Local variance for multi-scale analysis in geomorphometry

PubMed Central

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-01-01

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138

A three-dimensional comparison of a morphometric and conventional cephalometric midsagittal planes for craniofacial asymmetry.

PubMed

Damstra, Janalt; Fourie, Zacharias; De Wit, Marnix; Ren, Yijin

2012-02-01

Morphometric methods are used in biology to study object symmetry in living organisms and to determine the true plane of symmetry. The aim of this study was to determine if there are clinical differences between three-dimensional (3D) cephalometric midsagittal planes used to describe craniofacial asymmetry and a true symmetry plane derived from a morphometric method based on visible facial features. The sample consisted of 14 dry skulls (9 symmetric and 5 asymmetric) with metallic markers which were imaged with cone-beam computed tomography. An error study and statistical analysis were performed to validate the morphometric method. The morphometric and conventional cephalometric planes were constructed and compared. The 3D cephalometric planes constructed as perpendiculars to the Frankfort horizontal plane resembled the morphometric plane the most in both the symmetric and asymmetric groups with mean differences of less than 1.00 mm for most variables. However, the standard deviations were often large and clinically significant for these variables. There were clinically relevant differences (>1.00 mm) between the different 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features. The difference between 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features were clinically relevant. Care has to be taken using cephalometric midsagittal planes for diagnosis and treatment planning of craniofacial asymmetry as they might differ from the true plane of symmetry as determined by morphometrics.

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

PubMed

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

2015-12-23

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.

A web system of virtual morphometric globes for Mars and the Moon

NASA Astrophysics Data System (ADS)

Florinsky, I. V.; Garov, A. S.; Karachevtseva, I. P.

2018-09-01

We developed a web system of virtual morphometric globes for Mars and the Moon. As the initial data, we used 15-arc-minutes gridded global digital elevation models (DEMs) extracted from the Mars Orbiter Laser Altimeter (MOLA) and the Lunar Orbiter Laser Altimeter (LOLA) gridded archives. We derived global digital models of sixteen morphometric variables including horizontal, vertical, minimal, and maximal curvatures, as well as catchment area and topographic index. The morphometric models were integrated into the web system developed as a distributed application consisting of a client front-end and a server back-end. The following main functions are implemented in the system: (1) selection of a morphometric variable; (2) two-dimensional visualization of a calculated global morphometric model; (3) 3D visualization of a calculated global morphometric model on the sphere surface; (4) change of a globe scale; and (5) globe rotation by an arbitrary angle. Free, real-time web access to the system is provided. The web system of virtual morphometric globes can be used for geological and geomorphological studies of Mars and the Moon at the global, continental, and regional scales.

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

A 3-D morphometric analysis of erosional features in a contourite drift from offshore SE Brazil

NASA Astrophysics Data System (ADS)

Alves, Tiago M.

2010-12-01

A contourite drift from offshore Brazil is mapped in detail and investigated using state-of-the-art 3-D seismic data. The aim was to review the relevance of erosional features in contourite drifts accumulated on continental slopes. Topographically confined by growing salt diapirs, the mapped contourite ridge is limited by two erosional features, a contourite moat and a turbidite channel, showing multiple slide scars on it flanks. Associated with the latter features are thick accumulations of high-amplitude strata, probably comprising sandy/silty sediment of Miocene to Holocene age. The erosional unconformities are mostly observed in a region averaging 3.75km away from the axes of a channel and a moat, whose deposits interfinger with continuous strata in central parts of the contourite drift. The multiple unconformities observed are mostly related to slide scars and local erosion on the flanks of the drift. This work demonstrates that the existence of widespread unconformities within contourite drifts on continental slopes: (1) may not be as prominent as often documented, (2) are often diachronic and interfinger with correlative hiatuses or aggraded strata in axial regions of contourite drifts. Although less widespread than regional, or ocean-scale unconformities, these diachronous features result in significant hiatuses within contourite drifts and are, therefore, potentially mappable as relevant (regional-scale) unconformities on 2-D/3-D seismic data. Thus, without a full 3-D morphometric analysis of contourite drifts, significant errors may occur when estimating major changes in the dynamics of principal geostrophic currents based on single-site core data, or on direct correlations between stratigraphic surfaces of distinct contourite bodies.

New multi-scale approach to improve explanation of patterns of contemporary morphodynamics in the badland landscapes of Central Italy: the important Quaternary context

NASA Astrophysics Data System (ADS)

Vergari, Francesca; Troiani, Francesco; Della Seta, Marta; Faulkner, Hazel; Schwanghart, Wolfgang; Ciccacci, Sirio; Del Monte, Maurizio; Fredi, Paola

2016-04-01

Spatial patterns and magnitudes of short-term erosional processes are often the result of longer-term landscape-wide morphodynamics. Their combined analysis, however, is challenged by different spatial scales, data availability and resolution. Integrating both analyses has thus rarely been done though urgently needed to better understand and manage present day erosional dynamics and land degradation. In this study we aim at overcoming these shortcomings by exploring a multi-scale approach, based on a nested experimental design that integrates the traditional monitoring of erosion processes at local and short time scale, with the longer-term (over the last 103-105 yr) and basin-to-morphostructure scale analysis of landscape morphodynamics. We investigated the geomorphological behaviour of a Mediterranean active badland site located in the Upper Orcia Valley (Southern Tuscany, Italy). This choice is justified by the availability of decadal erosion monitoring datasets at a range of scales, and the rapidity of development of erosion processes. Based on the analysis of drainage network and its longitudinal and planform pattern, we tested the hypothesis that this rejuvenating, actively erosional landscape presents hotspots of denudation processes on hillslope and in channel network that are largely associated with (a) knickpoints on stream longitudinal profiles, (b) sites of strong connectivity, and (c) sites of strong divide competition with adjacent, aggressive and non-aggressive systems. To illustrate and explore this nested approach, we extracted the channel network and analysed stream longitudinal profiles using the MATLAB-based TopoToolbox program, starting from the 27x27 m Aster GDEM. The stream network morphometric analyses involved computing and mapping χ-values, a transformation that normalizes the longitudinal distance by upslope area and which serves as a proxy of the dynamic state of river basins based on the current geometry of the river network. Finally, we projected on the longitudinal profiles of the Orcia River and some of its main tributaries a full range of geomorphic features which are relevant for the interpretation of the landscape morphoevolution, connectivity and erosion/deposition dynamics: i) competitive divides; ii) sites with different degree of connectivity within the drainage system; iii) sites experiencing different erosion rates; iv) sites with in-channel depositional features and landslide deposits; v) remnants of relict geomorphic surfaces. The plano-altimetric distribution of such features, compared with the drainage network evolutionary stage, allowed to better understand the morphodynamics of badland areas and to define future scenarios in the perspective of a better management of hazardous processes.

Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment

NASA Astrophysics Data System (ADS)

Abdulkareem, Jabir Haruna; Pradhan, Biswajeet; Sulaiman, Wan Nor Azmin; Jamil, Nor Rohaizah

2018-05-01

This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC-HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07-0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.

Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment

NASA Astrophysics Data System (ADS)

Abdulkareem, Jabir Haruna; Pradhan, Biswajeet; Sulaiman, Wan Nor Azmin; Jamil, Nor Rohaizah

2018-03-01

This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC-HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07-0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

Comparison of Single and Multi-Scale Method for Leaf and Wood Points Classification from Terrestrial Laser Scanning Data

NASA Astrophysics Data System (ADS)

Wei, Hongqiang; Zhou, Guiyun; Zhou, Junjie

2018-04-01

The classification of leaf and wood points is an essential preprocessing step for extracting inventory measurements and canopy characterization of trees from the terrestrial laser scanning (TLS) data. The geometry-based approach is one of the widely used classification method. In the geometry-based method, it is common practice to extract salient features at one single scale before the features are used for classification. It remains unclear how different scale(s) used affect the classification accuracy and efficiency. To assess the scale effect on the classification accuracy and efficiency, we extracted the single-scale and multi-scale salient features from the point clouds of two oak trees of different sizes and conducted the classification on leaf and wood. Our experimental results show that the balanced accuracy of the multi-scale method is higher than the average balanced accuracy of the single-scale method by about 10 % for both trees. The average speed-up ratio of single scale classifiers over multi-scale classifier for each tree is higher than 30.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

NASA Astrophysics Data System (ADS)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Characterization and Biomimcry of Avian Nanostructured Tissues

DTIC Science & Technology

2016-01-19

keratin cortex (Maia et al. 2011) at the outer edge of barbs from TEM images. Geometric morphometrics of barb shape Digitized images of the barb thin...morphological measurements (all P > 0.05; Figure 4C; Table S2). Gloss and Barb Geometric Morphometrics Matte and glossy barbs differed significantly in...barbs and lack of multiple, clear anatomically homologous features, traditional landmark based morphometric techniques (Bookstein, 1982) would be

Characterizing the primary material sources and dominant erosional processes for post-fire debris-flow initiation in a headwater basin using multi-temporal terrestrial laser scanning data

USGS Publications Warehouse

Staley, Dennis M.; Waslewicz, Thad A.; Kean, Jason W.

2014-01-01

Wildfire dramatically alters the hydrologic response of a watershed such that even modest rainstorms can produce hazardous debris flows. Relative to shallow landslides, the primary sources of material and dominant erosional processes that contribute to post-fire debris-flow initiation are poorly constrained. Improving our understanding of how and where material is eroded from a watershed during a post-fire debris-flow requires (1) precise measurements of topographic change to calculate volumetric measurements of erosion and deposition, and (2) the identification of relevant morphometrically defined process domains to spatially constrain these measurements of erosion and deposition. In this study, we combine the morphometric analysis of a steep, small (0.01 km2) headwater drainage basin with measurements of topographic change using high-resolution (2.5 cm) multi-temporal terrestrial laser scanning data made before and after a post-fire debris flow. The results of the morphometric analysis are used to define four process domains: hillslope-divergent, hillslope-convergent, transitional, and channelized incision. We determine that hillslope-divergent and hillslope-convergent process domains represent the primary sources of material over the period of analysis in the study basin. From these results we conclude that raindrop-impact induced erosion, ravel, surface wash, and rilling are the primary erosional processes contributing to post-fire debris-flow initiation in the small, steep headwater basin. Further work is needed to determine (1) how these results vary with increasing drainage basin size, (2) how these data might scale upward for use with coarser resolution measurements of topography, and (3) how these results change with evolving sediment supply conditions and vegetation recovery.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluating the predictive power of multivariate tensor-based morphometry in Alzheimer's disease progression via convex fused sparse group Lasso

NASA Astrophysics Data System (ADS)

Tsao, Sinchai; Gajawelli, Niharika; Zhou, Jiayu; Shi, Jie; Ye, Jieping; Wang, Yalin; Lepore, Natasha

2014-03-01

Prediction of Alzheimers disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end we combine a predictive multi-task machine learning method1 with novel MR-based multivariate morphometric surface map of the hippocampus2 to predict future cognitive scores of patients. Previous work by Zhou et al.1 has shown that a multi-task learning framework that performs prediction of all future time points (or tasks) simultaneously can be used to encode both sparsity as well as temporal smoothness. They showed that this can be used in predicting cognitive outcomes of Alzheimers Disease Neuroimaging Initiative (ADNI) subjects based on FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied Shi et al.2s recently developed multivariate tensor-based (mTBM) parametric surface analysis method to extract features from the hippocampal surface. We show that by combining the power of the multi-task framework with the sensitivity of mTBM features of the hippocampus surface, we are able to improve significantly improve predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.

Fusion of infrared polarization and intensity images based on improved toggle operator

NASA Astrophysics Data System (ADS)

Zhu, Pan; Ding, Lei; Ma, Xiaoqing; Huang, Zhanhua

2018-01-01

Integration of infrared polarization and intensity images has been a new topic in infrared image understanding and interpretation. The abundant infrared details and target from infrared image and the salient edge and shape information from polarization image should be preserved or even enhanced in the fused result. In this paper, a new fusion method is proposed for infrared polarization and intensity images based on the improved multi-scale toggle operator with spatial scale, which can effectively extract the feature information of source images and heavily reduce redundancy among different scale. Firstly, the multi-scale image features of infrared polarization and intensity images are respectively extracted at different scale levels by the improved multi-scale toggle operator. Secondly, the redundancy of the features among different scales is reduced by using spatial scale. Thirdly, the final image features are combined by simply adding all scales of feature images together, and a base image is calculated by performing mean value weighted method on smoothed source images. Finally, the fusion image is obtained by importing the combined image features into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method obtains better performance in preserving the details and edge information as well as improving the image contrast.

Computer Aided Multi-Data Fusion Dismount Modeling

DTIC Science & Technology

2012-03-22

The ability of geometric morphometric methods to estimate a known covariance matrix., volume 49. Systematic Biology, 2000. [39] Wang C., Yuen M...the use of human shape descriptors like landmarks, body composition, body segmentation, skeletonisation, body representation using geometrical shapes...Springer. [10] Bookstein, F. L. “ Morphometric Tools for Landmark Data: Geometry and Biology.” Cambridge University Press, 1991. [11] Borengasser, M

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

A novel scheme for abnormal cell detection in Pap smear images

NASA Astrophysics Data System (ADS)

Zhao, Tong; Wachman, Elliot S.; Farkas, Daniel L.

2004-07-01

Finding malignant cells in Pap smear images is a "needle in a haystack"-type problem, tedious, labor-intensive and error-prone. It is therefore desirable to have an automatic screening tool in order that human experts can concentrate on the evaluation of the more difficult cases. Most research on automatic cervical screening tries to extract morphometric and texture features at the cell level, in accordance with the NIH "The Bethesda System" rules. Due to variances in image quality and features, such as brightness, magnification and focus, morphometric and texture analysis is insufficient to provide robust cervical cancer detection. Using a microscopic spectral imaging system, we have produced a set of multispectral Pap smear images with wavelengths from 400 nm to 690 nm, containing both spectral signatures and spatial attributes. We describe a novel scheme that combines spatial information (including texture and morphometric features) with spectral information to significantly improve abnormal cell detection. Three kinds of wavelet features, orthogonal, bi-orthogonal and non-orthogonal, are carefully chosen to optimize recognition performance. Multispectral feature sets are then extracted in the wavelet domain. Using a Back-Propagation Neural Network classifier that greatly decreases the influence of spurious events, we obtain a classification error rate of 5%. Cell morphometric features, such as area and shape, are then used to eliminate most remaining small artifacts. We report initial results from 149 cells from 40 separate image sets, in which only one abnormal cell was missed (TPR = 97.6%) and one normal cell was falsely classified as cancerous (FPR = 1%).

Morphological evidence for discrete stocks of yellow perch in Lake Erie

USGS Publications Warehouse

Kocovsky, Patrick M.; Knight, Carey T.

2012-01-01

Identification and management of unique stocks of exploited fish species are high-priority management goals in the Laurentian Great Lakes. We analyzed whole-body morphometrics of 1430 yellow perch Perca flavescens captured during 2007–2009 from seven known spawning areas in Lake Erie to determine if morphometrics vary among sites and management units to assist in identification of spawning stocks of this heavily exploited species. Truss-based morphometrics (n = 21 measurements) were analyzed using principal component analysis followed by ANOVA of the first three principal components to determine whether yellow perch from the several sampling sites varied morphometrically. Duncan's multiple range test was used to determine which sites differed from one another to test whether morphometrics varied at scales finer than management unit. Morphometrics varied significantly among sites and annually, but differences among sites were much greater. Sites within the same management unit typically differed significantly from one another, indicating morphometric variation at a scale finer than management unit. These results are largely congruent with recently-published studies on genetic variation of yellow perch from many of the same sampling sites. Thus, our results provide additional evidence that there are discrete stocks of yellow perch in Lake Erie and that management units likely comprise multiple stocks.

Morphometrical study on senile larynx.

PubMed

Zieliński, R

2001-01-01

The aim of the study was a morphometrical macroscopic evaluation of senile larynges, according to its usefulness in ORL diagnostic and operational methods. Larynx preparations were taken from cadavers of both sexes, of age 65 and over, about 24 hours after death. Clinically important laryngeal diameters were collected using common morphometrical methods. A few body features were also being gathered. Computer statistical methods were used in data assessment, including basic statistics and linear correlations between diameters and between diameters and body features. The data presented in the study may be very helpful in evaluation of diagnostic methods. It may also help in selection of right operational tool' sizes, the most appropriate operational technique choice, preoperative preparations and designing and building virtual and plastic models for physicians' training.

An improved KCF tracking algorithm based on multi-feature and multi-scale

NASA Astrophysics Data System (ADS)

Wu, Wei; Wang, Ding; Luo, Xin; Su, Yang; Tian, Weiye

2018-02-01

The purpose of visual tracking is to associate the target object in a continuous video frame. In recent years, the method based on the kernel correlation filter has become the research hotspot. However, the algorithm still has some problems such as video capture equipment fast jitter, tracking scale transformation. In order to improve the ability of scale transformation and feature description, this paper has carried an innovative algorithm based on the multi feature fusion and multi-scale transform. The experimental results show that our method solves the problem that the target model update when is blocked or its scale transforms. The accuracy of the evaluation (OPE) is 77.0%, 75.4% and the success rate is 69.7%, 66.4% on the VOT and OTB datasets. Compared with the optimal one of the existing target-based tracking algorithms, the accuracy of the algorithm is improved by 6.7% and 6.3% respectively. The success rates are improved by 13.7% and 14.2% respectively.

Glaciated valleys in Europe and western Asia

PubMed Central

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2015-01-01

In recent years, remote sensing, morphometric analysis, and other computational concepts and tools have invigorated the field of geomorphological mapping. Automated interpretation of digital terrain data based on impartial rules holds substantial promise for large dataset processing and objective landscape classification. However, the geomorphological realm presents tremendous complexity and challenges in the translation of qualitative descriptions into geomorphometric semantics. Here, the simple, conventional distinction of V-shaped fluvial and U-shaped glacial valleys was analyzed quantitatively using multi-scale curvature and a novel morphometric variable termed Difference of Minimum Curvature (DMC). We used this automated terrain analysis approach to produce a raster map at a scale of 1:6,000,000 showing the distribution of glaciated valleys across Europe and western Asia. The data set has a cell size of 3 arc seconds and consists of more than 40 billion grid cells. Glaciated U-shaped valleys commonly associated with erosion by warm-based glaciers are abundant in the alpine regions of mid Europe and western Asia but also occur at the margins of mountain ice sheets in Scandinavia. The high-level correspondence with field mapping and the fully transferable semantics validate this approach for automated analysis of yet unexplored terrain around the globe and qualify for potential applications on other planetary bodies like Mars. PMID:27019665

Clinical, morphologic, and morphometric features of cranial thoracic spinal stenosis in large and giant breed dogs.

PubMed

Johnson, Philippa; De Risio, Luisa; Sparkes, Andrew; McConnell, Fraser; Holloway, Andrew

2012-01-01

The clinical, morphologic, and morphometric features of cranial thoracic spinal stenosis were investigated in large and giant breed dogs. Seventy-nine magnetic resonance imaging studies of the cranial thoracic spine were assessed. Twenty-six were retrieved retrospectively and 53 were acquired prospectively using the same inclusion criteria. Images were evaluated using a modified compression scale as: no osseous stenosis (grade 0), osseous stenosis without spinal cord compression (grade 1), and osseous stenosis with spinal cord compression (grade 2). Morphometric analysis was performed and compared to the subjective grading system. Grades 1 and 2 cranial thoracic spinal stenosis were identified on 24 imaging studies in 23 dogs. Sixteen of 23 dogs had a conformation typified by Molosser breeds and 21/23 were male. The most common sites of stenosis were T2-3 and T3-4. The articular process joints were enlarged with abnormal oblique orientation. Stenosis was dorsolateral, lateralized, or dorsoventral. Concurrent osseous cervical spondylomyelopathy was recognized in six dogs and other neurologic disease in five dogs. Cranial thoracic spinal stenosis was the only finding in 12 dogs. In 9 of these 12 dogs (all grade 2) neurolocalization was to the T3-L3 spinal segment. The median age of these dogs was 9.5 months. In the remaining three dogs neurologic signs were not present. Stenosis ratios were of limited benefit in detecting stenotic sites. Grade 2 cranial thoracic spinal stenosis causing direct spinal cord compression may lead to neurologic signs, however milder stenosis (grade 1) is likely to be subclinical or incidental. © 2012 Veterinary Radiology & Ultrasound.

Multi-scale curvature for automated identification of glaciated mountain landscapes

NASA Astrophysics Data System (ADS)

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2014-03-01

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes.

Mapping the Proxies of Memory and Learning Function in Senior Adults with High-performing, Normal Aging and Neurocognitive Disorders.

PubMed

Lu, Hanna; Xi, Ni; Fung, Ada W T; Lam, Linda C W

2018-06-09

Memory and learning, as the core brain function, shows controversial results across studies focusing on aging and dementia. One of the reasons is because of the multi-faceted nature of memory and learning. However, there is still a dearth of comparable proxies with psychometric and morphometric portrait in clinical and non-clinical populations. We aim to investigate the proxies of memory and learning function with direct and derived measures and examine their associations with morphometric features in senior adults with different cognitive status. Based on two modality-driven tests, we assessed the component-specific memory and learning in the individuals with high performing (HP), normal aging, and neurocognitive disorders (NCD) (n = 488). Structural magnetic resonance imaging was used to measure the regional cortical thickness with surface-based morphometry analysis in a subsample (n = 52). Compared with HP elderly, the ones with normal aging and minor NCD showed declined recognition memory and working memory, whereas had better learning performance (derived scores). Meanwhile, major NCD patients showed more breakdowns of memory and learning function. The correlation between proxies of memory and learning and cortical thickness exhibited the overlapped and unique neural underpinnings. The proxies of memory and learning could be characterized by component-specific constructs with psychometric and morphometric bases. Overall, the constructs of memory are more likely related to the pathological changes, and the constructs of learning tend to reflect the cognitive abilities of compensation.

The morphometrics of "masculinity" in human faces.

PubMed

Mitteroecker, Philipp; Windhager, Sonja; Müller, Gerd B; Schaefer, Katrin

2015-01-01

In studies of social inference and human mate preference, a wide but inconsistent array of tools for computing facial masculinity has been devised. Several of these approaches implicitly assumed that the individual expression of sexually dimorphic shape features, which we refer to as maleness, resembles facial shape features perceived as masculine. We outline a morphometric strategy for estimating separately the face shape patterns that underlie perceived masculinity and maleness, and for computing individual scores for these shape patterns. We further show how faces with different degrees of masculinity or maleness can be constructed in a geometric morphometric framework. In an application of these methods to a set of human facial photographs, we found that shape features typically perceived as masculine are wide faces with a wide inter-orbital distance, a wide nose, thin lips, and a large and massive lower face. The individual expressions of this combination of shape features--the masculinity shape scores--were the best predictor of rated masculinity among the compared methods (r = 0.5). The shape features perceived as masculine only partly resembled the average face shape difference between males and females (sexual dimorphism). Discriminant functions and Procrustes distances to the female mean shape were poor predictors of perceived masculinity.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Evaluation of Chemical Preparation on Insect Wing Shape for Geometric Morphometrics

PubMed Central

Lorenz, Camila; Suesdek, Lincoln

2013-01-01

Geometric morphometrics is an approach that has been increasingly applied in studies with insects. A limiting factor of this technique is that some mosquitoes have wings with dark spots or many scales, which jeopardizes the visualization of landmarks for morphometric analysis. Recently, in some studies, chemically treatment (staining) of the wings was used to improve the viewing of landmarks. In this study, we evaluated whether this method causes deformation of the wing veins and tested whether it facilitates the visualization of the most problematic landmarks. In addition, we tested whether mechanical removal of the scales was sufficient for this purpose. The results showed that the physical and chemical treatments are equally effective in improving visualization of the landmarks. The chemical method did not cause deformation of the wing. Thus, some of these treatments should be performed before beginning geometric morphometric analysis to avoid erroneous landmark digitizing. PMID:24019438

Watershed-based Morphometric Analysis: A Review

NASA Astrophysics Data System (ADS)

Sukristiyanti, S.; Maria, R.; Lestiana, H.

2018-02-01

Drainage basin/watershed analysis based on morphometric parameters is very important for watershed planning. Morphometric analysis of watershed is the best method to identify the relationship of various aspects in the area. Despite many technical papers were dealt with in this area of study, there is no particular standard classification and implication of each parameter. It is very confusing to evaluate a value of every morphometric parameter. This paper deals with the meaning of values of the various morphometric parameters, with adequate contextual information. A critical review is presented on each classification, the range of values, and their implications. Besides classification and its impact, the authors also concern about the quality of input data, either in data preparation or scale/the detail level of mapping. This review paper hopefully can give a comprehensive explanation to assist the upcoming research dealing with morphometric analysis.

Morphometric information to reduce the semantic gap in the characterization of microscopic images of thyroid nodules.

PubMed

Macedo, Alessandra A; Pessotti, Hugo C; Almansa, Luciana F; Felipe, Joaquim C; Kimura, Edna T

2016-07-01

The analyses of several systems for medical-imaging processing typically support the extraction of image attributes, but do not comprise some information that characterizes images. For example, morphometry can be applied to find new information about the visual content of an image. The extension of information may result in knowledge. Subsequently, results of mappings can be applied to recognize exam patterns, thus improving the accuracy of image retrieval and allowing a better interpretation of exam results. Although successfully applied in breast lesion images, the morphometric approach is still poorly explored in thyroid lesions due to the high subjectivity thyroid examinations. This paper presents a theoretical-practical study, considering Computer Aided Diagnosis (CAD) and Morphometry, to reduce the semantic discontinuity between medical image features and human interpretation of image content. The proposed method aggregates the content of microscopic images characterized by morphometric information and other image attributes extracted by traditional object extraction algorithms. This method carries out segmentation, feature extraction, image labeling and classification. Morphometric analysis was included as an object extraction method in order to verify the improvement of its accuracy for automatic classification of microscopic images. To validate this proposal and verify the utility of morphometric information to characterize thyroid images, a CAD system was created to classify real thyroid image-exams into Papillary Cancer, Goiter and Non-Cancer. Results showed that morphometric information can improve the accuracy and precision of image retrieval and the interpretation of results in computer-aided diagnosis. For example, in the scenario where all the extractors are combined with the morphometric information, the CAD system had its best performance (70% of precision in Papillary cases). Results signalized a positive use of morphometric information from images to reduce semantic discontinuity between human interpretation and image characterization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

PubMed Central

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Hajnal, Joseph V.; Duncan, John S.; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2012-01-01

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study. PMID:22523539

VARSEDIG: an algorithm for morphometric characters selection and statistical validation in morphological taxonomy.

PubMed

Guisande, Cástor; Vari, Richard P; Heine, Jürgen; García-Roselló, Emilio; González-Dacosta, Jacinto; Perez-Schofield, Baltasar J García; González-Vilas, Luis; Pelayo-Villamil, Patricia

2016-09-12

We present and discuss VARSEDIG, an algorithm which identifies the morphometric features that significantly discriminate two taxa and validates the morphological distinctness between them via a Monte-Carlo test. VARSEDIG is freely available as a function of the RWizard application PlotsR (http://www.ipez.es/RWizard) and as R package on CRAN. The variables selected by VARSEDIG with the overlap method were very similar to those selected by logistic regression and discriminant analysis, but overcomes some shortcomings of these methods. VARSEDIG is, therefore, a good alternative by comparison to current classical classification methods for identifying morphometric features that significantly discriminate a taxon and for validating its morphological distinctness from other taxa. As a demonstration of the potential of VARSEDIG for this purpose, we analyze morphological discrimination among some species of the Neotropical freshwater family Characidae.

Complex, multi-scale small intestinal topography replicated in cellular growth substrates fabricated via chemical vapor deposition of Parylene C.

PubMed

Koppes, Abigail N; Kamath, Megha; Pfluger, Courtney A; Burkey, Daniel D; Dokmeci, Mehmet; Wang, Lin; Carrier, Rebecca L

2016-08-22

Native small intestine possesses distinct multi-scale structures (e.g., crypts, villi) not included in traditional 2D intestinal culture models for drug delivery and regenerative medicine. The known impact of structure on cell function motivates exploration of the influence of intestinal topography on the phenotype of cultured epithelial cells, but the irregular, macro- to submicron-scale features of native intestine are challenging to precisely replicate in cellular growth substrates. Herein, we utilized chemical vapor deposition of Parylene C on decellularized porcine small intestine to create polymeric intestinal replicas containing biomimetic irregular, multi-scale structures. These replicas were used as molds for polydimethylsiloxane (PDMS) growth substrates with macro to submicron intestinal topographical features. Resultant PDMS replicas exhibit multiscale resolution including macro- to micro-scale folds, crypt and villus structures, and submicron-scale features of the underlying basement membrane. After 10 d of human epithelial colorectal cell culture on PDMS substrates, the inclusion of biomimetic topographical features enhanced alkaline phosphatase expression 2.3-fold compared to flat controls, suggesting biomimetic topography is important in induced epithelial differentiation. This work presents a facile, inexpensive method for precisely replicating complex hierarchal features of native tissue, towards a new model for regenerative medicine and drug delivery for intestinal disorders and diseases.

A scale space feature based registration technique for fusion of satellite imagery

NASA Technical Reports Server (NTRS)

Raghavan, Srini; Cromp, Robert F.; Campbell, William C.

1997-01-01

Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.

A tree canopy height delineation method based on Morphological Reconstruction—Open Crown Decomposition

NASA Astrophysics Data System (ADS)

Liu, Q.; Jing, L.; Li, Y.; Tang, Y.; Li, H.; Lin, Q.

2016-04-01

For the purpose of forest management, high resolution LIDAR and optical remote sensing imageries are used for treetop detection, tree crown delineation, and classification. The purpose of this study is to develop a self-adjusted dominant scales calculation method and a new crown horizontal cutting method of tree canopy height model (CHM) to detect and delineate tree crowns from LIDAR, under the hypothesis that a treetop is radiometric or altitudinal maximum and tree crowns consist of multi-scale branches. The major concept of the method is to develop an automatic selecting strategy of feature scale on CHM, and a multi-scale morphological reconstruction-open crown decomposition (MRCD) to get morphological multi-scale features of CHM by: cutting CHM from treetop to the ground; analysing and refining the dominant multiple scales with differential horizontal profiles to get treetops; segmenting LiDAR CHM using watershed a segmentation approach marked with MRCD treetops. This method has solved the problems of false detection of CHM side-surface extracted by the traditional morphological opening canopy segment (MOCS) method. The novel MRCD delineates more accurate and quantitative multi-scale features of CHM, and enables more accurate detection and segmentation of treetops and crown. Besides, the MRCD method can also be extended to high optical remote sensing tree crown extraction. In an experiment on aerial LiDAR CHM of a forest of multi-scale tree crowns, the proposed method yielded high-quality tree crown maps.

The Morphometrics of “Masculinity” in Human Faces

PubMed Central

Mitteroecker, Philipp; Windhager, Sonja; Müller, Gerd B.; Schaefer, Katrin

2015-01-01

In studies of social inference and human mate preference, a wide but inconsistent array of tools for computing facial masculinity has been devised. Several of these approaches implicitly assumed that the individual expression of sexually dimorphic shape features, which we refer to as maleness, resembles facial shape features perceived as masculine. We outline a morphometric strategy for estimating separately the face shape patterns that underlie perceived masculinity and maleness, and for computing individual scores for these shape patterns. We further show how faces with different degrees of masculinity or maleness can be constructed in a geometric morphometric framework. In an application of these methods to a set of human facial photographs, we found that shape features typically perceived as masculine are wide faces with a wide inter-orbital distance, a wide nose, thin lips, and a large and massive lower face. The individual expressions of this combination of shape features—the masculinity shape scores—were the best predictor of rated masculinity among the compared methods (r = 0.5). The shape features perceived as masculine only partly resembled the average face shape difference between males and females (sexual dimorphism). Discriminant functions and Procrustes distances to the female mean shape were poor predictors of perceived masculinity. PMID:25671667

Morphometricity as a measure of the neuroanatomical signature of a trait.

PubMed

Sabuncu, Mert R; Ge, Tian; Holmes, Avram J; Smoller, Jordan W; Buckner, Randy L; Fischl, Bruce

2016-09-27

Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer's disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.

Morphometricity as a measure of the neuroanatomical signature of a trait

PubMed Central

Sabuncu, Mert R.; Ge, Tian; Holmes, Avram J.; Smoller, Jordan W.; Buckner, Randy L.; Fischl, Bruce

2016-01-01

Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques. PMID:27613854

Multi-scale curvature for automated identification of glaciated mountain landscapes☆

PubMed Central

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2014-01-01

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes. PMID:24748703

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Design and fabrication of thin microvascularised polymer matrices inspired from secondary lamellae of fish gills

NASA Astrophysics Data System (ADS)

Kumar, Prasoon; Gandhi, Prasanna S.; Majumder, Mainak

2016-04-01

Gills are one of the most primitive gas, solute exchange organs available in fishes. They facilitate exchange of gases, solutes and ions with a surrounding water medium through their functional unit called secondary lamella. These lamellae through their extraordinary morphometric features and peculiar arrangement in gills, achieve remarkable mass transport properties. Therefore, in the current study, modeling and simulation of convection-diffusion transport through a two dimensional model of secondary lamella and theoretical analysis of morphometric features of fish gills were carried out. Such study suggested an evolutionary conservation of parametric ratios across fishes of different weights. Further, we have also fabricated a thin microvascularised PDMS matrices mimicking secondary lamella by use of micro-technologies like electrospinning. In addition, we have also demonstrated the fluid flow by capillary action through these thin microvascularised PDMS matrices. Eventually, we also illustrated the application of these thin microvascularied PDMS matrices in solute exchange process under capillary flow conditions. Thus, our study suggested that fish gills have optimized parameteric ratios, at multiple length scale, throughout an evolution to achieve an organ with enhanced mass transport capabilities. Thus, these defined parametric ratios could be exploited to design and develop efficient, scaled-up gas/solute exchange microdevices. We also proposed an inexpensive and scalable method of fabrication of thin microvascularised polymer matrices and demonstrated its solute exchange capabilities under capillary flow conditions. Thus, mimicking the microstructures of secondary lamella will enable fabrication of microvascularised thin polymer systems through micro manufacturing technologies for potential applications in filtration, self-healing/cooling materials and bioengineering.

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Fabrication of Trabecular Bone-Templated Tissue-Engineered Constructs by 3D Inkjet Printing.

PubMed

Vanderburgh, Joseph P; Fernando, Shanik J; Merkel, Alyssa R; Sterling, Julie A; Guelcher, Scott A

2017-11-01

3D printing enables the creation of scaffolds with precisely controlled morphometric properties for multiple tissue types, including musculoskeletal tissues such as cartilage and bone. Computed tomography (CT) imaging has been combined with 3D printing to fabricate anatomically scaled patient-specific scaffolds for bone regeneration. However, anatomically scaled scaffolds typically lack sufficient resolution to recapitulate the <100 micrometer-scale trabecular architecture essential for investigating the cellular response to the morphometric properties of bone. In this study, it is hypothesized that the architecture of trabecular bone regulates osteoblast differentiation and mineralization. To test this hypothesis, human bone-templated 3D constructs are fabricated via a new micro-CT/3D inkjet printing process. It is shown that this process reproducibly fabricates bone-templated constructs that recapitulate the anatomic site-specific morphometric properties of trabecular bone. A significant correlation is observed between the structure model index (a morphometric parameter related to surface curvature) and the degree of mineralization of human mesenchymal stem cells, with more concave surfaces promoting more extensive osteoblast differentiation and mineralization compared to predominately convex surfaces. These findings highlight the significant effects of trabecular architecture on osteoblast function. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A new lizard species of the Phymaturus patagonicus group (Squamata: Liolaemini) from northern Patagonia, Neuquén, Argentina.

PubMed

Marín, Andrea González; Pérez, Cristian Hernán Fulvio; Minoli, Ignacio; Morando, Mariana; Avila, Luciano Javier

2016-06-10

The integrative taxonomy framework allows developing robust hypotheses of species limits based on the integration of results from different data sets and analytical methods. In this work, we test a candidate species hypothesis previously suggested based on molecular data, with geometric and traditional morphometrics analyses (multivariate and univariate). This new lizard species is part of the Phymaturus patagonicus group (payuniae clade) that is distributed in Neuquén and Mendoza provinces (Argentina). Our results showed that Phymaturus rahuensis sp. nov. differs from the other species of the payuniae clade by a higher number of midbody scales, and fewer supralabials scales, finger lamellae and toe lamellae. Also, its multidimensional spaces, both based on continuous lineal variables and geometric morphometrics (shape) characters, do not overlap with those of the other species in this clade. The results of the morphometric and geometric morphometric analyses presented here, coupled with previously published molecular data, represent three independent lines of evidence that support the diagnosis of this new taxon.

Capturing remote mixing due to internal tides using multi-scale modeling tool: SOMAR-LES

NASA Astrophysics Data System (ADS)

Santilli, Edward; Chalamalla, Vamsi; Scotti, Alberto; Sarkar, Sutanu

2016-11-01

Internal tides that are generated during the interaction of an oscillating barotropic tide with the bottom bathymetry dissipate only a fraction of their energy near the generation region. The rest is radiated away in the form of low- high-mode internal tides. These internal tides dissipate energy at remote locations when they interact with the upper ocean pycnocline, continental slope, and large scale eddies. Capturing the wide range of length and time scales involved during the life-cycle of internal tides is computationally very expensive. A recently developed multi-scale modeling tool called SOMAR-LES combines the adaptive grid refinement features of SOMAR with the turbulence modeling features of a Large Eddy Simulation (LES) to capture multi-scale processes at a reduced computational cost. Numerical simulations of internal tide generation at idealized bottom bathymetries are performed to demonstrate this multi-scale modeling technique. Although each of the remote mixing phenomena have been considered independently in previous studies, this work aims to capture remote mixing processes during the life cycle of an internal tide in more realistic settings, by allowing multi-level (coarse and fine) grids to co-exist and exchange information during the time stepping process.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

Mechanics, Hydrodynamics and Energetics of Blue Whale Lunge Feeding: Efficiency Dependence on Krill Density

DTIC Science & Technology

2011-01-01

obtained these morphometric data from blue whale specimens reposited at the National Museum of Natural History in Washington, DC (USNM 124326), the Santa...mouth-closing stage. The basic distance scale for this force is set by the ratio Ac/whead, calculated from Eqn A4, and the morphometrics of the body...allometry of mammalian metabolic rate supports niether geometric nor quarter-power scaling. Evolution 63, 2658-2667. Williams, T. M. (1999). The

Intraspecific scaling laws of vascular trees.

PubMed

Huo, Yunlong; Kassab, Ghassan S

2012-01-07

A fundamental physics-based derivation of intraspecific scaling laws of vascular trees has not been previously realized. Here, we provide such a theoretical derivation for the volume-diameter and flow-length scaling laws of intraspecific vascular trees. In conjunction with the minimum energy hypothesis, this formulation also results in diameter-length, flow-diameter and flow-volume scaling laws. The intraspecific scaling predicts the volume-diameter power relation with a theoretical exponent of 3, which is validated by the experimental measurements for the three major coronary arterial trees in swine (where a least-squares fit of these measurements has exponents of 2.96, 3 and 2.98 for the left anterior descending artery, left circumflex artery and right coronary artery trees, respectively). This scaling law as well as others agrees very well with the measured morphometric data of vascular trees in various other organs and species. This study is fundamental to the understanding of morphological and haemodynamic features in a biological vascular tree and has implications for vascular disease.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Cross-Domain Multi-View Object Retrieval via Multi-Scale Topic Models.

PubMed

Hong, Richang; Hu, Zhenzhen; Wang, Ruxin; Wang, Meng; Tao, Dacheng

2016-09-27

The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respected to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two datasets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two datasets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.

Multi-sensor image registration based on algebraic projective invariants.

PubMed

Li, Bin; Wang, Wei; Ye, Hao

2013-04-22

A new automatic feature-based registration algorithm is presented for multi-sensor images with projective deformation. Contours are firstly extracted from both reference and sensed images as basic features in the proposed method. Since it is difficult to design a projective-invariant descriptor from the contour information directly, a new feature named Five Sequential Corners (FSC) is constructed based on the corners detected from the extracted contours. By introducing algebraic projective invariants, we design a descriptor for each FSC that is ensured to be robust against projective deformation. Further, no gray scale related information is required in calculating the descriptor, thus it is also robust against the gray scale discrepancy between the multi-sensor image pairs. Experimental results utilizing real image pairs are presented to show the merits of the proposed registration method.

Correlation of tumor-infiltrating lymphocytes to histopathological features and molecular phenotypes in canine mammary carcinoma: A morphologic and immunohistochemical morphometric study.

PubMed

Kim, Jong-Hyuk; Chon, Seung-Ki; Im, Keum-Soon; Kim, Na-Hyun; Sur, Jung-Hyang

2013-04-01

Abundant lymphocyte infiltration is frequently found in canine malignant mammary tumors, but the pathological features and immunophenotypes associated with the infiltration remain to be elucidated. The aim of the present study was to evaluate the relationship between lymphocyte infiltration, histopathological features, and molecular phenotype in canine mammary carcinoma (MC). The study was done with archived formalin-fixed, paraffin-embedded samples (n = 47) by histologic and immunohistochemical methods. The degree of lymphocyte infiltration was evaluated by morphologic analysis, and the T- and B-cell populations as well as the T/B-cell ratio were evaluated by morphometric analysis; results were compared with the histologic features and molecular phenotypes. The degree of lymphocyte infiltration was significantly higher in MCs with lymphatic invasion than in those without lymphatic invasion (P < 0.0001) and in tumors of high histologic grade compared with those of lower histologic grade (P = 0.045). Morphometric analysis showed a larger amount of T-cells and B-cells in MCs with a higher histologic grade and lymphatic invasion, but the T/B ratio did not change. Lymphocyte infiltration was not associated with histologic type or molecular phenotype, as assessed from the immunohistochemical expression of epidermal growth factor receptor 2, estrogen receptor, cytokeratin 14, and p63. Since intense lymphocyte infiltration was associated with aggressive histologic features, lymphocytes may be important for tumor aggressiveness and greater malignant behavior in the tumor microenvironment.

Application of LOD technology to the economic residence GIS for industry and commerce administration

NASA Astrophysics Data System (ADS)

Song, Yongjun; Feng, Xuezhi; Zhao, Shuhe; Yin, Haiwei; Li, Yulin; Cui, Hongxia; Zhang, Hui; Zhong, Quanbao

2007-06-01

The LOD technology has an impact upon the multi-scale representation of spatial database. This paper takes advantage of LOD technology to express the multi-scale geographical data, and establish the exchange of multi-scale electronic map, further attain the goal that the details of geographic features such as point, line and polygon can be displayed more and more clearly with the display scale being enlarged to be convenient for the personnel of all offices of industry and commerce administration to label the locations of the corporations or enterprises.

Quantitative diagnosis of bladder cancer by morphometric analysis of HE images

NASA Astrophysics Data System (ADS)

Wu, Binlin; Nebylitsa, Samantha V.; Mukherjee, Sushmita; Jain, Manu

2015-02-01

In clinical practice, histopathological analysis of biopsied tissue is the main method for bladder cancer diagnosis and prognosis. The diagnosis is performed by a pathologist based on the morphological features in the image of a hematoxylin and eosin (HE) stained tissue sample. This manuscript proposes algorithms to perform morphometric analysis on the HE images, quantify the features in the images, and discriminate bladder cancers with different grades, i.e. high grade and low grade. The nuclei are separated from the background and other types of cells such as red blood cells (RBCs) and immune cells using manual outlining, color deconvolution and image segmentation. A mask of nuclei is generated for each image for quantitative morphometric analysis. The features of the nuclei in the mask image including size, shape, orientation, and their spatial distributions are measured. To quantify local clustering and alignment of nuclei, we propose a 1-nearest-neighbor (1-NN) algorithm which measures nearest neighbor distance and nearest neighbor parallelism. The global distributions of the features are measured using statistics of the proposed parameters. A linear support vector machine (SVM) algorithm is used to classify the high grade and low grade bladder cancers. The results show using a particular group of nuclei such as large ones, and combining multiple parameters can achieve better discrimination. This study shows the proposed approach can potentially help expedite pathological diagnosis by triaging potentially suspicious biopsies.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

PubMed

Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P; Gonzalez-Zacarias, Clio; Zhao, Lu; D'Arcy, Mike; Kesselman, Carl; Herting, Megan M; Dinov, Ivo D; Toga, Arthur W; Clark, Kristi A

2018-05-15

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases). Copyright © 2018 Elsevier Inc. All rights reserved.

Arabidopsis phenotyping through Geometric Morphometrics.

PubMed

Manacorda, Carlos A; Asurmendi, Sebastian

2018-06-18

Recently, much technical progress was achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it now possible to extract shape and size parameters for genetic, physiological and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of platform and segmentation software used are still lacking and shape descriptions still rely on ad hoc or even sometimes contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations amongst groups and measure them in shape distance units. Here, a particular scheme of landmarks placement on Arabidopsis rosette images is proposed to study shape variation in the case of viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown and reproducibility issues are assessed. Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner.

Statistical Distribution Analysis of Lineated Bands on Europa

NASA Astrophysics Data System (ADS)

Chen, T.; Phillips, C. B.; Pappalardo, R. T.

2016-12-01

Tina Chen, Cynthia B. Phillips, Robert T. Pappalardo Europa's surface is covered with intriguing linear and disrupted features, including lineated bands that range in scale and size. Previous studies have shown the possibility of an icy shell at the surface that may be concealing a liquid ocean with the potential to harboring life (Pappalardo et al., 1999). Utilizing the high-resolution imaging data from the Galileo spacecraft, we examined bands through a morphometric and morphologic approach. Greeley et al. (2000) and Procktor et al. (2002) have defined bands as wide, hummocky to lineated features that have distinctive surface texture and albedo compared to its surrounding terrain. We took morphometric measurements of lineated bands to find correlations in properties such as size, location, and orientation, and to shed light on formation models. We will present our measurements of over 100 bands on Europa that was mapped on the USGS Europa Global Mosaic Base Map (2002). We also conducted a statistical analysis to understand the distribution of lineated bands globally, and whether the widths of the bands differ by location. Our preliminary analysis from our statistical distribution evaluation, combined with the morphometric measurements, supports a uniform ice shell thickness for Europa rather than one that varies geographically. References: Greeley, Ronald, et al. "Geologic mapping of Europa." Journal of Geophysical Research: Planets 105.E9 (2000): 22559-22578.; Pappalardo, R. T., et al. "Does Europa have a subsurface ocean? Evaluation of the geological evidence." Journal of Geophysical Research: Planets 104.E10 (1999): 24015-24055.; Prockter, Louise M., et al. "Morphology of Europan bands at high resolution: A mid-ocean ridge-type rift mechanism." Journal of Geophysical Research: Planets 107.E5 (2002).; U.S. Geological Survey, 2002, Controlled photomosaic map of Europa, Je 15M CMN: U.S. Geological Survey Geologic Investigations Series I-2757, available at http://pubs.usgs.gov/imap/i2757/

Morphometric variability within the axial zone of the southern Juan de Fuca Ridge: Interpretation from Sea MARC II, Sea MARC I, and deep-sea photography

USGS Publications Warehouse

Kappel, Ellen S.; Normark, William R.

1987-01-01

The morphometric characteristics of the axial regions of oceanic spreading centers are determined by (1) the type of volcanic flows, (2) the relation between primary volcanic relief (on a scale of a few meters to tens of meters) and degree of sediment cover, and (3) the extent of surficial expression and timing of tectonic disruption of the young oceanic crust. Even within a single, continuous, linear spreading-ridge segment with relatively uniform axial valley dimensions over a distance of 50 or more kilometers, such as along the southern Juan de Fuca Ridge, the changes in morphometric characteristics along axis within the youngest crust indicate distinct variation in tectonic and volcanic activity over short distances within short time periods. An integrated analysis of Sea MARC I, Sea MARC II, and photographic data for the southernmost continuous segment of the Juan de Fuca Ridge shows that generalizations about tectonic and volcanic processes at spreading ridges must consider both the temporal scale of processes as well as the physical scales of observations if predictive models are to be successful. Comparison of the morphometric expression within the major hydrothermal vent area and the rest of the southernmost ridge segment suggests that the mapped distribution of hydrothermal vents may reflect the extent of survey effort rather than uniqueness of geologic setting.

MuSCoWERT: multi-scale consistence of weighted edge Radon transform for horizon detection in maritime images.

PubMed

Prasad, Dilip K; Rajan, Deepu; Rachmawati, Lily; Rajabally, Eshan; Quek, Chai

2016-12-01

This paper addresses the problem of horizon detection, a fundamental process in numerous object detection algorithms, in a maritime environment. The maritime environment is characterized by the absence of fixed features, the presence of numerous linear features in dynamically changing objects and background and constantly varying illumination, rendering the typically simple problem of detecting the horizon a challenging one. We present a novel method called multi-scale consistence of weighted edge Radon transform, abbreviated as MuSCoWERT. It detects the long linear features consistent over multiple scales using multi-scale median filtering of the image followed by Radon transform on a weighted edge map and computing the histogram of the detected linear features. We show that MuSCoWERT has excellent performance, better than seven other contemporary methods, for 84 challenging maritime videos, containing over 33,000 frames, and captured using visible range and near-infrared range sensors mounted onboard, onshore, or on floating buoys. It has a median error of about 2 pixels (less than 0.2%) from the center of the actual horizon and a median angular error of less than 0.4 deg. We are also sharing a new challenging horizon detection dataset of 65 videos of visible, infrared cameras for onshore and onboard ship camera placement.

Deep multi-scale convolutional neural network for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera).

PubMed

De Souza, Daiana A; Wang, Ying; Kaftanoglu, Osman; De Jong, David; Amdam, Gro V; Gonçalves, Lionel S; Francoy, Tiago M

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates.

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera)

PubMed Central

A. De Souza, Daiana; Wang, Ying; Kaftanoglu, Osman; De Jong, David; V. Amdam, Gro; S. Gonçalves, Lionel; M. Francoy, Tiago

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates. PMID:25894528

Computer vision approach to morphometric feature analysis of basal cell nuclei for evaluating malignant potentiality of oral submucous fibrosis.

PubMed

Muthu Rama Krishnan, M; Pal, Mousumi; Paul, Ranjan Rashmi; Chakraborty, Chandan; Chatterjee, Jyotirmoy; Ray, Ajoy K

2012-06-01

This research work presents a quantitative approach for analysis of histomorphometric features of the basal cell nuclei in respect to their size, shape and intensity of staining, from surface epithelium of Oral Submucous Fibrosis showing dysplasia (OSFD) to that of the Normal Oral Mucosa (NOM). For all biological activity, the basal cells of the surface epithelium form the proliferative compartment and therefore their morphometric changes will spell the intricate biological behavior pertaining to normal cellular functions as well as in premalignant and malignant status. In view of this, the changes in shape, size and intensity of staining of the nuclei in the basal cell layer of the NOM and OSFD have been studied. Geometric, Zernike moments and Fourier descriptor (FD) based as well as intensity based features are extracted for histomorphometric pattern analysis of the nuclei. All these features are statistically analyzed along with 3D visualization in order to discriminate the groups. Results showed increase in the dimensions (area and perimeter), shape parameters and decreasing mean nuclei intensity of the nuclei in OSFD in respect to NOM. Further, the selected features are fed to the Bayesian classifier to discriminate normal and OSFD. The morphometric and intensity features provide a good sensitivity of 100%, specificity of 98.53% and positive predicative accuracy of 97.35%. This comparative quantitative characterization of basal cell nuclei will be of immense help for oral onco-pathologists, researchers and clinicians to assess the biological behavior of OSFD, specially relating to their premalignant and malignant potentiality. As a future direction more extensive study involving more number of disease subjects is observed.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Variability of morphometric parameters of human trabecular tissue from coxo-arthritis and osteoporotic samples.

PubMed

Marinozzi, Franco; Marinozzi, Andrea; Bini, Fabiano; Zuppante, Francesca; Pecci, Raffaella; Bedini, Rossella

2012-01-01

Morphometric and architectural bone parameters change in diseases such as osteoarthritis and osteoporosis. The mechanical strength of bone is primarily influenced by bone quantity and quality. Bone quality is defined by parameters such as trabecular thickness, trabecular separation, trabecular density and degree of anisotropy that describe the micro-architectural structure of bone. Recently, many studies have validated microtomography as a valuable investigative technique to assess bone morphometry, thanks to micro-CT non-destructive, non-invasive and reliability features, in comparison to traditional techniques such as histology. The aim of this study is the analysis by micro-computed tomography of six specimens, extracted from patients affected by osteoarthritis and osteoporosis, in order to observe the tridimensional structure and calculate several morphometric parameters.

[Morphometric features of the structure of the central nucleus of the amygdala in men and women].

PubMed

Antyukhov, A D

2015-01-01

To identify the interhemispheric asymmetry in the structure of the central nucleus of the amygdala in men and women. Morphometric features of the structure of neurons of the central nucleus amygdala complex were studied in histological sections of the brain of 6 men and 6 women (24 hemispheres), aged 19 to 55 years, with no lifetime diagnosis of mental or neurological disease. The value of the profile fields of neurons of the central nucleus amygdala complex in the left and right hemispheres of the brain were investigated. In women, the average value of neurons in the left hemisphere was somewhat greater than in the right hemisphere, while in men this value was greater in the right hemisphere. The interhemispheric morphometric differences were not significant regardless of gender. In addition, the quantity of relevant fields of neurons in the central nucleus of the amygdala in women was significantly larger than that of men in both hemispheres. The authors attempted to associate the results obtained in the study with emotional perception in men and women.

Multi-scale computational modeling of developmental biology.

