Switching auditory attention using spatial and non-spatial features recruits different cortical networks.

PubMed

Larson, Eric; Lee, Adrian K C

2014-01-01

Switching attention between different stimuli of interest based on particular task demands is important in many everyday settings. In audition in particular, switching attention between different speakers of interest that are talking concurrently is often necessary for effective communication. Recently, it has been shown by multiple studies that auditory selective attention suppresses the representation of unwanted streams in auditory cortical areas in favor of the target stream of interest. However, the neural processing that guides this selective attention process is not well understood. Here we investigated the cortical mechanisms involved in switching attention based on two different types of auditory features. By combining magneto- and electro-encephalography (M-EEG) with an anatomical MRI constraint, we examined the cortical dynamics involved in switching auditory attention based on either spatial or pitch features. We designed a paradigm where listeners were cued in the beginning of each trial to switch or maintain attention halfway through the presentation of concurrent target and masker streams. By allowing listeners time to switch during a gap in the continuous target and masker stimuli, we were able to isolate the mechanisms involved in endogenous, top-down attention switching. Our results show a double dissociation between the involvement of right temporoparietal junction (RTPJ) and the left inferior parietal supramarginal part (LIPSP) in tasks requiring listeners to switch attention based on space and pitch features, respectively, suggesting that switching attention based on these features involves at least partially separate processes or behavioral strategies. © 2013 Elsevier Inc. All rights reserved.

Genotypic and technological diversity of Brevibacterium linens strains for use as adjunct starter cultures in 'Pecorino di Filiano' cheese ripened in two different environments.

PubMed

Bonomo, Maria Grazia; Cafaro, Caterina; Salzano, Giovanni

2015-01-01

Twenty-two Brevibacterium linens strains isolated from 'Pecorino di Filiano' cheese ripened in two different environments (natural cave and storeroom) were characterized and differentiated for features of technological interest and by genotypic methods, in order to select strains with specific features to be used as surface starter cultures. Results showed significant differences among strains on the basis of physiological and technological features, indicating heterogeneity within the species. A middle-low level of proteolytic activity was observed in 27.3 % of strains, while a small group (9.1 %) showed a high ability. Lipolytic activity was observed at three different temperatures and the highest value was detected at 20 °C with 13.6 % of strains, while an increase in temperature produced a slightly lower lipolysis in all strains. The evaluation of diacetyl production revealed that only 22.8 % of strains showed this ability, and most of them were isolated from product ripened in the natural cave. All strains exhibited only leu-aminopeptidase activity, with values more elevated in strains coming from the natural cave product. The combined analysis of genotypic results with the data obtained by the features of technological interest study established that the random amplified polymorphic DNA (RAPD) clusters obtained were composed not only of different genotypes but of different profiles based on technological properties too. This study demonstrated the importance of the ripening environment that affects the typical features of the artisanal product, leading to the selection of a specific surface microflora. Characterized strains could be associated within surface starters to standardize the production process of cheese, but preserving its typical organoleptic and sensory characteristics and improving the quality of the final product.

Remarks on forensically interesting Sony Playstation 3 console features

NASA Astrophysics Data System (ADS)

Daugs, Gunnar; Kröger, Knut; Creutzburg, Reiner

2012-02-01

This paper deals with forensically interesting features of the Sony Playstation 3 game console. The construction and the internal structure are analyzed more precisely. Interesting forensic features of the operating system and the file system are presented. Differences between a PS3 with and without jailbreak are introduced and possible forensic attempts when using an installed Linux are discussed.

Maps showing aeromagnetic data and interpretation for the Kalmiopsis Wilderness, southwestern Oregon

USGS Publications Warehouse

Blakely, Richard J.; Page, Norman J; Gray, Floyd; Senior, Lisa; Ryan, Holly F.

1983-01-01

Most individual anomalies in this area are caused by known geologic boundaries or topographic features; those that are not are of particular interest because they may reflect areas of increased or decreased magnetization associated with zones of minerlization. 

Database and Map of Quaternary Faults and Folds in Peru and its Offshore Region

USGS Publications Warehouse

Machare, Jose; Fenton, Clark H.; Machette, Michael N.; Lavenu, Alain; Costa, Carlos; Dart, Richard L.

2003-01-01

This publication consists of a main map of Quaternary faults and fiolds of Peru, a table of Quaternary fault data, a region inset map showing relative plate motion, and a second inset map of an enlarged area of interest in southern Peru. These maps and data compilation show evidence for activity of Quaternary faults and folds in Peru and its offshore regions of the Pacific Ocean. The maps show the locations, ages, and activity rates of major earthquake-related features such as faults and fault-related folds. These data are accompanied by text databases that describe these features and document current information on their activity in the Quaternary.

In vacuo dispersion features for gamma-ray-burst neutrinos and photons

NASA Astrophysics Data System (ADS)

Amelino-Camelia, Giovanni; D'Amico, Giacomo; Rosati, Giacomo; Loret, Niccoló

2017-07-01

Over the past 15 years there has been considerable interest in the possibility of quantum-gravity-induced in vacuo dispersion, the possibility that spacetime itself might behave essentially like a dispersive medium for particle propagation. Two recent studies have exposed what might be in vacuo dispersion features for gamma-ray-burst (GRB) neutrinos of energy in the range of 100 TeV and for GRB photons with energy in the range of 10 GeV. We here show that these two features are roughly compatible with a description such that the same effects apply over four orders of magnitude in energy. We also show that it should not happen so frequently that such pronounced features arise accidentally, as a result of (still unknown) aspects of the mechanisms producing photons at GRBs or as a result of background neutrinos accidentally fitting the profile of a GRB neutrino affected by in vacuo dispersion.

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software

PubMed Central

Lee, Myungeun; Woo, Boyeong; Kuo, Michael D.; Jamshidi, Neema

2017-01-01

Objective The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. Materials and Methods MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Results Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC < 0.5). Most first order statistics and morphometric features showed moderate-to-high NDR (4 > NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. Conclusion The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics. PMID:28458602

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software.

PubMed

Lee, Myungeun; Woo, Boyeong; Kuo, Michael D; Jamshidi, Neema; Kim, Jong Hyo

2017-01-01

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC < 0.5). Most first order statistics and morphometric features showed moderate-to-high NDR (4 > NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics.

Authentic Mars Research in the High School

NASA Astrophysics Data System (ADS)

Kortekaas, Katie; Leach, Dani

2015-01-01

As a 11th and 12th grade Astrobiology class we were charged with developing a scientific research question about the potential for life on Mars. We narrowed our big picture question to, 'Where should the next Mars rover land in order to study the volcanic and water features to find evidence of past or present extremophiles on Mars?'After a lot of searching through images on JMARS (although not extensive due to high school time constraints) we narrowed our interest to three areas of Mars we thought could be good candidates to land a rover there to do further research. We know from extremophiles on Earth that microscopic life need water and energy. It seems reasonable that Mars would be no different. We developed a research question, 'Does Kasei Valles, Dzigai Vallis and Hecate Tholus have volcanic features (lava flow, fractures, volcanoes, cryovolcanoes) and water features (layers of ice, hematite, carbonate, chaos)?'This question is important and interesting because by having a deeper understanding of whether these places have evidence of volcanic and water features, we will be able to decide where the best place to land a future rover would be. Evidence of volcanic and water features are important to help determine where to land our rover because in those areas, temperatures could have been warm and the land could be wet. In these conditions, the probability of life is higher.We individually did research through JMARS (CTX, THEMIS) in order to establish if those three areas could contain certain land features (volcanic and water features) that could possibly lead to the discovery of extremophiles. We evaluated the images to determine if the three areas have evidence of those volcanic and water features.Although we are not experts at identifying features we believe we have evidence to say that all three areas are interesting, astrobiologically, but Dzigai Vallis shows the most number of types of volcanic and water features. More importantly, through this process we as a class began to understand true authentic science and how it is performed.Thank you to Arizona State University for the curriculum and guidance.

Long Period Seismological Research Program

DTIC Science & Technology

1974-10-31

in central Asia as observed at the high-gain long- period sites. Preliminary results from observations at Chiang Mai (CHG) show that the complexity...Preliminary results from observations at Chiang Mai (CHG) show that the complexity of the surface wave signals from many events in the Tadzhik-Kirgiz...and receivers. A number of Interesting features can be illustrated by examining portions of three selsmograms recorded at Chiang Mai (CHO

Optimizing students' motivation in inquiry-based learning environments: The role of instructional practices

NASA Astrophysics Data System (ADS)

Kempler, Toni M.

The influence of inquiry science instruction on the motivation of 1360 minority inner-city seventh graders was examined. The project-based curriculum incorporates motivating features like real world questions, collaboration, technology, and lesson variety. Students design investigations, collect and analyze data, and create artifacts; challenging tasks require extensive use of learning and metacognitive strategies. Study 1 used Structural Equation Modeling to investigate student perceptions of the prevalence of project-based features, including real world connections, collaboration, academic press, and work norms, and their relation to interest, efficacy, cognitive engagement, and achievement. Perceptions of features related to different motivational outcomes, indicating the importance of using differentiated rather than single measures to study motivation in context. Cognitive engagement was enhanced by interest and efficacy but did not influence achievement, perhaps because students were not proficient strategy users and were new to inquiry. Study 2 examined the relationship between instructional practices and motivation. The 23 teachers in study 1 were observed six times during one unit. Observations focused on curriculum congruence, content accuracy, contextualization, sense making, and management and climate. A majority of teacher enactment was congruent with the curriculum, indicating that students experienced motivating features of project-based science. Hierarchical Linear Modeling showed that contextualization accounted for between-teacher variance in student interest, efficacy, and cognitive engagement; Teachers encouraged motivation through extended real world examples that related material to students' experiences. Cluster analysis was used to determine how patterns of practice affected motivation. Unexpectedly these patterns did not differentially relate to cognitive engagement. Findings showed that interest and efficacy were enhanced when teachers used particular sense making practices. These teachers provided explicit scaffolding for accomplishing complex tasks with questioning and feedback that highlighted key points. Teachers also used effective management practices and maintained a positive classroom climate. In contrast, a pattern of practice where teachers used questioning and feedback to press students to make connections and synthesize concepts without scaffolding support diminished motivation, because students may have needed more help to deal with challenge. Implications from both studies suggest inquiry teachers need to use explicit scaffolding and academic press together, with effective management practices, to support motivation.

