertebrae can be significantly improved through characterization of trabecular bone structure with GLCM-derived texture features.

An explorative childhood pneumonia analysis based on ultrasonic imaging texture features

NASA Astrophysics Data System (ADS)

Zenteno, Omar; Diaz, Kristians; Lavarello, Roberto; Zimic, Mirko; Correa, Malena; Mayta, Holger; Anticona, Cynthia; Pajuelo, Monica; Oberhelman, Richard; Checkley, William; Gilman, Robert H.; Figueroa, Dante; Castañeda, Benjamín.

2015-12-01

According to World Health Organization, pneumonia is the respiratory disease with the highest pediatric mortality rate accounting for 15% of all deaths of children under 5 years old worldwide. The diagnosis of pneumonia is commonly made by clinical criteria with support from ancillary studies and also laboratory findings. Chest imaging is commonly done with chest X-rays and occasionally with a chest CT scan. Lung ultrasound is a promising alternative for chest imaging; however, interpretation is subjective and requires adequate training. In the present work, a two-class classification algorithm based on four Gray-level co-occurrence matrix texture features (i.e., Contrast, Correlation, Energy and Homogeneity) extracted from lung ultrasound images from children aged between six months and five years is presented. Ultrasound data was collected using a L14-5/38 linear transducer. The data consisted of 22 positive- and 68 negative-diagnosed B-mode cine-loops selected by a medical expert and captured in the facilities of the Instituto Nacional de Salud del Niño (Lima, Peru), for a total number of 90 videos obtained from twelve children diagnosed with pneumonia. The classification capacity of each feature was explored independently and the optimal threshold was selected by a receiver operator characteristic (ROC) curve analysis. In addition, a principal component analysis was performed to evaluate the combined performance of all the features. Contrast and correlation resulted the two more significant features. The classification performance of these two features by principal components was evaluated. The results revealed 82% sensitivity, 76% specificity, 78% accuracy and 0.85 area under the ROC.

A new 3D texture feature based computer-aided diagnosis approach to differentiate pulmonary nodules

NASA Astrophysics Data System (ADS)

Han, Fangfang; Wang, Huafeng; Song, Bowen; Zhang, Guopeng; Lu, Hongbing; Moore, William; Zhao, Hong; Liang, Zhengrong

2013-02-01

To distinguish malignant pulmonary nodules from benign ones is of much importance in computer-aided diagnosis of lung diseases. Compared to many previous methods which are based on shape or growth assessing of nodules, this proposed three-dimensional (3D) texture feature based approach extracted fifty kinds of 3D textural features from gray level, gradient and curvature co-occurrence matrix, and more derivatives of the volume data of the nodules. To evaluate the presented approach, the Lung Image Database Consortium public database was downloaded. Each case of the database contains an annotation file, which indicates the diagnosis results from up to four radiologists. In order to relieve partial-volume effect, interpolation process was carried out to those volume data with image slice thickness more than 1mm, and thus we had categorized the downloaded datasets to five groups to validate the proposed approach, one group of thickness less than 1mm, two types of thickness range from 1mm to 1.25mm and greater than 1.25mm (each type contains two groups, one with interpolation and the other without). Since support vector machine is based on statistical learning theory and aims to learn for predicting future data, so it was chosen as the classifier to perform the differentiation task. The measure on the performance was based on the area under the curve (AUC) of Receiver Operating Characteristics. From 284 nodules (122 malignant and 162 benign ones), the validation experiments reported a mean of 0.9051 and standard deviation of 0.0397 for the AUC value on average over 100 randomizations.

Contextual descriptors and neural networks for scene analysis in VHR SAR images

NASA Astrophysics Data System (ADS)

Del Frate, Fabio; Picchiani, Matteo; Falasco, Alessia; Schiavon, Giovanni

2016-10-01

The development of SAR technology during the last decade has made it possible to collect a huge amount of data over many regions of the world. In particular, the availability of SAR images from different sensors, with metric or sub-metric spatial resolution, offers novel opportunities in different fields as land cover, urban monitoring, soil consumption etc. On the other hand, automatic approaches become crucial for the exploitation of such a huge amount of information. In such a scenario, especially if single polarization images are considered, the main issue is to select appropriate contextual descriptors, since the backscattering coefficient of a single pixel may not be sufficient to classify an object on the scene. In this paper a comparison among three different approaches for contextual features definition is presented so as to design optimum procedures for VHR SAR scene understanding. The first approach is based on Gray Level Co- Occurrence Matrix since it is widely accepted and several studies have used it for land cover classification with SAR data. The second approach is based on the Fourier spectra and it has been already proposed with positive results for this kind of problems, the third one is based on Auto-associative Neural Networks which have been already proven effective for features extraction from polarimetric SAR images. The three methods are evaluated in terms of the accuracy of the classified scene when the features extracted using each method are considered as input to a neural network classificator and applied on different Cosmo-SkyMed spotlight products.

Supervised pixel classification for segmenting geographic atrophy in fundus autofluorescene images

NASA Astrophysics Data System (ADS)

Hu, Zhihong; Medioni, Gerard G.; Hernandez, Matthias; Sadda, SriniVas R.

2014-03-01

Age-related macular degeneration (AMD) is the leading cause of blindness in people over the age of 65. Geographic atrophy (GA) is a manifestation of the advanced or late-stage of the AMD, which may result in severe vision loss and blindness. Techniques to rapidly and precisely detect and quantify GA lesions would appear to be of important value in advancing the understanding of the pathogenesis of GA and the management of GA progression. The purpose of this study is to develop an automated supervised pixel classification approach for segmenting GA including uni-focal and multi-focal patches in fundus autofluorescene (FAF) images. The image features include region wise intensity (mean and variance) measures, gray level co-occurrence matrix measures (angular second moment, entropy, and inverse difference moment), and Gaussian filter banks. A k-nearest-neighbor (k-NN) pixel classifier is applied to obtain a GA probability map, representing the likelihood that the image pixel belongs to GA. A voting binary iterative hole filling filter is then applied to fill in the small holes. Sixteen randomly chosen FAF images were obtained from sixteen subjects with GA. The algorithm-defined GA regions are compared with manual delineation performed by certified graders. Two-fold cross-validation is applied for the evaluation of the classification performance. The mean Dice similarity coefficients (DSC) between the algorithm- and manually-defined GA regions are 0.84 +/- 0.06 for one test and 0.83 +/- 0.07 for the other test and the area correlations between them are 0.99 (p < 0.05) and 0.94 (p < 0.05) respectively.

Improved characterization of molecular phenotypes in breast lesions using 18F-FDG PET image homogeneity

NASA Astrophysics Data System (ADS)

Cao, Kunlin; Bhagalia, Roshni; Sood, Anup; Brogi, Edi; Mellinghoff, Ingo K.; Larson, Steven M.

2015-03-01

Positron emission tomography (PET) using uorodeoxyglucose (18F-FDG) is commonly used in the assessment of breast lesions by computing voxel-wise standardized uptake value (SUV) maps. Simple metrics derived from ensemble properties of SUVs within each identified breast lesion are routinely used for disease diagnosis. The maximum SUV within the lesion (SUVmax) is the most popular of these metrics. However these simple metrics are known to be error-prone and are susceptible to image noise. Finding reliable SUV map-based features that correlate to established molecular phenotypes of breast cancer (viz. estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) expression) will enable non-invasive disease management. This study investigated 36 SUV features based on first and second order statistics, local histograms and texture of segmented lesions to predict ER and PR expression in 51 breast cancer patients. True ER and PR expression was obtained via immunohistochemistry (IHC) of tissue samples from each lesion. A supervised learning, adaptive boosting-support vector machine (AdaBoost-SVM), framework was used to select a subset of features to classify breast lesions into distinct phenotypes. Performance of the trained multi-feature classifier was compared against the baseline single-feature SUVmax classifier using receiver operating characteristic (ROC) curves. Results show that texture features encoding local lesion homogeneity extracted from gray-level co-occurrence matrices are the strongest discriminator of lesion ER expression. In particular, classifiers including these features increased prediction accuracy from 0.75 (baseline) to 0.82 and the area under the ROC curve from 0.64 (baseline) to 0.75.

Optimal Binarization of Gray-Scaled Digital Images via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor); Klinko, Steven J. (Inventor)

2007-01-01

A technique for finding an optimal threshold for binarization of a gray scale image employs fuzzy reasoning. A triangular membership function is employed which is dependent on the degree to which the pixels in the image belong to either the foreground class or the background class. Use of a simplified linear fuzzy entropy factor function facilitates short execution times and use of membership values between 0.0 and 1.0 for improved accuracy. To improve accuracy further, the membership function employs lower and upper bound gray level limits that can vary from image to image and are selected to be equal to the minimum and the maximum gray levels, respectively, that are present in the image to be converted. To identify the optimal binarization threshold, an iterative process is employed in which different possible thresholds are tested and the one providing the minimum fuzzy entropy measure is selected.

An Experimental Test of Competition among Mice, Chipmunks, and Squirrels in Deciduous Forest Fragments

PubMed Central

Brunner, Jesse L.; Duerr, Shannon; Keesing, Felicia; Killilea, Mary; Vuong, Holly; Ostfeld, Richard S.

2013-01-01

Mixed hardwood forests of the northeast United States support a guild of granivorous/omnivorous rodents including gray squirrels (Sciurus carolinensis), eastern chipmunks (Tamias striatus), and white-footed mice (Peromyscus leucopus). These species coincide geographically, co-occur locally, and consume similar food resources. Despite their idiosyncratic responses to landscape and patch variables, patch occupancy models suggest that competition may influence their respective distributions and abundances, and accordingly their influence on the rest of the forest community. Experimental studies, however, are wanting. We present the result of a large-scale experiment in which we removed white-footed mice or gray squirrels from small, isolated forest fragments in Dutchess County, New York, and added these mammals to other fragments in order to alter the abundance of these two species. We then used mark–recapture analyses to quantify the population-level and individual-level effects on resident mice, squirrels, and chipmunks. Overall, we found little evidence of competition. There were essentially no within-season numerical responses to changes in the abundance of putative competitors. Moreover, while individual-level responses (apparent survival and capture probability) did vary with competitor densities in some models, these effects were often better explained by site-specific parameters and were restricted to few of the 19 sites we studied. With only weak or nonexistent competition among these three common rodent species, we expect their patterns of habitat occupancy and population dynamics to be largely independent of one another. PMID:23824654

Image segmentation using local shape and gray-level appearance models

NASA Astrophysics Data System (ADS)

Seghers, Dieter; Loeckx, Dirk; Maes, Frederik; Suetens, Paul

2006-03-01

A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.

Worldwide Occurrence of Mycotoxins in Cereals and Cereal-Derived Food Products: Public Health Perspectives of Their Co-occurrence.

PubMed

Lee, Hyun Jung; Ryu, Dojin

2017-08-23

Cereal grains and their processed food products are frequently contaminated with mycotoxins. Among many, five major mycotoxins of aflatoxins, ochratoxins, fumonisins, deoxynivalenol, and zearalenone are of significant public health concern as they can cause adverse effects in humans. Being airborne or soilborne, the cosmopolitan nature of mycotoxigenic fungi contribute to the worldwide occurrence of mycotoxins. On the basis of the global occurrence data reported during the past 10 years, the incidences and maximum levels in raw cereal grains were 55% and 1642 μg/kg for aflatoxins, 29% and 1164 μg/kg for ochratoxin A, 61% and 71,121 μg/kg for fumonisins, 58% and 41,157 μg/kg, for deoxynivalenol, and 46% and 3049 μg/kg for zearalenone. The concentrations of mycotoxins tend to be lower in processed food products; the incidences varied depending on the individual mycotoxins, possibly due to the varying stability during processing and distribution of mycotoxins. It should be noted that more than one mycotoxin, produced by a single or several fungal species, may occur in various combinations in a given sample or food. Most studies reported additive or synergistic effects, suggesting that these mixtures may pose a significant threat to public health, particularly to infants and young children. Therefore, information on the co-occurrence of mycotoxins and their interactive toxicity is summarized in this paper.

Characteristics of cirrus clouds and tropical tropopause layer: Seasonal variation and long-term trends

NASA Astrophysics Data System (ADS)

Pandit, Amit Kumar; Gadhavi, Harish; Ratnam, M. Venkat; Jayaraman, A.; Raghunath, K.; Rao, S. Vijaya Bhaskara

2014-12-01

In the present study, characteristics of tropical cirrus clouds observed during 1998-2013 using a ground-based lidar located at Gadanki (13.5°N, 79.2°E), India, are presented. Altitude occurrences of cirrus clouds as well as its top and base heights are estimated using the advanced mathematical tool, wavelet covariance transform (WCT). The association of observed cirrus cloud properties with the characteristics of tropical tropopause layer (TTL) is investigated using co-located radiosonde measurements available since 2006. In general, cirrus clouds occurred for about 44% of the total lidar observation time (6246 h). The most probable altitude at which cirrus clouds occurr is 14.5 km. The occurrence of cirrus clouds exhibited a strong seasonal dependence with maximum occurrence during monsoon season (76%) and minimum occurrence during winter season (33%) which is consistent with the results reported recently using space-based lidar measurements. Most of the time, cirrus top was located within the TTL (between cold point and convective outflow level) while cirrus base occurred near the convective outflow level. The geometrical thickness of the cirrus cloud is found to be higher during monsoon season compared to winter and there exists a weak inverse relation with TTL thickness. During the observation period the percentage occurrence of cirrus clouds near the tropopause showed an 8.4% increase at 70% confidence level. In the last 16 years, top and base heights of cirrus cloud increased by 0.56 km and 0.41 km, respectively.

Daily co-occurrence of alcohol use and high-risk sexual behavior among heterosexual, heavy drinking emergency department patients.

PubMed

Wray, Tyler B; Celio, Mark A; Kahler, Christopher W; Barnett, Nancy P; Mastroleo, Nadine R; Operario, Don; Monti, Peter M

2015-07-01

Global association and experimental studies suggest that alcohol use may increase sexual behavior that poses risk for exposure to sexually transmitted infections (STI) among heterosexual men and women. However, results from longitudinal and daily recall studies exploring the co-occurrence of alcohol use with various sexual risk outcomes in more naturalistic contexts have been mixed, and the bulk of this research has focused on college students. The current study enrolled heavy-drinking emergency department (ED) patients and used a cross-sectional, 30-day Timeline Followback (TLFB) method to examine the daily co-occurrence between alcohol use and three sexual behavior outcomes: Any sex, unprotected intercourse (UI), and UI with casual partners (versus protected intercourse [PI] with casual partners, or UI/PI with steady partners). Results indicated that increasing levels of alcohol use on a given day increased the odds of engaging in any sexual activity and that heavy drinking (but not very heavy drinking) on a given day was associated with an increased odds of engaging in UI with either steady or casual partners. However, day-level alcohol use was not associated with an increased odds of UI with casual partners. These findings suggest that alcohol may play an important role in increasing risk for HIV/STIs among heterosexuals, and support the continued need to target heavy drinking in sex risk reduction interventions. However, our results also suggest that alcohol may not universally result in unprotected sex with casual partners, a behavior posing perhaps the highest risk for HIV/STI transmission. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modeling trophic dependencies and exchanges among insects' bacterial symbionts in a host-simulated environment.

PubMed

Opatovsky, Itai; Santos-Garcia, Diego; Ruan, Zhepu; Lahav, Tamar; Ofaim, Shany; Mouton, Laurence; Barbe, Valérie; Jiang, Jiandong; Zchori-Fein, Einat; Freilich, Shiri

2018-05-25

Individual organisms are linked to their communities and ecosystems via metabolic activities. Metabolic exchanges and co-dependencies have long been suggested to have a pivotal role in determining community structure. In phloem-feeding insects such metabolic interactions with bacteria enable complementation of their deprived nutrition. The phloem-feeding whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) harbors an obligatory symbiotic bacterium, as well as varying combinations of facultative symbionts. This well-defined bacterial community in B. tabaci serves here as a case study for a comprehensive and systematic survey of metabolic interactions within the bacterial community and their associations with documented occurrences of bacterial combinations. We first reconstructed the metabolic networks of five common B. tabaci symbionts genera (Portiera, Rickettsia, Hamiltonella, Cardinium and Wolbachia), and then used network analysis approaches to predict: (1) species-specific metabolic capacities in a simulated bacteriocyte-like environment; (2) metabolic capacities of the corresponding species' combinations, and (3) dependencies of each species on different media components. The predictions for metabolic capacities of the symbionts in the host environment were in general agreement with previously reported genome analyses, each focused on the single-species level. The analysis suggests several previously un-reported routes for complementary interactions and estimated the dependency of each symbiont in specific host metabolites. No clear association was detected between metabolic co-dependencies and co-occurrence patterns. The analysis generated predictions for testable hypotheses of metabolic exchanges and co-dependencies in bacterial communities and by crossing them with co-occurrence profiles, contextualized interaction patterns into a wider ecological perspective.

Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors

EPA Science Inventory

Part of the ecological risk assessment process involves examining the potential for environmental stressors and ecological receptors to co-occur across a landscape. In this study, we introduce a Bayesian joint modeling framework for use in evaluating and mapping the co-occurrence...

Impacts of elevated CO2 on exogenous Bacillus thuringiensis toxins and transgene expression in transgenic rice under different levels of nitrogen.

PubMed

Jiang, Shoulin; Lu, Yongqing; Dai, Yang; Qian, Lei; Muhammad, Adnan Bodlah; Li, Teng; Wan, Guijun; Parajulee, Megha N; Chen, Fajun

2017-11-07

Recent studies have highlighted great challenges of transgene silencing for transgenic plants facing climate change. In order to understand the impacts of elevated CO 2 on exogenous Bacillus thuringiensis (Bt) toxins and transgene expression in transgenic rice under different levels of N-fertilizer supply, we investigated the biomass, exogenous Bt toxins, Bt-transgene expression and methylation status in Bt rice exposed to two levels of CO 2 concentrations and nitrogen (N) supply (1/8, 1/4, 1/2, 1 and 2 N). It is elucidated that the increased levels of global atmospheric CO 2 concentration will trigger up-regulation of Bt toxin expression in transgenic rice, especially with appropriate increase of N fertilizer supply, while, to some extent, the exogenous Bt-transgene expression is reduced at sub-N levels (1/4 and 1/2N), even though the total protein of plant tissues is reduced and the plant growth is restricted. The unpredictable and stochastic occurrence of transgene silencing and epigenetic alternations remains unresolved for most transgenic plants. It is expected that N fertilization supply may promote the expression of transgenic Bt toxin in transgenic Bt rice, particularly under elevated CO 2 .

Parental Physical and Psychological Aggression: Psychological Symptoms in Young Adults

ERIC Educational Resources Information Center

Miller-Perrin, Cindy L.; Perrin, Robin D.; Kocur, Jodie L.

2009-01-01

Objective: The purpose of the present study was to evaluate the relationship between various levels of parent-child physical violence and psychological symptoms reported by college students, while controlling for demographic variables, severity and frequency of violence, and co-occurrence of parental psychological aggression. Method: Participants…

Attention Functioning among Adolescents with Multiple Learning, Attentional, Behavioral, and Emotional Difficulties

ERIC Educational Resources Information Center

Shalev, Lilach; Kolodny, Tamar; Shalev, Nir; Mevorach, Carmel

2016-01-01

Attention-deficit/hyperactivity disorder (ADHD) is characterized by high levels of inattention, hyperactivity, and impulsivity; however, these symptoms can result from a variety of reasons. To obtain a comprehensive understanding of the various difficulties of individuals with ADHD, especially when co-occurrence difficulties are present, it is…

"Mr. Database" : Jim Gray and the History of Database Technologies.

PubMed

Hanwahr, Nils C

2017-12-01

Although the widespread use of the term "Big Data" is comparatively recent, it invokes a phenomenon in the developments of database technology with distinct historical contexts. The database engineer Jim Gray, known as "Mr. Database" in Silicon Valley before his disappearance at sea in 2007, was involved in many of the crucial developments since the 1970s that constitute the foundation of exceedingly large and distributed databases. Jim Gray was involved in the development of relational database systems based on the concepts of Edgar F. Codd at IBM in the 1970s before he went on to develop principles of Transaction Processing that enable the parallel and highly distributed performance of databases today. He was also involved in creating forums for discourse between academia and industry, which influenced industry performance standards as well as database research agendas. As a co-founder of the San Francisco branch of Microsoft Research, Gray increasingly turned toward scientific applications of database technologies, e. g. leading the TerraServer project, an online database of satellite images. Inspired by Vannevar Bush's idea of the memex, Gray laid out his vision of a Personal Memex as well as a World Memex, eventually postulating a new era of data-based scientific discovery termed "Fourth Paradigm Science". This article gives an overview of Gray's contributions to the development of database technology as well as his research agendas and shows that central notions of Big Data have been occupying database engineers for much longer than the actual term has been in use.

Dynamics of fertility impairment in childhood brain tumour survivors.

PubMed

Pfitzer, C; Chen, C-M; Wessel, T; Keil, T; Sörgel, A; Langer, T; Steinmann, D; Borgmann-Staudt, A

2014-10-01

Fertility impairment and recovery after chemo- and radiotherapy have been reported in both male and female childhood cancer survivors, but little is known about the dynamics. Our aim, therefore, was to describe the development of fertility impairment and possible recovery in childhood brain tumour survivors. In this longitudinal study, we included 144 survivors, who were treated in two German paediatric oncology centres between 2000 and 2005. Fertility parameters were retrieved from medical records up to 12 years after diagnosis. Participants with age ≥13 years and formerly cranial irradiation ≥30 Gray (n = 23), including 83 % (n = 19) with craniospinal irradiation ≥30 Gray, had a higher median FSH concentration compared to 29 patients without chemoradiotherapy: 8.3 IU/l (IQR 6.5-11.2) versus 4.1 IU/l (IQR 3.2-5.1) 2 years after initial treatment; 8.9 IU/l (IQR 8.5-10.8) versus 4.2 IU/l (IQR 2.4-6.7) after 8 years; and 7.1 IU/l (IQR 6.7-7.7) versus 3.5 IU/l (IQR 2.8-4.2) after 10 years. Altogether, 11/65 women reported the occurrence of amenorrhoea 6.0 years (range 1-10) after diagnosis. Five of these women later developed a regular menstrual cycle without hormone replacement therapy. Patients' chance of recovery from fertility impairment was increased with time since diagnosis (p = 0.074). Signs of fertility impairment such as amenorrhoea and elevated FSH levels were observed at variable time points between 1 and 12 years after chemoradiotherapy. Decreasing FSH levels were observed 1-7 years after elevation and were interpreted either as an atrophy of the pituitary gland or as recovery from fertility impairment.

18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

PubMed

Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

2017-11-01

The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.

Joint estimation of habitat dynamics and species interactions: disturbance reduces co-occurrence of non-native predators with an endangered toad.

PubMed

Miller, David A W; Brehme, Cheryl S; Hines, James E; Nichols, James D; Fisher, Robert N

2012-11-01

1. Ecologists have long been interested in the processes that determine patterns of species occurrence and co-occurrence. Potential short-comings of many existing empirical approaches that address these questions include a reliance on patterns of occurrence at a single time point, failure to account properly for imperfect detection and treating the environment as a static variable. 2. We fit detection and non-detection data collected from repeat visits using a dynamic site occupancy model that simultaneously accounts for the temporal dynamics of a focal prey species, its predators and its habitat. Our objective was to determine how disturbance and species interactions affect the co-occurrence probabilities of an endangered toad and recently introduced non-native predators in stream breeding habitats. For this, we determined statistical support for alternative processes that could affect co-occurrence frequency in the system. 3. We collected occurrence data at stream segments in two watersheds where streams were largely ephemeral and one watershed dominated by perennial streams. Co-occurrence probabilities of toads with non-native predators were related to disturbance frequency, with low co-occurrence in the ephemeral watershed and high co-occurrence in the perennial watershed. This occurred because once predators were established at a site, they were rarely lost from the site except in cases when the site dried out. Once dry sites became suitable again, toads colonized them much more rapidly than predators, creating a period of predator-free space. 4. We attribute the dynamics to a storage effect, where toads persisting outside the stream environment during periods of drought rapidly colonized sites when they become suitable again. Our results support that even in highly connected stream networks, temporal disturbance can structure frequencies with which breeding amphibians encounter non-native predators. 5. Dynamic multi-state occupancy models are a powerful tool for rigorously examining hypotheses about inter-species and species-habitat interactions. In contrast to previous methods that infer dynamic processes based on static patterns in occupancy, the approach we took allows the dynamic processes that determine species-species and species-habitat interactions to be directly estimated. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

A Wireless and Batteryless Intelligent Carbon Monoxide Sensor.