PubMed

Setty, Yaki

2012-08-01

Normal development of multicellular organisms is regulated by a highly complex process in which a set of precursor cells proliferate, differentiate and move, forming over time a functioning tissue. To handle their complexity, developmental systems can be studied over distinct scales. The dynamics of each scale is determined by the collective activity of entities at the scale below it. I describe a multi-scale computational approach for modeling developmental systems and detail the methodology through a synthetic example of a developmental system that retains key features of real developmental systems. I discuss the simulation of the system as it emerges from cross-scale and intra-scale interactions and describe how an in silico study can be carried out by modifying these interactions in a way that mimics in vivo experiments. I highlight biological features of the results through a comparison with findings in Caenorhabditis elegans germline development and finally discuss about the applications of the approach in real developmental systems and propose future extensions. The source code of the model of the synthetic developmental system can be found in www.wisdom.weizmann.ac.il/~yaki/MultiScaleModel. yaki.setty@gmail.com Supplementary data are available at Bioinformatics online.

Morphometric and landsliding analyses in chain domain: the Roccella basin, NE Sicily, Italy

NASA Astrophysics Data System (ADS)

Rapisarda, Francesco

2009-10-01

The dynamic interaction of endogenic and exogenic processes in active geodynamic context leads to the deterioration of the physico-mechanical characteristics of the rocks, inducing slopes instability. In such context, the morphometric parameters and the analysis of landslide distribution contribute to appraise the evolutive state of hydrographic basins. The aim of the study is the morphometric characterization of the Roccella Torrent basin (Rtb) located in South Italy. Landsliding and tectonic structure dynamically interact with the drainage pattern that records these effects and permits the definition of the evolutive geomorphic stage of the basin. The Air Photograph Investigation and field surveys permitted to draw the main geomorphic features, the drainage pattern of the Rtb, to calculate the morphometric parameters and to delimit the landslides’ bodies. Detailed analysis about the landslide distribution within a test site 17 km2 wide were carried out to elaborate indicative indexes of the landslides type and to single out the lithotypes that are more involved in slope instability phenomena. The morphometric parameters indicate the rejuvenation state within the Rtb where the stream reaches show the effects of increased energy relief in agreement with the geological settings of this sector of the Apennine-Maghrebian Chain.

Stone loaches of Choman River system, Kurdistan, Iran (Teleostei: Cypriniformes: Nemacheilidae).

PubMed

Kamangar, Barzan Bahrami; Prokofiev, Artem M; Ghaderi, Edris; Nalbant, Theodore T

2014-01-20

For the first time, we present data on species composition and distributions of nemacheilid loaches in the Choman River basin of Kurdistan province, Iran. Two genera and four species are recorded from the area, of which three species are new for science: Oxynoemacheilus kurdistanicus, O. zagrosensis, O. chomanicus spp. nov., and Turcinoemacheilus kosswigi Băn. et Nalb. Detailed and illustrated morphological descriptions and univariate and multivariate analysis of morphometric and meristic features are for each of these species. Forty morphometric and eleven meristic characters were used in multivariate analysis to select characters that could discriminate between the four loach species. Discriminant Function Analysis revealed that sixteen morphometric measures and five meristic characters have the most variability between the loach species. The dendrograms based on cluster analysis of Mahalanobis distances of morphometrics and a combination of both characters confirmed two distinct groups: Oxynoemacheilus spp. and T. kosswigi. Within Oxynoemacheilus, O. zagrosensis and O. chomanicus are more similar to one other rather to either is to O. kurdistanicus.

Further study on Physaloptera clausa Rudolphi, 1819 (Spirurida: Physalopteridae) from the Amur hedgehog Erinaceus amurensis Schrenk (Eulipotyphla: Erinaceidae).

PubMed

Chen, Hui-Xia; Ju, Hui-Dong; Li, Yang; Li, Liang

2017-12-20

In the present study, light and scanning electron microscopy (SEM) were used to further study the detailed morphology of Physaloptera clausa Rudolphi, 1819, based on the material collected from the Amur hedgehog E. amurensis Schrenk in China. The results revealed a few previously unreported morphological features and some morphological and morphometric variability between our specimens and the previous studies. The present supplementary morphological characters and morphometric data could help us to recognize this species more accurately.

Application and assessment of multiscale bending energy for morphometric characterization of neural cells

NASA Astrophysics Data System (ADS)

Cesar, Roberto Marcondes; Costa, Luciano da Fontoura

1997-05-01

The estimation of the curvature of experimentally obtained curves is an important issue in many applications of image analysis including biophysics, biology, particle physics, and high energy physics. However, the accurate calculation of the curvature of digital contours has proven to be a difficult endeavor, mainly because of the noise and distortions that are always present in sampled signals. Errors ranging from 1% to 1000% have been reported with respect to the application of standard techniques in the estimation of the curvature of circular contours [M. Worring and A. W. M. Smeulders, CVGIP: Im. Understanding, 58, 366 (1993)]. This article explains how diagrams of multiscale bending energy can be easily obtained from curvegrams and used as a robust general feature for morphometric characterization of neural cells. The bending energy is an interesting global feature for shape characterization that expresses the amount of energy needed to transform the specific shape under analysis into its lowest energy state (i.e., a circle). The curvegram, which can be accurately obtained by using digital signal processing techniques (more specifically through the Fourier transform and its inverse, as described in this work), provides multiscale representation of the curvature of digital contours. The estimation of the bending energy from the curvegram is introduced and exemplified with respect to a series of neural cells. The masked high curvature effect is reported and its implications to shape analysis are discussed. It is also discussed and illustrated that, by normalizing the multiscale bending energy with respect to a standard circle of unitary perimeter, this feature becomes an effective means for expressing shape complexity in a way that is invariant to rotation, translation, and scaling, and that is robust to noise and other artifacts implied by image acquisition.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis

PubMed Central

Yasir, Muhammad Naveed; Koh, Bong-Hwan

2018-01-01

This paper presents the local mean decomposition (LMD) integrated with multi-scale permutation entropy (MPE), also known as LMD-MPE, to investigate the rolling element bearing (REB) fault diagnosis from measured vibration signals. First, the LMD decomposed the vibration data or acceleration measurement into separate product functions that are composed of both amplitude and frequency modulation. MPE then calculated the statistical permutation entropy from the product functions to extract the nonlinear features to assess and classify the condition of the healthy and damaged REB system. The comparative experimental results of the conventional LMD-based multi-scale entropy and MPE were presented to verify the authenticity of the proposed technique. The study found that LMD-MPE’s integrated approach provides reliable, damage-sensitive features when analyzing the bearing condition. The results of REB experimental datasets show that the proposed approach yields more vigorous outcomes than existing methods. PMID:29690526

Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis.

PubMed

Yasir, Muhammad Naveed; Koh, Bong-Hwan

2018-04-21

This paper presents the local mean decomposition (LMD) integrated with multi-scale permutation entropy (MPE), also known as LMD-MPE, to investigate the rolling element bearing (REB) fault diagnosis from measured vibration signals. First, the LMD decomposed the vibration data or acceleration measurement into separate product functions that are composed of both amplitude and frequency modulation. MPE then calculated the statistical permutation entropy from the product functions to extract the nonlinear features to assess and classify the condition of the healthy and damaged REB system. The comparative experimental results of the conventional LMD-based multi-scale entropy and MPE were presented to verify the authenticity of the proposed technique. The study found that LMD-MPE’s integrated approach provides reliable, damage-sensitive features when analyzing the bearing condition. The results of REB experimental datasets show that the proposed approach yields more vigorous outcomes than existing methods.

Geomorphometric multi-scale analysis for the recognition of Moon surface features using multi-resolution DTMs

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Jianping; Sofia, Giulia; Tarolli, Paolo

2014-05-01

Moon surface features have great significance in understanding and reconstructing the lunar geological evolution. Linear structures like rilles and ridges are closely related to the internal forced tectonic movement. The craters widely distributed on the moon are also the key research targets for external forced geological evolution. The extremely rare availability of samples and the difficulty for field works make remote sensing the most important approach for planetary studies. New and advanced lunar probes launched by China, U.S., Japan and India provide nowadays a lot of high-quality data, especially in the form of high-resolution Digital Terrain Models (DTMs), bringing new opportunities and challenges for feature extraction on the moon. The aim of this study is to recognize and extract lunar features using geomorphometric analysis based on multi-scale parameters and multi-resolution DTMs. The considered digital datasets include CE1-LAM (Chang'E One, Laser AltiMeter) data with resolution of 500m/pix, LRO-WAC (Lunar Reconnaissance Orbiter, Wide Angle Camera) data with resolution of 100m/pix, LRO-LOLA (Lunar Reconnaissance Orbiter, Lunar Orbiter Laser Altimeter) data with resolution of 60m/pix, and LRO-NAC (Lunar Reconnaissance Orbiter, Narrow Angle Camera) data with resolution of 2-5m/pix. We considered surface derivatives to recognize the linear structures including Rilles and Ridges. Different window scales and thresholds for are considered for feature extraction. We also calculated the roughness index to identify the erosion/deposits area within craters. The results underline the suitability of the adopted methods for feature recognition on the moon surface. The roughness index is found to be a useful tool to distinguish new craters, with higher roughness, from the old craters, which present a smooth and less rough surface.

Morphometric analysis of erythrocytes from patients with thalassemia using tomographic diffractive microscopy

NASA Astrophysics Data System (ADS)

Lin, Yang-Hsien; Huang, Shin-Shyang; Wu, Shang-Ju; Sung, Kung-Bin

2017-11-01

Complete blood count is the most common test to detect anemia, but it is unable to obtain the abnormal shape of erythrocytes, which highly correlates with the hematologic function. Tomographic diffractive microscopy (TDM) is an emerging technique capable of quantifying three-dimensional (3-D) refractive index (RI) distributions of erythrocytes without labeling. TDM was used to characterize optical and morphological properties of 172 erythrocytes from healthy volunteers and 419 erythrocytes from thalassemic patients. To efficiently extract and analyze the properties of erythrocytes, we developed an adaptive region-growing method for automatically delineating erythrocytes from 3-D RI maps. The thalassemic erythrocytes not only contained lower hemoglobin content but also showed doughnut shape and significantly lower volume, surface area, effective radius, and average thickness. A multi-indices prediction model achieved perfect accuracy of diagnosing thalassemia using four features, including the optical volume, surface-area-to-volume ratio, sphericity index, and surface area. The results demonstrate the ability of TDM to provide quantitative, hematologic measurements and to assess morphological features of erythrocytes to distinguish healthy and thalassemic erythrocytes.

- and Scene-Guided Integration of Tls and Photogrammetric Point Clouds for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Zieher, T.; Toschi, I.; Remondino, F.; Rutzinger, M.; Kofler, Ch.; Mejia-Aguilar, A.; Schlögel, R.

2018-05-01

Terrestrial and airborne 3D imaging sensors are well-suited data acquisition systems for the area-wide monitoring of landslide activity. State-of-the-art surveying techniques, such as terrestrial laser scanning (TLS) and photogrammetry based on unmanned aerial vehicle (UAV) imagery or terrestrial acquisitions have advantages and limitations associated with their individual measurement principles. In this study we present an integration approach for 3D point clouds derived from these techniques, aiming at improving the topographic representation of landslide features while enabling a more accurate assessment of landslide-induced changes. Four expert-based rules involving local morphometric features computed from eigenvectors, elevation and the agreement of the individual point clouds, are used to choose within voxels of selectable size which sensor's data to keep. Based on the integrated point clouds, digital surface models and shaded reliefs are computed. Using an image correlation technique, displacement vectors are finally derived from the multi-temporal shaded reliefs. All results show comparable patterns of landslide movement rates and directions. However, depending on the applied integration rule, differences in spatial coverage and correlation strength emerge.

Tensor scale-based fuzzy connectedness image segmentation

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Udupa, Jayaram K.

2003-05-01

Tangible solutions to image segmentation are vital in many medical imaging applications. Toward this goal, a framework based on fuzzy connectedness was developed in our laboratory. A fundamental notion called "affinity" - a local fuzzy hanging togetherness relation on voxels - determines the effectiveness of this segmentation framework in real applications. In this paper, we introduce the notion of "tensor scale" - a recently developed local morphometric parameter - in affinity definition and study its effectiveness. Although, our previous notion of "local scale" using the spherical model successfully incorporated local structure size into affinity and resulted in measureable improvements in segmentation results, a major limitation of the previous approach was that it ignored local structural orientation and anisotropy. The current approach of using tensor scale in affinity computation allows an effective utilization of local size, orientation, and ansiotropy in a unified manner. Tensor scale is used for computing both the homogeneity- and object-feature-based components of affinity. Preliminary results of the proposed method on several medical images and computer generated phantoms of realistic shapes are presented. Further extensions of this work are discussed.

Seasonal and gender-related differences in morphometric features and cellular and biochemical parameters of Carcinus aestuarii from the Lagoon of Venice.

PubMed

Matozzo, Valerio; Boscolo, Alice; Marin, Maria Gabriella

2013-08-01

In this study, the seasonal variations in the morphometric features and in the cellular and biochemical parameters of the haemolymph were investigated in both male and female crabs (Carcinus aestuarii). Crabs were seasonally (November 2010-August 2011) collected from the Lagoon of Venice, and the moult stage, weight, width and length of the carapace, and width and length of the bigger chela were evaluated. In addition, the total haemocyte count (THC), haemocyte diameter and volume, haemolymph glucose and total protein levels, and haemolymph phenoloxidase (PO) and N-acetyl-β-glucosaminidase (NAG) activities were measured. The results demonstrated that the collected crabs were all in the intermoult stage and that the males were bigger than the females. A two-way ANOVA revealed a significant effect of season on the THC and the haemocyte volume and a significant influence of gender on the haemocyte diameter. Season and gender significantly affected the haemolymph glucose concentration, whereas haemolymph protein levels were dependent only on the season. In addition, both season and gender significantly influenced the PO and NAG activities in the haemolymph. Overall, the results demonstrated that crab morphometric features as well as haemolymph cellular and biochemical parameters varied markedly as a function of both season and gender. Copyright © 2013 Elsevier Ltd. All rights reserved.

Sensitivity of the Modified Children's Yale-Brown Obsessive Compulsive Scale to Detect Change: Results from Two Multi-Site Trials

ERIC Educational Resources Information Center

Scahill, Lawrence; Sukhodolsky, Denis G.; Anderberg, Emily; Dimitropoulos, Anastasia; Dziura, James; Aman, Michael G.; McCracken, James; Tierney, Elaine; Hallett, Victoria; Katz, Karol; Vitiello, Benedetto; McDougle, Christopher

2016-01-01

Repetitive behavior is a core feature of autism spectrum disorder. We used 8-week data from two federally funded, multi-site, randomized trials with risperidone conducted by the Research Units on Pediatric Psychopharmacology Autism Network to evaluate the sensitivity of the Children's Yale-Brown Obsessive Compulsive Scale modified for autism…

A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection

NASA Astrophysics Data System (ADS)

Li, Yongbo; Yang, Yuantao; Li, Guoyan; Xu, Minqiang; Huang, Wenhu

2017-07-01

Health condition identification of planetary gearboxes is crucial to reduce the downtime and maximize productivity. This paper aims to develop a novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox. MMSDE is proposed to quantify the regularity of time series, which can assess the dynamical characteristics over a range of scales. MMSDE has obvious advantages in the detection of dynamical changes and computation efficiency. Then, the mRMR approach is introduced to refine the fault features. Lastly, the obtained new features are fed into the least square support vector machine (LSSVM) to complete the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault types of planetary gearboxes.

Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)

PubMed Central

Wang, Hu; Ren, Yanshuang; Bai, Lijun; Zhang, Wensheng; Tian, Jie

2012-01-01

Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest. PMID:22540000

Multifractal characterisation of a simulated surface flow: A case study with Multi-Hydro in Jouy-en-Josas, France

NASA Astrophysics Data System (ADS)

Gires, Auguste; Abbes, Jean-Baptiste; da Silva Rocha Paz, Igor; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2018-03-01

In this paper we suggest to innovatively use scaling laws and more specifically Universal Multifractals (UM) to analyse simulated surface runoff and compare the retrieved scaling features with the rainfall ones. The methodology is tested on a 3 km2 semi-urbanised with a steep slope study area located in the Paris area along the Bièvre River. First Multi-Hydro, a fully distributed model is validated on this catchment for four rainfall events measured with the help of a C-band radar. The uncertainty associated with small scale unmeasured rainfall, i.e. occurring below the 1 km × 1 km × 5 min observation scale, is quantified with the help of stochastic downscaled rainfall fields. It is rather significant for simulated flow and more limited on overland water depth for these rainfall events. Overland depth is found to exhibit a scaling behaviour over small scales (10 m-80 m) which can be related to fractal features of the sewer network. No direct and obvious dependency between the overland depth multifractal features (quality of the scaling and UM parameters) and the rainfall ones was found.

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators

PubMed Central

Bai, Xiangzhi

2015-01-01

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion. PMID:26184229

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

PubMed

Bai, Xiangzhi

2015-07-15

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

Multi-Scale Distributed Representation for Deep Learning and its Application to b-Jet Tagging

NASA Astrophysics Data System (ADS)

Lee, Jason Sang Hun; Park, Inkyu; Park, Sangnam

2018-06-01

Recently machine learning algorithms based on deep layered artificial neural networks (DNNs) have been applied to a wide variety of high energy physics problems such as jet tagging or event classification. We explore a simple but effective preprocessing step which transforms each realvalued observational quantity or input feature into a binary number with a fixed number of digits. Each binary digit represents the quantity or magnitude in different scales. We have shown that this approach improves the performance of DNNs significantly for some specific tasks without any further complication in feature engineering. We apply this multi-scale distributed binary representation to deep learning on b-jet tagging using daughter particles' momenta and vertex information.

Reviewing the upper Pleistocene human footprints from the 'Sala dei Misteri' in the Grotta della Bàsura (Toirano, northern Italy) cave: An integrated morphometric and morpho-classificatory approach

NASA Astrophysics Data System (ADS)

Paolo Citton; Romano, Marco; Salvador, Isabella; Avanzini, Marco

2017-08-01

About thirty human footprints made approximately 12,000 years B.P. inside the 'Sala dei Misteri' Cave of Básura near Toirano, Liguria, northern Italy, were studied by standard ichnological analysis. Eleven of the best-preserved tracks were examined further using morpho-classificatory and morphometric approaches, in order to estimate the minimum number of trackmakers; biometric measurements were also used to tentatively determine their physical characteristics (e.g., height and age). Results indicate at least three different producers, two youths and the third of tender age. Analysis of the data demonstrate the power of 3D, of landmark-based morphometrics, and the utility of methods of forensic anthropology in the determination of human footprints. The study of the number of trackmakers using the principal component analysis (PCA) on 'multi-trampling' surfaces could represent a model in the ichnological study of cave sites.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Computational Modeling of Multi-Scale Material Features in Cement Paste - An Overview

DTIC Science & Technology

2015-05-25

and concrete ; though commonly used are one of the most complex in terms of material morphology and structure than most materials, for example...across the multiple scales are required. In this paper, recent work from our research group on the nano to continuum level modeling of cementitious...of our research work consisting of, • Molecular Dynamics (MD) modeling for the nano scale features of the cementitious material chemistry. • Micro

Fused Traditional and Geometric Morphometrics Demonstrate Pinniped Whisker Diversity

PubMed Central

Ginter, Carly C.; DeWitt, Thomas J.; Fish, Frank E.; Marshall, Christopher D.

2012-01-01

Vibrissae (whiskers) are important components of the mammalian tactile sensory system, and primarily function as detectors of vibrotactile information from the environment. Pinnipeds possess the largest vibrissae among mammals and their vibrissal hair shafts demonstrate a diversity of shapes. The vibrissae of most phocid seals exhibit a beaded morphology with repeating sequences of crests and troughs along their length. However, there are few detailed analyses of pinniped vibrissal morphology, and these are limited to a few species. Therefore, we comparatively characterized differences in vibrissal hair shaft morphologies among phocid species with a beaded profile, phocid species with a smooth profile, and otariids with a smooth profile using traditional and geometric morphometric methods. Traditional morphometric measurements (peak-to-peak distance, crest width, trough width and total length) were collected using digital photographs. Elliptic Fourier analysis (geometric morphometrics) was used to quantify the outlines of whole vibrissae. The traditional and geometric morphometric datasets were subsequently combined by mathematically scaling each to true rank, followed by a single eigendecomposition. Quadratic discriminant function analysis demonstrated that 79.3, 97.8 and 100% of individuals could be correctly classified to their species based on vibrissal shape variables in the traditional, geometric and combined morphometric analyses, respectively. Phocids with beaded vibrissae, phocids with smooth vibrissae, and otariids each occupied distinct morphospace in the geometric morphometric and combined data analyses. Otariids split into two groups in the geometric morphometric analysis and gray seals appeared intermediate between beaded- and smooth-whiskered species in the traditional and combined analyses. Vibrissal hair shafts modulate the transduction of environmental stimuli to the mechanoreceptors in the follicle-sinus complex (F-SC), which results in vibrotactile reception, but it is currently unclear how the diversity of shapes affects environmental signal modulation. PMID:22509310

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

NASA Astrophysics Data System (ADS)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

Detection of Neuron Membranes in Electron Microscopy Images Using Multi-scale Context and Radon-Like Features

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

Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.

2011-10-01

Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output ofmore » each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.« less

A morphometric assessment and classification of coral reef spur and groove morphology

NASA Astrophysics Data System (ADS)

Duce, S.; Vila-Concejo, A.; Hamylton, S. M.; Webster, J. M.; Bruce, E.; Beaman, R. J.

2016-07-01

Spurs and grooves (SaGs) are a common and important feature of coral reef fore slopes worldwide. However, they are difficult to access and hence their morphodynamics and formation are poorly understood. We use remote sensing, with extensive ground truthing, to measure SaG morphometrics and environmental factors at 11,430 grooves across 17 reefs in the southern Great Barrier Reef, Australia. We revealed strong positive correlations between groove length, orientation and wave exposure with longer, more closely-spaced grooves oriented easterly reflecting the dominant swell regime. Wave exposure was found to be the most important factor controlling SaG distribution and morphology. Gradient of the upper reef slope was also an important limiting factor, with SaGs less likely to develop in steeply sloping (> 5°) areas. We used a subset of the morphometric data (11 reefs) to statistically define four classes of SaG. This classification scheme was tested on the remaining six reefs. SaGs in the four classes differ in morphology, groove substrate and coral cover. These differences provide insights into SaG formation mechanisms with implications to reef platform growth and evolution. We hypothesize SaG formation is dominated by coral growth processes at two classes and erosion processes at one class. A fourth class may represent relic features formed earlier in the Holocene transgression. The classes are comparable with SaGs elsewhere, suggesting the classification could be applied globally with the addition of new classes if necessary. While further research is required, we show remotely sensed SaG morphometrics can provide useful insights into reef platform evolution.

[A method for obtaining redshifts of quasars based on wavelet multi-scaling feature matching].

PubMed

Liu, Zhong-Tian; Li, Xiang-Ru; Wu, Fu-Chao; Zhao, Yong-Heng

2006-09-01

The LAMOST project, the world's largest sky survey project being implemented in China, is expected to obtain 10(5) quasar spectra. The main objective of the present article is to explore methods that can be used to estimate the redshifts of quasar spectra from LAMOST. Firstly, the features of the broad emission lines are extracted from the quasar spectra to overcome the disadvantage of low signal-to-noise ratio. Then the redshifts of quasar spectra can be estimated by using the multi-scaling feature matching. The experiment with the 15, 715 quasars from the SDSS DR2 shows that the correct rate of redshift estimated by the method is 95.13% within an error range of 0. 02. This method was designed to obtain the redshifts of quasar spectra with relative flux and a low signal-to-noise ratio, which is applicable to the LAMOST data and helps to study quasars and the large-scale structure of the universe etc.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Influence of Sub-Daily Variation on Multi-Fractal Detrended Fluctuation Analysis of Wind Speed Time Series

PubMed Central

Li, Weinan; Kong, Yanjun; Cong, Xiangyu

2016-01-01

Using multi-fractal detrended fluctuation analysis (MF-DFA), the scaling features of wind speed time series (WSTS) could be explored. In this paper, we discuss the influence of sub-daily variation, which is a natural feature of wind, in MF-DFA of WSTS. First, the choice of the lower bound of the segment length, a significant parameter of MF-DFA, was studied. The results of expanding the lower bound into sub-daily scope shows that an abrupt declination and discrepancy of scaling exponents is caused by the inability to keep the whole diel process of wind in one single segment. Additionally, the specific value, which is effected by the sub-daily feature of local meteo-climatic, might be different. Second, the intra-day temporal order of wind was shuffled to determine the impact of diel variation on scaling exponents of MF-DFA. The results illustrate that disregarding diel variation leads to errors in scaling. We propose that during the MF-DFA of WSTS, the segment length should be longer than 1 day and the diel variation of wind should be maintained to avoid abnormal phenomena and discrepancy in scaling exponents. PMID:26741491

Range-wide wetland associations of the King Rail: A multi-scale approach

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.; Laxson, Thomas A.

2015-01-01

King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.

A multi-machine scaling of halo current rotation

NASA Astrophysics Data System (ADS)

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; Gerhardt, S. P.; Granetz, R. S.; Hender, T. C.; Pautasso, G.; Contributors, JET

2018-01-01

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: (1) the machine-specific minimum current quench time, \

A multi-machine scaling of halo current rotation

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

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

A multi-machine scaling of halo current rotation

DOE PAGES

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; ...

2017-12-12

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

Revision of the Malagasy Camponotus edmondi species group (Hymenoptera, Formicidae, Formicinae): integrating qualitative morphology and multivariate morphometric analysis.

PubMed

Rakotonirina, Jean Claude; Csősz, Sándor; Fisher, Brian L

2016-01-01

The Malagasy Camponotus edmondi species group is revised based on both qualitative morphological traits and multivariate analysis of continuous morphometric data. To minimize the effect of the scaling properties of diverse traits due to worker caste polymorphism, and to achieve the desired near-linearity of data, morphometric analyses were done only on minor workers. The majority of traits exhibit broken scaling on head size, dividing Camponotus workers into two discrete subcastes, minors and majors. This broken scaling prevents the application of algorithms that uses linear combination of data to the entire dataset, hence only minor workers were analyzed statistically. The elimination of major workers resulted in linearity and the data meet required assumptions. However, morphometric ratios for the subsets of minor and major workers were used in species descriptions and redefinitions. Prior species hypotheses and the goodness of clusters were tested on raw data by confirmatory linear discriminant analysis. Due to the small sample size available for some species, a factor known to reduce statistical reliability, hypotheses generated by exploratory analyses were tested with extreme care and species delimitations were inferred via the combined evidence of both qualitative (morphology and biology) and quantitative data. Altogether, fifteen species are recognized, of which 11 are new to science: Camponotus alamaina sp. n. , Camponotus androy sp. n. , Camponotus bevohitra sp. n. , Camponotus galoko sp. n. , Camponotus matsilo sp. n. , Camponotus mifaka sp. n. , Camponotus orombe sp. n. , Camponotus tafo sp. n. , Camponotus tratra sp. n. , Camponotus varatra sp. n. , and Camponotus zavo sp. n. Four species are redescribed: Camponotus echinoploides Forel, Camponotus edmondi André, Camponotus ethicus Forel, and Camponotus robustus Roger. Camponotus edmondi ernesti Forel, syn. n. is synonymized under Camponotus edmondi . This revision also includes an identification key to species for both minor and major castes, information on geographic distribution and biology, taxonomic discussions, and descriptions of intraspecific variation. Traditional taxonomy and multivariate morphometric analysis are independent sources of information which, in combination, allow more precise species delimitation. Moreover, quantitative characters included in identification keys improve accuracy of determination in difficult cases.

Revision of the Malagasy Camponotus edmondi species group (Hymenoptera, Formicidae, Formicinae): integrating qualitative morphology and multivariate morphometric analysis

PubMed Central

Rakotonirina, Jean Claude; Csősz, Sándor; Fisher, Brian L.

2016-01-01

Abstract The Malagasy Camponotus edmondi species group is revised based on both qualitative morphological traits and multivariate analysis of continuous morphometric data. To minimize the effect of the scaling properties of diverse traits due to worker caste polymorphism, and to achieve the desired near-linearity of data, morphometric analyses were done only on minor workers. The majority of traits exhibit broken scaling on head size, dividing Camponotus workers into two discrete subcastes, minors and majors. This broken scaling prevents the application of algorithms that uses linear combination of data to the entire dataset, hence only minor workers were analyzed statistically. The elimination of major workers resulted in linearity and the data meet required assumptions. However, morphometric ratios for the subsets of minor and major workers were used in species descriptions and redefinitions. Prior species hypotheses and the goodness of clusters were tested on raw data by confirmatory linear discriminant analysis. Due to the small sample size available for some species, a factor known to reduce statistical reliability, hypotheses generated by exploratory analyses were tested with extreme care and species delimitations were inferred via the combined evidence of both qualitative (morphology and biology) and quantitative data. Altogether, fifteen species are recognized, of which 11 are new to science: Camponotus alamaina sp. n., Camponotus androy sp. n., Camponotus bevohitra sp. n., Camponotus galoko sp. n., Camponotus matsilo sp. n., Camponotus mifaka sp. n., Camponotus orombe sp. n., Camponotus tafo sp. n., Camponotus tratra sp. n., Camponotus varatra sp. n., and Camponotus zavo sp. n. Four species are redescribed: Camponotus echinoploides Forel, Camponotus edmondi André, Camponotus ethicus Forel, and Camponotus robustus Roger. Camponotus edmondi ernesti Forel, syn. n. is synonymized under Camponotus edmondi. This revision also includes an identification key to species for both minor and major castes, information on geographic distribution and biology, taxonomic discussions, and descriptions of intraspecific variation. Traditional taxonomy and multivariate morphometric analysis are independent sources of information which, in combination, allow more precise species delimitation. Moreover, quantitative characters included in identification keys improve accuracy of determination in difficult cases. PMID:28050160

Data fusion of multi-scale representations for structural damage detection

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data.

PubMed

Scales, Matthew; Jäger, Roland; Migliorini, Gabriele; Houlston, Richard S; Henrion, Marc Y R

2014-01-01

We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk), a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R, Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser or the WashU Epigenome Browser allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV). Other locally run data visualisation software such as Circos require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…). It also allows annotation of genes and other custom features in the plotted region(s). Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3).

Hepatic Histology and Morphometric Measurements in Idiopathic Extrahepatic Portal Vein Thrombosis in Children, Correlated to Clinical Outcome of Meso-Rex Bypass.

PubMed

Tantemsapya, Niramol; Superina, Riccardo; Wang, Deli; Kronauer, Grace; Whitington, Peter F; Melin-Aldana, Hector

2018-06-01

The aim of this study was to correlate clinical, histologic, and morphometric features of the liver in children with extrahepatic portal vein thrombosis (EHPVT), with surgical outcome after Meso-Rex bypass (MRB). Idiopathic EHPVT, a significant cause of portal hypertension, is surgically corrected by MRB. Correlation of histologic and morphometric features of the liver with outcome has not been reported in children. We retrospectively reviewed clinical and intraoperative data of 45 children with idiopathic EHPVT. Liver samples were obtained at the time of MRB. Morphometric measurements of portal tract structures were performed and correlated with surgical outcome. Median follow-up was 3.65 years after surgery (range 1.5 to 10 years). Thirty-seven (82.2%) children had successful MRB. There was no association between age, sex, and suture material with surgical outcome. Average patient age was higher in patients with postoperative complications (P = NS). Portal fibrosis, bridging, parenchymal nodules, portal inflammation, hepatocellular swelling, steatosis, dilatation of portal lymphatics, and periductal fibrosis did not show a significant difference between the 2 groups. Portal vein and bile duct area index were significantly smaller in the unsuccessful group (P = 0.004 and 0.003, respectively). A portal vein area index <0.08 had a lower chance of successful surgical outcome. Hepatic artery area index was not significantly different. Measured intraoperative portal blood inflow was the only significant clinical factor affecting surgical outcome (P = 0.0003). Low portal vein area index and intraoperative portal blood inflow may be negative prognostic factors for MRB outcome in children with idiopathic EHPVT. Average patient age was higher, although not statistically significant, in patients with postoperative complications.

Quantitative pathology in virtual microscopy: history, applications, perspectives.

PubMed

Kayser, Gian; Kayser, Klaus

2013-07-01

With the emerging success of commercially available personal computers and the rapid progress in the development of information technologies, morphometric analyses of static histological images have been introduced to improve our understanding of the biology of diseases such as cancer. First applications have been quantifications of immunohistochemical expression patterns. In addition to object counting and feature extraction, laws of thermodynamics have been applied in morphometric calculations termed syntactic structure analysis. Here, one has to consider that the information of an image can be calculated for separate hierarchical layers such as single pixels, cluster of pixels, segmented small objects, clusters of small objects, objects of higher order composed of several small objects. Using syntactic structure analysis in histological images, functional states can be extracted and efficiency of labor in tissues can be quantified. Image standardization procedures, such as shading correction and color normalization, can overcome artifacts blurring clear thresholds. Morphometric techniques are not only useful to learn more about biological features of growth patterns, they can also be helpful in routine diagnostic pathology. In such cases, entropy calculations are applied in analogy to theoretical considerations concerning information content. Thus, regions with high information content can automatically be highlighted. Analysis of the "regions of high diagnostic value" can deliver in the context of clinical information, site of involvement and patient data (e.g. age, sex), support in histopathological differential diagnoses. It can be expected that quantitative virtual microscopy will open new possibilities for automated histological support. Automated integrated quantification of histological slides also serves for quality assurance. The development and theoretical background of morphometric analyses in histopathology are reviewed, as well as their application and potential future implementation in virtual microscopy. Copyright © 2012 Elsevier GmbH. All rights reserved.

Landmark-based geometric morphometric analysis of wing shape among certain species of Aedes mosquitoes in District Dehradun (Uttarakhand), India.

PubMed

Mondal, Ritwik; Devi, N Pemola; Jauhari, R K

2015-06-01

Insect wing morphology has been used in many studies to describe variations among species and populations using traditional morphometrics, and more recently geometric morphometrics. A landmark-based geometric morphometric analysis of the wings of three species of Aedes (Diptera: Culicidae), viz. Ae. aegypti, Ae. albopictus and Ae. pseudotaeniatus, at District Dehradun was conducted belling on the fact that it can provide insight into the population structure, ecology and taxonomic identification. Adult Aedes mosquito specimens were randomly collected using aerial nets and morphologically examined and identified. The landmarks were identified on the basis of landmark based geometric morphometric analysis thin-plate spline (mainly the software tps-Util 1.28; tps-Dig 1.40; tps-Relw 1.53; and tps-Spline 1.20) and integrated morphometrics programme (mainly twogroup win8 and PCA win8) were utilized. In relative warp (RW) analysis, the first two RW of Ae. aegypti accounted for the highest value (95.82%), followed by Ae. pseudotaeniatus (90.89%), while the lowest (90.12%) being recorded for Ae. albopictus. The bending energies of Ae. aegypti and Ae. pseudotaeniatus were quite identical being 0.1882 and 0.1858 respectively, while Ae. albopictus recorded the highest value of 0.9774. The mean difference values of the distances among Aedes species performing Hotelling's T 2 test were significantly high, predicting major differences among the taxa. In PCA analysis, the horizontal and vertical axis summarized 52.41 and 23.30% of variances respectively. The centroid size exhibited significant differences among populations (non-parametric Kruskal-Wallis test, H = 10.56, p < 0.01). It has been marked out that the geometric morphometrics utilizes powerful and comprehensive statistical procedures to analyze the shape differences of a morphological feature, assuming that the studied mosquitoes may represent different genotypes and probably come from one diverse gene pool.

A novel fruit shape classification method based on multi-scale analysis

NASA Astrophysics Data System (ADS)

Gui, Jiangsheng; Ying, Yibin; Rao, Xiuqin

2005-11-01

Shape is one of the major concerns and which is still a difficult problem in automated inspection and sorting of fruits. In this research, we proposed the multi-scale energy distribution (MSED) for object shape description, the relationship between objects shape and its boundary energy distribution at multi-scale was explored for shape extraction. MSED offers not only the mainly energy which represent primary shape information at the lower scales, but also subordinate energy which represent local shape information at higher differential scales. Thus, it provides a natural tool for multi resolution representation and can be used as a feature for shape classification. We addressed the three main processing steps in the MSED-based shape classification. They are namely, 1) image preprocessing and citrus shape extraction, 2) shape resample and shape feature normalization, 3) energy decomposition by wavelet and classification by BP neural network. Hereinto, shape resample is resample 256 boundary pixel from a curve which is approximated original boundary by using cubic spline in order to get uniform raw data. A probability function was defined and an effective method to select a start point was given through maximal expectation, which overcame the inconvenience of traditional methods in order to have a property of rotation invariants. The experiment result is relatively well normal citrus and serious abnormality, with a classification rate superior to 91.2%. The global correct classification rate is 89.77%, and our method is more effective than traditional method. The global result can meet the request of fruit grading.

Rotation, scale, and translation invariant pattern recognition using feature extraction

NASA Astrophysics Data System (ADS)

Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

1997-03-01

A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.

Structural health monitoring using DOG multi-scale space: an approach for analyzing damage characteristics

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-03-01

Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

A fault diagnosis scheme for planetary gearboxes using adaptive multi-scale morphology filter and modified hierarchical permutation entropy

NASA Astrophysics Data System (ADS)

Li, Yongbo; Li, Guoyan; Yang, Yuantao; Liang, Xihui; Xu, Minqiang

2018-05-01

The fault diagnosis of planetary gearboxes is crucial to reduce the maintenance costs and economic losses. This paper proposes a novel fault diagnosis method based on adaptive multi-scale morphological filter (AMMF) and modified hierarchical permutation entropy (MHPE) to identify the different health conditions of planetary gearboxes. In this method, AMMF is firstly adopted to remove the fault-unrelated components and enhance the fault characteristics. Second, MHPE is utilized to extract the fault features from the denoised vibration signals. Third, Laplacian score (LS) approach is employed to refine the fault features. In the end, the obtained features are fed into the binary tree support vector machine (BT-SVM) to accomplish the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault categories of planetary gearboxes.

Response of Moist Convection to Multi-scale Surface Flux Heterogeneity

NASA Astrophysics Data System (ADS)

Kang, S. L.; Ryu, J. H.

2015-12-01

We investigate response of moist convection to multi-scale feature of the spatial variation of surface sensible heat fluxes (SHF) in the afternoon evolution of the convective boundary layer (CBL), utilizing a mesoscale-domain large eddy simulation (LES) model. The multi-scale surface heterogeneity feature is analytically created as a function of the spectral slope in the wavelength range from a few tens of km to a few hundreds of m in the spectrum of surface SHF on a log-log scale. The response of moist convection to the κ-3 - slope (where κ is wavenumber) surface SHF field is compared with that to the κ-2 - slope surface, which has a relatively weak mesoscale feature, and the homogeneous κ0 - slope surface. Given the surface energy balance with a spatially uniform available energy, the prescribed SHF has a 180° phase lag with the latent heat flux (LHF) in a horizontal domain of (several tens of km)2. Thus, warmer (cooler) surface is relatively dry (moist). For all the cases, the same observation-based sounding is prescribed for the initial condition. For all the κ-3 - slope surface heterogeneity cases, early non-precipitating shallow clouds further develop into precipitating deep thunderstorms. But for all the κ-2 - slope cases, only shallow clouds develop. We compare the vertical profiles of domain-averaged fluxes and variances, and the contribution of the mesoscale and turbulence contributions to the fluxes and variances, between the κ-3 versus κ-2 slope cases. Also the cross-scale processes are investigated.

Capability of applying morphometric parameters of relief in river basins for geomorphological zoning of a territory

NASA Astrophysics Data System (ADS)

Ivanov, M. A.; Yermolaev, O. P.

2018-01-01

Information about morphometric characteristics of relief is necessary for researches devoted to geographic characteristics of territory, its zoning, assessment of erosion processes, geoecological condition and others. For the Volga Federal District for the first time a spatial database of geomorphometric parameters 1: 200 000 scale was created, based on a river basin approach. Watersheds are used as a spatial units created by semi-automated method using the terrain and hydrological modeling techniques implemented in the TAS GIS and WhiteBox GIS. As input data DEMs SRTM and Aster GDEM and hydrographic network vectorized from topographic maps were used. Using DEM highlighted above for each river basin, basic morphometric relief characteristics such as mean height, slope steepness, slope length, height range, river network density and factor LS were calculated. Basins belonging to the geomorphological regions and landscape zones was determined, according to the map of geomorphological zoning and landscape map. Analysis of variance revealed a statistically significant relationship between these characteristics and geomorphological regions and landscape zones. Consequently, spatial trends of changes of analyzed morphometric characteristics were revealed.

Multi-scale evaporator architectures for geothermal binary power plants

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

Sabau, Adrian S; Nejad, Ali; Klett, James William

2016-01-01

In this paper, novel geometries of heat exchanger architectures are proposed for evaporators that are used in Organic Rankine Cycles. A multi-scale heat exchanger concept was developed by employing successive plenums at several length-scale levels. Flow passages contain features at both macro-scale and micro-scale, which are designed from Constructal Theory principles. Aside from pumping power and overall thermal resistance, several factors were considered in order to fully assess the performance of the new heat exchangers, such as weight of metal structures, surface area per unit volume, and total footprint. Component simulations based on laminar flow correlations for supercritical R134a weremore » used to obtain performance indicators.« less

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Morphologic and morphometric studies of impact craters in the northern plains of Mars

NASA Technical Reports Server (NTRS)

Barlow, N. G.

1993-01-01

Fresh impact craters in the northern plains of Mars display a variety of morphologic and morphometric properties. Ejecta morphologies range from radial to fluidized, interior features include central peaks and central pits, fluidized morphologies display a range of sinuosities, and depth-diameter ratios are being measured to determine regional variations. Studies of the martian northern plains over the past five years have concentrated in three areas: (1) determining correlations of ejecta morphologies with crater diameter, latitude, and underlying terrain; (2) determining variations in fluidized ejecta blanket sinuosity across the planet; and (3) measurement of depth-diameter ratios and determination of regional variations in this ratio.

Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

NASA Astrophysics Data System (ADS)

Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

2018-01-01

Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

A multi-layer MRI description of Parkinson's disease

NASA Astrophysics Data System (ADS)

La Rocca, M.; Amoroso, N.; Lella, E.; Bellotti, R.; Tangaro, S.

2017-09-01

Magnetic resonance imaging (MRI) along with complex network is currently one of the most widely adopted techniques for detection of structural changes in neurological diseases, such as Parkinson's Disease (PD). In this paper, we present a digital image processing study, within the multi-layer network framework, combining more classifiers to evaluate the informative power of the MRI features, for the discrimination of normal controls (NC) and PD subjects. We define a network for each MRI scan; the nodes are the sub-volumes (patches) the images are divided into and the links are defined using the Pearson's pairwise correlation between patches. We obtain a multi-layer network whose important network features, obtained with different feature selection methods, are used to feed a supervised multi-level random forest classifier which exploits this base of knowledge for accurate classification. Method evaluation has been carried out using T1 MRI scans of 354 individuals, including 177 PD subjects and 177 NC from the Parkinson's Progression Markers Initiative (PPMI) database. The experimental results demonstrate that the features obtained from multiplex networks are able to accurately describe PD patterns. Besides, also if a privileged scale for studying PD disease exists, exploring the informative content of more scales leads to a significant improvement of the performances in the discrimination between disease and healthy subjects. In particular, this method gives a comprehensive overview of brain regions statistically affected by the disease, an additional value to the presented study.

Phase diagrams of vortex matter with multi-scale inter-vortex interactions in layered superconductors.

PubMed

Meng, Qingyou; Varney, Christopher N; Fangohr, Hans; Babaev, Egor

2017-01-25

It was recently proposed to use the stray magnetic fields of superconducting vortex lattices to trap ultracold atoms for building quantum emulators. This calls for new methods for engineering and manipulating of the vortex states. One of the possible routes utilizes type-1.5 superconducting layered systems with multi-scale inter-vortex interactions. In order to explore the possible vortex states that can be engineered, we present two phase diagrams of phenomenological vortex matter models with multi-scale inter-vortex interactions featuring several attractive and repulsive length scales. The phase diagrams exhibit a plethora of phases, including conventional 2D lattice phases, five stripe phases, dimer, trimer, and tetramer phases, void phases, and stable low-temperature disordered phases. The transitions between these states can be controlled by the value of an applied external field.

The research and application of multi-biometric acquisition embedded system

NASA Astrophysics Data System (ADS)

Deng, Shichao; Liu, Tiegen; Guo, Jingjing; Li, Xiuyan

2009-11-01

The identification technology based on multi-biometric can greatly improve the applicability, reliability and antifalsification. This paper presents a multi-biometric system bases on embedded system, which includes: three capture daughter boards are applied to obtain different biometric: one each for fingerprint, iris and vein of the back of hand; FPGA (Field Programmable Gate Array) is designed as coprocessor, which uses to configure three daughter boards on request and provides data path between DSP (digital signal processor) and daughter boards; DSP is the master processor and its functions include: control the biometric information acquisition, extracts feature as required and responsible for compare the results with the local database or data server through network communication. The advantages of this system were it can acquire three different biometric in real time, extracts complexity feature flexibly in different biometrics' raw data according to different purposes and arithmetic and network interface on the core-board will be the solution of big data scale. Because this embedded system has high stability, reliability, flexibility and fit for different data scale, it can satisfy the demand of multi-biometric recognition.

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

NASA Astrophysics Data System (ADS)

Yang, Xue; Sun, Hao; Fu, Kun; Yang, Jirui; Sun, Xian; Yan, Menglong; Guo, Zhi

2018-01-01

Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.

Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.

PubMed

Donnelly-Kehoe, Patricio Andres; Pascariello, Guido Orlando; Gómez, Juan Carlos

2018-05-15

We present our results in the International challenge for automated prediction of MCI from MRI data. We evaluate the performance of MRI-based neuromorphometrics features (nMF) in the classification of Healthy Controls (HC), Mild Cognitive Impairment (MCI), converters MCI (cMCI) and Alzheimer's Disease (AD) patients. We propose to segregate participants in three groups according to Mini Mental State Examination score (MMSEs), searching for the main nMF in each group. Then we use them to develop a Multi Classifier System (MCS). We compare the MCS against a single classifier scheme using both MMSEs+nMF and nMF only. We repeat this comparison using three state-of-the-art classification algorithms. The MCS showed the best performance on both Accuracy and Area Under the Receiver Operating Curve (AUC) in comparison with single classifiers. The multiclass AUC for the MCS classification on Test Dataset were 0.83 for HC, 0.76 for cMCI, 0.65 for MCI and 0.95 for AD. Furthermore, MCS's optimum accuracy on Neurodegenerative Disease (ND) detection (AD+cMCI vs MCI+HC) was 81.0% (AUC=0.88), while the single classifiers got 71.3% (AUC=0.86) and 63.1% (AUC=0.79) for MMSEs+nMF and only nMF respectively. The proposed MCS showed a better performance than using all nMF into a single state-of-the-art classifier. These findings suggest that using cognitive scoring, e.g. MMSEs, in the design of a Multi Classifier System improves performance by allowing a better selection of MRI-based features. Copyright © 2017 Elsevier B.V. All rights reserved.

Diagnostic and prognostic histopathology system using morphometric indices

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

Parvin, Bahram; Chang, Hang; Han, Ju

Determining at least one of a prognosis or a therapy for a patient based on a stained tissue section of the patient. An image of a stained tissue section of a patient is processed by a processing device. A set of features values for a set of cell-based features is extracted from the processed image, and the processed image is associated with a particular cluster of a plurality of clusters based on the set of feature values, where the plurality of clusters is defined with respect to a feature space corresponding to the set of features.

The Segmental Morphometric Properties of the Horse Cervical Spinal Cord: A Study of Cadaver

PubMed Central

Bahar, Sadullah; Bolat, Durmus; Selcuk, Muhammet Lutfi

2013-01-01

Although the cervical spinal cord (CSC) of the horse has particular importance in diseases of CNS, there is very little information about its segmental morphometry. The objective of the present study was to determine the morphometric features of the CSC segments in the horse and possible relationships among the morphometric features. The segmented CSC from five mature animals was used. Length, weight, diameter, and volume measurements of the segments were performed macroscopically. Lengths and diameters of segments were measured histologically, and area and volume measurements were performed using stereological methods. The length, weight, and volume of the CSC were 61.6 ± 3.2 cm, 107.2 ± 10.4 g, and 95.5 ± 8.3 cm3, respectively. The length of the segments was increased from C 1 to C 3, while it decreased from C 3 to C 8. The gross section (GS), white matter (WM), grey matter (GM), dorsal horn (DH), and ventral horn (VH) had the largest cross-section areas at C 8. The highest volume was found for the total segment and WM at C 4, GM, DH, and VH at C 7, and the central canal (CC) at C 3. The data obtained not only contribute to the knowledge of the normal anatomy of the CSC but may also provide reference data for veterinary pathologists and clinicians. PMID:23476145

Morphometrical differences between resectable and non-resectable pancreatic cancer: a fractal analysis.

PubMed

Vasilescu, Catalin; Giza, Dana Elena; Petrisor, Petre; Dobrescu, Radu; Popescu, Irinel; Herlea, Vlad

2012-01-01

Pancreatic cancer is a highly aggressive cancer with a rising incidence and poor prognosis despite active surgical treatment. Candidates for surgical resection should be carefully selected. In order to avoid unnecessary laparotomy it is useful to identify reliable factors that may predict resectability. Nuclear morphometry and fractal dimension of pancreatic nuclear features could provide important preoperative information in assessing pancreas resectability. Sixty-one patients diagnosed with pancreatic cancer were enrolled in this retrospective study between 2003 and 2005. Patients were divided into two groups: one resectable cancer group and one with non-resectable pancreatic cancer. Morphometric parameters measured were: nuclear area, length of minor axis and length of major axis. Nuclear shape and chromatin distribution of the pancreatic tumor cells were both estimated using fractal dimension. Morphometric measurements have shown significant differences between the nuclear area of the resectable group and the non-resectable group (61.9 ± 19.8µm vs. 42.2 ± 15.6µm). Fractal dimension of the nuclear outlines and chromatin distribution was found to have a higher value in the non-resectable group (p<0.05). Objective measurements should be performed to improve risk assessment and therapeutic decisions in pancreatic cancer. Nuclear morphometry of the pancreatic nuclear features can provide important pre-operative information in resectability assessment. The fractal dimension of the nuclear shape and chromatin distribution may be considered a new promising adjunctive tool for conventional pathological analysis.

Action detection by double hierarchical multi-structure space-time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-03-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Action detection by double hierarchical multi-structure space–time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-06-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Geometric morphometrics in primatology: craniofacial variation in Homo sapiens and Pan troglodytes.

PubMed

Lynch, J M; Wood, C G; Luboga, S A

1996-01-01

Traditionally, morphometric studies have relied on statistical analysis of distances, angles or ratios to investigate morphometric variation among taxa. Recently, geometric techniques have been developed for the direct analysis of landmark data. In this paper, we offer a summary (with examples) of three of these newer techniques, namely shape coordinate, thin-plate spline and relative warp analyses. Shape coordinate analysis detected significant craniofacial variation between 4 modern human populations, with African and Australian Aboriginal specimens being relatively prognathous compared with their Eurasian counterparts. In addition, the Australian specimens exhibited greater basicranial flexion than all other samples. The observed relationships between size and craniofacial shape were weak. The decomposition of shape variation into affine and non-affine components is illustrated via a thin-plate spline analysis of Homo and Pan cranial landmarks. We note differences between Homo and Pan in the degree of prognathism and basicranial flexion and the position and orientation of the foramen magnum. We compare these results with previous studies of these features in higher primates and discuss the utility of geometric morphometrics as a tool in primatology and physical anthropology. We conclude that many studies of morphological variation, both within and between taxa, would benefit from the graphical nature of these techniques.

Medial prefrontal aberrations in major depressive disorder revealed by cytoarchitectonically informed voxel-based morphometry

PubMed Central

Bludau, Sebastian; Bzdok, Danilo; Gruber, Oliver; Kohn, Nils; Riedl, Valentin; Sorg, Christian; Palomero-Gallagher, Nicola; Müller, Veronika I.; Hoffstaedter, Felix; Amunts, Katrin; Eickhoff, Simon B.

2017-01-01

Objective The heterogeneous human frontal pole has been identified as a node in the dysfunctional network of major depressive disorder. The contribution of the medial (socio-affective) versus lateral (cognitive) frontal pole to major depression pathogenesis is currently unclear. The present study performs morphometric comparison of the microstructurally informed subdivisions of human frontal pole between depressed patients and controls using both uni- and multivariate statistics. Methods Multi-site voxel- and region-based morphometric MRI analysis of 73 depressed patients and 73 matched controls without psychiatric history. Frontal pole volume was first compared between depressed patients and controls by subdivision-wise classical morphometric analysis. In a second approach, frontal pole volume was compared by subdivision-naive multivariate searchlight analysis based on support vector machines. Results Subdivision-wise morphometric analysis found a significantly smaller medial frontal pole in depressed patients with a negative correlation of disease severity and duration. Histologically uninformed multivariate voxel-wise statistics provided converging evidence for structural aberrations specific to the microstructurally defined medial area of the frontal pole in depressed patients. Conclusions Across disparate methods, we demonstrated subregion specificity in the left medial frontal pole volume in depressed patients. Indeed, the frontal pole was shown to structurally and functionally connect to other key regions in major depression pathology like the anterior cingulate cortex and the amygdala via the uncinate fasciculus. Present and previous findings consolidate the left medial portion of the frontal pole as particularly altered in major depression. PMID:26621569

Biological effects of ultraviolet irradiation on bees

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

Es`kov, E.K.

1995-09-01

The influence of natural solar and artificial ultraviolet irradiation on developing bees was studied. Lethal exposures to irradiation at different stages of development were determined. The influence of irradiation on the variability of the morphometric features of bees was revealed. 5 refs., 1 fig.