Hydraulic Jumps, Waves and Other Flow Features Found by Modeling Stably-Stratified Flows in the Salt Lake Valley

NASA Astrophysics Data System (ADS)

Chen, Y.; Ludwig, F.; Street, R.

2003-12-01

The Advanced Regional Prediction System (ARPS) was used to simulate weak synoptic wind conditions with stable stratification and pronounced drainage flow at night in the vicinity of the Jordan Narrows at the south end of Salt Lake Valley. The simulations showed the flow to be quite complex with hydraulic jumps and internal waves that make it essential to use a complete treatment of the fluid dynamics. Six one-way nested grids were used to resolve the topography; they ranged from 20-km grid spacing, initialized by ETA 40-km operational analyses down to 250-m horizontal resolution and 200 vertically stretched levels to a height of 20 km, beginning with a 10-m cell at the surface. Most of the features of interest resulted from interactions with local terrain features, so that little was lost by using one-way nesting. Canyon, gap, and over-terrain flows have a large effect on mixing and vertical transport, especially in the regions where hydraulic jumps are likely. Our results also showed that the effect of spatial resolution on simulation performance is profound. The horizontal resolution must be such that the smallest features that are likely to have important impact on the flow are spanned by at least a few grid points. Thus, the 250 m minimum resolution of this study is appropriate for treating the effects of features of about 1 km or greater extent. To be consistent, the vertical cell dimension must resolve the same terrain features resolved by the horizontal grid. These simulations show that many of the interesting flow features produce observable wind and temperature gradients at or near the surface. Accordingly, some relatively simple field measurements might be made to confirm that the mixing phenomena that were simulated actually take place in the real atmosphere, which would be very valuable for planning large, expensive field campaigns. The work was supported by the Atmospheric Sciences Program, Office of Biological and Environmental Research, U.S. Department of Energy. The National Energy Research Scientific Computing Center (NERSC) provided computational time. We thank Professor Ming Xue and others at the University of Oklahoma for their help.

Virtual Steel Connection Sculpture--Student Learning Assessment

ERIC Educational Resources Information Center

Chou, Karen C.; Moaveni, Saeed; Drane, Denise

2016-01-01

A Virtual Steel Connection Sculpture was developed through a grant from the National Science Foundation. The Virtual Sculpture is an interactive tool that shows students and anyone interested in connections how steel members are connected. This tool is created to complement students' steel design courses. The features of this educational tool,…

Intelligent Learning Management Systems: Definition, Features and Measurement of Intelligence

ERIC Educational Resources Information Center

Fardinpour, Ali; Pedram, Mir Mohsen; Burkle, Martha

2014-01-01

Virtual Learning Environments have been the center of attention in the last few decades and help educators tremendously with providing students with educational resources. Since artificial intelligence was used for educational proposes, learning management system developers showed much interest in making their products smarter and more…

Automatic detection of Martian dark slope streaks by machine learning using HiRISE images

NASA Astrophysics Data System (ADS)

Wang, Yexin; Di, Kaichang; Xin, Xin; Wan, Wenhui

2017-07-01

Dark slope streaks (DSSs) on the Martian surface are one of the active geologic features that can be observed on Mars nowadays. The detection of DSS is a prerequisite for studying its appearance, morphology, and distribution to reveal its underlying geological mechanisms. In addition, increasingly massive amounts of Mars high resolution data are now available. Hence, an automatic detection method for locating DSSs is highly desirable. In this research, we present an automatic DSS detection method by combining interest region extraction and machine learning techniques. The interest region extraction combines gradient and regional grayscale information. Moreover, a novel recognition strategy is proposed that takes the normalized minimum bounding rectangles (MBRs) of the extracted regions to calculate the Local Binary Pattern (LBP) feature and train a DSS classifier using the Adaboost machine learning algorithm. Comparative experiments using five different feature descriptors and three different machine learning algorithms show the superiority of the proposed method. Experimental results utilizing 888 extracted region samples from 28 HiRISE images show that the overall detection accuracy of our proposed method is 92.4%, with a true positive rate of 79.1% and false positive rate of 3.7%, which in particular indicates great performance of the method at eliminating non-DSS regions.

Low-level awareness accompanies "unconscious" high-level processing during continuous flash suppression.

PubMed

Gelbard-Sagiv, Hagar; Faivre, Nathan; Mudrik, Liad; Koch, Christof

2016-01-01

The scope and limits of unconscious processing are a matter of ongoing debate. Lately, continuous flash suppression (CFS), a technique for suppressing visual stimuli, has been widely used to demonstrate surprisingly high-level processing of invisible stimuli. Yet, recent studies showed that CFS might actually allow low-level features of the stimulus to escape suppression and be consciously perceived. The influence of such low-level awareness on high-level processing might easily go unnoticed, as studies usually only probe the visibility of the feature of interest, and not that of lower-level features. For instance, face identity is held to be processed unconsciously since subjects who fail to judge the identity of suppressed faces still show identity priming effects. Here we challenge these results, showing that such high-level priming effects are indeed induced by faces whose identity is invisible, but critically, only when a lower-level feature, such as color or location, is visible. No evidence for identity processing was found when subjects had no conscious access to any feature of the suppressed face. These results suggest that high-level processing of an image might be enabled by-or co-occur with-conscious access to some of its low-level features, even when these features are not relevant to the processed dimension. Accordingly, they call for further investigation of lower-level awareness during CFS, and reevaluation of other unconscious high-level processing findings.

Emotion Discrimination Using Spatially Compact Regions of Interest Extracted from Imaging EEG Activity

PubMed Central

Padilla-Buritica, Jorge I.; Martinez-Vargas, Juan D.; Castellanos-Dominguez, German

2016-01-01

Lately, research on computational models of emotion had been getting much attention due to their potential for understanding the mechanisms of emotions and their promising broad range of applications that potentially bridge the gap between human and machine interactions. We propose a new method for emotion classification that relies on features extracted from those active brain areas that are most likely related to emotions. To this end, we carry out the selection of spatially compact regions of interest that are computed using the brain neural activity reconstructed from Electroencephalography data. Throughout this study, we consider three representative feature extraction methods widely applied to emotion detection tasks, including Power spectral density, Wavelet, and Hjorth parameters. Further feature selection is carried out using principal component analysis. For validation purpose, these features are used to feed a support vector machine classifier that is trained under the leave-one-out cross-validation strategy. Obtained results on real affective data show that incorporation of the proposed training method in combination with the enhanced spatial resolution provided by the source estimation allows improving the performed accuracy of discrimination in most of the considered emotions, namely: dominance, valence, and liking. PMID:27489541

Establish and Evaluate Ada Runtime Features of Interest for Real-Time Systems

DTIC Science & Technology

1989-02-15

Runtime Features of Interest for Real - Time Systems -,-. CLEARED POR :)E,4 pUEL tCATLON SEP 2 0 19E19 ,CETM ORP t ’R RE LOO O Nt-U~HM- ANDQ SECURITY...ESTABLISH AND EVALUATE py ADA RUNTIME FEATURES OF INTEREST FOR REAL - TIME SYSTEMS CONTRACT NUMBER: MDA 903-87-D-0056 IITRI PROJECT NUMBER: T06168 PREPARED...2 2.0 SELECTION PROCESS OVERVIEW .................................... 3 2.1 REAL - TIME SYSTEMS IDENTIFICATION ........................... 4 2.2

Development of students' interest in particle physics as effect of participating in a Masterclass

NASA Astrophysics Data System (ADS)

Gedigk, Kerstin; Pospiech, Gesche

2016-05-01

The International Hands On Particle Physics Masterclasses are enjoying increasing popularity worldwide every year. In Germany a national program was brought to live in 2010, which offers these appreciated events to whole classes or courses of high school students all over the year. These events were evaluated concerning the issues of students' interest in particle physics and their perception of the events. How several interest variables interact with each other and the perception of the events is answered by structural equation modelling (sect. 5.2). The results give information about the events' effects on the students' interest development in particle physics, show which event features are important ( e.g. the authenticity) and give information about practical approaches to improve the effects of the Masterclasses. Section 5.3 deals with a group of participants which have a high interest in particle physics 6-8 weeks after the participation. The number of these students is remarkable large, with 26% of all participants. The investigation of this group shows that the Masterclass participation has the same positive effect on both sexes and all levels of physics education.