PubMed

Chen, Chen-Chia; Sung, Gang-Neng; Chen, Wen-Ching; Kuo, Chih-Ting; Chue, Jin-Ju; Wu, Chieh-Ming; Huang, Chun-Ming

2016-09-23

Carbon monoxide (CO) poisoning from natural gas water heaters is a common household accident in Taiwan. We propose a wireless and batteryless intelligent CO sensor for improving the safety of operating natural gas water heaters. A micro-hydropower generator supplies power to a CO sensor without battery (COSWOB) (2.5 W at a flow rate of 4.2 L/min), and the power consumption of the COSWOB is only ~13 mW. The COSWOB monitors the CO concentration in ambient conditions around natural gas water heaters and transmits it to an intelligent gateway. When the CO level reaches a dangerous level, the COSWOB alarm sounds loudly. Meanwhile, the intelligent gateway also sends a trigger to activate Wi-Fi alarms and sends notifications to the mobile device through the Internet. Our strategy can warn people indoors and outdoors, thereby reducing CO poisoning accidents. We also believe that our technique not only can be used for home security but also can be used in industrial applications (for example, to monitor leak occurrence in a pipeline).

A Wireless and Batteryless Intelligent Carbon Monoxide Sensor

PubMed Central

Chen, Chen-Chia; Sung, Gang-Neng; Chen, Wen-Ching; Kuo, Chih-Ting; Chue, Jin-Ju; Wu, Chieh-Ming; Huang, Chun-Ming

2016-01-01

Carbon monoxide (CO) poisoning from natural gas water heaters is a common household accident in Taiwan. We propose a wireless and batteryless intelligent CO sensor for improving the safety of operating natural gas water heaters. A micro-hydropower generator supplies power to a CO sensor without battery (COSWOB) (2.5 W at a flow rate of 4.2 L/min), and the power consumption of the COSWOB is only ~13 mW. The COSWOB monitors the CO concentration in ambient conditions around natural gas water heaters and transmits it to an intelligent gateway. When the CO level reaches a dangerous level, the COSWOB alarm sounds loudly. Meanwhile, the intelligent gateway also sends a trigger to activate Wi-Fi alarms and sends notifications to the mobile device through the Internet. Our strategy can warn people indoors and outdoors, thereby reducing CO poisoning accidents. We also believe that our technique not only can be used for home security but also can be used in industrial applications (for example, to monitor leak occurrence in a pipeline). PMID:27669255

Association of white matter hyperintensities and gray matter volume with cognition in older individuals without cognitive impairment.

PubMed

Arvanitakis, Zoe; Fleischman, Debra A; Arfanakis, Konstantinos; Leurgans, Sue E; Barnes, Lisa L; Bennett, David A

2016-05-01

Both presence of white matter hyperintensities (WMH) and smaller total gray matter volume on brain magnetic resonance imaging (MRI) are common findings in old age, and contribute to impaired cognition. We tested whether total WMH volume and gray matter volume had independent associations with cognition in community-dwelling individuals without dementia or mild cognitive impairment (MCI). We used data from participants of the Rush Memory and Aging Project. Brain MRI was available in 209 subjects without dementia or MCI (mean age 80; education = 15 years; 74 % women). WMH and gray matter were automatically segmented, and the total WMH and gray matter volumes were measured. Both MRI-derived measures were normalized by the intracranial volume. Cognitive data included composite measures of five different cognitive domains, based on 19 individual tests. Linear regression analyses, adjusted for age, sex, and education, were used to examine the relationship of logarithmically-transformed total WMH volume and of total gray matter volume to cognition. Larger total WMH volumes were associated with lower levels of perceptual speed (p < 0.001), but not with episodic memory, semantic memory, working memory, or visuospatial abilities (all p > 0.10). Smaller total gray matter volumes were associated with lower levels of perceptual speed (p = 0.013) and episodic memory (p = 0.001), but not with the other three cognitive domains (all p > 0.14). Larger total WMH volume was correlated with smaller total gray matter volume (p < 0.001). In a model with both MRI-derived measures included, the relation of WMH to perceptual speed remained significant (p < 0.001), while gray matter volumes were no longer related (p = 0.14). This study of older community-dwelling individuals without overt cognitive impairment suggests that the association of larger total WMH volume with lower perceptual speed is independent of total gray matter volume. These results help elucidate the pathological processes leading to lower cognitive function in aging.

Dynamic texture recognition using local binary patterns with an application to facial expressions.

PubMed

Zhao, Guoying; Pietikäinen, Matti

2007-06-01

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

Co-Occurrence Patterns of Common and Rare Leaf-Litter Frogs, Epiphytic Ferns and Dung Beetles across a Gradient of Human Disturbance

PubMed Central

Oldekop, Johan A.; Bebbington, Anthony J.; Truelove, Nathan K.; Tysklind, Niklas; Villamarín, Santiago; Preziosi, Richard F.

2012-01-01

Indicator taxa are commonly used to identify priority areas for conservation or to measure biological responses to environmental change. Despite their widespread use, there is no general consensus about the ability of indicator taxa to predict wider trends in biodiversity. Many studies have focused on large-scale patterns of species co-occurrence to identify areas of high biodiversity, threat or endemism, but there is much less information about patterns of species co-occurrence at local scales. In this study, we assess fine-scale co-occurrence patterns of three indicator taxa (epiphytic ferns, leaf litter frogs and dung beetles) across a remotely sensed gradient of human disturbance in the Ecuadorian Amazon. We measure the relative contribution of rare and common species to patterns of total richness in each taxon and determine the ability of common and rare species to act as surrogate measures of human disturbance and each other. We find that the species richness of indicator taxa changed across the human disturbance gradient but that the response differed among taxa, and between rare and common species. Although we find several patterns of co-occurrence, these patterns differed between common and rare species. Despite showing complex patterns of species co-occurrence, our results suggest that species or taxa can act as reliable indicators of each other but that this relationship must be established and not assumed. PMID:22701730

Statistical power to detect change in a mangrove shoreline fish community adjacent to a nuclear power plant.

PubMed

Dolan, T E; Lynch, P D; Karazsia, J L; Serafy, J E

2016-03-01

An expansion is underway of a nuclear power plant on the shoreline of Biscayne Bay, Florida, USA. While the precise effects of its construction and operation are unknown, impacts on surrounding marine habitats and biota are considered by experts to be likely. The objective of the present study was to determine the adequacy of an ongoing monitoring survey of fish communities associated with mangrove habitats directly adjacent to the power plant to detect fish community changes, should they occur, at three spatial scales. Using seasonally resolved data recorded during 532 fish surveys over an 8-year period, power analyses were performed for four mangrove fish metrics (fish diversity, fish density, and the occurrence of two ecologically important fish species: gray snapper (Lutjanus griseus) and goldspotted killifish (Floridichthys carpio). Results indicated that the monitoring program at current sampling intensity allows for detection of <33% changes in fish density and diversity metrics in both the wet and the dry season in the two larger study areas. Sampling effort was found to be insufficient in either season to detect changes at this level (<33%) in species-specific occurrence metrics for the two fish species examined. The option of supplementing ongoing, biological monitoring programs for improved, focused change detection deserves consideration from both ecological and cost-benefit perspectives.

Type and Degree of Co-Occurrence of the Educational Communication in a Community of Inquiry

ERIC Educational Resources Information Center

Gutiérrez-Santiuste, Elba; Gallego-Arrufat, María-Jesús

2017-01-01

The study analyzes the type and quantity of co-occurrence of social, cognitive, and teaching presence in a Community of Inquiry (CoI). Content analysis of the virtual educational communication shows units of analysis that must be assigned to more than one category. By crossing the categories of the CoI model, we observe that Social Presence is…

Detection of LSB+/-1 steganography based on co-occurrence matrix and bit plane clipping

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Aghaeinia, Hassan; Faez, Karim; Mehrabi, Mohammad Ali

2010-01-01

Spatial LSB+/-1 steganography changes smooth characteristics between adjoining pixels of the raw image. We present a novel steganalysis method for LSB+/-1 steganography based on feature vectors derived from the co-occurrence matrix in the spatial domain. We investigate how LSB+/-1 steganography affects the bit planes of an image and show that it changes more least significant bit (LSB) planes of it. The co-occurrence matrix is derived from an image in which some of its most significant bit planes are clipped. By this preprocessing, in addition to reducing the dimensions of the feature vector, the effects of embedding were also preserved. We compute the co-occurrence matrix in different directions and with different dependency and use the elements of the resulting co-occurrence matrix as features. This method is sensitive to the data embedding process. We use a Fisher linear discrimination (FLD) classifier and test our algorithm on different databases and embedding rates. We compare our scheme with the current LSB+/-1 steganalysis methods. It is shown that the proposed scheme outperforms the state-of-the-art methods in detecting the LSB+/-1 steganographic method for grayscale images.

Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects.

PubMed

Brunellière, Angèle; Perre, Laetitia; Tran, ThiMai; Bonnotte, Isabelle

2017-09-01

In recent decades, many computational techniques have been developed to analyse the contextual usage of words in large language corpora. The present study examined whether the co-occurrence frequency obtained from large language corpora might boost purely semantic priming effects. Two experiments were conducted: one with conscious semantic priming, the other with subliminal semantic priming. Both experiments contrasted three semantic priming contexts: an unrelated priming context and two related priming contexts with word pairs that are semantically related and that co-occur either frequently or infrequently. In the conscious priming presentation (166-ms stimulus-onset asynchrony, SOA), a semantic priming effect was recorded in both related priming contexts, which was greater with higher co-occurrence frequency. In the subliminal priming presentation (66-ms SOA), no significant priming effect was shown, regardless of the related priming context. These results show that co-occurrence frequency boosts pure semantic priming effects and are discussed with reference to models of semantic network.

Using Co-Occurrence to Evaluate Belief Coherence in a Large Non Clinical Sample

PubMed Central

Pechey, Rachel; Halligan, Peter

2012-01-01

Much of the recent neuropsychological literature on false beliefs (delusions) has tended to focus on individual or single beliefs, with few studies actually investigating the relationship or co-occurrence between different types of co-existing beliefs. Quine and Ullian proposed the hypothesis that our beliefs form an interconnected web in which the beliefs that make up that system must somehow “cohere” with one another and avoid cognitive dissonance. As such beliefs are unlikely to be encapsulated (i.e., exist in isolation from other beliefs). The aim of this preliminary study was to empirically evaluate the probability of belief co-occurrence as one indicator of coherence in a large sample of subjects involving three different thematic sets of beliefs (delusion-like, paranormal & religious, and societal/cultural). Results showed that the degree of belief co-endorsement between beliefs within thematic groupings was greater than random occurrence, lending support to Quine and Ullian’s coherentist account. Some associations, however, were relatively weak, providing for well-established examples of cognitive dissonance. PMID:23155383

High fidelity chemistry and radiation modeling for oxy -- combustion scenarios

NASA Astrophysics Data System (ADS)

Abdul Sater, Hassan A.

To account for the thermal and chemical effects associated with the high CO2 concentrations in an oxy-combustion atmosphere, several refined gas-phase chemistry and radiative property models have been formulated for laminar to highly turbulent systems. This thesis examines the accuracies of several chemistry and radiative property models employed in computational fluid dynamic (CFD) simulations of laminar to transitional oxy-methane diffusion flames by comparing their predictions against experimental data. Literature review about chemistry and radiation modeling in oxy-combustion atmospheres considered turbulent systems where the predictions are impacted by the interplay and accuracies of the turbulence, radiation and chemistry models. Thus, by considering a laminar system we minimize the impact of turbulence and the uncertainties associated with turbulence models. In the first section of this thesis, an assessment and validation of gray and non-gray formulations of a recently proposed weighted-sum-of-gray gas model in oxy-combustion scenarios was undertaken. Predictions of gas, wall temperatures and flame lengths were in good agreement with experimental measurements. The temperature and flame length predictions were not sensitive to the radiative property model employed. However, there were significant variations between the gray and non-gray model radiant fraction predictions with the variations in general increasing with decrease in Reynolds numbers possibly attributed to shorter flames and steeper temperature gradients. The results of this section confirm that non-gray model predictions of radiative heat fluxes are more accurate than gray model predictions especially at steeper temperature gradients. In the second section, the accuracies of three gas-phase chemistry models were assessed by comparing their predictions against experimental measurements of temperature, species concentrations and flame lengths. The chemistry was modeled employing the Eddy Dissipation Concept (EDC) employing a 41-step detailed chemistry mechanism, the non-adiabatic extension of the equilibrium Probability Density Function (PDF) based mixture-fraction model and a two-step global finite rate chemistry model with modified rate constants proposed to work well in oxy-methane flames. Based on the results from this section, the equilibrium PDF model in conjunction with a high-fidelity non-gray model for the radiative properties of the gas-phase may be deemed as accurate to capture the major gas species concentrations, temperatures and flame lengths in oxy-methane flames. The third section examines the variations in radiative transfer predictions due to the choice of chemistry and gas-phase radiative property models. The radiative properties were estimated employing four weighted-sum-of-gray-gases models (WSGGM) that were formulated employing different spectroscopic/model databases. An average variation of 14 -- 17% in the wall incident radiative fluxes was observed between the EDC and equilibrium mixture fraction chemistry models, due to differences in their temperature predictions within the flame. One-dimensional, line-of-sight radiation calculations showed a 15 -- 25 % reduction in the directional radiative fluxes at lower axial locations as a result of ignoring radiation from CO and CH4. Under the constraints of fixed temperature and species distributions, the flame radiant power estimates and average wall incident radiative fluxes varied by nearly 60% and 11% respectively among the different WSGG models.

Radiative interactions in molecular gases under local and nonlocal thermodynamic equilibrium conditions

NASA Technical Reports Server (NTRS)

Tiwari, S. N.; Jha, M. K.

1993-01-01

Basic formulations, analyses, and numerical procedures are presented to investigate radiative heat interactions in diatomic and polyatomic gases under local and nonlocal thermodynamic equilibrium conditions. Essential governing equations are presented for both gray and nongray gases. Information is provided on absorption models, relaxation times, and transfer equations. Radiative flux equations are developed which are applicable under local and nonlocal thermodynamic equilibrium conditions. The problem is solved for fully developed laminar incompressible flows between two parallel plates under the boundary condition of a uniform surface heat flux. For specific applications, three diatomic and three polyatomic gases are considered. The results are obtained numerically by employing the method of variation of parameters. The results are compared under local and nonlocal thermodynamic equilibrium conditions at different temperature and pressure conditions. Both gray and nongray studies are conducted extensively for all molecular gases considered. The particular gases selected for this investigation are CO, NO, OH, CO2, H2O, and CH4. The temperature and pressure range considered are 300-2000 K and 0.1-10 atmosphere, respectively. In general, results demonstrate that the gray gas approximation overestimates the effect of radiative interaction for all conditions. The conditions of NLTE, however, result in underestimation of radiative interactions. The method developed for this study can be extended to solve complex problems of radiative heat transfer involving nonequilibrium phenomena.

Antecedents of Gray Divorce: A Life Course Perspective.

PubMed

Lin, I-Fen; Brown, Susan L; Wright, Matthew R; Hammersmith, Anna M

2016-12-16

Increasingly, older adults are experiencing divorce, yet little is known about the risk factors associated with divorce after age 50 (termed "gray divorce"). Guided by a life course perspective, our study examined whether key later life turning points are related to gray divorce. We used data from the 1998-2012 Health and Retirement Study to conduct a prospective, couple-level discrete-time event history analysis of the antecedents of gray divorce. Our models incorporated key turning points (empty nest, retirement, and poor health) as well as demographic characteristics and economic resources. Contrary to our expectations, the onset of an empty nest, the wife's or husband's retirement, and the wife's or husband's chronic conditions were unrelated to the likelihood of gray divorce. Rather, factors traditionally associated with divorce among younger adults were also salient for older adults. Marital duration, marital quality, home ownership, and wealth were negatively related to the risk of gray divorce. Gray divorce is especially likely to occur among couples who are socially and economically disadvantaged, raising new questions about the consequences of gray divorce for individual health and well-being. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-04-01

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

At-risk depressive symptoms and alcohol use trajectories in adolescence: a person-centred analysis of co-occurrence.

PubMed

Willoughby, Teena; Fortner, Adrian

2015-04-01

Long-term longitudinal studies that examine whether there are distinct trajectories of at-risk depressive symptoms and alcohol use across the high school years (e.g., high co-occurrence) are rare in normative samples of adolescent boys and girls; yet, this assessment is of critical importance for developing effective prevention and intervention strategies. Moreover, the role of self-regulation and novelty-seeking behavior in differentiating among distinct subgroups of adolescents is not clear. To address these gaps, the present study sought to identify subgroups of adolescent boys and girls that indicated at-risk trajectories across the high school years for both depressive symptoms and alcohol use, and examined the role of delay of gratification and novelty seeking at baseline in differentiating among the subgroups. Canadian adolescents (N = 4,412; 49 % female) were surveyed at four time points (grades 9, 10, 11, and 12). Parallel process latent class growth analyses revealed four distinct subgroups for both boys and girls, encompassing high co-occurrence, depressive symptoms only, alcohol use only, and low co-occurrence. Across gender, delay of gratification at baseline differentiated among the four subgroups, with the High Co-Occurrence Group group scoring the lowest and the Low Co-Occurrence Group the highest. Lower novelty-seeking scores at baseline were associated more with being in the Depressive Symptoms Only Group relative to the other groups, particularly the Alcohol Use Only Group for boys. Thus, delay of gratification and novelty seeking may be useful in identifying youth at risk for co-occurring depressive symptoms and alcohol use trajectories, as well as at-risk trajectories for only one of these behaviors.

A Case for Hydrothermal Gray Hematite in Aram Chaos

NASA Technical Reports Server (NTRS)

Catling, D. C.; Moore, J. M.

2003-01-01

The Thermal Emission Spectrometer (TES) on Mars Global Surveyor has detected deposits of coarsegrained, gray crystalline hematite in Sinus Meridiani, Aram Chaos, and Vallis Marineris [1]. Detailed features in the hematite spectral signature of the Sinus Meridiani region show that the spectrum is consistent with emission dominated by crystal c-faces of hematite, implying that the hematite is specular [2]. Gray specular hematite (also known as specularite ) is a particular gray crystalline form that has intergrown, hexagonal plates with a silvery metallic luster. We believe that the key to the origin of specularite is that it requires crystallization at temperatures in excess of about 100 C. In reviewing the occurrence of gray hematite on Earth, we find no exceptions to this warm temperature requirement [3]. Thermal crystallization on Mars could occur (1) as diagenesis at a depth of a few kilometers of sediments originally formed in lowtemperature waters, or (2) as direct precipitation from hydrothermal solution. Aram Chaos has unique chaotic terrain that offers more clues to the formation of the hematite than the relatively featureless flat terrain (as seen from orbit) of Sinus Meridiani. Aram Chaos provides the opportunity to look at a combination of TES data, Mars Orbiter Camera images, and Mars Orbiter Laser Altimeter (MOLA) topography. This combination of data suggests that high concentrations of hematite were formed in planar strata and have since been exposed by erosion of an overlying light-toned, caprock. Lesser concentrations of hematite are found adjacent to these strata at lower elevations, which we interpret as perhaps a lag deposit. The topography and the collapsed nature of the chaotic terrain favor a hydrothermally charged aquifer as the original setting where the hematite formed. An alternative sedimentary origin requires post-depositional burial to a depth of 3-5 km to induce thermally driven recrystallization of fine-grained iron oxides to coarse-grained hematite.

Calibration Methods for a 3D Triangulation Based Camera

NASA Astrophysics Data System (ADS)

Schulz, Ulrike; Böhnke, Kay

A sensor in a camera takes a gray level image (1536 x 512 pixels), which is reflected by a reference body. The reference body is illuminated by a linear laser line. This gray level image can be used for a 3D calibration. The following paper describes how a calibration program calculates the calibration factors. The calibration factors serve to determine the size of an unknown reference body.

Quantitative co-occurrence of sesquiterpenes; a tool for elucidating their biosynthesis in Indian sandalwood, Santalum album.

PubMed

Jones, Christopher G; Ghisalberti, Emilio L; Plummer, Julie A; Barbour, Elizabeth L

2006-11-01

A chemotaxonomic approach was used to investigate biosynthetic relationships between heartwood sesquiterpenes in Indian sandalwood, Santalum album L. Strong, linear relationships exist between four structural classes of sesquiterpenes; alpha- and beta-santalenes and bergamotene; gamma- and beta-curcumene; beta-bisabolene and alpha-bisabolol and four unidentified sesquiterpenes. All samples within the heartwood yielded the same co-occurrence patterns, however wood from young trees tended to be more variable. It is proposed that the biosynthesis of each structural class of sesquiterpene in sandalwood oil is linked through common carbocation intermediates. Lack of co-occurrence between each structural class suggests that four separate cyclase enzymes may be operative. The biosynthesis of sandalwood oil sesquiterpenes is discussed with respect to these co-occurrence patterns. Extractable oil yield was correlated to heartwood content of each wood core and the oil composition did not vary significantly throughout the tree.

Quantitative analysis of ultrasonic images of fibrotic liver using co-occurrence matrix based on multi-Rayleigh model

NASA Astrophysics Data System (ADS)

Isono, Hiroshi; Hirata, Shinnosuke; Hachiya, Hiroyuki

2015-07-01

In medical ultrasonic images of liver disease, a texture with a speckle pattern indicates a microscopic structure such as nodules surrounded by fibrous tissues in hepatitis or cirrhosis. We have been applying texture analysis based on a co-occurrence matrix to ultrasonic images of fibrotic liver for quantitative tissue characterization. A co-occurrence matrix consists of the probability distribution of brightness of pixel pairs specified with spatial parameters and gives new information on liver disease. Ultrasonic images of different types of fibrotic liver were simulated and the texture-feature contrast was calculated to quantify the co-occurrence matrices generated from the images. The results show that the contrast converges with a value that can be theoretically estimated using a multi-Rayleigh model of echo signal amplitude distribution. We also found that the contrast value increases as liver fibrosis progresses and fluctuates depending on the size of fibrotic structure.

Crossover Patterning by the Beam-Film Model: Analysis and Implications

PubMed Central

Zhang, Liangran; Liang, Zhangyi; Hutchinson, John; Kleckner, Nancy

2014-01-01

Crossing-over is a central feature of meiosis. Meiotic crossover (CO) sites are spatially patterned along chromosomes. CO-designation at one position disfavors subsequent CO-designation(s) nearby, as described by the classical phenomenon of CO interference. If multiple designations occur, COs tend to be evenly spaced. We have previously proposed a mechanical model by which CO patterning could occur. The central feature of a mechanical mechanism is that communication along the chromosomes, as required for CO interference, can occur by redistribution of mechanical stress. Here we further explore the nature of the beam-film model, its ability to quantitatively explain CO patterns in detail in several organisms, and its implications for three important patterning-related phenomena: CO homeostasis, the fact that the level of zero-CO bivalents can be low (the “obligatory CO”), and the occurrence of non-interfering COs. Relationships to other models are discussed. PMID:24497834

Understanding comorbidity among internalizing problems: Integrating latent structural models of psychopathology and risk mechanisms

PubMed Central

Hankin, Benjamin L.; Snyder, Hannah R.; Gulley, Lauren D.; Schweizer, Tina H.; Bijttebier, Patricia; Nelis, Sabine; Toh, Gim; Vasey, Michael W.

2016-01-01

It is well known that comorbidity is the rule, not the exception, for categorically defined psychiatric disorders, and this is also the case for internalizing disorders of depression and anxiety. This theoretical review paper addresses the ubiquity of comorbidity among internalizing disorders. Our central thesis is that progress in understanding this co-occurrence can be made by employing latent dimensional structural models that organize both psychopathology as well as vulnerabilities and risk mechanisms and by connecting the multiple levels of risk and psychopathology outcomes together. Different vulnerabilities and risk mechanisms are hypothesized to predict different levels of the structural model of psychopathology. We review the present state of knowledge based on concurrent and developmental sequential comorbidity patterns among common discrete psychiatric disorders in youth, and then we advocate for the use of more recent bifactor dimensional models of psychopathology (e.g., p factor, Caspi et al., 2014) that can help to explain the co-occurrence among internalizing symptoms. In support of this relatively novel conceptual perspective, we review six exemplar vulnerabilities and risk mechanisms, including executive function, information processing biases, cognitive vulnerabilities, positive and negative affectivity aspects of temperament, and autonomic dysregulation, along with the developmental occurrence of stressors in different domains, to show how these vulnerabilities can predict the general latent psychopathology factor, a unique latent internalizing dimension, as well as specific symptom syndrome manifestations. PMID:27739389

Powdery mildew suppresses herbivore-induced plant volatiles and interferes with parasitoid attraction in Brassica rapa

USDA-ARS?s Scientific Manuscript database

The co-occurrence of different antagonists on a plant can greatly affect infochemicals with ecological consequences for higher trophic levels. Here we investigated how the presence of a plant pathogen, the powdery mildew Erysiphe cruciferarum, on Brassica rapa affects 1) plant volatiles emitted in r...