The shape of the hominoid proximal femur: a geometric morphometric analysis

PubMed Central

Harmon, Elizabeth H

2007-01-01

As part of the hip joint, the proximal femur is an integral locomotor component. Although a link between locomotion and the morphology of some aspects of the proximal femur has been identified, inclusive shapes of this element have not been compared among behaviourally heterogeneous hominoids. Previous analyses have partitioned complex proximal femoral morphology into discrete features (e.g. head, neck, greater trochanter) to facilitate conventional linear measurements. In this study, three-dimensional geometric morphometrics are used to examine the shape of the proximal femur in hominoids to determine whether femoral shape co-varies with locomotor category. Fourteen landmarks are recorded on adult femora of Homo, Pan, Gorilla, Pongo and Hylobates. Generalized Procrustes analysis (GPA) is used to adjust for position, orientation and scale among landmark configurations. Principal components analysis is used to collapse and compare variation in residuals from GPA, and thin-plate spline analysis is used to visualize shape change among taxa. The results indicate that knucklewalking African apes are similar to one another in femoral shape, whereas the more suspensory Asian apes diverge from the African ape pattern. The shape of the human and orangutan proximal femur converge, a result that is best explained in terms of the distinct requirements for locomotion in each group. These findings suggest that the shape of the proximal femur is brought about primarily by locomotor behaviour. PMID:17310545

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

PubMed Central

Wang, Kun-Ching

2015-01-01

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech. PMID:25594590

A real-time multi-scale 2D Gaussian filter based on FPGA

NASA Astrophysics Data System (ADS)

Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin

2014-11-01

Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.

Multi-scale heterogeneity of the 2011 Great Tohoku-oki Earthquake from dynamic simulations

NASA Astrophysics Data System (ADS)

Aochi, H.; Ide, S.

2011-12-01

In order to explain the scaling issues of earthquakes of different sizes, multi-scale heterogeneity conception is necessary to characterize earthquake faulting property (Ide and Aochi, JGR, 2005; Aochi and Ide, JGR, 2009).The 2011 Great Tohoku-oki earthquake (M9) is characterized by a slow initial phase of about M7, a M8 class deep rupture, and a M9 main rupture with quite large slip near the trench (e.g. Ide et al., Science, 2011) as well as the presence of foreshocks. We dynamically model these features based on the multi-scale conception. We suppose a significantly large fracture energy (corresponding to slip-weakening distance of 3.2 m) in most of the fault dimension to represent the M9 rupture. However we give local heterogeneity with relatively small circular patches of smaller fracture energy, by assuming the linear scaling relation between the radius and fracture energy. The calculation is carried out using 3D Boundary Integral Equation Method. We first begin only with the mainshock (Aochi and Ide, EPS, 2011), but later we find it important to take into account of a series of foreshocks since the 9th March (M7.4). The smaller patches including the foreshock area are necessary to launch the M9 rupture area of large fracture energy. We then simulate the ground motion in low frequencies using Finite Difference Method. Qualitatively, the observed tendency is consistent with our simulations, in the meaning of the transition from the central part to the southern part in low frequencies (10 - 20 sec). At higher frequencies (1-10 sec), further small asperities are inferred in the observed signals, and this feature matches well with our multi-scale conception.

The evaluation of multi-structure, multi-atlas pelvic anatomy features in a prostate MR lymphography CAD system

NASA Astrophysics Data System (ADS)

Meijs, M.; Debats, O.; Huisman, H.

2015-03-01

In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.

eDNAoccupancy: An R package for multi-scale occupancy modeling of environmental DNA data

USGS Publications Warehouse

Dorazio, Robert; Erickson, Richard A.

2017-01-01

In this article we describe eDNAoccupancy, an R package for fitting Bayesian, multi-scale occupancy models. These models are appropriate for occupancy surveys that include three, nested levels of sampling: primary sample units within a study area, secondary sample units collected from each primary unit, and replicates of each secondary sample unit. This design is commonly used in occupancy surveys of environmental DNA (eDNA). eDNAoccupancy allows users to specify and fit multi-scale occupancy models with or without covariates, to estimate posterior summaries of occurrence and detection probabilities, and to compare different models using Bayesian model-selection criteria. We illustrate these features by analyzing two published data sets: eDNA surveys of a fungal pathogen of amphibians and eDNA surveys of an endangered fish species.

Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

PubMed

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-02-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Multi-scale learning based segmentation of glands in digital colonrectal pathology images

NASA Astrophysics Data System (ADS)

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-03-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Understanding of the Geomorphological Elements in Discrimination of Typical Mediterranean Land Cover Types

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Boteva, Silvena

2017-12-01

Quantification of geomorphometric features is the keystone concern of the current study. The quantification was based on the statistical approach in term of multivariate analysis of local topographic features. The implemented algorithm utilizes the Digital Elevation Model (DEM) to categorize and extract the geomorphometric features embedded in the topographic dataset. The morphological settings were exercised on the central pixel of 3x3 per-defined convolution kernel to evaluate the surrounding pixels under the right directional pour point model (D8) of the azimuth viewpoints. Realization of unsupervised classification algorithm in term of Iterative Self-Organizing Data Analysis Technique (ISODATA) was carried out on ASTER GDEM within the boundary of the designated study area to distinguish 10 morphometric classes. The morphometric classes expressed spatial distribution variation in the study area. The adopted methodology is successful to appreciate the spatial distribution of the geomorphometric features under investigation. The conducted results verified the superimposition of the delineated geomorphometric elements over a given remote sensing imagery to be further analyzed. Robust relationship between different Land Cover types and the geomorphological elements was established in the context of the study area. The domination and the relative association of different Land Cover types in corresponding to its geomorphological elements were demonstrated.

An ensemble learning system for a 4-way classification of Alzheimer's disease and mild cognitive impairment.

PubMed

Yao, Dongren; Calhoun, Vince D; Fu, Zening; Du, Yuhui; Sui, Jing

2018-05-15

Discriminating Alzheimer's disease (AD) from its prodromal form, mild cognitive impairment (MCI), is a significant clinical problem that may facilitate early diagnosis and intervention, in which a more challenging issue is to classify MCI subtypes, i.e., those who eventually convert to AD (cMCI) versus those who do not (MCI). To solve this difficult 4-way classification problem (AD, MCI, cMCI and healthy controls), a competition was hosted by Kaggle to invite the scientific community to apply their machine learning approaches on pre-processed sets of T1-weighted magnetic resonance images (MRI) data and the demographic information from the international Alzheimer's disease neuroimaging initiative (ADNI) database. This paper summarizes our competition results. We first proposed a hierarchical process by turning the 4-way classification into five binary classification problems. A new feature selection technology based on relative importance was also proposed, aiming to identify a more informative and concise subset from 426 sMRI morphometric and 3 demographic features, to ensure each binary classifier to achieve its highest accuracy. As a result, about 2% of the original features were selected to build a new feature space, which can achieve the final four-way classification with a 54.38% accuracy on testing data through hierarchical grouping, higher than several alternative methods in comparison. More importantly, the selected discriminative features such as hippocampal volume, parahippocampal surface area, and medial orbitofrontal thickness, etc. as well as the MMSE score, are reasonable and consistent with those reported in AD/MCI deficits. In summary, the proposed method provides a new framework for multi-way classification using hierarchical grouping and precise feature selection. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of dietary Tenebrio molitor meal inclusion in free-range chickens.

PubMed

Biasato, I; De Marco, M; Rotolo, L; Renna, M; Lussiana, C; Dabbou, S; Capucchio, M T; Biasibetti, E; Costa, P; Gai, F; Pozzo, L; Dezzutto, D; Bergagna, S; Martínez, S; Tarantola, M; Gasco, L; Schiavone, A

2016-12-01

Insects are currently being considered as a novel protein source for animal feeds, because they contain a large amount of protein. The larvae of Tenebrio molitor (TM) have been shown to be an acceptable protein source for broiler chickens in terms of growth performance, but till now, no data on histological or intestinal morphometric features have been reported. This study has had the aim of evaluating the effects of dietary TM inclusion on the performance, welfare, intestinal morphology and histological features of free-range chickens. A total of 140 medium-growing hybrid female chickens were free-range reared and randomly allotted to two dietary treatments: (i) a control group and (ii) a TM group, in which TM meal was included at 75 g/kg. Each group consisted of five pens as replicates, with 14 chicks per pen. Growth performance, haematological and serum parameters and welfare indicators were evaluated, and the animals were slaughtered at the age of 97 days. Two birds per pen (10 birds/treatment) were submitted to histological (liver, spleen, thymus, bursa of Fabricius, kidney, heart, glandular stomach and gut) and morphometric (duodenum, jejunum and ileum) investigations. The inclusion of TM did not affect the growth performance, haematological or serum parameters. The morphometric and histological features were not significantly affected either, thus suggesting no influence on nutrient metabolization, performance or animal health. Glandular stomach alterations (chronic flogosis with epithelial squamous metaplasia) were considered paraphysiological in relation to free-range farming. The observed chronic intestinal flogosis, with concomitant activation of the lymphoid tissue, was probably due to previous parasitic infections, which are very frequently detected in free-range chickens. In conclusion, the findings of this study show that yellow mealworm inclusion does not affect the welfare, productive performances or morphological features of free-range chickens, thus confirming that TM can be used safely in poultry diets. Journal of Animal Physiology and Animal Nutrition © 2016 Blackwell Verlag GmbH.

Repeatability, Reproducibility, Separative Power and Subjectivity of Different Fish Morphometric Analysis Methods

PubMed Central

Takács, Péter

2016-01-01

We compared the repeatability, reproducibility (intra- and inter-measurer similarity), separative power and subjectivity (measurer effect on results) of four morphometric methods frequently used in ichthyological research, the “traditional” caliper-based (TRA) and truss-network (TRU) distance methods and two geometric methods that compare landmark coordinates on the body (GMB) and scales (GMS). In each case, measurements were performed three times by three measurers on the same specimen of three common cyprinid species (roach Rutilus rutilus (Linnaeus, 1758), bleak Alburnus alburnus (Linnaeus, 1758) and Prussian carp Carassius gibelio (Bloch, 1782)) collected from three closely-situated sites in the Lake Balaton catchment (Hungary) in 2014. TRA measurements were made on conserved specimens using a digital caliper, while TRU, GMB and GMS measurements were undertaken on digital images of the bodies and scales. In most cases, intra-measurer repeatability was similar. While all four methods were able to differentiate the source populations, significant differences were observed in their repeatability, reproducibility and subjectivity. GMB displayed highest overall repeatability and reproducibility and was least burdened by measurer effect. While GMS showed similar repeatability to GMB when fish scales had a characteristic shape, it showed significantly lower reproducability (compared with its repeatability) for each species than the other methods. TRU showed similar repeatability as the GMS. TRA was the least applicable method as measurements were obtained from the fish itself, resulting in poor repeatability and reproducibility. Although all four methods showed some degree of subjectivity, TRA was the only method where population-level detachment was entirely overwritten by measurer effect. Based on these results, we recommend a) avoidance of aggregating different measurer’s datasets when using TRA and GMS methods; and b) use of image-based methods for morphometric surveys. Automation of the morphometric workflow would also reduce any measurer effect and eliminate measurement and data-input errors. PMID:27327896

MULTI-SCALE REMOTE SENSING MAPPING OF ANTHROPOGENIC IMPERVIOUS SURFACES: SPATIAL AND TEMPORAL SCALING ISSUES RELATED TO ECOLOGICAL AND HYDROLOGICAL LANDSCAPE ANALYSES

EPA Science Inventory

Anthropogenic impervious surfaces are leading contributors to non-point-source water pollution in urban watersheds. These human-created surfaces include such features as roads, parking lots, rooftops, sideways, and driveways. Aerial photography provides a historical vehicle for...

Discovery of multi-ring basins - Gestalt perception in planetary science

NASA Technical Reports Server (NTRS)

Hartmann, W. K.

1981-01-01

Early selenographers resolved individual structural components of multi-ring basin systems but missed the underlying large-scale multi-ring basin patterns. The recognition of multi-ring basins as a general class of planetary features can be divided into five steps. Gilbert (1893) took a first step in recognizing radial 'sculpture' around the Imbrium basin system. Several writers through the 1940's rediscovered the radial sculpture and extended this concept by describing concentric rings around several circular maria. Some reminiscences are given about the fourth step - discovery of the Orientale basin and other basin systems by rectified lunar photography at the University of Arizona in 1961-62. Multi-ring basins remained a lunar phenomenon until the fifth step - discovery of similar systems of features on other planets, such as Mars (1972), Mercury (1974), and possibly Callisto and Ganymede (1979). This sequence is an example of gestalt recognition whose implications for scientific research are discussed.

A web-system of virtual morphometric globes

NASA Astrophysics Data System (ADS)

Florinsky, Igor; Garov, Andrei; Karachevtseva, Irina

2017-04-01

Virtual globes — programs implementing interactive three-dimensional (3D) models of planets — are increasingly used in geo- and planetary sciences. We develop a web-system of virtual morphometric globes. As the initial data, we used the following global digital elevation models (DEMs): (1) a DEM of the Earth extracted from SRTM30_PLUS database; (2) a DEM of Mars extracted from the Mars Orbiter Laser Altimeter (MOLA) gridded data record archive; and (3) A DEM of the Moon extracted from the Lunar Orbiter Laser Altimeter (LOLA) gridded data record archive. From these DEMs, we derived global digital models of the following 16 local, nonlocal, and combined morphometric variables: horizontal curvature, vertical curvature, mean curvature, Gaussian curvature, minimal curvature, maximal curvature, unsphericity curvature, difference curvature, vertical excess curvature, horizontal excess curvature, ring curvature, accumulation curvature, catchment area, dispersive area, topographic index, and stream power index (definitions, formulae, and interpretations can be found elsewhere [1]). To calculate local morphometric variables, we applied a finite-difference method intended for spheroidal equal angular grids [1]. Digital models of a nonlocal and combined morphometric variables were derived by a method of Martz and de Jong adapted to spheroidal equal angular grids [1]. DEM processing was performed in the software LandLord [1]. The calculated morphometric models were integrated into the testing version of the system. The following main functions are implemented in the system: (1) selection of a celestial body; (2) selection of a morphometric variable; (3) 2D visualization of a calculated global morphometric model (a map in equirectangular projection); (4) 3D visualization of a calculated global morphometric model on the sphere surface (a globe by itself); (5) change of a globe scale (zooming); and (6) globe rotation by an arbitrary angle. The testing version of the system represents morphometric models with the resolution of 15'. In the final version of the system, we plan to implement a multiscale 3D visualization for models of 17 morphometric variables with the resolution from 15' to 30". The web-system of virtual morphometric globes is designed as a separate unit of a 3D web GIS for storage, processing, and access to planetary data [2], which is currently developed as an extension of an existing 2D web GIS (http://cartsrv.mexlab.ru/geoportal). Free, real-time web access to the system of virtual globes will be provided. The testing version of the system is available at: http://cartsrv.mexlab.ru/virtualglobe. The study is supported by the Russian Foundation for Basic Research, grant 15-07-02484. References 1. Florinsky, I.V., 2016. Digital Terrain Analysis in Soil Science and Geology. 2nd ed. Academic Press, Amsterdam, 486 p. 2. Garov, A.S., Karachevtseva, I.P., Matveev, E.V., Zubarev, A.E., and Florinsky, I.V., 2016. Development of a heterogenic distributed environment for spatial data processing using cloud technologies. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 41(B4): 385-390.

Network features of sector indexes spillover effects in China: A multi-scale view

NASA Astrophysics Data System (ADS)

Feng, Sida; Huang, Shupei; Qi, Yabin; Liu, Xueyong; Sun, Qingru; Wen, Shaobo

2018-04-01

The spillover effects among sectors are of concern for distinct market participants, who are in distinct investment horizons and concerned with the information in different time scales. In order to uncover the hidden spillover information in multi-time scales in the rapidly changing stock market and thereby offer guidance to different investors concerning distinct time scales from a system perspective, this paper constructed directional spillover effect networks for the economic sectors in distinct time scales. The results are as follows: (1) The "2-4 days" scale is the most risky scale, and the "8-16 days" scale is the least risky one. (2) The most influential and sensitive sectors are distinct in different time scales. (3) Although two sectors in the same community may not have direct spillover relations, the volatility of one sector will have a relatively strong influence on the other through indirect relations.

Scale invariant texture descriptors for classifying celiac disease

PubMed Central

Hegenbart, Sebastian; Uhl, Andreas; Vécsei, Andreas; Wimmer, Georg

2013-01-01

Scale invariant texture recognition methods are applied for the computer assisted diagnosis of celiac disease. In particular, emphasis is given to techniques enhancing the scale invariance of multi-scale and multi-orientation wavelet transforms and methods based on fractal analysis. After fine-tuning to specific properties of our celiac disease imagery database, which consists of endoscopic images of the duodenum, some scale invariant (and often even viewpoint invariant) methods provide classification results improving the current state of the art. However, not each of the investigated scale invariant methods is applicable successfully to our dataset. Therefore, the scale invariance of the employed approaches is explicitly assessed and it is found that many of the analyzed methods are not as scale invariant as they theoretically should be. Results imply that scale invariance is not a key-feature required for successful classification of our celiac disease dataset. PMID:23481171

Scarp development in the Valles Marineris

NASA Technical Reports Server (NTRS)

Patton, P. C.

1984-01-01

The scarps along the margins of the Vales Marineris display a complex assemblage of forms that have been related to a variety of mass wasting and sapping processes. These scarp segments display variations in the degree of development of spur and gully topography, the number and density of apparent sapping features and the frequency of large scale landslides which reflect the age, geology and processes of slope development throughout the Valles Marineris. This regional analysis should provide more information on the geologic evolution of the Valles Marineris as well as new insight into the relative importance of different processes in the development of the scarp forms. In order to evaluate the regional variation in scarp form and the influence of time and structure on scarp development geomorphic mapping and morphometric analysis of geologically distinct regions of Valles Marineris is being undertaken.

Scaling relationships and concavity of small valley networks on Mars

NASA Astrophysics Data System (ADS)

Penido, Julita C.; Fassett, Caleb I.; Som, Sanjoy M.

2013-01-01

Valley networks are widely interpreted as the preserved erosional record of water flowing across the martian surface. The manner in which valley morphometric properties scale with drainage area has been widely examined on Earth. Earlier studies assessing these properties on Mars have suggested that martian valleys are morphometrically distinct from those on Earth. However, these earlier measurements were generally made on large valley systems because of the limited topographic data available. In this study, we determine the scaling properties of valley networks at smaller scales than have been previously assessed, using digital elevation models from the High Resolution Stereo Camera (HRSC). We find a Hack's law exponent of 0.74, larger than on Earth, and our measurements also reveal that individual small valleys have concave up, concave down, and quasi-linear longitudinal profiles, consistent with earlier studies of dissected terrain on Mars. However, for many valleys, widths are observed to increase downstream similarly to how they scale in terrestrial channels. The similarities and differences between valley networks on Mars and Earth are consistent with the idea that valleys on Mars are comparatively immature, and precipitation was a likely mechanism for delivering water to these networks.

Assessment of bronchial wall thickness and lumen diameter in human adults using multi-detector computed tomography: comparison with theoretical models

PubMed Central

Montaudon, M; Desbarats, P; Berger, P; de Dietrich, G; Marthan, R; Laurent, F

2007-01-01

A thickened bronchial wall is the morphological substratum of most diseases of the airway. Theoretical and clinical models of bronchial morphometry have so far focused on bronchial lumen diameter, and bronchial length and angles, mainly assessed from bronchial casts. However, these models do not provide information on bronchial wall thickness. This paper reports in vivo values of cross-sectional wall area, lumen area, wall thickness and lumen diameter in ten healthy subjects as assessed by multi-detector computed tomography. A validated dedicated software package was used to measure these morphometric parameters up to the 14th bronchial generation, with respect to Weibel's model of bronchial morphometry, and up to the 12th according to Boyden's classification. Measured lumen diameters and homothety ratios were compared with theoretical values obtained from previously published studies, and no difference was found when considering dichotomic division of the bronchial tree. Mean wall area, lumen area, wall thickness and lumen diameter were then provided according to bronchial generation order, and mean homothety ratios were computed for wall area, lumen area and wall thickness as well as equations giving the mean value of each parameter for a given bronchial generation with respect to its value in generation 0 (trachea). Multi-detector computed tomography measurements of bronchial morphometric parameters may help to improve our knowledge of bronchial anatomy in vivo, our understanding of the pathophysiology of bronchial diseases and the evaluation of pharmacological effects on the bronchial wall. PMID:17919291

Right-Scaling Stewardship: A Multi-Scale Perspective on Cooperative Print Management

ERIC Educational Resources Information Center

Malpas, Constance; Lavoie, Brian

2014-01-01

The goal of this report is to provide an empirically-based assessment, based on WorldCat bibliographic and holdings data, of the size, scope, and salient features of these collections, with special attention to identifying and characterizing segments consisting of relatively scarce and relatively widely-held materials. The analysis also employs a…

Visual texture perception via graph-based semi-supervised learning

NASA Astrophysics Data System (ADS)

Zhang, Qin; Dong, Junyu; Zhong, Guoqiang

2018-04-01

Perceptual features, for example direction, contrast and repetitiveness, are important visual factors for human to perceive a texture. However, it needs to perform psychophysical experiment to quantify these perceptual features' scale, which requires a large amount of human labor and time. This paper focuses on the task of obtaining perceptual features' scale of textures by small number of textures with perceptual scales through a rating psychophysical experiment (what we call labeled textures) and a mass of unlabeled textures. This is the scenario that the semi-supervised learning is naturally suitable for. This is meaningful for texture perception research, and really helpful for the perceptual texture database expansion. A graph-based semi-supervised learning method called random multi-graphs, RMG for short, is proposed to deal with this task. We evaluate different kinds of features including LBP, Gabor, and a kind of unsupervised deep features extracted by a PCA-based deep network. The experimental results show that our method can achieve satisfactory effects no matter what kind of texture features are used.

No-Reference Image Quality Assessment by Wide-Perceptual-Domain Scorer Ensemble Method.

PubMed

Liu, Tsung-Jung; Liu, Kuan-Hsien

2018-03-01

A no-reference (NR) learning-based approach to assess image quality is presented in this paper. The devised features are extracted from wide perceptual domains, including brightness, contrast, color, distortion, and texture. These features are used to train a model (scorer) which can predict scores. The scorer selection algorithms are utilized to help simplify the proposed system. In the final stage, the ensemble method is used to combine the prediction results from selected scorers. Two multiple-scale versions of the proposed approach are also presented along with the single-scale one. They turn out to have better performances than the original single-scale method. Because of having features from five different domains at multiple image scales and using the outputs (scores) from selected score prediction models as features for multi-scale or cross-scale fusion (i.e., ensemble), the proposed NR image quality assessment models are robust with respect to more than 24 image distortion types. They also can be used on the evaluation of images with authentic distortions. The extensive experiments on three well-known and representative databases confirm the performance robustness of our proposed model.

Hi-fidelity multi-scale local processing for visually optimized far-infrared Herschel images

NASA Astrophysics Data System (ADS)

Li Causi, G.; Schisano, E.; Liu, S. J.; Molinari, S.; Di Giorgio, A.

2016-07-01

In the context of the "Hi-Gal" multi-band full-plane mapping program for the Galactic Plane, as imaged by the Herschel far-infrared satellite, we have developed a semi-automatic tool which produces high definition, high quality color maps optimized for visual perception of extended features, like bubbles and filaments, against the high background variations. We project the map tiles of three selected bands onto a 3-channel panorama, which spans the central 130 degrees of galactic longitude times 2.8 degrees of galactic latitude, at the pixel scale of 3.2", in cartesian galactic coordinates. Then we process this image piecewise, applying a custom multi-scale local stretching algorithm, enforced by a local multi-scale color balance. Finally, we apply an edge-preserving contrast enhancement to perform an artifact-free details sharpening. Thanks to this tool, we have thus produced a stunning giga-pixel color image of the far-infrared Galactic Plane that we made publicly available with the recent release of the Hi-Gal mosaics and compact source catalog.

Correlation between three-dimensional power Doppler and morphometric measurement of endometrial vascularity at the time of embryo implantation in women with unexplained recurrent miscarriage.

PubMed

Chen, Xiaoyan; Saravelos, Sotirios H; Liu, Yingyu; Huang, Jin; Wang, Chi Chiu; Li, Tin Chiu

2017-06-01

Power Doppler in combination with three-dimensional (3D-PD) ultrasonography has been used as a noninvasive tool to evaluate the vascularity. However, it is unclear whether 3D-PD can accurately reflect endometrial vascularization and replace the invasive endometrial biopsy. This study aims to investigate the correlation between 3D-PD and micro vessel morphometric measurement of endometrial vascularity. Twenty-five women with unexplained recurrent miscarriage were recruited for 3D-PD and endometrial biopsy on precisely day LH + 7. Immunohistochemistry using vWF was employed to identify micro vessels in endometrial biopsy specimens followed by the use of morphometric technique to measure the mean vessel diameter and volume fractions. The vascularization index (VI), flow index (FI) and vascularization flow index (VFI) assessed by 3D-PD were calculated for both the endometrial and sub-endometrial regions. There were no significant correlations between any of the ultrasonographic measurements (endometrial thickness, endometrial volume, endometrial VI/FI/VFI, sub-endometrial volume, sub-endometrial VI/FI/VFI) and morphometric features (number of micro vessel, mean diameter of micro vessel and volume fraction measurement of vessel). This study indicates that endometrial vascularity assessed by 3D-PD could not be used to reflect changes in micro vessels of the endometrium at the time of embryo implantation in women with unexplained recurrent miscarriage.

Hydrological inferences through morphometric analysis of lower Kosi river basin of India for water resource management based on remote sensing data

NASA Astrophysics Data System (ADS)

Rai, Praveen Kumar; Chandel, Rajeev Singh; Mishra, Varun Narayan; Singh, Prafull

2018-03-01

Satellite based remote sensing technology has proven to be an effectual tool in analysis of drainage networks, study of surface morphological features and their correlation with groundwater management prospect at basin level. The present study highlights the effectiveness and advantage of remote sensing and GIS-based analysis for quantitative and qualitative assessment of flood plain region of lower Kosi river basin based on morphometric analysis. In this study, ASTER DEM is used to extract the vital hydrological parameters of lower Kosi river basin in ARC GIS software. Morphometric parameters, e.g., stream order, stream length, bifurcation ratio, drainage density, drainage frequency, drainage texture, form factor, circularity ratio, elongation ratio, etc., have been calculated for the Kosi basin and their hydrological inferences were discussed. Most of the morphometric parameters such as bifurcation ratio, drainage density, drainage frequency, drainage texture concluded that basin has good prospect for water management program for various purposes and also generated data base that can provide scientific information for site selection of water-harvesting structures and flood management activities in the basin. Land use land cover (LULC) of the basin were also prepared from Landsat data of 2005, 2010 and 2015 to assess the change in dynamic of the basin and these layers are very noteworthy for further watershed prioritization.

Flexure in the Corinth rift: reconciling marine terraces, rivers, offshore data and fault modeling

NASA Astrophysics Data System (ADS)

de Gelder, G.; Fernández-Blanco, D.; Jara-Muñoz, J.; Melnick, D.; Duclaux, G.; Bell, R. E.; Lacassin, R.; Armijo, R.

2016-12-01

The Corinth rift (Greece) is an exceptional area to study the large-scale mechanics of a young rift system, due to its extremely high extension rates and fault slip rates. Late Pleistocene activity of large normal faults has created a mostly asymmetric E-W trending graben, mainly driven by N-dipping faults that shape the southern margin of the Corinth Gulf. Flexural footwall uplift of these faults is evidenced by Late Pleistocene coastal fan deltas that are presently up to 1700m in elevation, a drainage reversal of some major river systems, and flights of marine terraces that have been uplifted along the southern margin of the Gulf. To improve constraints on this footwall uplift, we analysed the extensive terrace sequence between Xylokastro and Corinth - uplifted by the Xylokastro Fault - using 2m-resolution digital surface models developed from Pleiades satellite imagery (acquired through the Isis and Tosca programs of the French CNES). We refined and improved the spatial uplift pattern and age correlation of these terraces, through a detailed analysis of the shoreline angles using the graphical interface TerraceM, and 2D numerical modeling of terrace formation. We combine the detailed record of flexure provided by this analysis with a morphometric analysis of the major river systems along the southern shore, obtaining constraints of footwall uplift on a longer time scale and larger spatial scale. Flexural subsidence of the hanging wall is evidenced by offshore seismic sections, for which we depth-converted a multi-channel seismic section north of the Xylokastro Fault. We use the full profile of the fault geometry and its associated deformation pattern as constraints to reproduce the long-term flexural wavelength and uplift/subsidence ratio through fault modeling. Using PyLith, an open-source finite element code for quasi-static viscoelastic simulations, we find that a steep-dipping planar fault to the brittle-ductile transition provides the best fit to reproduce the observed deformation pattern on- and offshore. The combined results of this study allow us to compare flexural normal faulting on different scales, and recorded in different elements of the Corinth rift, allowing us to put forward a comprehensive discussion on the deformation mechanisms and the mechanical behavior of this crustal scale feature.

Three new stingrays (Myliobatiformes: Dasyatidae) from the Indo-West Pacific.

PubMed

Last, Peter R; White, William T; Naylor, Gavin

2016-08-05

Three undescribed stingrays were discovered as part of a broader revision of the family Dasyatidae that formed part of the Chondrichthyan Tree of Life project. This research forms part of a sequence of papers on rays aimed at describing unnamed species for inclusion in a multi-authored guide to rays of the world. The first part of this series focused on a redefinition of genera of the family Dasyatidae. The new Indo-West Pacific taxa are represented by separate genera from three dasyatid subfamilies: Himantura australis sp. nov. (northern Australia and Papua New Guinea), Taeniura lessoni sp. nov. (Melanesia) and Telatrygon biasa sp. nov. (Indo-Malay Archipelago). Himantura australis sp. nov., which belongs to a complex of four closely related reticulate whiprays, differs subtly from its congeners in coloration, morphometrics and distribution. Taeniura lessoni sp. nov. is the second species in a genus containing the widely-distributed T. lymma, which is possibly the most abundant stingray in shallow coral-reef habitats of the Indo-Pacific, with the new species apparently restricted to Melanesia. Taeniura lessoni sp. nov. is distinguishable by the absence of a distinctive pair of vivid blue longitudinal stripes on the dorsolateral edges of the tail which is one of the most distinctive features of T. lymma. Telatrygon biasa sp. nov. belongs to a small, recently designated genus of stingrays represented by four species in the tropical Indo-West Pacific. Telatrygon biasa sp. nov. differs from these species in morphometrics. The new species differs markedly from T. zugei in its NADH2 sequence. Telatrygon crozieri is resurrected as a valid northern Indian Ocean representative of the T. zugei complex.

Morphometric analysis with open source software to explore shallow hydrogeological features in Senegal and Guinea

NASA Astrophysics Data System (ADS)

Fussi, Fabio; Di Leo, Margherita; Bonomi, Tullia; Di Mauro, Biagio; Fava, Francesco; Fumagalli, Letizia; Hamidou Kane, Cheikh; Faye, Gayane; Niang, Magatte; Wade, Souleye; Hamidou, Barry; Colombo, Roberto

2015-04-01

Water represents a vital resource for everyone on this Planet, but, for some populations, the access to potable water is not given for granted. Recently, the interest in low cost technical solutions to improve access to ground water in developing countries, especially for people located in remote areas, has increased. Manual drilling (techniques to drill boreholes for water using human or animal power) is well known and practiced for centuries in many countries and represents a valid alternative to increase water access. Lately, this practice has raised the attention of national governments and international organizations. This technique is applicable only where hydrogeological conditions are suitable, namely in presence of thick layers of unconsolidated sediments and a shallow water table Aim of this study is exploring the potential of morphometric analysis to improve the methodology to identify areas with suitable hydrogeological conditions for manual drilling, supporting the implementation of water supply programs that can have great impact on living condition of the population. The characteristics of shallow geological layers are strongly dependent from geomorphological processes and are usually reflected in the morphological characteristics of landforms. Under these hypotheses, we have been investigating the geo-statistical correlation between several morphometric variables and a set of hydrogeological variables used in the estimation of suitability for manual drilling: thickness of unconsolidated sediments, texture, hydraulic conductivity of shallow aquifer, depth of water table. The morphology of two study areas with different landscape characteristics in Guinea and Senegal has been investigated coupling the Free and Open Source Software GRASS GIS and R. Several morphometric parameters have been extracted from ASTER GDEM digital elevation model, and have been compared with a set of hydrogeological characteristics obtained from semi-automatic analysis of stratigraphic logs from water boreholes. We observed the relationships between the spatial distribution of hydrogeological features and the morphology, applying multivariate statistical analysis. The ultimate goal of this study is to infer hydrogeological information of shallow aquifers, exploiting morphometric parameters (together with other layers of information from existing thematic maps and remote sensing) and to reconstruct the geometry and the characteristic of shallow porous aquifer. This research is part of a larger project financed by NERC (National Environment Research Council, UK) in the framework of the program UPGRO (Unlocking the Potential of Groundwater for the Poors), with the collaboration of different partners from Italy, Senegal and Guinea

A semi-automatic method for analysis of landscape elements using Shuttle Radar Topography Mission and Landsat ETM+ data

NASA Astrophysics Data System (ADS)

Ehsani, Amir Houshang; Quiel, Friedrich

2009-02-01

In this paper, we demonstrate artificial neural networks—self-organizing map (SOM)—as a semi-automatic method for extraction and analysis of landscape elements in the man and biosphere reserve "Eastern Carpathians". The Shuttle Radar Topography Mission (SRTM) collected data to produce generally available digital elevation models (DEM). Together with Landsat Thematic Mapper data, this provides a unique, consistent and nearly worldwide data set. To integrate the DEM with Landsat data, it was re-projected from geographic coordinates to UTM with 28.5 m spatial resolution using cubic convolution interpolation. To provide quantitative morphometric parameters, first-order (slope) and second-order derivatives of the DEM—minimum curvature, maximum curvature and cross-sectional curvature—were calculated by fitting a bivariate quadratic surface with a window size of 9×9 pixels. These surface curvatures are strongly related to landform features and geomorphological processes. Four morphometric parameters and seven Landsat-enhanced thematic mapper (ETM+) bands were used as input for the SOM algorithm. Once the network weights have been randomly initialized, different learning parameter sets, e.g. initial radius, final radius and number of iterations, were investigated. An optimal SOM with 20 classes using 1000 iterations and a final neighborhood radius of 0.05 provided a low average quantization error of 0.3394 and was used for further analysis. The effect of randomization of initial weights for optimal SOM was also studied. Feature space analysis, three-dimensional inspection and auxiliary data facilitated the assignment of semantic meaning to the output classes in terms of landform, based on morphometric analysis, and land use, based on spectral properties. Results were displayed as thematic map of landscape elements according to form, cover and slope. Spectral and morphometric signature analysis with corresponding zoom samples superimposed by contour lines were compared in detail to clarify the role of morphometric parameters to separate landscape elements. The results revealed the efficiency of SOM to integrate SRTM and Landsat data in landscape analysis. Despite the stochastic nature of SOM, the results in this particular study are not sensitive to randomization of initial weight vectors if many iterations are used. This procedure is reproducible for the same application with consistent results.

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

PubMed

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

Multi-scale Visualization of Molecular Architecture Using Real-Time Ambient Occlusion in Sculptor.

PubMed

Wahle, Manuel; Wriggers, Willy

2015-10-01

The modeling of large biomolecular assemblies relies on an efficient rendering of their hierarchical architecture across a wide range of spatial level of detail. We describe a paradigm shift currently under way in computer graphics towards the use of more realistic global illumination models, and we apply the so-called ambient occlusion approach to our open-source multi-scale modeling program, Sculptor. While there are many other higher quality global illumination approaches going all the way up to full GPU-accelerated ray tracing, they do not provide size-specificity of the features they shade. Ambient occlusion is an aspect of global lighting that offers great visual benefits and powerful user customization. By estimating how other molecular shape features affect the reception of light at some surface point, it effectively simulates indirect shadowing. This effect occurs between molecular surfaces that are close to each other, or in pockets such as protein or ligand binding sites. By adding ambient occlusion, large macromolecular systems look much more natural, and the perception of characteristic surface features is strongly enhanced. In this work, we present a real-time implementation of screen space ambient occlusion that delivers realistic cues about tunable spatial scale characteristics of macromolecular architecture. Heretofore, the visualization of large biomolecular systems, comprising e.g. hundreds of thousands of atoms or Mega-Dalton size electron microscopy maps, did not take into account the length scales of interest or the spatial resolution of the data. Our approach has been uniquely customized with shading that is tuned for pockets and cavities of a user-defined size, making it useful for visualizing molecular features at multiple scales of interest. This is a feature that none of the conventional ambient occlusion approaches provide. Actual Sculptor screen shots illustrate how our implementation supports the size-dependent rendering of molecular surface features.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

NASA Astrophysics Data System (ADS)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

Phenotypes of intermediate forms of Fasciola hepatica and F. gigantica in buffaloes from Central Punjab, Pakistan.

PubMed

Afshan, K; Valero, M A; Qayyum, M; Peixoto, R V; Magraner, A; Mas-Coma, S

2014-12-01

Fascioliasis is an important food-borne parasitic disease caused by the two trematode species, Fasciola hepatica and Fasciola gigantica. The phenotypic features of fasciolid adults and eggs infecting buffaloes inhabiting the Central Punjab area, Pakistan, have been studied to characterize fasciolid populations involved. Morphometric analyses were made with a computer image analysis system (CIAS) applied on the basis of standardized measurements. Since it is the first study of this kind undertaken in Pakistan, the results are compared to pure fasciolid populations: (a) F. hepatica from the European Mediterranean area; and (b) F. gigantica from Burkina Faso; i.e. geographical areas where both species do not co-exist. Only parasites obtained from bovines were used. The multivariate analysis showed that the characteristics, including egg morphometrics, of fasciolids from Central Punjab, Pakistan, are between F. hepatica and F. gigantica standard populations. Similarly, the morphometric measurements of fasciolid eggs from Central Punjab are also between F. hepatica and F. gigantica standard populations. These results demonstrate the existence of fasciolid intermediate forms in endemic areas in Pakistan.

Scale Interactions in the Tropics from a Simple Multi-Cloud Model

NASA Astrophysics Data System (ADS)

Niu, X.; Biello, J. A.

2017-12-01

Our lack of a complete understanding of the interaction between the moisture convection and equatorial waves remains an impediment in the numerical simulation of large-scale organization, such as the Madden-Julian Oscillation (MJO). The aim of this project is to understand interactions across spatial scales in the tropics from a simplified framework for scale interactions while a using a simplified framework to describe the basic features of moist convection. Using multiple asymptotic scales, Biello and Majda[1] derived a multi-scale model of moist tropical dynamics (IMMD[1]), which separates three regimes: the planetary scale climatology, the synoptic scale waves, and the planetary scale anomalies regime. The scales and strength of the observed MJO would categorize it in the regime of planetary scale anomalies - which themselves are forced from non-linear upscale fluxes from the synoptic scales waves. In order to close this model and determine whether it provides a self-consistent theory of the MJO. A model for diabatic heating due to moist convection must be implemented along with the IMMD. The multi-cloud parameterization is a model proposed by Khouider and Majda[2] to describe the three basic cloud types (congestus, deep and stratiform) that are most responsible for tropical diabatic heating. We implement a simplified version of the multi-cloud model that is based on results derived from large eddy simulations of convection [3]. We present this simplified multi-cloud model and show results of numerical experiments beginning with a variety of convective forcing states. Preliminary results on upscale fluxes, from synoptic scales to planetary scale anomalies, will be presented. [1] Biello J A, Majda A J. Intraseasonal multi-scale moist dynamics of the tropical atmosphere[J]. Communications in Mathematical Sciences, 2010, 8(2): 519-540. [2] Khouider B, Majda A J. A simple multicloud parameterization for convectively coupled tropical waves. Part I: Linear analysis[J]. Journal of the atmospheric sciences, 2006, 63(4): 1308-1323. [3] Dorrestijn J, Crommelin D T, Biello J A, et al. A data-driven multi-cloud model for stochastic parametrization of deep convection[J]. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 2013, 371(1991): 20120374.

Aneurysms of the anterior and posterior cerebral circulation: comparison of the morphometric features.

PubMed

Tykocki, Tomasz; Kostkiewicz, Bogusław

2014-09-01

Intracranial aneurysms (IAs) located in the posterior circulation are considered to have higher annual bleed rates than those in the anterior circulation. The aim of the study was to compare the morphometric factors differentiating between IAs located in the anterior and posterior cerebral circulation. A total number of 254 IAs diagnosed between 2009 and 2012 were retrospectively analyzed. All patients qualified for diagnostic, three-dimensional rotational angiography. IAs were assigned to either the anterior or posterior cerebral circulation subsets for the analysis. Means were compared with a t-test. The univariate and stepwise logistic regression analyses were used to determine the predictors of morphometric differences between the groups. For the defined predictors, ROC (receiver-operating characteristic) curves and interactive dot diagrams were calculated with the cutoff values of the morphometric factors. The number of anterior cerebral circulation IAs was 179 (70.5 %); 141 (55.5 %) aneurysms were ruptured. Significant differences between anterior and posterior circulation IAs were found for: the parent artery size (5.08 ± 1.8 mm vs. 3.95 ± 1.5 mm; p < 0.05), size ratio (2.22 ± 0.9 vs. 3.19 ± 1.8; p < 0.045) and aspect ratio (AR) (1.91 ± 0.8 vs. 2.75 ± 1.8; p = 0.02). Predicting factors differentiating anterior and posterior circulation IAs were: the AR (OR = 2.20; 95 % CI 1.80-270; Is 270 correct or should it be 2.70 and parent artery size (OR = 0.44; 95 % CI 0.38-0.54). The cutoff point in the ROC curve was 2.185 for the AR and 4.89 mm for parent artery size. Aspect ratio and parent artery size were found to be predictive morphometric factors in differentiating between anterior and posterior cerebral IAs.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

A numerical multi-scale model to predict macroscopic material anisotropy of multi-phase steels from crystal plasticity material definitions

NASA Astrophysics Data System (ADS)

Ravi, Sathish Kumar; Gawad, Jerzy; Seefeldt, Marc; Van Bael, Albert; Roose, Dirk

2017-10-01

A numerical multi-scale model is being developed to predict the anisotropic macroscopic material response of multi-phase steel. The embedded microstructure is given by a meso-scale Representative Volume Element (RVE), which holds the most relevant features like phase distribution, grain orientation, morphology etc., in sufficient detail to describe the multi-phase behavior of the material. A Finite Element (FE) mesh of the RVE is constructed using statistical information from individual phases such as grain size distribution and ODF. The material response of the RVE is obtained for selected loading/deformation modes through numerical FE simulations in Abaqus. For the elasto-plastic response of the individual grains, single crystal plasticity based plastic potential functions are proposed as Abaqus material definitions. The plastic potential functions are derived using the Facet method for individual phases in the microstructure at the level of single grains. The proposed method is a new modeling framework and the results presented in terms of macroscopic flow curves are based on the building blocks of the approach, while the model would eventually facilitate the construction of an anisotropic yield locus of the underlying multi-phase microstructure derived from a crystal plasticity based framework.

Stream network analysis and geomorphic flood plain mapping from orbital and suborbital remote sensing imagery application to flood hazard studies in central Texas

NASA Technical Reports Server (NTRS)

Baker, V. R. (Principal Investigator); Holz, R. K.; Hulke, S. D.; Patton, P. C.; Penteado, M. M.

1975-01-01

The author has identified the following significant results. Development of a quantitative hydrogeomorphic approach to flood hazard evaluation was hindered by (1) problems of resolution and definition of the morphometric parameters which have hydrologic significance, and (2) mechanical difficulties in creating the necessary volume of data for meaningful analysis. Measures of network resolution such as drainage density and basin Shreve magnitude indicated that large scale topographic maps offered greater resolution than small scale suborbital imagery and orbital imagery. The disparity in network resolution capabilities between orbital and suborbital imagery formats depends on factors such as rock type, vegetation, and land use. The problem of morphometric data analysis was approached by developing a computer-assisted method for network analysis. The system allows rapid identification of network properties which can then be related to measures of flood response.

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

NASA Astrophysics Data System (ADS)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Pattern recognition invariant under changes of scale and orientation

NASA Astrophysics Data System (ADS)

Arsenault, Henri H.; Parent, Sebastien; Moisan, Sylvain

1997-08-01

We have used a modified method proposed by neiberg and Casasent to successfully classify five kinds of military vehicles. The method uses a wedge filter to achieve scale invariance, and lines in a multi-dimensional feature space correspond to each target with out-of-plane orientations over 360 degrees around a vertical axis. The images were not binarized, but were filtered in a preprocessing step to reduce aliasing. The feature vectors were normalized and orthogonalized by means of a neural network. Out-of-plane rotations of 360 degrees and scale changes of a factor of four were considered. Error-free classification was achieved.

Impact of materials engineering on edge placement error (Conference Presentation)

NASA Astrophysics Data System (ADS)

Freed, Regina; Mitra, Uday; Zhang, Ying

2017-04-01

Transistor scaling has transitioned from wavelength scaling to multi-patterning techniques, due to the resolution limits of immersion of immersion lithography. Deposition and etch have enabled scaling in the by means of SADP and SAQP. Spacer based patterning enables extremely small linewidths, sufficient for several future generations of transistors. However, aligning layers in Z-direction, as well as aligning cut and via patterning layers, is becoming a road-block due to global and local feature variation and fidelity. This presentation will highlight the impact of deposition and etch on this feature alignment (EPE) and illustrate potential paths toward lowering EPE using material engineering.

Engineering design of sub-micron topographies for simultaneously adherent and reflective metal-polymer interfaces

NASA Technical Reports Server (NTRS)

Brown, Christopher A.

1993-01-01

The approach of the project is to base the design of multi-function, reflective topographies on the theory that topographically dependent phenomena react with surfaces and interfaces at certain scales. The first phase of the project emphasizes the development of methods for understanding the sizes of topographic features which influence reflectivity. Subsequent phases, if necessary, will address the scales of interaction for adhesion and manufacturing processes. A simulation of the interaction of electromagnetic radiation, or light, with a reflective surface is performed using specialized software. Reflectivity of the surface as a function of scale is evaluated and the results from the simulation are compared with reflectivity measurements made on multi-function, reflective surfaces.

Partial polygon pruning of hydrographic features in automated generalization

USGS Publications Warehouse

Stum, Alexander K.; Buttenfield, Barbara P.; Stanislawski, Larry V.

2017-01-01

This paper demonstrates a working method to automatically detect and prune portions of waterbody polygons to support creation of a multi-scale hydrographic database. Water features are known to be sensitive to scale change; and thus multiple representations are required to maintain visual and geographic logic at smaller scales. Partial pruning of polygonal features—such as long and sinuous reservoir arms, stream channels that are too narrow at the target scale, and islands that begin to coalesce—entails concurrent management of the length and width of polygonal features as well as integrating pruned polygons with other generalized point and linear hydrographic features to maintain stream network connectivity. The implementation follows data representation standards developed by the U.S. Geological Survey (USGS) for the National Hydrography Dataset (NHD). Portions of polygonal rivers, streams, and canals are automatically characterized for width, length, and connectivity. This paper describes an algorithm for automatic detection and subsequent processing, and shows results for a sample of NHD subbasins in different landscape conditions in the United States.

Analysis of Morphological Features of Benign and Malignant Breast Cell Extracted From FNAC Microscopic Image Using the Pearsonian System of Curves.

PubMed

Rajbongshi, Nijara; Bora, Kangkana; Nath, Dilip C; Das, Anup K; Mahanta, Lipi B

2018-01-01

Cytological changes in terms of shape and size of nuclei are some of the common morphometric features to study breast cancer, which can be observed by careful screening of fine needle aspiration cytology (FNAC) images. This study attempts to categorize a collection of FNAC microscopic images into benign and malignant classes based on family of probability distribution using some morphometric features of cell nuclei. For this study, features namely area, perimeter, eccentricity, compactness, and circularity of cell nuclei were extracted from FNAC images of both benign and malignant samples using an image processing technique. All experiments were performed on a generated FNAC image database containing 564 malignant (cancerous) and 693 benign (noncancerous) cell level images. The five-set extracted features were reduced to three-set (area, perimeter, and circularity) based on the mean statistic. Finally, the data were fitted to the generalized Pearsonian system of frequency curve, so that the resulting distribution can be used as a statistical model. Pearsonian system is a family of distributions where kappa (κ) is the selection criteria computed as functions of the first four central moments. For the benign group, kappa (κ) corresponding to area, perimeter, and circularity was -0.00004, 0.0000, and 0.04155 and for malignant group it was 1016942, 0.01464, and -0.3213, respectively. Thus, the family of distribution related to these features for the benign and malignant group were different, and therefore, characterization of their probability curve will also be different.

A 3D convolutional neural network approach to land cover classification using LiDAR and multi-temporal Landsat imagery

NASA Astrophysics Data System (ADS)

Xu, Z.; Guan, K.; Peng, B.; Casler, N. P.; Wang, S. W.

2017-12-01

Landscape has complex three-dimensional features. These 3D features are difficult to extract using conventional methods. Small-footprint LiDAR provides an ideal way for capturing these features. Existing approaches, however, have been relegated to raster or metric-based (two-dimensional) feature extraction from the upper or bottom layer, and thus are not suitable for resolving morphological and intensity features that could be important to fine-scale land cover mapping. Therefore, this research combines airborne LiDAR and multi-temporal Landsat imagery to classify land cover types of Williamson County, Illinois that has diverse and mixed landscape features. Specifically, we applied a 3D convolutional neural network (CNN) method to extract features from LiDAR point clouds by (1) creating occupancy grid, intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into a 3D CNN feature extractor for many epochs of learning. The learned features (e.g., morphological features, intensity features, etc) were combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. We used photo interpretation for training and testing data generation. The classification results show that our approach outperforms traditional methods using LiDAR derived feature maps, and promises to serve as an effective methodology for creating high-quality land cover maps through fusion of complementary types of remote sensing data.

Morphometric Analysis to Prioritize Sub-Watershed for Flood Risk Assessment in Central Karakoram National Park Using Gis/rs Approach

NASA Astrophysics Data System (ADS)

Syed, N. H.; Rehman, A. A.; Hussain, D.; Ishaq, S.; Khan, A. A.

2017-11-01

Morphometric analysis is vital for any watershed investigation and it is inevitable for flood risk assessment in sub-watershed basins. Present study undertaken to carry out critical evaluation and assessment of sub watershed morphological parameters for flood risk assessment of Central Karakorum National Park (CKNP), where Geographical information system and remote sensing (GIS & RS) approach used for quantifying the parameter and mapping of sub watershed units. ASTER DEM used as a geo-spatial data for watershed delineation and stream network. Morphometric analysis carried out using spatial analyst tool of ArcGIS 10.2. The parameters included were bifurcation ratio (Rb), Drainage Texture (Rt), Circulatory ratio (Rc), Elongated ratio (Re), Drainage density (Dd), Stream Length (Lu), Stream order (Su), Slope and Basin length (Lb) have calculated separately. The analysis revealed that the stream order varies from order 1 to 6 and the total numbers of stream segments of all orders were 52. Multi criteria analysis process used to calculate the risk factor. As an accomplished result, map of sub watershed prioritization developed using weighted standardized risk factor. These results helped to understand sensitivity of flush floods in different sub watersheds of the study area and leaded to better management of the mountainous regions in prospect of flush floods.

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Large area sub-micron chemical imaging of magnesium in sea urchin teeth.

PubMed

Masic, Admir; Weaver, James C

2015-03-01

The heterogeneous and site-specific incorporation of inorganic ions can profoundly influence the local mechanical properties of damage tolerant biological composites. Using the sea urchin tooth as a research model, we describe a multi-technique approach to spatially map the distribution of magnesium in this complex multiphase system. Through the combined use of 16-bit backscattered scanning electron microscopy, multi-channel energy dispersive spectroscopy elemental mapping, and diffraction-limited confocal Raman spectroscopy, we demonstrate a new set of high throughput, multi-spectral, high resolution methods for the large scale characterization of mineralized biological materials. In addition, instrument hardware and data collection protocols can be modified such that several of these measurements can be performed on irregularly shaped samples with complex surface geometries and without the need for extensive sample preparation. Using these approaches, in conjunction with whole animal micro-computed tomography studies, we have been able to spatially resolve micron and sub-micron structural features across macroscopic length scales on entire urchin tooth cross-sections and correlate these complex morphological features with local variability in elemental composition. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

Clastic polygonal networks around Lyot crater, Mars: Possible formation mechanisms from morphometric analysis

NASA Astrophysics Data System (ADS)

Brooker, L. M.; Balme, M. R.; Conway, S. J.; Hagermann, A.; Barrett, A. M.; Collins, G. S.; Soare, R. J.

2018-03-01

Polygonal networks of patterned ground are a common feature in cold-climate environments. They can form through the thermal contraction of ice-cemented sediment (i.e. formed from fractures), or the freezing and thawing of ground ice (i.e. formed by patterns of clasts, or ground deformation). The characteristics of these landforms provide information about environmental conditions. Analogous polygonal forms have been observed on Mars leading to inferences about environmental conditions. We have identified clastic polygonal features located around Lyot crater, Mars (50°N, 30°E). These polygons are unusually large (>100 m diameter) compared to terrestrial clastic polygons, and contain very large clasts, some of which are up to 15 metres in diameter. The polygons are distributed in a wide arc around the eastern side of Lyot crater, at a consistent distance from the crater rim. Using high-resolution imaging data, we digitised these features to extract morphological information. These data are compared to existing terrestrial and Martian polygon data to look for similarities and differences and to inform hypotheses concerning possible formation mechanisms. Our results show the clastic polygons do not have any morphometric features that indicate they are similar to terrestrial sorted, clastic polygons formed by freeze-thaw processes. They are too large, do not show the expected variation in form with slope, and have clasts that do not scale in size with polygon diameter. However, the clastic networks are similar in network morphology to thermal contraction cracks, and there is a potential direct Martian analogue in a sub-type of thermal contraction polygons located in Utopia Planitia. Based upon our observations, we reject the hypothesis that polygons located around Lyot formed as freeze-thaw polygons and instead an alternative mechanism is put forward: they result from the infilling of earlier thermal contraction cracks by wind-blown material, which then became compressed and/or cemented resulting in a resistant fill. Erosion then leads to preservation of these polygons in positive relief, while later weathering results in the fracturing of the fill material to form angular clasts. These results suggest that there was an extensive area of ice-rich terrain, the extent of which is linked to ejecta from Lyot crater.