Possible Fluvial Features in Golden Crater

NASA Image and Video Library

2015-03-25

This observation from NASA Mars Reconnaissance Orbiter shows an interesting crater floor with what appear to be inverted channels, rounded lobe-like landforms, and light-toned layered deposits along the southern portion of the crater wall. High resolution can help study the layers, with an enhanced-color image showing us any variations in composition between those light-toned layers and the darker-toned surfaces. http://photojournal.jpl.nasa.gov/catalog/PIA19353

Binary classification of items of interest in a repeatable process

DOEpatents

Abell, Jeffrey A.; Spicer, John Patrick; Wincek, Michael Anthony; Wang, Hui; Chakraborty, Debejyo

2014-06-24

A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the subsequent item of interest.

Periodic and Aperiodic Close Packing: A Spontaneous Hard-Sphere Model.

ERIC Educational Resources Information Center

van de Waal, B. W.

1985-01-01

Shows how to make close-packed models from balloons and table tennis balls to illustrate structural features of clusters and organometallic cluster-compounds (which are of great interest in the study of chemical reactions). These models provide a very inexpensive and tactile illustration of the organization of matter for concrete operational…

Enhancement of morphological and vascular features in OCT images using a modified Bayesian residual transform

PubMed Central

Tan, Bingyao; Wong, Alexander; Bizheva, Kostadinka

2018-01-01

A novel image processing algorithm based on a modified Bayesian residual transform (MBRT) was developed for the enhancement of morphological and vascular features in optical coherence tomography (OCT) and OCT angiography (OCTA) images. The MBRT algorithm decomposes the original OCT image into multiple residual images, where each image presents information at a unique scale. Scale selective residual adaptation is used subsequently to enhance morphological features of interest, such as blood vessels and tissue layers, and to suppress irrelevant image features such as noise and motion artefacts. The performance of the proposed MBRT algorithm was tested on a series of cross-sectional and enface OCT and OCTA images of retina and brain tissue that were acquired in-vivo. Results show that the MBRT reduces speckle noise and motion-related imaging artefacts locally, thus improving significantly the contrast and visibility of morphological features in the OCT and OCTA images. PMID:29760996

Volumetric quantitative characterization of human patellar cartilage with topological and geometrical features on phase-contrast X-ray computed tomography.

PubMed

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

2015-11-01

Phase-contrast X-ray computed tomography (PCI-CT) has attracted significant interest in recent years for its ability to provide significantly improved image contrast in low absorbing materials such as soft biological tissue. In the research context of cartilage imaging, previous studies have demonstrated the ability of PCI-CT to visualize structural details of human patellar cartilage matrix and capture changes to chondrocyte organization induced by osteoarthritis. This study evaluates the use of geometrical and topological features for volumetric characterization of such chondrocyte patterns in the presence (or absence) of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and topological features derived from Minkowski Functionals were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). Our results show that the classification performance of SIM-derived geometrical features (AUC: 0.90 ± 0.09) is significantly better than Minkowski Functionals volume (AUC: 0.54 ± 0.02), surface (AUC: 0.72 ± 0.06), mean breadth (AUC: 0.74 ± 0.06) and Euler characteristic (AUC: 0.78 ± 0.04) (p < 10(-4)). These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as diagnostic imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Laser-induced patterns on metals and polymers for biomimetic surface engineering

NASA Astrophysics Data System (ADS)

Kietzig, Anne-Marie; Lehr, Jorge; Matus, Luke; Liang, Fang

2014-03-01

One common feature of many functional surfaces found in nature is their modular composition often exhibiting several length scales. Prominent natural examples for extreme behaviors can be named in various plant leaf (rose, peanut, lotus) or animal toe surfaces (Gecko, tree frog). Influence factors of interest are the surface's chemical composition, its microstructure, its organized or random roughness and hence the resulting surface wetting and adhesion character. Femtosecond (fs) laser micromachining offers a possibility to render all these factors in one single processing step on metallic and polymeric surfaces. Exemplarily, studies on Titanium and PTFE are shown, where the dependence of the resulting feature sizes on lasing intensity is investigated. While Ti surfaces show rigid surface patterns of micrometer scaled features with superimposed nanostructures, PTFE exhibits elastic hairy structures of nanometric diameter, which upon a certain threshold tend to bundle to larger features. Both surface patterns can be adjusted to mimic specific wetting and flow behaviour as seen on natural examples. Therefore, fs-laser micromachining is suggested as an interesting industrially scalable technique to pattern and fine-tune the surface wettability of a surface to the desired extends in one process step. Possible applications can be seen with surfaces, which require specific wetting, fouling, icing, friction or cell adhesion behaviour.

Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

PubMed Central

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-01-01

Purpose: Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis (CAD) schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification. Methods: We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features, and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest (ROIs), we performed the study using a ten-fold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only. Results: The area under the receiver operating characteristic curve (AUC) = 0.805±0.012 was obtained for the classification task. The results also showed that the most frequently-selected features by the SFFS-based algorithm in 10-fold iterations were those related to mass shape, isodensity and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions. Conclusions: In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be useful as a “second reader” in future clinical practice. PMID:24664267

A Content-Adaptive Analysis and Representation Framework for Audio Event Discovery from "Unscripted" Multimedia

NASA Astrophysics Data System (ADS)

Radhakrishnan, Regunathan; Divakaran, Ajay; Xiong, Ziyou; Otsuka, Isao

2006-12-01

We propose a content-adaptive analysis and representation framework to discover events using audio features from "unscripted" multimedia such as sports and surveillance for summarization. The proposed analysis framework performs an inlier/outlier-based temporal segmentation of the content. It is motivated by the observation that "interesting" events in unscripted multimedia occur sparsely in a background of usual or "uninteresting" events. We treat the sequence of low/mid-level features extracted from the audio as a time series and identify subsequences that are outliers. The outlier detection is based on eigenvector analysis of the affinity matrix constructed from statistical models estimated from the subsequences of the time series. We define the confidence measure on each of the detected outliers as the probability that it is an outlier. Then, we establish a relationship between the parameters of the proposed framework and the confidence measure. Furthermore, we use the confidence measure to rank the detected outliers in terms of their departures from the background process. Our experimental results with sequences of low- and mid-level audio features extracted from sports video show that "highlight" events can be extracted effectively as outliers from a background process using the proposed framework. We proceed to show the effectiveness of the proposed framework in bringing out suspicious events from surveillance videos without any a priori knowledge. We show that such temporal segmentation into background and outliers, along with the ranking based on the departure from the background, can be used to generate content summaries of any desired length. Finally, we also show that the proposed framework can be used to systematically select "key audio classes" that are indicative of events of interest in the chosen domain.

Criticality for charged black branes

NASA Astrophysics Data System (ADS)

Hennigar, Robie A.

2017-09-01

We show that the inclusion of higher curvature terms in the gravitational action can lead to phase transitions and critical behaviour for charged black branes. The higher curvature terms considered here belong to the recently constructed generalized quasi-topological class [arXiv:1703.01631], which possess a number of interesting properties, such as being ghost-free on constant curvature backgrounds and non-trivial in four dimensions. We show that critical behaviour is a generic feature of the black branes in all dimensions d ≥ 4, and contextualize the results with a review of the properties of black branes in Lovelock and quasi-topological gravity, where critical behaviour is not possible. These results may have interesting implications for the CFTs dual to this class of theories.

Science Is Women's Work: Photos and Biographies of American Women in the Sciences.

ERIC Educational Resources Information Center

Gallop, Nancy

Girls show an early interest in science, but are deterred from pursuing science careers as they get older due to society's stereotypes. This text identifies the many women in history who have made significant contributions to all scientific fields. The volume features the biographies of Maria Mitchell (Astronomer); Ellen Richards (Chemist,…

Seeing Coloured Fruits: Utilisation of the Theory of Adaptive Memory in Teaching Botany

ERIC Educational Resources Information Center

Prokop, Pavol; Fancovicová, Jana

2014-01-01

Plants are characterised by a great diversity of easily observed features such as colours or shape, but children show low interest in learning about them. Here, we integrated modern theory of adaptive memory and evolutionary views of the function of fruit colouration on children's retention of information. Survival-relevant (fruit toxicity) and…

FSMRank: feature selection algorithm for learning to rank.

PubMed

Lai, Han-Jiang; Pan, Yan; Tang, Yong; Yu, Rong

2013-06-01

In recent years, there has been growing interest in learning to rank. The introduction of feature selection into different learning problems has been proven effective. These facts motivate us to investigate the problem of feature selection for learning to rank. We propose a joint convex optimization formulation which minimizes ranking errors while simultaneously conducting feature selection. This optimization formulation provides a flexible framework in which we can easily incorporate various importance measures and similarity measures of the features. To solve this optimization problem, we use the Nesterov's approach to derive an accelerated gradient algorithm with a fast convergence rate O(1/T(2)). We further develop a generalization bound for the proposed optimization problem using the Rademacher complexities. Extensive experimental evaluations are conducted on the public LETOR benchmark datasets. The results demonstrate that the proposed method shows: 1) significant ranking performance gain compared to several feature selection baselines for ranking, and 2) very competitive performance compared to several state-of-the-art learning-to-rank algorithms.

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

Honorio, J.; Goldstein, R.; Honorio, J.

We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statisticalmore » theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.« less

[Progressive lost of interest of family medicine residents with regard to home follow-up of the elderly].

PubMed

Aubry, François; Couturier, Yves; Dumont, Serge

2014-06-01

This paper deals with the lack of interest shown by family medicine residents in Quebec (Canada) in home follow-up or monitoring of the elderly. By collecting and analyzing data from sixteen family medicine residents before and after their first experience of home follow-up, and from four medical supervisors, we found that residents experience a rapid loss of interest in this practice over a very short period. We show that this lack of interest stems first from the difficulty of applying the principle of patient-centered care, wherein medical interventions must meet the needs of the elderly in their entirety. Secondly, residents complain that they have to deal with many administrative tasks. They call for implementation of professional features to better integrate services such as case management.