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.

Mining co-occurrence and sequence patterns from cancer diagnoses in New York State.

PubMed

Wang, Yu; Hou, Wei; Wang, Fusheng

2018-01-01

The goal of this study is to discover disease co-occurrence and sequence patterns from large scale cancer diagnosis histories in New York State. In particular, we want to identify disparities among different patient groups. Our study will provide essential knowledge for clinical researchers to further investigate comorbidities and disease progression for improving the management of multiple diseases. We used inpatient discharge and outpatient visit records from the New York State Statewide Planning and Research Cooperative System (SPARCS) from 2011-2015. We grouped each patient's visit history to generate diagnosis sequences for seven most popular cancer types. We performed frequent disease co-occurrence mining using the Apriori algorithm, and frequent disease sequence patterns discovery using the cSPADE algorithm. Different types of cancer demonstrated distinct patterns. Disparities of both disease co-occurrence and sequence patterns were observed from patients within different age groups. There were also considerable disparities in disease co-occurrence patterns with respect to different claim types (i.e., inpatient, outpatient, emergency department and ambulatory surgery). Disparities regarding genders were mostly found where the cancer types were gender specific. Supports of most patterns were usually higher for males than for females. Compared with secondary diagnosis codes, primary diagnosis codes can convey more stable results. Two disease sequences consisting of the same diagnoses but in different orders were usually with different supports. Our results suggest that the methods adopted can generate potentially interesting and clinically meaningful disease co-occurrence and sequence patterns, and identify disparities among various patient groups. These patterns could imply comorbidities and disease progressions.

Prevalence and factors associated with the co-occurrence of health risk behaviors in adolescents

PubMed Central

Brito, Anísio Luiz da Silva; Hardman, Carla Meneses; de Barros, Mauro Virgílio Gomes

2015-01-01

Objective: To analyze the prevalence and factors associated with the co-occurrence of health risk behaviors in adolescents. Methods: A cross-sectional study was performed with a sample of high school students from state public schools in Pernambuco, Brazil (n=4207, 14-19 years old). Data were obtained using a questionnaire. The co-occurrence of health risk behaviors was established based on the sum of five behavioral risk factors (low physical activity, sedentary behavior, low consumption of fruits/vegetables, alcohol consumption and tobacco use). The independent variables were gender, age group, time of day attending school, school size, maternal education, occupational status, skin color, geographic region and place of residence. Data were analyzed by ordinal logistic regression with proportional odds model. Results: Approximately 10% of adolescents were not exposed to health risk behaviors, while 58.5% reported being exposed to at least two health risk behaviors simultaneously. There was a higher likelihood of co-occurrence of health risk behaviors among adolescents in the older age group, with intermediate maternal education (9-11 years of schooling), and who reported living in the driest (semi-arid) region of the state of Pernambuco. Adolescents who reported having a job and living in rural areas had a lower likelihood of co-occurrence of risk behaviors. Conclusions: The findings suggest a high prevalence of co-occurrence of health risk behaviors in this group of adolescents, with a higher chance in five subgroups (older age, intermediate maternal education, the ones that reported not working, those living in urban areas and in the driest region of the state). PMID:26298656

Governance in Afghanistan: Context and Possibilities

DTIC Science & Technology

2011-05-19

Nathaniel. Russia in Central Asia in 1889 & the Anglo-Russian Question. London: Longmans, Green , and Co., 1889. Drage, Geoffrey. Russian Affairs. New York...Richard Bentley, 1839. Gray, John Alfred. At the Court of the Amir of Afghanistan. New York: Kegan Paul, 2002. Holdich, T. Hungerford. Through Central

Lesquerella seed and oil yield response to split-applied N fertilizer

USDA-ARS?s Scientific Manuscript database

Agronomic management information is critical for successfully commercial production of new crops such as lesquerella [lesquerella ferndleri Gray (Wats.)]. Response of lesquerella to six nitrogen (N) fertilizer rates under well-watered and water-stressed treatments were studied in irrigated desert co...

Multiple Assembly Rules Drive the Co-occurrence of Orthopteran and Plant Species in Grasslands: Combining Network, Functional and Phylogenetic Approaches

PubMed Central

Fournier, Bertrand; Mouly, Arnaud; Gillet, François

2016-01-01

Understanding the factors underlying the co-occurrence of multiple species remains a challenge in ecology. Biotic interactions, environmental filtering and neutral processes are among the main mechanisms evoked to explain species co-occurrence. However, they are most often studied separately or even considered as mutually exclusive. This likely hampers a more global understanding of species assembly. Here, we investigate the general hypothesis that the structure of co-occurrence networks results from multiple assembly rules and its potential implications for grassland ecosystems. We surveyed orthopteran and plant communities in 48 permanent grasslands of the French Jura Mountains and gathered functional and phylogenetic data for all species. We constructed a network of plant and orthopteran species co-occurrences and verified whether its structure was modular or nested. We investigated the role of all species in the structure of the network (modularity and nestedness). We also investigated the assembly rules driving the structure of the plant-orthopteran co-occurrence network by using null models on species functional traits, phylogenetic relatedness and environmental conditions. We finally compared our results to abundance-based approaches. We found that the plant-orthopteran co-occurrence network had a modular organization. Community assembly rules differed among modules for plants while interactions with plants best explained the distribution of orthopterans into modules. Few species had a disproportionately high positive contribution to this modular organization and are likely to have a key importance to modulate future changes. The impact of agricultural practices was restricted to some modules (3 out of 5) suggesting that shifts in agricultural practices might not impact the entire plant-orthopteran co-occurrence network. These findings support our hypothesis that multiple assembly rules drive the modular structure of the plant-orthopteran network. This modular structure is likely to play a key role in the response of grassland ecosystems to future changes by limiting the impact of changes in agricultural practices such as intensification to some modules leaving species from other modules poorly impacted. The next step is to understand the importance of this modular structure for the long-term maintenance of grassland ecosystem structure and functions as well as to develop tools to integrate network structure into models to improve their capacity to predict future changes. PMID:27582754

Seed viability detection using computerized false-color radiographic image enhancement

NASA Technical Reports Server (NTRS)

Vozzo, J. A.; Marko, Michael

1994-01-01

Seed radiographs are divided into density zones which are related to seed germination. The seeds which germinate have densities relating to false-color red. In turn, a seed sorter may be designed which rejects those seeds not having sufficient red to activate a gate along a moving belt containing the seed source. This results in separating only seeds with the preselected densities representing biological viability lending to germination. These selected seeds demand a higher market value. Actual false-coloring isn't required for a computer to distinguish the significant gray-zone range. This range can be predetermined and screened without the necessity of red imaging. Applying false-color enhancement is a means of emphasizing differences in densities of gray within any subject from photographic, radiographic, or video imaging. Within the 0-255 range of gray levels, colors can be assigned to any single level or group of gray levels. Densitometric values then become easily recognized colors which relate to the image density. Choosing a color to identify any given density allows separation by morphology or composition (form or function). Additionally, relative areas of each color are readily available for determining distribution of that density by comparison with other densities within the image.

Gray bats and pollution in Missouri and northern Alabama

USGS Publications Warehouse

Clark, D.R.; Bunck, C.M.; Cromartie, E.; LaVal, R.K.; Tuttle, M.D.

1981-01-01

Gray bats died with lethal brain concentrations of dieldrin and rising levels of heptachlor epoxide in 1976, 1977, and 1978 at Bat Caves No. 2-3, Franklin County, Missouri. The colony disappeared in 1979. Dieldrin was banned in 1974 and 1981 was the last year for heptachlor use in Missouri. The State is recommendiing three organophosphates (chlorpyrifos or Dursban, dyfonate or Fonophos, and ethoprop or Mocap) as substitutes for heptachlor. All three compounds have excellent records in the environment. Analyses of insects collected where bats of this colony fed showed beetles, particularly rove beetles (Staphylinidae), to be the most heavily contaminated part of the bat's diet. Lactation concentrated these residues so that levels in milk were approximately 30 times those in the insect diet. Gray bats found dead in caves in northern Alabama showed DDD (a DDT derivative) contamination. Bats from the colony at Cave Springs Cave on the Wheeler National Wildlife Refuge contained up to 29 ppm DDD in their brains, but this is probably less than one-half the lethal level. Bats from other colonies contained less. The DDD contamination enters the Terinessee River just above the Wheeler Refuge and is seen in gray bat colonies as far as 60 miles downriver.

Temporal dynamics and longitudinal co-occurrence of depression and different anxiety syndromes in youth: Evidence for reciprocal patterns in a 3-year prospective study.

PubMed

Long, Erin E; Young, Jami F; Hankin, Benjamin L

2018-07-01

Depression is highly comorbid with anxiety in youth. It is frequently reported that anxiety precedes depression; however, evidence surrounding the temporal precedence of anxiety over depression is mixed. Many studies of anxiety-depression co-occurrence lump distinct forms of anxiety, obscuring information regarding trajectories of specific anxiety syndromes. This study sought to more accurately describe the development of anxiety and depression over time by moving beyond the question of temporal precedence to investigate a developmentally dynamic model of anxiety-depression co-occurrence. A community sample of 665 youth (M= 11.8, SD= 2.4; 55% female) completed repeated self-report measures of depression and anxiety (social, physical, and separation anxiety) over a 3-year longitudinal study. Prospective associations between distinct syndromes of anxiety with depression were analyzed using an autoregressive cross-lagged path model over four time points. Physical symptoms and depression symptoms reciprocally predicted each other, above and beyond the stability of either domain. Social anxiety and depression symptoms similarly predicted each other in a systematic pattern. Our study is limited in its generalizability to other forms of anxiety, like worry. Additional research is needed to determine whether similar patterns exist in clinical populations, and whether these processes maintain symptoms once they reach diagnostic levels. The development of syndromes of depression, physical, and social anxiety during childhood and adolescence occurs in a predictable, systematic reciprocal pattern, rather than sequentially and unidirectionally (i.e., anxiety syndromes precede depression). Results are clinically useful for predicting risk for disorder, and demonstrate the necessity of tracking symptom levels across domains. Copyright © 2018 Elsevier B.V. All rights reserved.

Adaptive Electronic Camouflage Using Texture Synthesis

DTIC Science & Technology

2012-04-01

algorithm begins by computing the GLCMs, GIN and GOUT , of the input image (e.g., image of local environment) and output image (randomly generated...respectively. The algorithm randomly selects a pixel from the output image and cycles its gray-level through all values. For each value, GOUT is updated...The value of the selected pixel is permanently changed to the gray-level value that minimizes the error between GIN and GOUT . Without selecting a

Posttraumatic stress disorder symptoms in youth with vs without chronic pain.

PubMed

Noel, Melanie; Wilson, Anna C; Holley, Amy Lewandowski; Durkin, Lindsay; Patton, Michaela; Palermo, Tonya M

2016-10-01

Chronic pain and posttraumatic stress disorder (PTSD) symptoms have been found to co-occur in adults; however, research has not examined this co-occurrence in adolescence, when pediatric chronic pain often first emerges. The aims of this study were to compare the frequency and intensity of PTSD symptoms and stressful life events in cohorts of youth with (n = 95) and without (n = 100) chronic pain and their parents and to determine the association between PTSD symptoms, health-related quality of life, and pain symptoms within the chronic pain sample. All participants completed questionnaire measures through an online survey. Findings revealed that youth with chronic pain and their parents had significantly higher levels of PTSD symptoms as compared with pain-free peers. More youth with chronic pain (32%) and their parents (20%) reported clinically significant elevations in PTSD symptoms than youth without chronic pain (8%) and their parents (1%). Youth with chronic pain also reported a greater number of stressful life events than those without chronic pain, and this was associated with higher PTSD symptoms. Among the chronic pain cohort, higher levels of PTSD symptoms were predictive of worse health-related quality of life and were associated with higher pain intensity, unpleasantness, and interference. Results suggest that elevated PTSD symptoms are common and linked to reduced functioning among youth with chronic pain. Future research is needed to examine PTSD at the diagnostic level and the underlying mechanisms that may explain why this co-occurrence exists.

A Nonlinear Diffusion Equation-Based Model for Ultrasound Speckle Noise Removal

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Guo, Zhichang; Zhang, Dazhi; Wu, Boying

2018-04-01

Ultrasound images are contaminated by speckle noise, which brings difficulties in further image analysis and clinical diagnosis. In this paper, we address this problem in the view of nonlinear diffusion equation theories. We develop a nonlinear diffusion equation-based model by taking into account not only the gradient information of the image, but also the information of the gray levels of the image. By utilizing the region indicator as the variable exponent, we can adaptively control the diffusion type which alternates between the Perona-Malik diffusion and the Charbonnier diffusion according to the image gray levels. Furthermore, we analyze the proposed model with respect to the theoretical and numerical properties. Experiments show that the proposed method achieves much better speckle suppression and edge preservation when compared with the traditional despeckling methods, especially in the low gray level and low-contrast regions.

Impact of CO2 on Intracranial Hypertension in Spaceflight. Visual Impairment and Intracranial Hypertension: An Emerging Spaceflight Risk [Part 1 and 2

NASA Technical Reports Server (NTRS)

Fogarty, Jennifer A.; Polk, James D.; Tarver, William J.; Gibson, Charles R.; Sargsyan, Ashot E.; Taddeo, Terrance A.; Alexander, David J.; Otto, Christian A.

2010-01-01

A. CO2 - Acute: Given the history of uneven removal of CO2 from spacecraft areas, there is a history of acute illness that impacts short-term health and performance. 1) Acute CO2 symptoms occur in space flight due to a combination of CO2 scrubbing limitations, microgravity-related lack of convection, and possibly interaction with microgravity-related physiological changes. 2) Reported symptoms mainly include headaches, malaise, and lethargy. Symptoms are treatable with analgesics, rest, temporarily increasing scrubbing capability, and breathing oxygen. This does not treat the underlying pathology. 3)ld prevent occurrence of symptoms. B. CO2 - Chronic: Given prolonged exposure to elevated CO2 levels, there is a history that the long-term health of the crew is impacted. 1) Chronic CO2 exposures occur in space flight due to a combination of CO2 scrubbing limitations and microgravity-related lack of convection, with possible contribution from microgravity-related physiological changes. 2) Since acute symptoms are experienced at levels significantly lower than expected, there are unidentified long-term effects from prolonged exposure to elevated CO2 levels on orbit. There have been long term effects seen terrestrially and research needed to further elucidate long term effects on orbit. 3) Recommended disposition: Research required to further elucidate long term effects. In particular, elucidation of the role of elevated CO2 on various levels of CO2 vasodilatation of intracranial blood vessels and its potential contribution to elevation of intracranial pressure.

Species co-occurrence affects the trophic interactions of two juvenile reef shark species in tropical lagoon nurseries in Moorea (French Polynesia).

PubMed

Matich, Philip; Kiszka, Jeremy J; Mourier, Johann; Planes, Serge; Heithaus, Michael R

2017-06-01

Food web structure is shaped by interactions within and across trophic levels. As such, understanding how the presence and absence of predators, prey, and competitors affect species foraging patterns is important for predicting the consequences of changes in species abundances, distributions, and behaviors. Here, we used plasma δ 13 C and δ 15 N values from juvenile blacktip reef sharks (Carcharhinus melanopterus) and juvenile sicklefin lemon sharks (Negaprion acutidens) to investigate how species co-occurrence affects their trophic interactions in littoral waters of Moorea, French Polynesia. Co-occurrence led to isotopic niche partitioning among sharks within nurseries, with significant increases in δ 15 N values among sicklefin lemon sharks, and significant decreases in δ 15 N among blacktip reef sharks. Niche segregation likely promotes coexistence of these two predators during early years of growth and development, but data do not suggest coexistence affects life history traits, such as body size, body condition, and ontogenetic niche shifts. Plasticity in trophic niches among juvenile blacktip reef sharks and sicklefin lemon sharks also suggests these predators are able to account for changes in community structure, resource availability, and intra-guild competition, and may fill similar functional roles in the absence of the other species, which is important as environmental change and human impacts persist in coral reef ecosystems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mycotoxigenic fungi and natural co-occurrence of mycotoxins in rainbow trout (Oncorhynchus mykiss) feeds.

PubMed

Greco, Mariana; Pardo, Alejandro; Pose, Graciela

2015-11-05

Samples of rainbow trout feed were analyzed with the aim to determine the mycobiota composition and the co-occurrence of mycotoxins. A total of 28 samples of finished rainbow trout feed from hatcheries in the provinces of Río Negro and Neuquén, Argentina, were studied. Fungal counts were obtained on three culture media in the ranges of <10 to 4.2 × 10⁴ CFU/g on Dichloran Rose Bengal Chloramphenicol Agar (DRBC), <10 to 5.1 × 10⁴ CFU/g on Dichloran Chloramphenicol Peptone Agar (DCPA) and <10 to 3.6 × 10⁴ CFU/g on Dichloran 18% Glycerol Agar (DG18). The most frequent mycotoxigenic fungi were Eurotium (frequency (Fr) 25.0%), followed by Penicillium (Fr 21.4%) and Aspergillus (Fr 3.6%). The most prevalent mycotoxigenic species were E. repens (Fr 21.4%) and E. rubrum (Fr 14.3%). All samples were contaminated with mycotoxins: 64% samples were contaminated with T-2 toxin (median 70.08 ppb), 50% samples with zearalenone (median 87.97 ppb) and aflatoxins (median 2.82 ppb), 25% with ochratoxin A (median 5.26 ppb) and 3.57% samples with deoxynivalenol (median 230 ppb). Eight samples had a fumonisins contamination level below the limit of detection. Co-occurrence of six mycotoxins was determined in 7% of the samples.

Mycotoxigenic Fungi and Natural Co-Occurrence of Mycotoxins in Rainbow Trout (Oncorhynchus mykiss) Feeds

PubMed Central

Greco, Mariana; Pardo, Alejandro; Pose, Graciela

2015-01-01

Samples of rainbow trout feed were analyzed with the aim to determine the mycobiota composition and the co-occurrence of mycotoxins. A total of 28 samples of finished rainbow trout feed from hatcheries in the provinces of Río Negro and Neuquén, Argentina, were studied. Fungal counts were obtained on three culture media in the ranges of <10 to 4.2 × 104 CFU/g on Dichloran Rose Bengal Chloramphenicol Agar (DRBC), <10 to 5.1 × 104 CFU/g on Dichloran Chloramphenicol Peptone Agar (DCPA) and <10 to 3.6 × 104 CFU/g on Dichloran 18% Glycerol Agar (DG18). The most frequent mycotoxigenic fungi were Eurotium (frequency (Fr) 25.0%), followed by Penicillium (Fr 21.4%) and Aspergillus (Fr 3.6%). The most prevalent mycotoxigenic species were E. repens (Fr 21.4%) and E. rubrum (Fr 14.3%). All samples were contaminated with mycotoxins: 64% samples were contaminated with T-2 toxin (median 70.08 ppb), 50% samples with zearalenone (median 87.97 ppb) and aflatoxins (median 2.82 ppb), 25% with ochratoxin A (median 5.26 ppb) and 3.57% samples with deoxynivalenol (median 230 ppb). Eight samples had a fumonisins contamination level below the limit of detection. Co-occurrence of six mycotoxins was determined in 7% of the samples. PMID:26556374

Spread of Botrytis cinerea Strains with Multiple Fungicide Resistance in German Horticulture

PubMed Central

Rupp, Sabrina; Weber, Roland W. S.; Rieger, Daniel; Detzel, Peter; Hahn, Matthias

2017-01-01

Botrytis cinerea is a major plant pathogen, causing gray mold rot in a variety of cultures. Repeated fungicide applications are common but have resulted in the development of fungal populations with resistance to one or more fungicides. In this study, we have monitored fungicide resistance frequencies and the occurrence of multiple resistance in Botrytis isolates from raspberries, strawberries, grapes, stone fruits and ornamental flowers in Germany in 2010 to 2015. High frequencies of resistance to all classes of botryticides was common in all cultures, and isolates with multiple fungicide resistance represented a major part of the populations. A monitoring in a raspberry field over six seasons revealed a continuous increase in resistance frequencies and the emergence of multiresistant Botrytis strains. In a cherry orchard and a vineyard, evidence of the immigration of multiresistant strains from the outside was obtained. Inoculation experiments with fungicide-treated leaves in the laboratory and with strawberry plants cultivated in the greenhouse or outdoors revealed a nearly complete loss of fungicide efficacy against multiresistant strains. B. cinerea field strains carrying multiple resistance mutations against all classes of site-specific fungicides were found to show similar fitness as sensitive field strains under laboratory conditions, based on their vegetative growth, reproduction, stress resistance, virulence and competitiveness in mixed infection experiments. Our data indicate an alarming increase in the occurrence of multiresistance in B. cinerea populations from different cultures, which presents a major threat to the chemical control of gray mold. PMID:28096799

Spread of Botrytis cinerea Strains with Multiple Fungicide Resistance in German Horticulture.

PubMed

Rupp, Sabrina; Weber, Roland W S; Rieger, Daniel; Detzel, Peter; Hahn, Matthias

2016-01-01

Botrytis cinerea is a major plant pathogen, causing gray mold rot in a variety of cultures. Repeated fungicide applications are common but have resulted in the development of fungal populations with resistance to one or more fungicides. In this study, we have monitored fungicide resistance frequencies and the occurrence of multiple resistance in Botrytis isolates from raspberries, strawberries, grapes, stone fruits and ornamental flowers in Germany in 2010 to 2015. High frequencies of resistance to all classes of botryticides was common in all cultures, and isolates with multiple fungicide resistance represented a major part of the populations. A monitoring in a raspberry field over six seasons revealed a continuous increase in resistance frequencies and the emergence of multiresistant Botrytis strains. In a cherry orchard and a vineyard, evidence of the immigration of multiresistant strains from the outside was obtained. Inoculation experiments with fungicide-treated leaves in the laboratory and with strawberry plants cultivated in the greenhouse or outdoors revealed a nearly complete loss of fungicide efficacy against multiresistant strains. B. cinerea field strains carrying multiple resistance mutations against all classes of site-specific fungicides were found to show similar fitness as sensitive field strains under laboratory conditions, based on their vegetative growth, reproduction, stress resistance, virulence and competitiveness in mixed infection experiments. Our data indicate an alarming increase in the occurrence of multiresistance in B. cinerea populations from different cultures, which presents a major threat to the chemical control of gray mold.

The co-occurrence of multiple sclerosis and type 1 diabetes: shared aetiologic features and clinical implication for MS aetiology.

PubMed

Tettey, Prudence; Simpson, Steve; Taylor, Bruce V; van der Mei, Ingrid A F

2015-01-15

We reviewed the evidence for the co-occurrence of type 1 diabetes mellitus (T1D) and multiple sclerosis (MS), and assessed the clinical significance of this association and the shared aetiological features of the two diseases. T1D and MS contribute considerably to the burden of autoimmune diseases in young adults. The co-occurrence of MS and T1D has been reported by a number of studies, suggesting that the two conditions share one or more aetiological components. Both conditions have been associated with distinct human leukocyte antigen (HLA) haplotypes but share a number of similarities in clinical, epidemiological and immunological features, leading to suggestions of possible common mechanisms of development. While underlying genetic factors may be important for the co-occurrence of both conditions, some evidence suggests that environmental factors such as vitamin D deficiency may also modulate an individual's risk for the development of both conditions. Evidence on whether the co-occurrence of the two autoimmune conditions will affect the disease course and severity of MS is merely absent. Further studies need to be conducted to ascertain whether the neuropathology associated with T1D might influence the disease course and contribute to the severity of MS. Copyright © 2014 Elsevier B.V. All rights reserved.

[Sexual violence and co-occurrences suffered by children and adolescents: study of incidents over a decade].

PubMed

de Oliveira, Jacqueline Reiter; Costa, Maria Conceição Oliveira; Amaral, Magali Teresópolis Reis; Santos, Clarice Alves; de Assis, Simone Gonçalves; do Nascimento, Ohana Cunha

2014-03-01

The study analyzes the evolution of the incidence of sexual violence (SV) and co-occurrences between 2001 and 2010. The records of the Guardianship Councils in Feira de Santana, State of Bahia, Brazil were used and the incidence rates and graphs of the events during the period were calculated. Of the total of the different types of violence, 21.8 % involved co-occurrences, the majority being female, most frequently during adolescence. There was a high proportion of abuse in male children, with most offenders bring family members or acquaintances. The incidence of SV revealed an increasing trend in both sexes during the decade, more significantly in females in 2002 and 2009. The age groups indicated the same trend, with a higher proportion of cases in adolescence. The record of co-occurrences with SV was more pronounced in the second half of the decade, namely psychological violence in 2008, neglect in 2008 and physical violence in 2009. The conclusion is that the increase in the coefficients of sexual violence and co-occurrences may indicate an improvement of the reporting system of instances in reference, as well as greater citizen participation through the Dial 100 complaint hotline. The indicators help to prevent and control violence against children.