A New Method for Automated Identification and Morphometry of Myelinated Fibers Through Light Microscopy Image Analysis.

PubMed

Novas, Romulo Bourget; Fazan, Valeria Paula Sassoli; Felipe, Joaquim Cezar

2016-02-01

Nerve morphometry is known to produce relevant information for the evaluation of several phenomena, such as nerve repair, regeneration, implant, transplant, aging, and different human neuropathies. Manual morphometry is laborious, tedious, time consuming, and subject to many sources of error. Therefore, in this paper, we propose a new method for the automated morphometry of myelinated fibers in cross-section light microscopy images. Images from the recurrent laryngeal nerve of adult rats and the vestibulocochlear nerve of adult guinea pigs were used herein. The proposed pipeline for fiber segmentation is based on the techniques of competitive clustering and concavity analysis. The evaluation of the proposed method for segmentation of images was done by comparing the automatic segmentation with the manual segmentation. To further evaluate the proposed method considering morphometric features extracted from the segmented images, the distributions of these features were tested for statistical significant difference. The method achieved a high overall sensitivity and very low false-positive rates per image. We detect no statistical difference between the distribution of the features extracted from the manual and the pipeline segmentations. The method presented a good overall performance, showing widespread potential in experimental and clinical settings allowing large-scale image analysis and, thus, leading to more reliable results.

How High is that Dune? A Comparison of Methods Used to Constrain the Morphometry of Aeolian Bedforms on Mars

NASA Technical Reports Server (NTRS)

Bourke, M.; Balme, M.; Beyer, R. A.; Williams, K. K.

2004-01-01

Methods traditionally used to estimate the relative height of surface features on Mars include: photoclinometry, shadow length and stereography. The MOLA data set enables a more accurate assessment of the surface topography of Mars. However, many small-scale aeolian bedforms remain below the sample resolution of the MOLA data set. In response to this a number of research teams have adopted and refined existing methods and applied them to high resolution (2-6 m/pixel) narrow angle MOC satellite images. Collectively, the methods provide data on a range of morphometric parameters (many not previously available for dunes on Mars). These include dune height, width, length, surface area, volume, longitudinal and cross profiles). This data will facilitate a more accurate analysis of aeolian bedforms on Mars. In this paper we undertake a comparative analysis of methods used to determine the height of aeolian dunes and ripples.

The Ecology, Biogeochemistry, and Optical Properties of Coccolithophores

NASA Astrophysics Data System (ADS)

Balch, William M.

2018-01-01

Coccolithophores are major contributors to phytoplankton communities and ocean biogeochemistry and are strong modulators of the optical field in the sea. New discoveries are changing paradigms about these calcifiers. A new role for silicon in coccolithophore calcification is coupling carbonate and silicon cycles. Phosphorus and iron play key roles in regulating coccolithophore growth. Comparing molecular phylogenies with coccolith morphometrics is forcing the reconciliation of biological and geological observations. Mixotrophy may be a possible life strategy for deep-dwelling species, which has ramifications for biological pump and alkalinity pump paradigms. Climate, ocean temperatures, and pH appear to be affecting coccolithophores in unexpected ways. Global calcification is approximately 1-3% of primary productivity and affects CO2 budgets. New measurements of the backscattering cross section of coccolithophores have improved satellite-based algorithms and their application in case I and case II optical waters. Remote sensing has allowed the detection of basin-scale coccolithophore features in the Southern Ocean.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Off the scale: a new species of fish-scale gecko (Squamata: Gekkonidae: Geckolepis) with exceptionally large scales

PubMed Central

Daza, Juan D.; Köhler, Jörn; Vences, Miguel; Glaw, Frank

2017-01-01

The gecko genus Geckolepis, endemic to Madagascar and the Comoro archipelago, is taxonomically challenging. One reason is its members ability to autotomize a large portion of their scales when grasped or touched, most likely to escape predation. Based on an integrative taxonomic approach including external morphology, morphometrics, genetics, pholidosis, and osteology, we here describe the first new species from this genus in 75 years: Geckolepis megalepis sp. nov. from the limestone karst of Ankarana in northern Madagascar. The new species has the largest known body scales of any gecko (both relatively and absolutely), which come off with exceptional ease. We provide a detailed description of the skeleton of the genus Geckolepis based on micro-Computed Tomography (micro-CT) analysis of the new species, the holotype of G. maculata, the recently resurrected G. humbloti, and a specimen belonging to an operational taxonomic unit (OTU) recently suggested to represent G. maculata. Geckolepis is characterized by highly mineralized, imbricated scales, paired frontals, and unfused subolfactory processes of the frontals, among other features. We identify diagnostic characters in the osteology of these geckos that help define our new species and show that the OTU assigned to G. maculata is probably not conspecific with it, leaving the taxonomic identity of this species unclear. We discuss possible reasons for the extremely enlarged scales of G. megalepis in the context of an anti-predator defence mechanism, and the future of Geckolepis taxonomy. PMID:28194313

Morphometrics applied to medical entomology.

PubMed

Dujardin, Jean-Pierre

2008-12-01

Morphometrics underwent a revolution more than one decade ago. In the modern morphometrics, the estimate of size is now contained in a single variable reflecting variation in many directions, as many as there are landmarks under study, and shape is defined as their relative positions after correcting for size, position and orientation. With these informative data, and the corresponding software freely available to conduct complex analyses, significant biological and epidemiological features can be quantified more accurately. We discuss the evolutionary significance of the environmental impact on metric variability, mentioning the importance of concepts like genetic assimilation, genetic accommodation, and epigenetics. We provide examples of measuring the effect of selection on metric variation by comparing (unpublished) Qst values with corresponding (published) Fst. The primary needs of medical entomologists are to distinguish species, especially cryptic species, and to detect them where they are not expected. We explain how geometric morphometrics could apply to these questions, and where there are deficiencies preventing the approach from being utilized at its maximum potential. Medical entomologists in connection with control programs aim to identify isolated populations where the risk of reinfestation after treatment would be low ("biogeographical islands"). Identifying them can be obtained from estimating the number of migrants per generation. Direct assessment of movement remains the most valid approach, but it scores active movement only. Genetic methods estimating gene flow levels among interbreeding populations are commonly used, but gene flow does not necessarily mean the current flow of migrants. Methods using the morphometric variation are neither suited to evaluate gene flow, nor are they adapted to estimate the flow of migrants. They may provide, however, the information needed to create a preliminary map pointing to relevant areas where one could invest in using molecular machinery. In case of reinfesting specimens after treatment, the question relates to the likely source of reinfesting specimens: are they a residual sample not affected by the control measures, or are they individuals migrating from surrounding, untreated foci? We explain why the morphometric approach may be adapted to answer such question. Thus, we describe the differences between estimating the flow of migrants and identifying the source of reinfestation after treatment: although morphometrics is not suited to deal with the former, it may be an appropriate tool to address the latter.

Molecular characterization and species delimiting of plant-parasitic nematodes of the genus Pratylenchus from the penetrans group (Nematoda: Pratylenchidae).

PubMed

Janssen, Toon; Karssen, Gerrit; Orlando, Valeria; Subbotin, Sergei A; Bert, Wim

2017-12-01

Root-lesion nematodes of the genus Pratylenchus are an important pest parasitizing a wide range of vascular plants including several economically important crops. However, morphological diagnosis of the more than 100 species is problematic due to the low number of diagnostic features, high morphological plasticity and incomplete taxonomic descriptions. In order to employ barcoding based diagnostics, a link between morphology and species specific sequences has to be established. In this study, we reconstructed a multi-gene phylogeny of the Penetrans group using nuclear ribosomal and mitochondrial gene sequences. A combination of this phylogenetic framework with molecular species delineation analysis, population genetics, morphometric information and sequences from type location material allowed us to establish the species boundaries within the Penetrans group and as such clarify long-standing controversies about the taxonomic status of P. penetrans, P. fallax and P. convallariae. Our study also reveals a remarkable amount of cryptic biodiversity within the genus Pratylenchus confirming that identification on morphology alone can be inconclusive in this taxonomically confusing genus. Copyright © 2017 Elsevier Inc. All rights reserved.

An effective image classification method with the fusion of invariant feature and a new color descriptor

NASA Astrophysics Data System (ADS)

Mansourian, Leila; Taufik Abdullah, Muhamad; Nurliyana Abdullah, Lili; Azman, Azreen; Mustaffa, Mas Rina

2017-02-01

Pyramid Histogram of Words (PHOW), combined Bag of Visual Words (BoVW) with the spatial pyramid matching (SPM) in order to add location information to extracted features. However, different PHOW extracted from various color spaces, and they did not extract color information individually, that means they discard color information, which is an important characteristic of any image that is motivated by human vision. This article, concatenated PHOW Multi-Scale Dense Scale Invariant Feature Transform (MSDSIFT) histogram and a proposed Color histogram to improve the performance of existing image classification algorithms. Performance evaluation on several datasets proves that the new approach outperforms other existing, state-of-the-art methods.

Morphometrics of Daucus (Apiaceae): A counterpart to a phylogenomic study

USDA-ARS?s Scientific Manuscript database

Molecular phylogenetics of genome-scale data sets (phylogenomics) often produces phylogenetic trees with unprecedented resolution. A companion phylogenomics analysis of Daucus (carrots) using 94 conserved nuclear orthologs supported many of the traditional species but showed unexpected results that ...

Pore network properties of sandstones in a fault damage zone

NASA Astrophysics Data System (ADS)

Bossennec, Claire; Géraud, Yves; Moretti, Isabelle; Mattioni, Luca; Stemmelen, Didier

2018-05-01

The understanding of fluid flow in faulted sandstones is based on a wide range of techniques. These depend on the multi-method determination of petrological and structural features, porous network properties and both spatial and temporal variations and interactions of these features. The question of the multi-parameter analysis on fluid flow controlling properties is addressed for an outcrop damage zone in the hanging wall of a normal fault zone on the western border of the Upper Rhine Graben, affecting the Buntsandstein Group (Early Triassic). Diagenetic processes may alter the original pore type and geometry in fractured and faulted sandstones. Therefore, these may control the ultimate porosity and permeability of the damage zone. The classical model of evolution of hydraulic properties with distance from the major fault core is nuanced here. The hydraulic behavior of the rock media is better described by a pluri-scale model including: 1) The grain scale, where the hydraulic properties are controlled by sedimentary features, the distance from the fracture, and the impact of diagenetic processes. These result in the ultimate porous network characteristics observed. 2) A larger scale, where the structural position and characteristics (density, connectivity) of the fracture corridors are strongly correlated with both geo-mechanical and hydraulic properties within the damage zone.

Sequence-based genotyping clarifies conflicting historical morphometric and biological data for 5 Eimeria species infecting turkeys.

PubMed

El-Sherry, S; Ogedengbe, M E; Hafeez, M A; Sayf-Al-Din, M; Gad, N; Barta, J R

2015-02-01

Unlike with Eimeria species infecting chickens, specific identification and nomenclature of Eimeria species infecting turkeys is complicated, and in the absence of molecular data, imprecise. In an attempt to reconcile contradictory data reported on oocyst morphometrics and biological descriptions of various Eimeria species infecting turkey, we established single oocyst derived lines of 5 important Eimeria species infecting turkeys, Eimeria meleagrimitis (USMN08-01 strain), Eimeria adenoeides (Guelph strain), Eimeria gallopavonis (Weybridge strain), Eimeria meleagridis (USAR97-01 strain), and Eimeria dispersa (Briston strain). Short portions (514 bp) of mitochondrial cytochrome c oxidase subunit I gene (mt COI) from each were amplified and sequenced. Comparison of these sequences showed sufficient species-specific sequence variation to recommend these short mt COI sequences as species-specific markers. Uniformity of oocyst features (dimensions and oocyst structure) of each pure line was observed. Additional morphological features of the oocysts of these species are described as useful for the microscopic differentiation of these Eimeria species. Combined molecular and morphometric data on these single species lines compared with the original species descriptions and more recent data have helped to clarify some confusing, and sometimes conflicting, features associated with these Eimeria spp. For example, these new data suggest that the KCH and KR strains of E. adenoeides reported previously represent 2 distinct species, E. adenoeides and E. meleagridis, respectively. Likewise, analysis of the Weybridge strain of E. adenoeides, which has long been used as a reference strain in various studies conducted on the pathogenicity of E. adenoeides, indicates that this coccidium is actually a strain of E. gallopavonis. We highly recommend mt COI sequence-based genotyping be incorporated into all studies using Eimeria spp. of turkeys to confirm species identifications and so that any resulting data can be associated correctly with a single named Eimeria species. © 2015 Poultry Science Association Inc.

Closed depressions in the European loess belt - Natural or anthropogenic origin?

NASA Astrophysics Data System (ADS)

Kołodyńska-Gawrysiak, Renata; Poesen, Jean

2017-07-01

Closed depressions (CDs) are typical geomorphological features of the loess belt in Europe. CDs have been reported in several regions of the European loess belt, where they are described as hollows, mardeles, wymoki, crovuri, bludtsa and zapadiny. The natural and anthropogenic origins of CDs are debated in literature. Moreover, no comprehensive review of the geomorphic properties or the evolution of these depressions exists. Therefore this paper reviews the characteristics of CDs in the European loess belt and attempts to better understand their genesis based on detailed case studies. The main morphometric features as well as sediment deposits within CDs in several sub-regions of Europe were analysed and compared. Morphometric properties of CDs from the West European and East European loess belt were investigated through a comparison of CDs from two representative regions, i.e. East Poland and Central Belgium. In both study areas, CDs under cropland are similar. However, a comparison of morphological features of CDs under forest, revealed clear differences, suggesting a different origin of CDs from both regions. Infilled sediments in CDs show various litho-genetical features in different regions of the European loess belt. The morphometric features, ages and stratigraphy of infillings clearly indicate that both anthropogenic and natural processes have shaped these landforms within the loess belt of Europe. CDs observed in Eastern Europe may have a very different origin than those documented in Western Europe. Detailed analysis of CDs in Poland and in neighbouring regions of East Europe, suggest that CDs are natural landforms: thermokarst, deflation and dissolution of loess are reported as probable genetic processes. In contrast, several studies in Western Europe indicate a dominant anthropogenic origin (i.e. digging of calcareous loess or marls, bomb and mining craters, collapse of underground limestone quarries), although CDs formed by natural processes (i.e. piping, dissolution of limestone and salt lenses below the loess cover) are reported as well. CDs act as important archives, allowing one to reconstruct both natural and anthropogenic processes operating in the past. As CDs store most sediments eroded within their catchment they provide ideal sediment traps to assess long-term erosion rates in these environments which have hitherto been under-researched. More research is needed to unravel the genesis and evolution of these depressions to better understand the importance of the Late Glacial and Holocene stages for the morphogenesis of the loess belt in Europe.

Mapping the Regional Influence of Genetics on Brain Structure Variability - A Tensor-Based Morphometry Study

PubMed Central

Brun, Caroline; Leporé, Natasha; Pennec, Xavier; Lee, Agatha D.; Barysheva, Marina; Madsen, Sarah K.; Avedissian, Christina; Chou, Yi-Yu; de Zubicaray, Greig I.; McMahon, Katie; Wright, Margaret; Toga, Arthur W.; Thompson, Paul M.

2010-01-01

Genetic and environmental factors influence brain structure and function profoundly The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins’ 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject’s anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions which have a more protracted maturational time-course. PMID:19446645

Continuous micron-scaled rope engineering using a rotating multi-nozzle electrospinning emitter

NASA Astrophysics Data System (ADS)

Zhang, Chunchen; Gao, Chengcheng; Chang, Ming-Wei; Ahmad, Zeeshan; Li, Jing-Song

2016-10-01

Electrospinning (ES) enables simple production of fibers for broad applications (e.g., biomedical engineering, energy storage, and electronics). However, resulting structures are predominantly random; displaying significant disordered fiber entanglement, which inevitably gives rise to structural variations and reproducibility on the micron scale. Surface and structural features on this scale are critical for biomaterials, tissue engineering, and pharmaceutical sciences. In this letter, a modified ES technique using a rotating multi-nozzle emitter is developed and utilized to fabricate continuous micron-scaled polycaprolactone (PCL) ropes, providing control on fiber intercalation (twist) and structural order. Micron-scaled ropes comprising 312 twists per millimeter are generated, and rope diameter and pitch length are regulated using polymer concentration and process parameters. Electric field simulations confirm vector and distribution mechanisms, which influence fiber orientation and deposition during the process. The modified fabrication system provides much needed control on reproducibility and fiber entanglement which is crucial for electrospun biomedical materials.

Vehicle license plate recognition based on geometry restraints and multi-feature decision

NASA Astrophysics Data System (ADS)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Morphometric analysis of the Marmara Sea river basins, Turkey

NASA Astrophysics Data System (ADS)

Elbaşı, Emre; Ozdemir, Hasan

2014-05-01

The drainage basin, the fundamental unit of the fluvial landscape, has been focus of research aimed at understanding the geometric characteristics of the master channel and its tributary network. This geometry is referred to as the basin morphometry and is nicely reviewed by Abrahams (1984). A great amount of research has focused on geometric characteristic of drainage basins, including the topology of the stream networks, and quantitative description of drainage texture, pattern, shape, and relief characteristics. Evaluation of morphometric parameters necessitates the analysis of various drainage parameters such as ordering of the various streams, measurement of basin area and perimeter, length of drainage channels, drainage density (Dd), stream frequency (Fs), bifurcation ratio (Rb), texture ratio (T), basin relief (Bh), Ruggedness number (Rn), time of concentration (Tc), hypsometric curve and integral (Hc and Hi) (Horton, 1932, Schumn, 1956, Strahler, 1957; Verstappen 1983; Keller and Pinter, 2002; Ozdemir and Bird, 2009). These morphometric parameters have generally been used to predict flood peaks, to assess sediment yield, and to estimate erosion rates in the basins. River basins of the Marmara Sea, has an area of approximately 40,000 sqkm, are the most important basins in Turkey based on their dense populations, industry and transportation systems. The primary aim of this study is to determine and analyse of morphometric characteristics of the Marmara Sea river basins using 10 m resolution Digital Elevation Model (DEM) and to evaluate of the results. For these purposes, digital 10 m contour maps scaled 1:25000 and geological maps scaled 1:100000 were used as the main data sources in the study. 10 m resolution DEM data were created using the contour maps and then drainage networks and their watersheds were extracted using D8 pour point model. Finally, linear, areal and relief morphometries were applied to the river basins using Geographic Information Systems (GIS). This study shows that morphometric analysis of the basins in regional level are very important to understand general morphological characteristics of the basins. In this case, tectonic and lithological conditions of the basins have greatly affected the morphometric characteristics of the north and south basins of the Marmara Sea. References Abrahams, AD. 1984. Channel Networks: A Geomorphological Perspective. Water Resources Research, Volume 20, Issue 2, pages 161-188. Horton, R.E. 1932. Drainage basin characteristics. Trans Am Geophys Union 13:350-361. Keller, E.A., Pinter, N. 2002. Active Tectonics Earthquakes, Uplift, and Landscape, Second Edition, Prentice Hall, New Jersey. Ozdemir H., Bird D. 2009. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods, Environmental Geology, vol.56, pp.1405-1415. Schumm, S.A. 1956. Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geol Soc Am Bull 67:597-646. Strahler, A.N. 1957. Quantitative geomorphology of drainage and channel networks. In: Chow YT (ed) Handbook of appliecl hydrology. Me Graw Hill Book Company, New York. Verstappen, H.Th. 1983. Applied geomorphology. ITC, Enschede.

Rapid multi-modality preregistration based on SIFT descriptor.

PubMed

Chen, Jian; Tian, Jie

2006-01-01

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

Disappearance of Anisotropic Intermittency in Large-amplitude MHD Turbulence and Its Comparison with Small-amplitude MHD Turbulence

NASA Astrophysics Data System (ADS)

Yang, Liping; Zhang, Lei; He, Jiansen; Tu, Chuanyi; Li, Shengtai; Wang, Xin; Wang, Linghua

2018-03-01

Multi-order structure functions in the solar wind are reported to display a monofractal scaling when sampled parallel to the local magnetic field and a multifractal scaling when measured perpendicularly. Whether and to what extent will the scaling anisotropy be weakened by the enhancement of turbulence amplitude relative to the background magnetic strength? In this study, based on two runs of the magnetohydrodynamic (MHD) turbulence simulation with different relative levels of turbulence amplitude, we investigate and compare the scaling of multi-order magnetic structure functions and magnetic probability distribution functions (PDFs) as well as their dependence on the direction of the local field. The numerical results show that for the case of large-amplitude MHD turbulence, the multi-order structure functions display a multifractal scaling at all angles to the local magnetic field, with PDFs deviating significantly from the Gaussian distribution and a flatness larger than 3 at all angles. In contrast, for the case of small-amplitude MHD turbulence, the multi-order structure functions and PDFs have different features in the quasi-parallel and quasi-perpendicular directions: a monofractal scaling and Gaussian-like distribution in the former, and a conversion of a monofractal scaling and Gaussian-like distribution into a multifractal scaling and non-Gaussian tail distribution in the latter. These results hint that when intermittencies are abundant and intense, the multifractal scaling in the structure functions can appear even if it is in the quasi-parallel direction; otherwise, the monofractal scaling in the structure functions remains even if it is in the quasi-perpendicular direction.

Protective Effects of Trehalose on the Corneal Epithelial Cells

PubMed Central

Aragona, Pasquale; Colosi, Pietro; Colosi, Francesca; Pisani, Antonina; Puzzolo, Domenico; Micali, Antonio

2014-01-01

Purpose. Aim of the present work was to evaluate the effects of the trehalose on the corneal epithelium undergoing alcohol delamination. Methods. Twelve patients undergoing laser subepithelial keratomileusis (LASEK) were consecutively included in the study. The right eyes were pretreated with 3% trehalose eye drops, whilst left eyes were used as control. Epithelial specimens were processed for cells vitality assessment, apoptosis, and light and transmission electron microscopy; a morphometric analysis was performed in both groups. Results. In both trehalose-untreated eyes (TUE) and trehalose-treated eyes (TTE), the percentage of vital cells was similar and no apoptotic cells were observed. In TUE, the corneal epithelium showed superficial cells with reduced microfolds, wing cells with vesicles and dilated intercellular spaces, and dark basal cells with vesicles and wide clefts. In TTE, superficial and wing cells were better preserved, and basal cells were generally clear with intracytoplasmatic vesicles. The morphometric analysis showed statistically significant differences between the two groups: the TTE epithelial height was higher, the basal cells showed larger area and clearer cytoplasm. The distribution of desmosomes and hemidesmosomes was significantly different between the groups. Conclusions. Trehalose administration better preserved morphological and morphometric features of alcohol-treated corneal epithelium, when compared to controls. PMID:25045743

Protective effects of trehalose on the corneal epithelial cells.

PubMed

Aragona, Pasquale; Colosi, Pietro; Rania, Laura; Colosi, Francesca; Pisani, Antonina; Puzzolo, Domenico; Micali, Antonio

2014-01-01

Aim of the present work was to evaluate the effects of the trehalose on the corneal epithelium undergoing alcohol delamination. Twelve patients undergoing laser subepithelial keratomileusis (LASEK) were consecutively included in the study. The right eyes were pretreated with 3% trehalose eye drops, whilst left eyes were used as control. Epithelial specimens were processed for cells vitality assessment, apoptosis, and light and transmission electron microscopy; a morphometric analysis was performed in both groups. In both trehalose-untreated eyes (TUE) and trehalose-treated eyes (TTE), the percentage of vital cells was similar and no apoptotic cells were observed. In TUE, the corneal epithelium showed superficial cells with reduced microfolds, wing cells with vesicles and dilated intercellular spaces, and dark basal cells with vesicles and wide clefts. In TTE, superficial and wing cells were better preserved, and basal cells were generally clear with intracytoplasmatic vesicles. The morphometric analysis showed statistically significant differences between the two groups: the TTE epithelial height was higher, the basal cells showed larger area and clearer cytoplasm. The distribution of desmosomes and hemidesmosomes was significantly different between the groups. Trehalose administration better preserved morphological and morphometric features of alcohol-treated corneal epithelium, when compared to controls.

Morphometric traits capture the climatically driven species turnover of 10 spruce taxa across China.

PubMed

Li, He; Wang, GuoHong; Zhang, Yun; Zhang, WeiKang

2016-02-01

This study explored the relative roles of climate and phylogenetic background in driving morphometric trait variation in 10 spruce taxa in China. The study further addressed the hypothesis that these variations are consistent with species turnover on climatic gradients. Nine morphometric traits of leaves, seed cones, and seeds for the 10 studied spruce taxa were measured at 504 sites. These data were analyzed in combination with species DNA sequences from NCBI GenBank. We detected the effects of phylogeny and climate through trait-variation-based K statistics and phylogenetic eigenvector regression (PVR) analyses. Multivariate analyses were performed to detect trait variation along climatic gradients with species replacement. The estimated K-values for the nine studied morphometric traits ranged from 0.19 to 0.68, and the studied environmental variables explained 39-83% of the total trait variation. Trait variation tended to be determined largely by a temperature gradient varying from wet-cool climates to dry-warm summers and, additionally, by a moisture gradient. As the climate became wetter and cooler, spruce species tended to be replaced by other spruces with smaller needle leaves and seeds but larger cones and seed scales. A regression analysis showed that spruce species tended to be successively replaced by other species, along the gradient, although the trends observed within species were not necessarily consistent with the overall trend. The climatically driven replacement of the spruces in question could be well indicated by the between-species variation in morphometric traits that carry lower phylogenetic signal. Between-species variation in these traits is driven primarily by climatic factors. These species demonstrate a narrower ecological amplitude in temperature but wider ranges on the moisture gradient.

Multi-scale image segmentation method with visual saliency constraints and its application

NASA Astrophysics Data System (ADS)

Chen, Yan; Yu, Jie; Sun, Kaimin

2018-03-01

Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works better for texture image segmentation than traditional multi-scale image segmentation methods, and can enable us to give priority control to the saliency objects of interest. This method has been used in image quality evaluation, scattered residential area extraction, sparse forest extraction and other applications to verify its validation. All applications showed good results.

Multi-length Scale Material Model Development for Armorgrade Composites

DTIC Science & Technology

2014-05-02

various microstructural features and processes , at different length- scales, to the macroscopic-level ballistic-penetration resistance of PPTA-based...fabric or PPTA-fiber-reinforced polymer-matrix composites. Specifically, the role of various material-synthesis-/fiber- processing -induced defects, as...well as defects induced during the weaving process , was investigated. The results obtained clearly revealed that 1. REPORT DATE (DD-MM-YYYY) 4. TITLE

A simple method to achieve full-field and real-scale reconstruction using a movable stereo rig

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Song, Zhan; Tang, Suming

2018-06-01

This paper introduces a simple method to achieve full-field and real-scale reconstruction using a movable binocular vision system (MBVS). The MBVS is composed of two cameras, one is called the tracking camera, and the other is called the working camera. The tracking camera is used for tracking the positions of the MBVS and the working camera is used for the 3D reconstruction task. The MBVS has several advantages compared with a single moving camera or multi-camera networks. Firstly, the MBVS could recover the real-scale-depth-information from the captured image sequences without using auxiliary objects whose geometry or motion should be precisely known. Secondly, the removability of the system could guarantee appropriate baselines to supply more robust point correspondences. Additionally, using one camera could avoid the drawback which exists in multi-camera networks, that the variability of a cameras’ parameters and performance could significantly affect the accuracy and robustness of the feature extraction and stereo matching methods. The proposed framework consists of local reconstruction and initial pose estimation of the MBVS based on transferable features, followed by overall optimization and accurate integration of multi-view 3D reconstruction data. The whole process requires no information other than the input images. The framework has been verified with real data, and very good results have been obtained.

Verification of LANDSAT imagery for morphametric and topological studies of drainage basins in a section of the western plateau of Sao Paulo State: Tiete-Aguapei watershed. M.S. Thesis; [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Camargo, J. C. G.

1982-01-01

The potential of using LANDSAT MSS imagery for morphometric and topological studies of drainage basins was verified. Using Tiete and Aguapei watershed (Western Plateau) as the test site because of its homogeneous landscape. Morphometric variables collected for ten drainage basins include: circularity index; river density; drainage density; topographic texture; areal and index length; basin parameter; and main river length 1st order and 2nd order channel length. The topographical variables determined were: order; magnitude; bifuraction ratio; weighted bifuraction ratio; number of segments; number of linking; trajectory length; and topological diameter. Data were collected on topographical maps at the scale of 1:250,000 and 1:59,000 and on LANDSAT imagery at the scale of 1:250,000. The results which were summarized on tables for further analysis, show that LANDSAT imagery can supply the lack of topographic charts for drainage studies.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

Vitamin B12 deficiency: Characterization of psychometrics and MRI morphometrics.

PubMed

Hsu, Yen-Hsuan; Huang, Ching-Feng; Lo, Chung-Ping; Wang, Tzu-Lan; Tu, Min-Chien

2016-01-01

Vitamin B12 is essential for the integrity of the central nervous system. However, performances in different cognitive domains relevant to vitamin B12 deficiency remain to be detailed. To date, there have been limited studies that examined the relationships between cognitions and structural neuroimaging in a single cohort of low-vitamin B12 status. The present study aimed to depict psychometrics and magnetic resonance imaging (MRI) morphometrics among patients with vitamin B12 deficiency, and to examine their inter-relations. We compared 34 consecutive patients with vitamin B12 deficiency (serum level ≤ 250 pg/ml) to 34 demographically matched controls by their cognitive performances and morphometric indices of brain MRI. The correlations between psychometrics and morphometrics were analyzed. The vitamin B12 deficiency group had lower scores than the controls on total scores of Mini-Mental Status Examination (MMSE) and Cognitive Abilities Screening Instrument (CASI) (both P < 0.05), language (P < 0.01), orientation (P < 0.01), and mental manipulation (P < 0.05). The patients also showed a greater frontal horn ratio than the controls (P < 0.05). Bicaudate ratio, fronto-occipital ratio, uncotemporal index, and normalized interuncal distance all showed a strong correlation with the total score of MMSE and CASI (all P < 0.01). Among these psychometric and morphometric indices, pronounced correlations between bicaudate ratio and long-term memory, mental manipulation, orientation, language, and verbal fluency were noted (all P < 0.01). Vitamin B12 deficiency is associated with a global cognition decline with language, orientation, and mental manipulation selectively impaired. Preferential atrophy in frontal regions is the main neuroimaging feature. Although the frontal ratio highlights the relevant atrophy among patients, the bicaudate ratio might be the best index on the basis of its strong association with global cognition and related cognitive domains, implying dysfunction of fronto-subcortical circuits as the fundamental pathogenesis related to vitamin B12 deficiency.

Sensor-based auto-focusing system using multi-scale feature extraction and phase correlation matching.

PubMed

Jang, Jinbeum; Yoo, Yoonjong; Kim, Jongheon; Paik, Joonki

2015-03-10

This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems.

Sensor-Based Auto-Focusing System Using Multi-Scale Feature Extraction and Phase Correlation Matching

PubMed Central

Jang, Jinbeum; Yoo, Yoonjong; Kim, Jongheon; Paik, Joonki

2015-01-01

This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems. PMID:25763645

Seed morphometric characteristics of European species of Elatine (Elatinaceae)

PubMed Central

Łysko, Andrzej; Białecka, Bożenna; Bihun, Magdalena Marta; Sramkó, Gábor; Staroń, Waldemar; Wieczorek, Anetta; Molnár V., Attila

2017-01-01

Elatine L. contains ca. 25 small, herbaceous, annual species distributed in ephemeral waters in both hemispheres. All species are amphibious and characterized by a high degree of morphological variability. The importance of seed morphology in Elatine taxonomy has been emphasized by many authors. The degree of seed curvature and seed coat reticulation have been traditionally considered very important in recognizing individual species of this genus. Seed morphometric characteristics of 10 Elatine species, including all European native taxa, are provided on the basis of material from two or three populations of each species. A total of 24–50 seeds were studied from each population, altogether 1,260 images were used for the morphometric study. In total, six parameters were measured from SEM pictures: object surface area, profile specific perimeter (object circuit), rectangle of the object (a) length, rectangle of the object (b) width, angle of the seed curvature, and number of pits in the seed coat counted in the middle row. Our study shows that the range of morphological variation of seeds in European species of Elatine is great, both between the species and the populations. Discrimination analysis showed that all six traits significantly differentiate the populations studied (λ = 0.001, p < 0.001), and the greatest contributions were “number of pits”, “rectangle_a”, and “the angle curvature”. Multidimensional scaling based on a correlation matrix of Mahalanobis distance of the six features studied revealed the greatest similarity between the three populations of E. alsinastrum, E. macropoda, and E. hexandra. Regarding interspecific differences, a Kruskal–Wallis tests showed that, in many cases, lack of statistically significant differences between species relative to the studied seed traits. If distinction of species is only based on seeds, especially if only a few seeds are evaluated, the following species pairs can be easily confused: E. alsinastrum and E. orthosperma, E. hexandra and E. macropoda, E. campylosperma and E. hydropiper, as well and E. gussonei and E. hungarica. We found no diversity in seed coat micromorphology within pits that could have potential taxonomic importance. An identification key and descriptions of species are provided on the basis of seeds traits. PMID:28584724

Finger-Vein Verification Based on Multi-Features Fusion

PubMed Central

Qin, Huafeng; Qin, Lan; Xue, Lian; He, Xiping; Yu, Chengbo; Liang, Xinyuan

2013-01-01

This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time, a region-based matching scheme is investigated by employing the Scale Invariant Feature Transform (SIFT) matching method. Finally, the finger-vein shape, orientation and SIFT features are combined to further enhance the performance. The experimental results on databases of 426 and 170 fingers demonstrate the consistent superiority of the proposed approach. PMID:24196433

Morphological characters of the thickbody skate Amblyraja frerichsi (Krefft 1968) (Rajiformes: Rajidae), with notes on its biology.

PubMed

Bustamante, Carlos; Lamilla, Julio; Concha, Francisco; Ebert, David A; Bennett, Michael B

2012-01-01

Detailed descriptions of morphological features, morphometrics, neurocranium anatomy, clasper structure and egg case descriptions are provided for the thickbody skate Amblyraja frerichsi; a rare, deep-water species from Chile, Argentina and Falkland Islands. The species diagnosis is complemented from new observations and aspects such as colour, size and distribution are described. Geographic and bathymetric distributional ranges are discussed as relevant features of this taxońs biology. Additionally, the conservation status is assessed including bycatch records from Chilean fisheries.

Morphological Characters of the Thickbody Skate Amblyraja frerichsi (Krefft 1968) (Rajiformes: Rajidae), with Notes on Its Biology

PubMed Central

Bustamante, Carlos; Lamilla, Julio; Concha, Francisco; Ebert, David A.; Bennett, Michael B.

2012-01-01

Detailed descriptions of morphological features, morphometrics, neurocranium anatomy, clasper structure and egg case descriptions are provided for the thickbody skate Amblyraja frerichsi; a rare, deep-water species from Chile, Argentina and Falkland Islands. The species diagnosis is complemented from new observations and aspects such as colour, size and distribution are described. Geographic and bathymetric distributional ranges are discussed as relevant features of this taxońs biology. Additionally, the conservation status is assessed including bycatch records from Chilean fisheries. PMID:22768186

Interspecific variation in the tetradactyl manus of modern tapirs (Perissodactyla: Tapirus) exposed using geometric morphometrics.

PubMed

MacLaren, Jamie A; Nauwelaerts, Sandra

2017-11-01

The distal forelimb (autopodium) of quadrupedal mammals is a key morphological unit involved in locomotion, body support, and interaction with the substrate. The manus of the tapir (Perissodactyla: Tapirus) is unique within modern perissodactyls, as it retains the plesiomorphic tetradactyl (four-toed) condition also exhibited by basal equids and rhinoceroses. Tapirs are known to exhibit anatomical mesaxonic symmetry in the manus, although interspecific differences and biomechanical mesaxony have yet to be rigorously tested. Here, we investigate variation in the manus morphology of four modern tapir species (Tapirus indicus, Tapirus bairdii, Tapirus pinchaque, and Tapirus terrestris) using a geometric morphometric approach. Autopodial bones were laser scanned to capture surface shape and morphology was quantified using 3D-landmark analysis. Landmarks were aligned using Generalised Procrustes Analysis, with discriminant function and partial least square analyses performed on aligned coordinate data to identify features that significantly separate tapir species. Overall, our results support the previously held hypothesis that T. indicus is morphologically separate from neotropical tapirs; however, previous conclusions regarding function from morphological differences are shown to require reassessment. We find evidence indicating that T. bairdii exhibits reduced reliance on the lateral fifth digit compared to other tapirs. Morphometric assessment of the metacarpophalangeal joint and the morphology of the distal facets of the lunate lend evidence toward high loading on the lateral digits of both the large T. indicus (large body mass) and the small, long limbed T. pinchaque (ground impact). Our results support other recent studies on T. pinchaque, suggesting subtle but important adaptations to a compliant but inclined habitat. In conclusion, we demonstrate further evidence that the modern tapir forelimb is a variable locomotor unit with a range of interspecific features tailored to habitual and biomechanical needs of each species. © 2017 Wiley Periodicals, Inc.

Adult Neandertal clavicles from the El Sidrón site (Asturias, Spain) in the context of Homo pectoral girdle evolution.

PubMed

Rosas, Antonio; Rodriguez-Perez, Francisco Javier; Bastir, Markus; Estalrrich, Almudena; Huguet, Rosa; García-Tabernero, Antonio; Pastor, Juan Francisco; de la Rasilla, Marco

2016-06-01

We undertook a three-dimensional geometric morphometric (3DGM) analysis on 12 new Neandertal clavicle specimens from the El Sidrón site (Spain), dated to 49,000 years ago. The 3DGM methods were applied in a comparative framework in order to improve our understanding of trait polarity in features related to Homo pectoral girdle evolution, using other Neandertals, Homo sapiens, Pan, ATD6-50 (Homo antecessor), and KNM-WT 15000 (Homo ergaster/erectus) in the reference collection. Twenty-nine homologous landmarks were measured for each clavicle. Variation and morphological similarities were assessed through principal component analysis, conducted separately for the complete clavicle and the diaphysis. On average, Neandertal clavicles had significantly larger muscular entheses, double dorsal curvature, clavicle torsion, and cranial orientation of the acromial end than non-Neandertal clavicles; the El Sidrón clavicles fit this pattern. Variation within the samples was large, with extensive overlap between Homo species; only chimpanzee specimens clearly differed from the other specimens in morphometric terms. Taken together, our morphometric analyses are consistent with the following phylogenetic sequence. The primitive condition of the clavicle is manifest in the cranial orientation of both the acromial and sternal ends. The derived condition expressed in the H. sapiens + Neandertal clade is defined by caudal rotation of both the sternal and acromial ends, but with variation in the number of acromia remaining in a certain cranial orientation. Finally, the autapomorphic Neandertal condition is defined by secondarily acquired primitive cranial re-orientation of the acromial end, which varies from individual to individual. These results suggest that the pace of phylogenetic change in the pectoral girdle does not seem to follow that of other postcranial skeletal features. Copyright © 2016 Elsevier Ltd. All rights reserved.

Individualized adjustments to reference phantom internal organ dosimetry—scaling factors given knowledge of patient external anatomy

NASA Astrophysics Data System (ADS)

Wayson, Michael B.; Bolch, Wesley E.

2018-04-01

Internal radiation dose estimates for diagnostic nuclear medicine procedures are typically calculated for a reference individual. Resultantly, there is uncertainty when determining the organ doses to patients who are not at 50th percentile on either height or weight. This study aims to better personalize internal radiation dose estimates for individual patients by modifying the dose estimates calculated for reference individuals based on easily obtainable morphometric characteristics of the patient. Phantoms of different sitting heights and waist circumferences were constructed based on computational reference phantoms for the newborn, 10 year-old, and adult. Monoenergetic photons and electrons were then simulated separately at 15 energies. Photon and electron specific absorbed fractions (SAFs) were computed for the newly constructed non-reference phantoms and compared to SAFs previously generated for the age-matched reference phantoms. Differences in SAFs were correlated to changes in sitting height and waist circumference to develop scaling factors that could be applied to reference SAFs as morphometry corrections. A further set of arbitrary non-reference phantoms were then constructed and used in validation studies for the SAF scaling factors. Both photon and electron dose scaling methods were found to increase average accuracy when sitting height was used as the scaling parameter (~11%). Photon waist circumference-based scaling factors showed modest increases in average accuracy (~7%) for underweight individuals, but not for overweight individuals. Electron waist circumference-based scaling factors did not show increases in average accuracy. When sitting height and waist circumference scaling factors were combined, modest average gains in accuracy were observed for photons (~6%), but not for electrons. Both photon and electron absorbed doses are more reliably scaled using scaling factors computed in this study. They can be effectively scaled using sitting height alone as patient-specific morphometric parameter.

Individualized adjustments to reference phantom internal organ dosimetry-scaling factors given knowledge of patient external anatomy.

PubMed

Wayson, Michael B; Bolch, Wesley E

2018-04-13

Internal radiation dose estimates for diagnostic nuclear medicine procedures are typically calculated for a reference individual. Resultantly, there is uncertainty when determining the organ doses to patients who are not at 50th percentile on either height or weight. This study aims to better personalize internal radiation dose estimates for individual patients by modifying the dose estimates calculated for reference individuals based on easily obtainable morphometric characteristics of the patient. Phantoms of different sitting heights and waist circumferences were constructed based on computational reference phantoms for the newborn, 10 year-old, and adult. Monoenergetic photons and electrons were then simulated separately at 15 energies. Photon and electron specific absorbed fractions (SAFs) were computed for the newly constructed non-reference phantoms and compared to SAFs previously generated for the age-matched reference phantoms. Differences in SAFs were correlated to changes in sitting height and waist circumference to develop scaling factors that could be applied to reference SAFs as morphometry corrections. A further set of arbitrary non-reference phantoms were then constructed and used in validation studies for the SAF scaling factors. Both photon and electron dose scaling methods were found to increase average accuracy when sitting height was used as the scaling parameter (~11%). Photon waist circumference-based scaling factors showed modest increases in average accuracy (~7%) for underweight individuals, but not for overweight individuals. Electron waist circumference-based scaling factors did not show increases in average accuracy. When sitting height and waist circumference scaling factors were combined, modest average gains in accuracy were observed for photons (~6%), but not for electrons. Both photon and electron absorbed doses are more reliably scaled using scaling factors computed in this study. They can be effectively scaled using sitting height alone as patient-specific morphometric parameter.

Anthropometrics of mental foramen in dry dentate and edentulous mandibles in Coastal Andhra population of Andhra Pradesh State.

PubMed

Moogala, Srinivas; Sanivarapu, Sahitya; Boyapati, Ramanarayana; Devulapalli, Narasimha Swamy; Chakrapani, Swarna; Kolaparthy, Laxmikanth

2014-07-01

The aim of this study is to determine the morphological features and morphometrics of mental foramen with reference to surrounding anatomical landmarks in Coastal Andhra population of Andhra Pradesh State. Two-hundred and nineteen dry dentate and edentulous mandibles are examined in this study. Out of these 127 were dentate and 92 were edentulous. Various morphological and morphometrical parameters were measured by using digital Vernier caliper, metallic wire and metallic scale on both the right and left sides. In the present study, the distance between most anterior margin of mental foramen and posterior border of ramus of the mandible is [MF-PR], MF-PR is 69.61 ± 6.03 mm on the right side and is 69.17 ± 6. 0 mm on left side in dentate mandible. In edentulous type, MF-PR is 68.39 ±6.4 mm on right side and 68.81 ± 6.55 mm on left side. In the present study, the distance between symphysis menti and most anterior margin of mental foramen [MF-SM] in dentate mandible is 28.24 ± 5.09 mm on right side and is 27.45 ± 3.7 mm on left side. In edentulous mandible (MF-SM) is 28.51 ± 4.5 mm on right side and on left side is 27.99 ± 4.50 mm. Acquiring the knowledge and importance of anatomy of mental foramen is helpful in avoiding neurovascular complications, during regional anesthesia, peri apical surgeries, nerve repositioning and dental implant placement.

A geometric morphometric study of regional differences in the ontogeny of the modern human facial skeleton.

PubMed

Vioarsdóttir, Una Strand; O'Higgins, Paul; Stringer, Chris

2002-09-01

This study examines interpopulation variations in the facial skeleton of 10 modern human populations and places these in an ontogenetic perspective. It aims to establish the extent to which the distinctive features of adult representatives of these populations are present in the early post natal period and to what extent population differences in ontogenetic scaling and allometric trajectories contribute to distinct facial forms. The analyses utilize configurations of facial landmarks and are carried out using geometric morphometric methods. The results of this study show that modern human populations can be distinguished based on facial shape alone, irrespective of age or sex, indicating the early presence of differences. Additionally, some populations have statistically distinct facial ontogenetic trajectories that lead to the development of further differences later in ontogeny. We conclude that population-specific facial morphologies develop principally through distinctions in facial shape probably already present at birth and further accentuated and modified to variable degrees during growth. These findings raise interesting questions regarding the plasticity of facial growth patterns in modern humans. Further, they have important implications in relation to the study of growth in the face of fossil hominins and in relation to the possibility of developing effective discriminant functions for the identification of population affinities of immature facial skeletal material. Such tools would be of value in archaeological, forensic and anthropological applications. The findings of this study underline the need to examine more deeply, and in more detail, the ontogenetic basis of other causes of craniometric variation, such as sexual dimorphism and hominin species differentiation.

Comprehensive evolutionary analysis of the Anthroherpon radiation (Coleoptera, Leiodidae, Leptodirini).

PubMed

Njunjić, Iva; Perrard, Adrien; Hendriks, Kasper; Schilthuizen, Menno; Perreau, Michel; Merckx, Vincent; Baylac, Michel; Deharveng, Louis

2018-01-01

The genus Anthroherpon Reitter, 1889 exhibits the most pronounced troglomorphic characters among Coleoptera, and represents one of the most spectacular radiations of subterranean beetles. However, radiation, diversification, and biogeography of this genus have never been studied in a phylogenetic context. This study provides a comprehensive evolutionary analysis of the Anthroherpon radiation, using a dated molecular phylogeny as a framework for understanding Anthroherpon diversification, reconstructing the ancestral range, and exploring troglomorphic diversity. Based on 16 species and 22 subspecies, i.e. the majority of Anthroherpon diversity, we reconstructed the phylogeny using Bayesian analysis of six loci, both mitochondrial and nuclear, comprising a total of 4143 nucleotides. In parallel, a morphometric analysis was carried out with 79 landmarks on the body that were subjected to geometric morphometrics. We optimized morphometric features to phylogeny, in order to recognize the way troglomorphy was expressed in different clades of the tree, and did character evolution analyses. Finally, we reconstructed the ancestral range of the genus using BioGeoBEARS. Besides further elucidating the suprageneric classification of the East-Mediterranean Leptodirini, our main findings also show that Anthroherpon dates back to the Early Miocene (ca. 22 MYA) and that the genus diversified entirely underground. Biogeographic reconstruction of the ancestral range shows the origin of the genus in the area comprising three high mountains in western Montenegro, which is in the accordance with the available data on the paleogeography of the Balkan Peninsula. Character evolution analysis indicates that troglomorphic morphometric traits in Anthroherpon mostly evolve neutrally but may diverge adaptively under syntopic competition.

Hystricognathy vs Sciurognathy in the Rodent Jaw: A New Morphometric Assessment of Hystricognathy Applied to the Living Fossil Laonastes (Diatomyidae)

PubMed Central

Hautier, Lionel; Lebrun, Renaud; Saksiri, Soonchan; Michaux, Jacques; Vianey-Liaud, Monique; Marivaux, Laurent

2011-01-01

While exceptional for an intense diversification of lineages, the evolutionary history of the order Rodentia comprises only a limited number of morphological morphotypes for the mandible. This situation could partly explain the intense debates about the taxonomic position of the latest described member of this clade, the Laotian rock rat Laonastes aenigmamus (Diatomyidae). This discovery has re-launched the debate on the definition of the Hystricognathi suborder identified using the angle of the jaw relative to the plane of the incisors. Our study aims to end this ambiguity. For clarity, it became necessary to revisit the entire morphological diversity of the mandible in extant and extinct rodents. However, current and past rodent diversity brings out the limitations of the qualitative descriptive approach and highlights the need for a quantitative approach. Here, we present the first descriptive comparison of the masticatory apparatus within the Ctenohystrica clade, in combining classic comparative anatomy with morphometrical methods. First, we quantified the shape of the mandible in rodents using 3D landmarks. Then, the analysis of osteological features was compared to myological features in order to understand the biomechanical origin of this morphological diversity. Among the morphological variation observed, the mandible of Laonastes aenigmamus displays an intermediate association of features that could be considered neither as sciurognathous nor as hystricognathous. PMID:21490933

Sexual dimorphic features within extant great ape faciodental skeletal anatomy and testing the single species hypothesis.

PubMed

Cameron, D W

1997-01-01

This paper examines sexually dimorphic skeletal characters within the face and upper dentition of extant hominids (great ape), not including members of the Hominini. Specimens of Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo pygmaeus are used to help identify likely sex specific characters for the Hominidae. The aim of this paper is to identify extant hominid faciodental sexual features which can be used to help sex fossil specimens. A morphometric and skeletal study of sexual variability demonstrates relatively diverse patterns of sexual variability within the extant hominids. In terms of morphometrics, P. paniscus is relatively non-dimorphic, while P. troglodytes, Gorilla and Pongo display a large degree of sexual dimorphism. In their respective skeletal anatomies, however, each has specific characters which tend to differentiate between the sexes. Some faciodental sex features are shown to be common amongst all four taxa and as such are likely to be important criteria for determining the sex of Miocene and Plio-Pleistocene fossil hominid specimens. The construction of extant great ape sexual ranges of variability are also important in helping to test the fossil ape single species hypotheses. The testing of sex and species ranges of variability should employ range based statistics not only because they are sample size independent, (relative to C.V.) but also because they are of low power.

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Huang, K. S.; Diep, J.

1993-01-01

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

Multi-scaling modelling in financial markets

NASA Astrophysics Data System (ADS)

Liu, Ruipeng; Aste, Tomaso; Di Matteo, T.

2007-12-01

In the recent years, a new wave of interest spurred the involvement of complexity in finance which might provide a guideline to understand the mechanism of financial markets, and researchers with different backgrounds have made increasing contributions introducing new techniques and methodologies. In this paper, Markov-switching multifractal models (MSM) are briefly reviewed and the multi-scaling properties of different financial data are analyzed by computing the scaling exponents by means of the generalized Hurst exponent H(q). In particular we have considered H(q) for price data, absolute returns and squared returns of different empirical financial time series. We have computed H(q) for the simulated data based on the MSM models with Binomial and Lognormal distributions of the volatility components. The results demonstrate the capacity of the multifractal (MF) models to capture the stylized facts in finance, and the ability of the generalized Hurst exponents approach to detect the scaling feature of financial time series.

Automated Image Registration Using Morphological Region of Interest Feature Extraction

NASA Technical Reports Server (NTRS)

Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2005-01-01

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

In this paper, we describe a novel deep convolutional neural network (CNN) that is deeper and wider than other existing deep networks for hyperspectral image classification. Unlike current state-of-the-art approaches in CNN-based hyperspectral image classification, the proposed network, called contextual deep CNN, can optimally explore local contextual interactions by jointly exploiting local spatio-spectral relationships of neighboring individual pixel vectors. The joint exploitation of the spatio-spectral information is achieved by a multi-scale convolutional filter bank used as an initial component of the proposed CNN pipeline. The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map. The joint feature map representing rich spectral and spatial properties of the hyperspectral image is then fed through a fully convolutional network that eventually predicts the corresponding label of each pixel vector. The proposed approach is tested on three benchmark data sets: the Indian Pines data set, the Salinas data set, and the University of Pavia data set. Performance comparison shows enhanced classification performance of the proposed approach over the current state-of-the-art on the three data sets.

[The forensic medical evaluation of the injuries inflicted inside the passenger compartment of a moving car equipped with the modern personal safety systems].

PubMed

Pigolkin, Yu I; Dubrovin, I A; Mosoyan, A S; Bychkov, A A

The objective of the present study was to elucidate the characteristic features of the injuries inflicted to the victims of a road traffic accident inside the passenger compartment of a moving car equipped with the modern personal safety systems. The materials available for the present work included the lesions documented in 210 drivers and 150 occupants of the car passenger compartments. Both comparative, morphometric and statistical methods were used to analyze the data obtained. The morphometric analysis included identification of the form of the injury, such as extravasation, wounds, fractures, and lesions of the internal organs (e.g. hemorrhages, ruptures, etc.), their number and localization. Special attention was given to the specific features of the injuries to the occupants of the cars equipped with the modern personal safety systems. The study has demonstrated that the form, frequency, and localization of the injuries inflicted to the victims of a road traffic accident inside the passenger car compartment (including the drivers and other occupants) can be used for determining the positions of the victims at the moment of the accident.

A practical salient region feature based 3D multi-modality registration method for medical images

NASA Astrophysics Data System (ADS)

Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

2006-03-01

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

Learning relevant features of data with multi-scale tensor networks

NASA Astrophysics Data System (ADS)

Miles Stoudenmire, E.

2018-07-01

Inspired by coarse-graining approaches used in physics, we show how similar algorithms can be adapted for data. The resulting algorithms are based on layered tree tensor networks and scale linearly with both the dimension of the input and the training set size. Computing most of the layers with an unsupervised algorithm, then optimizing just the top layer for supervised classification of the MNIST and fashion MNIST data sets gives very good results. We also discuss mixing a prior guess for supervised weights together with an unsupervised representation of the data, yielding a smaller number of features nevertheless able to give good performance.