A blur-invariant local feature for motion blurred image matching

NASA Astrophysics Data System (ADS)

Tong, Qiang; Aoki, Terumasa

2017-07-01

Image matching between a blurred (caused by camera motion, out of focus, etc.) image and a non-blurred image is a critical task for many image/video applications. However, most of the existing local feature schemes fail to achieve this work. This paper presents a blur-invariant descriptor and a novel local feature scheme including the descriptor and the interest point detector based on moment symmetry - the authors' previous work. The descriptor is based on a new concept - center peak moment-like element (CPME) which is robust to blur and boundary effect. Then by constructing CPMEs, the descriptor is also distinctive and suitable for image matching. Experimental results show our scheme outperforms state of the art methods for blurred image matching

Simulation of synthetic gecko arrays shearing on rough surfaces

PubMed Central

Gillies, Andrew G.; Fearing, Ronald S.

2014-01-01

To better understand the role of surface roughness and tip geometry in the adhesion of gecko synthetic adhesives, a model is developed that attempts to uncover the relationship between surface feature size and the adhesive terminal feature shape. This model is the first to predict the adhesive behaviour of a plurality of hairs acting in shear on simulated rough surfaces using analytically derived contact models. The models showed that the nanoscale geometry of the tip shape alters the macroscale adhesion of the array of fibres by nearly an order of magnitude, and that on sinusoidal surfaces with amplitudes much larger than the nanoscale features, spatula-shaped features can increase adhesive forces by 2.5 times on smooth surfaces and 10 times on rough surfaces. Interestingly, the summation of the fibres acting in concert shows behaviour much more complex that what could be predicted with the pull-off model of a single fibre. Both the Johnson–Kendall–Roberts and Kendall peel models can explain the experimentally observed frictional adhesion effect previously described in the literature. Similar to experimental results recently reported on the macroscale features of the gecko adhesive system, adhesion drops dramatically when surface roughness exceeds the size and spacing of the adhesive fibrillar features. PMID:24694893

Binary classification of items of interest in a repeatable process

DOEpatents

Abell, Jeffrey A; Spicer, John Patrick; Wincek, Michael Anthony; Wang, Hui; Chakraborty, Debejyo

2015-01-06

A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.

Psychopathy and interests: Implications of psychopathic personality traits for vocational and avocational preferences.

PubMed

Nagel, Madeline G; Watts, Ashley L; Murphy, Brett A; Lilienfeld, Scott O

2018-06-21

General personality traits and interests, both vocational and avocational, have long been considered intertwined constructs. Nevertheless, the linkages between personality disorder features, such as psychopathy, and interests are poorly understood. This study bridges this gap by examining how psychopathic traits relate to vocational and avocational interests, and to what extent these associations are distinctive to psychopathy as opposed to a broader pattern of general and abnormal personality traits. In a sample of 426 community participants, Psychopathic Personality Inventory-Revised Fearless Dominance features of psychopathy were associated with interest in a broad swath of vocational and avocational interests, whereas Self-Centered Impulsivity features were associated with realistic, artistic, enterprising, and conventional interests; most zero-order associations were in the small to medium range. Coldheartedness and the factors derived from the Levenson Self-Report Psychopathy Scale were largely unrelated to interests, although there were several notable exceptions. Narcissistic traits, as well as HEXACO (Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness) Honesty-Humility, Extraversion, and Openness to Experience, were also related broadly to interests. The patterns of interests associated with personality disorder traits may ultimately bear practical implications for interventions as individuals seek out positions or hobbies that suit their traits. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Dynamics and circuit of a chaotic system with a curve of equilibrium points

NASA Astrophysics Data System (ADS)

Pham, Viet-Thanh; Volos, Christos; Kapitaniak, Tomasz; Jafari, Sajad; Wang, Xiong

2018-03-01

Although chaotic systems have been intensively studied since the 1960s, new systems with mysterious features are still of interest. A novel chaotic system including hyperbolic functions is proposed in this work. Especially, the system has an infinite number of equilibrium points. Dynamics of the system are investigated by using non-linear tools such as phase portrait, bifurcation diagram, and Lyapunov exponent. It is interesting that the system can display coexisting chaotic attractors. An electronic circuit for realising the chaotic system has been implemented. Experimental results show a good agreement with theoretical ones.

Amorphous photonic crystals with only short-range order.

PubMed

Shi, Lei; Zhang, Yafeng; Dong, Biqin; Zhan, Tianrong; Liu, Xiaohan; Zi, Jian

2013-10-04

Distinct from conventional photonic crystals with both short- and long-range order, amorphous photonic crystals that possess only short-range order show interesting optical responses owing to their unique structural features. Amorphous photonic crystals exhibit unique light scattering and transport, which lead to a variety of interesting phenomena such as isotropic photonic bandgaps or pseudogaps, noniridescent structural colors, and light localization. Recent experimental and theoretical advances in the study of amorphous photonic crystals are summarized, focusing on their unique optical properties, artificial fabrication, bionspiration, and potential applications. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Overview and forensic investigation approaches of the gaming console Sony PlayStation Portable

NASA Astrophysics Data System (ADS)

Schön, Stephan; Schön, Ralph; Kröger, Knut; Creutzburg, Reiner

2013-03-01

This paper addresses the forensically interesting features of the Sony PlayStation Portable game console. The construction and the internal structure are analyzed precisely and interesting forensic features of the operating system and the file system are presented.

Closed-Loop Process Control for Electron Beam Freeform Fabrication and Deposition Processes

NASA Technical Reports Server (NTRS)

Taminger, Karen M. (Inventor); Hofmeister, William H. (Inventor); Martin, Richard E. (Inventor); Hafley, Robert A. (Inventor)

2013-01-01

A closed-loop control method for an electron beam freeform fabrication (EBF(sup 3)) process includes detecting a feature of interest during the process using a sensor(s), continuously evaluating the feature of interest to determine, in real time, a change occurring therein, and automatically modifying control parameters to control the EBF(sup 3) process. An apparatus provides closed-loop control method of the process, and includes an electron gun for generating an electron beam, a wire feeder for feeding a wire toward a substrate, wherein the wire is melted and progressively deposited in layers onto the substrate, a sensor(s), and a host machine. The sensor(s) measure the feature of interest during the process, and the host machine continuously evaluates the feature of interest to determine, in real time, a change occurring therein. The host machine automatically modifies control parameters to the EBF(sup 3) apparatus to control the EBF(sup 3) process in a closed-loop manner.

3D Texture Features Mining for MRI Brain Tumor Identification

NASA Astrophysics Data System (ADS)

Rahim, Mohd Shafry Mohd; Saba, Tanzila; Nayer, Fatima; Syed, Afraz Zahra

2014-03-01

Medical image segmentation is a process to extract region of interest and to divide an image into its individual meaningful, homogeneous components. Actually, these components will have a strong relationship with the objects of interest in an image. For computer-aided diagnosis and therapy process, medical image segmentation is an initial mandatory step. Medical image segmentation is a sophisticated and challenging task because of the sophisticated nature of the medical images. Indeed, successful medical image analysis heavily dependent on the segmentation accuracy. Texture is one of the major features to identify region of interests in an image or to classify an object. 2D textures features yields poor classification results. Hence, this paper represents 3D features extraction using texture analysis and SVM as segmentation technique in the testing methodologies.

Visually assessed colour overlay features in shear-wave elastography for breast masses: quantification and diagnostic performance.

PubMed

Gweon, Hye Mi; Youk, Ji Hyun; Son, Eun Ju; Kim, Jeong-Ah

2013-03-01

To determine whether colour overlay features can be quantified by the standard deviation (SD) of the elasticity measured in shear-wave elastography (SWE) and to evaluate the diagnostic performance for breast masses. One hundred thirty-three breast lesions in 119 consecutive women who underwent SWE before US-guided core needle biopsy or surgical excision were analysed. SWE colour overlay features were assessed using two different colour overlay pattern classifications. Quantitative SD of the elasticity value was measured with the region of interest including the whole breast lesion. For the four-colour overlay pattern, the area under the ROC curve (Az) was 0.947; with a cutoff point between pattern 2 and 3, sensitivity and specificity were 94.4 % and 81.4 %. According to the homogeneity of the elasticity, the Az was 0.887; with a cutoff point between reasonably homogeneous and heterogeneous, sensitivity and specificity were 86.1 % and 82.5 %. For the SD of the elasticity, the Az was 0.944; with a cutoff point of 12.1, sensitivity and specificity were 88.9 % and 89.7 %. The colour overlay features showed significant correlations with the quantitative SD of the elasticity (P < 0.001). The colour overlay features and the SD of the elasticity in SWE showed excellent diagnostic performance and showed good correlations between them.

Commentary: Tablet PCs--Lightweights with a Teaching Punch

ERIC Educational Resources Information Center

Parslow, Graham R.

2010-01-01

Tablet (or slate) computers are a group of small portable computers that have two features in common, a touch screen and wireless connectivity to the web. At the 2010 Consumer Electronics show held in January in Las Vegas, this category of product caused the greatest interest ahead of the release of the Apple iPad (www.cesweb.org). The tablet PC…

Genome Sequence of Streptococcus phocae subsp. salmonis Strain C-4T, Isolated from Atlantic Salmon (Salmo salar)

PubMed Central

Suarez, Rudy; Lazo, Eduardo; Bravo, Diego; Llegues, Katerina O.; Romalde, Jesús L.; Godoy, Marcos G.