Prevalence of West Nile virus in migratory birds during spring and fall migration

USGS Publications Warehouse

Dusek, Robert J.; McLean, R.G.; Kramer, L.D.; Ubico, S.R.; Dupuis, A.P.; Ebel, G.D.; Guptill, S.C.

2009-01-01

To investigate the role of migratory birds in the dissemination of West Nile virus (WNV), we measured the prevalence of infectious WNV and specific WNV neutralizing antibodies in birds, principally Passeriformes, during spring and fall migrations in the Atlantic and Mississippi flyways from 2001-2003. Blood samples were obtained from 13,403 birds, representing 133 species. Specific WNV neutralizing antibody was detected in 254 resident and migratory birds, representing 39 species, and was most commonly detected in northern cardinals (Cardinalis cardinalis) (9.8%, N = 762) and gray catbirds (Dumetella carolinensis) (3.2%,N = 3188). West Nile virus viremias were detected in 19 birds, including 8 gray catbirds, and only during the fall migratory period. These results provide additional evidence that migratory birds may have been a principal agent for the spread of WNV in North America and provide data on the occurrence of WNV in a variety of bird species. Copyright ?? 2009 by The American Society of Tropical Medicine and Hygiene.

Sedimentology and petroleum occurrence, Schoolhouse Member, Maroon Formation (Lower Permian), northwestern Colorado

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

Johnson, S.Y.; Schenk, C.J.; Anders, D.L.

The Lower Permian Schoolhouse Member of the Maroon Formation (formerly considered the Schoolhouse Tongue of the Weber Sandstone) forms a partly exhumed petroleum reservoir in the Eagle basin of northwestern Colorado. The Schoolhouse consists mainly of yellowish gray to gray, low-angle to parallel bedded, very fine to fine-grained sandstone of eolian sand-sheet origin; interbedded fluvial deposits are present in most sections. The sand-sheet deposits of the Schoolhouse Member are sedimentologically and petrologically similar to those in the underlying red beds of the main body of the Maroon Formation, and the Schoolhouse is considered the uppermost sand sheet in the Maroonmore » depositional sequence. The bleached and oil-stained Schoolhouse member is distinguished from the underlying Maroon red beds on the basis of its diagenetic history, which is related to regional hydrocarbon migration and development of secondary porosity. Geological and geochemical data suggest that Schoolhouse Member oils have upper Paleozoic sources, including the intrabasinal Belden Formation. 13 figs., 1 tab.« less

The Interrelatedness of Multiple Forms of Childhood Abuse, Neglect, and Household Dysfunction

ERIC Educational Resources Information Center

Dong, Maxia; Anda, Robert .F.; Felitti, Vincent , J.; Dube, Shanta R.; Williamson, David F.; Thompson, Theodore, J.; Loo, Clifton , M.; Giles, Wayne, H.

2004-01-01

Objective: Childhood abuse and other adverse childhood experiences (ACEs) have historically been studied individually, and relatively little is known about the co-occurrence of these events. The purpose of this study is to examine the degree to which ACEs co-occur as well as the nature of their co-occurrence. Method: We used data from 8,629 adult…

Coupled X-ray computed tomography and grey level co-occurrence matrices as a method for quantification of mineralogy and texture in 3D

NASA Astrophysics Data System (ADS)

Jardine, M. A.; Miller, J. A.; Becker, M.

2018-02-01

Texture is one of the most basic descriptors used in the geological sciences. The value derived from textural characterisation extends into engineering applications associated with mining, mineral processing and metal extraction where quantitative textural information is required for models predicting the response of the ore through a particular process. This study extends the well-known 2D grey level co-occurrence matrices methodology into 3D as a method for image analysis of 3D x-ray computed tomography grey scale volumes of drill core. Subsequent interrogation of the information embedded within the grey level occurrence matrices (GLCM) indicates they are sensitive to changes in mineralogy and texture of samples derived from a magmatic nickel sulfide ore. The position of the peaks in the GLCM is an indication of the relative density (specific gravity, SG) of the minerals and when interpreted using a working knowledge of the mineralogy of the ore presented a means to determine the relative abundance of the sulfide minerals (SG > 4), dense silicate minerals (SG > 3), and lighter silicate minerals (SG < 3). The spread of the peaks in the GLCM away from the diagonal is an indication of the degree of grain boundary interaction with wide peaks representing fine grain sizes and narrow peaks representing coarse grain sizes. The method lends itself to application as part of a generic methodology for routine use on large XCT volumes providing quantitative, timely, meaningful and automated information on mineralogy and texture in 3D.

The Role of Color and Morphologic Characteristics in Dermoscopic Diagnosis.

PubMed

Bajaj, Shirin; Marchetti, Michael A; Navarrete-Dechent, Cristian; Dusza, Stephen W; Kose, Kivanc; Marghoob, Ashfaq A

2016-06-01

Both colors and structures are considered important in the dermoscopic evaluation of skin lesions but their relative significance is unknown. To determine if diagnostic accuracy for common skin lesions differs between gray-scale and color dermoscopic images. A convenience sample of 40 skin lesions (8 nevi, 8 seborrheic keratoses, 7 basal cell carcinomas, 7 melanomas, 4 hemangiomas, 4 dermatofibromas, 2 squamous cell carcinomas [SCCs]) was selected and shown to attendees of a dermoscopy course (2014 Memorial Sloan Kettering Cancer Center dermoscopy course). Twenty lesions were shown only once, either in gray-scale (n = 10) or color (n = 10) (nonpaired). Twenty lesions were shown twice, once in gray-scale (n = 20) and once in color (n = 20) (paired). Participants provided their diagnosis and confidence level for each of the 60 images. Of the 261 attendees, 158 participated (60.5%) in the study. Most were attending physicians (n = 76 [48.1%]). Most participants were practicing or training in dermatology (n = 144 [91.1%]). The median (interquartile range) experience evaluating skin lesions and using dermoscopy of participants was 6 (13.5) and 2 (4.0) years, respectively. Diagnostic accuracy and confidence level of participants evaluating gray-scale and color images. Two separate analyses were performed: (1) an unpaired evaluation comparing gray-scale and color images shown either once or for the first time, and (2) a paired evaluation comparing pairs of gray-scale and color images of the same lesion. In univariate analysis of unpaired images, color images were less likely to be diagnosed correctly compared with gray-scale images (odds ratio [OR], 0.8; P < .001). Using gray-scale images as the reference, multivariate analyses of both unpaired and paired images found no association between correct lesion diagnosis and use of color images (OR, 1.0; P = .99, and OR, 1.2; P = .82, respectively). Stratified analysis of paired images using a color by diagnosis interaction term showed that participants were more likely to make a correct diagnosis of SCC and hemangioma in color (P < .001 for both comparisons) and dermatofibroma in gray-scale (P < .001). Morphologic characteristics (ie, structures and patterns), not color, provide the primary diagnostic clue in dermoscopy. Use of gray-scale images may improve teaching of dermoscopy to novices by emphasizing the evaluation of morphology.

Scanning Probe Platform | Materials Science | NREL

Science.gov Websites

level; this image obtained using a scanning tunneling microscope shows gray and white clusters of produce high-resolution color images or maps like this one obtained using scanning tunneling luminescence gray clusters. Gold substrate: (Left) STM image reveals the terraces of the H2 flamed substrate. (Right

Positive emotion, appraisal, and the role of appraisal overlap in positive emotion co-occurrence.

PubMed

Tong, Eddie M W; Jia, Lile

2017-02-01

Appraisal research has traditionally focused on negative emotions but has not addressed issues concerning the relationships between several positive emotions and appraisals in daily life and the extent to which co-occurrence of positive emotions can be explained by overlap in appraisals. Driven by a priori hypotheses on appraisal-emotion relationships, this study investigated 12 positive emotions and 13 appraisal dimensions using Ecological Momentary Assessment. The results provide strong evidence that positive emotions and appraisals correlate significantly in daily life. Importantly, we found that the positive emotions' overlap on theoretically relevant, as compared to irrelevant, appraisals was stronger and more predictive of their co-occurrence. Furthermore, appraisal overlap on theoretically relevant appraisals predicted the co-occurrence of positive emotions even when the appraisal of pleasantness was excluded, indicating that positive emotions do not co-occur just by virtue of their shared valence. Our findings affirmed and refined the appraisal profiles of positive emotions and underscore the importance of appraisals in accounting for the commonality and differences among positive emotions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Multidecadal Increase in North Atlantic Coccolithophores and Potential Role of Increasing CO2

NASA Astrophysics Data System (ADS)

Rivero-Calle, S.; Gnanadesikan, A.; del Castillo, C. E.; Balch, W. M.; Guikema, S.

2016-02-01

As anthropogenic CO2 emissions acidify the oceans, calcifiers are expected to be negatively impacted. Using data from the Continuous Plankton Recorder, we show that coccolithophore occurrence in the North Atlantic has increased from 2 to over 20% from 1965 through 2010. We used Random Forest models to examine more than 20 possible environmental drivers of this change. CO2 and the Atlantic Multidecadal Oscillation were the best predictors. Since coccolithophore photosynthesis is strongly carbon-limited, we hypothesize that higher CO2 levels might be encouraging growth. A compilation of 41 independent laboratory studies supports our hypothesis. Our study shows a long-term basin-scale increase in coccolithophores and suggests that increasing pCO2 and temperature accelerated the growth rate of a key phytoplankton group for carbon cycling.

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

Childhood aggression and the co-occurrence of behavioural and emotional problems: results across ages 3-16 years from multiple raters in six cohorts in the EU-ACTION project.

PubMed

Bartels, Meike; Hendriks, Anne; Mauri, Matteo; Krapohl, Eva; Whipp, Alyce; Bolhuis, Koen; Conde, Lucia Colodro; Luningham, Justin; Fung Ip, Hill; Hagenbeek, Fiona; Roetman, Peter; Gatej, Raluca; Lamers, Audri; Nivard, Michel; van Dongen, Jenny; Lu, Yi; Middeldorp, Christel; van Beijsterveldt, Toos; Vermeiren, Robert; Hankemeijer, Thomas; Kluft, Cees; Medland, Sarah; Lundström, Sebastian; Rose, Richard; Pulkkinen, Lea; Vuoksimaa, Eero; Korhonen, Tellervo; Martin, Nicholas G; Lubke, Gitta; Finkenauer, Catrin; Fanos, Vassilios; Tiemeier, Henning; Lichtenstein, Paul; Plomin, Robert; Kaprio, Jaakko; Boomsma, Dorret I

2018-05-29

Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. We focus on the co-occurrence of aggression and other childhood behavioural and emotional problems, including other externalising problems, attention problems and anxiety-depression. The data were brought together within the EU-ACTION (Aggression in Children: unravelling gene-environment interplay to inform Treatment and InterventiON strategies) project. We analysed the co-occurrence of aggression and other childhood behavioural and emotional problems as a function of the child's age (ages 3 through 16 years), gender, the person rating the behaviour (father, mother or self) and assessment instrument. The data came from six large population-based European cohort studies from the Netherlands (2x), the UK, Finland and Sweden (2x). Multiple assessment instruments, including the Child Behaviour Checklist (CBCL), the Strengths and Difficulties Questionnaire (SDQ) and Multidimensional Peer Nomination Inventory (MPNI), were used. There was a good representation of boys and girls in each age category, with data for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds (49.0% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 12- to 13-year-olds (48.9% boys) and 10,088 15- to 16-year-olds (46.6% boys). We replicated the well-established gender differences in average aggression scores at most ages for parental ratings. The gender differences decreased with age and were not present for self-reports. Aggression co-occurred with the majority of other behavioural and social problems, from both externalising and internalising domains. At each age, the co-occurrence was particularly prevalent for aggression and oppositional and ADHD-related problems, with correlations of around 0.5 in general. Aggression also showed substantial associations with anxiety-depression and other internalizing symptoms (correlations around 0.4). Co-occurrence for self-reported problems was somewhat higher than for parental reports, but we found neither rater differences, nor differences across assessment instruments in co-occurrence patterns. There were large similarities in co-occurrence patterns across the different European countries. Finally, co-occurrence was generally stable across age and sex, and if any change was observed, it indicated stronger correlations when children grew older. We present an online tool to visualise these associations as a function of rater, gender, instrument and cohort. In addition, we present a description of the full EU-ACTION projects, its first results and the future perspectives.

Assessment of the biological activity of soils in the subtropical zone of Azerbaijan

NASA Astrophysics Data System (ADS)

Babaev, M. P.; Orujova, N. I.

2009-10-01

The enzymatic activity; the microbial population; and the intensities of the nitrification, ammonification, CO2emission, and cellulose decomposition were studied in gray-brown, meadow-sierozemic, meadow-forest alluvial, and yellow (zheltozem) gley soils in the subtropical zone of Azerbaijan under natural vegetation, crop rotation systems with vegetables, and permanent vegetable crops. On this basis, the biological diagnostics of these soils were suggested and the soil ecological health was evaluated. It was shown that properly chosen crop rotation systems on irrigated lands make it possible to preserve the fertility of the meadow-forest alluvial and zheltozem-gley soils and to improve the fertility of the gray-brown and meadow-sierozemic soils.

Neutron scattered dose equivalent to a fetus from proton radiotherapy of the mother.

PubMed

Mesoloras, Geraldine; Sandison, George A; Stewart, Robert D; Farr, Jonathan B; Hsi, Wen C

2006-07-01

Scattered neutron dose equivalent to a representative point for a fetus is evaluated in an anthropomorphic phantom of the mother undergoing proton radiotherapy. The effect on scattered neutron dose equivalent to the fetus of changing the incident proton beam energy, aperture size, beam location, and air gap between the beam delivery snout and skin was studied for both a small field snout and a large field snout. Measurements of the fetus scattered neutron dose equivalent were made by placing a neutron bubble detector 10 cm below the umbilicus of an anthropomorphic Rando phantom enhanced by a wax bolus to simulate a second trimester pregnancy. The neutron dose equivalent in milliSieverts (mSv) per proton treatment Gray increased with incident proton energy and decreased with aperture size, distance of the fetus representative point from the field edge, and increasing air gap. Neutron dose equivalent to the fetus varied from 0.025 to 0.450 mSv per proton Gray for the small field snout and from 0.097 to 0.871 mSv per proton Gray for the large field snout. There is likely to be no excess risk to the fetus of severe mental retardation for a typical proton treatment of 80 Gray to the mother since the scattered neutron dose to the fetus of 69.7 mSv is well below the lower confidence limit for the threshold of 300 mGy observed for the occurrence of severe mental retardation in prenatally exposed Japanese atomic bomb survivors. However, based on the linear no threshold hypothesis, and this same typical treatment for the mother, the excess risk to the fetus of radiation induced cancer death in the first 10 years of life is 17.4 per 10,000 children.

Performance impact of stop lists and morphological decomposition on word-word corpus-based semantic space models.

PubMed

Keith, Jeff; Westbury, Chris; Goldman, James

2015-09-01

Corpus-based semantic space models, which primarily rely on lexical co-occurrence statistics, have proven effective in modeling and predicting human behavior in a number of experimental paradigms that explore semantic memory representation. The most widely studied extant models, however, are strongly influenced by orthographic word frequency (e.g., Shaoul & Westbury, Behavior Research Methods, 38, 190-195, 2006). This has the implication that high-frequency closed-class words can potentially bias co-occurrence statistics. Because these closed-class words are purported to carry primarily syntactic, rather than semantic, information, the performance of corpus-based semantic space models may be improved by excluding closed-class words (using stop lists) from co-occurrence statistics, while retaining their syntactic information through other means (e.g., part-of-speech tagging and/or affixes from inflected word forms). Additionally, very little work has been done to explore the effect of employing morphological decomposition on the inflected forms of words in corpora prior to compiling co-occurrence statistics, despite (controversial) evidence that humans perform early morphological decomposition in semantic processing. In this study, we explored the impact of these factors on corpus-based semantic space models. From this study, morphological decomposition appears to significantly improve performance in word-word co-occurrence semantic space models, providing some support for the claim that sublexical information-specifically, word morphology-plays a role in lexical semantic processing. An overall decrease in performance was observed in models employing stop lists (e.g., excluding closed-class words). Furthermore, we found some evidence that weakens the claim that closed-class words supply primarily syntactic information in word-word co-occurrence semantic space models.

Longitudinal evaluation of T1ρ and T2 spatial distribution in osteoarthritic and healthy medial knee cartilage.

PubMed

Schooler, J; Kumar, D; Nardo, L; McCulloch, C; Li, X; Link, T M; Majumdar, S

2014-01-01

To investigate longitudinal changes in laminar and spatial distribution of knee articular cartilage magnetic resonance imaging (MRI) T1ρ and T2 relaxation times, in individuals with and without medial compartment cartilage defects. All subjects (at baseline n = 88, >18 years old) underwent 3-Tesla knee MRI at baseline and annually thereafter for 3 years. The MR studies were evaluated for presence of cartilage defects (modified Whole-Organ Magnetic Resonance Imaging Scoring - mWORMS), and quantitative T1ρ and T2 relaxation time maps. Subjects were segregated into those with (mWORMS ≥2) and without (mWORMS ≤1) cartilage lesions at the medial tibia (MT) or medial femur (MF) at each time point. Laminar (bone and articular layer) and spatial (gray level co-occurrence matrix - GLCM) distribution of the T1ρ and T2 relaxation time maps were calculated. Linear regression models (cross-sectional) and Generalized Estimating Equations (GEEs) (longitudinal) were used. Global T1ρ, global T2 and articular layer T2 relaxation times at the MF, and global and articular layer T2 relaxation times at the MT, were higher in subjects with cartilage lesions compared to those without lesions. At the MT global T1ρ relaxation times were higher at each time point in subjects with lesions. MT T1ρ and T2 became progressively more heterogeneous than control compartments over the course of the study. Spatial distribution of T1ρ and T2 relaxation time maps in medial knee OA using GLCM technique may be a sensitive indicator of cartilage deterioration, in addition to whole-compartment relaxation time data. Copyright © 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

GyneScan

PubMed Central

Acharya, U. Rajendra; Sree, S. Vinitha; Kulshreshtha, Sanjeev; Molinari, Filippo; Koh, Joel En Wei; Saba, Luca; Suri, Jasjit S.

2014-01-01

Ovarian cancer is the fifth highest cause of cancer in women and the leading cause of death from gynecological cancers. Accurate diagnosis of ovarian cancer from acquired images is dependent on the expertise and experience of ultrasonographers or physicians, and is therefore, associated with inter observer variabilities. Computer Aided Diagnostic (CAD) techniques use a number of different data mining techniques to automatically predict the presence or absence of cancer, and therefore, are more reliable and accurate. A review of published literature in the field of CAD based ovarian cancer detection indicates that many studies use ultrasound images as the base for analysis. The key objective of this work is to propose an effective adjunct CAD technique called GyneScan for ovarian tumor detection in ultrasound images. In our proposed data mining framework, we extract several texture features based on first order statistics, Gray Level Co-occurrence Matrix and run length matrix. The significant features selected using t-test are then used to train and test several supervised learning based classifiers such as Probabilistic Neural Networks (PNN), Support Vector Machine (SVM), Decision Tree (DT), k-Nearest Neighbor (KNN), and Naïve Bayes (NB). We evaluated the developed framework using 1300 benign and 1300 malignant images. Using 11 significant features in KNN/PNN classifiers, we were able to achieve 100% classification accuracy, sensitivity, specificity, and positive predictive value in detecting ovarian tumor. Even though more validation using larger databases would better establish the robustness of our technique, the preliminary results are promising. This technique could be used as a reliable adjunct method to existing imaging modalities to provide a more confident second opinion on the presence/absence of ovarian tumor. PMID:24325128

A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

Classification of small lesions in dynamic breast MRI: Eliminating the need for precise lesion segmentation through spatio-temporal analysis of contrast enhancement over time.

PubMed

Nagarajan, Mahesh B; Huber, Markus B; Schlossbauer, Thomas; Leinsinger, Gerda; Krol, Andrzej; Wismüller, Axel

2013-10-01

Characterizing the dignity of breast lesions as benign or malignant is specifically difficult for small lesions; they don't exhibit typical characteristics of malignancy and are harder to segment since margins are harder to visualize. Previous attempts at using dynamic or morphologic criteria to classify small lesions (mean lesion diameter of about 1 cm) have not yielded satisfactory results. The goal of this work was to improve the classification performance in such small diagnostically challenging lesions while concurrently eliminating the need for precise lesion segmentation. To this end, we introduce a method for topological characterization of lesion enhancement patterns over time. Three Minkowski Functionals were extracted from all five post-contrast images of sixty annotated lesions on dynamic breast MRI exams. For each Minkowski Functional, topological features extracted from each post-contrast image of the lesions were combined into a high-dimensional texture feature vector. These feature vectors were classified in a machine learning task with support vector regression. For comparison, conventional Haralick texture features derived from gray-level co-occurrence matrices (GLCM) were also used. A new method for extracting thresholded GLCM features was also introduced and investigated here. The best classification performance was observed with Minkowski Functionals area and perimeter , thresholded GLCM features f8 and f9, and conventional GLCM features f4 and f6. However, both Minkowski Functionals and thresholded GLCM achieved such results without lesion segmentation while the performance of GLCM features significantly deteriorated when lesions were not segmented ( p < 0.05). This suggests that such advanced spatio-temporal characterization can improve the classification performance achieved in such small lesions, while simultaneously eliminating the need for precise segmentation.

Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

PubMed

Wu, Jia; Gong, Guanghua; Cui, Yi; Li, Ruijiang

2016-11-01

To predict pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). In this Institutional Review Board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 3T DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with high temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast washout were statistically significant (P < 0.05) after correcting for multiple testing, with area under the receiver operating characteristic (ROC) curve (AUC) or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (P = 0.002) in leave-one-out cross-validation. This improved upon conventional imaging predictors such as tumor volume (AUC = 0.53) and texture features based on whole-tumor analysis (AUC = 0.65). The heterogeneity of the tumor subregion associated with fast washout on DCE-MRI predicted pathological response to NAC in breast cancer. J. Magn. Reson. Imaging 2016;44:1107-1115. © 2016 International Society for Magnetic Resonance in Medicine.

Radiomic texture-curvature (RTC) features for precision medicine of patients with rheumatoid arthritis-associated interstitial lung disease

NASA Astrophysics Data System (ADS)

Watari, Chinatsu; Matsuhiro, Mikio; Näppi, Janne J.; Nasirudin, Radin A.; Hironaka, Toru; Kawata, Yoshiki; Niki, Noboru; Yoshida, Hiroyuki

2018-03-01

We investigated the effect of radiomic texture-curvature (RTC) features of lung CT images in the prediction of the overall survival of patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). We retrospectively collected 70 RA-ILD patients who underwent thin-section lung CT and serial pulmonary function tests. After the extraction of the lung region, we computed hyper-curvature features that included the principal curvatures, curvedness, bright/dark sheets, cylinders, blobs, and curvature scales for the bronchi and the aerated lungs. We also computed gray-level co-occurrence matrix (GLCM) texture features on the segmented lungs. An elastic-net penalty method was used to select and combine these features with a Cox proportional hazards model for predicting the survival of the patient. Evaluation was performed by use of concordance index (C-index) as a measure of prediction performance. The C-index values of the texture features, hyper-curvature features, and the combination thereof (RTC features) in predicting patient survival was estimated by use of bootstrapping with 2,000 replications, and they were compared with an established clinical prognostic biomarker known as the gender, age, and physiology (GAP) index by means of two-sided t-test. Bootstrap evaluation yielded the following C-index values for the clinical and radiomic features: (a) GAP index: 78.3%; (b) GLCM texture features: 79.6%; (c) hypercurvature features: 80.8%; and (d) RTC features: 86.8%. The RTC features significantly outperformed any of the other predictors (P < 0.001). The Kaplan-Meier survival curves of patients stratified to low- and high-risk groups based on the RTC features showed statistically significant (P < 0.0001) difference. Thus, the RTC features can provide an effective imaging biomarker for predicting the overall survival of patients with RA-ILD.

Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, J. X.; Zhao, Z.; Ma, A. D.

2015-06-01

Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It's of great significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery.

Investigation of gastric cancers in nude mice using X-ray in-line phase contrast imaging.