Machine Learning for Big Data: A Study to Understand Limits at Scale

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

Sukumar, Sreenivas R.; Del-Castillo-Negrete, Carlos Emilio

This report aims to empirically understand the limits of machine learning when applied to Big Data. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical data mining and machine learning under more scrutiny, evaluation and application for gleaning insights from the data than ever before. Much is expected from algorithms without understanding their limitations at scale while dealing with massive datasets. In that context, we pose and address the following questions How does a machine learning algorithm perform on measuresmore » such as accuracy and execution time with increasing sample size and feature dimensionality? Does training with more samples guarantee better accuracy? How many features to compute for a given problem? Do more features guarantee better accuracy? Do efforts to derive and calculate more features and train on larger samples worth the effort? As problems become more complex and traditional binary classification algorithms are replaced with multi-task, multi-class categorization algorithms do parallel learners perform better? What happens to the accuracy of the learning algorithm when trained to categorize multiple classes within the same feature space? Towards finding answers to these questions, we describe the design of an empirical study and present the results. We conclude with the following observations (i) accuracy of the learning algorithm increases with increasing sample size but saturates at a point, beyond which more samples do not contribute to better accuracy/learning, (ii) the richness of the feature space dictates performance - both accuracy and training time, (iii) increased dimensionality often reflected in better performance (higher accuracy in spite of longer training times) but the improvements are not commensurate the efforts for feature computation and training and (iv) accuracy of the learning algorithms drop significantly with multi-class learners training on the same feature matrix and (v) learning algorithms perform well when categories in labeled data are independent (i.e., no relationship or hierarchy exists among categories).« less

An algorithm of adaptive scale object tracking in occlusion

NASA Astrophysics Data System (ADS)

Zhao, Congmei

2017-05-01

Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there are still some problems in handling scale variations, object occlusion, fast motions and so on. In this paper, a multi-scale kernel correlation filter algorithm based on random fern detector was proposed. The tracking task was decomposed into the target scale estimation and the translation estimation. At the same time, the Color Names features and HOG features were fused in response level to further improve the overall tracking performance of the algorithm. In addition, an online random fern classifier was trained to re-obtain the target after the target was lost. By comparing with some algorithms such as KCF, DSST, TLD, MIL, CT and CSK, experimental results show that the proposed approach could estimate the object state accurately and handle the object occlusion effectively.

Detecting Multi-scale Structures in Chandra Images of Centaurus A

NASA Astrophysics Data System (ADS)

Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

1999-12-01

Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods

NASA Astrophysics Data System (ADS)

Piao, Lin; Fu, Zuntao

2016-11-01

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods.

PubMed

Piao, Lin; Fu, Zuntao

2016-11-09

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

2008-07-01

Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

NASA Astrophysics Data System (ADS)

Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

2015-12-01

The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

Neandertal talus bones from El Sidrón site (Asturias, Spain): A 3D geometric morphometrics analysis.

PubMed

Rosas, Antonio; Ferrando, Anabel; Bastir, Markus; García-Tabernero, Antonio; Estalrrich, Almudena; Huguet, Rosa; García-Martínez, Daniel; Pastor, Juan Francisco; de la Rasilla, Marco

2017-10-01

The El Sidrón tali sample is assessed in an evolutionary framework. We aim to explore the relationship between Neandertal talus morphology and body size/shape. We test the hypothesis 1: talar Neandertal traits are influenced by body size, and the hypothesis 2: shape variables independent of body size correspond to inherited primitive features. We quantify 35 landmarks through 3D geometric morphometrics techniques to describe H. neanderthalensis-H. sapiens shape variation, by Mean Shape Comparisons, Principal Component, Phenetic Clusters, Minimum spanning tree analyses and partial least square and regression of talus shape on body variables. Shape variation correlated to body size is compared to Neandertals-Modern Humans (MH) evolutionary shape variation. The Neandertal sample is compared to early hominins. Neandertal talus presents trochlear hypertrophy, a larger equality of trochlear rims, a shorter neck, a more expanded head, curvature and an anterior location of the medial malleolar facet, an expanded and projected lateral malleolar facet and laterally expanded posterior calcaneal facet compared to MH. The Neandertal talocrural joint morphology is influenced by body size. The other Neandertal talus traits do not co-vary with it or not follow the same co-variation pattern as MH. Besides, the trochlear hypertrophy, the trochlear rims equality and the short neck could be inherited primitive features; the medial malleolar facet morphology could be an inherited primitive feature or a secondarily primitive trait; and the calcaneal posterior facet would be an autapomorphic feature of the Neandertal lineage. © 2017 Wiley Periodicals, Inc.

Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network

NASA Astrophysics Data System (ADS)

Patel, Ajay; van de Leemput, Sil C.; Prokop, Mathias; van Ginneken, Bram; Manniesing, Rashindra

2017-03-01

Segmentation of anatomical structures is fundamental in the development of computer aided diagnosis systems for cerebral pathologies. Manual annotations are laborious, time consuming and subject to human error and observer variability. Accurate quantification of cerebrospinal fluid (CSF) can be employed as a morphometric measure for diagnosis and patient outcome prediction. However, segmenting CSF in non-contrast CT images is complicated by low soft tissue contrast and image noise. In this paper we propose a state-of-the-art method using a multi-scale three-dimensional (3D) fully convolutional neural network (CNN) to automatically segment all CSF within the cranial cavity. The method is trained on a small dataset comprised of four manually annotated cerebral CT images. Quantitative evaluation of a separate test dataset of four images shows a mean Dice similarity coefficient of 0.87 +/- 0.01 and mean absolute volume difference of 4.77 +/- 2.70 %. The average prediction time was 68 seconds. Our method allows for fast and fully automated 3D segmentation of cerebral CSF in non-contrast CT, and shows promising results despite a limited amount of training data.

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

Agnes, P.; et al.

The DarkSide-50 experiment, located at the “Laboratori Nazionali del Gran Sasso (INFN)”, is based on low-radioactivity argon double phase time projection chamber, surrounded by an active liquid scintillator veto, designed for the zero background achievement. The liquid argon features sufficient self shielding and easy scalability to multi-tons scale. The impressive reduction of the 39Ar isotope (compared to the atmospheric argon), along with the excellent pulse shape discrimination, make this technology a possible candidate for the forthcoming generation of multi-ton Dark Matter experiments.

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

NASA Astrophysics Data System (ADS)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

Crowd counting via region based multi-channel convolution neural network

NASA Astrophysics Data System (ADS)

Cao, Xiaoguang; Gao, Siqi; Bai, Xiangzhi

2017-11-01

This paper proposed a novel region based multi-channel convolution neural network architecture for crowd counting. In order to effectively solve the perspective distortion in crowd datasets with a great diversity of scales, this work combines the main channel and three branch channels. These channels extract both the global and region features. And the results are used to estimate density map. Moreover, kernels with ladder-shaped sizes are designed across all the branch channels, which generate adaptive region features. Also, branch channels use relatively deep and shallow network to achieve more accurate detector. By using these strategies, the proposed architecture achieves state-of-the-art performance on ShanghaiTech datasets and competitive performance on UCF_CC_50 datasets.

Quantitative analysis of histopathological findings using image processing software.

PubMed

Horai, Yasushi; Kakimoto, Tetsuhiro; Takemoto, Kana; Tanaka, Masaharu

2017-10-01

In evaluating pathological changes in drug efficacy and toxicity studies, morphometric analysis can be quite robust. In this experiment, we examined whether morphometric changes of major pathological findings in various tissue specimens stained with hematoxylin and eosin could be recognized and quantified using image processing software. Using Tissue Studio, hypertrophy of hepatocytes and adrenocortical cells could be quantified based on the method of a previous report, but the regions of red pulp, white pulp, and marginal zones in the spleen could not be recognized when using one setting condition. Using Image-Pro Plus, lipid-derived vacuoles in the liver and mucin-derived vacuoles in the intestinal mucosa could be quantified using two criteria (area and/or roundness). Vacuoles derived from phospholipid could not be quantified when small lipid deposition coexisted in the liver and adrenal cortex. Mononuclear inflammatory cell infiltration in the liver could be quantified to some extent, except for specimens with many clustered infiltrating cells. Adipocyte size and the mean linear intercept could be quantified easily and efficiently using morphological processing and the macro tool equipped in Image-Pro Plus. These methodologies are expected to form a base system that can recognize morphometric features and analyze quantitatively pathological findings through the use of information technology.

[The morphometric characteristics of the main structural components of renal nephrons in the white rats with experimentally induced acute and chronic alcohol intoxication].

PubMed

Shcherbakova, V M

2016-01-01

The objective of the present work was to study the morphometric characteristics of the main structural components of renal nephrons in the white rats with the experimentally induced acute and chronic alcohol intoxication. We undertook the morphometric examination of the structural elements of rat kidneys with the subsequent statistical analysis of the data obtained. The results of the study give evidence of the toxic action of ethanol on all structural components of the nephron in the case of both acute and chronic alcohol intoxication. The study revealed some specific features of the development of pathological process in the renal tissue structures at different stages of alcohol intoxication. The most pronounced morphological changes were observed in the renal proximal tubules and the least pronounced ones in the structure of the renal glomeruli. The earliest morphological changes become apparent in distal convoluted tubules of the nephron; in the case of persistent alcoholemia, they first develop in the renal corpuscles and thereafter in the distal proximal tubules. The maximum changes occur in the case of acute alcohol intoxication and between 2 weeks and 2 months of chronic intoxication; they become less conspicuous during a later period.

First metatarsophalangeal joint motion in Homo sapiens: theoretical association of two-axis kinematics and specific morphometrics.

PubMed

Durrant, Michael N; McElroy, Tucker; Durrant, Lara

2012-01-01

The metatarsal head and proximal phalanx exhibit considerable asymmetry in their shape and geometry, but there is little documentation in the literature regarding the prevalence of structural characteristics that occur in a given population. Although there is a considerable volume of in vivo and in vitro experiments demonstrating first metatarsal inversion around its longitudinal axis with dorsiflexion, little is known regarding the applicability of specific morphometrics to these motions. Nine distinctive osseous characteristics in the metatarsal head and phalanx were selected based on their location, geometry, and perceived functional relationship to previous studies describing metatarsal motion as inversion with dorsiflexion. The prevalences of the chosen characteristics were determined in a cohort of 21 randomly selected skeletal specimens, 19 of which were provided by the anatomical preparation office at the University of California, San Diego, and two of which were in the possession of one of us (M.D.). The frequency of occurrence of each selected morphological characteristic in this sample and the relevant summary statistics confirm a strong association between the selected features and a conceptual two-axis kinematic model of the metatarsophalangeal joint. The selected morphometrics are consistent with inversion of the metatarsal around its longitudinal axis as it dorsiflexes.

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight

PubMed Central

Guo, Siqiu; Zhang, Tao; Song, Yulong

2018-01-01

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios. PMID:29690610

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.

PubMed

Guo, Siqiu; Zhang, Tao; Song, Yulong; Qian, Feng

2018-04-23

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

Differential diagnosis of neurodegenerative diseases using structural MRI data

PubMed Central

Koikkalainen, Juha; Rhodius-Meester, Hanneke; Tolonen, Antti; Barkhof, Frederik; Tijms, Betty; Lemstra, Afina W.; Tong, Tong; Guerrero, Ricardo; Schuh, Andreas; Ledig, Christian; Rueckert, Daniel; Soininen, Hilkka; Remes, Anne M.; Waldemar, Gunhild; Hasselbalch, Steen; Mecocci, Patrizia; van der Flier, Wiesje; Lötjönen, Jyrki

2016-01-01

Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making. PMID:27104138

Borderline Personality Features in Students: the Predicting Role of Schema, Emotion Regulation, Dissociative Experience and Suicidal Ideation.

PubMed

Sajadi, Seyede Fateme; Arshadi, Nasrin; Zargar, Yadolla; Mehrabizade Honarmand, Mahnaz; Hajjari, Zahra

2015-06-01

Numerous studies have demonstrated that early maladaptive schemas, emotional dysregulation are supposed to be the defining core of borderline personality disorder. Many studies have also found a strong association between the diagnosis of borderline personality and the occurrence of suicide ideation and dissociative symptoms. The present study was designed to investigate the relationship between borderline personality features and schema, emotion regulation, dissociative experiences and suicidal ideation among high school students in Shiraz City, Iran. In this descriptive correlational study, 300 students (150 boys and 150 girls) were selected from the high schools in Shiraz, Iran, using the multi-stage random sampling. Data were collected using some instruments including borderline personality feature scale for children, young schema questionnaire-short form, difficulties in emotion-regulation scale (DERS), dissociative experience scale and beck suicide ideation scale. Data were analyzed using the Pearson correlation coefficient and multivariate regression analysis. The results showed a significant positive correlation between schema, emotion regulation, dissociative experiences and suicide ideation with borderline personality features. Moreover, the results of multivariate regression analysis suggested that among the studied variables, schema was the most effective predicting variable of borderline features (P < 0.001). The findings of this study are in accordance with findings from previous studies, and generally show a meaningful association between schema, emotion regulation, dissociative experiences, and suicide ideation with borderline personality features.

A new interpretation of the bee fossil Melitta willardi Cockerell (Hymenoptera, Melittidae) based on geometric morphometrics of the wing.

PubMed

Dewulf, Alexandre; De Meulemeester, Thibaut; Dehon, Manuel; Engel, Michael S; Michez, Denis

2014-01-01

Although bees are one of the major lineages of pollinators and are today quite diverse, few well-preserved fossils are available from which to establish the tempo of their diversification/extinction since the Early Cretaceous. Here we present a reassessment of the taxonomic affinities of Melitta willardiCockerell 1909, preserved as a compression fossil from the Florissant shales of Colorado, USA. Based on geometric morphometric wing shape analyses M. willardi cannot be confidently assigned to the genus Melitta Kirby (Anthophila, Melittidae). Instead, the species exhibits phenotypic affinity with the subfamily Andreninae (Anthophila, Andrenidae), but does not appear to belong to any of the known genera therein. Accordingly, we describe a new genus, Andrenopteryx gen. n., based on wing shape as well as additional morphological features and to accommodate M. willardi. The new combination Andrenopteryx willardi (Cockerell) is established.

A new interpretation of the bee fossil Melitta willardi Cockerell (Hymenoptera, Melittidae) based on geometric morphometrics of the wing

PubMed Central

Dewulf, Alexandre; De Meulemeester, Thibaut; Dehon, Manuel; Engel, Michael S.; Michez, Denis

2014-01-01

Abstract Although bees are one of the major lineages of pollinators and are today quite diverse, few well-preserved fossils are available from which to establish the tempo of their diversification/extinction since the Early Cretaceous. Here we present a reassessment of the taxonomic affinities of Melitta willardi Cockerell 1909, preserved as a compression fossil from the Florissant shales of Colorado, USA. Based on geometric morphometric wing shape analyses M. willardi cannot be confidently assigned to the genus Melitta Kirby (Anthophila, Melittidae). Instead, the species exhibits phenotypic affinity with the subfamily Andreninae (Anthophila, Andrenidae), but does not appear to belong to any of the known genera therein. Accordingly, we describe a new genus, Andrenopteryx gen. n., based on wing shape as well as additional morphological features and to accommodate M. willardi. The new combination Andrenopteryx willardi (Cockerell) is established. PMID:24715773

Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events

USDA-ARS?s Scientific Manuscript database

Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...

Daily monitoring of vegetation conditions and evapotranspiration at field scale by fusing multi-satellite images

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires frequent remote sensing observations. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for vegetation monitoring. The medium spatial resolution (10-100m) sensors are su...

Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network.

PubMed

Prasoon, Adhish; Petersen, Kersten; Igel, Christian; Lauze, François; Dam, Erik; Nielsen, Mads

2013-01-01

Segmentation of anatomical structures in medical images is often based on a voxel/pixel classification approach. Deep learning systems, such as convolutional neural networks (CNNs), can infer a hierarchical representation of images that fosters categorization. We propose a novel system for voxel classification integrating three 2D CNNs, which have a one-to-one association with the xy, yz and zx planes of 3D image, respectively. We applied our method to the segmentation of tibial cartilage in low field knee MRI scans and tested it on 114 unseen scans. Although our method uses only 2D features at a single scale, it performs better than a state-of-the-art method using 3D multi-scale features. In the latter approach, the features and the classifier have been carefully adapted to the problem at hand. That we were able to get better results by a deep learning architecture that autonomously learns the features from the images is the main insight of this study.

A general purpose feature extractor for light detection and ranging data.

PubMed

Li, Yangming; Olson, Edwin B

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.

A General Purpose Feature Extractor for Light Detection and Ranging Data

PubMed Central

Li, Yangming; Olson, Edwin B.

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset. PMID:22163474

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

Tightly integrated single- and multi-crystal data collection strategy calculation and parallelized data processing in JBluIce beamline control system

PubMed Central

Pothineni, Sudhir Babu; Venugopalan, Nagarajan; Ogata, Craig M.; Hilgart, Mark C.; Stepanov, Sergey; Sanishvili, Ruslan; Becker, Michael; Winter, Graeme; Sauter, Nicholas K.; Smith, Janet L.; Fischetti, Robert F.

2014-01-01

The calculation of single- and multi-crystal data collection strategies and a data processing pipeline have been tightly integrated into the macromolecular crystallographic data acquisition and beamline control software JBluIce. Both tasks employ wrapper scripts around existing crystallographic software. JBluIce executes scripts through a distributed resource management system to make efficient use of all available computing resources through parallel processing. The JBluIce single-crystal data collection strategy feature uses a choice of strategy programs to help users rank sample crystals and collect data. The strategy results can be conveniently exported to a data collection run. The JBluIce multi-crystal strategy feature calculates a collection strategy to optimize coverage of reciprocal space in cases where incomplete data are available from previous samples. The JBluIce data processing runs simultaneously with data collection using a choice of data reduction wrappers for integration and scaling of newly collected data, with an option for merging with pre-existing data. Data are processed separately if collected from multiple sites on a crystal or from multiple crystals, then scaled and merged. Results from all strategy and processing calculations are displayed in relevant tabs of JBluIce. PMID:25484844

Tightly integrated single- and multi-crystal data collection strategy calculation and parallelized data processing in JBluIce beamline control system

DOE PAGES

Pothineni, Sudhir Babu; Venugopalan, Nagarajan; Ogata, Craig M.; ...

2014-11-18

The calculation of single- and multi-crystal data collection strategies and a data processing pipeline have been tightly integrated into the macromolecular crystallographic data acquisition and beamline control software JBluIce. Both tasks employ wrapper scripts around existing crystallographic software. JBluIce executes scripts through a distributed resource management system to make efficient use of all available computing resources through parallel processing. The JBluIce single-crystal data collection strategy feature uses a choice of strategy programs to help users rank sample crystals and collect data. The strategy results can be conveniently exported to a data collection run. The JBluIce multi-crystal strategy feature calculates amore » collection strategy to optimize coverage of reciprocal space in cases where incomplete data are available from previous samples. The JBluIce data processing runs simultaneously with data collection using a choice of data reduction wrappers for integration and scaling of newly collected data, with an option for merging with pre-existing data. Data are processed separately if collected from multiple sites on a crystal or from multiple crystals, then scaled and merged. Results from all strategy and processing calculations are displayed in relevant tabs of JBluIce.« less

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.

A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

PubMed

Xue, Xiaoming; Zhou, Jianzhong

2017-01-01

To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Use of terrestrial laser scanning for the documentation of quaternary caves

NASA Astrophysics Data System (ADS)

Tyszkowski, Sebastian; Kramkowski, Mateusz; Wiśniewska, Daria; Urban, Jan

2016-04-01

Due to the nature of their occurrence and genesis, caves in the Polish Lowlands represent a peculiarity of geological heritage, unique on the European scale. They are developed in Quaternary deposits, mostly at the contact of slabs or irregular bodies of cemented glacial or glaciofluvial deposits: conglomerates and sandstones, with unconsolidated deposits, mostly sands, gravels and clays. So far, 20 such caves have been recorded in Polish Lowlands. Most caves are only several meters long, the largest one is over 60 m long. Regardless of their origins, the character of host rocks is the reason that processes leading to their formation are simultaneously the destroying processes. Thus, the studied caves, as well as other caves of this region, are unstable, gradually evolving objects. The changes taking place in them are continuous and intense enough, therefore the documentation of their shape with the greatest possible accuracy and resolution becomes crucial. Such possibility can provide the technique of laser scanning. In 2014 three caves, including one recently discovered, were scanned using the TLS. Measurements of caves and their surroundings were conducted in May and July 2014 with a scanner RIEGL VZ-4000. Point clouds from several scanner positions were combined using the module Multi Station Adjustment in the RiSCAN software. This module allows to connect point clouds from successive positions without any objects of reference. After the merger of point clouds from individual positions and their filtration, a collection of several million points was obtained. The number of points projected on the wall was over 20 000 per m2. The using of TLS enabled to present the morphometric features impossible to obtain using traditional methods. High density of the point clouds allows registering even small details on the cave walls, as well as monitoring leaching, falling, grinding and flaking processes taking place in them. Thus, the most important advantage of the TLS is the "visual protection" of these objects unstable in geological time-scale. This study is a contribution to the Virtual Institute of Integrated Climate and Landscape Evolution Analyses - ICLEA- of the Helmholtz Association, Grant No VH-VI-415

Histomorphometric analysis of collagen architecture of auricular keloids in an Asian population.

PubMed

Chong, Yosep; Park, Tae Hwan; Seo, Sang won; Chang, Choong Hyun

2015-03-01

Keloids are a pathologic condition of the reparative process, which present as excessive scar formation that involves various cells and cytokines. Many studies focusing on the histologic feature of keloids, however, have shown discordant results without consideration of architectural aspect of collagen structure. The purpose of this study was to demonstrate a schematic illustration of collagen architecture of keloids, specifically auricular keloids, and to analyze each part on the histomorphologic and morphometric basis. Thirty-nine surgically excised auricular keloids were retrieved from the file of Kangbuk Samsung Hospital. After exhaustive histomorphologic analysis, 3 distinctive structural parts, keloidal collagen, organizing collagen, and proliferating core collagen, were identified and mapped in every case. Cellularity of fibroblasts, blood vessel density, degree of inflammatory cell infiltration, and mast cells counts using Masson trichrome stain, Van Gieson stain, toluidine blue stain, and immunohistochemical stains for CD31 and smooth muscle actin were analyzed in each part of each case. Morphometric analysis on these parameters using ImageJ software was performed using 3 representative images of each part. Three parts were histomorphologically distinct by shape and array of collagen bundles, fibroblasts cellularity, blood vessel density, degree of inflammatory cells, and mast cell infiltration. Morphometric analysis revealed statistically significant difference between each part in fibroblasts cellularity, blood vessel density, degree of inflammatory cell infiltration, and mast cells count. All parameters were exceedingly high in whorling hypercellular fibrous nodules in proliferating core collagen showing simultaneous changes in other parts. Morphologically and morphometrically, 3 distinctive parts were identified in auricular keloids. Mast cell infiltrations, blood vessel density, and fibroblast cellularity are simultaneously increased or decreased according to these parts. Proliferating core collagen might serve as a proliferating center of keloids and might be a key portion for tumor growth and recurrence.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

PubMed Central

Chang, Chi-Ying; Chang, Chia-Chi; Hsiao, Tzu-Chien

2013-01-01

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes. PMID:24240806

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I N; Tavakoli, M; Malik, R A

2011-10-01

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation. Copyright © 2011 Elsevier B.V. All rights reserved.

Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

PubMed

Savala, Rajiv; Dey, Pranab; Gupta, Nalini

2018-03-01

To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem. In this article, we attempted to build an artificial neural network (ANN) model from the cytological and morphometric features of the FNAC smears of thyroid to distinguish FA from FC. The cytological features and morphometric analysis were done on the FNAC smears of histology proven cases of FA (26) and FC (31). The cytological features were analysed semi-quantitatively by two independent observers (RS and PD). These data were used to make an ANN model to differentiate FA versus FC on FNAC material. The performance of this ANN model was assessed by analysing the confusion matrix and receiving operator curve. There were 39 cases in training set, 9 cases each in validation and test sets. In the test group, ANN model successfully distinguished all cases (9/9) of FA and FC. The area under receiver operating curve was 1. The present ANN model is efficient to diagnose follicular adenoma and carcinoma cases on cytology smears without any error. In future, this ANN model will be able to diagnose follicular adenoma and carcinoma cases on thyroid aspirate. This study has immense potential in future. This is an open ended ANN model and more parameters and more cases can be included to make the model much stronger. © 2017 Wiley Periodicals, Inc.

On the formalization of multi-scale and multi-science processes for integrative biology

PubMed Central

Díaz-Zuccarini, Vanessa; Pichardo-Almarza, César

2011-01-01

The aim of this work is to introduce the general concept of ‘Bond Graph’ (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the ‘elements’ of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The ‘effort’ and ‘flow’ variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view. PMID:22670211

Insights into subglacial eruptions based on geomorphometry: Broad scale analysis of subglacial edifices in Iceland

NASA Astrophysics Data System (ADS)

Pedersen, Gro; Grosse, Pablo

2014-05-01

The two main types of subglacial volcanic edifices, tuyas and tindars, have classicaly been known for their distinct morphometric characteristics. Tuyas are roughly equidimensional, steep-sided, flat topped mountains, while tindars are elongate, linear, steep sided, serrated ridges. In particular, the passage zone is morphometrically diagnostic, with a break in slope marking the transition from steep scree flanks to a low sloping lava cap [e.g. 1]. The passage zone thereby records the englacial water level coeval with delta formation and thereby provides important paleoenvironmental parameters regarding ice thickness, paleo-ice surface and the eruption environment. This study utilizes these morphometric characteristics to make a broad scale assessment of Icelandic subglacial edifices in the neovolcanic zone based on the TK-50 digital elevation model (20m/pixel) from the company Loftmyndir ehf. The edifice boundaries are delimited by concave breaks in slope around their bases and the passage zones are extracted as convex breaks in slope. This extraction is performed through object-based image analysis of slope and profile curvature maps with the eCognition program [2]. The MORVOLC code [3] is then used to calculate several morphometric parameters for each edifice: volume, edifice height, passage zone height, slope, base area, base width, ellipticity and irregularity. Analysis of the morphometric parameters allows grouping of subglacial edifices by to volume, with a continuum of landforms ranging from small tindars (group 1) to large tuyas (group 3), with an intermediate complex group of edifices (group 2). The plan shape indexes (ellipticity and irregularity) and the strike of main elongation show a first order correlation with the 3 classes and groups. Furthermore, correlations of passage zone heights, volumes and information regarding englacial lake stability allows us to investigate several aspects of tuya formation, including(1) spatial distribution of tuya sizes in rift and plume dominated volcanic systems, (2) estimation of paleo-ice surface height based on passage zone elevation, and (3) correlation between eruption size, approximate paleo-ice surface height and meltwater drainage. This study shows how a new semi-automated geomorphometric analysis of subglacial volcanic morphologies can provide information on the eruption environment. Furthermore, the technique can be used for submarine and planetary volcanic environments given a sufficiently accurate topographic model, providing a consistent approach to compare volcanic edifices in different environments. [1] Jones (1969) Quarterly Journal of the Geological Society 124, 197-211. [2] Benz et al. (2004) ISPRS Journal of photogrammetry & remote sensing 58, 239-258. [3] Grosse et al. (2012) Geomorphology 136, 114-131.

Morphometry of network and nonnetwork space of basins

NASA Astrophysics Data System (ADS)

Chockalingam, L.; Daya Sagar, B. S.

2005-08-01

Morphometric analysis of channel network of a basin provides several scale- independent measures. To better characterize basin morphology, one requires, besides channel morphometric properties, scale-independent but shape-dependent measures to record the sensitive differences in the morphological organization of nonnetwork spaces. These spaces are planar forms of hillslopes or the retained portion after subtracting the channel network from the basin space. The principal aim of this paper is to focus on explaining the importance of alternative scale-independent but shape-dependent measures of nonnetwork spaces of basins. Toward this goal, we explore how mathematical morphology-based decomposition procedures can be used to derive basic measures required to quantify estimates, such as dimensionless power laws, that are useful to express the importance of characteristics of nonnetwork spaces via decomposition rules. We demonstrate our results through characterization of nonnetwork spaces of eight subbasins of the Gunung Ledang region of peninsular Malaysia. We decompose the nonnetwork spaces of eight fourth-order basins in a two-dimensional discrete space into simple nonoverlapping disks (NODs) of various sizes by employing morphological transformations. Furthermore, we show relationships between the dimensions estimated via morphometries of the network and their corresponding nonnetwork spaces. This study can be extended to characterize hillslope morphologies, where decomposition of three-dimensional hillslopes needs to be addressed.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

Comparison of the morphometric features of the left and right horse kidneys: a stereological approach.

PubMed

Bolat, D; Bahar, S; Tipirdamaz, S; Selcuk, M L

2013-12-01

The aims of this study were to determine the total volume of the horse kidney and volume fractions of its functional subcomponents (cortex, medulla, renal pelvis) using stereological methods and investigate any possible difference in the functional subcomponents of the right and left kidneys that may arise from differences in shape. The study was carried out on the kidneys of 5 horses of different breed and sex. The weight of the kidneys was measured by a digital scale, and kidney volume was calculated by Archimedes' principle. Total kidney volume and volume fractions of subcomponents of the right and left kidneys were estimated by the Cavalieri's principle. The weights of the right and left kidneys were 550 ± 25 g and 585 ± 23 g, respectively. The volumes of the right and left kidneys estimated using the Cavalieri method were 542 ± 46 ml and 581 ± 29 ml. The relative organ weight of the kidneys was calculated as 1:330. The densities of the right and left kidneys were determined to be 1.01 and 1.00, respectively. The mean volume fractions of the cortex, medulla and renal pelvis were determined as 55.6, 42.7 and 1.7 in both kidneys. No statistically significant difference existed between morphometric data pertaining to the right and left kidneys (P > 0.05). To determine precisely whether differences in shape cause any difference in the functional subcomponents of the right and left kidneys requires further investigation of differences in the number of microscopically functional unit of the kidney such as renal glomeruli and nephrons. © 2013 Blackwell Verlag GmbH.

SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation.

PubMed

Xue, Yuan; Xu, Tao; Zhang, Han; Long, L Rodney; Huang, Xiaolei

2018-05-03

Inspired by classic Generative Adversarial Networks (GANs), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single scalar real/fake output of a classic GAN's discriminator may be ineffective in producing stable and sufficient gradient feedback to the networks. Instead, we use a fully convolutional neural network as the segmentor to generate segmentation label maps, and propose a novel adversarial critic network with a multi-scale L 1 loss function to force the critic and segmentor to learn both global and local features that capture long- and short-range spatial relationships between pixels. In our SegAN framework, the segmentor and critic networks are trained in an alternating fashion in a min-max game: The critic is trained by maximizing a multi-scale loss function, while the segmentor is trained with only gradients passed along by the critic, with the aim to minimize the multi-scale loss function. We show that such a SegAN framework is more effective and stable for the segmentation task, and it leads to better performance than the state-of-the-art U-net segmentation method. We tested our SegAN method using datasets from the MICCAI BRATS brain tumor segmentation challenge. Extensive experimental results demonstrate the effectiveness of the proposed SegAN with multi-scale loss: on BRATS 2013 SegAN gives performance comparable to the state-of-the-art for whole tumor and tumor core segmentation while achieves better precision and sensitivity for Gd-enhance tumor core segmentation; on BRATS 2015 SegAN achieves better performance than the state-of-the-art in both dice score and precision.

Lie-algebraic classification of effective theories with enhanced soft limits

NASA Astrophysics Data System (ADS)

Bogers, Mark P.; Brauner, Tomáš

2018-05-01

A great deal of effort has recently been invested in developing methods of calculating scattering amplitudes that bypass the traditional construction based on Lagrangians and Feynman rules. Motivated by this progress, we investigate the long-wavelength behavior of scattering amplitudes of massless scalar particles: Nambu-Goldstone (NG) bosons. The low-energy dynamics of NG bosons is governed by the underlying spontaneously broken symmetry, which likewise allows one to bypass the Lagrangian and connect the scaling of the scattering amplitudes directly to the Lie algebra of the symmetry generators. We focus on theories with enhanced soft limits, where the scattering amplitudes scale with a higher power of momentum than expected based on the mere existence of Adler's zero. Our approach is complementary to that developed recently in ref. [1], and in the first step we reproduce their result. That is, as far as Lorentz-invariant theories with a single physical NG boson are concerned, we find no other nontrivial theories featuring enhanced soft limits beyond the already well-known ones: the Galileon and the Dirac-Born-Infeld (DBI) scalar. Next, we show that in a certain sense, these theories do not admit a nontrivial generalization to non-Abelian internal symmetries. Namely, for compact internal symmetry groups, all NG bosons featuring enhanced soft limits necessarily belong to the center of the group. For noncompact symmetry groups such as the ISO( n) group featured by some multi-Galileon theories, these NG bosons then necessarily belong to an Abelian normal subgroup. The Lie-algebraic consistency constraints admit two infinite classes of solutions, generalizing the known multi-Galileon and multi-flavor DBI theories.

Multi-scale Gaussian representation and outline-learning based cell image segmentation.

PubMed

Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli

2013-01-01

High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.

Multi-scale Gaussian representation and outline-learning based cell image segmentation

PubMed Central

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

Quantifying shapes of volcanoes on Venus

NASA Technical Reports Server (NTRS)

Garvin, J. B.

1994-01-01

A large population of discrete volcanic edifices on Venus has been identified and cataloged by means of Magellan SAR images, and an extensive database describing thousands of such features is in final preparation. Those volcanoes categorized as Intermediate to Large in scale, while relatively small in number (approx. 400), nonetheless constitute a significant volumetric component (approx. 13 x 10(exp 6) cu km) of the total apparent crustal volume of Venus. For this reason, we have focused attention on the morphometry of a representative suite of the larger edifices on Venus and, in particular, on ways of constraining the eruptive histories of these possibly geologically youthful landforms. Our approach has been to determine a series of reproducible morphometric parameters for as many of the discrete volcanoes on Venus that have an obvious expression within the global altimetry data acquired by Magellan. In addition, we have attempted to objectively and systematically define the mathematical essence of the shapes of these larger volcanoes using a polynomial cross-section approximation involving only parameters easily measured from digital topography, as well as with simple surface cylindrical harmonic expansions. The goal is to reduce the topological complexities of the larger edifices to a few simple parameters which can then be related to similar expressions for well-studied terrestrial and martian features.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Directional Multi-scale Modeling of High-Resolution Computed Tomography (HRCT) Lung Images for Diffuse Lung Disease Classification

NASA Astrophysics Data System (ADS)

Vo, Kiet T.; Sowmya, Arcot

A directional multi-scale modeling scheme based on wavelet and contourlet transforms is employed to describe HRCT lung image textures for classifying four diffuse lung disease patterns: normal, emphysema, ground glass opacity (GGO) and honey-combing. Generalized Gaussian density parameters are used to represent the detail sub-band features obtained by wavelet and contourlet transforms. In addition, support vector machines (SVMs) with excellent performance in a variety of pattern classification problems are used as classifier. The method is tested on a collection of 89 slices from 38 patients, each slice of size 512x512, 16 bits/pixel in DICOM format. The dataset contains 70,000 ROIs of those slices marked by experienced radiologists. We employ this technique at different wavelet and contourlet transform scales for diffuse lung disease classification. The technique presented here has best overall sensitivity 93.40% and specificity 98.40%.

Multi-scale Imaging of Cellular and Sub-cellular Structures using Scanning Probe Recognition Microscopy.

NASA Astrophysics Data System (ADS)

Chen, Q.; Rice, A. F.

2005-03-01

Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).

Multi-modal imaging predicts memory performance in normal aging and cognitive decline.

PubMed

Walhovd, K B; Fjell, A M; Dale, A M; McEvoy, L K; Brewer, J; Karow, D S; Salmon, D P; Fennema-Notestine, C

2010-07-01

This study (n=161) related morphometric MR imaging, FDG-PET and APOE genotype to memory scores in normal controls (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Stepwise regression analyses focused on morphometric and metabolic characteristics of the episodic memory network: hippocampus, entorhinal, parahippocampal, retrosplenial, posterior cingulate, precuneus, inferior parietal, and lateral orbitofrontal cortices. In NC, hippocampal metabolism predicted learning; entorhinal metabolism predicted recognition; and hippocampal metabolism predicted recall. In MCI, thickness of the entorhinal and precuneus cortices predicted learning, while parahippocampal metabolism predicted recognition. In AD, posterior cingulate cortical thickness predicted learning, while APOE genotype predicted recognition. In the total sample, hippocampal volume and metabolism, cortical thickness of the precuneus, and inferior parietal metabolism predicted learning; hippocampal volume and metabolism, parahippocampal thickness and APOE genotype predicted recognition. Imaging methods appear complementary and differentially sensitive to memory in health and disease. Medial temporal and parietal metabolism and morphometry best explained memory variance. Medial temporal characteristics were related to learning, recall and recognition, while parietal structures only predicted learning. Copyright 2008. Published by Elsevier Inc.

Intermediate scale plasma density irregularities in the polar ionosphere inferred from radio occultation

NASA Astrophysics Data System (ADS)

Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O. P.; Butala, M.; Mannucci, A. J.

2014-12-01

In this research, we report intermediate scale plasma density irregularities in the high-latitude ionosphere inferred from high-resolution radio occultation (RO) measurements in the CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) - GPS (Global Positioning System) satellites radio link. The high inclination of the CASSIOPE satellite and high rate of signal receptionby the occultation antenna of the GPS Attitude, Positioning and Profiling (GAP) instrument on the Enhanced Polar Outflow Probe platform on CASSIOPE enable a high temporal and spatial resolution investigation of the dynamics of the polar ionosphere, magnetosphere-ionospherecoupling, solar wind effects, etc. with unprecedented details compared to that possible in the past. We have carried out high spatial resolution analysis in altitude and geomagnetic latitude of scintillation-producing plasma density irregularities in the polar ionosphere. Intermediate scale, scintillation-producing plasma density irregularities, which corresponds to 2 to 40 km spatial scales were inferred by applying multi-scale spectral analysis on the RO phase delay measurements. Using our multi-scale spectral analysis approach and Polar Operational Environmental Satellites (POES) and Defense Meteorological Satellite Program (DMSP) observations, we infer that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap regions. In specific terms, we found that large length scales and and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap region. Hence, the irregularity scales and phase scintillation characteristics are a function of the solar wind and the magnetospheric forcing. Multi-scale analysis may become a powerful diagnostic tool for characterizing how the ionosphere is dynamically driven by these factors.

Homo floresiensis Contextualized: A Geometric Morphometric Comparative Analysis of Fossil and Pathological Human Samples

PubMed Central

Baab, Karen L.; McNulty, Kieran P.; Harvati, Katerina

2013-01-01

The origin of hominins found on the remote Indonesian island of Flores remains highly contentious. These specimens may represent a new hominin species, Homo floresiensis, descended from a local population of Homo erectus or from an earlier (pre-H. erectus) migration of a small-bodied and small-brained hominin out of Africa. Alternatively, some workers suggest that some or all of the specimens recovered from Liang Bua are pathological members of a small-bodied modern human population. Pathological conditions proposed to explain their documented anatomical features include microcephaly, myxoedematous endemic hypothyroidism (“cretinism”) and Laron syndrome (primary growth hormone insensitivity). This study evaluates evolutionary and pathological hypotheses through comparative analysis of cranial morphology. Geometric morphometric analyses of landmark data show that the sole Flores cranium (LB1) is clearly distinct from healthy modern humans and from those exhibiting hypothyroidism and Laron syndrome. Modern human microcephalic specimens converge, to some extent, on crania of extinct species of Homo. However in the features that distinguish these two groups, LB1 consistently groups with fossil hominins and is most similar to H. erectus. Our study provides further support for recognizing the Flores hominins as a distinct species, H. floresiensis, whose affinities lie with archaic Homo. PMID:23874886

Exploring Eucladoceros ecomorphology using geometric morphometrics.

PubMed

Curran, Sabrina C

2015-01-01

An increasingly common method for reconstructing paleoenvironmental parameters of hominin sites is ecological functional morphology (ecomorphology). This study provides a geometric morphometric study of cervid rearlimb morphology as it relates to phylogeny, size, and ecomorphology. These methods are then applied to an extinct Pleistocene cervid, Eucladoceros, which is found in some of the earliest hominin-occupied sites in Eurasia. Variation in cervid postcranial functional morphology associated with different habitats can be summarized as trade-offs between joint stability versus mobility and rapid movement versus power-generation. Cervids in open habitats emphasize limb stability to avoid joint dislocation during rapid flight from predators. Closed-adapted cervids require more joint mobility to rapidly switch directions in complex habitats. Two skeletal features (of the tibia and calcaneus) have significant phylogenetic signals, while two (the femur and third phalanx) do not. Additionally, morphology of two of these features (tibia and third phalanx) were correlated with body size. For the tibial analysis (but not the third phalanx) this correlation was ameliorated when phylogeny was taken into account. Eucladoceros specimens from France and Romania fall on the more open side of the habitat continuum, a result that is at odds with reconstructions of their diet as browsers, suggesting that they may have had a behavioral regime unlike any extant cervid. © 2014 Wiley Periodicals, Inc.

Interpretations of gravity and magnetic anomalies in the Songliao Basin with Wavelet Multi-scale Decomposition

NASA Astrophysics Data System (ADS)

Li, Changbo; Wang, Liangshu; Sun, Bin; Feng, Runhai; Wu, Yongjing

2015-09-01

In this paper, we introduce the method of Wavelet Multi-scale Decomposition (WMD) combined with Power Spectrum Analysis (PSA) for the separation of regional gravity and magnetic anomalies. The Songliao Basin is situated between the Siberian Plate and the North China Plate, and its main structural trend of gravity and magnetic anomaly fields is NNE. The study area shows a significant feature of deep collage-type construction. According to the feature of gravity field, the region was divided into five sub-regions. The gravity and magnetic fields of the Songliao Basin were separated using WMD with a 4th order separation. The apparent depth of anomalies in each order was determined by Logarithmic PSA. Then, the shallow high-frequency anomalies were removed and the 2nd-4th order wavelet detail anomalies were used to study the basin's major faults. Twenty-six faults within the basement were recognized. The 4th order wavelet approximate anomalies were used for the inversion of the Moho discontinuity and the Curie isothermal surface.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of the US3D Code for Advanced Compressible and Reacting Flow Simulations

NASA Technical Reports Server (NTRS)

Candler, Graham V.; Johnson, Heath B.; Nompelis, Ioannis; Subbareddy, Pramod K.; Drayna, Travis W.; Gidzak, Vladimyr; Barnhardt, Michael D.

2015-01-01

Aerothermodynamics and hypersonic flows involve complex multi-disciplinary physics, including finite-rate gas-phase kinetics, finite-rate internal energy relaxation, gas-surface interactions with finite-rate oxidation and sublimation, transition to turbulence, large-scale unsteadiness, shock-boundary layer interactions, fluid-structure interactions, and thermal protection system ablation and thermal response. Many of the flows have a large range of length and time scales, requiring large computational grids, implicit time integration, and large solution run times. The University of Minnesota NASA US3D code was designed for the simulation of these complex, highly-coupled flows. It has many of the features of the well-established DPLR code, but uses unstructured grids and has many advanced numerical capabilities and physical models for multi-physics problems. The main capabilities of the code are described, the physical modeling approaches are discussed, the different types of numerical flux functions and time integration approaches are outlined, and the parallelization strategy is overviewed. Comparisons between US3D and the NASA DPLR code are presented, and several advanced simulations are presented to illustrate some of novel features of the code.

Modeling process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-02-01

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

PubMed

Zhu, Guohun; Li, Yan; Wen, Peng Paul; Wang, Shuaifang

2015-01-01

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Discontinuous Galerkin methods for modeling Hurricane storm surge

NASA Astrophysics Data System (ADS)

Dawson, Clint; Kubatko, Ethan J.; Westerink, Joannes J.; Trahan, Corey; Mirabito, Christopher; Michoski, Craig; Panda, Nishant

2011-09-01

Storm surge due to hurricanes and tropical storms can result in significant loss of life, property damage, and long-term damage to coastal ecosystems and landscapes. Computer modeling of storm surge can be used for two primary purposes: forecasting of surge as storms approach land for emergency planning and evacuation of coastal populations, and hindcasting of storms for determining risk, development of mitigation strategies, coastal restoration and sustainability. Storm surge is modeled using the shallow water equations, coupled with wind forcing and in some events, models of wave energy. In this paper, we will describe a depth-averaged (2D) model of circulation in spherical coordinates. Tides, riverine forcing, atmospheric pressure, bottom friction, the Coriolis effect and wind stress are all important for characterizing the inundation due to surge. The problem is inherently multi-scale, both in space and time. To model these problems accurately requires significant investments in acquiring high-fidelity input (bathymetry, bottom friction characteristics, land cover data, river flow rates, levees, raised roads and railways, etc.), accurate discretization of the computational domain using unstructured finite element meshes, and numerical methods capable of capturing highly advective flows, wetting and drying, and multi-scale features of the solution. The discontinuous Galerkin (DG) method appears to allow for many of the features necessary to accurately capture storm surge physics. The DG method was developed for modeling shocks and advection-dominated flows on unstructured finite element meshes. It easily allows for adaptivity in both mesh ( h) and polynomial order ( p) for capturing multi-scale spatial events. Mass conservative wetting and drying algorithms can be formulated within the DG method. In this paper, we will describe the application of the DG method to hurricane storm surge. We discuss the general formulation, and new features which have been added to the model to better capture surge in complex coastal environments. These features include modifications to the method to handle spherical coordinates and maintain still flows, improvements in the stability post-processing (i.e. slope-limiting), and the modeling of internal barriers for capturing overtopping of levees and other structures. We will focus on applications of the model to recent events in the Gulf of Mexico, including Hurricane Ike.

Multi-scale structures of turbulent magnetic reconnection

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

Nakamura, T. K. M., E-mail: takuma.nakamura@oeaw.ac.at; Nakamura, R.; Narita, Y.

2016-05-15

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in whichmore » modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.« less

Multi-scale structures of turbulent magnetic reconnection

NASA Astrophysics Data System (ADS)

Nakamura, T. K. M.; Nakamura, R.; Narita, Y.; Baumjohann, W.; Daughton, W.

2016-05-01

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in which modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Space Technology 5 Multi-point Observations of Field-aligned Currents: Temporal Variability of Meso-Scale Structures

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2007-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of - 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approx. 1 min for meso-scale currents and approx. 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

USGS Publications Warehouse

Maxwell, S.K.; Schmidt, Gail L.; Storey, James C.

2007-01-01

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

3D ion-scale dynamics of BBFs and their associated emissions in Earth's magnetotail using 3D hybrid simulations and MMS multi-spacecraft observations

NASA Astrophysics Data System (ADS)

Breuillard, H.; Aunai, N.; Le Contel, O.; Catapano, F.; Alexandrova, A.; Retino, A.; Cozzani, G.; Gershman, D. J.; Giles, B. L.; Khotyaintsev, Y. V.; Lindqvist, P. A.; Ergun, R.; Strangeway, R. J.; Russell, C. T.; Magnes, W.; Plaschke, F.; Nakamura, R.; Fuselier, S. A.; Turner, D. L.; Schwartz, S. J.; Torbert, R. B.; Burch, J.

2017-12-01

Transient and localized jets of hot plasma, also known as Bursty Bulk Flows (BBFs), play a crucial role in Earth's magnetotail dynamics because the energy input from the solar wind is partly dissipated in their vicinity, notably in their embedded dipolarization front (DF). This dissipation is in the form of strong low-frequency waves that can heat and accelerate energetic particles up to the high-latitude plasma sheet. The ion-scale dynamics of BBFs have been revealed by the Cluster and THEMIS multi-spacecraft missions. However, the dynamics of BBF propagation in the magnetotail are still under debate due to instrumental limitations and spacecraft separation distances, as well as simulation limitations. The NASA/MMS fleet, which features unprecedented high time resolution instruments and four spacecraft separated by kinetic-scale distances, has also shown recently that the DF normal dynamics and its associated emissions are below the ion gyroradius scale in this region. Large variations in the dawn-dusk direction were also observed. However, most of large-scale simulations are using the MHD approach and are assumed 2D in the XZ plane. Thus, in this study we take advantage of both multi-spacecraft observations by MMS and large-scale 3D hybrid simulations to investigate the 3D dynamics of BBFs and their associated emissions at ion-scale in Earth's magnetotail, and their impact on particle heating and acceleration.

Model of human recurrent respiratory papilloma on chicken embryo chorioallantoic membrane for tumor angiogenesis research.

PubMed

Uloza, Virgilijus; Kuzminienė, Alina; Palubinskienė, Jolita; Balnytė, Ingrida; Ulozienė, Ingrida; Valančiūtė, Angelija

2017-07-01

We aimed to develop a chick embryo chorioallantoic membrane (CAM) model of recurrent respiratory papilloma (RPP) and to evaluate its morphological and morphometric characteristics, together with angiogenic features. Fresh RRP tissue samples obtained from 13 patients were implanted in 174 chick embryo CAMs. Morphological, morphometric, and angiogenic changes in the CAM and chorionic epithelium were evaluated up until 7 days after the implantation. Immunohistochemical analysis (34βE12, Ki-67, MMP-9, PCNA, and Sambucus nigra staining) was performed to detect cytokeratins and endothelial cells and to evaluate proliferative capacity of the RRP before and after implantation on the CAM. The implanted RRP tissue samples survived on CAM in 73% of cases while retaining their essential morphologic characteristics and proliferative capacity of the original tumor. Implants induced thickening of both the CAM (241-560%, p=0.001) and the chorionic epithelium (107-151%, p=0.001), while the number of blood vessels (37-85%, p=0.001) in the CAM increased. The results of the present study confirmed that chick embryo CAM is a relevant host for serving as a medium for RRP fresh tissue implantation. The CAM assay demonstrated the specific RRP tumor growth pattern after implantation and provided the first morphological and morphometric characterization of the RRP CAM model that opens new horizons in studying this disease.

A minimally invasive methodology based on morphometric parameters for day 2 embryo quality assessment.

PubMed

Molina, Inmaculada; Lázaro-Ibáñez, Elisa; Pertusa, Jose; Debón, Ana; Martínez-Sanchís, Juan Vicente; Pellicer, Antonio

2014-10-01

The risk of multiple pregnancy to maternal-fetal health can be minimized by reducing the number of embryos transferred. New tools for selecting embryos with the highest implantation potential should be developed. The aim of this study was to evaluate the ability of morphological and morphometric variables to predict implantation by analysing images of embryos. This was a retrospective study of 135 embryo photographs from 112 IVF-ICSI cycles carried out between January and March 2011. The embryos were photographed immediately before transfer using Cronus 3 software. Their images were analysed using the public program ImageJ. Significant effects (P < 0.05), and higher discriminant power to predict implantation were observed for the morphometric embryo variables compared with morphological ones. The features for successfully implanted embryos were as follows: four cells on day 2 of development; all blastomeres with circular shape (roundness factor greater than 0.9), an average zona pellucida thickness of 13 µm and an average of 17695.1 µm² for the embryo area. Embryo size, which is described by its area and the average roundness factor for each cell, provides two objective variables to consider when predicting implantation. This approach should be further investigated for its potential ability to improve embryo scoring. Copyright © 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Pyramidal neurons in the septal and temporal CA1 field of the human and hedgehog tenrec hippocampus.

PubMed

Liagkouras, Ioannis; Michaloudi, Helen; Batzios, Christos; Psaroulis, Dimitrios; Georgiadis, Marios; Künzle, Heinz; Papadopoulos, Georgios C

2008-07-07

The present study examines comparatively the cellular density of disector-counted/Nissl-stained CA1 pyramidal neurons and the morphometric characteristics (dendritic number/length, spine number/density and Sholl-counted dendritic branch points/20 microm) of the basal and apical dendritic systems of Golgi-impregnated CA1 neurons, in the septal and temporal hippocampus of the human and hedgehog tenrec brain. The obtained results indicate that in both hippocampal parts the cellular density of the CA1 pyramidal neurons is lower in human than in tenrec. However, while the human pyramidal cell density is higher in the septal hippocampal part than in the temporal one, in the tenrec the density of these cells is higher in the temporal part. The dendritic tree of the CA1 pyramidal cells, more developed in the septal than in temporal hippocampus in both species studied, is in general more complex in the human hippocampus. The basal and the apical dendritic systems exhibit species related morphometric differences, while dendrites of different orders exhibit differences in their number and length, and in their spine density. Finally, in both species, as well as hippocampal parts and dendritic systems, changes of dendritic morphometric features along ascending dendritic orders fluctuate in a similar way, as do the number of dendritic branch points in relation to the distance from the neuron soma.

Agile Multi-Scale Decompositions for Automatic Image Registration

NASA Technical Reports Server (NTRS)

Murphy, James M.; Leija, Omar Navarro; Le Moigne, Jacqueline

2016-01-01

In recent works, the first and third authors developed an automatic image registration algorithm based on a multiscale hybrid image decomposition with anisotropic shearlets and isotropic wavelets. This prototype showed strong performance, improving robustness over registration with wavelets alone. However, this method imposed a strict hierarchy on the order in which shearlet and wavelet features were used in the registration process, and also involved an unintegrated mixture of MATLAB and C code. In this paper, we introduce a more agile model for generating features, in which a flexible and user-guided mix of shearlet and wavelet features are computed. Compared to the previous prototype, this method introduces a flexibility to the order in which shearlet and wavelet features are used in the registration process. Moreover, the present algorithm is now fully coded in C, making it more efficient and portable than the MATLAB and C prototype. We demonstrate the versatility and computational efficiency of this approach by performing registration experiments with the fully-integrated C algorithm. In particular, meaningful timing studies can now be performed, to give a concrete analysis of the computational costs of the flexible feature extraction. Examples of synthetically warped and real multi-modal images are analyzed.

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

PubMed

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Objective grading of facial paralysis using Local Binary Patterns in video processing.

PubMed

He, Shu; Soraghan, John J; O'Reilly, Brian F

2008-01-01

This paper presents a novel framework for objective measurement of facial paralysis in biomedial videos. The motion information in the horizontal and vertical directions and the appearance features on the apex frames are extracted based on the Local Binary Patterns (LBP) on the temporal-spatial domain in each facial region. These features are temporally and spatially enhanced by the application of block schemes. A multi-resolution extension of uniform LBP is proposed to efficiently combine the micro-patterns and large-scale patterns into a feature vector, which increases the algorithmic robustness and reduces noise effects while still retaining computational simplicity. The symmetry of facial movements is measured by the Resistor-Average Distance (RAD) between LBP features extracted from the two sides of the face. Support Vector Machine (SVM) is applied to provide quantitative evaluation of facial paralysis based on the House-Brackmann (H-B) Scale. The proposed method is validated by experiments with 197 subject videos, which demonstrates its accuracy and efficiency.