2014-01-01

Streptococcus phocae subsp. salmonis is a fish pathogen that has an important impact on the Chilean salmon industry. Here, we report the genome sequence of the type strain C-4T isolated from Atlantic salmon (Salmo salar), showing a number of interesting features and genes related to its possible virulence factors. PMID:25502668

Image search engine with selective filtering and feature-element-based classification

NASA Astrophysics Data System (ADS)

Li, Qing; Zhang, Yujin; Dai, Shengyang

2001-12-01

With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.

Modal method for Second Harmonic Generation in nanostructures

NASA Astrophysics Data System (ADS)

Héron, S.; Pardo, F.; Bouchon, P.; Pelouard, J.-L.; Haïdar, R.

2015-05-01

Nanophotonic devices show interesting features for nonlinear response enhancement but numerical tools are mandatory to fully determine their behaviour. To address this need, we present a numerical modal method dedicated to nonlinear optics calculations under the undepleted pump approximation. It is brie y explained in the frame of Second Harmonic Generation for both plane waves and focused beams. The nonlinear behaviour of selected nanostructures is then investigated to show comparison with existing analytical results and study the convergence of the code.

Genetic loss of diazepam binding inhibitor in mice impairs social interest.

PubMed

Ujjainwala, A L; Courtney, C D; Rhoads, S G; Rhodes, J S; Christian, C A

2018-06-01

Neuropsychiatric disorders in which reduced social interest is a common symptom, such as autism, depression, and anxiety, are frequently associated with genetic mutations affecting γ-aminobutyric acid (GABA)ergic transmission. Benzodiazepine treatment, acting via GABA type-A receptors, improves social interaction in male mouse models with autism-like features. The protein diazepam binding inhibitor (DBI) can act as an endogenous benzodiazepine, but a role for DBI in social behavior has not been described. Here, we investigated the role of DBI in the social interest and recognition behavior of mice. The responses of DBI wild-type and knockout male and female mice to ovariectomized female wild-type mice (a neutral social stimulus) were evaluated in a habituation/dishabituation task. Both male and female knockout mice exhibited reduced social interest, and DBI knockout mice lacked the sex difference in social interest levels observed in wild-type mice, in which males showed higher social interest levels than females. The ability to discriminate between familiar and novel stimulus mice (social recognition) was not impaired in DBI-deficient mice of either sex. DBI knockouts could learn a rotarod motor task, and could discriminate between social and nonsocial odors. Both sexes of DBI knockout mice showed increased repetitive grooming behavior, but not in a manner that would account for the decrease in social investigation time. Genetic loss of DBI did not alter seminal vesicle weight, indicating that the social interest phenotype of males lacking DBI is not due to reduced circulating testosterone. Together, these studies show a novel role of DBI in driving social interest and motivation. © 2017 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Relating interesting quantitative time series patterns with text events and text features

NASA Astrophysics Data System (ADS)

Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other application domains such as data analysis of smart grids, cyber physical systems or the security of critical infrastructure, where the data consists of a combination of quantitative and textual time series data.

Identifying significant environmental features using feature recognition.

DOT National Transportation Integrated Search

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

An eye tracking study of bloodstain pattern analysts during pattern classification.

PubMed

Arthur, R M; Hoogenboom, J; Green, R D; Taylor, M C; de Bruin, K G

2018-05-01

Bloodstain pattern analysis (BPA) is the forensic discipline concerned with the classification and interpretation of bloodstains and bloodstain patterns at the crime scene. At present, it is unclear exactly which stain or pattern properties and their associated values are most relevant to analysts when classifying a bloodstain pattern. Eye tracking technology has been widely used to investigate human perception and cognition. Its application to forensics, however, is limited. This is the first study to use eye tracking as a tool for gaining access to the mindset of the bloodstain pattern expert. An eye tracking method was used to follow the gaze of 24 bloodstain pattern analysts during an assigned task of classifying a laboratory-generated test bloodstain pattern. With the aid of an automated image-processing methodology, the properties of selected features of the pattern were quantified leading to the delineation of areas of interest (AOIs). Eye tracking data were collected for each AOI and combined with verbal statements made by analysts after the classification task to determine the critical range of values for relevant diagnostic features. Eye-tracking data indicated that there were four main regions of the pattern that analysts were most interested in. Within each region, individual elements or groups of elements that exhibited features associated with directionality, size, colour and shape appeared to capture the most interest of analysts during the classification task. The study showed that the eye movements of trained bloodstain pattern experts and their verbal descriptions of a pattern were well correlated.

Turbulence Measurements of Separate Flow Nozzles with Mixing Enhancement Features

NASA Technical Reports Server (NTRS)

Bridges, James; Wernet, Mark P.

2002-01-01

Comparison of turbulence data taken in three separate flow nozzles, two with mixing enhancement features on their core nozzle, shows how the mixing enhancement features modify turbulence to reduce jet noise. The three nozzles measured were the baseline axisymmetric nozzle 3BB, the alternating chevron nozzle, 3A12B, with 6-fold symmetry, and the flipper tab nozzle 3T24B also with 6-fold symmetry. The data presented show the differences in turbulence characteristics produced by the geometric differences in the nozzles, with emphasis on those characteristics of interest in jet noise. Among the significant findings: the enhanced mixing devices reduce turbulence in the jet mixing region while increasing it in the fan/core shear layer, the ratios of turbulence components are significantly altered by the mixing devices, and the integral lengthscales do not conform to any turbulence model yet proposed. These findings should provide guidance for modeling the statistical properties of turbulence to improve jet noise prediction.

Individual differences in the processing of smoking-cessation video messages: An imaging genetics study.

PubMed

Shi, Zhenhao; Wang, An-Li; Aronowitz, Catherine A; Romer, Daniel; Langleben, Daniel D

2017-09-01

Studies testing the benefits of enriching smoking-cessation video ads with attention-grabbing sensory features have yielded variable results. Dopamine transporter gene (DAT1) has been implicated in attention deficits. We hypothesized that DAT1 polymorphism is partially responsible for this variability. Using functional magnetic resonance imaging, we examined brain responses to videos high or low in attention-grabbing features, indexed by "message sensation value" (MSV), in 53 smokers genotyped for DAT1. Compared to other smokers, 10/10 homozygotes showed greater neural response to High- vs. Low-MSV smoking-cessation videos in two a priori regions of interest: the right temporoparietal junction and the right ventrolateral prefrontal cortex. These regions are known to underlie stimulus-driven attentional processing. Exploratory analysis showed that the right temporoparietal response positively predicted follow-up smoking behavior indexed by urine cotinine. Our findings suggest that responses to attention-grabbing features in smoking-cessation messages is affected by the DAT1 genotype. Copyright © 2017. Published by Elsevier B.V.

Micro- and Nano-Liquid Phases Coexistent with Ice as Separation and Reaction Media.

PubMed

Okada, Tetsuo

2017-04-01

Ice has a variety of scientifically interesting features, some of which have not been reasonably interpreted despite substantial efforts by researchers. Most chemical studies of ice have focused on the elucidation of its physicochemical nature and its roles in the natural environment. Ice often contains impurities, such as salts, and in such cases, a liquid phase coexists with solid ice over a wide temperature range. This impure ice also acts as a cryoreactor, governing the circulation of chemical species of environmental importance. Reactions and phenomena occurring in this liquid phase show features different from those seen in normal bulk aqueous solutions. In the present account, we discuss the chemical characteristics of the liquid phase that develops in a frozen aqueous phase and show how novel analytical systems can be designed based on he features of the liquid phase which are predictable in some cases but unpredictable in others. © 2017 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Attentional Bias in Human Category Learning: The Case of Deep Learning.

PubMed

Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

2018-01-01

Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures. Third, we show that even BP can exhibit human like learning differences between integral and separable category structures when high dimensional stimuli (face exemplars) are used. We conclude, after visualizing the hidden unit representations, that DL appears to extend initial learning due to feature development thereby reducing destructive feature competition by incrementally refining feature detectors throughout later layers until a tipping point (in terms of error) is reached resulting in rapid asymptotic learning.

A Feature Fusion Based Forecasting Model for Financial Time Series

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

2014-01-01

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

Effects of Individual Differences and Situational Features on Age Differences in Mindless Reading.

PubMed

Shake, Matthew C; Shulley, Leah J; Soto-Freita, Angelica M

2016-09-01

Mindless reading occurs when an individual shifts their attention away from the text and toward other off-task thoughts. This study examined whether previously reported age-related declines in mindless reading episodes are due primarily to (a) situational features related to the text itself (e.g., text genre or interest in the text) and/or (b) individual differences in cognitive ability. Participants read 2 texts written in different genres but about the same topic. During reading, they were randomly probed to indicate whether they were on-task or mind-wandering. They also indicated their perceptions regarding the interest and difficulty of the text, and completed a battery of cognitive ability measures. The results showed that (a) text genre may engender some age differences in mindless reading and (b) greater age and perceived interest in the text were each uniquely predictive of reduced mindless reading for both text genres. Individual differences in cognitive abilities (e.g., working memory, vocabulary) did not account for additional significant variance in mindless reading after interest and age were taken into account. Our findings are discussed in terms of implications for age differences in lapses of attention during reading and predictors of mind-wandering generally. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Multimodal Event Detection in Twitter Hashtag Networks

DOE PAGES

Yilmaz, Yasin; Hero, Alfred O.