PubMed

Tao, Qiang; Luo, Shuqian

2014-07-24

This paper is to report the new imaging of gastric cancers without the use of imaging agents. Both gastric normal regions and gastric cancer regions can be distinguished by using the principal component analysis (PCA) based on the gray level co-occurrence matrix (GLCM). Human gastric cancer BGC823 cells were implanted into the stomachs of nude mice. Then, 3, 5, 7, 9 or 11 days after cancer cells implantation, the nude mice were sacrificed and their stomachs were removed. X-ray in-line phase contrast imaging (XILPCI), an X-ray phase contrast imaging method, has greater soft tissue contrast than traditional absorption radiography and generates higher-resolution images. The gastric specimens were imaged by an XILPCIs' charge coupled device (CCD) of 9 μm image resolution. The PCA of the projective images' region of interests (ROIs) based on GLCM were extracted to discriminate gastric normal regions and gastric cancer regions. Different stages of gastric cancers were classified by using support vector machines (SVMs). The X-ray in-line phase contrast images of nude mice gastric specimens clearly show the gastric architectures and the details of the early gastric cancers. The phase contrast computed tomography (CT) images of nude mice gastric cancer specimens are better than the traditional absorption CT images without the use of imaging agents. The results of the PCA of the texture parameters based on GLCM of normal regions is (F1+F2) >8.5, but those of cancer regions is (F1+F2) <8.5. The classification accuracy is 83.3% that classifying gastric specimens into different stages using SVMs. This is a very preliminary feasibility study. With further researches, XILPCI could become a noninvasive method for future the early detection of gastric cancers or medical researches.

Military personnel recognition system using texture, colour, and SURF features

NASA Astrophysics Data System (ADS)

Irhebhude, Martins E.; Edirisinghe, Eran A.

2014-06-01

This paper presents an automatic, machine vision based, military personnel identification and classification system. Classification is done using a Support Vector Machine (SVM) on sets of Army, Air Force and Navy camouflage uniform personnel datasets. In the proposed system, the arm of service of personnel is recognised by the camouflage of a persons uniform, type of cap and the type of badge/logo. The detailed analysis done include; camouflage cap and plain cap differentiation using gray level co-occurrence matrix (GLCM) texture feature; classification on Army, Air Force and Navy camouflaged uniforms using GLCM texture and colour histogram bin features; plain cap badge classification into Army, Air Force and Navy using Speed Up Robust Feature (SURF). The proposed method recognised camouflage personnel arm of service on sets of data retrieved from google images and selected military websites. Correlation-based Feature Selection (CFS) was used to improve recognition and reduce dimensionality, thereby speeding the classification process. With this method success rates recorded during the analysis include 93.8% for camouflage appearance category, 100%, 90% and 100% rates of plain cap and camouflage cap categories for Army, Air Force and Navy categories, respectively. Accurate recognition was recorded using SURF for the plain cap badge category. Substantial analysis has been carried out and results prove that the proposed method can correctly classify military personnel into various arms of service. We show that the proposed method can be integrated into a face recognition system, which will recognise personnel in addition to determining the arm of service which the personnel belong. Such a system can be used to enhance the security of a military base or facility.

Using X-Ray In-Line Phase-Contrast Imaging for the Investigation of Nude Mouse Hepatic Tumors

PubMed Central

Zhang, Lu; Luo, Shuqian

2012-01-01

The purpose of this paper is to report the noninvasive imaging of hepatic tumors without contrast agents. Both normal tissues and tumor tissues can be detected, and tumor tissues in different stages can be classified quantitatively. We implanted BEL-7402 human hepatocellular carcinoma cells into the livers of nude mice and then imaged the livers using X-ray in-line phase-contrast imaging (ILPCI). The projection images' texture feature based on gray level co-occurrence matrix (GLCM) and dual-tree complex wavelet transforms (DTCWT) were extracted to discriminate normal tissues and tumor tissues. Different stages of hepatic tumors were classified using support vector machines (SVM). Images of livers from nude mice sacrificed 6 days after inoculation with cancer cells show diffuse distribution of the tumor tissue, but images of livers from nude mice sacrificed 9, 12, or 15 days after inoculation with cancer cells show necrotic lumps in the tumor tissue. The results of the principal component analysis (PCA) of the texture features based on GLCM of normal regions were positive, but those of tumor regions were negative. The results of PCA of the texture features based on DTCWT of normal regions were greater than those of tumor regions. The values of the texture features in low-frequency coefficient images increased monotonically with the growth of the tumors. Different stages of liver tumors can be classified using SVM, and the accuracy is 83.33%. Noninvasive and micron-scale imaging can be achieved by X-ray ILPCI. We can observe hepatic tumors and small vessels from the phase-contrast images. This new imaging approach for hepatic cancer is effective and has potential use in the early detection and classification of hepatic tumors. PMID:22761929

Genetic and isotope ratio mass spectrometric evidence for the occurrence of starch degradation and cycling in illuminated Arabidopsis leaves

PubMed Central

Baslam, Marouane; Baroja-Fernández, Edurne; Ricarte-Bermejo, Adriana; Sánchez-López, Ángela María; Aranjuelo, Iker; Bahaji, Abdellatif; Muñoz, Francisco José; Almagro, Goizeder; Pujol, Pablo; Galarza, Regina; Teixidor, Pilar; Pozueta-Romero, Javier

2017-01-01

Although there is a great wealth of data supporting the occurrence of simultaneous synthesis and breakdown of storage carbohydrate in many organisms, previous 13CO2 pulse-chase based studies indicated that starch degradation does not operate in illuminated Arabidopsis leaves. Here we show that leaves of gwd, sex4, bam4, bam1/bam3 and amy3/isa3/lda starch breakdown mutants accumulate higher levels of starch than wild type (WT) leaves when cultured under continuous light (CL) conditions. We also show that leaves of CL grown dpe1 plants impaired in the plastidic disproportionating enzyme accumulate higher levels of maltotriose than WT leaves, the overall data providing evidence for the occurrence of extensive starch degradation in illuminated leaves. Moreover, we show that leaves of CL grown mex1/pglct plants impaired in the chloroplastic maltose and glucose transporters display a severe dwarf phenotype and accumulate high levels of maltose, strongly indicating that the MEX1 and pGlcT transporters are involved in the export of starch breakdown products to the cytosol to support growth during illumination. To investigate whether starch breakdown products can be recycled back to starch during illumination through a mechanism involving ADP-glucose pyrophosphorylase (AGP) we conducted kinetic analyses of the stable isotope carbon composition (δ13C) in starch of leaves of 13CO2 pulsed-chased WT and AGP lacking aps1 plants. Notably, the rate of increase of δ13C in starch of aps1 leaves during the pulse was exceedingly higher than that of WT leaves. Furthermore, δ13C decline in starch of aps1 leaves during the chase was much faster than that of WT leaves, which provides strong evidence for the occurrence of AGP-mediated cycling of starch breakdown products in illuminated Arabidopsis leaves. PMID:28152100

A 1500-year record of climatic and environmental change in Elk Lake, Minnesota I: Varve thickness and gray-scale density

USGS Publications Warehouse

Dean, W.; Anderson, R.; Platt, Bradbury J.; Anderson, D.

2002-01-01

The deepest part (29.5 m) of Elk Lake, Clearwater County, northwestern Minnesota, contains a complete Holocene section that is continuously varved. The varve components are predominantly autochthonous (CaCO3, organic matter, biogenic silica, and several iron and manganese minerals), but the varves do contain a minor detrital-clastic (aluminosilicate) component that is predominantly wind-borne (eolian) and provides an important record of atmospheric conditions. Singular spectrum analysis (SSA) and wavelet analysis of varve thickness recognized significant periodicities in the multicentennial and multidecadal bands that varied in power (i.e., variable significance) and position (i.e., variable period) within the periodic bands. Persistent periodicities of about 10, 22, 40, and 90 years, and, in particular, multicentennial periodicities in varve thickness and other proxy variables are similar to those in spectra of radiocarbon production, a proxy for past solar activity. This suggests that there may be a solar control, perhaps through geomagnetic effects on atmospheric circulation. Multicentennial and multidecadal periodicities also occur in wavelet spectra of relative gray-scale density. However, gray-scale density does not appear to correlate with any of the measured proxy variables, and at this point we do not know what controlled gray scale.

Two Distinct Origins of Long-Term Learning Effects in Verbal Short-Term Memory

ERIC Educational Resources Information Center

Majerus, Steve; Perez, Trecy Martinez; Oberauer, Klaus

2012-01-01

Verbal short-term memory (STM) is highly sensitive to learning effects: digit sequences or nonword sequences which have been rendered more familiar via repeated exposure are recalled more accurately. In this study we show that sublist-level, incidental learning of item co-occurrence regularities affects immediate serial recall of words and…

Detection of High Levels of Endocrine Activity in Selected Environmental Surface Water Samples Using ER, AR, and GR-mediated In Vitro Bioassays

EPA Science Inventory

Determining the associated health risks of exposure to complex mixtures in the environment is a recognized challenge. The Chemical Mixtures project, a collaborative effort between USEPA and USGS, is making a step in that direction by examining the co-occurrence of chemicals and b...

A-law/Mu-law Dynamic Range Compression Deconvolution (Preprint)

DTIC Science & Technology

2008-02-04

noise filtering via the spectrum proportionality filter, and second the signal deblurring via the inverse filter. In this process for regions when...is the joint image of motion impulse response and the noisy blurred image with signal to noise ratio 5, 6(A’) is the gray level recovered image...joint image of motion impulse response and the noisy blurred image with signal to noise ratio 5, (A’) the gray level recovered image using the A-law

A Chemical and Dynamical Link Between Red Centaur Objects and the Cold Classical Kuiper Belt

NASA Astrophysics Data System (ADS)

Tegler, Stephen C.; Romanishin, William; Consolmagno, Guy

2015-11-01

We present new B-V, V-R, and B-R colors for 32 Centaurs objects using the 4.3-meter Discovery Channel Telescope (DCT) near Happy Jack, AZ and the 1.8-meter Vatican Advanced Technology Telescope on Mt. Graham, AZ. Combining these new colors with our previously reported colors, we now have optical broad-band colors for 58 Centaur objects.Application of the non-parametric Dip Test to our previous sample of only 26 objects showed Centaurs split into gray and red groups at the 99.5% confidence level, and application of the Wilcoxon Rank Sum Test to the same sample showed that red Centaurs have a higher median albedo than gray Centaurs at the 99% confidence level (Tegler et al., 2008, Solar System Beyond Neptune, U Arizona Press, pp. 105-114).Here we report application of the Wilcoxon Rank Sum Test to our sample of 58 Centaurs. We confirm red Centaurs have a higher median albedo than gray Centaurs at the 99.7% level. In addition, we find that red Centaurs have a lower median inclination angle than gray Centaurs at the 99.5% confidence level. Because of their red colors and lower inclination angles, we suggest red Centaurs originate in the cold classical Kuiper belt. We thank the NASA Solar System Observations Program for its support.

A western gray whale mitigation and monitoring program for a 3-D seismic survey, Sakhalin Island, Russia.

PubMed

Johnson, S R; Richardson, W J; Yazvenko, S B; Blokhin, S A; Gailey, G; Jenkerson, M R; Meier, S K; Melton, H R; Newcomer, M W; Perlov, A S; Rutenko, S A; Würsig, B; Martin, C R; Egging, D E

2007-11-01

The introduction of anthropogenic sounds into the marine environment can impact some marine mammals. Impacts can be greatly reduced if appropriate mitigation measures and monitoring are implemented. This paper concerns such measures undertaken by Exxon Neftegas Limited, as operator of the Sakhalin-1 Consortium, during the Odoptu 3-D seismic survey conducted during 17 August-9 September 2001. The key environmental issue was protection of the critically endangered western gray whale (Eschrichtius robustus), which feeds in summer and fall primarily in the Piltun feeding area off northeast Sakhalin Island. Existing mitigation and monitoring practices for seismic surveys in other jurisdictions were evaluated to identify best practices for reducing impacts on feeding activity by western gray whales. Two buffer zones were established to protect whales from physical injury or undue disturbance during feeding. A 1 km buffer protected all whales from exposure to levels of sound energy potentially capable of producing physical injury. A 4-5 km buffer was established to avoid displacing western gray whales from feeding areas. Trained Marine Mammal Observers (MMOs) on the seismic ship Nordic Explorer had the authority to shut down the air guns if whales were sighted within these buffers. Additional mitigation measures were also incorporated: Temporal mitigation was provided by rescheduling the program from June-August to August-September to avoid interference with spring arrival of migrating gray whales. The survey area was reduced by 19% to avoid certain waters <20 m deep where feeding whales concentrated and where seismic acquisition was a lower priority. The number of air guns and total volume of the air guns were reduced by about half (from 28 to 14 air guns and from 3,390 in(3) to 1,640 in(3)) relative to initial plans. "Ramp-up" (="soft-start") procedures were implemented. Monitoring activities were conducted as needed to implement some mitigation measures, and to assess residual impacts. Aerial and vessel-based surveys determined the distribution of whales before, during and after the seismic survey. Daily aerial reconnaissance helped verify whale-free areas and select the sequence of seismic lines to be surveyed. A scout vessel with MMOs aboard was positioned 4 km shoreward of the active seismic vessel to provide better visual coverage of the 4-5 km buffer and to help define the inshore edge of the 4-5 km buffer. A second scout vessel remained near the seismic vessel. Shore-based observers determined whale numbers, distribution, and behavior during and after the seismic survey. Acoustic monitoring documented received sound levels near and in the main whale feeding area. Statistical analyses of aerial survey data indicated that about 5-10 gray whales moved away from waters near (inshore of) the seismic survey during seismic operations. They shifted into the core gray whale feeding area farther south, and the proportion of gray whales observed feeding did not change over the study period. Five shutdowns of the air guns were invoked for gray whales seen within or near the buffer. A previously unknown gray whale feeding area (the Offshore feeding area) was discovered south and offshore from the nearshore Piltun feeding area. The Offshore area has subsequently been shown to be used by feeding gray whales during several years when no anthropogenic activity occurred near the Piltun feeding area.Shore-based counts indicated that whales continued to feed inshore of the Odoptu block throughout the seismic survey, with no significant correlation between gray whale abundance and seismic activity. Average values of most behavioral parameters were similar to those without seismic surveys. Univariate analysis showed no correlation between seismic sound levels and any behavioral parameter. Multiple regression analyses indicated that, after allowance for environmental covariates, 5 of 11 behavioral parameters were statistically correlated with estimated seismic survey-related variables; 6 of 11 behavioral parameters were not statistically correlated with seismic survey-related variables. Behavioral parameters that were correlated with seismic variables were transient and within the range of variation attributable to environmental effects. Acoustic monitoring determined that the 4-5 km buffer zone, in conjunction with reduction of the air gun array to 14 guns and 1,640 in(3), was effective in limiting sound exposure. Within the Piltun feeding area, these mitigation measures were designed to insure that western gray whales were not exposed to received levels exceeding the 163 dB re 1 microPa (rms) threshold. This was among the most complex and intensive mitigation programs ever conducted for any marine mammal. It provided valuable new information about underwater sounds and gray whale responses during a nearshore seismic program that will be useful in planning future work. Overall, the efforts in 2001 were successful in reducing impacts to levels tolerable by western gray whales. Research in 2002-2005 suggested no biologically significant or population-level impacts of the 2001 seismic survey.

A maize caffeoyl-CoA O-methyltransferase gene confers quantitative resistance to multiple pathogens

USDA-ARS?s Scientific Manuscript database

Alleles that confer multiple disease resistance (MDR) are valuable in crop improvement though molecular mechanisms underlying their functions remain largely unknown. A QTL, qMdr9.02, associated with resistance to three important foliar maize diseases, southern leaf blight (SLB), gray leaf spot (GLS)...

Mammal caching of oak acorns in a red pine and a mixed oak stand

Treesearch

E.R. Thorn; W.M. Tzilkowski

1991-01-01

Small mammal caching of oak (Quercus spp.) acorns in adjacent red pine (Pinus resinosa) and mixed-oak stands was investigated at The Penn State Experimental Forest, Huntingdon Co., Pennsylvania. Gray squirrels (Sciurus carolinensis) and mice (Peromyscus spp.) were the most common acorn-caching...

Detection of stable community structures within gut microbiota co-occurrence networks from different human populations.

PubMed

Jackson, Matthew A; Bonder, Marc Jan; Kuncheva, Zhana; Zierer, Jonas; Fu, Jingyuan; Kurilshikov, Alexander; Wijmenga, Cisca; Zhernakova, Alexandra; Bell, Jordana T; Spector, Tim D; Steves, Claire J

2018-01-01

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.

Co-occurrence Networks Among Bacteria and Microbial Eukaryotes of Lake Baikal During a Spring Phytoplankton Bloom.

PubMed

Mikhailov, Ivan S; Zakharova, Yulia R; Bukin, Yuri S; Galachyants, Yuri P; Petrova, Darya P; Sakirko, Maria V; Likhoshway, Yelena V

2018-06-07

The pelagic zone of Lake Baikal is an ecological niche where phytoplankton bloom causes increasing microbial abundance in spring which plays a key role in carbon turnover in the freshwater lake. Co-occurrence patterns revealed among different microbes can be applied to predict interactions between the microbes and environmental conditions in the ecosystem. We used 454 pyrosequencing of 16S rRNA and 18S rRNA genes to study bacterial and microbial eukaryotic communities and their co-occurrence patterns at the pelagic zone of Lake Baikal during a spring phytoplankton bloom. We found that microbes within one domain mostly correlated positively with each other and are highly interconnected. The highly connected taxa in co-occurrence networks were operational taxonomic units (OTUs) of Actinobacteria, Bacteroidetes, Alphaproteobacteria, and autotrophic and unclassified Eukaryota which might be analogous to microbial keystone taxa. Constrained correspondence analysis revealed the relationships of bacterial and microbial eukaryotic communities with geographical location.

Response of the oligodendrocyte progenitor cell population (defined by NG2 labelling) to demyelination of the adult spinal cord.

PubMed

Keirstead, H S; Levine, J M; Blakemore, W F

1998-02-01

Elucidation of the response of oligodendrocyte progenitor cell populations to demyelination in the adult central nervous system (CNS) is critical to understanding why remyelination fails in multiple sclerosis. Using the anti-NG2 monoclonal antibody to identify oligodendrocyte progenitor cells, we have documented their response to antibody-induced demyelination in the dorsal column of the adult rat spinal cord. The number of NG2+ cells in the vicinity of demyelinated lesions increased by 72% over the course of 3 days following the onset of demyelination. This increase in NG2+ cell numbers did not reflect a nonspecific staining of reactive cells, as GFAP, OX-42, and Rip antibodies did not co-localise with NG2 + cells in double immunostained tissue sections. NG2 + cells incorporated BrdU 48-72 h following the onset of demyelination. After the onset of remyelination (10-14 days), the number of NG2+ cells decreased to 46% of control levels and remained consistently low for 2 months. When spinal cords were exposed to 40 Grays of x-irradiation prior to demyelination, the number of NG2+ cells decreased to 48% of control levels by 3 days following the onset of demyelination and remained unchanged at 3 weeks. Since 40 Grays of x-irradiation kills dividing cells, these studies illustrate a responsive and nonresponsive NG2+ cell population following demyelination in the adult spinal cord and suggest that the responsive NG2+ cell population does not renew itself.

Substance use and regional gray matter volume in individuals at high risk of psychosis.

PubMed

Stone, James M; Bhattacharyya, Sagnik; Barker, Gareth J; McGuire, Philip K

2012-02-01

Individuals with an at risk mental state (ARMS) are at greatly increased risk of developing a psychotic illness. Risk of transition to psychosis is associated with regionally reduced cortical gray matter volume. There has been considerable interest in the interaction between psychosis risk and substance use. In this study we investigate the relationship between alcohol, cannabis and nicotine use with gray matter volume in ARMS subjects and healthy volunteers. Twenty seven ARMS subjects and 27 healthy volunteers took part in the study. All subjects underwent volumetric MRI imaging. The relationship between regional gray matter volume and cannabis use, smoking, and alcohol use in controls and ARMS subjects was analysed using voxel-based morphometry. In any region where a significant relationship with drug was present, data were analysed to determine if there was any group difference in this relationship. Alcohol intake was inversely correlated with gray matter volume in cerebellum, cannabis intake was use was inversely correlated with gray matter volume in prefrontal cortex and tobacco intake was inversely correlated with gray matter volume in left temporal cortex. There were no significant interactions by group in any region. There is no evidence to support the hypothesis of increased susceptibility to harmful effects of drugs and alcohol on regional gray matter in ARMS subjects. However, alcohol, tobacco and cannabis at low to moderate intake may be associated with lower gray matter in both ARMS subjects and healthy volunteers-possibly representing low-level cortical damage or change in neural plasticity. Copyright © 2011 Elsevier B.V. All rights reserved.

Chronic obstructive lung disease and posttraumatic stress disorder: current perspectives

PubMed Central

Abrams, Thad E; Blevins, Amy; Weg, Mark W Vander

2015-01-01

Background Several studies have reported on the co-occurrence of chronic obstructive pulmonary disease (COPD) and psychiatric conditions, with the most robust evidence base demonstrating an impact of comorbid anxiety and depression on COPD-related outcomes. In recent years, research has sought to determine if there is a co-occurrence between COPD and posttraumatic stress disorder (PTSD) as well as for associations between PTSD and COPD-related outcomes. To date, there have been no published reviews summarizing this emerging literature. Objectives The primary objective of this review was to determine if there is adequate evidence to support a co-occurrence between PTSD and COPD. Secondary objectives were to: 1) determine if there are important clinical considerations regarding the impact of PTSD on COPD management, and 2) identify targeted areas for further research. Methods A structured review was performed using a systematic search strategy limited to studies in English, addressing adults, and to articles that examined: 1) the co-occurrence of COPD and PTSD and 2) the impact of PTSD on COPD-related outcomes. To be included, articles must have addressed some type of nonreversible obstructive lung pathology. Results A total of 598 articles were identified for initial review. Upon applying the inclusion and exclusion criteria, n=19 articles or abstracts addressed our stated objectives. Overall, there is inconclusive evidence to support the co-occurrence between PTSD and COPD. Studies finding a significant co-occurrence generally had inferior methods of identifying COPD; in contrast, studies that utilized more robust COPD measures (such as a physician exam) generally failed to find a relationship. Among studies that examined the impact of PTSD on COPD-related outcomes, there was more consistent evidence that PTSD affects the perception of respiratory symptom burden and management. In addition, methods for measuring an important confounder (smoking) were generally lacking. Conclusion There is inconclusive evidence to support the co-occurrence of COPD and PTSD. There was stronger evidence implicating PTSD as an important comorbidity impacting COPD management. Further research is needed to: 1) determine whether or not COPD and PTSD are likely to be comorbid, and 2) further elucidate the mechanisms connecting PTSD and COPD-related outcomes. PMID:26508851

Chronic obstructive lung disease and posttraumatic stress disorder: current perspectives.

PubMed

Abrams, Thad E; Blevins, Amy; Weg, Mark W Vander

2015-01-01

Several studies have reported on the co-occurrence of chronic obstructive pulmonary disease (COPD) and psychiatric conditions, with the most robust evidence base demonstrating an impact of comorbid anxiety and depression on COPD-related outcomes. In recent years, research has sought to determine if there is a co-occurrence between COPD and posttraumatic stress disorder (PTSD) as well as for associations between PTSD and COPD-related outcomes. To date, there have been no published reviews summarizing this emerging literature. The primary objective of this review was to determine if there is adequate evidence to support a co-occurrence between PTSD and COPD. Secondary objectives were to: 1) determine if there are important clinical considerations regarding the impact of PTSD on COPD management, and 2) identify targeted areas for further research. A structured review was performed using a systematic search strategy limited to studies in English, addressing adults, and to articles that examined: 1) the co-occurrence of COPD and PTSD and 2) the impact of PTSD on COPD-related outcomes. To be included, articles must have addressed some type of nonreversible obstructive lung pathology. A total of 598 articles were identified for initial review. Upon applying the inclusion and exclusion criteria, n=19 articles or abstracts addressed our stated objectives. Overall, there is inconclusive evidence to support the co-occurrence between PTSD and COPD. Studies finding a significant co-occurrence generally had inferior methods of identifying COPD; in contrast, studies that utilized more robust COPD measures (such as a physician exam) generally failed to find a relationship. Among studies that examined the impact of PTSD on COPD-related outcomes, there was more consistent evidence that PTSD affects the perception of respiratory symptom burden and management. In addition, methods for measuring an important confounder (smoking) were generally lacking. There is inconclusive evidence to support the co-occurrence of COPD and PTSD. There was stronger evidence implicating PTSD as an important comorbidity impacting COPD management. Further research is needed to: 1) determine whether or not COPD and PTSD are likely to be comorbid, and 2) further elucidate the mechanisms connecting PTSD and COPD-related outcomes.