Space Technology 5 Multi-Point Observations of Temporal Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2008-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of approximately 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approximately 1 min for meso-scale currents and approximately 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Prevalence, topographic and morphometric features of femoral cam-type deformity: changes in relation to age and gender.

PubMed

Morales-Avalos, R; Leyva-Villegas, J I; Sánchez-Mejorada, G; Reynaga-Obregón, J; Galindo-de León, S; Vílchez-Cavazos, F; Espinosa-Uribe, A G; Acosta-Olivo, C; de la Garza-Castro, O; Guzmán-Avilan, R I; Elizondo-Omaña, R E; Guzmán-López, S

2016-09-01

Femoroacetabular impingement (FAI) syndrome is a frequent cause of pain and in recent years considered to be a precursor of premature hip osteoarthritis. The structural abnormalities which characterize FAI syndrome, such as the cam-type deformity, are associated with morphological alterations that may lead to hip osteoarthritis. The aim of this study was to determine the prevalence and topographic and morphometric features of the cam deformity in a series of 326 femur specimens obtained from a Mexican population, as well as changes in prevalence in relation to age and gender. The specimens were subdivided into groups according to gender and age. A standardized photograph of the proximal femur of each specimen was taken, and the photograph was used to determine the alpha angle using a computer program; the location of the lesion was determined by quadrant and the morphometric characteristics were determined by direct observation. The overall prevalence of cam deformities in the femur specimens was 29.8 % (97/326), with a prevalence by gender of 35.2 % (64/182) in men and 22.9 % (33/144) in women. The mean alpha angle was 54.6° ± 8.5° in all of the osteological specimens and 65.6° ± 7.5° in those specimens exhibiting a cam deformity. Cam deformities were found topographically in the anterior-superior quadrant of the femoral head-neck junction in 86.6 % (84/97) of the femurs. Deformities were found in 28.2 % of the right femurs and 31.3 % of the left femurs. The prevalence of cam deformity was higher in the femur specimens of young men and in those of middle-aged and older women. There were no significant differences in this deformity in relation to the alpha angle according to age and gender.

Quantitative analysis and implications of drainage morphometry of the Agula watershed in the semi-arid northern Ethiopia

NASA Astrophysics Data System (ADS)

Fenta, Ayele Almaw; Yasuda, Hiroshi; Shimizu, Katsuyuki; Haregeweyn, Nigussie; Woldearegay, Kifle

2017-11-01

This study aimed at quantitative analysis of morphometric parameters of Agula watershed and its sub-watersheds using remote sensing data, geographic information system, and statistical methods. Morphometric parameters were evaluated from four perspectives: drainage network, watershed geometry, drainage texture, and relief characteristics. A sixth-order river drains Agula watershed and the drainage network is mainly dendritic type. The mean bifurcation ratio ( R b) was 4.46 and at sub-watershed scale, high R b values ( R b > 5) were observed which might be expected in regions of steeply sloping terrain. The longest flow path of Agula watershed is 48.5 km, with knickpoints along the main river which could be attributed to change of lithology and major faults which are common along the rift escarpments. The watershed has elongated shape suggesting low peak flows for longer duration and hence easier flood management. The drainage texture analysis revealed fine drainage which implies the dominance of impermeable soft rock with low resistance against erosion. High relief and steep slopes dominates, by which rough landforms (hills, breaks, and low mountains) make up 76% of the watershed. The S-shaped hypsometric curve with hypsometric integral of 0.4 suggests that Agula watershed is in equilibrium or mature stage of geomorphic evolution. At sub-watershed scale, the derived morphometric parameters were grouped into three clusters (low, moderate, and high) and considerable spatial variability was observed. The results of this study provide information on drainage morphometry that can help better understand the watershed characteristics and serve as a basis for improved planning, management, and decision making to ensure sustainable use of watershed resources.

Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin-Upper Tons Basin, Indian Himalayas.

PubMed

Das, Sayantan; Patel, Priyank Pravin; Sengupta, Somasis

2016-01-01

With myriad geospatial datasets now available for terrain information extraction and particularly streamline demarcation, there arises questions regarding the scale, accuracy and sensitivity of the initial dataset from which these aspects are derived, as they influence all other parameters computed subsequently. In this study, digital elevation models (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER V2), Shuttle Radar Topography Mission (SRTM V4, C-Band, 3 arc-second), Cartosat -1 (CartoDEM 1.0) and topographical maps (R.F. 1:250,000 and 1:50,000), have been used to individually extract and analyze the relief, surface, size, shape and texture properties of a mountainous drainage basin. Nestled inside a mountainous setting, the basin is a semi-elongated one with high relief ratio (>90), steep slopes (25°-30°) and high drainage density (>3.5 km/sq km), as computed from the different DEMs. The basin terrain and stream network is extracted from each DEM, whose morphometric attributes are compared with the surveyed stream networks present in the topographical maps, with resampling of finer DEM datasets to coarser resolutions, to reduce scale-implications during the delineation process. Ground truth verifications for altitudinal accuracy have also been done by a GPS survey. DEMs derived from the 1:50,000 topographical map and ASTER GDEM V2 data are found to be more accurate and consistent in terms of absolute accuracy, than the other generated or available DEM data products, on basis of the morphometric parameters extracted from each. They also exhibit a certain degree of proximity to the surveyed topographical map.

Development of a new morphometric to assess beach storm response and recovery

NASA Astrophysics Data System (ADS)

Brenner, O.; Hapke, C. J.

2014-12-01

Various morphometrics are used to measure coastal change over a variety of time scales including shoreline, dune elevation and position, and beach profile volume. Each has limitations, many of which became apparent in the aftermath of Hurricane Sandy, including the juxtaposition of levelled dunes and a substantially prograded shoreline. In order to understand sustained beach behavior, including recovery after Hurricane Sandy, we develop a new morphometric - an upper beach change envelope (BCE) specific to Fire Island, NY. The upper beach better captures impacts from more frequent moderate storms during which there may be substantial beach change but less impact to the dune, and is less subject to the variable fluctuations nearer to the shoreline that only marginally influence future vulnerability and overall coastal resilience. The BCE can also be used to quantify the gradual recovery of the beach after storm events and is not reliant on the presence of a morphologic feature such as a dune, which may take many years to recover after a severe storm.The BCE at Fire Island is based on a time series of historical response to storms. The BCE boundaries are elevation contours that capture the portion of the upper beach that experiences erosion during moderate nor'easter events but is above the influence of tides and lesser events. In an application of the BCE concept, we use the BCE boundary elevations to quantify beach response from Hurricane Sandy and document the subsequent recovery, using a time series of post-Sandy elevation contours. The data include 10 profile sites from Fire Island that were surveyed multiple times from October 2012 to June 2014. Utilizing this time series we measure changes in the cross shore position of the BCE elevation boundaries. Initial assessments indicate the BCE successfully captures coastal response through time, including extensive change during Hurricane Sandy as well as subsequent seasonal changes. The recent data indicate there is a temporal trend towards widening of the BCE, due to sustained progradation of the lower boundary. This trend may represent a new "recovery state" of the beach which is wider than the pre-Sandy beach, providing an increase in the fetch that favors the aeolian processes of dune reformation.

Linear Polarization Properties of Parsec-Scale AGN Jets

NASA Astrophysics Data System (ADS)

Pushkarev, Alexander; Kovalev, Yuri; Lister, Matthew; Savolainen, Tuomas; Aller, Margo; Aller, Hugh; Hodge, Mary

2017-12-01

We used 15 GHz multi-epoch Very Long Baseline Array (VLBA) polarization sensitive observations of 484 sources within a time interval 1996--2016 from the MOJAVE program, and also from the NRAO data archive. We have analyzed the linear polarization characteristics of the compact core features and regions downstream, and their changes along and across the parsec-scale active galactic nuclei (AGN) jets. We detected a significant increase of fractional polarization with distance from the radio core along the jet as well as towards the jet edges. Compared to quasars, BL Lacs have a higher degree of polarization and exhibit more stable electric vector position angles (EVPAs) in their core features and a better alignment of the EVPAs with the local jet direction. The latter is accompanied by a higher degree of linear polarization, suggesting that compact bright jet features might be strong transverse shocks, which enhance magnetic field regularity by compression.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

The Impact of Solid Surface Features on Fluid-Fluid Interface Configuration

NASA Astrophysics Data System (ADS)

Araujo, J. B.; Brusseau, M. L. L.

2017-12-01

Pore-scale fluid processes in geological media are critical for a broad range of applications such as radioactive waste disposal, carbon sequestration, soil moisture distribution, subsurface pollution, land stability, and oil and gas recovery. The continued improvement of high-resolution image acquisition and processing have provided a means to test the usefulness of theoretical models developed to simulate pore-scale fluid processes, through the direct quantification of interfaces. High-resolution synchrotron X-ray microtomography is used in combination with advanced visualization tools to characterize fluid distributions in natural geologic media. The studies revealed the presence of fluid-fluid interface associated with macroscopic features on the surfaces of the solids such as pits and crevices. These features and respective fluid interfaces, which are not included in current theoretical or computational models, may have a significant impact on accurate simulation and understanding of multi-phase flow, energy, heat and mass transfer processes.

Multi-scale fluctuation analysis of precipitation in Beijing by Extreme-point Symmetric Mode Decomposition

NASA Astrophysics Data System (ADS)

Li, Jiqing; Duan, Zhipeng; Huang, Jing

2018-06-01

With the aggravation of the global climate change, the shortage of water resources in China is becoming more and more serious. Using reasonable methods to study changes in precipitation is very important for planning and management of water resources. Based on the time series of precipitation in Beijing from 1951 to 2015, the multi-scale features of precipitation are analyzed by the Extreme-point Symmetric Mode Decomposition (ESMD) method to forecast the precipitation shift. The results show that the precipitation series have periodic changes of 2.6, 4.3, 14 and 21.7 years, and the variance contribution rate of each modal component shows that the inter-annual variation dominates the precipitation in Beijing. It is predicted that precipitation in Beijing will continue to decrease in the near future.

Target matching based on multi-view tracking

NASA Astrophysics Data System (ADS)

Liu, Yahui; Zhou, Changsheng

2011-01-01

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Aphanius arakensis, a new species of tooth-carp (Actinopterygii, Cyprinodontidae) from the endorheic Namak Lake basin in Iran.

PubMed

Teimori, Azad; Esmaeili, Hamid Reza; Gholami, Zeinab; Zarei, Neda; Reichenbacher, Bettina

2012-01-01

A new species of tooth-carp, Aphanius arakensissp. n., is described from the Namak Lake basin in Iran. The new species is distinguished by the congeners distributed in Iran by the following combination of characters: 10-12 anal fin rays, 28-32 lateral line scales, 10-13 caudal peduncle scales, 8-10 gill rakers, 12-19, commonly 15-16, clearly defined flank bars in males, a more prominent pigmentation along the flank added by relatively big blotches in the middle and posterior flank segments in females, a short but high antirostrum of the otolith that has a wide excisura, and a ventral rim with some small, drop-like processes, and 19 molecular apomorphies (17 transitions, two transversions) in the cytochrome b gene. It was suggested based on the phylogenetic analysis that the new species is sister to Aphanius sophiae from the Kor River and that Aphanius farsicus from the Maharlu Lake basin is sister to Aphanius arakensis plus Aphanius sophiae. A noticeable feature of the Aphanius diversity in Iran is the conservatism of the external morphology as well as morphometric and meristic characters, while distinctive differences are present in genetic characters, otolith morphology, and male color pattern. Transformation of the latter was probably driven by sexual selection.

A new species of Aspidoras Ihering (Siluriformes: Callichthyidae: Corydoradinae) from the Rio Xingu Basin, Pará, Brazil.

PubMed

Leão, Manuela D V; Britto, Marcelo R; Wosiacki, Wolmar B

2015-07-21

A new species of Aspidoras is described from an unnamed stream in the Rio Xingu Basin, Castelo de Sonhos municipality, Pará State, representing the northernmost record of the genus along the edge of the Brazilian Shield in the Amazon Basin. Aspidoras marianae is easily distinguished from all congeners in having minute odontode-bearing platelets scattered over the surface of the snout region, minute platelets between the parieto-supraoccipital process and the nuchal plate, and other shared features related to color pattern, morphometrics, meristics and morphological data. Comments about exclusive and shared features are presented.

Somatostatinoma: collision with neurofibroma and ultrastructural features.

PubMed

Varikatt, W; Yong, J L C; Killingsworth, M C

2006-11-01

The clinical presentation, histopathology and immunoelectron microscopic features of two cases of duodenal somatostatinoma are described, one of which is a hitherto unreported example of a collision tumour with a neurofibroma. Ultrastructural morphometric immunoelectron microscopy studies revealed the presence of four types of cells in both tumours, but there was no difference in the proportions of these cells between the collision tumour and the non-collision tumour. Neurosecretory granules ranging in size from 255-815 nm were generally larger than those previously reported for somatostatinomas and somatostatin was identified in granules of all sizes across this range. Neither tumour was associated with the somatostatinoma syndrome comprising associated diabetes mellitis, steatorrhoea and cholelithiasis.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Relationships between development/decay of a vortex and its topology in different flow scales in an isotropic homogeneous turbulence

NASA Astrophysics Data System (ADS)

Yamamoto, Keisuke; Nakayama, Katsuyuki

2017-11-01

Development or decay of a vortex in terms of the local flow topology has been shown to be highly correlated with its topological feature, i.e., vortical flow symmetry (skewness), in an isotropic homogeneous turbulence. Since a turbulent flow might include vortices in multi-scales, the present study investigates the characteristics of this relationships between the development or decay of a vortex and the vortical flow symmetry in several scales in an isotropic homogeneous turbulence in low Reynols number. Swirlity is a physical quantity of an intensity of swirling in terms of the geometrical average of the azimuthal flow, and represents the behavior of the development or decay of a vortex in this study. Flow scales are decomposed into three scales specified by the Fourier coefficients of the velocity applying the band-pass filter. The analysis shows that vortices in the different scales have a universal feature that the time derivative of swirlity and that of the symmetry have high correlation. Especially they have more stronger correlation at their birth and extinction.

Compound cooling flow turbulator for turbine component

DOEpatents

Lee, Ching-Pang; Jiang, Nan; Marra, John J; Rudolph, Ronald J

2014-11-25

Multi-scale turbulation features, including first turbulators (46, 48) on a cooling surface (44), and smaller turbulators (52, 54, 58, 62) on the first turbulators. The first turbulators may be formed between larger turbulators (50). The first turbulators may be alternating ridges (46) and valleys (48). The smaller turbulators may be concave surface features such as dimples (62) and grooves (54), and/or convex surface features such as bumps (58) and smaller ridges (52). An embodiment with convex turbulators (52, 58) in the valleys (48) and concave turbulators (54, 62) on the ridges (46) increases the cooling surface area, reduces boundary layer separation, avoids coolant shadowing and stagnation, and reduces component mass.

Morphometric analysis and neuroanatomical mapping of the zebrafish brain.

PubMed

Gupta, Tripti; Marquart, Gregory D; Horstick, Eric J; Tabor, Kathryn M; Pajevic, Sinisa; Burgess, Harold A

2018-06-21

Large-scale genomic studies have recently identified genetic variants causative for major neurodevelopmental disorders, such as intellectual disability and autism. However, determining how underlying developmental processes are affected by these mutations remains a significant challenge in the field. Zebrafish is an established model system in developmental neurogenetics that may be useful in uncovering the mechanisms of these mutations. Here we describe the use of voxel-intensity, deformation field, and volume-based morphometric techniques for the systematic and unbiased analysis of gene knock-down and environmental exposure-induced phenotypes in zebrafish. We first present a computational method for brain segmentation based on transgene expression patterns to create a comprehensive neuroanatomical map. This map allowed us to disclose statistically significant changes in brain microstructure and composition in neurodevelopmental models. We demonstrate the effectiveness of morphometric techniques in measuring changes in the relative size of neuroanatomical subdivisions in atoh7 morphant larvae and in identifying phenotypes in larvae treated with valproic acid, a chemical demonstrated to increase the risk of autism in humans. These tools enable rigorous evaluation of the effects of gene mutations and environmental exposures on neural development, providing an entry point for cellular and molecular analysis of basic developmental processes as well as neurodevelopmental and neurodegenerative disorders. Published by Elsevier Inc.

Discrimination of snipefish Macroramphosus species and boarfish Capros aper morphotypes through multivariate analysis of body shape

NASA Astrophysics Data System (ADS)

Lopes, Marta; Murta, Alberto G.; Cabral, Henrique N.

2006-03-01

The existence of two species of the genus Macroramphosus Lacepède 1803, has been discussed based on morphometric characters, diet composition and depth distribution. Another species, the boarfish Capros aper (Linnaeus 1758), caugth along the Portuguese coast, shows two different morphotypes, one type with smaller eyes and a deeper body than the other, occurring with intermediate forms. In both snipefish and boarfish no sexual dimorphism was found with respect to shape and length relationships. However, females in both genera were on average bigger than males. A multidimensional scaling analysis was performed using Procrustes distances, in order to check if shape geometry was effective in distinguishing the species of snipefish as well as the morphotypes of boarfish. A multivariate discriminant analysis using morphometric characters of snipefish and boarfish was carried out to validate the visual criteria for a distinction of species and morphotypes, respectively. Morphometric characters revealed a great discriminatory power to distinguish morphotypes. Both snipefish and boarfish are very abundant in Portuguese waters, showing two well-defined morphologies and intermediate forms. This study suggests that there may be two different species in each genus and that further studies on these fish should be carried out to investigate if there is reproductive isolation between the morphotypes of boarfish and to validate the species of snipefish.

Analysis of the human female foot in two different measurement systems: from geometric morphometrics to functional morphology.

PubMed

Bookstein, Fred L; Domjanić, Jacqueline

2014-09-01

The relationship of geometric morphometrics (GMM) to functional analysis of the same morphological resources is currently a topic of active interest among functional morphologists. Although GMM is typically advertised as free of prior assumptions about shape features or morphological theories, it is common for GMM findings to be concordant with findings from studies based on a-priori lists of shape features whenever prior insights or theories have been properly accounted for in the study design. The present paper demonstrates this happy possibility by revisiting a previously published GMM analysis of footprint outlines for which there is also functionally relevant information in the form of a-pri-ori foot measurements. We show how to convert the conventional measurements into the language of shape, thereby affording two parallel statistical analyses. One is the classic multivariate analysis of "shape features", the other the equally classic GMM of semilandmark coordinates. In this example, the two data sets, analyzed by protocols that are remarkably different in both their geometry and their algebra, nevertheless result in one common biometrical summary: wearing high heels is bad for women inasmuch as it leads to the need for orthotic devices to treat the consequently flattened arch. This concordance bears implications for other branches of applied anthropology. To carry out a good biomedical analysis of applied anthropometric data it may not matter whether one uses GMM or instead an adequate assortment of conventional measurements. What matters is whether the conventional measurements have been selected in order to match the natural spectrum of functional variation.

High throughput, detailed, cell-specific neuroanatomy of dendritic spines using microinjection and confocal microscopy

PubMed Central

Dumitriu, Dani; Rodriguez, Alfredo; Morrison, John H.

2012-01-01

Morphological features such as size, shape and density of dendritic spines have been shown to reflect important synaptic functional attributes and potential for plasticity. Here we describe in detail a protocol for obtaining detailed morphometric analysis of spines using microinjection of fluorescent dyes, high resolution confocal microscopy, deconvolution and image analysis using NeuronStudio. Recent technical advancements include better preservation of tissue resulting in prolonged ability to microinject, and algorithmic improvements that compensate for the residual Z-smear inherent in all optical imaging. Confocal imaging parameters were probed systematically for the identification of both optimal resolution as well as highest efficiency. When combined, our methods yield size and density measurements comparable to serial section transmission electron microscopy in a fraction of the time. An experiment containing 3 experimental groups with 8 subjects in each can take as little as one month if optimized for speed, or approximately 4 to 5 months if the highest resolution and morphometric detail is sought. PMID:21886104

Karstic terrain in the equatorial layered deposits within a crater in northern Sinus Meridiani, Mars.

NASA Astrophysics Data System (ADS)

Baioni, Davide

2017-04-01

This work investigates the equatorial layered deposits (ELDs) located within a crater located in northern Sinus Meridiani, Mars (4.430 N, 3.320 W), which display traits that are consistent with formation by karst-driven processes. Here, shallow depressions showing a variety of plan forms ranging from rounded, circular, elongated, polygonal and drop-like to elliptical can be observed. The morphologic and morphometric analyses performed, highlight that these depressions display strong morphometric (sizes) and morphologic (shapes, bottoms, walls) similarities with the karst depressions that are common on limestone and evaporite terrains on the Earth and other regions on Mars. On the basis of the characteristics of the investigated landforms and the similarities of features on Earth and Mars, and after discarding other possible origins such as, aeolian, periglacial, volcanic or impact related processes, it has been inferred that the depressions are karstic dolines formed polygenetically by corrosion and solution-related intra-crater processes.

Disentangling diatom species complexes: does morphometry suffice?

PubMed Central

Borrego-Ramos, María; Olenici, Adriana

2017-01-01

Accurate taxonomic resolution in light microscopy analyses of microalgae is essential to achieve high quality, comparable results in both floristic analyses and biomonitoring studies. A number of closely related diatom taxa have been detected to date co-occurring within benthic diatom assemblages, sharing many morphological, morphometrical and ecological characteristics. In this contribution, we analysed the hypothesis that, where a large sample size (number of individuals) is available, common morphometrical parameters (valve length, width and stria density) are sufficient to achieve a correct identification to the species level. We focused on some common diatom taxa belonging to the genus Gomphonema. More than 400 valves and frustules were photographed in valve view and measured using Fiji software. Several statistical tools (mixture and discriminant analysis, k-means clustering, classification trees, etc.) were explored to test whether mere morphometry, independently of other valve features, leads to correct identifications, when compared to identifications made by experts. In view of the results obtained, morphometry-based determination in diatom taxonomy is discouraged. PMID:29250472

Morphometrics and structure of complete baleen racks in gray whales (Eschrichtius robustus) from the Eastern North Pacific Ocean.

PubMed

Young, Samantha; DeméRé, Thomas A; Ekdale, Eric G; Berta, Annalisa; Zellmer, Nicholas

2015-04-01

Mysticetes have evolved a novel filter feeding apparatus-baleen-an epidermal keratinous tissue composed of keratin that grows as a serial arrangement of transverse cornified laminae from the right and left sides of the palate. The structure and function of baleen varies among extant mysticete clades and this variation likely can be viewed as adaptations related to different filter feeding strategies. In one of the first morphometric studies of the full baleen apparatus, we describe the morphology of complete baleen racks in neonate, yearling and adult gray whales (Eschrichtius robustus), and note morphometric variations between age groups as well as within individual racks. Morphometric data and detailed descriptions were collected from the full baleen apparatus of three frozen specimens of E. robustus using previously derived ecologically significant and broad scale measurements of baleen. Additionally, characters of the baleen apparatus were described based on visible patterns of baleen laminae and plates on the dorsal root of the rack. Results indicate that the longest, widest, and thickest plates and laminae are found toward the posterior half of the rack, resulting in the greatest surface area for filtration of prey occurring in this region. Ontogenetic changes were also documented that reveal a progressive increase in the filter surface area of the developing baleen apparatus as baleen laminae and main plates grow in length and width. Also noted was a progressive posterior shift in the position of greatest filtration area. Histological examination of the epithelial base (Zwischensubstanz) and laminae showed basic epidermal layers, as well as gapping between layers and vacuoles. © 2015 Wiley Periodicals, Inc.

Toward a global multi-scale heliophysics observatory

NASA Astrophysics Data System (ADS)

Semeter, J. L.

2017-12-01

We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.

Self-induced flavor conversion of supernova neutrinos on small scales

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

Chakraborty, S.; Hansen, R. S.; Izaguirre, I.

2016-01-15

Self-induced flavor conversion of supernova (SN) neutrinos is a generic feature of neutrino-neutrino dispersion. The corresponding run-away modes in flavor space can spontaneously break the original symmetries of the neutrino flux and in particular can spontaneously produce small-scale features as shown in recent schematic studies. However, the unavoidable “multi-angle matter effect” shifts these small-scale instabilities into regions of matter and neutrino density which are not encountered on the way out from a SN. The traditional modes which are uniform on the largest scales are most prone for instabilities and thus provide the most sensitive test for the appearance of self-inducedmore » flavor conversion. As a by-product we clarify the relation between the time evolution of an expanding neutrino gas and the radial evolution of a stationary SN neutrino flux. Our results depend on several simplifying assumptions, notably stationarity of the solution, the absence of a “backward” neutrino flux caused by residual scattering, and global spherical symmetry of emission.« less

Self-induced flavor conversion of supernova neutrinos on small scales

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

Chakraborty, S.; Izaguirre, I.; Raffelt, G.G.

2016-01-01

Self-induced flavor conversion of supernova (SN) neutrinos is a generic feature of neutrino-neutrino dispersion. The corresponding run-away modes in flavor space can spontaneously break the original symmetries of the neutrino flux and in particular can spontaneously produce small-scale features as shown in recent schematic studies. However, the unavoidable ''multi-angle matter effect'' shifts these small-scale instabilities into regions of matter and neutrino density which are not encountered on the way out from a SN. The traditional modes which are uniform on the largest scales are most prone for instabilities and thus provide the most sensitive test for the appearance of self-inducedmore » flavor conversion. As a by-product we clarify the relation between the time evolution of an expanding neutrino gas and the radial evolution of a stationary SN neutrino flux. Our results depend on several simplifying assumptions, notably stationarity of the solution, the absence of a ''backward'' neutrino flux caused by residual scattering, and global spherical symmetry of emission.« less

Lung morphometry using hyperpolarized 129 Xe multi-b diffusion MRI with compressed sensing in healthy subjects and patients with COPD.

PubMed

Zhang, Huiting; Xie, Junshuai; Xiao, Sa; Zhao, Xiuchao; Zhang, Ming; Shi, Lei; Wang, Ke; Wu, Guangyao; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2018-05-04

To demonstrate the feasibility of compressed sensing (CS) to accelerate the acquisition of hyperpolarized (HP) 129 Xe multi-b diffusion MRI for quantitative assessments of lung microstructural morphometry. Six healthy subjects and six chronic obstructive pulmonary disease (COPD) subjects underwent HP 129 Xe multi-b diffusion MRI (b = 0, 10, 20, 30, and 40 s/cm 2 ). First, a fully sampled (FS) acquisition of HP 129 Xe multi-b diffusion MRI was conducted in one healthy subject. The acquired FS dataset was retrospectively undersampled in the phase encoding direction, and an optimal twofold undersampled pattern was then obtained by minimizing mean absolute error (MAE) between retrospective CS (rCS) and FS MR images. Next, the FS and CS acquisitions during separate breath holds were performed on five healthy subjects (including the above one). Additionally, the FS and CS synchronous acquisitions during a single breath hold were performed on the sixth healthy subject and one COPD subject. However, only CS acquisitions were conducted in the rest of the five COPD subjects. Finally, all the acquired FS, rCS and CS MR images were used to obtain morphometric parameters, including acinar duct radius (R), acinar lumen radius (r), alveolar sleeve depth (h), mean linear intercept (L m ), and surface-to-volume ratio (SVR). The Wilcoxon signed-rank test and the Bland-Altman plot were employed to assess the fidelity of the CS reconstruction. Moreover, the t-test was used to demonstrate the effectiveness of the multi-b diffusion MRI with CS in clinical applications. The retrospective results demonstrated that there was no statistically significant difference between rCS and FS measurements using the Wilcoxon signed-rank test (P > 0.05). Good agreement between measurements obtained with the CS and FS acquisitions during separate breath holds was demonstrated in Bland-Altman plots of slice differences. Specifically, the mean biases of the R, r, h, L m , and SVR between the CS and FS acquisitions were 1.0%, 2.6%, -0.03%, 1.5%, and -5.5%, respectively. Good agreement between measurements with the CS and FS acquisitions was also observed during the single breath-hold experiments. Furthermore, there were significant differences between the morphometric parameters for the healthy and COPD subjects (P < 0.05). Our study has shown that HP 129 Xe multi-b diffusion MRI with CS could be beneficial in lung microstructural assessments by acquiring less data while maintaining the consistent results with the FS acquisitions. © 2018 American Association of Physicists in Medicine.

High Fidelity Modeling of Turbulent Mixing and Chemical Kinetics Interactions in a Post-Detonation Flow Field

NASA Astrophysics Data System (ADS)

Sinha, Neeraj; Zambon, Andrea; Ott, James; Demagistris, Michael

2015-06-01

Driven by the continuing rapid advances in high-performance computing, multi-dimensional high-fidelity modeling is an increasingly reliable predictive tool capable of providing valuable physical insight into complex post-detonation reacting flow fields. Utilizing a series of test cases featuring blast waves interacting with combustible dispersed clouds in a small-scale test setup under well-controlled conditions, the predictive capabilities of a state-of-the-art code are demonstrated and validated. Leveraging physics-based, first principle models and solving large system of equations on highly-resolved grids, the combined effects of finite-rate/multi-phase chemical processes (including thermal ignition), turbulent mixing and shock interactions are captured across the spectrum of relevant time-scales and length scales. Since many scales of motion are generated in a post-detonation environment, even if the initial ambient conditions are quiescent, turbulent mixing plays a major role in the fireball afterburning as well as in dispersion, mixing, ignition and burn-out of combustible clouds in its vicinity. Validating these capabilities at the small scale is critical to establish a reliable predictive tool applicable to more complex and large-scale geometries of practical interest.

Ontogenetic scaling of the olfactory antennae and flicking behavior of the shore crab, Hemigrapsus oregonensis.

PubMed

Waldrop, Lindsay D

2013-07-01

Malacostracan crustaceans such as crabs flick antennae with arrays of olfactory sensilla called aesthetascs through the water to sense odors. Flicking by crabs consists of a quick downstroke, in which aesthetascs are deflected laterally (splayed), and a slower, reversed return stroke, in which aesthetascs clump together. This motion causes water to be flushed within and then held in between aesthetascs to deliver odor molecules to olfactory receptors. Although this odor sampling method relies on a narrow range of speeds, sizes, and specific arrangements of aesthetascs, most crabs dramatically change these during ontogeny. In this study, the morphometrics of the aesthetascs, array, and antennae and the flicking kinematics of the Oregon shore crab, Hemigrapsus oregonensis (Decapoda: Brachyura), are examined to determine their scaling relationships during ontogeny. The morphometrics of the array and antennae increase more slowly than would be predicted by isometry. Juvenile crabs' aesthetascs splay relatively further apart than adults, likely due to changing material properties of aesthetasc cuticle during growth. These results suggest that disproportionate growth and altered aesthetasc splay during flicking will mediate the size changes due to growth that would otherwise lead to a loss of function.

Towards designing an optical-flow based colonoscopy tracking algorithm: a comparative study

NASA Astrophysics Data System (ADS)

Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

2013-03-01

Automatic co-alignment of optical and virtual colonoscopy images can supplement traditional endoscopic procedures, by providing more complete information of clinical value to the gastroenterologist. In this work, we present a comparative analysis of our optical flow based technique for colonoscopy tracking, in relation to current state of the art methods, in terms of tracking accuracy, system stability, and computational efficiency. Our optical-flow based colonoscopy tracking algorithm starts with computing multi-scale dense and sparse optical flow fields to measure image displacements. Camera motion parameters are then determined from optical flow fields by employing a Focus of Expansion (FOE) constrained egomotion estimation scheme. We analyze the design choices involved in the three major components of our algorithm: dense optical flow, sparse optical flow, and egomotion estimation. Brox's optical flow method,1 due to its high accuracy, was used to compare and evaluate our multi-scale dense optical flow scheme. SIFT6 and Harris-affine features7 were used to assess the accuracy of the multi-scale sparse optical flow, because of their wide use in tracking applications; the FOE-constrained egomotion estimation was compared with collinear,2 image deformation10 and image derivative4 based egomotion estimation methods, to understand the stability of our tracking system. Two virtual colonoscopy (VC) image sequences were used in the study, since the exact camera parameters(for each frame) were known; dense optical flow results indicated that Brox's method was superior to multi-scale dense optical flow in estimating camera rotational velocities, but the final tracking errors were comparable, viz., 6mm vs. 8mm after the VC camera traveled 110mm. Our approach was computationally more efficient, averaging 7.2 sec. vs. 38 sec. per frame. SIFT and Harris affine features resulted in tracking errors of up to 70mm, while our sparse optical flow error was 6mm. The comparison among egomotion estimation algorithms showed that our FOE-constrained egomotion estimation method achieved the optimal balance between tracking accuracy and robustness. The comparative study demonstrated that our optical-flow based colonoscopy tracking algorithm maintains good accuracy and stability for routine use in clinical practice.

Mapping of major volcanic structures on Pavonis Mons in Tharsis, Mars

NASA Astrophysics Data System (ADS)

Orlandi, Diana; Mazzarini, Francesco; Pagli, Carolina; Pozzobon, Riccardo

2017-04-01

Pavonis Mons, with its 300 km of diameter and 14 km of height, is one of the largest volcanoes of Mars. It rests on a topographic high called Tharsis rise and it is located in the centre of a SW-NE trending row of volcanoes, including Arsia and Ascraeus Montes. In this study we mapped and analyzed the volcanic and tectonic structures of Pavonis Mons in order to understand its formation and the relationship between magmatic and tectonic activity. We use the mapping ArcGIS software and vast set of high resolution topographic and multi-spectral images including CTX (6 m/pixel) as well as HRSC (12.5 m/pixel) and HiRiSE ( 0.25 m/pixel) mosaic images. Furthemore, we used MOLA ( 463 m/pixel in the MOLA MEGDR gridded topographic data), THEMIS thermal inertia (IR-day, 100 m/pixel) and THEMIS (IR-night, 100 m/pixel) images global mosaic to map structures at the regional scale. We found a wide range of structures including ring dykes, wrinkle ridges, pit chains, lava flows, lava channels, fissures and depressions that we preliminary interpreted as coalescent lava tubes. Many sinuous rilles have eroded Pavonis' slopes and culminate with lava aprons, similar to alluvial fans. South of Pavonis Mons we also identify a series of volcanic vents mainly aligned along a SW-NE trend. Displacements across recent crater rim and volcanic deposits (strike slip faults and wrinkle ridges) have been documented suggesting that, at least during the most recent volcanic phases, the regional tectonics has contributed in shaping the morphology of Pavonis. The kinematics of the mapped structures is consistent with a ENE-SSW direction of the maximum horizontal stress suggesting a possible interaction with nearby Valles Marineris. Our study provides new morphometric analysis of volcano-tectonic features that can be used to depict an evolutionary history for the Pavonis Volcano.

An automated approach for extracting Barrier Island morphology from digital elevation models

NASA Astrophysics Data System (ADS)

Wernette, Phillipe; Houser, Chris; Bishop, Michael P.

2016-06-01

The response and recovery of a barrier island to extreme storms depends on the elevation of the dune base and crest, both of which can vary considerably alongshore and through time. Quantifying the response to and recovery from storms requires that we can first identify and differentiate the dune(s) from the beach and back-barrier, which in turn depends on accurate identification and delineation of the dune toe, crest and heel. The purpose of this paper is to introduce a multi-scale automated approach for extracting beach, dune (dune toe, dune crest and dune heel), and barrier island morphology. The automated approach introduced here extracts the shoreline and back-barrier shoreline based on elevation thresholds, and extracts the dune toe, dune crest and dune heel based on the average relative relief (RR) across multiple spatial scales of analysis. The multi-scale automated RR approach to extracting dune toe, dune crest, and dune heel based upon relative relief is more objective than traditional approaches because every pixel is analyzed across multiple computational scales and the identification of features is based on the calculated RR values. The RR approach out-performed contemporary approaches and represents a fast objective means to define important beach and dune features for predicting barrier island response to storms. The RR method also does not require that the dune toe, crest, or heel are spatially continuous, which is important because dune morphology is likely naturally variable alongshore.

Optimal Information Extraction of Laser Scanning Dataset by Scale-Adaptive Reduction

NASA Astrophysics Data System (ADS)

Zang, Y.; Yang, B.

2018-04-01

3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

Creation of a virtual cutaneous tissue bank

NASA Astrophysics Data System (ADS)

LaFramboise, William A.; Shah, Sujal; Hoy, R. W.; Letbetter, D.; Petrosko, P.; Vennare, R.; Johnson, Peter C.

2000-04-01

Cellular and non-cellular constituents of skin contain fundamental morphometric features and structural patterns that correlate with tissue function. High resolution digital image acquisitions performed using an automated system and proprietary software to assemble adjacent images and create a contiguous, lossless, digital representation of individual microscope slide specimens. Serial extraction, evaluation and statistical analysis of cutaneous feature is performed utilizing an automated analysis system, to derive normal cutaneous parameters comprising essential structural skin components. Automated digital cutaneous analysis allows for fast extraction of microanatomic dat with accuracy approximating manual measurement. The process provides rapid assessment of feature both within individual specimens and across sample populations. The images, component data, and statistical analysis comprise a bioinformatics database to serve as an architectural blueprint for skin tissue engineering and as a diagnostic standard of comparison for pathologic specimens.

Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Perdomo, Oscar; Arevalo, John; González, Fabio A.

2017-11-01

Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

Long-term penile morphometric alterations in patients treated with robot-assisted versus open radical prostatectomy.

PubMed

Capogrosso, P; Ventimiglia, E; Cazzaniga, W; Stabile, A; Pederzoli, F; Boeri, L; Gandaglia, G; Dehò, F; Briganti, A; Montorsi, F; Salonia, A

2018-01-01

Neglected side effects after radical prostatectomy have been previously reported. In this context, the prevalence of penile morphometric alterations has never been assessed in robot-assisted radical prostatectomy series. We aimed to assess prevalence of and predictors of penile morphometric alterations (i.e. penile shortening or penile morphometric deformation) at long-term follow-up in patients submitted to either robot-assisted (robot-assisted radical prostatectomy) or open radical prostatectomy. Sexually active patients after either robot-assisted radical prostatectomy or open radical prostatectomy prospectively completed a 28-item questionnaire, with sensitive issues regarding sexual function, namely orgasmic functioning, climacturia and changes in morphometric characteristics of the penis. Only patients with a post-operative follow-up ≥ 24 months were included. Patients submitted to either adjuvant or salvage therapies or those who refused to comprehensively complete the questionnaire were excluded from the analyses. A propensity-score matching analysis was implemented to control for baseline differences between groups. Logistic regression models tested potential predictors of penile morphometric alterations at long-term post-operative follow-up. Overall, 67 (50%) and 67 (50%) patients were included after open radical prostatectomy or robot-assisted radical prostatectomy, respectively. Self-rated post-operative penile shortening and penile morphometric deformation were reported by 75 (56%) and 29 (22.8%) patients, respectively. Rates of penile shortening and penile morphometric deformation were not different after open radical prostatectomy and robot-assisted radical prostatectomy [all p > 0.5]. At univariable analysis, self-reported penile morphometric alterations (either penile shortening or penile morphometric deformation) were significantly associated with baseline international index of erectile function-erectile function scores, body mass index, post-operative erectile function recovery, year of surgery and type of surgery (all p < 0.05). At multivariable analysis, robot-assisted radical prostatectomy was independently associated with a lower risk of post-operative penile morphometric alterations (OR: 0.38; 95% CI: 0.16-0.93). Self-perceived penile morphometric alterations were reported in one of two patients after radical prostatectomy at long-term follow-up, with open surgery associated with a potential higher risk of this self-perception. © 2017 American Society of Andrology and European Academy of Andrology.

A Comparison of Methods Used to Estimate the Height of Sand Dunes on Mars

NASA Technical Reports Server (NTRS)

Bourke, M. C.; Balme, M.; Beyer, R. A.; Williams, K. K.; Zimbelman, J.

2006-01-01

The collection of morphometric data on small-scale landforms from other planetary bodies is difficult. We assess four methods that can be used to estimate the height of aeolian dunes on Mars. These are (1) stereography, (2) slip face length, (3) profiling photoclinometry, and (4) Mars Orbiter Laser Altimeter (MOLA). Results show that there is good agreement among the methods when conditions are ideal. However, limitations inherent to each method inhibited their accurate application to all sites. Collectively, these techniques provide data on a range of morphometric parameters, some of which were not previously available for dunes on Mars. They include dune height, width, length, surface area, volume, and longitudinal and transverse profiles. Thc utilization of these methods will facilitate a more accurate analysis of aeolian dunes on Mars and enable comparison with dunes on other planetary surfaces.

A novel multiscale topo-morphometric approach for separating arteries and veins via pulmonary CT imaging

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Gao, Zhiyun; Alford, Sara; Sonka, Milan; Hoffman, Eric

2009-02-01

Distinguishing arterial and venous trees in pulmonary multiple-detector X-ray computed tomography (MDCT) images (contrast-enhanced or unenhanced) is a critical first step in the quantification of vascular geometry for purposes of determining, for instance, pulmonary hypertension, using vascular dimensions as a comparator for assessment of airway size, detection of pulmonary emboli and more. Here, a novel method is reported for separating arteries and veins in MDCT pulmonary images. Arteries and veins are modeled as two iso-intensity objects closely entwined with each other at different locations at various scales. The method starts with two sets of seeds -- one for arteries and another for veins. Initialized with seeds, arteries and veins grow iteratively while maintaining their spatial separation and eventually forming two disjoint objects at convergence. The method combines fuzzy distance transform, a morphologic feature, with a topologic connectivity property to iteratively separate finer and finer details starting at a large scale and progressing towards smaller scales. The method has been validated in mathematically generated tubular objects with different levels of fuzziness, scale and noise. Also, it has been successfully applied to clinical CT pulmonary data. The accuracy of the method has been quantitatively evaluated by comparing its results with manual outlining. For arteries, the method has yielded correctness of 81.7% at the cost of 6.7% false positives and 11.6% false negatives. Our method is very promising for automated separation of arteries and veins in MDCT pulmonary images even when there is no mark of intensity variation at conjoining locations.

Imaging of earthquake faults using small UAVs as a pathfinder for air and space observations

USGS Publications Warehouse

Donnellan, Andrea; Green, Joseph; Ansar, Adnan; Aletky, Joseph; Glasscoe, Margaret; Ben-Zion, Yehuda; Arrowsmith, J. Ramón; DeLong, Stephen B.

2017-01-01

Large earthquakes cause billions of dollars in damage and extensive loss of life and property. Geodetic and topographic imaging provide measurements of transient and long-term crustal deformation needed to monitor fault zones and understand earthquakes. Earthquake-induced strain and rupture characteristics are expressed in topographic features imprinted on the landscapes of fault zones. Small UAVs provide an efficient and flexible means to collect multi-angle imagery to reconstruct fine scale fault zone topography and provide surrogate data to determine requirements for and to simulate future platforms for air- and space-based multi-angle imaging.

Earth Studies Using L-band Synthetic Aperture Radar

NASA Technical Reports Server (NTRS)

Rosen, Paul A.

1999-01-01

L-band SAR has played an important role in studies of the Earth by revealing the nature of the larger-scale (decimeter) surface features. JERS-1, by supplying multi-seasonal coverage of the much of the earth, has demonstrated the importance of L-band SARs. Future L-band SARs such as ALOS and LightSAR will pave the way for science missions that use SAR instruments. As technology develops to enable lower cost SAR instruments, missions will evolve to each have a unique science focus. International coordination of multi-parameter constellations and campaigns will maximize science return.

Image Description with Local Patterns: An Application to Face Recognition

NASA Astrophysics Data System (ADS)

Zhou, Wei; Ahrary, Alireza; Kamata, Sei-Ichiro

In this paper, we propose a novel approach for presenting the local features of digital image using 1D Local Patterns by Multi-Scans (1DLPMS). We also consider the extentions and simplifications of the proposed approach into facial images analysis. The proposed approach consists of three steps. At the first step, the gray values of pixels in image are represented as a vector giving the local neighborhood intensity distrubutions of the pixels. Then, multi-scans are applied to capture different spatial information on the image with advantage of less computation than other traditional ways, such as Local Binary Patterns (LBP). The second step is encoding the local features based on different encoding rules using 1D local patterns. This transformation is expected to be less sensitive to illumination variations besides preserving the appearance of images embedded in the original gray scale. At the final step, Grouped 1D Local Patterns by Multi-Scans (G1DLPMS) is applied to make the proposed approach computationally simpler and easy to extend. Next, we further formulate boosted algorithm to extract the most discriminant local features. The evaluated results demonstrate that the proposed approach outperforms the conventional approaches in terms of accuracy in applications of face recognition, gender estimation and facial expression.

Structural control in sinkhole development and speleogenesis: a case study from the High Murge karst landscape (Apulia, Italy)

NASA Astrophysics Data System (ADS)

Pepe, M.; Parise, M.

2012-04-01

The Murge plateau is the main karst sector of Apulia, an almost entirely carbonate region of SE Italy. It can be, in turn, subdivided into two sectors: High Murge, the inland plateau, where remnants of an ancient tropical karst are still recognizable; and Low Murge, closer to the Adriatic Sea, with smoother karst morphologies and landforms, but, at the same time, hosting some of the longest underground karst system in the region (Parise, 1998, 2006). Even though showing low energy relief, the landscape of High Murge is very articulated when examined at greater detail, with several interesting karst features. Among these, sinkholes are definitely the most significant, showing a variety of typologies and, at the same time, a high frequency, both as individual features and as coalescent landforms, giving origin to more complex depressions (Parise, 2011). Previous studies carried out in the High Murge through morphometric analysis of the main sinkholes identified on the 1:25,000 scale topographic maps from the Italian Army Geographical Institute indicated their likely genesis in a low relief cockpit karst (Sauro, 1991). Over such landscape, developed in Upper Tertiary, a hydrographic pattern was superimposed, that partly opened some of the depressions, also dismantling sectors of the karst relief and producing talus deposits (Caldara & Ciaranfi, 1988). In the present work we take into consideration the southern countryside of Ruvo di Puglia. Choice of the area, which extends over 15 km2, was dictated by presence of a high number of sinkholes, and of several important caves with prevailing vertical development, including the deepest pit ever explored in Apulia (Grave della Ferratella, depth - 320 m). The cave is nowadays not accessible, due to clogging caused by land use changes during the 80's. Based upon extensive field surveys and interpretation of multi-year aerial photographs (time range 1955-2003), integrated by surveying in selected caves, the main hydro-geomorphological and karst features of the area have been outlined. Structural data have been collected at both the outcrop and within caves, in order to assess the likely connections between the karst drainage pattern and the main tectonic features. Eventually, a karst geomorphological map has been produced to describe the karst character of the landforms in the area, with a distinction of the recognized sinkholes in different categories in function of their genesis. In addition to the strictly geomorphological theme, outcomes of this study may be of interest to cavers for planning future activities in this and nearby areas, in the attempt to identify new caves, or extend the present development of those already known.

Addressing scale dependence in roughness and morphometric statistics derived from point cloud data.

NASA Astrophysics Data System (ADS)

Buscombe, D.; Wheaton, J. M.; Hensleigh, J.; Grams, P. E.; Welcker, C. W.; Anderson, K.; Kaplinski, M. A.

2015-12-01

The heights of natural surfaces can be measured with such spatial density that almost the entire spectrum of physical roughness scales can be characterized, down to the morphological form and grain scales. With an ability to measure 'microtopography' comes a demand for analytical/computational tools for spatially explicit statistical characterization of surface roughness. Detrended standard deviation of surface heights is a popular means to create continuous maps of roughness from point cloud data, using moving windows and reporting window-centered statistics of variations from a trend surface. If 'roughness' is the statistical variation in the distribution of relief of a surface, then 'texture' is the frequency of change and spatial arrangement of roughness. The variance in surface height as a function of frequency obeys a power law. In consequence, roughness is dependent on the window size through which it is examined, which has a number of potential disadvantages: 1) the choice of window size becomes crucial, and obstructs comparisons between data; 2) if windows are large relative to multiple roughness scales, it is harder to discriminate between those scales; 3) if roughness is not scaled by the texture length scale, information on the spacing and clustering of roughness `elements' can be lost; and 4) such practice is not amenable to models describing the scattering of light and sound from rough natural surfaces. We discuss the relationship between roughness and texture. Some useful parameters which scale vertical roughness to characteristic horizontal length scales are suggested, with examples of bathymetric point clouds obtained using multibeam from two contrasting riverbeds, namely those of the Colorado River in Grand Canyon, and the Snake River in Hells Canyon. Such work, aside from automated texture characterization and texture segmentation, roughness and grain size calculation, might also be useful for feature detection and classification from point clouds.

Telescopic multi-resolution augmented reality

NASA Astrophysics Data System (ADS)

Jenkins, Jeffrey; Frenchi, Christopher; Szu, Harold

2014-05-01

To ensure a self-consistent scaling approximation, the underlying microscopic fluctuation components can naturally influence macroscopic means, which may give rise to emergent observable phenomena. In this paper, we describe a consistent macroscopic (cm-scale), mesoscopic (micron-scale), and microscopic (nano-scale) approach to introduce Telescopic Multi-Resolution (TMR) into current Augmented Reality (AR) visualization technology. We propose to couple TMR-AR by introducing an energy-matter interaction engine framework that is based on known Physics, Biology, Chemistry principles. An immediate payoff of TMR-AR is a self-consistent approximation of the interaction between microscopic observables and their direct effect on the macroscopic system that is driven by real-world measurements. Such an interdisciplinary approach enables us to achieve more than multiple scale, telescopic visualization of real and virtual information but also conducting thought experiments through AR. As a result of the consistency, this framework allows us to explore a large dimensionality parameter space of measured and unmeasured regions. Towards this direction, we explore how to build learnable libraries of biological, physical, and chemical mechanisms. Fusing analytical sensors with TMR-AR libraries provides a robust framework to optimize testing and evaluation through data-driven or virtual synthetic simulations. Visualizing mechanisms of interactions requires identification of observable image features that can indicate the presence of information in multiple spatial and temporal scales of analog data. The AR methodology was originally developed to enhance pilot-training as well as `make believe' entertainment industries in a user-friendly digital environment We believe TMR-AR can someday help us conduct thought experiments scientifically, to be pedagogically visualized in a zoom-in-and-out, consistent, multi-scale approximations.

Identification of Novel Pro-Migratory, Cancer-Associated Genes Using Quantitative, Microscopy-Based Screening

PubMed Central

Naffar-Abu-Amara, Suha; Shay, Tal; Galun, Meirav; Cohen, Naomi; Isakoff, Steven J.; Kam, Zvi; Geiger, Benjamin

2008-01-01

Background Cell migration is a highly complex process, regulated by multiple genes, signaling pathways and external stimuli. To discover genes or pharmacological agents that can modulate the migratory activity of cells, screening strategies that enable the monitoring of diverse migratory parameters in a large number of samples are necessary. Methodology In the present study, we describe the development of a quantitative, high-throughput cell migration assay, based on a modified phagokinetic tracks (PKT) procedure, and apply it for identifying novel pro-migratory genes in a cancer-related gene library. In brief, cells are seeded on fibronectin-coated 96-well plates, covered with a monolayer of carboxylated latex beads. Motile cells clear the beads, located along their migratory paths, forming tracks that are visualized using an automated, transmitted-light screening microscope. The tracks are then segmented and characterized by multi-parametric, morphometric analysis, resolving a variety of morphological and kinetic features. Conclusions In this screen we identified 4 novel genes derived from breast carcinoma related cDNA library, whose over-expression induces major alteration in the migration of the stationary MCF7 cells. This approach can serve for high throughput screening for novel ways to modulate cellular migration in pathological states such as tumor metastasis and invasion. PMID:18213366

Real-time ultrasound image classification for spine anesthesia using local directional Hadamard features.

PubMed

Pesteie, Mehran; Abolmaesumi, Purang; Ashab, Hussam Al-Deen; Lessoway, Victoria A; Massey, Simon; Gunka, Vit; Rohling, Robert N

2015-06-01

Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for detecting the laminae and facet joints in ultrasound images has been proposed. The system has the potential to assist the anesthesiologists in quickly finding the target plane for epidural steroid injections and facet joint injections.

A hierarchical pyramid method for managing large-scale high-resolution drainage networks extracted from DEM

NASA Astrophysics Data System (ADS)

Bai, Rui; Tiejian, Li; Huang, Yuefei; Jiaye, Li; Wang, Guangqian; Yin, Dongqin

2015-12-01

The increasing resolution of Digital Elevation Models (DEMs) and the development of drainage network extraction algorithms make it possible to develop high-resolution drainage networks for large river basins. These vector networks contain massive numbers of river reaches with associated geographical features, including topological connections and topographical parameters. These features create challenges for efficient map display and data management. Of particular interest are the requirements of data management for multi-scale hydrological simulations using multi-resolution river networks. In this paper, a hierarchical pyramid method is proposed, which generates coarsened vector drainage networks from the originals iteratively. The method is based on the Horton-Strahler's (H-S) order schema. At each coarsening step, the river reaches with the lowest H-S order are pruned, and their related sub-basins are merged. At the same time, the topological connections and topographical parameters of each coarsened drainage network are inherited from the former level using formulas that are presented in this study. The method was applied to the original drainage networks of a watershed in the Huangfuchuan River basin extracted from a 1-m-resolution airborne LiDAR DEM and applied to the full Yangtze River basin in China, which was extracted from a 30-m-resolution ASTER GDEM. In addition, a map-display and parameter-query web service was published for the Mississippi River basin, and its data were extracted from the 30-m-resolution ASTER GDEM. The results presented in this study indicate that the developed method can effectively manage and display massive amounts of drainage network data and can facilitate multi-scale hydrological simulations.

Multi-scale clustering by building a robust and self correcting ultrametric topology on data points.