2016-07-01

In this study, event detection in a multimodal Twitter dataset is considered. We treat the hashtags in the dataset as instances with two modes: text and geolocation features. The text feature consists of a bag-of-words representation. The geolocation feature consists of geotags (i.e., geographical coordinates) of the tweets. Fusing the multimodal data we aim to detect, in terms of topic and geolocation, the interesting events and the associated hashtags. To this end, a generative latent variable model is assumed, and a generalized expectation-maximization (EM) algorithm is derived to learn the model parameters. The proposed method is computationally efficient, and lendsmore » itself to big datasets. Lastly, experimental results on a Twitter dataset from August 2014 show the efficacy of the proposed method.« less

Context-dependent logo matching and recognition.

PubMed

Sahbi, Hichem; Ballan, Lamberto; Serra, Giuseppe; Del Bimbo, Alberto

2013-03-01

We contribute, through this paper, to the design of a novel variational framework able to match and recognize multiple instances of multiple reference logos in image archives. Reference logos and test images are seen as constellations of local features (interest points, regions, etc.) and matched by minimizing an energy function mixing: 1) a fidelity term that measures the quality of feature matching, 2) a neighborhood criterion that captures feature co-occurrence/geometry, and 3) a regularization term that controls the smoothness of the matching solution. We also introduce a detection/recognition procedure and study its theoretical consistency. Finally, we show the validity of our method through extensive experiments on the challenging MICC-Logos dataset. Our method overtakes, by 20%, baseline as well as state-of-the-art matching/recognition procedures.

A novel method for unsteady flow field segmentation based on stochastic similarity of direction

NASA Astrophysics Data System (ADS)

Omata, Noriyasu; Shirayama, Susumu

2018-04-01

Recent developments in fluid dynamics research have opened up the possibility for the detailed quantitative understanding of unsteady flow fields. However, the visualization techniques currently in use generally provide only qualitative insights. A method for dividing the flow field into physically relevant regions of interest can help researchers quantify unsteady fluid behaviors. Most methods at present compare the trajectories of virtual Lagrangian particles. The time-invariant features of an unsteady flow are also frequently of interest, but the Lagrangian specification only reveals time-variant features. To address these challenges, we propose a novel method for the time-invariant spatial segmentation of an unsteady flow field. This segmentation method does not require Lagrangian particle tracking but instead quantitatively compares the stochastic models of the direction of the flow at each observed point. The proposed method is validated with several clustering tests for 3D flows past a sphere. Results show that the proposed method reveals the time-invariant, physically relevant structures of an unsteady flow.

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data

DOEpatents

Perkins, David Nikolaus; Brost, Randolph; Ray, Lawrence P.

2017-08-08

Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

Spin transfer nano-oscillators.

PubMed

Zeng, Zhongming; Finocchio, Giovanni; Jiang, Hongwen

2013-03-21

The use of spin transfer nano-oscillators (STNOs) to generate microwave signals in nanoscale devices has aroused tremendous and continuous research interest in recent years. Their key features are frequency tunability, nanoscale size, broad working temperature, and easy integration with standard silicon technology. In this feature article, we give an overview of recent developments and breakthroughs in the materials, geometry design and properties of STNOs. We focus in more depth on our latest advances in STNOs with perpendicular anisotropy, showing a way to improve the output power of STNO towards the μW range. Challenges and perspectives of the STNOs that might be productive topics for future research are also briefly discussed.

Agent based models for wealth distribution with preference in interaction

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Sen, Parongama

2014-12-01

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

Genome Sequence of Torulaspora delbrueckii NRRL Y-50541, Isolated from Mezcal Fermentation

PubMed Central

Gomez-Angulo, Jorge; Vega-Alvarado, Leticia; Escalante-García, Zazil; Grande, Ricardo; Gschaedler-Mathis, Anne; Amaya-Delgado, Lorena

2015-01-01

Torulaspora delbrueckii presents metabolic features interesting for biotechnological applications (in the dairy and wine industries). Recently, the T. delbrueckii CBS 1146 genome, which has been maintained under laboratory conditions since 1970, was published. Thus, a genome of a new mezcal yeast was sequenced and characterized and showed genetic differences and a higher genome assembly quality, offering a better reference genome. PMID:26205871

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection

PubMed Central

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-01-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices. PMID:25177107

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

PubMed

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-11-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

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

PubMed

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

2014-03-01

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

Deep features for efficient multi-biometric recognition with face and ear images

NASA Astrophysics Data System (ADS)

Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

2017-07-01

Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

Accuracy and variability of texture-based radiomics features of lung lesions across CT imaging conditions

NASA Astrophysics Data System (ADS)

Zheng, Yuese; Solomon, Justin; Choudhury, Kingshuk; Marin, Daniele; Samei, Ehsan

2017-03-01

Texture analysis for lung lesions is sensitive to changing imaging conditions but these effects are not well understood, in part, due to a lack of ground-truth phantoms with realistic textures. The purpose of this study was to explore the accuracy and variability of texture features across imaging conditions by comparing imaged texture features to voxel-based 3D printed textured lesions for which the true values are known. The seven features of interest were based on the Grey Level Co-Occurrence Matrix (GLCM). The lesion phantoms were designed with three shapes (spherical, lobulated, and spiculated), two textures (homogenous and heterogeneous), and two sizes (diameter < 1.5 cm and 1.5 cm < diameter < 3 cm), resulting in 24 lesions (with a second replica of each). The lesions were inserted into an anthropomorphic thorax phantom (Multipurpose Chest Phantom N1, Kyoto Kagaku) and imaged using a commercial CT system (GE Revolution) at three CTDI levels (0.67, 1.42, and 5.80 mGy), three reconstruction algorithms (FBP, IR-2, IR-4), four reconstruction kernel types (standard, soft, edge), and two slice thicknesses (0.6 mm and 5 mm). Another repeat scan was performed. Texture features from these images were extracted and compared to the ground truth feature values by percent relative error. The variability across imaging conditions was calculated by standard deviation across a certain imaging condition for all heterogeneous lesions. The results indicated that the acquisition method has a significant influence on the accuracy and variability of extracted features and as such, feature quantities are highly susceptible to imaging parameter choices. The most influential parameters were slice thickness and reconstruction kernels. Thin slice thickness and edge reconstruction kernel overall produced more accurate and more repeatable results. Some features (e.g., Contrast) were more accurately quantified under conditions that render higher spatial frequencies (e.g., thinner slice thickness and sharp kernels), while others (e.g., Homogeneity) showed more accurate quantification under conditions that render smoother images (e.g., higher dose and smoother kernels). Care should be exercised is relating texture features between cases of varied acquisition protocols, with need to cross calibration dependent on the feature of interest.

Family physicians' interests in special features of electronic publication

PubMed Central

Torre, Dario M.; Wright, Scott M.; Wilson, Renee F.; Diener-West, Marie; Bass, Eric B.

2003-01-01

Objective: Because many of the medical journals read by family physicians now have an electronic version, the authors conducted a survey to determine the interest of family physicians in specific features of electronic journal publications. Setting and Participants: We surveyed 175 family physicians randomly selected from the American Academy of Family Physicians. Results: The response rate was 63%. About half of family physicians reported good to excellent computer proficiency, and about one quarter used online journals sometimes or often. Many respondents reported high interest in having links to: an electronic medical text (48% for original articles, 56% for review articles), articles' list of references (52% for original articles, 56% for review articles), and health-related Websites (48% for original and review articles). Conclusion: Primary care–oriented journals should consider the interests of family physicians when developing and offering electronic features for their readers. PMID:12883561

The Centre for Speech, Language and the Brain (CSLB) concept property norms.

PubMed

Devereux, Barry J; Tyler, Lorraine K; Geertzen, Jeroen; Randall, Billi

2014-12-01

Theories of the representation and processing of concepts have been greatly enhanced by models based on information available in semantic property norms. This information relates both to the identity of the features produced in the norms and to their statistical properties. In this article, we introduce a new and large set of property norms that are designed to be a more flexible tool to meet the demands of many different disciplines interested in conceptual knowledge representation, from cognitive psychology to computational linguistics. As well as providing all features listed by 2 or more participants, we also show the considerable linguistic variation that underlies each normalized feature label and the number of participants who generated each variant. Our norms are highly comparable with the largest extant set (McRae, Cree, Seidenberg, & McNorgan, 2005) in terms of the number and distribution of features. In addition, we show how the norms give rise to a coherent category structure. We provide these norms in the hope that the greater detail available in the Centre for Speech, Language and the Brain norms should further promote the development of models of conceptual knowledge. The norms can be downloaded at www.csl.psychol.cam.ac.uk/propertynorms.

An intelligent framework for medical image retrieval using MDCT and multi SVM.

PubMed

Balan, J A Alex Rajju; Rajan, S Edward

2014-01-01

Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

Characterization of the major histopathological components of thyroid nodules using sonographic textural features for clinical diagnosis and management.