Signal recognition by green treefrogs (Hyla cinerea) and Cope's gray treefrogs (Hyla chrysoscelis) in naturally fluctuating noise.

PubMed

Vélez, Alejandro; Bee, Mark A

2013-05-01

This study tested three hypotheses about the ability of female frogs to exploit temporal fluctuations in the level of background noise to overcome the problem of recognizing male advertisement calls in noisy breeding choruses. Phonotaxis tests with green treefrogs (Hyla cinerea) and Cope's gray treefrogs (Hyla chrysoscelis) were used to measure thresholds for recognizing calls in the presence of noise maskers with (a) no level fluctuations, (b) random fluctuations, or level fluctuations characteristic of (c) conspecific choruses and (d) heterospecific choruses. The dip-listening hypothesis predicted lower signal recognition thresholds in the presence of fluctuating maskers compared with nonfluctuating maskers. Support for the dip-listening hypothesis was weak; only Cope's gray treefrogs experienced dip listening and only in the presence of randomly fluctuating maskers. The natural soundscapes advantage hypothesis predicted lower recognition thresholds when level fluctuations resembled those of natural soundscapes compared with artificial fluctuations. This hypothesis was rejected. In noise backgrounds with natural fluctuations, the species-specific advantage hypothesis predicted lower recognition thresholds when fluctuations resembled species-specific patterns of conspecific soundscapes. No evidence was found to support this hypothesis. These results corroborate previous findings showing that Cope's gray treefrogs, but not green treefrogs, experience dip listening under some noise conditions. Together, the results suggest level fluctuations in the soundscape of natural breeding choruses may present few dip-listening opportunities. The findings of this study provide little support for the hypothesis that receivers are adapted to exploit level fluctuations of natural soundscapes in recognizing communication signals.

Signal Recognition by Green Treefrogs (Hyla cinerea) and Cope’s Gray Treefrogs (Hyla chrysoscelis) in Naturally Fluctuating Noise

PubMed Central

Vélez, Alejandro; Bee, Mark A.

2013-01-01

This study tested three hypotheses about the ability of female frogs to exploit temporal fluctuations in the level of background noise to overcome the problem of recognizing male advertisement calls in noisy breeding choruses. Phonotaxis tests with green treefrogs (Hyla cinerea) and Cope’s gray treefrogs (Hyla chrysoscelis) were used to measure thresholds for recognizing calls in the presence of noise maskers with (i) no level fluctuations, (ii) random fluctuations, or level fluctuations characteristic of (iii) conspecific choruses and (iv) heterospecific choruses. The dip-listening hypothesis predicted lower signal recognition thresholds in the presence of fluctuating maskers compared with non-fluctuating maskers. Support for the dip listening hypothesis was weak; only Cope’s gray treefrogs experienced dip listening and only in the presence of randomly fluctuating maskers. The natural soundscapes advantage hypothesis predicted lower recognition thresholds when level fluctuations resembled those of natural soundscapes compared with artificial fluctuations. This hypothesis was rejected. In noise backgrounds with natural fluctuations, the species-specific advantage hypothesis predicted lower recognition thresholds when fluctuations resembled species-specific patterns of conspecific soundscapes. No evidence was found to support this hypothesis. These results corroborate previous findings showing that Cope’s gray treefrogs, but not green treefrogs, experience dip listening under some noise conditions. Together, the results suggest level fluctuations in the soundscape of natural breeding choruses may present few dip-listening opportunities. The findings of this study provide little support for the hypothesis that receivers are adapted to exploit level fluctuations of natural soundscapes in recognizing communication signals. PMID:23106802

Waves, Hydrodynamics and Sediment Transport Modeling at Grays Harbor, WA

DTIC Science & Technology

2010-12-01

Grays Harbor Federal navigation project. At the same time, offshore wind and wave data were available from NDBC Buoy 46029 and CDIP Buoy 036 / NDBC...is forced by the regional ADCIRC water levels and currents, surface wind field, and offshore waves based on the CDIP Buoy 036 (NDBC 46211). Figures

Gray matter responsiveness to adaptive working memory training: a surface-based morphometry study

PubMed Central

Román, Francisco J.; Lewis, Lindsay B.; Chen, Chi-Hua; Karama, Sherif; Burgaleta, Miguel; Martínez, Kenia; Lepage, Claude; Jaeggi, Susanne M.; Evans, Alan C.; Kremen, William S.

2016-01-01

Here we analyze gray matter indices before and after completing a challenging adaptive cognitive training program based on the n-back task. The considered gray matter indices were cortical thickness (CT) and cortical surface area (CSA). Twenty-eight young women (age range 17–22 years) completed 24 training sessions over the course of 3 months (12 weeks, 24 sessions), showing expected performance improvements. CT and CSA values for the training group were compared with those of a matched control group. Statistical analyses were computed using a ROI framework defined by brain areas distinguished by their genetic underpinning. The interaction between group and time was analyzed. Middle temporal, ventral frontal, inferior parietal cortices, and pars opercularis were the regions where the training group showed conservation of gray matter with respect to the control group. These regions support working memory, resistance to interference, and inhibition. Furthermore, an interaction with baseline intelligence differences showed that the expected decreasing trend at the biological level for individuals showing relatively low intelligence levels at baseline was attenuated by the completed training. PMID:26701168

Species distribution models for a migratory bird based on citizen science and satellite tracking data

USGS Publications Warehouse

Coxen, Christopher L.; Frey, Jennifer K.; Carleton, Scott A.; Collins, Daniel P.

2017-01-01

Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata) species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1) satellite tracked birds and 2) observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4), and high overlap between suitability scores (I statistic 0.786) and suitable habitat patches (relative rank 0.639). Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.

Gray-scale transform and evaluation for digital x-ray chest images on CRT monitor

NASA Astrophysics Data System (ADS)

Furukawa, Isao; Suzuki, Junji; Ono, Sadayasu; Kitamura, Masayuki; Ando, Yutaka

1997-04-01

In this paper, an experimental evaluation of a super high definition (SHD) imaging system for digital x-ray chest images is presented. The SHD imaging system is proposed as a platform for integrating conventional image media. We are involved in the use of SHD images in the total digitizing of medical records that include chest x-rays and pathological microscopic images, both which demand the highest level of quality among the various types of medical images. SHD images use progressive scanning and have a spatial resolution of 2000 by 2000 pixels or more and a temporal resolution (frame rate) of 60 frames/sec or more. For displaying medical x-ray images on a CRT, we derived gray scale transform characteristics based on radiologists' comments during the experiment, and elucidated the relationship between that gray scale transform and the linearization transform for maintaining the linear relationship with the luminance of film on a light box (luminance linear transform). We then carried out viewing experiments based on a five-stage evaluation. Nine radiologists participated in our experiment, and the ten cases evaluated included pulmonary fibrosis, lung cancer, and pneumonia. The experimental results indicated that conventional film images and those on super high definition CRT monitors have nearly the same quality. They also show that the gray scale transform for CRT images decided according to radiologists' comments agrees with the luminance linear transform in the high luminance region. And in the low luminance region, it was found that the gray scale transform had the characteristics of level expansion to increase the number of levels that can be expressed.

CO-OCCURRENCE OF OZONE AND ACIDIC CLOUD WATER IN HIGH-ELEVATION FORESTS

EPA Science Inventory

A chemical climatology for high-elevation forests was estimated from ozone and cloudwater acidity data collected in the eastern United States. esides frequent ozone-only and pH-only single-pollutant episodes, both simultaneous and sequential co-occurrence of ozone and acidic clou...

To compute lightness, illumination is not estimated, it is held constant.

PubMed

Gilchrist, Alan L

2018-05-03

The light reaching the eye from a surface does not indicate the black-gray-white shade of a surface (called lightness) because the effects of illumination level are confounded with the reflectance of the surface. Rotating a gray paper relative to a light source alters its luminance (intensity of light reaching the eye) but the lightness of the paper remains relatively constant. Recent publications have argued, as had Helmholtz (1866/1924), that the visual system unconsciously estimates the direction and intensity of the light source. We report experiments in which this theory was pitted against an alternative theory according to which illumination level and surface reflectance are disentangled by comparing only those surfaces that are equally illuminated, in other words, by holding illumination level constant. A 3-dimensional scene was created within which the rotation of a target surface would be expected to become darker gray according to the lighting estimation theory, but lighter gray according to the equi-illumination comparison theory, with results clearly favoring the latter. In a further experiment cues held to indicate light source direction (cast shadows, attached shadows, and glossy highlights) were completely eliminated and yet this had no effect on the results. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A comprehensive evaluation of different radiation models in a gas turbine combustor under conditions of oxy-fuel combustion with dry recycle

NASA Astrophysics Data System (ADS)

Kez, V.; Liu, F.; Consalvi, J. L.; Ströhle, J.; Epple, B.

2016-03-01

The oxy-fuel combustion is a promising CO2 capture technology from combustion systems. This process is characterized by much higher CO2 concentrations in the combustion system compared to that of the conventional air-fuel combustion. To accurately predict the enhanced thermal radiation in oxy-fuel combustion, it is essential to take into account the non-gray nature of gas radiation. In this study, radiation heat transfer in a 3D model gas turbine combustor under two test cases at 20 atm total pressure was calculated by various non-gray gas radiation models, including the statistical narrow-band (SNB) model, the statistical narrow-band correlated-k (SNBCK) model, the wide-band correlated-k (WBCK) model, the full spectrum correlated-k (FSCK) model, and several weighted sum of gray gases (WSGG) models. Calculations of SNB, SNBCK, and FSCK were conducted using the updated EM2C SNB model parameters. Results of the SNB model are considered as the benchmark solution to evaluate the accuracy of the other models considered. Results of SNBCK and FSCK are in good agreement with the benchmark solution. The WBCK model is less accurate than SNBCK or FSCK. Considering the three formulations of the WBCK model, the multiple gases formulation is the best choice regarding the accuracy and computational cost. The WSGG model with the parameters of Bordbar et al. (2014) [20] is the most accurate of the three investigated WSGG models. Use of the gray WSSG formulation leads to significant deviations from the benchmark data and should not be applied to predict radiation heat transfer in oxy-fuel combustion systems. A best practice to incorporate the state-of-the-art gas radiation models for high accuracy of radiation heat transfer calculations at minimal increase in computational cost in CFD simulation of oxy-fuel combustion systems for pressure path lengths up to about 10 bar m is suggested.

Plasma copeptin as a predictor of intoxication severity and delayed neurological sequelae in acute carbon monoxide poisoning.

PubMed

Pang, Li; Wang, He-Lei; Wang, Zhi-Hao; Wu, Yang; Dong, Ning; Xu, Da-Hai; Wang, Da-Wei; Xu, Hong; Zhang, Nan

2014-09-01

The present study was designed to assess the usefulness of measuring plasma levels of copeptin (a peptide co-released with the hypothalamic stress hormone vasopressin) as a biomarker for the severity of carbon monoxide (CO) poisoning and for predicting delayed neurological sequelae (DNS). Seventy-two patients with CO poisoning and 72 sex and age matched healthy individuals were recruited. Plasma copeptin levels were measured on admission from CO poisoning patients and for healthy individuals at study entry by using a sandwich immunoassay. The CO poisoning patients were divided into two groups according to severity (unconscious and conscious) and occurrence of DNS. The mean plasma copeptin levels (52.5±18.5 pmol/L) in the unconscious group were significantly higher than in the conscious group (26.3±12.7 pmol/L) (P<0.001). Plasma copeptin levels of more than 39.0 pmol/L detected CO poisoning with severe neurological symptoms e.g. unconsciousness (sensitivity 84.6% and specificity 81.4%). The plasma copeptin levels were higher in patients with DNS compared to patients without DNS (52.2±20.6 pmol/L vs. 27.9±14.8 pmol/L, P<0.001). Plasma copeptin levels higher than 40.5 pmol/L predicted the development of DNS (sensitivity 77.8%, specificity 82.1%). Plasma copeptin levels were identified as an independent predictor for intoxication severity [odds ratio (OR) 1.261, 95% confidence interval (CI) 1.112-1.638, P=0.002] and DNS (OR 1.313, 95% CI 1.106-1.859, P=0.001). Thus, plasma copeptin levels independently related to intoxication severity and were identified as a novel biomarker for predicting DNS after acute CO poisoning. Copyright © 2014 Elsevier Inc. All rights reserved.

Automated Texture Classification of the Mawrth Vallis Landing Site Region

NASA Astrophysics Data System (ADS)

Parente, M.; Bayley, L.; Hunkins, L.; McKeown, N. K.; Bishop, J. L.

2009-12-01

Supervised classification techniques have been developed to discriminate geomorphologic units in HiRISE images of Mawrth Vallis on Mars, one of the MSL candidate landing sites. A variety of clay minerals that indicate water was once present have been identified in the ancient bedrock at Mawrth Vallis [1-7]. These clay-rich rocks exhibit distinct surface textures in HiRISE images, where the nontronite-bearing unit consists of two primary textures: 2-5 m irregular inverted polygons and irregular parallel fracture sets ([8,13], Fig. b-c). In contrast, the montmorillonite-bearing unit consists of 0.5-1.5 m regular polygons ([8,13], Fig. e). We also characterized dunes (Fig. d), and the spectrally unremarkable caprock unit (Fig. a). Classification of these textures was performed by extracting discriminatory features from gray-level run length matrices (GLRLMs) [9], gray-level co-occurrence matrices (GLCMs) [10], and semivariograms [11] calculated for small blocks of data in HiRISE images. Preliminary results using an algorithm containing eight of these classification features produced a texture classification technique that is 85 percent accurate. The discriminant analysis (e.g. [12]) classifier we used modeled a linear discriminant function for each class based on the training feature vectors for that class. The test vector with the largest value for its discriminant function was then assigned to each class. We assumed linear functions were acceptable for small training sets and we performed automated selection in order to identify the most discriminative features for the textures in Mawrth Vallis. Continued efforts are underway to test and refine this procedure in order to optimize texture recognition on a broader collection of textures, representing additional surface components from Mawrth Vallis and other landing sites on Mars. [1] Bibring, J.-P., et al. (2005) Science, 307, 1576-1581. [2] Poulet, F., et al. (2005) Nature, 438, 632-627. [3] Bishop, J. L., et al. (2008) Science, 321, 830-833. [4] Wray, J. J., et al. (2008) GRL, 35, L12202. [5] Loizeau, D., et al. (2009) Icarus, (in press). [6] McKeown, N. K., et al. (2009) JGR- Planets, (in press). [7] Noe Dobrea, E. Z., et al. (2009) JGR- Planets, (in revision). [8] McKeown, N. K. et al. (2009) LPSC abs. #2433. [9] Galloway, M. M., (1975),Computer Graphics and Image Processing 4, 172-179. [10] Haralick, R. M., (1973) IEEE Trans. on Systems, Man and Cybernetics 3, 610-621. [11] Curran, P. J., Remote Sensing of Environment 24, 493-507, 1988. [12] Hastie T., et al. (2005), The elements of statistical learning. Springer. [13] McKeown, N. K., et al. (2009) AGU

Network analysis reveals seasonal variation of co-occurrence correlations between Cyanobacteria and other bacterioplankton.

PubMed

Zhao, Dayong; Shen, Feng; Zeng, Jin; Huang, Rui; Yu, Zhongbo; Wu, Qinglong L

2016-12-15

Association network approaches have recently been proposed as a means for exploring the associations between bacterial communities. In the present study, high-throughput sequencing was employed to investigate the seasonal variations in the composition of bacterioplankton communities in six eutrophic urban lakes of Nanjing City, China. Over 150,000 16S rRNA sequences were derived from 52 water samples, and correlation-based network analyses were conducted. Our results demonstrated that the architecture of the co-occurrence networks varied in different seasons. Cyanobacteria played various roles in the ecological networks during different seasons. Co-occurrence patterns revealed that members of Cyanobacteria shared a very similar niche and they had weak positive correlations with other phyla in summer. To explore the effect of environmental factors on species-species co-occurrence networks and to determine the most influential environmental factors, the original positive network was simplified by module partitioning and by calculating module eigengenes. Module eigengene analysis indicated that temperature only affected some Cyanobacteria; the rest were mainly affected by nitrogen associated factors throughout the year. Cyanobacteria were dominant in summer which may result from strong co-occurrence patterns and suitable living conditions. Overall, this study has improved our understanding of the roles of Cyanobacteria and other bacterioplankton in ecological networks. Copyright © 2016 Elsevier B.V. All rights reserved.

Intimate Partner Violence and Cigarette Smoking: Association Between Smoking Risk and Psychological Abuse With and Without Co-Occurrence of Physical and Sexual Abuse

PubMed Central

Jun, Hee-Jin; Rich-Edwards, Janet W.; Boynton-Jarrett, Renée; Wright, Rosalind J.

2008-01-01

Objectives. We examined the association between psychological abuse in a current relationship and current cigarette smoking among women, with and without the co-occurrence of physical or sexual abuse. Methods. Women’s experience of psychological abuse, experience of physical or sexual abuse, and smoking status were ascertained through a survey of female nurses. A score of 20 or more on the Women’s Experience With Battering scale defined psychological abuse. We used logistic regression to predict current smoking, adjusting for demographic and social covariates. Analyses included women in a current relationship (n=54200). Results. Adjusted analyses demonstrated that women experiencing only psychological abuse alone were 33% (95% confidence interval [CI]=13%, 57%) more likely to smoke than nonabused women. Compared with nonabused women, psychologically abused women’s risk of smoking was greater if they reported a single co-occurrence of physical or sexual abuse (odds ratio [OR]=1.5; 95% CI=1.3, 1.8) or multiple co-occurrences (OR=1.9; 95% CI=1.7, 2.3). Conclusions. Psychological abuse in a current relationship was associated with an increased risk of smoking in this cohort of largely White, well-educated, and employed women. The co-occurrence of physical or sexual abuse enhanced that risk. Further research is needed to see if these associations hold for other groups. PMID:17600272

The Co-Occurrence of Autism and Attention Deficit Hyperactivity Disorder in Children – What Do We Know?

PubMed Central

Leitner, Yael

2014-01-01

Symptoms of attention deficit hyperactivity disorder (ADHD) and autistic spectrum disorder (ASD) often co-occur. The DSM-IV had specified that an ASD diagnosis is an exclusion criterion for ADHD, thereby limiting research of this common clinical co-occurrence. As neurodevelopmental disorders, both ASD and ADHD share some phenotypic similarities, but are characterized by distinct diagnostic criteria. The present review will examine the frequency and implications of this clinical co-occurrence in children, with an emphasis on the available data regarding pre-school age. The review will highlight possible etiologies explaining it, and suggest future research directions necessary to enhance our understanding of both etiology and therapeutic interventions, in light of the new DSM-V criteria, allowing for a dual diagnosis. PMID:24808851

Physical activity, fitness, and gray matter volume

PubMed Central

Erickson, Kirk I.; Leckie, Regina L.; Weinstein, Andrea M.

2014-01-01

In this review we explore the association between physical activity, cardiorespiratory fitness, and exercise on gray matter volume in older adults. We conclude that higher cardiorespiratory fitness levels are routinely associated with greater gray matter volume in the prefrontal cortex and hippocampus, and less consistently in other regions. We also conclude that physical activity is associated with greater gray matter volume in the same regions that are associated with cardiorespiratory fitness including the prefrontal cortex and hippocampus. Some heterogeneity in the literature may be explained by effect moderation by age, stress, or other factors. Finally, we report promising results from randomized exercise interventions that suggest that the volume of the hippocampus and prefrontal cortex remain pliable and responsive to moderate intensity exercise for 6-months to 1-year. Physical activity appears to be a propitious method for influencing gray matter volume in late adulthood, but additional well-controlled studies are necessary to inform public policies about the potential protective or therapeutic effects of exercise on brain volume. PMID:24952993

Bicarbonate-dependent, carbonate radical anion-driven tocopherol-mediated human LDL peroxidation: an in vitro and in vivo study.

PubMed

Lapenna, Domenico; Ciofani, Giuliano; Cuccurullo, Chiara; Neri, Matteo; Giamberardino, Maria Adele; Cuccurullo, Franco

2012-11-01

We have here investigated possible occurrence of bicarbonate-dependent, carbonate radical anion (CO(3)(•-))-driven tocopherol-mediated human LDL peroxidation (TMP) in vitro and in vivo. CO(3)(•-), generated in vitro by the SOD1/H(2)O(2)/bicarbonate system, readily promoted TMP, which was dependent on α-tocopherol and bicarbonate concentrations, and was inhibited by the CO(3)(•-) scavenger ethanol; moreover, TMP induced in vitro by the SOD1/H(2)O(2)/bicarbonate system occurred in the presence of α-tocopherol that typically underwent slow oxidative consumption. In the in vivo clinical setting, we showed that, compared to controls, hypertensive patients with diuretic-induced metabolic alkalosis and heightened blood bicarbonate concentration had lipid hydroperoxide burden and decreased α-tocopherol content in the LDL fraction, with direct significant correlation between the LDL levels of α-tocopherol and those of lipid hydroperoxides; remarkably, after resolution of metabolic alkalosis, together with normalization of blood bicarbonate concentration, the LDL content of lipid hydroperoxides was decreased and that of α-tocopherol augmented significantly. These findings suggest bicarbonate-dependent, CO(3)(•-)-driven LDL TMP in vivo. In conclusion, the present study highlights the occurrence of bicarbonate-dependent, CO(3)(•-)-driven human LDL TMP, the role of which in pathological conditions such as atherosclerosis warrants, however, further investigation.

Factors associated with sources, transport, and fate of chloroform and three other trihalomethanes in untreated groundwater used for drinking water

USGS Publications Warehouse

Carter, Janet M.; Moran, Michael J.; Zogorski, John S.; Price, Curtis V.

2012-01-01

Multiple lines of evidence for indicating factors associated with the sources, transport, and fate of chloroform and three other trihalomethanes (THMs) in untreated groundwater were revealed by evaluating low-level analytical results and logistic regression results for THMs. Samples of untreated groundwater from wells used for drinking water were collected from 1996-2007 from 2492 wells across the United States and analyzed for chloroform, bromodichloromethane, dibromochloromethane, and bromoform by a low-level analytical method implemented in April 1996. Using an assessment level of 0.02 μg/L, chloroform was detected in 36.5% of public-well samples and 17.6% of domestic-well samples, with most concentrations less than 1 μg/L. Brominated THMs occurred less frequently than chloroform but more frequently in public-well samples than domestic-well samples. For both public and domestic wells, THMs occurred most frequently in urban areas. Logistic regression analyses showed that the occurrence of THMs was related to nonpoint sources such as urban land use and to point sources like septic systems. The frequent occurrence and concentration distribution pattern of THMs, as well as their frequent co-occurrence with other organic compounds and nitrate, all known to have anthropogenic sources, and the positive associations between THM occurrence and dissolved oxygen and recharge indicate the recycling of water that contains THMs and other anthropogenic contaminants.

Tissue-Selective Salvage of the White Matter by Successful Endovascular Stroke Therapy.

PubMed

Kleine, Justus F; Kaesmacher, Mirjam; Wiestler, Benedikt; Kaesmacher, Johannes

2017-10-01

White matter (WM) is less vulnerable to ischemia than gray matter. In ischemic stroke caused by acute large-vessel occlusion, successful recanalization might therefore sometimes selectively salvage the WM, leading to infarct patterns confined to gray matter. This study examines occurrence, determinants, and clinical significance of such effects. Three hundred twenty-two patients with acute middle cerebral artery occlusion subjected to mechanical thrombectomy were included. Infarct patterns were categorized into WM - (sparing the WM) and WM + (involving WM). National Institutes of Health Stroke Scale-based measures of neurological outcome, including National Institutes of Health Stroke Scale improvement or National Institutes of Health Stroke Scale worsening, good functional midterm outcome (day 90-modified Rankin Scale score of ≤2), the occurrence of malignant swelling, and in-hospital mortality were predefined outcome measures. WM - infarcts occurred in 118 of 322 patients and were associated with successful recanalization and better collateral grades ( P <0.05). Shorter symptom-onset to recanalization times were also associated with WM - infarcts in univariate analysis, but not when adjusted for collateral grades. WM - infarcts were independently associated with good neurological outcome (adjusted odds ratio, 3.003; 95% confidence interval, 1.186-7.607; P =0.020) and good functional midterm outcome (adjusted odds ratio, 8.618; 95% confidence interval, 2.409-30.828; P =0.001) after correcting for potential confounders, including final infarct volume. Only 2.6% of WM - patients, but 20.5% of WM + patients exhibited neurological worsening, and none versus 12.8% developed malignant swelling ( P <0.001), contributing to lower mortality in this group (2.5% versus 10.3%; P =0.014). WM infarction commonly commences later than gray matter infarction after acute middle cerebral artery occlusion. Successful recanalization can therefore salvage completely the WM at risk in many patients even several hours after symptom onset. Preservation of the WM is associated with better neurological recovery, prevention of malignant swelling, and reduced mortality. This has important implications for neuroprotective strategies, and perfusion imaging-based patient selection, and provides a rationale for treating selected patients in extended time windows. © 2017 American Heart Association, Inc.