PubMed

Fushing, Hsieh; Wang, Hui; Vanderwaal, Kimberly; McCowan, Brenda; Koehl, Patrice

2013-01-01

The advent of high-throughput technologies and the concurrent advances in information sciences have led to an explosion in size and complexity of the data sets collected in biological sciences. The biggest challenge today is to assimilate this wealth of information into a conceptual framework that will help us decipher biological functions. A large and complex collection of data, usually called a data cloud, naturally embeds multi-scale characteristics and features, generically termed geometry. Understanding this geometry is the foundation for extracting knowledge from data. We have developed a new methodology, called data cloud geometry-tree (DCG-tree), to resolve this challenge. This new procedure has two main features that are keys to its success. Firstly, it derives from the empirical similarity measurements a hierarchy of clustering configurations that captures the geometric structure of the data. This hierarchy is then transformed into an ultrametric space, which is then represented via an ultrametric tree or a Parisi matrix. Secondly, it has a built-in mechanism for self-correcting clustering membership across different tree levels. We have compared the trees generated with this new algorithm to equivalent trees derived with the standard Hierarchical Clustering method on simulated as well as real data clouds from fMRI brain connectivity studies, cancer genomics, giraffe social networks, and Lewis Carroll's Doublets network. In each of these cases, we have shown that the DCG trees are more robust and less sensitive to measurement errors, and that they provide a better quantification of the multi-scale geometric structures of the data. As such, DCG-tree is an effective tool for analyzing complex biological data sets.

Scalable non-negative matrix tri-factorization.

PubMed

Čopar, Andrej; Žitnik, Marinka; Zupan, Blaž

2017-01-01

Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining. Matrix factorization learns a latent data model that takes a data matrix and transforms it into a latent feature space enabling generalization, noise removal and feature discovery. However, factorization algorithms are numerically intensive, and hence there is a pressing challenge to scale current algorithms to work with large datasets. Our focus in this paper is matrix tri-factorization, a popular method that is not limited by the assumption of standard matrix factorization about data residing in one latent space. Matrix tri-factorization solves this by inferring a separate latent space for each dimension in a data matrix, and a latent mapping of interactions between the inferred spaces, making the approach particularly suitable for biomedical data mining. We developed a block-wise approach for latent factor learning in matrix tri-factorization. The approach partitions a data matrix into disjoint submatrices that are treated independently and fed into a parallel factorization system. An appealing property of the proposed approach is its mathematical equivalence with serial matrix tri-factorization. In a study on large biomedical datasets we show that our approach scales well on multi-processor and multi-GPU architectures. On a four-GPU system we demonstrate that our approach can be more than 100-times faster than its single-processor counterpart. A general approach for scaling non-negative matrix tri-factorization is proposed. The approach is especially useful parallel matrix factorization implemented in a multi-GPU environment. We expect the new approach will be useful in emerging procedures for latent factor analysis, notably for data integration, where many large data matrices need to be collectively factorized.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Geometric Morphometrics on Gene Expression Patterns Within Phenotypes: A Case Example on Limb Development

PubMed Central

Martínez-Abadías, Neus; Mateu, Roger; Niksic, Martina; Russo, Lucia; Sharpe, James

2016-01-01

How the genotype translates into the phenotype through development is critical to fully understand the evolution of phenotypes. We propose a novel approach to directly assess how changes in gene expression patterns are associated with changes in morphology using the limb as a case example. Our method combines molecular biology techniques, such as whole-mount in situ hybridization, with image and shape analysis, extending the use of Geometric Morphometrics to the analysis of nonanatomical shapes, such as gene expression domains. Elliptical Fourier and Procrustes-based semilandmark analyses were used to analyze the variation and covariation patterns of the limb bud shape with the expression patterns of two relevant genes for limb morphogenesis, Hoxa11 and Hoxa13. We devised a multiple thresholding method to semiautomatically segment gene domains at several expression levels in large samples of limb buds from C57Bl6 mouse embryos between 10 and 12 postfertilization days. Besides providing an accurate phenotyping tool to quantify the spatiotemporal dynamics of gene expression patterns within developing structures, our morphometric analyses revealed high, non-random, and gene-specific variation undergoing canalization during limb development. Our results demonstrate that Hoxa11 and Hoxa13, despite being paralogs with analogous functions in limb patterning, show clearly distinct dynamic patterns, both in shape and size, and are associated differently with the limb bud shape. The correspondence between our results and already well-established molecular processes underlying limb development confirms that this morphometric approach is a powerful tool to extract features of development regulating morphogenesis. Such multilevel analyses are promising in systems where not so much molecular information is available and will advance our understanding of the genotype–phenotype map. In systematics, this knowledge will increase our ability to infer how evolution modified a common developmental pattern to generate a wide diversity of morphologies, as in the vertebrate limb. PMID:26377442

Choice matters: incipient speciation in Gyrodactylus corydori (Monogenoidea: Gyrodactylidae).

PubMed

Bueno-Silva, Marlus; Boeger, Walter A; Pie, Marcio R

2011-05-01

We investigated how Gyrodactylus corydoriBueno-Silva and Boeger, 2009 exploits two sympatric host species, Corydoras paleatus (Jenyns, 1842) and Corydoras ehrhardti Steindachner, 1910. Specimens of G. corydori were collected from the Piraquara and Miringuava Rivers, State of Paraná, Brazil, between 2005 and 2006. A total of 167 parasites was measured from both host species. Nine morphometric features of the haptoral sclerites were measured and analyzed by discriminant analysis, cluster analysis and multivariate analysis of variance. A fragment of the mitochondrial cytochrome oxidase I gene (COI) (∼740 bp) and the rDNA internal transcribed spacers (ITS) (∼1200 bp) of G. corydori were sequenced. Bayesian and parsimony analyses of COI recognized two genetically structured clades of G. corydori, which corresponded closely with the two species of Corydoras. Twenty-eight haplotypes were detected (18 were exclusive to C. ehrhardti and seven were exclusive to C. paleatus). The same general pattern between parasites and host species was observed in the morphometric analyses. Nevertheless, poor correlation of genetic and morphometric variation strongly supports the plastic nature of the morphological variation of haptoral sclerites. The existence of two clades with limited gene flow would suggest that G. corydori already represents two cryptic species. However, the morphometric and molecular data showed that there is insufficient evidence to support two valid species. The low COI (0.1-6.2%) and ITS (0.09-3.5%) divergence within G. corydori suggest a recent separation of the lineages between distinct host species (less than 1 million years). As the hypothesis of secondary contact of the parasite demographic history was rejected, our results point to the possibility of sympatric incipient ongoing speciation of G. corydori to form distinct parasite lineages adapted to C. ehrhardti and C. paleatus. This may be a common event within the Gyrodactylidae, adding a yet unreported mode of adaptive speciation that helps to understand its rate of diversification. Copyright © 2011 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Simulation of reaction diffusion processes over biologically relevant size and time scales using multi-GPU workstations

PubMed Central

Hallock, Michael J.; Stone, John E.; Roberts, Elijah; Fry, Corey; Luthey-Schulten, Zaida

2014-01-01

Simulation of in vivo cellular processes with the reaction-diffusion master equation (RDME) is a computationally expensive task. Our previous software enabled simulation of inhomogeneous biochemical systems for small bacteria over long time scales using the MPD-RDME method on a single GPU. Simulations of larger eukaryotic systems exceed the on-board memory capacity of individual GPUs, and long time simulations of modest-sized cells such as yeast are impractical on a single GPU. We present a new multi-GPU parallel implementation of the MPD-RDME method based on a spatial decomposition approach that supports dynamic load balancing for workstations containing GPUs of varying performance and memory capacity. We take advantage of high-performance features of CUDA for peer-to-peer GPU memory transfers and evaluate the performance of our algorithms on state-of-the-art GPU devices. We present parallel e ciency and performance results for simulations using multiple GPUs as system size, particle counts, and number of reactions grow. We also demonstrate multi-GPU performance in simulations of the Min protein system in E. coli. Moreover, our multi-GPU decomposition and load balancing approach can be generalized to other lattice-based problems. PMID:24882911

Simulation of reaction diffusion processes over biologically relevant size and time scales using multi-GPU workstations.

PubMed

Hallock, Michael J; Stone, John E; Roberts, Elijah; Fry, Corey; Luthey-Schulten, Zaida

2014-05-01

Simulation of in vivo cellular processes with the reaction-diffusion master equation (RDME) is a computationally expensive task. Our previous software enabled simulation of inhomogeneous biochemical systems for small bacteria over long time scales using the MPD-RDME method on a single GPU. Simulations of larger eukaryotic systems exceed the on-board memory capacity of individual GPUs, and long time simulations of modest-sized cells such as yeast are impractical on a single GPU. We present a new multi-GPU parallel implementation of the MPD-RDME method based on a spatial decomposition approach that supports dynamic load balancing for workstations containing GPUs of varying performance and memory capacity. We take advantage of high-performance features of CUDA for peer-to-peer GPU memory transfers and evaluate the performance of our algorithms on state-of-the-art GPU devices. We present parallel e ciency and performance results for simulations using multiple GPUs as system size, particle counts, and number of reactions grow. We also demonstrate multi-GPU performance in simulations of the Min protein system in E. coli . Moreover, our multi-GPU decomposition and load balancing approach can be generalized to other lattice-based problems.

Landscape variation of seasonal pool plant communities in forests of northern Minnesota, USA

Treesearch

Brian Palik; Dwight Streblow; Leanne Egeland; Richard Buech

2007-01-01

Seasonal forest pools are abundant in the northern Great Lakes forest landscape, but the range of variation in their plant communities and the relationship of this variation to multi-scale landscape features remains poorly quantified. We examined seasonal pools in forests of northern Minnesota USA with the objective of quantifying the range of variation in plant...

Biomimetic surface structuring using cylindrical vector femtosecond laser beams

NASA Astrophysics Data System (ADS)

Skoulas, Evangelos; Manousaki, Alexandra; Fotakis, Costas; Stratakis, Emmanuel

2017-03-01

We report on a new, single-step and scalable method to fabricate highly ordered, multi-directional and complex surface structures that mimic the unique morphological features of certain species found in nature. Biomimetic surface structuring was realized by exploiting the unique and versatile angular profile and the electric field symmetry of cylindrical vector (CV) femtosecond (fs) laser beams. It is shown that, highly controllable, periodic structures exhibiting sizes at nano-, micro- and dual- micro/nano scales can be directly written on Ni upon line and large area scanning with radial and azimuthal polarization beams. Depending on the irradiation conditions, new complex multi-directional nanostructures, inspired by the Shark’s skin morphology, as well as superhydrophobic dual-scale structures mimicking the Lotus’ leaf water repellent properties can be attained. It is concluded that the versatility and features variations of structures formed is by far superior to those obtained via laser processing with linearly polarized beams. More important, by exploiting the capabilities offered by fs CV fields, the present technique can be further extended to fabricate even more complex and unconventional structures. We believe that our approach provides a new concept in laser materials processing, which can be further exploited for expanding the breadth and novelty of applications.

A fault diagnosis scheme for rolling bearing based on local mean decomposition and improved multiscale fuzzy entropy

NASA Astrophysics Data System (ADS)

Li, Yongbo; Xu, Minqiang; Wang, Rixin; Huang, Wenhu

2016-01-01

This paper presents a new rolling bearing fault diagnosis method based on local mean decomposition (LMD), improved multiscale fuzzy entropy (IMFE), Laplacian score (LS) and improved support vector machine based binary tree (ISVM-BT). When the fault occurs in rolling bearings, the measured vibration signal is a multi-component amplitude-modulated and frequency-modulated (AM-FM) signal. LMD, a new self-adaptive time-frequency analysis method can decompose any complicated signal into a series of product functions (PFs), each of which is exactly a mono-component AM-FM signal. Hence, LMD is introduced to preprocess the vibration signal. Furthermore, IMFE that is designed to avoid the inaccurate estimation of fuzzy entropy can be utilized to quantify the complexity and self-similarity of time series for a range of scales based on fuzzy entropy. Besides, the LS approach is introduced to refine the fault features by sorting the scale factors. Subsequently, the obtained features are fed into the multi-fault classifier ISVM-BT to automatically fulfill the fault pattern identifications. The experimental results validate the effectiveness of the methodology and demonstrate that proposed algorithm can be applied to recognize the different categories and severities of rolling bearings.

Highly efficient spatial data filtering in parallel using the opensource library CPPPO

NASA Astrophysics Data System (ADS)

Municchi, Federico; Goniva, Christoph; Radl, Stefan

2016-10-01

CPPPO is a compilation of parallel data processing routines developed with the aim to create a library for "scale bridging" (i.e. connecting different scales by mean of closure models) in a multi-scale approach. CPPPO features a number of parallel filtering algorithms designed for use with structured and unstructured Eulerian meshes, as well as Lagrangian data sets. In addition, data can be processed on the fly, allowing the collection of relevant statistics without saving individual snapshots of the simulation state. Our library is provided with an interface to the widely-used CFD solver OpenFOAM®, and can be easily connected to any other software package via interface modules. Also, we introduce a novel, extremely efficient approach to parallel data filtering, and show that our algorithms scale super-linearly on multi-core clusters. Furthermore, we provide a guideline for choosing the optimal Eulerian cell selection algorithm depending on the number of CPU cores used. Finally, we demonstrate the accuracy and the parallel scalability of CPPPO in a showcase focusing on heat and mass transfer from a dense bed of particles.

Contrasting Patterns in Solitary and Eusocial Bees While Responding to Landscape Features in the Brazilian Cerrado: a Multiscaled Perspective.

PubMed

Silva, D P; Nogueira, D S; De Marco, P

2017-06-01

Landscape structure is an important determinant of biological fluxes and species composition, but species do not respond equally to landscape features or spatial extents. Evaluating "multi-scale" responses of species to landscape structure is an important framework to be considered, allowing insights about habitat requirements for different groups. We evaluated the response of Brazilian Cerrado's bees (eusocial vs. solitary ones) to both the amount and isolation of remnant vegetation in eight nested multiple-local scales. Response variables included abundance, observed, and estimated species richness, and beta diversity (split into nestedness and turnover resultant dissimilarities). Eusocial species' abundance responded to landscape structure at narrow scales of fragment isolation (250 m of radius from sampling sites), while solitary species' abundance responded to broader scales to fragment area (2000 m). Eusocial species nestedness also responded to landscape features in broader scales (1500 m), especially to increasing fragment isolation. However, all the remaining response variables did not respond to any other landscape variables in any spatial scale considered. Such contrasting responses of the abundances of eusocial vs. solitary species are related to the inherent life-history traits of each group. Important attributes in this context are different requirements on food resources, population features, and flight abilities. Species-specific dispersal abilities may be the main determinants of the nested patterns found for eusocial species at 1500 m. Considering these results, we suggest that different bee groups are considered separately in further landscape analyses, especially in other Brazilian biomes, for a better understanding of landscape effects on these organisms.

Application of finite elements heterogeneous multi-scale method to eddy currents non destructive testing of carbon composites material

NASA Astrophysics Data System (ADS)

Khebbab, Mohamed; Feliachi, Mouloud; El Hadi Latreche, Mohamed

2018-03-01

In this present paper, a simulation of eddy current non-destructive testing (EC NDT) on unidirectional carbon fiber reinforced polymer is performed; for this magneto-dynamic formulation in term of magnetic vector potential is solved using finite element heterogeneous multi-scale method (FE HMM). FE HMM has as goal to compute the homogenized solution without calculating the homogenized tensor explicitly, the solution is based only on the physical characteristic known in micro domain. This feature is well adapted to EC NDT to evaluate defect in carbon composite material in microscopic scale, where the defect detection is performed by coil impedance measurement; the measurement value is intimately linked to material characteristic in microscopic level. Based on this, our model can handle different defects such as: cracks, inclusion, internal electrical conductivity changes, heterogeneities, etc. The simulation results were compared with the solution obtained with homogenized material using mixture law, a good agreement was found.

A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture

PubMed Central

Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis

2015-01-01

A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Computer-assisted sperm morphometry fluorescence-based analysis has potential to determine progeny sex.

PubMed

Santolaria, Pilar; Pauciullo, Alfredo; Silvestre, Miguel A; Vicente-Fiel, Sandra; Villanova, Leyre; Pinton, Alain; Viruel, Juan; Sales, Ester; Yániz, Jesús L

2016-01-01

This study was designed to determine the ability of computer-assisted sperm morphometry analysis (CASA-Morph) with fluorescence to discriminate between spermatozoa carrying different sex chromosomes from the nuclear morphometrics generated and different statistical procedures in the bovine species. The study was divided into two experiments. The first was to study the morphometric differences between X- and Y-chromosome-bearing spermatozoa (SX and SY, respectively). Spermatozoa from eight bulls were processed to assess simultaneously the sex chromosome by FISH and sperm morphometry by fluorescence-based CASA-Morph. SX cells were larger than SY cells on average (P < 0.001) although with important differences between bulls. A simultaneous evaluation of all the measured features by discriminant analysis revealed that nuclear area and average fluorescence intensity were the variables selected by stepwise discriminant function analysis as the best discriminators between SX and SY. In the second experiment, the sperm nuclear morphometric results from CASA-Morph in nonsexed (mixed SX and SY) and sexed (SX) semen samples from four bulls were compared. FISH allowed a successful classification of spermatozoa according to their sex chromosome content. X-sexed spermatozoa displayed a larger size and fluorescence intensity than nonsexed spermatozoa (P < 0.05). We conclude that the CASA-Morph fluorescence-based method has the potential to find differences between X- and Y-chromosome-bearing spermatozoa in bovine species although more studies are needed to increase the precision of sex determination by this technique.

Morphological and morphometric features of nematode-cysts in Gymnotus inaequilabiatus liver in the Brazilian Pantanal.

PubMed

Galindo, Gizela Melina; Rodrigues, Robson Andrade; Marcondes, Sandriely Fernanda; Soares, Priscilla; Tavares, Luiz Eduardo Roland; Fernandes, Carlos Eurico

2017-01-01

The aim of this study was to determine the morphometric measures and morphological aspects of nematode-cysts in Gymnotus inaequilabiatus, and the presence of melanomacrophage centers (MMCs) associated with the periphery of cysts and in the liver parenchyma. Adult specimens, 34 female (123.1 ± 43.9g) and 45 male (135.5 ± 43.4g), from Paraguay River, Corumbá, Brazil, were used. The number of nematode-cysts was determined in 79 livers and 25 of them randomly selected for histopathological analysis and morphometric measures of nematode-cysts (mean diameter, thickness of collagen layer, and cyst-wall layer). The percentage of cysts with MMCs on the periphery and density in the liver parenchyma was estimated. The average number of macroscopic cysts was of 48.7 ± 2.78. Granulomatous reaction was observed surrounding the cysts. Diameter, collagen layer and cyst-wall measurements were 293.0 ± 75.18 (µm), 17.72 ± 6.01 (µm) and 12.21 ± 9.51 (µm), respectively. The number of nematode-cysts was correlated with hepatosomatic index, (r=0.26, P<0.05). Collagen layer was correlated with cyst diameter (r=0.62, P<0.01). Pericystic and parenchymatous MMCs were moderately (r=0.48) and highly (r=0.90) correlated with nematode-cysts number. Morphological characteristics of hepatic tissue and cysts-nematodes measures suggest that G. inaequilabiatus acts as a paratenic host to nematodes in the larval stage.

Geometric morphometric footprint analysis of young women

PubMed Central

2013-01-01

Background Most published attempts to quantify footprint shape are based on a small number of measurements. We applied geometric morphometric methods to study shape variation of the complete footprint outline in a sample of 83 adult women. Methods The outline of the footprint, including the toes, was represented by a comprehensive set of 85 landmarks and semilandmarks. Shape coordinates were computed by Generalized Procrustes Analysis. Results The first four principal components represented the major axes of variation in foot morphology: low-arched versus high-arched feet, long and narrow versus short and wide feet, the relative length of the hallux, and the relative length of the forefoot. These shape features varied across the measured individuals without any distinct clusters or discrete types of footprint shape. A high body mass index (BMI) was associated with wide and flat feet, and a high frequency of wearing high-heeled shoes was associated with a larger forefoot area of the footprint and a relatively long hallux. Larger feet had an increased length-to-width ratio of the footprint, a lower-arched foot, and longer toes relative to the remaining foot. Footprint shape differed on average between left and right feet, and the variability of footprint asymmetry increased with BMI. Conclusions Foot shape is affected by lifestyle factors even in a sample of young women (median age 23 years). Geometric morphometrics proved to be a powerful tool for the detailed analysis of footprint shape that is applicable in various scientific disciplines, including forensics, orthopedics, and footwear design. PMID:23886074

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis.

PubMed

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3-10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception.

Intraspecific scaling of the minimum metabolic cost of transport in leghorn chickens (Gallus gallus domesticus): links with limb kinematics, morphometrics and posture.

PubMed

Rose, Kayleigh A; Nudds, Robert L; Codd, Jonathan R

2015-04-01

The minimum metabolic cost of transport (CoTmin; J kg(-1) m(-1)) scales negatively with increasing body mass (∝Mb (-1/3)) across species from a wide range of taxa associated with marked differences in body plan. At the intraspecific level, or between closely related species, however, CoTmin does not always scale with Mb. Similarity in physiology, dynamics of movement, skeletal geometry and posture between closely related individuals is thought to be responsible for this phenomenon, despite the fact that energetic, kinematic and morphometric data are rarely collected together. We examined the relationship between these integrated components of locomotion in leghorn chickens (Gallus gallus domesticus) selectively bred for large and bantam (miniature) varieties. Interspecific allometry predicts a CoTmin ∼16% greater in bantams compared with the larger variety. However, despite 38% and 23% differences in Mb and leg length, respectively, the two varieties shared an identical walking CoTmin, independent of speed and equal to the allometric prediction derived from interspecific data for the larger variety. Furthermore, the two varieties moved with dynamic similarity and shared geometrically similar appendicular and axial skeletons. Hip height, however, did not scale geometrically and the smaller variety had more erect limbs, contrary to interspecific scaling trends. The lower than predicted CoTmin in bantams for their Mb was associated with both the more erect posture and a lower cost per stride (J kg(-1) stride(-1)). Therefore, our findings are consistent with the notion that a more erect limb is associated with a lower CoTmin and with the previous assumption that similarity in skeletal shape, inherently linked to walking dynamics, is associated with similarity in CoTmin. © 2015. Published by The Company of Biologists Ltd.

Intraspecific scaling of the minimum metabolic cost of transport in leghorn chickens (Gallus gallus domesticus): links with limb kinematics, morphometrics and posture

PubMed Central

Rose, Kayleigh A.; Nudds, Robert L.; Codd, Jonathan R.

2015-01-01

ABSTRACT The minimum metabolic cost of transport (CoTmin; J kg−1 m−1) scales negatively with increasing body mass (∝Mb−1/3) across species from a wide range of taxa associated with marked differences in body plan. At the intraspecific level, or between closely related species, however, CoTmin does not always scale with Mb. Similarity in physiology, dynamics of movement, skeletal geometry and posture between closely related individuals is thought to be responsible for this phenomenon, despite the fact that energetic, kinematic and morphometric data are rarely collected together. We examined the relationship between these integrated components of locomotion in leghorn chickens (Gallus gallus domesticus) selectively bred for large and bantam (miniature) varieties. Interspecific allometry predicts a CoTmin ∼16% greater in bantams compared with the larger variety. However, despite 38% and 23% differences in Mb and leg length, respectively, the two varieties shared an identical walking CoTmin, independent of speed and equal to the allometric prediction derived from interspecific data for the larger variety. Furthermore, the two varieties moved with dynamic similarity and shared geometrically similar appendicular and axial skeletons. Hip height, however, did not scale geometrically and the smaller variety had more erect limbs, contrary to interspecific scaling trends. The lower than predicted CoTmin in bantams for their Mb was associated with both the more erect posture and a lower cost per stride (J kg−1 stride−1). Therefore, our findings are consistent with the notion that a more erect limb is associated with a lower CoTmin and with the previous assumption that similarity in skeletal shape, inherently linked to walking dynamics, is associated with similarity in CoTmin. PMID:25657211

Characterising the Geomorphology of Forested Floodplains Using High Resolution Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Sear, D. A.; Brasington, J.; Darby, S. E.

2007-12-01

Forested floodplain environments represent the undisturbed land cover of most temperate and tropical river systems, but they are under threat from human resource management (Hughes et al., 2005, FLOBAR II Project report). A scientific understanding of forest floodplain processes therefore has relevance to ecosystem conservation and restoration, and the interpretation of pre-historic river and floodplain evolution. Empirical research has highlighted how overbank flows are relatively shallow and strongly modified by floodplain topography and the presence of vegetation and organic debris on the woodland floor [Jeffries et al., 2003, Geomorphology, 51, 61-80; Millington and Sear, 2007, Earth. Surf. Proc. Landforms, 32, doi: 10.1002/esp.1552]. In such instances flow blockage and diversions are common, and there is the possibility of frequent switches from sub-critical to locally super-critical flow. Such conditions also favour turbulence generation, both by wakes and by shear. Consequently, the floodplain terrain (where we take 'terrain' to include the underlying topography, root structures, and organic debris) plays a key role in modulating the processes of erosion and sedimentation that underpin the physical habitat diversity and hydraulic characteristics of complex wooded floodplain surfaces. However, despite the importance of these issues, as yet there are no formal, quantitative, descriptions of the highly complex and spatially diverse micro- and meso-topography that appears to be characteristic of forested floodplain surfaces. To address this gap, we have undertaken detailed surveys on a small floodplain reach within the Highland Water Research Catchment (HWRC: see http://www.geog.soton.ac.uk/research/nfrc/default.asp), which is a UK national reference site for lowland floodplain forest streams. This involved the deployment of a Leica ScanStation terrestrial laser-scanner from 14 setups and ranges of less than 30 m to acquire an extremely high resolution, accurate (185 million xyz observations, with absolute mean registration errors of 2 mm) 3-d point cloud model of the floodplain. These raw data were processed using a combination of Leica CYCLONE and bespoke filtering algorithms to construct a multi-resolution DTM of the forested floodplain at hitherto unprecedented detail (median point density ~4500 pts m-2). A key point is that the extreme precision and point density permit relevant features of the terrain (micro-topography, protruding roots, branches and stems, and surficial debris) that contribute to the floodplain roughness, to be readily and directly be incorporated in the DTM as topographic features. To characterise the morphology of the floodplain surface we have used the DTM to analyse a range of floodplain morphometric indices, in particular focusing on derivative surface roughness metrics (including roughness height) which are relevant in the parameterization of flow resistance. These are analysed at the floodplain scale to show the spatial distribution of roughness, and at a patch scale selected from a simple classification of floodplain surface. The analysis demonstrates spatial variability in roughness metrics at both scales, which have implications for parameterising flow resistance in models of wooded floodplains.

Patterns of genetic and morphometric diversity in baobab (Adansonia digitata) populations across different climatic zones of Benin (West Africa).

PubMed

Assogbadjo, A E; Kyndt, T; Sinsin, B; Gheysen, G; van Damme, P

2006-05-01

Baobab (Adansonia digitata) is a multi-purpose tree used daily by rural African communities. The present study aimed at investigating the level of morphometric and genetic variation and spatial genetic structure within and between threatened baobab populations from the three climatic zones of Benin. A total of 137 individuals from six populations were analysed using morphometric data as well as molecular marker data generated using the AFLP technique. Five primer pairs resulted in a total of 217 scored bands with 78.34 % of them being polymorphic. A two-level AMOVA of 137 individuals from six baobab populations revealed 82.37 % of the total variation within populations and 17.63 % among populations (P < 0.001). Analysis of population structure with allele-frequency based F-statistics revealed a global F(ST) of 0.127 +/- 0.072 (P < 0.001). The mean gene diversity within populations (H(S)) and the average gene diversity between populations (D(ST)) were estimated at 0.309 +/- 0.000 and 0.045 +/- 0.072, respectively. Baobabs in the Sudanian and Sudan-Guinean zones of Benin were short and produced the highest yields of pulp, seeds and kernels, in contrast to the ones in the Guinean zone, which were tall and produced only a small number of fruits with a low pulp, seed and kernel productivity. A statistically significant correlation with the observed patterns of genetic diversity was observed for three morphological characteristics: height of the trees, number of branches and thickness of the capsules. The results indicate some degree of physical isolation of the populations collected in the different climatic zones and suggest a substantial amount of genetic structuring between the analysed populations of baobab. Sampling options of the natural populations are suggested for in or ex situ conservation.

Improving resolution of dynamic communities in human brain networks through targeted node removal

PubMed Central

Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2017-01-01

Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662

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

Majda, Andrew J.; Xing, Yulong; Mohammadian, Majid

Determining the finite-amplitude preconditioned states in the hurricane embryo, which lead to tropical cyclogenesis, is a central issue in contemporary meteorology. In the embryo there is competition between different preconditioning mechanisms involving hydrodynamics and moist thermodynamics, which can lead to cyclogenesis. Here systematic asymptotic methods from applied mathematics are utilized to develop new simplified moist multi-scale models starting from the moist anelastic equations. Three interesting multi-scale models emerge in the analysis. The balanced mesoscale vortex (BMV) dynamics and the microscale balanced hot tower (BHT) dynamics involve simplified balanced equations without gravity waves for vertical vorticity amplification due to moist heatmore » sources and incorporate nonlinear advective fluxes across scales. The BMV model is the central one for tropical cyclogenesis in the embryo. The moist mesoscale wave (MMW) dynamics involves simplified equations for mesoscale moisture fluctuations, as well as linear hydrostatic waves driven by heat sources from moisture and eddy flux divergences. A simplified cloud physics model for deep convection is introduced here and used to study moist axisymmetric plumes in the BHT model. A simple application in periodic geometry involving the effects of mesoscale vertical shear and moist microscale hot towers on vortex amplification is developed here to illustrate features of the coupled multi-scale models. These results illustrate the use of these models in isolating key mechanisms in the embryo in a simplified content.« less

Final report for LDRD project 11-0029 : high-interest event detection in large-scale multi-modal data sets : proof of concept.

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

Rohrer, Brandon Robinson

2011-09-01

Events of interest to data analysts are sometimes difficult to characterize in detail. Rather, they consist of anomalies, events that are unpredicted, unusual, or otherwise incongruent. The purpose of this LDRD was to test the hypothesis that a biologically-inspired anomaly detection algorithm could be used to detect contextual, multi-modal anomalies. There currently is no other solution to this problem, but the existence of a solution would have a great national security impact. The technical focus of this research was the application of a brain-emulating cognition and control architecture (BECCA) to the problem of anomaly detection. One aspect of BECCA inmore » particular was discovered to be critical to improved anomaly detection capabilities: it's feature creator. During the course of this project the feature creator was developed and tested against multiple data types. Development direction was drawn from psychological and neurophysiological measurements. Major technical achievements include the creation of hierarchical feature sets created from both audio and imagery data.« less

A desktop system of virtual morphometric globes for Mars and the Moon

NASA Astrophysics Data System (ADS)

Florinsky, I. V.; Filippov, S. V.

2017-03-01

Global morphometric models can be useful for earth and planetary studies. Virtual globes - programs implementing interactive three-dimensional (3D) models of planets - are increasingly used in geo- and planetary sciences. We describe the development of a desktop system of virtual morphometric globes for Mars and the Moon. As the initial data, we used 15'-gridded global digital elevation models (DEMs) extracted from the Mars Orbiter Laser Altimeter (MOLA) and the Lunar Orbiter Laser Altimeter (LOLA) gridded archives. For two celestial bodies, we derived global digital models of several morphometric attributes, such as horizontal curvature, vertical curvature, minimal curvature, maximal curvature, and catchment area. To develop the system, we used Blender, the free open-source software for 3D modeling and visualization. First, a 3D sphere model was generated. Second, the global morphometric maps were imposed to the sphere surface as textures. Finally, the real-time 3D graphics Blender engine was used to implement rotation and zooming of the globes. The testing of the developed system demonstrated its good performance. Morphometric globes clearly represent peculiarities of planetary topography, according to the physical and mathematical sense of a particular morphometric variable.

Matching of renewable source of energy generation graphs and electrical load in local energy system

NASA Astrophysics Data System (ADS)

Lezhniuk, Petro; Komar, Vyacheslav; Sobchuk, Dmytro; Kravchuk, Sergiy; Kacejko, Piotr; Zavidsky, Vladislav

2017-08-01

The paper contains the method of matching generation graph of photovoltaic electric stations and consumers. Characteristic feature of this method is the application of morphometric analysis for assessment of non-uniformity of the integrated graph of energy supply, optimal coefficients of current distribution, that enables by mean of refining the powers, transferring in accordance with the graph , to provide the decrease of electric energy losses in the grid and transport task, as the optimization tool.

A new method using multiphoton imaging and morphometric analysis for differentiating chromophobe renal cell carcinoma and oncocytoma kidney tumors

NASA Astrophysics Data System (ADS)

Wu, Binlin; Mukherjee, Sushmita; Jain, Manu

2016-03-01

Distinguishing chromophobe renal cell carcinoma (chRCC) from oncocytoma on hematoxylin and eosin images may be difficult and require time-consuming ancillary procedures. Multiphoton microscopy (MPM), an optical imaging modality, was used to rapidly generate sub-cellular histological resolution images from formalin-fixed unstained tissue sections from chRCC and oncocytoma.Tissues were excited using 780nm wavelength and emission signals (including second harmonic generation and autofluorescence) were collected in different channels between 390 nm and 650 nm. Granular structure in the cell cytoplasm was observed in both chRCC and oncocytoma. Quantitative morphometric analysis was conducted to distinguish chRCC and oncocytoma. To perform the analysis, cytoplasm and granules in tumor cells were segmented from the images. Their area and fluorescence intensity were found in different channels. Multiple features were measured to quantify the morphological and fluorescence properties. Linear support vector machine (SVM) was used for classification. Re-substitution validation, cross validation and receiver operating characteristic (ROC) curve were implemented to evaluate the efficacy of the SVM classifier. A wrapper feature algorithm was used to select the optimal features which provided the best predictive performance in separating the two tissue types (classes). Statistical measures such as sensitivity, specificity, accuracy and area under curve (AUC) of ROC were calculated to evaluate the efficacy of the classification. Over 80% accuracy was achieved as the predictive performance. This method, if validated on a larger and more diverse sample set, may serve as an automated rapid diagnostic tool to differentiate between chRCC and oncocytoma. An advantage of such automated methods are that they are free from investigator bias and variability.

The Value of Molecular vs. Morphometric and Acoustic Information for Species Identification Using Sympatric Molossid Bats

PubMed Central

Gager, Yann; Tarland, Emilia; Lieckfeldt, Dietmar; Ménage, Matthieu; Botero-Castro, Fidel; Rossiter, Stephen J.; Kraus, Robert H. S.; Ludwig, Arne; Dechmann, Dina K. N.

2016-01-01

A fundamental condition for any work with free-ranging animals is correct species identification. However, in case of bats, information on local species assemblies is frequently limited especially in regions with high biodiversity such as the Neotropics. The bat genus Molossus is a typical example of this, with morphologically similar species often occurring in sympatry. We used a multi-method approach based on molecular, morphometric and acoustic information collected from 962 individuals of Molossus bondae, M. coibensis, and M. molossus captured in Panama. We distinguished M. bondae based on size and pelage coloration. We identified two robust species clusters composed of M. molossus and M. coibensis based on 18 microsatellite markers but also on a more stringently determined set of four markers. Phylogenetic reconstructions using the mitochondrial gene co1 (DNA barcode) were used to diagnose these microsatellite clusters as M. molossus and M. coibensis. To differentiate species, morphological information was only reliable when forearm length and body mass were combined in a linear discriminant function (95.9% correctly identified individuals). When looking in more detail at M. molossus and M. coibensis, only four out of 13 wing parameters were informative for species differentiation, with M. coibensis showing lower values for hand wing area and hand wing length and higher values for wing loading. Acoustic recordings after release required categorization of calls into types, yielding only two informative subsets: approach calls and two-toned search calls. Our data emphasizes the importance of combining morphological traits and independent genetic data to inform the best choice and combination of discriminatory information used in the field. Because parameters can vary geographically, the multi-method approach may need to be adjusted to local species assemblies and populations to be entirely informative. PMID:26943355

Pollen Image Recognition Based on DGDB-LBP Descriptor

NASA Astrophysics Data System (ADS)

Han, L. P.; Xie, Y. H.

2018-01-01

In this paper, we propose DGDB-LBP, a local binary pattern descriptor based on the pixel blocks in the dominant gradient direction. Differing from traditional LBP and its variants, DGDB-LBP encodes by comparing the main gradient magnitude of each block rather than the single pixel value or the average of pixel blocks, in doing so, it reduces the influence of noise on pollen images and eliminates redundant and non-informative features. In order to fully describe the texture features of pollen images and analyze it under multi-scales, we propose a new sampling strategy, which uses three types of operators to extract the radial, angular and multiple texture features under different scales. Considering that the pollen images have some degree of rotation under the microscope, we propose the adaptive encoding direction, which is determined by the texture distribution of local region. Experimental results on the Pollenmonitor dataset show that the average correct recognition rate of our method is superior to other pollen recognition methods in recent years.

Technologically Reflective Individuals as Enablers of Social Innovation.

PubMed

Schweitzer, Fiona; Rau, Christiane; Gassmann, Oliver; van den Hende, Ellis

2015-11-01

This paper identifies technologically reflective individuals and demonstrates their ability to develop innovations that benefit society. Technological reflectiveness (TR) is the tendency to think about the societal impact of an innovation, and those who display this capability in public are individuals who participate in online idea competitions focused on technical solutions for social problems (such as General Electric's eco-challenge, the James Dyson Award, and the BOSCH Technology Horizon Award). However, technologically reflective individuals also reflect in private settings (e.g., when reading news updates), thus requiring a scale to identify them. This paper describes the systematic development of an easy-to-administer multi-item scale to measure an individual's level of TR. Applying the TR scale in an empirical study on a health monitoring system confirmed that individuals' degree of TR relates positively to their ability to generate (1) more new product features and uses, (2) features with higher levels of societal impact, and (3) features that are more elaborated. This scale allows firms seeking to implement co-creation in their new product development (NPD) process and sustainable solutions to identify such individuals. Thus, this paper indicates that companies wishing to introduce new technological products with a positive societal impact may profit from involving technologically reflective individuals in the NPD process.

Methodological Issues in the Study of Teachers' Careers: Critical Features of a Truly Longitudinal Study. Working Paper Series.

ERIC Educational Resources Information Center

Singer, Judith D.; Willett, John B.

The National Center for Education Statistics (NCES) is exploring the possibility of conducting a large-scale multi-year study of teachers' careers. The proposed new study is intended to follow a national probability sample of teachers over an extended period of time. A number of methodological issues need to be addressed before the study can be…

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology.

PubMed

Fondi, Marco; Liò, Pietro

2015-02-01

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists. Copyright © 2015. Published by Elsevier GmbH.

Multilayer Brain Networks

NASA Astrophysics Data System (ADS)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

PubMed

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

Researching into the cellular shape, volume and elasticity of mesenchymal stem cells, osteoblasts and osteosarcoma cells by atomic force microscopy

PubMed Central

Docheva, Denitsa; Padula, Daniela; Popov, Cvetan; Mutschler, Wolf; Clausen-Schaumann, Hauke; Schieker, Matthias

2008-01-01

Abstract Within the bone lie several different cell types, including osteoblasts (OBs) and mesenchymal stem cells (MSCs). The MSCs are ideal targets for regenerative medicine of bone due to their differentiation potential towards OBs. Human MSCs exhibit two distinct morphologies: rapidly self-renewing cells (RS) and flat cells (FC) with very low proliferation rates. Another cell type found in pathological bone conditions is osteosarcoma. In this study, we compared the topographic and morphometric features of RS and FC cells, human OBs and MG63 osteosarcoma cells by atomic force microscopy (AFM). The results demonstrated clear differences: FC and hOB cells showed similar ruffled topography, whereas RS and MG63 cells exhibited smoother surfaces. Furthermore, we investigated how selected substrates influence cell morphometry. We found that RS and MG63 cells were flatter on fibrous substrates such as polystyrene and collagen I, but much more rounded on glass, the smoothest surface. In contrast, cells with large area, namely FC and hOB cells, did not exhibit pronounced changes in flatness with regards to the different substrates. They were, however, remarkably flatter in comparison to RS and MG63 cells. We could explain the differences in flatness by the extent of adhesion. Indeed, FC and hOB cells showed much higher content of focal adhesions. Finally, we used the AFM to determine the cellular Young's modulus. RS, FC and hOB cells showed comparable stiffness on the three different substrates, while MG63 cells demonstrated the unique feature of increased elasticity on collagen I. In summary, our results show, for the first time, a direct comparison between the morphometric and biophysical features of different human cell types derived from normal and pathological bone. Our study manifests the opinion that along with RNA, proteomic and functional research, morphological and biomechanical characterization of cells also reveals novel cell features and interrelationships. PMID:18419596

Metrics for comparing neuronal tree shapes based on persistent homology.

PubMed

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A; Mitra, Partha; Wang, Yusu

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework.

Metrics for comparing neuronal tree shapes based on persistent homology

PubMed Central

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A.; Mitra, Partha

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities—Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework. PMID:28809960

Climate-physiographically differentiated Pan-European landslide susceptibility assessment using spatial multi-criteria evaluation and transnational landslide information

NASA Astrophysics Data System (ADS)

Günther, Andreas; Van Den Eeckhaut, Miet; Malet, Jean-Philippe; Reichenbach, Paola; Hervás, Javier

2014-11-01

With the adoption of the EU Thematic Strategy for Soil Protection in 2006, small-scale (1:1 M) assessments of threats affecting soils over Europe received increasing attention. As landslides have been recognized as one of eight threats requiring a Pan-European evaluation, we present an approach for landslide susceptibility evaluation at the continental scale over Europe. Unlike previous continental and global scale landslide susceptibility studies not utilizing spatial information on the events, we collected more than 102,000 landslide locations in 22 European countries. These landslides are heterogeneously distributed over Europe, but are indispensable for the evaluation and classification of Pan-European datasets used as spatial predictors, and the validation of the resulting assessments. For the analysis we subdivided the European territory into seven different climate-physiographical zones by combining morphometric and climatic data for terrain differentiation, and adding a coastal zone defined as a 1 km strip inland from the coastline. Landslide susceptibility modeling was performed for each zone using heuristic spatial multicriteria evaluations supported by analytical hierarchy processes, and validated with the inventory data using the receiver operating characteristics. In contrast to purely data-driven statistical modeling techniques, our semi-quantitative approach is capable to introduce expert knowledge into the analysis, which is indispensable considering quality and resolution of the input data, and incompleteness and bias in the inventory information. The reliability of the resulting susceptibility map ELSUS 1000 Version 1 (1 km resolution) was examined on an administrative terrain unit level in areas with landslide information and through the comparison with available national susceptibility zonations. These evaluations suggest that although the ELSUS 1000 is capable for a correct synoptic prediction of landslide susceptibility in the majority of the area, it needs further improvement in terms of data used.

Bat Species Comparisons Based on External Morphology: A Test of Traditional versus Geometric Morphometric Approaches

PubMed Central

Schmieder, Daniela A.; Benítez, Hugo A.; Borissov, Ivailo M.; Fruciano, Carmelo

2015-01-01

External morphology is commonly used to identify bats as well as to investigate flight and foraging behavior, typically relying on simple length and area measures or ratios. However, geometric morphometrics is increasingly used in the biological sciences to analyse variation in shape and discriminate among species and populations. Here we compare the ability of traditional versus geometric morphometric methods in discriminating between closely related bat species – in this case European horseshoe bats (Rhinolophidae, Chiroptera) – based on morphology of the wing, body and tail. In addition to comparing morphometric methods, we used geometric morphometrics to detect interspecies differences as shape changes. Geometric morphometrics yielded improved species discrimination relative to traditional methods. The predicted shape for the variation along the between group principal components revealed that the largest differences between species lay in the extent to which the wing reaches in the direction of the head. This strong trend in interspecific shape variation is associated with size, which we interpret as an evolutionary allometry pattern. PMID:25965335

Characterizing the SEMG patterns with myofascial pain using a multi-scale wavelet model through machine learning approaches.

PubMed

Lin, Yu-Ching; Yu, Nan-Ying; Jiang, Ching-Fen; Chang, Shao-Hsia

2018-06-02

In this paper, we introduce a newly developed multi-scale wavelet model for the interpretation of surface electromyography (SEMG) signals and validate the model's capability to characterize changes in neuromuscular activation in cases with myofascial pain syndrome (MPS) via machine learning methods. The SEMG data collected from normal (N = 30; 27 women, 3 men) and MPS subjects (N = 26; 22 women, 4 men) were adopted for this retrospective analysis. SMEGs were measured from the taut-band loci on both sides of the trapezius muscle on the upper back while he/she conducted a cyclic bilateral backward shoulder extension movement within 1 min. Classification accuracy of the SEMG model to differentiate MPS patients from normal subjects was 77% using template matching and 60% using K-means clustering. Classification consistency between the two machine learning methods was 87% in the normal group and 93% in the MPS group. The 2D feature graphs derived from the proposed multi-scale model revealed distinct patterns between normal subjects and MPS patients. The classification consistency using template matching and K-means clustering suggests the potential of using the proposed model to characterize interference pattern changes induced by MPS. Copyright © 2018. Published by Elsevier Ltd.

Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering.

PubMed

Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

2014-04-01

Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively.

Basilar membrane and reticular lamina motion in a multi-scale finite element model of the mouse cochlea

NASA Astrophysics Data System (ADS)

Soons, Joris; Dirckx, Joris; Steele, Charles; Puria, Sunil

2015-12-01

A multi-scale finite element (FE) model of the mouse cochlea, based on its anatomy and material properties is presented. The important feature in the model is a lattice of 400 Y-shaped structures in the longitudinal direction, each formed by Deiters cells, phalangeal processes and outer hair cells (OHC). OHC somatic motility is modeled by an expansion force proportional to the shear on the stereocilia, which in turn is proportional to the pressure difference between the scala vestibule and scala tympani. Basilar membrane (BM) and reticular lamina (RL) velocity compare qualitatively very well with recent in vivo measurements in guinea pig [2]. Compared to the BM, the RL is shown to have higher amplification and a shift to higher frequencies. This comes naturally from the realistic Y-shaped cell organization without tectorial membrane tuning.

Effects of freezing on white perch Morone americana (Gmelin, 1789): Implications for multivariate morphometrics

USGS Publications Warehouse

Kocovsky, Patrick

2016-01-01

This study tested the hypothesis that duration of freezing differentially affects whole-body morphometrics of a derived teleost. Whole-body morphometrics are frequently analyzed to test hypotheses of different species, or stocks within a species, of fishes. Specimens used for morphometric analyses are typically fixed or preserved prior to analysis, yet little research has been done on how fixation or preservation methods or duration of preservation of specimens might affect outcomes of multivariate statistical analyses of differences in shape. To determine whether whole-body morphometrics changed as a result of freezing, 23 whole-body morphometrics of age-1 white perch (Morone americana) from western Lake Erie (n = 211) were analyzed immediately after capture, after being held on ice overnight, and after freezing for 100 or 200 days. Discriminant function analysis revealed that all four groups differed significantly from one another (P < 0.0001). The first canonical axis reflected long-axis morphometrics, where there was a clear pattern of positive translation along this axis with duration of preservation. Re-classification analysis demonstrated fish were typically assigned to their original preservation class except for fish frozen 100 days, which assigned mostly to frozen 200 days. Morphometric comparisons using frozen fish must be done on fish frozen for identical periods of time to avoid biases related to the length of time they were frozen. Similar experiments should be conducted on other species and also using formalin- and alcohol-preserved specimens.

A New DEM Generalization Method Based on Watershed and Tree Structure

PubMed Central

Chen, Yonggang; Ma, Tianwu; Chen, Xiaoyin; Chen, Zhende; Yang, Chunju; Lin, Chenzhi; Shan, Ligang

2016-01-01

The DEM generalization is the basis of multi-dimensional observation, the basis of expressing and analyzing the terrain. DEM is also the core of building the Multi-Scale Geographic Database. Thus, many researchers have studied both the theory and the method of DEM generalization. This paper proposed a new method of generalizing terrain, which extracts feature points based on the tree model construction which considering the nested relationship of watershed characteristics. The paper used the 5 m resolution DEM of the Jiuyuan gully watersheds in the Loess Plateau as the original data and extracted the feature points in every single watershed to reconstruct the DEM. The paper has achieved generalization from 1:10000 DEM to 1:50000 DEM by computing the best threshold. The best threshold is 0.06. In the last part of the paper, the height accuracy of the generalized DEM is analyzed by comparing it with some other classic methods, such as aggregation, resample, and VIP based on the original 1:50000 DEM. The outcome shows that the method performed well. The method can choose the best threshold according to the target generalization scale to decide the density of the feature points in the watershed. Meanwhile, this method can reserve the skeleton of the terrain, which can meet the needs of different levels of generalization. Additionally, through overlapped contour contrast, elevation statistical parameters and slope and aspect analysis, we found out that the W8D algorithm performed well and effectively in terrain representation. PMID:27517296

Automatic classification for mammogram backgrounds based on bi-rads complexity definition and on a multi content analysis framework

NASA Astrophysics Data System (ADS)

Wu, Jie; Besnehard, Quentin; Marchessoux, Cédric

2011-03-01

Clinical studies for the validation of new medical imaging devices require hundreds of images. An important step in creating and tuning the study protocol is the classification of images into "difficult" and "easy" cases. This consists of classifying the image based on features like the complexity of the background, the visibility of the disease (lesions). Therefore, an automatic medical background classification tool for mammograms would help for such clinical studies. This classification tool is based on a multi-content analysis framework (MCA) which was firstly developed to recognize image content of computer screen shots. With the implementation of new texture features and a defined breast density scale, the MCA framework is able to automatically classify digital mammograms with a satisfying accuracy. BI-RADS (Breast Imaging Reporting Data System) density scale is used for grouping the mammograms, which standardizes the mammography reporting terminology and assessment and recommendation categories. Selected features are input into a decision tree classification scheme in MCA framework, which is the so called "weak classifier" (any classifier with a global error rate below 50%). With the AdaBoost iteration algorithm, these "weak classifiers" are combined into a "strong classifier" (a classifier with a low global error rate) for classifying one category. The results of classification for one "strong classifier" show the good accuracy with the high true positive rates. For the four categories the results are: TP=90.38%, TN=67.88%, FP=32.12% and FN =9.62%.

Multi-task feature selection in microarray data by binary integer programming.

PubMed

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Aphanius arakensis, a new species of tooth-carp (Actinopterygii, Cyprinodontidae) from the endorheic Namak Lake basin in Iran

PubMed Central

Teimori, Azad; Esmaeili, Hamid Reza; Gholami, Zeinab; Zarei, Neda; Reichenbacher, Bettina

2012-01-01

Abstract A new species of tooth-carp, Aphanius arakensis sp. n., is described from the Namak Lake basin in Iran. The new species is distinguished by the congeners distributed in Iran by the following combination of characters: 10–12 anal fin rays, 28–32 lateral line scales, 10–13 caudal peduncle scales, 8–10 gill rakers, 12–19, commonly 15–16, clearly defined flank bars in males, a more prominent pigmentation along the flank added by relatively big blotches in the middle and posterior flank segments in females, a short but high antirostrum of the otolith that has a wide excisura, and a ventral rim with some small, drop-like processes, and 19 molecular apomorphies (17 transitions, two transversions) in the cytochrome b gene. It was suggested based on the phylogenetic analysis that the new species is sister to Aphanius sophiae from the Kor River and that Aphanius farsicus from the Maharlu Lake basin is sister to Aphanius arakensis plus Aphanius sophiae. A noticeable feature of the Aphanius diversity in Iran is the conservatism of the external morphology as well as morphometric and meristic characters, while distinctive differences are present in genetic characters, otolith morphology, and male color pattern. Transformation of the latter was probably driven by sexual selection. PMID:22936871

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

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

A cortical framework for invariant object categorization and recognition.

PubMed

Rodrigues, João; Hans du Buf, J M

2009-08-01

In this paper we present a new model for invariant object categorization and recognition. It is based on explicit multi-scale features: lines, edges and keypoints are extracted from responses of simple, complex and end-stopped cells in cortical area V1, and keypoints are used to construct saliency maps for Focus-of-Attention. The model is a functional but dichotomous one, because keypoints are employed to model the "where" data stream, with dynamic routing of features from V1 to higher areas to obtain translation, rotation and size invariance, whereas lines and edges are employed in the "what" stream for object categorization and recognition. Furthermore, both the "where" and "what" pathways are dynamic in that information at coarse scales is employed first, after which information at progressively finer scales is added in order to refine the processes, i.e., both the dynamic feature routing and the categorization level. The construction of group and object templates, which are thought to be available in the prefrontal cortex with "what" and "where" components in PF46d and PF46v, is also illustrated. The model was tested in the framework of an integrated and biologically plausible architecture.

Multiplex congruence network of natural numbers.

PubMed

Yan, Xiao-Yong; Wang, Wen-Xu; Chen, Guan-Rong; Shi, Ding-Hua

2016-03-31

Congruence theory has many applications in physical, social, biological and technological systems. Congruence arithmetic has been a fundamental tool for data security and computer algebra. However, much less attention was devoted to the topological features of congruence relations among natural numbers. Here, we explore the congruence relations in the setting of a multiplex network and unveil some unique and outstanding properties of the multiplex congruence network. Analytical results show that every layer therein is a sparse and heterogeneous subnetwork with a scale-free topology. Counterintuitively, every layer has an extremely strong controllability in spite of its scale-free structure that is usually difficult to control. Another amazing feature is that the controllability is robust against targeted attacks to critical nodes but vulnerable to random failures, which also differs from ordinary scale-free networks. The multi-chain structure with a small number of chain roots arising from each layer accounts for the strong controllability and the abnormal feature. The multiplex congruence network offers a graphical solution to the simultaneous congruences problem, which may have implication in cryptography based on simultaneous congruences. Our work also gains insight into the design of networks integrating advantages of both heterogeneous and homogeneous networks without inheriting their limitations.