PubMed

Chen, Shao-Jer; Yu, Sung-Nien; Tzeng, Jeh-En; Chen, Yen-Ting; Chang, Ku-Yaw; Cheng, Kuo-Sheng; Hsiao, Fu-Tsung; Wei, Chang-Kuo

2009-02-01

In this study, the characteristic sonographic textural feature that represents the major histopathologic components of the thyroid nodules was objectively quantified to facilitate clinical diagnosis and management. A total of 157 regions-of-interest thyroid ultrasound image was recruited in the study. The sonographic system used was the GE LOGIQ 700), (General Electric Healthcare, Chalfant St. Giles, UK). The parameters affecting image acquisition were kept in the same condition for all lesions. Commonly used texture analysis methods were applied to characterize thyroid ultrasound images. Image features were classified according to the corresponding pathologic findings. To estimate their relevance and performance to classification, ReliefF was used as a feature selector. Among the various textural features, the sum average value derived from co-occurrence matrix can well reflect echogenicity and can effectively differentiate between follicles and fibrosis base thyroid nodules. Fibrosis shows lowest echogenicity and lowest difference sum average value. Enlarged follicles show highest echogenicity and difference sum average values. Papillary cancer or follicular tumors show the difference sum average values and echogenicity between. The rule of thumb for the echogenicity is that the more follicles are mixed in, the higher the echo of the follicular tumor and papillary cancer will be and vice versa for fibrosis mixed. Areas with intermediate and lower echo should address the possibility of follicular or papillary neoplasm mixed with either follicles or fibrosis. These areas provide more cellular information for ultrasound guided aspiration

Medusae Fossae

NASA Technical Reports Server (NTRS)

2002-01-01

[figure removed for brevity, see original site] (Released 31 July 2002) This image crosses the equator at about 155 W longitude and shows a sample of the middle member of the Medusae Fossae formation. The layers exposed in the southeast-facing scarp suggest that there is a fairly competent unit underlying the mesa in the center of the image. Dust-avalanches are apparent in the crater depression near the middle of the image. The mesa of Medusae Fossae material has the geomorphic signatures that are typical of the formation elsewhere on Mars, but the surface is probably heavily mantled with fine dust, masking the small-scale character of the unit. The close proximity of the Medusae Fossae unit to the Tharsis region may suggest that it is an ignimbrite or volcanic airfall deposit, but it's eroded character hasn't preserved the primary depositional features that would give away the secrets of formation. One of the most interesting feature in the image is the high-standing knob at the base of the scarp in the lower portion of the image. This knob or butte is high standing because it is composed of material that is not as easily eroded as the rest of the unit. There are a number of possible explanations for this feature, including volcano, inverted crater, or some localized process that caused once friable material to become cemented. Another interesting set of features are the long troughs on the slope in the lower portion of the image. The fact that the features keep the same width for the entire length suggests that these are not simple landslides.

Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.

PubMed

Reavis, Eric A; Frank, Sebastian M; Tse, Peter U

2015-04-15

Useful information in the visual environment is often contained in specific conjunctions of visual features (e.g., color and shape). The ability to quickly and accurately process such conjunctions can be learned. However, the neural mechanisms responsible for such learning remain largely unknown. It has been suggested that some forms of visual learning might involve the dopaminergic neuromodulatory system (Roelfsema et al., 2010; Seitz and Watanabe, 2005), but this hypothesis has not yet been directly tested. Here we test the hypothesis that learning visual feature conjunctions involves the dopaminergic system, using functional neuroimaging, genetic assays, and behavioral testing techniques. We use a correlative approach to evaluate potential associations between individual differences in visual feature conjunction learning rate and individual differences in dopaminergic function as indexed by neuroimaging and genetic markers. We find a significant correlation between activity in the caudate nucleus (a component of the dopaminergic system connected to visual areas of the brain) and visual feature conjunction learning rate. Specifically, individuals who showed a larger difference in activity between positive and negative feedback on an unrelated cognitive task, indicative of a more reactive dopaminergic system, learned visual feature conjunctions more quickly than those who showed a smaller activity difference. This finding supports the hypothesis that the dopaminergic system is involved in visual learning, and suggests that visual feature conjunction learning could be closely related to associative learning. However, no significant, reliable correlations were found between feature conjunction learning and genotype or dopaminergic activity in any other regions of interest. Copyright © 2015 Elsevier Inc. All rights reserved.

Selection-for-action in visual search.

PubMed

Hannus, Aave; Cornelissen, Frans W; Lindemann, Oliver; Bekkering, Harold

2005-01-01

Grasping an object rather than pointing to it enhances processing of its orientation but not its color. Apparently, visual discrimination is selectively enhanced for a behaviorally relevant feature. In two experiments we investigated the limitations and targets of this bias. Specifically, in Experiment 1 we were interested to find out whether the effect is capacity demanding, therefore we manipulated the set-size of the display. The results indicated a clear cognitive processing capacity requirement, i.e. the magnitude of the effect decreased for a larger set size. Consequently, in Experiment 2, we investigated if the enhancement effect occurs only at the level of behaviorally relevant feature or at a level common to different features. Therefore we manipulated the discriminability of the behaviorally neutral feature (color). Again, results showed that this manipulation influenced the action enhancement of the behaviorally relevant feature. Particularly, the effect of the color manipulation on the action enhancement suggests that the action effect is more likely to bias the competition between different visual features rather than to enhance the processing of the relevant feature. We offer a theoretical account that integrates the action-intention effect within the biased competition model of visual selective attention.

Interesting features of transmission across locally periodic delta potentials

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

Dharani, M., E-mail: m-dharani@blr.amrita.edu, E-mail: mdharu@yahoo.co.in; Shastry, C. S.

2016-05-23

We study the theory of transmission of electrons through N delta potential barriers as well as wells. Some of the interesting features like the correlation between resonance peak positions and box states, number of peaks in transmission band and bound states are analyzed for locally periodic attractive, repulsive and pair of attractive and repulsive potentials.

Situation Awareness. Report of Break-Out Group 4.

DTIC Science & Technology

2006-10-01

abstraction of the objects and contents, which are displayed and analysed with a visualisation tool. To get a clear picture of the situation around you do...cities, villages etc.). It is possible for other types of information to be visualised /handled similarly for network and data analysis. A good example...interesting feature of a visualisation tool concerning reliability/uncertainty might be the possibility to show/hide uncertain information. This means that

Genome Sequence of Torulaspora delbrueckii NRRL Y-50541, Isolated from Mezcal Fermentation.

PubMed

Gomez-Angulo, Jorge; Vega-Alvarado, Leticia; Escalante-García, Zazil; Grande, Ricardo; Gschaedler-Mathis, Anne; Amaya-Delgado, Lorena; Arrizon, Javier; Sanchez-Flores, Alejandro

2015-07-23

Torulaspora delbrueckii presents metabolic features interesting for biotechnological applications (in the dairy and wine industries). Recently, the T. delbrueckii CBS 1146 genome, which has been maintained under laboratory conditions since 1970, was published. Thus, a genome of a new mezcal yeast was sequenced and characterized and showed genetic differences and a higher genome assembly quality, offering a better reference genome. Copyright © 2015 Gomez-Angulo et al.

A Silent Witness for Peace: The Case of Schoolteacher Mary Stone McDowell and America at War

ERIC Educational Resources Information Center

Howlett, Patricia; Howlett, Charles F.

2008-01-01

A 1964 television series, "Profiles in Courage," based on the late President John F. Kennedy's Pulitzer prize-winning book, featured the life of Mary Stone McDowell, a quiet, yet strong, teacher. Within peace circles, McDowell was a well-known figure. Yet what captured the interest of the show's producers was the stand she took during World War I.…

Genome Sequence of Streptococcus phocae subsp. salmonis Strain C-4T, Isolated from Atlantic Salmon (Salmo salar).

PubMed

Avendaño-Herrera, Ruben; Suarez, Rudy; Lazo, Eduardo; Bravo, Diego; Llegues, Katerina O; Romalde, Jesús L; Godoy, Marcos G

2014-12-11

Streptococcus phocae subsp. salmonis is a fish pathogen that has an important impact on the Chilean salmon industry. Here, we report the genome sequence of the type strain C-4(T) isolated from Atlantic salmon (Salmo salar), showing a number of interesting features and genes related to its possible virulence factors. Copyright © 2014 Avendaño-Herrera et al.

Construction of Polynuclear Lanthanide (Ln = Dy(III), Tb(III), and Nd(III)) Cage Complexes Using Pyridine-Pyrazole-Based Ligands: Versatile Molecular Topologies and SMM Behavior.

PubMed

Bala, Sukhen; Sen Bishwas, Mousumi; Pramanik, Bhaskar; Khanra, Sumit; Fromm, Katharina M; Poddar, Pankaj; Mondal, Raju

2015-09-08

Employment of two different pyridyl-pyrazolyl-based ligands afforded three octanuclear lanthanide(III) (Ln = Dy, Tb) cage compounds and one hexanuclear neodymium(III) coordination cage, exhibiting versatile molecular architectures including a butterfly core. Relatively less common semirigid pyridyl-pyrazolyl-based asymmetric ligand systems show an interesting trend of forming polynuclear lanthanide cage complexes with different coordination environments around the metal centers. It is noteworthy here that construction of lanthanide complex itself is a challenging task in a ligand system as soft N-donor rich as pyridyl-pyrazol. We report herein some lanthanide complexes using ligand containing only one or two O-donors compare to five N-coordinating sites. The resultant multinuclear lanthanide complexes show interesting magnetic and spectroscopic features originating from different spatial arrangements of the metal ions. Alternating current (ac) susceptibility measurements of the two dysprosium complexes display frequency- and temperature-dependent out-of-phase signals in zero and 0.5 T direct current field, a typical characteristic feature of single-molecule magnet (SMM) behavior, indicating different energy reversal barriers due to different molecular topologies. Another aspect of this work is the occurrence of the not-so-common SMM behavior of the terbium complex, further confirmed by ac susceptibility measurement.

[Recurrent nevus: Case-report about a pagetoid form occurring from a congenital nevus in infancy].