Socioeconomic and Marital Outcomes of Adolescent Marriage, Adolescent Childbirth, and Their Co-Occurrence.

ERIC Educational Resources Information Center

Teti, Douglas M.; Lamb, Michael E.

1989-01-01

Examined adolescent marriage, adolescent childbirth, and their co-occurrence in adult women. Poorest socioeconomic outcomes were associated with adolescent childbirth regardless of presence or timing of first marriage. Marital instability was associated with both adolescent marriage and adolescent childbirth. Findings suggest that risk associated…

Visualizing the Structure of Medical Informatics Using Term Co-Occurrence Analysis.

ERIC Educational Resources Information Center

Morris, Theodore Allan

2000-01-01

Examines the structure of medical informatics and the relationship between biomedicine and information science and information technology. Uses co-occurrence analysis of subject headings assigned to items indexed for MEDLINE as well as multidimensional scaling to show seven to eight broad multidisciplinary subject clusters. (Contains 28…

Drunkorexia: Understanding the Co-Occurrence of Alcohol Consumption and Eating/Exercise Weight Management Behaviors

ERIC Educational Resources Information Center

Barry, Adam E.; Piazza-Gardner, Anna K.

2012-01-01

Objective: Examine the co-occurrence of alcohol consumption, physical activity, and disordered eating behaviors via a drunkorexia perspective. Participants: Nationally representative sample (n = 22,488) of college students completing the Fall 2008 National College Health Assessment. Methods: Hierarchical logistic regression was employed to…

Natural Co-Occurrence of Mycotoxins in Foods and Feeds and Their in vitro Combined Toxicological Effects.

PubMed

Smith, Marie-Caroline; Madec, Stéphanie; Coton, Emmanuel; Hymery, Nolwenn

2016-03-26

Some foods and feeds are often contaminated by numerous mycotoxins, but most studies have focused on the occurrence and toxicology of a single mycotoxin. Regulations throughout the world do not consider the combined effects of mycotoxins. However, several surveys have reported the natural co-occurrence of mycotoxins from all over the world. Most of the published data has concerned the major mycotoxins aflatoxins (AFs), ochratoxin A (OTA), zearalenone (ZEA), fumonisins (FUM) and trichothecenes (TCTs), especially deoxynivalenol (DON). Concerning cereals and derived cereal product samples, among the 127 mycotoxin combinations described in the literature, AFs+FUM, DON+ZEA, AFs+OTA, and FUM+ZEA are the most observed. However, only a few studies specified the number of co-occurring mycotoxins with the percentage of the co-contaminated samples, as well as the main combinations found. Studies of mycotoxin combination toxicity showed antagonist, additive or synergic effects depending on the tested species, cell model or mixture, and were not necessarily time- or dose-dependent. This review summarizes the findings on mycotoxins and their co-occurrence in various foods and feeds from all over the world as well as in vitro experimental data on their combined toxicity.

Natural Co-Occurrence of Mycotoxins in Foods and Feeds and Their in vitro Combined Toxicological Effects

PubMed Central

Smith, Marie-Caroline; Madec, Stéphanie; Coton, Emmanuel; Hymery, Nolwenn

2016-01-01

Some foods and feeds are often contaminated by numerous mycotoxins, but most studies have focused on the occurrence and toxicology of a single mycotoxin. Regulations throughout the world do not consider the combined effects of mycotoxins. However, several surveys have reported the natural co-occurrence of mycotoxins from all over the world. Most of the published data has concerned the major mycotoxins aflatoxins (AFs), ochratoxin A (OTA), zearalenone (ZEA), fumonisins (FUM) and trichothecenes (TCTs), especially deoxynivalenol (DON). Concerning cereals and derived cereal product samples, among the 127 mycotoxin combinations described in the literature, AFs+FUM, DON+ZEA, AFs+OTA, and FUM+ZEA are the most observed. However, only a few studies specified the number of co-occurring mycotoxins with the percentage of the co-contaminated samples, as well as the main combinations found. Studies of mycotoxin combination toxicity showed antagonist, additive or synergic effects depending on the tested species, cell model or mixture, and were not necessarily time- or dose-dependent. This review summarizes the findings on mycotoxins and their co-occurrence in various foods and feeds from all over the world as well as in vitro experimental data on their combined toxicity. PMID:27023609

Image Edge Extraction via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A. (Inventor); Klinko, Steve (Inventor)

2008-01-01

A computer-based technique for detecting edges in gray level digital images employs fuzzy reasoning to analyze whether each pixel in an image is likely on an edge. The image is analyzed on a pixel-by-pixel basis by analyzing gradient levels of pixels in a square window surrounding the pixel being analyzed. An edge path passing through the pixel having the greatest intensity gradient is used as input to a fuzzy membership function, which employs fuzzy singletons and inference rules to assigns a new gray level value to the pixel that is related to the pixel's edginess degree.

Evolutionary Importance of the Intramolecular Pathways of Hydrolysis of Phosphate Ester Mixed Anhydrides with Amino Acids and Peptides

NASA Astrophysics Data System (ADS)

Liu, Ziwei; Beaufils, Damien; Rossi, Jean-Christophe; Pascal, Robert

2014-12-01

Aminoacyl adenylates (aa-AMPs) constitute essential intermediates of protein biosynthesis. Their polymerization in aqueous solution has often been claimed as a potential route to abiotic peptides in spite of a highly efficient CO2-promoted pathway of hydrolysis. Here we investigate the efficiency and relevance of this frequently overlooked pathway from model amino acid phosphate mixed anhydrides including aa-AMPs. Its predominance was demonstrated at CO2 concentrations matching that of physiological fluids or that of the present-day ocean, making a direct polymerization pathway unlikely. By contrast, the occurrence of the CO2-promoted pathway was observed to increase the efficiency of peptide bond formation owing to the high reactivity of the N-carboxyanhydride (NCA) intermediate. Even considering CO2 concentrations in early Earth liquid environments equivalent to present levels, mixed anhydrides would have polymerized predominantly through NCAs. The issue of a potential involvement of NCAs as biochemical metabolites could even be raised. The formation of peptide-phosphate mixed anhydrides from 5(4H)-oxazolones (transiently formed through prebiotically relevant peptide activation pathways) was also observed as well as the occurrence of the reverse cyclization process in the reactions of these mixed anhydrides. These processes constitute the core of a reaction network that could potentially have evolved towards the emergence of translation.

Exploring the role of testosterone in the cerebellum link to neuroticism: From adolescence to early adulthood.

PubMed

Schutter, Dennis J L G; Meuwese, Rosa; Bos, Marieke G N; Crone, Eveline A; Peper, Jiska S

2017-04-01

Previous research has found an association between a smaller cerebellar volume and higher levels of neuroticism. The steroid hormone testosterone reduces stress responses and the susceptibility to negative mood. Together with in vitro studies showing a positive effect of testosterone on cerebellar gray matter volumes, we set out to explore the role of testosterone in the relation between cerebellar gray matter and neuroticism. Structural magnetic resonance imaging scans were acquired, and indices of neurotic personality traits were assessed by administering the depression and anxiety scale of the revised NEO personality inventory and Gray's behavioural avoidance in one hundred and forty-nine healthy volunteers between 12 and 27 years of age. Results demonstrated an inverse relation between total brain corrected cerebellar volumes and neurotic personality traits in adolescents and young adults. In males, higher endogenous testosterone levels were associated with lower scores on neurotic personality traits and larger cerebellar gray matter volumes. No such relations were observed in the female participants. Analyses showed that testosterone significantly mediated the relation between male cerebellar gray matter and measures of neuroticism. Our findings on the interrelations between endogenous testosterone, neuroticism and cerebellar morphology provide a cerebellum-oriented framework for the susceptibility to experience negative emotions and mood in adolescence and early adulthood. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Multidecadal increase in North Atlantic coccolithophores and the potential role of rising CO2

NASA Astrophysics Data System (ADS)

Rivero-Calle, Sara; Gnanadesikan, Anand; Del Castillo, Carlos E.; Balch, William M.; Guikema, Seth D.

2015-12-01

As anthropogenic carbon dioxide (CO2) emissions acidify the oceans, calcifiers generally are expected to be negatively affected. However, using data from the Continuous Plankton Recorder, we show that coccolithophore occurrence in the North Atlantic increased from ~2 to more than 20% from 1965 through 2010. We used random forest models to examine more than 20 possible environmental drivers of this change, finding that CO2 and the Atlantic Multidecadal Oscillation were the best predictors, leading us to hypothesize that higher CO2 levels might be encouraging growth. A compilation of 41 independent laboratory studies supports our hypothesis. Our study shows a long-term basin-scale increase in coccolithophores and suggests that increasing CO2 and temperature have accelerated the growth of a phytoplankton group that is important for carbon cycling.

Alcohol-Use Disorders and Nonmedical Use of Prescription Drugs Among U.S. College Students*

PubMed Central

McCABE, SEAN ESTEBAN; WEST, BRADY T.; WECHSLER, HENRY

2008-01-01

Objective The purpose of this study was to examine the association between Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), alcohol-use disorders (AUDs) and nonmedical use of prescription drugs (NMPD) among U.S. college students. A secondary aim of this study was to identify individual-level and college-level characteristics associated with the co-occurrence of AUDs and NMPD. Method Data were collected from self-administered mail surveys, sent to a random sample of approximately 14,000 college students from a nationally representative sample of 119 U.S. colleges and universities. Results Among U.S. college students, those with AUDs represented approximately 75% of nonmedical users of prescription drugs. Multivariate logistic regression analyses indicated that college students with past-year DSM-IV alcohol abuse only (adjusted odds ratio [AOR] = 4.46, 95% confidence interval [CI] = 3.59-5.55) and students with past-year DSM-IV alcohol dependence (AOR = 9.17, 95% CI = 7.05-11.93) had significantly increased odds of NMPD in the past year compared with students without AUDs. The co-occurrence of AUDs and NMPD was more likely among college students who were male, white, earned lower grade point averages, and attended co-ed colleges and institutions located in Southern or Northeastern U.S. regions. Conclusions The findings provide evidence that NMPD is more prevalent among those college students with AUDs, especially individuals with past-year DSM-IV alcohol dependence. The assessment and treatment of AUDs among college students should account for other forms of drug use such as NMPD. PMID:17568959

Growth, photosynthetic acclimation and yield quality in legumes under climate change simulations: an updated survey.

PubMed

Irigoyen, J J; Goicoechea, N; Antolín, M C; Pascual, I; Sánchez-Díaz, M; Aguirreolea, J; Morales, F

2014-09-01

Continued emissions of CO2, derived from human activities, increase atmospheric CO2 concentration. The CO2 rise stimulates plant growth and affects yield quality. Effects of elevated CO2 on legume quality depend on interactions with N2-fixing bacteria and mycorrhizal fungi. Growth at elevated CO2 increases photosynthesis under short-term exposures in C3 species. Under long-term exposures, however, plants generally acclimate to elevated CO2 decreasing their photosynthetic capacity. An updated survey of the literature indicates that a key factor, perhaps the most important, that characteristically influences this phenomenon, its occurrence and extent, is the plant source-sink balance. In legumes, the ability of exchanging C for N at nodule level with the N2-fixing symbionts creates an extra C sink that avoids the occurrence of photosynthetic acclimation. Arbuscular mycorrhizal fungi colonizing roots may also result in increased C sink, preventing photosynthetic acclimation. Defoliation (Anthyllis vulneraria, simulated grazing) or shoot cutting (alfalfa, usual management as forage) largely increases root/shoot ratio. During re-growth at elevated CO2, new shoots growth and nodule respiration function as strong C sinks that counteracts photosynthetic acclimation. In the presence of some limiting factor, the legumes response to elevated CO2 is weakened showing photosynthetic acclimation. This survey has identified limiting factors that include an insufficient N supply from bacterial strains, nutrient-poor soils, low P supply, excess temperature affecting photosynthesis and/or nodule activity, a genetically determined low nodulation capacity, an inability of species or varieties to increase growth (and therefore C sink) at elevated CO2 and a plant phenological state or season when plant growth is stopped. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Decreased hepatic contents of coenzyme A molecular species in mice after subchronic mild social defeat stress.

PubMed

Kubota, Yoshifumi; Goto, Tatsuhiko; Hagiya, Yuki; Chohnan, Shigeru; Toyoda, Atsushi

2016-01-01

Social stress may precipitate psychiatric disorders such as depression, which is related to the occurrence of the metabolic syndrome, including obesity and type 2 diabetes. We have evaluated the effects of social stress on central and peripheral metabolism using a model of depression in mice. In the present study, we focused on coenzyme A (CoA) molecular species [i.e. non-esterified CoA (CoASH), acetyl-CoA and malonyl-CoA] which play important roles in numerous metabolic pathways, and we analyzed changes in expression of these molecules in the hypothalamus and liver of adult male mice (C57BL/6J) subjected to 10 days of subchronic mild social defeat stress (sCSDS) with ICR mice as aggressors. Mice (n = 12) exposed to showed hyperphagia- and polydipsia-like symptoms and increased body weight gain compared with control mice which were not affected by exposure to ICR mice (n = 12). To elucidate the underlying metabolic features in the sCSDS model, acetyl-CoA, malonyl-CoA and CoASH tissue levels were analyzed using the acyl-CoA cycling method. The levels of hypothalamic malonyl-CoA, which decreases feeding behavior, were not influenced by sCSDS. However, sCSDS reduced levels of acetyl-CoA, malonyl-CoA and total CoA (sum of the three CoA molecular species) in the liver. Hence, hyperphagia-like symptoms in sCSDS mice evidently occurred independently of hypothalamic malonyl-CoA, but might consequently lead to down-regulation of hepatic CoA via altered expression of nudix hydrolase 7. Future studies should investigate the molecular mechanism(s) underlying the down-regulation of liver CoA pools in sCSDS mice.

On the relationship between positive and negative affect: Their correlation and their co-occurrence.

PubMed

Larsen, Jeff T; Hershfield, Hal E; Stastny, Bradley J; Hester, Neil

2017-03-01

Understanding the nature of emotional experience requires understanding the relationship between positive and negative affect. Two particularly important aspects of that relationship are the extent to which positive and negative affect are correlated with one another and the extent to which they co-occur. Some researchers have assumed that weak negative correlations imply greater co-occurrence (i.e., more mixed emotions) than do strong negative correlations, but others have noted that correlations may imply very little about co-occurrence. We investigated the relationship between the correlation between positive and negative affect and co-occurrence. Participants in each of 2 samples provided moment-to-moment happiness and sadness ratings as they watched an evocative film and listened to music. Results indicated (a) that 4 measures of the correlation between positive and negative affect were quite highly related to 1 another; (b) that the strength of the correlation between measures of mixed emotions varied considerably; (c) that correlational measures were generally (but not always) weakly correlated with mixed emotion measures; and (d) that bittersweet stimuli consistently led to elevations in mixed emotion measures but did not consistently weaken the correlation between positive and negative affect. Results highlight that the correlation between positive and negative affect and their co-occurrence are distinct aspects of the relationship between positive and negative affect. Such insight helps clarify the implications of existing work on age-related and cultural differences in emotional experience and sets the stage for greater understanding of the experience of mixed emotions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Reduced Brain Gray Matter Concentration in Patients With Obstructive Sleep Apnea Syndrome

PubMed Central

Joo, Eun Yeon; Tae, Woo Suk; Lee, Min Joo; Kang, Jung Woo; Park, Hwan Seok; Lee, Jun Young; Suh, Minah; Hong, Seung Bong

2010-01-01

Study Objectives: To investigate differences in brain gray matter concentrations or volumes in patients with obstructive sleep apnea syndrome (OSA) and healthy volunteers. Designs: Optimized voxel-based morphometry, an automated processing technique for MRI, was used to characterize structural differences in gray matter in newly diagnosed male patients. Setting: University hospital Patients and Participants: The study consisted of 36 male OSA and 31 non-apneic male healthy volunteers matched for age (mean age, 44.8 years). Interventions: Using the t-test, gray matter differences were identified. The statistical significance level was set to a false discovery rate P < 0.05 with an extent threshold of kE > 200 voxels. Measurements and Results: The mean apnea-hypopnea index (AHI) of patients was 52.5/ h. On visual inspection of MRI, no structural abnormalities were observed. Compared to healthy volunteers, the gray matter concentrations of OSA patients were significantly decreased in the left gyrus rectus, bilateral superior frontal gyri, left precentral gyrus, bilateral frontomarginal gyri, bilateral anterior cingulate gyri, right insular gyrus, bilateral caudate nuclei, bilateral thalami, bilateral amygdalo-hippocampi, bilateral inferior temporal gyri, and bilateral quadrangular and biventer lobules in the cerebellum (false discovery rate P < 0.05). Gray matter volume was not different between OSA patients and healthy volunteers. Conclusions: The brain gray matter deficits may suggest that memory impairment, affective and cardiovascular disturbances, executive dysfunctions, and dysregulation of autonomic and respiratory control frequently found in OSA patients might be related to morphological differences in the brain gray matter areas. Citation: Joo EY; Tae WS; Lee MJ; Kang JW; Park HS; Lee JY; Suh M; Hong SB. Reduced brain gray matter concentration in patients with obstructive sleep apnea syndrome. SLEEP 2010;33(2):235-241. PMID:20175407

Migratory behavior of eastern North Pacific gray whales tracked using a hydrophone array

PubMed Central

Helble, Tyler A.; D’Spain, Gerald L.; Weller, David W.; Wiggins, Sean M.; Hildebrand, John A.

2017-01-01

Eastern North Pacific gray whales make one of the longest annual migrations of any mammal, traveling from their summer feeding areas in the Bering and Chukchi Seas to their wintering areas in the lagoons of Baja California, Mexico. Although a significant body of knowledge on gray whale biology and behavior exists, little is known about their vocal behavior while migrating. In this study, we used a sparse hydrophone array deployed offshore of central California to investigate how gray whales behave and use sound while migrating. We detected, localized, and tracked whales for one full migration season, a first for gray whales. We verified and localized 10,644 gray whale M3 calls and grouped them into 280 tracks. Results confirm that gray whales are acoustically active while migrating and their swimming and acoustic behavior changes on daily and seasonal time scales. The seasonal timing of the calls verifies the gray whale migration timing determined using other methods such as counts conducted by visual observers. The total number of calls and the percentage of calls that were part of a track changed significantly over both seasonal and daily time scales. An average calling rate of 5.7 calls/whale/day was observed, which is significantly greater than previously reported migration calling rates. We measured a mean speed of 1.6 m/s and quantified heading, direction, and water depth where tracks were located. Mean speed and water depth remained constant between night and day, but these quantities had greater variation at night. Gray whales produce M3 calls with a root mean square source level of 156.9 dB re 1 μPa at 1 m. Quantities describing call characteristics were variable and dependent on site-specific propagation characteristics. PMID:29084266

Accelerated Gray and White Matter Deterioration With Age in Schizophrenia.

PubMed

Cropley, Vanessa L; Klauser, Paul; Lenroot, Rhoshel K; Bruggemann, Jason; Sundram, Suresh; Bousman, Chad; Pereira, Avril; Di Biase, Maria A; Weickert, Thomas W; Weickert, Cynthia Shannon; Pantelis, Christos; Zalesky, Andrew

2017-03-01

Although brain changes in schizophrenia have been proposed to mirror those found with advancing age, the trajectory of gray matter and white matter changes during the disease course remains unclear. The authors sought to measure whether these changes in individuals with schizophrenia remain stable, are accelerated, or are diminished with age. Gray matter volume and fractional anisotropy were mapped in 326 individuals diagnosed with schizophrenia or schizoaffective disorder and in 197 healthy comparison subjects aged 20-65 years. Polynomial regression was used to model the influence of age on gray matter volume and fractional anisotropy at a whole-brain and voxel level. Between-group differences in gray matter volume and fractional anisotropy were regionally localized across the lifespan using permutation testing and cluster-based inference. Significant loss of gray matter volume was evident in schizophrenia, progressively worsening with age to a maximal loss of 8% in the seventh decade of life. The inferred rate of gray matter volume loss was significantly accelerated in schizophrenia up to middle age and plateaued thereafter. In contrast, significant reductions in fractional anisotropy emerged in schizophrenia only after age 35, and the rate of fractional anisotropy deterioration with age was constant and best modeled with a straight line. The slope of this line was 60% steeper in schizophrenia relative to comparison subjects, indicating a significantly faster rate of white matter deterioration with age. The rates of reduction of gray matter volume and fractional anisotropy were significantly faster in males than in females, but an interaction between sex and diagnosis was not evident. The findings suggest that schizophrenia is characterized by an initial, rapid rate of gray matter loss that slows in middle life, followed by the emergence of a deficit in white matter that progressively worsens with age at a constant rate.

Migratory behavior of eastern North Pacific gray whales tracked using a hydrophone array.

PubMed

Guazzo, Regina A; Helble, Tyler A; D'Spain, Gerald L; Weller, David W; Wiggins, Sean M; Hildebrand, John A

2017-01-01

Eastern North Pacific gray whales make one of the longest annual migrations of any mammal, traveling from their summer feeding areas in the Bering and Chukchi Seas to their wintering areas in the lagoons of Baja California, Mexico. Although a significant body of knowledge on gray whale biology and behavior exists, little is known about their vocal behavior while migrating. In this study, we used a sparse hydrophone array deployed offshore of central California to investigate how gray whales behave and use sound while migrating. We detected, localized, and tracked whales for one full migration season, a first for gray whales. We verified and localized 10,644 gray whale M3 calls and grouped them into 280 tracks. Results confirm that gray whales are acoustically active while migrating and their swimming and acoustic behavior changes on daily and seasonal time scales. The seasonal timing of the calls verifies the gray whale migration timing determined using other methods such as counts conducted by visual observers. The total number of calls and the percentage of calls that were part of a track changed significantly over both seasonal and daily time scales. An average calling rate of 5.7 calls/whale/day was observed, which is significantly greater than previously reported migration calling rates. We measured a mean speed of 1.6 m/s and quantified heading, direction, and water depth where tracks were located. Mean speed and water depth remained constant between night and day, but these quantities had greater variation at night. Gray whales produce M3 calls with a root mean square source level of 156.9 dB re 1 μPa at 1 m. Quantities describing call characteristics were variable and dependent on site-specific propagation characteristics.

Sensitivity to Punishment and Explanatory Style as Predictors of Public Speaking State Anxiety. Brief Reports

ERIC Educational Resources Information Center

Kopecky, Courtney; Sawyer, Chris; Behnke, Ralph

2004-01-01

Recent biological theories of state anxiety have focused on temperament and neurophysiology as factors that predispose some people to be particularly at risk of debilitating levels of performance anxiety. The present study extends Gray's (1982; Gray & McNaughton, 2000) reinforcement sensitivity theory by proposing a linkage between sensitivity to…

Identification of alleles conferring resistance to gray leaf spot in maize derived from its wild progenitor species teosinte (Zea mays ssp. parviglumis)

USDA-ARS?s Scientific Manuscript database

Gray Leaf Spot [(GLS), causal agent Cercospora zeae-maydis and Cercospora zeina] is an important maize disease in the United States. Current control methods for GLS include using resistant cultivars, crop rotation, chemical applications, and conventional tillage to reduce inoculum levels. Teosinte ...

Experiments in encoding multilevel images as quadtrees

NASA Technical Reports Server (NTRS)

Lansing, Donald L.

1987-01-01

Image storage requirements for several encoding methods are investigated and the use of quadtrees with multigray level or multicolor images are explored. The results of encoding a variety of images having up to 256 gray levels using three schemes (full raster, runlength and quadtree) are presented. Although there is considerable literature on the use of quadtrees to store and manipulate binary images, their application to multilevel images is relatively undeveloped. The potential advantage of quadtree encoding is that an entire area with a uniform gray level may be encoded as a unit. A pointerless quadtree encoding scheme is described. Data are presented on the size of the quadtree required to encode selected images and on the relative storage requirements of the three encoding schemes. A segmentation scheme based on the statistical variation of gray levels within a quadtree quadrant is described. This parametric scheme may be used to control the storage required by an encoded image and to preprocess a scene for feature identification. Several sets of black and white and pseudocolor images obtained by varying the segmentation parameter are shown.

Parallel processing for digital picture comparison

NASA Technical Reports Server (NTRS)

Cheng, H. D.; Kou, L. T.