Multiplex congruence network of natural numbers

NASA Astrophysics Data System (ADS)

Yan, Xiao-Yong; Wang, Wen-Xu; Chen, Guan-Rong; Shi, Ding-Hua

2016-03-01

Congruence theory has many applications in physical, social, biological and technological systems. Congruence arithmetic has been a fundamental tool for data security and computer algebra. However, much less attention was devoted to the topological features of congruence relations among natural numbers. Here, we explore the congruence relations in the setting of a multiplex network and unveil some unique and outstanding properties of the multiplex congruence network. Analytical results show that every layer therein is a sparse and heterogeneous subnetwork with a scale-free topology. Counterintuitively, every layer has an extremely strong controllability in spite of its scale-free structure that is usually difficult to control. Another amazing feature is that the controllability is robust against targeted attacks to critical nodes but vulnerable to random failures, which also differs from ordinary scale-free networks. The multi-chain structure with a small number of chain roots arising from each layer accounts for the strong controllability and the abnormal feature. The multiplex congruence network offers a graphical solution to the simultaneous congruences problem, which may have implication in cryptography based on simultaneous congruences. Our work also gains insight into the design of networks integrating advantages of both heterogeneous and homogeneous networks without inheriting their limitations.

Effects of landscape features on waterbird use of rice fields

USGS Publications Warehouse

King, S.; Elphick, C.S.; Guadagnin, D.; Taft, O.; Amano, T.

2010-01-01

Literature is reviewed to determine the effects of landscape features on waterbird use of fields in regions where rice (Oryza sativa) is grown. Rice-growing landscapes often consist of diverse land uses and land cover, including rice fields, irrigation ditches, other agricultural fields, grasslands, forests and natural wetlands. Numerous studies indicate that local management practices, such as water depth and timing of flooding and drawdown, can strongly influence waterbird use of a given rice field. However, the effects of size and distribution of rice fields and associated habitats at a landscape scale have received less attention. Even fewer studies have focused on local and landscape effects simultaneously. Habitat connectivity, area of rice, distance to natural wetlands, and presence and distance to unsuitable habitat can be important parameters influencing bird use of rice fields. However, responses to a given landscape vary with landscape structure, scale of analysis, among taxa and within taxa among seasons. A lack of multi-scale studies, particularly those extending beyond simple presence and abundance of a given species, and a lack of direct tests comparing the relative importance of landscape features with in-field management activities limits understanding of the importance of landscape in these systems and hampers waterbird conservation and management.

Robust multi-atlas label propagation by deep sparse representation

PubMed Central

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2016-01-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer (label-specific dictionaries) consists of groups of representative atlas patches and the subsequent layers (residual dictionaries) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods. PMID:27942077

Robust multi-atlas label propagation by deep sparse representation.

PubMed

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2017-03-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer ( label-specific dictionaries ) consists of groups of representative atlas patches and the subsequent layers ( residual dictionaries ) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods.

Virtual reconstruction and geometric morphometrics as tools for paleopathology: a new approach to study rare developmental disorders of the skeleton.

PubMed

Milella, Marco; Zollikofer, Christoph P E; Ponce de León, Marcia S

2015-02-01

Survey studies of osteoarchaeological collections occasionally yield specimens exhibiting rare skeletal developmental disorders. Beyond paleopathological diagnosis, however, it is often difficult to gain insight into the processes, mechanisms, and consequences of the pathology, notably because archaeological specimens are often fragmentary. Here, we propose a combination of virtual reconstruction (VR) and geometric morphometrics (GM) to address these issues. As an example, we use VR to reconstruct the only known archaeological specimen exhibiting persistence of the pelvic triradiate cartilage and compare it via GM with a set of healthy pelvises representing both sexes and different ontogenetic stages. Our results evidence (i) a marked deviation of the pathological pelvis from the adult mean shape, (ii) the retention of typical male features, and (iii) the retention of a paedomorphic ratio between iliac and ischiopubic size. Altogether, such data offer new insights into the modularity and integration of pelvic ontogeny, while at the same time demonstrating the usefulness of a combined VR/GM approach as complement to classical methods of paleopathology. © 2014 Wiley Periodicals, Inc.

Hierarchical Multi-atlas Label Fusion with Multi-scale Feature Representation and Label-specific Patch Partition

PubMed Central

Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C.; Shen, Dinggang

2014-01-01

Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications. In general, to achieve label fusion a single target image is first registered to several atlas images, after registration a label is assigned to each target point in the target image by determining the similarity between the underlying target image patch (centered at the target point) and the aligned image patch in each atlas image. To achieve the highest level of accuracy during the label fusion process it’s critical the chosen patch similarity measurement accurately captures the tissue/shape appearance of the anatomical structure. One major limitation of existing state-of-the-art label fusion methods is that they often apply a fixed size image patch throughout the entire label fusion procedure. Doing so may severely affect the fidelity of the patch similarity measurement, which in turn may not adequately capture complex tissue appearance patterns expressed by the anatomical structure. To address this limitation, we advance state-of-the-art by adding three new label fusion contributions: First, each image patch now characterized by a multi-scale feature representation that encodes both local and semi-local image information. Doing so will increase the accuracy of the patch-based similarity measurement. Second, to limit the possibility of the patch-based similarity measurement being wrongly guided by the presence of multiple anatomical structures in the same image patch, each atlas image patch is further partitioned into a set of label-specific partial image patches according to the existing labels. Since image information has now been semantically divided into different patterns, these new label-specific atlas patches make the label fusion process more specific and flexible. Lastly, in order to correct target points that are mislabeled during label fusion, a hierarchically approach is used to improve the label fusion results. In particular, a coarse-to-fine iterative label fusion approach is used that gradually reduces the patch size. To evaluate the accuracy of our label fusion approach, the proposed method was used to segment the hippocampus in the ADNI dataset and 7.0 tesla MR images, sub-cortical regions in LONI LBPA40 dataset, mid-brain regions in SATA dataset from MICCAI 2013 segmentation challenge, and a set of key internal gray matter structures in IXI dataset. In all experiments, the segmentation results of the proposed hierarchical label fusion method with multi-scale feature representations and label-specific atlas patches are more accurate than several well-known state-of-the-art label fusion methods. PMID:25463474

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis

PubMed Central

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3–10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception. PMID:28052103

Systematic Review of Ossicular Chain Anatomy: Strategic Planning for Development of Novel Middle Ear Prostheses.

PubMed

Kamrava, Brandon; Roehm, Pamela C

2017-08-01

Objective To systematically review the anatomy of the ossicular chain. Data Sources Google Scholar, PubMed, and otologic textbooks. Review Methods A systematic literature search was performed on January 26, 2015. Search terms used to discover articles consisted of combinations of 2 keywords. One keyword from both groups was used: [ ossicular, ossicle, malleus, incus, stapes] and [ morphology, morphometric, anatomy, variation, physiology], yielding more than 50,000 hits. Articles were then screened by title and abstract if they did not contain information relevant to human ossicular chain anatomy. In addition to this search, references of selected articles were studied as well as suggested relevant articles from publication databases. Standard otologic textbooks were screened using the search criteria. Results Thirty-three sources were selected for use in this review. From these studies, data on the composition, physiology, morphology, and morphometrics were acquired. In addition, any correlations or lack of correlations between features of the ossicular chain and other features of the ossicular chain or patient were noted, with bilateral symmetry between ossicles being the only important correlation reported. Conclusion There was significant variation in all dimensions of each ossicle between individuals, given that degree of variation, custom fitting, or custom manufacturing of prostheses for each patient could optimize prosthesis fit. From published data, an accurate 3-dimensional model of the malleus, incus, and stapes can be created, which can then be further modified for each patient's individual anatomy.

The alterations of the sigmoid-rectal junction in diverticular disease of the colon revealed by MR-defecography.

PubMed

Romagnoli, Francesco; Colaiacomo, Maria Chiara; De Milito, Ritanna; Modini, Claudio; Gualdi, Gianfranco; Catani, Marco

2014-01-01

The sigmoidorectal junction (SRJ) has been defined as an anatomical sphincter with particular physiological behavior that regulates sigmoid and rectum evacuation. Its function in clinical conditions, such as diverticular disease has been advocated. The aim of our study is to identify the SRJ and to compare the morphometric and dynamic features of the SRJ between patients with diverticular disease and healthy subjects using MR-defecography. Sixteen individuals, eight with uncomplicated diverticular disease and eight healthy subjects, were studied using MR-defecography to identify the SRJ and to compare the morphometric and dynamic features observed. In each subject studied, MR-defecography was able to identify the SRJ. This resulted in the identification of a discrete anatomical entity with a mean length of 31.23 mm, located in front of the first sacral vertebra (S1) and at a mean distance of 15.55 cm from the anal verge, with a mean wall thickness of 4.45 mm, significantly different from the sigmoid and rectal parietal thickness. The SRJ wall was significantly thicker in patients with diverticular disease than the controls (P = 0.005), showing a unique shape and behavior in dynamic sequences. Our findings support the hypothesis that SRJ plays a critical role in patients with symptomatic diverticular disease; further investigation may clarify whether specific SRJ analysis, such as MR-defecography, would predict inflammatory complications of this diffuse and heterogenic disease.

Numerical analysis of dysplasia-associated changes in depth-dependent light scattering profile of cervical epithelium

NASA Astrophysics Data System (ADS)

Arifler, Dizem; MacAulay, Calum; Follen, Michele; Guillaud, Martial

2013-06-01

Dysplastic progression is known to be associated with changes in morphology and internal structure of cells. A detailed assessment of the influence of these changes on cellular scattering response is needed to develop and optimize optical diagnostic techniques. In this study, we first analyzed a set of quantitative histopathologic images from cervical biopsies and we obtained detailed information on morphometric and photometric features of segmented epithelial cell nuclei. Morphometric parameters included average size and eccentricity of the best-fit ellipse. Photometric parameters included optical density measures that can be related to dielectric properties and texture characteristics of the nuclei. These features enabled us to construct realistic three-dimensional computational models of basal, parabasal, intermediate, and superficial cell nuclei that were representative of four diagnostic categories, namely normal (or negative for dysplasia), mild dysplasia, moderate dysplasia, and severe dysplasia or carcinoma in situ. We then employed the finite-difference time-domain method, a popular numerical tool in electromagnetics, to compute the angle-resolved light scattering properties of these representative models. Results indicated that a high degree of variability can characterize a given diagnostic category, but scattering from moderately and severely dysplastic or cancerous nuclei was generally observed to be stronger compared to scattering from normal and mildly dysplastic nuclei. Simulation results also pointed to significant intensity level variations among different epithelial depths. This suggests that intensity changes associated with dysplastic progression need to be analyzed in a depth-dependent manner.

The Use of a Geomorphometric Classification to Estimate Subsurface Heterogeneity in the Unconsolidated Sediments of Mountain Watersheds

NASA Astrophysics Data System (ADS)

Cairns, D.; Byrne, J. M.; Jiskoot, H.; McKenzie, J. M.; Johnson, D. L.

2013-12-01

Groundwater controls many aspects of water quantity and quality in mountain watersheds. Groundwater recharge and flow originating in mountain watersheds are often difficult to quantify due to challenges in the characterization of the local geology, as subsurface data are sparse and difficult to collect. Remote sensing data are more readily available and are beneficial for the characterization of watershed hydrodynamics. We present an automated geomorphometric model to identify the approximate spatial distribution of geomorphic features, and to segment each of these features based on relative hydrostratigraphic differences. A digital elevation model (DEM) dataset and predefined indices are used as inputs in a mountain watershed. The model uses periglacial, glacial, fluvial, slope evolution and lacustrine processes to identify regions that are subsequently delineated using morphometric principles. A 10 m cell size DEM from the headwaters of the St. Mary River watershed in Glacier National Park, Montana, was considered sufficient for this research. Morphometric parameters extracted from the DEM that were found to be useful for the calibration of the model were elevation, slope, flow direction, flow accumulation, and surface roughness. Algorithms were developed to utilize these parameters and delineate the distributions of bedrock outcrops, periglacial landscapes, alluvial channels, fans and outwash plains, glacial depositional features, talus slopes, and other mass wasted material. Theoretical differences in sedimentation and hydrofacies associated with each of the geomorphic features were used to segment the watershed into units reflecting similar hydrogeologic properties such as hydraulic conductivity and thickness. The results of the model were verified by comparing the distribution of geomorphic features with published geomorphic maps. Although agreement in semantics between datasets caused difficulties, a consensus yielded a comparison Dice Coefficient of 0.65. The results can be used to assist in groundwater model calibration, or to estimate spatial differences in near-surface groundwater behaviour. Verification of the geomorphometric model would be augmented by evaluating its success after use in the calibration of the groundwater simulation. These results may also be used directly in momentum-based equations to create a stochastic routing routine beneath the soil interface for a hydrometeorological model.

A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.

PubMed

Bruse, Jan L; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N; Capelli, Claudio; Hsia, Tain-Yen; Sermesant, Maxime; Pennec, Xavier; Taylor, Andrew M; Schievano, Silvia

2016-05-31

Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.

Closed form unsupervised registration of multi-temporal structure from motion-multiview stereo data using non-linearly weighted image features

NASA Astrophysics Data System (ADS)

Seers, T. D.; Hodgetts, D.

2013-12-01

Seers, T. D. & Hodgetts, D. School of Earth, Atmospheric and Environmental Sciences, University of Manchester, UK. M13 9PL. The detection of topological change at the Earth's surface is of considerable scholarly interest, allowing the quantification of the rates of geomorphic processes whilst providing lucid insights into the underlying mechanisms driving landscape evolution. In this regard, the past decade has witnessed the ever increasing proliferation of studies employing multi-temporal topographic data in within the geosciences, bolstered by continuing technical advancements in the acquisition and processing of prerequisite datasets. Provided by workers within the field of Computer Vision, multiview stereo (MVS) dense surface reconstructions, primed by structure-from-motion (SfM) based camera pose estimation represents one such development. Providing a cost effective, operationally efficient data capture medium, the modest requirement of a consumer grade camera for data collection coupled with the minimal user intervention required during post-processing makes SfM-MVS an attractive alternative to terrestrial laser scanners for collecting multi-temporal topographic datasets. However, in similitude to terrestrial scanner derived data, the co-registration of spatially coincident or partially overlapping scans produced by SfM-MVS presents a major technical challenge, particularly in the case of semi non-rigid scenes produced during topographic change detection studies. Moreover, the arbitrary scaling resulting from SfM ambiguity requires that a scale matrix must be estimated during the transformation, introducing further complexity into its formulation. Here, we present a novel, fully unsupervised algorithm which utilises non-linearly weighted image features for the solving the similarity transform (scale, translation rotation) between partially overlapping scans produced by SfM-MVS image processing. With the only initialization condition being partial intersection between input image sets, our method has major advantages over conventional iterative least squares minimization based methods (e.g. Iterative Closest Point variants), acting only on rigid areas of target scenes, being capable of reliably estimating the scaling factor and requiring no incipient estimation of the transformation to initialize (i.e. manual rough alignment). Moreover, because the solution is closed form, convergence is considerably more expedient that most iterative methods. It is hoped that the availability of improved co-registration routines, such as the one presented here, will facilitate the routine collection of multi-temporal topographic datasets by a wider range of geoscience practitioners.

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

Multi-platform observations on melt pond in Arctic summer 2010

NASA Astrophysics Data System (ADS)

Wang, Y.; Huang, W.; Lu, P.; Li, Z.

2011-12-01

Melt ponds play an important role in sea ice surface albedo and further affect the heat budget between ice-air interface. The overall reductions of Arctic sea ice extend and thickness especially in recent years is considered to be enhanced partly by the melt ponds, and understanding of melt ponds on how they change the heat and mass balance of sea ice through the ice surface albedo decrease is urgently required. Although satellite remote sensing is a general tool to observe sea ice surface features on a large scale, the small scale information with higher spatial and temporal resolution is more helpful to understand the physical mechanism in the evolution of melt ponds. Arctic summer in 2010 is special because of an obvious trans-polar melting, during which the multi-year ice in the central Arctic was seriously melted, and formed a trans-polar zone with ice concentration less than 80% stretching from the Chukchi Sea to the Greenland Sea. It provided a fantastic opportunity to observe melt ponds especially at the high latitude. The Fourth Chinese National Arctic Research Expedition in 2010 (CHINARE-2010) was carried out from July 1 to September 20, 2010. As R/V Xuelong sailing in the ice-infested seas, a multi-platform observation was conducted to investigate the evolution of melt ponds on Arctic sea ice. Among which, aerial photography provided a downward-looking snapshot of the ice surface by using the camera installed on a helicopter, and melt pond information on a 100-meter scale can be obtained. Shipboard photography gave an inclined inspection on the ice conditions beside the ship using the camera installed on the vessel, and melt pond information on a 10-meter scale can be determined. Ground-based photography was similar to the shipboard photography, but the camera with tilt angle was installed on the top of a vertical lifting device fixed on the ice, and melt pond information on a 1-meter scale can be observed. Over 10,000 sea ice images from different platforms were collected during the cruise, and the survey area covered the regions 140°W-180°W, 70°N-88°N. An image processing technique based on difference in colors of the surface features was used to divide each image into three components: snow-covered ice floes, melt ponds and leads. And then geometric features of melt ponds, such as area, perimeter, and roundness, could be extracted from the aerial images. These data can enrich our knowledge on the distribution of melt pond on different spatial scale, especially those in the high latitude regions where summer melting was never so serious in previous years.

Exploring a multi-scale method for molecular simulation in continuum solvent model: Explicit simulation of continuum solvent as an incompressible fluid.

PubMed

Xiao, Li; Luo, Ray

2017-12-07

We explored a multi-scale algorithm for the Poisson-Boltzmann continuum solvent model for more robust simulations of biomolecules. In this method, the continuum solvent/solute interface is explicitly simulated with a numerical fluid dynamics procedure, which is tightly coupled to the solute molecular dynamics simulation. There are multiple benefits to adopt such a strategy as presented below. At this stage of the development, only nonelectrostatic interactions, i.e., van der Waals and hydrophobic interactions, are included in the algorithm to assess the quality of the solvent-solute interface generated by the new method. Nevertheless, numerical challenges exist in accurately interpolating the highly nonlinear van der Waals term when solving the finite-difference fluid dynamics equations. We were able to bypass the challenge rigorously by merging the van der Waals potential and pressure together when solving the fluid dynamics equations and by considering its contribution in the free-boundary condition analytically. The multi-scale simulation method was first validated by reproducing the solute-solvent interface of a single atom with analytical solution. Next, we performed the relaxation simulation of a restrained symmetrical monomer and observed a symmetrical solvent interface at equilibrium with detailed surface features resembling those found on the solvent excluded surface. Four typical small molecular complexes were then tested, both volume and force balancing analyses showing that these simple complexes can reach equilibrium within the simulation time window. Finally, we studied the quality of the multi-scale solute-solvent interfaces for the four tested dimer complexes and found that they agree well with the boundaries as sampled in the explicit water simulations.

Digital pathology imaging as a novel platform for standardization and globalization of quantitative nephropathology

PubMed Central

Gimpel, Charlotte; Kain, Renate; Laurinavicius, Arvydas; Bueno, Gloria; Zeng, Caihong; Liu, Zhihong; Schaefer, Franz; Kretzler, Matthias; Holzman, Lawrence B.; Hewitt, Stephen M.

2017-01-01

Abstract The introduction of digital pathology to nephrology provides a platform for the development of new methodologies and protocols for visual, morphometric and computer-aided assessment of renal biopsies. Application of digital imaging to pathology made substantial progress over the past decade; it is now in use for education, clinical trials and translational research. Digital pathology evolved as a valuable tool to generate comprehensive structural information in digital form, a key prerequisite for achieving precision pathology for computational biology. The application of this new technology on an international scale is driving novel methods for collaborations, providing unique opportunities but also challenges. Standardization of methods needs to be rigorously evaluated and applied at each step, from specimen processing to scanning, uploading into digital repositories, morphologic, morphometric and computer-aided assessment, data collection and analysis. In this review, we discuss the status and opportunities created by the application of digital imaging to precision nephropathology, and present a vision for the near future. PMID:28584625

Geometric morphometrics reveals sex-differential shape allometry in a spider.

PubMed

Fernández-Montraveta, Carmen; Marugán-Lobón, Jesús

2017-01-01

Common scientific wisdom assumes that spider sexual dimorphism (SD) mostly results from sexual selection operating on males. However, testing predictions from this hypothesis, particularly male size hyperallometry, has been restricted by methodological constraints. Here, using geometric morphometrics (GMM) we studied for the first time sex-differential shape allometry in a spider ( Donacosa merlini , Araneae: Lycosidae) known to exhibit the reverse pattern (i.e., male-biased) of spider sexual size dimorphism. GMM reveals previously undetected sex-differential shape allometry and sex-related shape differences that are size independent (i.e., associated to the y-intercept, and not to size scaling). Sexual shape dimorphism affects both the relative carapace-to-opisthosoma size and the carapace geometry, arguably resulting from sex differences in both reproductive roles (female egg load and male competition) and life styles (wandering males and burrowing females). Our results demonstrate that body portions may vary modularly in response to different selection pressures, giving rise to sex differences in shape, which reconciles previously considered mutually exclusive interpretations about the origins of spider SD.

Digital pathology imaging as a novel platform for standardization and globalization of quantitative nephropathology.

PubMed

Barisoni, Laura; Gimpel, Charlotte; Kain, Renate; Laurinavicius, Arvydas; Bueno, Gloria; Zeng, Caihong; Liu, Zhihong; Schaefer, Franz; Kretzler, Matthias; Holzman, Lawrence B; Hewitt, Stephen M

2017-04-01

The introduction of digital pathology to nephrology provides a platform for the development of new methodologies and protocols for visual, morphometric and computer-aided assessment of renal biopsies. Application of digital imaging to pathology made substantial progress over the past decade; it is now in use for education, clinical trials and translational research. Digital pathology evolved as a valuable tool to generate comprehensive structural information in digital form, a key prerequisite for achieving precision pathology for computational biology. The application of this new technology on an international scale is driving novel methods for collaborations, providing unique opportunities but also challenges. Standardization of methods needs to be rigorously evaluated and applied at each step, from specimen processing to scanning, uploading into digital repositories, morphologic, morphometric and computer-aided assessment, data collection and analysis. In this review, we discuss the status and opportunities created by the application of digital imaging to precision nephropathology, and present a vision for the near future.

Distribution and predictors of wing shape and size variability in three sister species of solitary bees

PubMed Central

Prunier, Jérôme G.; Dewulf, Alexandre; Kuhlmann, Michael; Michez, Denis

2017-01-01

Morphological traits can be highly variable over time in a particular geographical area. Different selective pressures shape those traits, which is crucial in evolutionary biology. Among these traits, insect wing morphometry has already been widely used to describe phenotypic variability at the inter-specific level. On the contrary, fewer studies have focused on intra-specific wing morphometric variability. Yet, such investigations are relevant to study potential convergences of variation that could highlight micro-evolutionary processes. The recent sampling and sequencing of three solitary bees of the genus Melitta across their entire species range provides an excellent opportunity to jointly analyse genetic and morphometric variability. In the present study, we first aim to analyse the spatial distribution of the wing shape and centroid size (used as a proxy for body size) variability. Secondly, we aim to test different potential predictors of this variability at both the intra- and inter-population levels, which includes genetic variability, but also geographic locations and distances, elevation, annual mean temperature and precipitation. The comparison of spatial distribution of intra-population morphometric diversity does not reveal any convergent pattern between species, thus undermining the assumption of a potential local and selective adaptation at the population level. Regarding intra-specific wing shape differentiation, our results reveal that some tested predictors, such as geographic and genetic distances, are associated with a significant correlation for some species. However, none of these predictors are systematically identified for the three species as an important factor that could explain the intra-specific morphometric variability. As a conclusion, for the three solitary bee species and at the scale of this study, our results clearly tend to discard the assumption of the existence of a common pattern of intra-specific signal/structure within the intra-specific wing shape and body size variability. PMID:28273178

Leaf Morphology, Taxonomy and Geometric Morphometrics: A Simplified Protocol for Beginners

PubMed Central

Viscosi, Vincenzo; Cardini, Andrea

2011-01-01

Taxonomy relies greatly on morphology to discriminate groups. Computerized geometric morphometric methods for quantitative shape analysis measure, test and visualize differences in form in a highly effective, reproducible, accurate and statistically powerful way. Plant leaves are commonly used in taxonomic analyses and are particularly suitable to landmark based geometric morphometrics. However, botanists do not yet seem to have taken advantage of this set of methods in their studies as much as zoologists have done. Using free software and an example dataset from two geographical populations of sessile oak leaves, we describe in detailed but simple terms how to: a) compute size and shape variables using Procrustes methods; b) test measurement error and the main levels of variation (population and trees) using a hierachical design; c) estimate the accuracy of group discrimination; d) repeat this estimate after controlling for the effect of size differences on shape (i.e., allometry). Measurement error was completely negligible; individual variation in leaf morphology was large and differences between trees were generally bigger than within trees; differences between the two geographic populations were small in both size and shape; despite a weak allometric trend, controlling for the effect of size on shape slighly increased discrimination accuracy. Procrustes based methods for the analysis of landmarks were highly efficient in measuring the hierarchical structure of differences in leaves and in revealing very small-scale variation. In taxonomy and many other fields of botany and biology, the application of geometric morphometrics contributes to increase scientific rigour in the description of important aspects of the phenotypic dimension of biodiversity. Easy to follow but detailed step by step example studies can promote a more extensive use of these numerical methods, as they provide an introduction to the discipline which, for many biologists, is less intimidating than the often inaccessible specialistic literature. PMID:21991324

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

NASA Astrophysics Data System (ADS)

Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

2014-02-01

Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

Interevent time distributions of human multi-level activity in a virtual world

NASA Astrophysics Data System (ADS)

Mryglod, O.; Fuchs, B.; Szell, M.; Holovatch, Yu.; Thurner, S.

2015-02-01

Studying human behavior in virtual environments provides extraordinary opportunities for a quantitative analysis of social phenomena with levels of accuracy that approach those of the natural sciences. In this paper we use records of player activities in the massive multiplayer online game Pardus over 1238 consecutive days, and analyze dynamical features of sequences of actions of players. We build on previous work where temporal structures of human actions of the same type were quantified, and provide an empirical understanding of human actions of different types. This study of multi-level human activity can be seen as a dynamic counterpart of static multiplex network analysis. We show that the interevent time distributions of actions in the Pardus universe follow highly non-trivial distribution functions, from which we extract action-type specific characteristic 'decay constants'. We discuss characteristic features of interevent time distributions, including periodic patterns on different time scales, bursty dynamics, and various functional forms on different time scales. We comment on gender differences of players in emotional actions, and find that while males and females act similarly when performing some positive actions, females are slightly faster for negative actions. We also observe effects on the age of players: more experienced players are generally faster in making decisions about engaging in and terminating enmity and friendship, respectively.

Biomimetic surface structuring using cylindrical vector femtosecond laser beams

PubMed Central

Skoulas, Evangelos; Manousaki, Alexandra; Fotakis, Costas; Stratakis, Emmanuel

2017-01-01

We report on a new, single-step and scalable method to fabricate highly ordered, multi-directional and complex surface structures that mimic the unique morphological features of certain species found in nature. Biomimetic surface structuring was realized by exploiting the unique and versatile angular profile and the electric field symmetry of cylindrical vector (CV) femtosecond (fs) laser beams. It is shown that, highly controllable, periodic structures exhibiting sizes at nano-, micro- and dual- micro/nano scales can be directly written on Ni upon line and large area scanning with radial and azimuthal polarization beams. Depending on the irradiation conditions, new complex multi-directional nanostructures, inspired by the Shark’s skin morphology, as well as superhydrophobic dual-scale structures mimicking the Lotus’ leaf water repellent properties can be attained. It is concluded that the versatility and features variations of structures formed is by far superior to those obtained via laser processing with linearly polarized beams. More important, by exploiting the capabilities offered by fs CV fields, the present technique can be further extended to fabricate even more complex and unconventional structures. We believe that our approach provides a new concept in laser materials processing, which can be further exploited for expanding the breadth and novelty of applications. PMID:28327611

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

PubMed

Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

2018-09-01

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

Knowledge Discovery for Transonic Regional-Jet Wing through Multidisciplinary Design Exploration

NASA Astrophysics Data System (ADS)

Chiba, Kazuhisa; Obayashi, Shigeru; Morino, Hiroyuki

Data mining is an important facet of solving multi-objective optimization problem. Because it is one of the effective manner to discover the design knowledge in the multi-objective optimization problem which obtains large data. In the present study, data mining has been performed for a large-scale and real-world multidisciplinary design optimization (MDO) to provide knowledge regarding the design space. The MDO among aerodynamics, structures, and aeroelasticity of the regional-jet wing was carried out using high-fidelity evaluation models on the adaptive range multi-objective genetic algorithm. As a result, nine non-dominated solutions were generated and used for tradeoff analysis among three objectives. All solutions evaluated during the evolution were analyzed for the tradeoffs and influence of design variables using a self-organizing map to extract key features of the design space. Although the MDO results showed the inverted gull-wings as non-dominated solutions, one of the key features found by data mining was the non-gull wing geometry. When this knowledge was applied to one optimum solution, the resulting design was found to have better performance compared with the original geometry designed in the conventional manner.

Morphometric synaptology of a whole neuron profile using a semiautomatic interactive computer system.

PubMed

Saito, K; Niki, K

1983-07-01

We propose a new method of dealing with morphometric synaptology that processes all synapses and boutons around the HRP marked neuron on a large composite electron micrograph, rather than a qualitative or a piecemeal quantitative study of a particular synapse and/or bouton that is not positioned on the surface of the neuron. This approach requires the development of both neuroanatomical procedures, by which a specific whole neuronal profile is identified, and valuable specialized tools, which support the collection and analysis of a great volume of morphometric data from composite electron micrographs, in order to reduce the burden of the morphologist. The present report is also concerned with the total and reliable semi-automatic interactive computer system for gathering and analyzing morphometric data that has been under development in our laboratory. A morphologist performs the pattern recognition portion by using a large-sized tablet digitizer and a menu-sheet command, and the system registers the various morphometric values of many different neurons and performs statistical analysis. Some examples of morphometric measurements and analysis show the usefulness and efficiency of the proposed system and method.

Morphometric changes of corneal endothelial cells following intracameral air for micro perforation of the Descemet Membrane during big-bubble deep anterior lamellar keratoplasty.

PubMed

Khattak, Ashbala; Nakhli, Fouad R; Abdullatif Abouollo, Hussam Mohammad

2016-01-01

The aim of this study was to assess the effect of intracameral air on the endothelial cell morphometrics. This is a retrospective controlled interventional cohort study of 26 patients (18 males and 8 females) who underwent unilateral deep anterior lamellar keratoplasty (DALK) for moderate keratoconus. The DALK patients were divided into two groups: a treatment group (14), which had micro perforations of the Descemet Membrane (DM) intraoperatively and received intracameral air at the end of the surgery; and an independent control group (12), which had no micro perforation and thus no intracameral air was injected. Postoperative best corrected visual acuity (BCVA), sphere, cylinder, spherical equivalent (SEQ), central corneal thickness, and endothelial cell morphometric features consisted of the endothelial cell density (ECD), polymegathism, and pleomorphism were compared between treatment and control groups. The mean BCVA was 0.36 ± 0.36 logMAR in the treatment group and 0.17 ± 0.11 logMAR in the control group (p = 0.081), and the mean corneal thickness was 507.86 ± 62.69 μm in the treatment group and 525.67 ± 37.54 μm in the control group air (p = 0.399). Furthermore, the mean sphere was -5.14 ± 4.17D and -1.02 ± 3.29D, the mean cylinder was -3.16 ± 2.20D and -2.88 ± 1.21D, and the mean SEQ was -6.72 ± 4.66D and -2.46 ± 3.14D and in the treatment and control groups respectively (p = 0.011, 0.693, and 0.013). As to morphometric features, the mean ECD was 2176.76 ± 549.18 cell/mm(2) and 2257.30 ± 436.12 cell/mm(2) in the treatment and control groups respectively (p = 0.686), and the mean pleomorphism 0.48 ± 0.09 and 0.54 ± 0.10 in the treatment and control groups respectively (p = 0.139). In contrast, the mean polymegathism was 0.37 ± 0.06 and 0.31 ± 0.05 in the treatment and control groups respectively (p = 0.009). The presence of air inside the anterior chamber for a short term may not cause further endothelial cell loss and can be safely performed to prevent postoperative Descemet Membrane detachment in case of micro perforations.

Compressive strain in Lunae Planum-shortening across wrinkle ridges

NASA Technical Reports Server (NTRS)

Plescia, J. B.

1991-01-01

Wrinkle ridges have long been considered to be structural or structurally controlled features. Most, but not all, recent studies have converged on a model in which wrinkle ridges are structural features formed under compressive stress; the deformation being accommodated by faulting and folding. Given that wrinkle ridges are compressive tectonic features, an analysis of the associated shortening and strain provides important quantitative information about local and regional deformation. Lunae Planum is dominated by north-south trending ridges extending from Kasei Valles in the north to Valles Marineris in the south. To quantify the morphometric character, a photoclinometric study was undertaken for ridges on Lunae Planum using the Davis and Soderblom. More than 25 ridges were examined between long. 57 and 80 deg, lat. 5 to 25 deg N. For each ridge, several profiles were obtained along its length. Ridge width, total relief, and elevation offset were measured for each ridge. Analyses are given.

Allometry and Interspecific Differences in the Facial Cranium of Two Closely Related Macaque Species

PubMed Central

Ito, Tsuyoshi; Nishimura, Takeshi; Takai, Masanaru

2011-01-01

Interpreting evolutionary history of macaque monkeys from fossil evidence is difficult, because their evolutionary fluctuations in body size might have removed or formed important morphological features differently in each lineage. We employed geometric morphometrics to explore allometric trajectories of craniofacial shape in two closely related species, Macaca fascicularis and M. fuscata. These two species exhibit a single shared allometric trajectory in superoinferior deflection of the anterior face, indicating that the differences in this feature can be explained by size variation. In contrast, two parallel trajectories are demonstrated in craniofacial protrusion, indicating that even if they are comparable in size, M. fuscata has a higher and shorter face than M. fascicularis. The degree of facial protrusion is most likely a critical feature for phyletic evaluation in the fascicularis group. Such analyses in various macaques would help to resolve controversies regarding phyletic interpretations of fossil macaques. PMID:22567301

Study of Automatic Image Rectification and Registration of Scanned Historical Aerial Photographs

NASA Astrophysics Data System (ADS)

Chen, H. R.; Tseng, Y. H.

2016-06-01

Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS) of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform) for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus) to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images.With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex.

PubMed

Ibayashi, Kenji; Kunii, Naoto; Matsuo, Takeshi; Ishishita, Yohei; Shimada, Seijiro; Kawai, Kensuke; Saito, Nobuhito

2018-01-01

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

PubMed Central

Ibayashi, Kenji; Kunii, Naoto; Matsuo, Takeshi; Ishishita, Yohei; Shimada, Seijiro; Kawai, Kensuke; Saito, Nobuhito

2018-01-01

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs. PMID:29674950

Remote sensing of land degradation: experiences from Latin America and the Caribbean.

PubMed

Metternicht, G; Zinck, J A; Blanco, P D; del Valle, H F

2010-01-01

Land degradation caused by deforestation, overgrazing, and inappropriate irrigation practices affects about 16% of Latin America and the Caribbean (LAC). This paper addresses issues related to the application of remote sensing technologies for the identification and mapping of land degradation features, with special attention to the LAC region. The contribution of remote sensing to mapping land degradation is analyzed from the compilation of a large set of research papers published between the 1980s and 2009, dealing with water and wind erosion, salinization, and changes of vegetation cover. The analysis undertaken found that Landsat series (MSS, TM, ETM+) are the most commonly used data source (49% of the papers report their use), followed by aerial photographs (39%), and microwave sensing (ERS, JERS-1, Radarsat) (27%). About 43% of the works analyzed use multi-scale, multi-sensor, multi-spectral approaches for mapping degraded areas, with a combination of visual interpretation and advanced image processing techniques. The use of more expensive hyperspectral and/or very high spatial resolution sensors like AVIRIS, Hyperion, SPOT-5, and IKONOS tends to be limited to small surface areas. The key issue of indicators that can directly or indirectly help recognize land degradation features in the visible, infrared, and microwave regions of the electromagnetic spectrum are discussed. Factors considered when selecting indicators for establishing land degradation baselines include, among others, the mapping scale, the spectral characteristics of the sensors, and the time of image acquisition. The validation methods used to assess the accuracy of maps produced with satellite data are discussed as well.

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Cerebral Microcirculation and Oxygen Tension in the Human Secondary Cortex

PubMed Central

Linninger, A. A.; Gould, I. G.; Marinnan, T.; Hsu, C.-Y.; Chojecki, M.; Alaraj, A.

2013-01-01

The three-dimensional spatial arrangement of the cortical microcirculatory system is critical for understanding oxygen exchange between blood vessels and brain cells. A three-dimensional computer model of a 3 × 3 × 3 mm3 subsection of the human secondary cortex was constructed to quantify oxygen advection in the microcirculation, tissue oxygen perfusion, and consumption in the human cortex. This computer model accounts for all arterial, capillary and venous blood vessels of the cerebral microvascular bed as well as brain tissue occupying the extravascular space. Microvessels were assembled with optimization algorithms emulating angiogenic growth; a realistic capillary bed was built with space filling procedures. The extravascular tissue was modeled as a porous medium supplied with oxygen by advection–diffusion to match normal metabolic oxygen demand. The resulting synthetic computer generated network matches prior measured morphometrics and fractal patterns of the cortical microvasculature. This morphologically accurate, physiologically consistent, multi-scale computer network of the cerebral microcirculation predicts the oxygen exchange of cortical blood vessels with the surrounding gray matter. Oxygen tension subject to blood pressure and flow conditions were computed and validated for the blood as well as brain tissue. Oxygen gradients along arterioles, capillaries and veins agreed with in vivo trends observed recently in imaging studies within experimental tolerances and uncertainty. PMID:23842693

Upscale Impact of Mesoscale Disturbances of Tropical Convection on Convectively Coupled Kelvin Waves

NASA Astrophysics Data System (ADS)

Yang, Q.; Majda, A.

2017-12-01

Tropical convection associated with convectively coupled Kelvin waves (CCKWs) is typically organized by an eastward-moving synoptic-scale convective envelope with numerous embedded westward-moving mesoscale disturbances. It is of central importance to assess upscale impact of mesoscale disturbances on CCKWs as mesoscale disturbances propagate at various tilt angles and speeds. Here a simple multi-scale model is used to capture this multi-scale structure, where mesoscale fluctuations are directly driven by mesoscale heating and synoptic-scale circulation is forced by mean heating and eddy transfer of momentum and temperature. The two-dimensional version of the multi-scale model drives the synoptic-scale circulation, successfully reproduces key features of flow fields with a front-to-rear tilt and compares well with results from a cloud resolving model. In the scenario with an elevated upright mean heating, the tilted vertical structure of synoptic-scale circulation is still induced by the upscale impact of mesoscale disturbances. In a faster propagation scenario, the upscale impact becomes less important, while the synoptic-scale circulation response to mean heating dominates. In the unrealistic scenario with upward/westward tilted mesoscale heating, positive potential temperature anomalies are induced in the leading edge, which will suppress shallow convection in a moist environment. In its three-dimensional version, results show that upscale impact of mesoscale disturbances that propagate at tilt angles (110o 250o) induces negative lower-tropospheric potential temperature anomalies in the leading edge, providing favorable conditions for shallow convection in a moist environment, while the remaining tilt angle cases have opposite effects. Even in the presence of upright mean heating, the front-to-rear tilted synoptic-scale circulation can still be induced by eddy terms at tilt angles (120o 240o). In the case with fast propagating mesoscale heating, positive potential temperature anomalies are induced in the lower troposphere, suppressing convection in a moist environment. This simple model also reproduces convective momentum transport and CCKWs in agreement with results from a recent cloud resolving simulation.

Morphometric and magmatic evolution at the Boset-Bericha Volcanic Complex in the Main Ethiopian Rift

NASA Astrophysics Data System (ADS)

Siegburg, Melanie; Gernon, Thomas; Bull, Jonathan; Keir, Derek; Taylor, Rex; Nixon, Casey; Abebe, Bekele; Ayele, Atalay

2017-04-01

Tectono-magmatic interactions are an intrinsic feature of continental rifting and break up in the Main Ethiopian Rift (MER). The Boset-Bericha volcanic complex (BBVC) is one of the largest stratovolcanoes in the MER (with a total area of ˜870 km2), with volcanism largely occurring over the last ˜2 Myr. Despite the fact that 4 million people live within 100 km of the volcano, little is known about its eruptive history and how the volcanic system interacts with rift valley tectonics. Here, we present a detailed relative eruption chronology combined with morphometric analyses of different elements of the volcanic complex and petrological analyses to constrain morphometric and magmatic evolution at the BBVC. Additionally, tectonic activity has been characterised around the BBVC, all based on field observations and mapping using high-resolution digital elevation data. The BBVC consists of the Gudda Volcano and the younger Bericha Volcano, two silicic eruption centres located along the NNE-SSW trending rift axis. The fault population predominantly comprises distributed extensional faults parallel to the rift axis, as well as localised discrete faults with displacements of up to 50 m in the rift centre, and up to 200 m in the NE-SW trending border fault system. Multiple cones, craters and fissure systems are also oriented parallel to the rift axis, i.e. perpendicular to the minimum compressive stress. The eruption history of BBVC can be differentiated into 5 main eruption stages, subdivided into at least 12 eruptive phases with a total of 128 mappable lava flows. Crosscutting relationships of lava flows provide a relative chronology of the eruptive history of the BBVC, starting with pre-BBVC rift floor basalts, pre-caldera and caldera activity, three post-caldera phases at the Gudda Volcano and two phases forming the Bericha Volcano. At least four fissure eruption phases occurred along the rift axis temporally in between the main eruptive phases. Morphometric analyses indicate a total corrected volume of eruptive material at the BBVC of ˜36 km3. The magmatic and morphometric evolution of the BBVC is spatially and temporally complex, showing a bimodal distribution of effusive basalts towards explosive peralkaline trachytic and rhyolitic lavas for the Gudda and Bericha Volcano, respectively, with rare intermediate lavas from fissure eruptions. Preliminary geochemical data suggest that fractional crystallisation may have played an important role in driving magmatic evolution the BBVC. This study emphasises the important role of tectono-magmatic interactions in the evolution of a continental rift system.

Cyprinid fishes of the genus Neolissochilus in Peninsular Malaysia.

PubMed

Khaironizam, M Z; Akaria-Ismail, M; Armbruster, Jonathan W

2015-05-22

Meristic, morphometric and distributional patterns of cyprinid fishes of the genus Neolissochilus found in Peninsular Malaysia are presented. Based on the current concept of Neolissochilus, only two species are present: N. soroides and N. hendersoni. Neolissochilus hendersoni differs from N. soroides by having lower scale and gill raker counts. Neolissochilus soroides has three mouth types (normal with a rounded snout, snout with a truncate edge, and lobe with a comparatively thick lower lip). A PCA of log-transformed measurements did not reveal significant differences between N. hendersoni and N. soroides, or between any of the morphotypes of N. soroides; however, a CVA of log-transformed measurements successfully classified 87.1% of all specimens. Removing body size by running a CVA on all of the principal components except PC1 (which was correlated with length) only slightly decreased the successful classification rate to 86.1%. Differences in morphometrics were as great between the three morphotypes of N. soroides as between any of the morphotypes and N. hendersoni suggesting that the morphotypes should be examined in greater detail with genetic tools. The PCA of morphometrics revealed separate clouds for N. hendersoni and N. soroides, but no differences between the N. soroides morphotypes. This study revealed that N. hendersoni is recorded for the first time in the mainland area of Peninsular Malaysia. Other nominal species of Neolissochilus reported to occur in the river systems of Peninsular Malaysia are discussed. Lissochilus tweediei Herre in Herre & Myers 1937 and Tor soro Bishop 1973 are synonyms of Neolissochilus soroides.

Phenotypic variation in dorsal fin morphology of coastal bottlenose dolphins (Tursiops truncatus) off Mexico

PubMed Central

Rocha-Olivares, Axayácatl; Morteo, Rodrigo; Weller, David W.

2017-01-01

Geographic variation in external morphology is thought to reflect an interplay between genotype and the environment. Morphological variation has been well-described for a number of cetacean species, including the bottlenose dolphin (Tursiops truncatus). In this study we analyzed dorsal fin morphometric variation in coastal bottlenose dolphins to search for geographic patterns at different spatial scales. A total of 533 dorsal fin images from 19 available photo-identification catalogs across the three Mexican oceanic regions (Pacific Ocean n = 6, Gulf of California n = 6 and, Gulf of Mexico n = 7) were used in the analysis. Eleven fin shape measurements were analyzed to evaluate fin polymorphism through multivariate tests. Principal Component Analysis on log-transformed standardized ratios explained 94% of the variance. Canonical Discriminant Function Analysis on factor scores showed separation among most study areas (p < 0.05) with exception of the Gulf of Mexico where a strong morphometric cline was found. Possible explanations for the observed differences are related to environmental, biological and evolutionary processes. Shape distinction between dorsal fins from the Pacific and those from the Gulf of California were consistent with previously reported differences in skull morphometrics and genetics. Although the functional advantages of dorsal fin shape remains to be assessed, it is not unlikely that over a wide range of environments, fin shape may represent a trade-off among thermoregulatory capacity, hydrodynamic performance and the swimming/hunting behavior of the species. PMID:28626607

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

Human seizures couple across spatial scales through travelling wave dynamics

NASA Astrophysics Data System (ADS)

Martinet, L.-E.; Fiddyment, G.; Madsen, J. R.; Eskandar, E. N.; Truccolo, W.; Eden, U. T.; Cash, S. S.; Kramer, M. A.

2017-04-01

Epilepsy--the propensity toward recurrent, unprovoked seizures--is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms--namely, the effects of an increased extracellular potassium concentration diffusing in space--that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures--and connecting these dynamics to specific biological mechanisms--promises new insights to treat this devastating disease.

Multi-Scale Ordered Cell Structure for Cost Effective Production of Hydrogen by HTWS

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

Elangovan, Elango; Rao, Ranjeet; Colella, Whitney

Production of hydrogen using an electrochemical device provides for large scale, high efficiency conversion and storage of electrical energy. When renewable electricity is used for conversion of steam to hydrogen, a low-cost and low emissions pathway to hydrogen production emerges. This project was intended to demonstrate a high efficiency High Temperature Water Splitting (HTWS) stack for the electrochemical production of low cost H2. The innovations investigated address the limitations of the state of the art through the use of a novel architecture that introduces macro-features to provide mechanical support of a thin electrolyte, and micro-features of the electrodes to lowermore » polarization losses. The approach also utilizes a combination of unique sets of fabrication options that are scalable to achieve manufacturing cost objectives. The development of HTWS process and device is guided by techno-economic and life cycle analyses.« less

A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being.

PubMed

Ravindran, Sindhu; Jambek, Asral Bahari; Muthusamy, Hariharan; Neoh, Siew-Chin

2015-01-01

A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

PubMed Central

Zhang, Shaowei; Yu, Jiancheng; Zhang, Aiqun; Yang, Lei; Shu, Yeqiang

2012-01-01

The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results. PMID:22368475

A description of the new 3D electron gun and collector modeling tool: MICHELLE

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

Petillo, J.; Mondelli, A.; Krueger, W.

1999-07-01

A new 3D finite element gun and collector modeling code is under development at SAIC in collaboration with industrial partners and national laboratories. This development program has been designed specifically to address the shortcomings of current simulation and modeling tools. In particular, although there are 3D gun codes that exist today, their ability to address fine scale features is somewhat limited in 3D due to disparate length scales of certain classes of devices. Additionally, features like advanced emission rules, including thermionic Child's law and comprehensive secondary emission models also need attention. The program specifically targets problems classes including gridded-guns, sheet-beammore » guns, multi-beam devices, and anisotropic collectors. The presentation will provide an overview of the program objectives, the approach to be taken by the development team, and a status of the project.« less

A Feature-based Approach to Big Data Analysis of Medical Images

PubMed Central

Toews, Matthew; Wachinger, Christian; Estepar, Raul San Jose; Wells, William M.

2015-01-01

This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches in O(log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct. PMID:26221685

A Feature-Based Approach to Big Data Analysis of Medical Images.

PubMed

Toews, Matthew; Wachinger, Christian; Estepar, Raul San Jose; Wells, William M

2015-01-01

This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches-in O (log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods.. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct.

Cumulus cell expansion and first polar body extrusion during in vitro oocyte maturation in relation to morphological and morphometric characteristics of the dromedary camel ovary.

PubMed

Mesbah, F; Kafi, M; Nili, H

2016-12-01

The morphological and morphometric characteristics of the ovary are fundamental properties for in vitro oocyte maturation. Nuclear maturation, including first polar body (1PB) extrusion, cytoplasmic maturation and cumulus cell (CC) expansion are the criteria for in vitro maturation (IVM) of oocyte. This study was designed to determine the effect of morphological and morphometric features of the ovary on CC expansion and 1PB extrusion during IVM of oocyte in the adult female dromedary camel. The weight, volume and three dimensions of ovaries from slaughtered dromedary camels and oocytes inside zona diameter and zona pellucida thickness were measured. The follicles were classified in regard to the size and oocytes according to their ooplasm appearance and CC compactness. Aspirated cumulus oocyte complexes (COCs) were incubated for 48 hr (with a 6-hr interval) in Hams-F10, and CC expansion and 1PB extrusion were assessed. Significant differences were seen in the shape, weight, volume and three dimensions of the ovaries between ≤4-year-old and >4-year-old dromedary camel (p < .5). Approximately, 95.82% of follicles were 2-4 mm in diameter. The mean (±SD) of inside zona diameter of the oocyte and zona pellucida thickness was 132.22 ± 13.8 and 14.64 ± 2.24 μm, respectively, in >4-year-old dromedary camel. The CC expansion and 1PB extrusion were seen in 86% and 21.88% of COCs, respectively. Age and sexual conditions of dromedary camel influence the morphological and morphometric characteristics of the ovary. Most COCs retrieved from 2-6 mm follicles are cultivable. The most slaughterhouse-derived COCs retrieved from 2-6 mm follicles of non-pregnant dromedary camels are excellent and good and yielding a most favourable diameter to achieve the developmental competence for IVM in an optimal time of 24-30 hr; the optimal time for CC expansion is 24-30 hr in this species. However, the CC expansion is a prerequisite process, but not sufficient for IVM. © 2016 Blackwell Verlag GmbH.

Coupled binary embedding for large-scale image retrieval.

PubMed

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Multi-scale characterization of topographic anisotropy

NASA Astrophysics Data System (ADS)

Roy, S. G.; Koons, P. O.; Osti, B.; Upton, P.; Tucker, G. E.

2016-05-01

We present the every-direction variogram analysis (EVA) method for quantifying orientation and scale dependence of topographic anisotropy to aid in differentiation of the fluvial and tectonic contributions to surface evolution. Using multi-directional variogram statistics to track the spatial persistence of elevation values across a landscape, we calculate anisotropy as a multiscale, direction-sensitive variance in elevation between two points on a surface. Tectonically derived topographic anisotropy is associated with the three-dimensional kinematic field, which contributes (1) differential surface displacement and (2) crustal weakening along fault structures, both of which amplify processes of surface erosion. Based on our analysis, tectonic displacements dominate the topographic field at the orogenic scale, while a combination of the local displacement and strength fields are well represented at the ridge and valley scale. Drainage network patterns tend to reflect the geometry of underlying active or inactive tectonic structures due to the rapid erosion of faults and differential uplift associated with fault motion. Regions that have uniform environmental conditions and have been largely devoid of tectonic strain, such as passive coastal margins, have predominantly isotropic topography with typically dendritic drainage network patterns. Isolated features, such as stratovolcanoes, are nearly isotropic at their peaks but exhibit a concentric pattern of anisotropy along their flanks. The methods we provide can be used to successfully infer the settings of past or present tectonic regimes, and can be particularly useful in predicting the location and orientation of structural features that would otherwise be impossible to elude interpretation in the field. Though we limit the scope of this paper to elevation, EVA can be used to quantify the anisotropy of any spatially variable property.

Remote visual analysis of large turbulence databases at multiple scales

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

Pulido, Jesus; Livescu, Daniel; Kanov, Kalin

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methodsmore » supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.« less

Remote visual analysis of large turbulence databases at multiple scales

DOE PAGES

Pulido, Jesus; Livescu, Daniel; Kanov, Kalin; ...

2018-06-15

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methodsmore » supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.« less

Interactions of multi-scale heterogeneity in the lithosphere: Australia

NASA Astrophysics Data System (ADS)

Kennett, B. L. N.; Yoshizawa, K.; Furumura, T.

2017-10-01

Understanding the complex heterogeneity of the continental lithosphere involves a wide variety of spatial scales and the synthesis of multiple classes of information. Seismic surface waves and multiply reflected body waves provide the main constraints on broad-scale structure, and bounds on the extent of the lithosphere-asthenosphere transition (LAT) can be found from the vertical gradients of S wavespeed. Information on finer-scale structures comes through body wave studies, including detailed seismic tomography and P-wave reflectivity extracted from stacked autocorrelograms of continuous component records. With the inclusion of deterministic large-scale structure and realistic medium-scale stochastic features fine-scale variations are subdued. The resulting multi-scale heterogeneity model for the Australian region gives a good representation of the character of observed seismograms and their geographic variations and matches the observations of P-wave reflectivity. P reflections in the 0.5-3.0 Hz band in the uppermost mantle suggest variations on vertical scales of a few hundred metres with amplitudes of the order of 1%. Interference of waves reflected or converted at sequences of such modest variations in physical properties produce relatively simple behaviour for lower frequencies, which can suggest simpler structures than are actually present. Vertical changes in the character of fine-scale heterogeneity can produce apparent discontinuities. In Central Australia a 'mid-lithospheric discontinuity' can be tracked via changes in frequency content of station reflectivity, with links to the broad-scale pattern of wavespeed gradients and, in particular, the gradients of radial anisotropy. Comparisons with xenolith results from southeastern Australia indicate a strong tie between geochemical stratification and P-wave reflectivity.