1987-01-01

In picture processing an important problem is to identify two digital pictures of the same scene taken under different lighting conditions. This kind of problem can be found in remote sensing, satellite signal processing and the related areas. The identification can be done by transforming the gray levels so that the gray level histograms of the two pictures are closely matched. The transformation problem can be solved by using the packing method. Researchers propose a VLSI architecture consisting of m x n processing elements with extensive parallel and pipelining computation capabilities to speed up the transformation with the time complexity 0(max(m,n)), where m and n are the numbers of the gray levels of the input picture and the reference picture respectively. If using uniprocessor and a dynamic programming algorithm, the time complexity will be 0(m(3)xn). The algorithm partition problem, as an important issue in VLSI design, is discussed. Verification of the proposed architecture is also given.

An empirical assessment of the focal species hypothesis.

PubMed

Lindenmayer, D B; Lane, P W; Westgate, M J; Crane, M; Michael, D; Okada, S; Barton, P S

2014-12-01

Biodiversity surrogates and indicators are commonly used in conservation management. The focal species approach (FSA) is one method for identifying biodiversity surrogates, and it is underpinned by the hypothesis that management aimed at a particular focal species will confer protection on co-occurring species. This concept has been the subject of much debate, in part because the validity of the FSA has not been subject to detailed empirical assessment of the extent to which a given focal species actually co-occurs with other species in an assemblage. To address this knowledge gap, we used large-scale, long-term data sets of temperate woodland birds to select focal species associated with threatening processes such as habitat isolation and loss of key vegetation attributes. We quantified co-occurrence patterns among focal species, species in the wider bird assemblage, and species of conservation concern. Some, but not all, focal species were associated with high levels of species richness. One of our selected focal species was negatively associated with the occurrence of other species (i.e., it was an antisurrogate)-a previously undescribed property of nominated focal species. Furthermore, combinations of focal species were not associated with substantially elevated levels of bird species richness, relative to levels associated with individual species. Our results suggest that although there is some merit to the underpinning concept of the FSA, there is also a need to ensure that actions are sufficiently flexible because management tightly focused on a given focal species may not benefit some other species, including species of conservation concern, such of which might not occur in species-rich assemblages. © 2014 Society for Conservation Biology.

Do healthy and unhealthy behaviours cluster in New Zealand?

PubMed

Tobias, Martin; Jackson, Gary; Yeh, Li-Chia; Huang, Ken

2007-04-01

To describe the co-occurrence and clustering of healthy and unhealthy behaviours in New Zealand. Data were sourced from the 2002/03 New Zealand Health Survey. Behaviours selected for analysis were tobacco use, quantity and pattern of alcohol consumption, level of physical activity, and intake of fruit and vegetables. Clustering was defined as co-prevalence of behaviours greater than that expected based on the laws of probability. Co-occurrence was examined using multiple logistic regression modelling, while clustering was examined in a stratified analysis using age and (where appropriate) ethnic standardisation for confounding control. Approximately 29% of adults enjoyed a healthy lifestyle characterised by non-use of tobacco, non- or safe use of alcohol, sufficient physical activity and adequate fruit and vegetable intake. This is only slightly greater than the prevalence expected if all four behaviours were independently distributed through the population i.e. little clustering of healthy behaviours was found. By contrast, 1.5% of adults exhibited all four unhealthy behaviours and 13% exhibited any combination of three of the four unhealthy behaviours. Unhealthy behaviours were more clustered than healthy behaviours, yet Maori exhibited less clustering of unhealthy behaviours than other ethnic groups and no deprivation gradient was seen in clustering. The relative lack of clustering of healthy behaviours supports single issue universal health promotion strategies at the population level. Our results also support targeted interventions at the clinical level for the 15% with 'unhealthy lifestyles'. Our finding of only limited clustering of unhealthy behaviours among Maori and no deprivation gradient suggests that clustering does not contribute to the greater burden of disease experienced by these groups.

Classification Features of US Images Liver Extracted with Co-occurrence Matrix Using the Nearest Neighbor Algorithm

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Bibicu, Dorin; Moraru, Luminita; Nicolae, Mariana Carmen

2011-12-01

Co-occurrence matrix has been applied successfully for echographic images characterization because it contains information about spatial distribution of grey-scale levels in an image. The paper deals with the analysis of pixels in selected regions of interest of an US image of the liver. The useful information obtained refers to texture features such as entropy, contrast, dissimilarity and correlation extract with co-occurrence matrix. The analyzed US images were grouped in two distinct sets: healthy liver and steatosis (or fatty) liver. These two sets of echographic images of the liver build a database that includes only histological confirmed cases: 10 images of healthy liver and 10 images of steatosis liver. The healthy subjects help to compute four textural indices and as well as control dataset. We chose to study these diseases because the steatosis is the abnormal retention of lipids in cells. The texture features are statistical measures and they can be used to characterize irregularity of tissues. The goal is to extract the information using the Nearest Neighbor classification algorithm. The K-NN algorithm is a powerful tool to classify features textures by means of grouping in a training set using healthy liver, on the one hand, and in a holdout set using the features textures of steatosis liver, on the other hand. The results could be used to quantify the texture information and will allow a clear detection between health and steatosis liver.

Co-occurrence profiles of trace elements in potable water systems: a case study.

PubMed

Andra, Syam S; Makris, Konstantinos C; Charisiadis, Pantelis; Costa, Costas N

2014-11-01

Potable water samples (N = 74) from 19 zip code locations in a region of Greece were profiled for 13 trace elements composition using inductively coupled plasma mass spectrometry. The primary objective was to monitor the drinking water quality, while the primary focus was to find novel associations in trace elements occurrence that may further shed light on common links in their occurrence and fate in the pipe scales and corrosion products observed in urban drinking water distribution systems. Except for arsenic at two locations and in six samples, rest of the analyzed elements was below maximum contaminant levels, for which regulatory values are available. Further, we attempted to hierarchically cluster trace elements based on their covariances resulting in two groups; one with arsenic, antimony, zinc, cadmium, and copper and the second with the rest of the elements. The grouping trends were partially explained by elements' similar chemical activities in water, underscoring their potential for co-accumulation and co-mobilization phenomena from pipe scales into finished water. Profiling patterns of trace elements in finished water could be indicative of their load on pipe scales and corrosion products, with a corresponding risk of episodic contaminant release. Speculation was made on the role of disinfectants and disinfection byproducts in mobilizing chemically similar trace elements of human health interest from pipe scales to tap water. It is warranted that further studies may eventually prove useful to water regulators from incorporating the acquired knowledge in the drinking water safety plans.

Effect of Binder and Mold parameters on Collapsibility and Surface Finish of Gray Cast Iron No-bake Sand Molds

NASA Astrophysics Data System (ADS)

Srinivasulu Reddy, K.; Venkata Reddy, Vajrala; Mandava, Ravi Kumar

2017-08-01

Chemically bonded no-bake molds and cores have good mechanical properties and produce dimensionally accurate castings compared to green sand molds. Poor collapsibility property of CO2 hardened sodium silicate bonded sand mold and phenolic urethane no-bake (PUN) binder system, made the reclamation of the sands more important. In the present work fine silica sand is mixed with phenolic urethane no-bake binder and the sand sets in a very short time within few minutes. In this paper it is focused on optimizing the process parameters of PUN binder based sand castings for better collapsibility and surface finish of gray cast iron using Taguchi design. The findings were successfully verified through experiments.

Perceptions of Community of Practice Development in Online Graduate Education

ERIC Educational Resources Information Center

Marken, James A.; Dickinson, Gail K.

2013-01-01

Implementing Communities of Practice (CoP) in online learning is well documented (Gray, 2004; Wenger & Snyder, 2000), and is of particular interest to the LIS profession (Yukawa, 2010). Most of the students in school library programs are practicing teachers seeking to add the library science endorsement to their existing license. They are…

77 FR 27223 - Combined Notice of Filings #1

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-09

..., LLC, ESI Vansycle Partners, L.P., Florida Power & Light Co., FPL Energy Burleigh County Wind, LLC, FPL Energy Cabazon Wind, LLC, FPL Energy Cape, LLC, FPL Energy Cowboy Wind, LLC, FPL Energy Green Power Wind..., Garden Wind, LLC, Gray County Wind Energy, LLC, Hatch Solar Energy Center I, LLC, Hawkeye Power Partners...

On the verge of a respiratory-type panic attack: Selective activations of rostrolateral and caudoventrolateral periaqueductal gray matter following short-lasting escape to a low dose of potassium cyanide.

PubMed

Müller, Cláudia Janaina Torres; Quintino-Dos-Santos, Jeyce Willig; Schimitel, Fagna Giacomin; Tufik, Sérgio; Beijamini, Vanessa; Canteras, Newton Sabino; Schenberg, Luiz Carlos

2017-04-21

Intravenous injections of potassium cyanide (KCN) both elicit escape by its own and facilitate escape to electrical stimulation of the periaqueductal gray matter (PAG). Moreover, whereas the KCN-evoked escape is potentiated by CO 2 , it is suppressed by both lesions of PAG and clinically effective treatments with panicolytics. These and other data suggest that the PAG harbors a hypoxia-sensitive alarm system the activation of which could both precipitate panic and render the subject hypersensitive to CO 2 . Although prior c-Fos immunohistochemistry studies reported widespread activations of PAG following KCN injections, the employment of repeated injections of high doses of KCN (>60µg) in anesthetized rats compromised both the localization of KCN-responsive areas and their correlation with escape behavior. Accordingly, here we compared the brainstem activations of saline-injected controls (air/saline) with those produced by a single intravenous injection of 40-µg KCN (air/KCN), a 2-min exposure to 13% CO 2 (CO 2 /saline), or a combined stimulus (CO 2 /KCN). Behavioral effects of KCN microinjections into the PAG were assessed as well. Data showed that whereas the KCN microinjections were ineffective, KCN intravenous injections elicited escape in all tested rats. Moreover, whereas the CO 2 alone was ineffective, it potentiated the KCN-evoked escape. Compared to controls, the nucleus tractus solitarius was significantly activated in both CO 2 /saline and CO 2 /KCN groups. Additionally, whereas the laterodorsal tegmental nucleus was activated by all treatments, the rostrolateral and caudoventrolateral PAG were activated by air/KCN only. Data suggest that the latter structures are key components of a hypoxia-sensitive suffocation alarm which activation may trigger a panic attack. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Computerized image analysis: estimation of breast density on mammograms

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Petrick, Nicholas; Sahiner, Berkman; Helvie, Mark A.; Roubidoux, Marilyn A.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

2000-06-01

An automated image analysis tool is being developed for estimation of mammographic breast density, which may be useful for risk estimation or for monitoring breast density change in a prevention or intervention program. A mammogram is digitized using a laser scanner and the resolution is reduced to a pixel size of 0.8 mm X 0.8 mm. Breast density analysis is performed in three stages. First, the breast region is segmented from the surrounding background by an automated breast boundary-tracking algorithm. Second, an adaptive dynamic range compression technique is applied to the breast image to reduce the range of the gray level distribution in the low frequency background and to enhance the differences in the characteristic features of the gray level histogram for breasts of different densities. Third, rule-based classification is used to classify the breast images into several classes according to the characteristic features of their gray level histogram. For each image, a gray level threshold is automatically determined to segment the dense tissue from the breast region. The area of segmented dense tissue as a percentage of the breast area is then estimated. In this preliminary study, we analyzed the interobserver variation of breast density estimation by two experienced radiologists using BI-RADS lexicon. The radiologists' visually estimated percent breast densities were compared with the computer's calculation. The results demonstrate the feasibility of estimating mammographic breast density using computer vision techniques and its potential to improve the accuracy and reproducibility in comparison with the subjective visual assessment by radiologists.

The Influence of the Disturbed Continuity of the River and the Invasive Species--Potamopyrgus antipodarum (Gray, 1843), Gammarus tigrinus (Sexton, 1939) on Benthos Fauna: A Case Study on Urban Area in the River Ruda (Poland).

PubMed

Spyra, Aneta; Kubicka, Justyna; Strzelec, Małgorzata

2015-07-01

The progressive degradation of aquatic ecosystems and ecohydrological role of rivers is one of the most important global environmental issues. The loss of the ability of rivers to self-purify waters due to the disturbances of river continuity cause a lack of biological life in parts of rivers or even in an entire river. The appearance of alien species in degraded aquatic environments is an increasingly common phenomenon and constitutes one of the threats to biodiversity. The aim of the study was to evaluate the possible impact of alien species Potamopyrgus antipodarum (Gray, 1843) and Gammarus tigrinus (Sexton, 1939) on native invertebrates as well as the influence of environmental factors on the occurrence benthos fauna including also alien species. The study conducted in industrial area, in the River Ruda (Poland), showed that at the sites at which the occurrence of the two alien species was observed, the density of native benthos and diversity decreased significantly. CCA analysis showed that non-native species occurred in fast water velocity and that their presence was associated with high values of conductivity, hardness, and a high chloride content. The arrival of new species from other geographical areas is one of the factors that influences the species balance in native aquatic fauna. The number of alien species in freshwater ecosystems probably will increase in the future as new aliens are moved outside of their native ranges.

The Influence of the Disturbed Continuity of the River and the Invasive Species— Potamopyrgus antipodarum (Gray, 1843), Gammarus tigrinus (Sexton, 1939) on Benthos Fauna: A Case Study on Urban Area in the River Ruda (Poland)

NASA Astrophysics Data System (ADS)

Spyra, Aneta; Kubicka, Justyna; Strzelec, Małgorzata

2015-07-01

The progressive degradation of aquatic ecosystems and ecohydrological role of rivers is one of the most important global environmental issues. The loss of the ability of rivers to self-purify waters due to the disturbances of river continuity cause a lack of biological life in parts of rivers or even in an entire river. The appearance of alien species in degraded aquatic environments is an increasingly common phenomenon and constitutes one of the threats to biodiversity. The aim of the study was to evaluate the possible impact of alien species Potamopyrgus antipodarum (Gray, 1843) and Gammarus tigrinus (Sexton, 1939) on native invertebrates as well as the influence of environmental factors on the occurrence benthos fauna including also alien species. The study conducted in industrial area, in the River Ruda (Poland), showed that at the sites at which the occurrence of the two alien species was observed, the density of native benthos and diversity decreased significantly. CCA analysis showed that non-native species occurred in fast water velocity and that their presence was associated with high values of conductivity, hardness, and a high chloride content. The arrival of new species from other geographical areas is one of the factors that influences the species balance in native aquatic fauna. The number of alien species in freshwater ecosystems probably will increase in the future as new aliens are moved outside of their native ranges.

Investigating the Co-Occurrence of Self-Mutilation and Suicide Attempts among Opioid-Dependent Individuals

ERIC Educational Resources Information Center

Maloney, Elizabeth; Degenhardt, Louisa; Darke, Shane; Nelson, Elliot C.

2010-01-01

The prevalence and risk factors associated with self-mutilation among opioid dependent cases and controls were determined, and the co-occurrence of self-mutilation and attempted suicide was examined. The prevalence of self-mutilation among cases and controls did not differ significantly (25% vs. 23%, respectively), with gender differences…

Co-Occurrence of ADHD and High IQ: A Case Series Empirical Study

ERIC Educational Resources Information Center

Cordeiro, Mara L.; Farias, Antonio C.; Cunha, Alexandre; Benko, Cassia R.; Farias, Lucilene G.; Costa, Maria T.; Martins, Leandra F.; McCracken, James T.

2011-01-01

Objective: The validity of a diagnosis of ADHD in children with a high intelligence quotient (IQ) remains controversial. Using a multidisciplinary approach, rigorous diagnostic criteria, and worldwide-validated psychometric instruments, we identified a group of children attending public schools in southern Brazil for co-occurrence of high IQ and…

The Co-Occurrence of Quotatives with Mimetic Performances.

ERIC Educational Resources Information Center

Buchstaller, Isabelle

2003-01-01

This paper discusses mimesis, the direct representation and total imitation of an event. It studies the co-occurrence of quotative verbs with mimetic enactment based on two corpora of U.S. American English, both available through the University of Pennsylvania Data Consortium. The Switchboard Corpus has 542 speakers ranging in age from 20-60 years…

Alleviating Search Uncertainty through Concept Associations: Automatic Indexing, Co-Occurrence Analysis, and Parallel Computing.

ERIC Educational Resources Information Center

Chen, Hsinchun; Martinez, Joanne; Kirchhoff, Amy; Ng, Tobun D.; Schatz, Bruce R.

1998-01-01

Grounded on object filtering, automatic indexing, and co-occurrence analysis, an experiment was performed using a parallel supercomputer to analyze over 400,000 abstracts in an INSPEC computer engineering collection. A user evaluation revealed that system-generated thesauri were better than the human-generated INSPEC subject thesaurus in concept…

Substance Use, Aggression Perpetration, and Victimization: Temporal Co-Occurrence in College Males and Females

ERIC Educational Resources Information Center

Margolin, Gayla; Ramos, Michelle C.; Baucom, Brian R.; Bennett, Diana C.; Guran, Elyse L.

2013-01-01

Many studies have documented associations of substance use with aggression perpetration and aggression victimization; however, little is known about the co-occurrence of these problem behaviors within the same day in college students. The present study investigated whether substance use and aggression increase the likelihood of each other and…

Visualizing the Structure of Medical Informatics Using Term Co-Occurrence Analysis: II. INSPEC Perspective.

ERIC Educational Resources Information Center

Morris, Theodore

2001-01-01

Term co-occurrence analysis of INSPEC classification codes and thesaurus terms used to index Medical Informatics literature reveals an information science and technology perspective on the field, to accompany the biomedical perspective previously reported. This study continues the search for a better understanding of the structure of Medical…

Drug Use Risk Behavior Co-Occurrence among United States High School Students

ERIC Educational Resources Information Center

Di Bona, Vito Lorenzo; Erausquin, Jennifer Toller

2014-01-01

Purpose: Prevalence estimates for drug use health risk behaviors among high school students are widely available, but relatively few studies describe how and to what extent these risk behaviors occur together. Furthermore, little research has examined whether the co-occurrence of health risk behaviors varies by key demographic characteristics such…

Consonant-Vowel Co-Occurrence Patterns in Mandarin-Learning Infants

ERIC Educational Resources Information Center

Chen, Li-Mei; Kent, Raymond D.

2005-01-01

Most studies on CV co-occurrence patterns in early phonetic development have been based on Indo-European languages. Data from infants learning Mandarin, which has a substantially different phonological system from Indo-European languages, can confirm or refute the findings of previous studies, thus shedding further light on the theoretical bases…

Posttraumatic Stress Disorder and Substance Use Disorders in College Students

ERIC Educational Resources Information Center

Borsari, Brian; Read, Jennifer P.; Campbell, James F.

2008-01-01

Research indicates that many college students report posttraumatic stress disorder (PTSD) or substance use disorder (SUD), yet there has been scant attention paid to the co-occurrence of these disorders in college students. This review examines the co-occurrence of PTSD and SUD in college students. Recommendations for counseling centers are…

Extension of Weighted Sum of Gray Gas Data to Mathematical Simulation of Radiative Heat Transfer in a Boiler with Gas-Soot Media

PubMed Central

Nouri-Borujerdi, Ali; Kazi, Salim Newaz

2014-01-01

In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site. PMID:25143981

Extension of weighted sum of gray gas data to mathematical simulation of radiative heat transfer in a boiler with gas-soot media.

PubMed

Gharehkhani, Samira; Nouri-Borujerdi, Ali; Kazi, Salim Newaz; Yarmand, Hooman

2014-01-01

In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site.

Investigating species co-occurrence patterns when species are detected imperfectly

USGS Publications Warehouse

MacKenzie, D.I.; Bailey, L.L.; Nichols, J.D.

2004-01-01

1. Over the last 30 years there has been a great deal of interest in investigating patterns of species co-occurrence across a number of locations, which has led to the development of numerous methods to determine whether there is evidence that a particular pattern may not have occurred by random chance. 2. A key aspect that seems to have been largely overlooked is the possibility that species may not always be detected at a location when present, which leads to 'false absences' in a species presence/absence matrix that may cause incorrect inferences to be made about co-occurrence patterns. Furthermore, many of the published methods for investigating patterns of species co-occurrence do not account for potential differences in the site characteristics that may partially (at least) explain non-random patterns (e.g. due to species having similar/different habitat preferences). 3. Here we present a statistical method for modelling co-occurrence patterns between species while accounting for imperfect detection and site characteristics. This method requires that multiple presence/absence surveys for the species be conducted over a reasonably short period of time at most sites. The method yields unbiased estimates of probabilities of occurrence, and is practical when the number of species is small (< 4). 4. To illustrate the method we consider data collected on two terrestrial salamander species, Plethodonjordani and members of the Plethodon glutinosus complex, collected in the Great Smoky Mountains National Park, USA. We find no evidence that the species do not occur independently at sites once site elevation has been allowed for, although we find some evidence of a statistical interaction between species in terms of detectability that we suggest may be due to changes in relative abundances.

Paleosoils in the loess deposits of eastern Uzbekistan

NASA Astrophysics Data System (ADS)

Abdunazarov, U. K.; Stelmakh, A. G.

2010-12-01

Loess deposits of the eastern Uzbekistan are difficult to study the stratigraphy of the object. Clarification of the relationship of age and genetic features of the considered entities by traditional methods is difficult due to scarcity of remnants of the fauna and flora, the active Quaternary tectonics, the homogeneity of the rocks, especially the formation of loess sequences, specific conditions of geological and tectonic development, etc. In this regard, particularly relevant is the study of loess deposits by paleosoils subdivision and correlation. Paleosoils, which are present in the sections of loess sequences, distinct from loess-like loams, dividing them among themselves. Color these paleosoils noticeable brownish or brown, while the loess is a powdery mildew gray rock. Typically, the general scheme of occurrence of loess cover is linked with levels of relief mountainous areas. Recent studies show that the loess in the piedmont plains overlie a complex manner and include uneven paleosoils. Therefore, loess sequences of different geomorphological levels from the lower parts of slopes to the watershed have been studied in research paleosoils. The scheme was drawn up as a result of the studies. This scheme shows the main horizons paleosoils in loess deposits. Even-aged paleosoils and share their loess were identified in this scheme.

Impact of copper on the diazotroph abundance and community composition during swine manure composting.

PubMed

Yin, Yanan; Gu, Jie; Wang, Xiaojuan; Zhang, Kaiyu; Hu, Ting; Ma, Jiyue; Wang, Qianzhi

2018-05-01

Biological nitrogen fixation is a major pathway in ecosystems. This study investigated the effects of adding Cu at different levels (0, 200, and 2000 mg kg -1 ) on the diazotroph community during swine manure composting. Quantitative PCR and high-throughput sequencing were used to analyze the abundances of diazotrophs and the community composition based on the nifH gene. The nifH gene copy number was relatively high in the early stage of composting and Cu had a significant inhibitory effect on the nifH copy number. Furthermore, Cu decreased the diversity of nifH and changed the microbial community structure in the early stage. The nifH genes from members of Firmicutes and Clostridium were most abundant. Co-occurrence ecological network analysis showed that the Cu treatments affected the co-occurrence patterns of diazotroph communities and reduced the associations between different diazotrophs. Interestingly, Cu may weaken symbiotic diazotrophic interactions and enhance the roles of free-living diazotrophs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Co-occurrence and distribution of deoxynivalenol, nivalenol and zearalenone in wheat from Brazil.

PubMed

Calori-Domingues, Maria Antonia; Bernardi, Carolina Maria Gil; Nardin, Mariana Sartori; de Souza, Gláucia Vendramini; Dos Santos, Fernanda Gregório Ribeiro; Stein, Mirella de Abreu; Gloria, Eduardo Micotti da; Dias, Carlos Tadeu Dos Santos; de Camargo, Adriano Costa

2016-06-01

Fusarium mycotoxins deoxynivalenol (DON), nivalenol (NIV) and zearalenone (ZEN) were investigated in wheat from the 2009 and 2010 crop years. Samples (n = 745) from commercial fields were collected in four wheat producing regions (WPR) which differed in weather conditions. Analyses were performed using HPLC-DAD. Contamination with ZEN, DON and NIV occurred in 56, 86 and 50%, respectively. Also, mean concentrations were different: DON = 1046 µg kg(-1), NIV < 100 µg kg(-1) and ZEN = 82 µg kg(-1). Co-occurrence of ZEN, DON and NIV was observed in 74% of the samples from 2009 and in 12% from 2010. Wet/cold region WPR I had the highest mycotoxin concentration. Wet/moderately hot region WPR II had the lowest mycotoxin levels. Furthermore, the mean concentration of each mycotoxin was higher in samples from 2009 as compared with those from 2010. Precipitation during flowering or harvest periods may explain these results.

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

PubMed

Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-08-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.