PubMed

Bompy, L; Levasseur, J; Hallier, A; Fraitag, S; Aubriot-Lorton, M-H; Bonniaud, B; Zwetyenga, N

2018-04-03

Recurrent nevus (RN) is a cutaneous benign tumour with similarities with malignant lesions. Typically, it occurs after a partial resection of commun-acquired nevus. Its incidence varies from 0.3 to 27% according to the studies. We present here a pediatric case of a pagetoid form of a recurrent nevus occurring from a congenital nevus. A congenital nevus was removed from a 9-month-old girl. Pathologists concluded to a commun-acquired nevus of complete exeresis. Two other cutaneous lesions appeared and we decided to realise a total removal. Analysis showed a recurrent nevus with some atypical histological features. No recurrence has occurred during the three post-operative of follow-up. It is an interesting case because of the occurrence of a RN after the removal of a congenital nevus in a child. Furthermore, it displayed some atypical histological features. Practicians, such as surgeons, dermatologists or pathologists, have to be aware of the risk of misdiagnosis with this lesion, which presents some similarities with SSM melanoma. It would be interesting to determinate some markers to statuate about its benign feature. There is no management recommendation about this lesion but it seems to be necessary to remove it to eliminate a malignant tumour. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Discriminative Ocular Artifact Correction for Feature Learning in EEG Analysis.

PubMed

Xinyang Li; Cuntai Guan; Haihong Zhang; Kai Keng Ang

2017-08-01

Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain-computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels available for independent component analysis based ocular artifact removal. It is even more challenging to avoid loss of the signal of interest during the artifact correction process, where the signal of interest can be multiple magnitudes weaker than the artifact. To address these issues, we propose a novel discriminative ocular artifact correction approach for feature learning in EEG analysis. Without extra ocular movement measurements, the artifact is extracted from raw EEG data, which is totally automatic and requires no visual inspection of artifacts. Then, artifact correction is optimized jointly with feature extraction by maximizing oscillatory correlations between trials from the same class and minimizing them between trials from different classes. We evaluate this approach on a real-world EEG dataset comprising 68 subjects performing cognitive tasks. The results showed that the approach is capable of not only suppressing the artifact components but also improving the discriminative power of a classifier with statistical significance. We also demonstrate that the proposed method addresses the confounding issues induced by ocular movements in cognitive EEG study.

Surveying the interest of individuals with upper limb loss in novel prosthetic control techniques.

PubMed

Engdahl, Susannah M; Christie, Breanne P; Kelly, Brian; Davis, Alicia; Chestek, Cynthia A; Gates, Deanna H

2015-06-13

Novel techniques for the control of upper limb prostheses may allow users to operate more complex prostheses than those that are currently available. Because many of these techniques are surgically invasive, it is important to understand whether individuals with upper limb loss would accept the associated risks in order to use a prosthesis. An online survey of individuals with upper limb loss was conducted. Participants read descriptions of four prosthetic control techniques. One technique was noninvasive (myoelectric) and three were invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces). Participants rated how likely they were to try each technique if it offered each of six different functional features. They also rated their general interest in each of the six features. A two-way repeated measures analysis of variance with Greenhouse-Geisser corrections was used to examine the effect of the technique type and feature on participants' interest in each technique. Responses from 104 individuals were analyzed. Many participants were interested in trying the techniques - 83 % responded positively toward myoelectric control, 63 % toward targeted muscle reinnervation, 68 % toward peripheral nerve interfaces, and 39 % toward cortical interfaces. Common concerns about myoelectric control were weight, cost, durability, and difficulty of use, while the most common concern about the invasive techniques was surgical risk. Participants expressed greatest interest in basic prosthesis features (e.g., opening and closing the hand slowly), as opposed to advanced features like fine motor control and touch sensation. The results of these investigations may be used to inform the development of future prosthetic technologies that are appealing to individuals with upper limb loss.

Understanding performance properties of chemical engines under a trade-off optimization: Low-dissipation versus endoreversible model

NASA Astrophysics Data System (ADS)

Tang, F. R.; Zhang, Rong; Li, Huichao; Li, C. N.; Liu, Wei; Bai, Long

2018-05-01

The trade-off criterion is used to systemically investigate the performance features of two chemical engine models (the low-dissipation model and the endoreversible model). The optimal efficiencies, the dissipation ratios, and the corresponding ratios of the dissipation rates for two models are analytically determined. Furthermore, the performance properties of two kinds of chemical engines are precisely compared and analyzed, and some interesting physics is revealed. Our investigations show that the certain universal equivalence between two models is within the framework of the linear irreversible thermodynamics, and their differences are rooted in the different physical contexts. Our results can contribute to a precise understanding of the general features of chemical engines.

Passion fruit-like nano-architectures: a general synthesis route

NASA Astrophysics Data System (ADS)

Cassano, D.; David, J.; Luin, S.; Voliani, V.

2017-03-01

Noble metal nanostructures have demonstrated a number of intriguing features for both medicine and catalysis. However, accumulation issues have prevented their clinical translation, while their use in catalysis has shown serious efficiency and stability hurdles. Here we introduce a simple and robust synthetic protocol for passion fruit-like nano-architectures composed by a silica shell embedding polymeric arrays of ultrasmall noble metal nanoparticles. These nano-architectures show interesting features for both oncology and catalysis. They avoid the issue of persistence in organism thanks to their fast biodegradation in renal clearable building blocks. Furthermore, their calcination results in yolk-shell structures composed by naked metal or alloy nanospheres shielded from aggregation by a silica shell.

ARC-1990-A91-2013

NASA Image and Video Library

1990-02-14

Range : 1.4 to 2 million miles These are enhanced versions of four views of Venus taken by Galileo's Solid State Imaging System. The pictures in the top row were taken about 4 and 5 days after closest approach, and those in the bottom row 6 days after closest approach, 2 hours apart. These show the faint Venusian cloud features vary clearly. A high-pass filter way applied to bring out broader global variations in tone. The bright polar hoods are a well-known feature of Venus. Of particular interest to planetary atmospheric scientists are the complex cloud patterns near the equator, in the vicinity of the bright subsolar point, where convection is most prevalent.

Passion fruit-like nano-architectures: a general synthesis route

PubMed Central

Cassano, D.; David, J.; Luin, S.; Voliani, V.

2017-01-01

Noble metal nanostructures have demonstrated a number of intriguing features for both medicine and catalysis. However, accumulation issues have prevented their clinical translation, while their use in catalysis has shown serious efficiency and stability hurdles. Here we introduce a simple and robust synthetic protocol for passion fruit-like nano-architectures composed by a silica shell embedding polymeric arrays of ultrasmall noble metal nanoparticles. These nano-architectures show interesting features for both oncology and catalysis. They avoid the issue of persistence in organism thanks to their fast biodegradation in renal clearable building blocks. Furthermore, their calcination results in yolk-shell structures composed by naked metal or alloy nanospheres shielded from aggregation by a silica shell. PMID:28256565

New displacement-based methods for optimal truss topology design

NASA Technical Reports Server (NTRS)

Bendsoe, Martin P.; Ben-Tal, Aharon; Haftka, Raphael T.

1991-01-01

Two alternate methods for maximum stiffness truss topology design are presented. The ground structure approach is used, and the problem is formulated in terms of displacements and bar areas. This large, nonconvex optimization problem can be solved by a simultaneous analysis and design approach. Alternatively, an equivalent, unconstrained, and convex problem in the displacements only can be formulated, and this problem can be solved by a nonsmooth, steepest descent algorithm. In both methods, the explicit solving of the equilibrium equations and the assembly of the global stiffness matrix are circumvented. A large number of examples have been studied, showing the attractive features of topology design as well as exposing interesting features of optimal topologies.

A graph lattice approach to maintaining and learning dense collections of subgraphs as image features.

PubMed

Saund, Eric

2013-10-01

Effective object and scene classification and indexing depend on extraction of informative image features. This paper shows how large families of complex image features in the form of subgraphs can be built out of simpler ones through construction of a graph lattice—a hierarchy of related subgraphs linked in a lattice. Robustness is achieved by matching many overlapping and redundant subgraphs, which allows the use of inexpensive exact graph matching, instead of relying on expensive error-tolerant graph matching to a minimal set of ideal model graphs. Efficiency in exact matching is gained by exploitation of the graph lattice data structure. Additionally, the graph lattice enables methods for adaptively growing a feature space of subgraphs tailored to observed data. We develop the approach in the domain of rectilinear line art, specifically for the practical problem of document forms recognition. We are especially interested in methods that require only one or very few labeled training examples per category. We demonstrate two approaches to using the subgraph features for this purpose. Using a bag-of-words feature vector we achieve essentially single-instance learning on a benchmark forms database, following an unsupervised clustering stage. Further performance gains are achieved on a more difficult dataset using a feature voting method and feature selection procedure.

Sharp low-energy feature in single-particle spectra due to forward scattering in d-wave cuprate superconductors.

PubMed

Hong, Seung Hwan; Bok, Jin Mo; Zhang, Wentao; He, Junfeng; Zhou, X J; Varma, C M; Choi, Han-Yong

2014-08-01

There is an enormous interest in the renormalization of the quasiparticle (qp) dispersion relation of cuprate superconductors both below and above the critical temperature T_{c} because it enables the determination of the fluctuation spectrum to which the qp's are coupled. A remarkable discovery by angle-resolved photoemission spectroscopy (ARPES) is a sharp low-energy feature (LEF) in qp spectra well below the superconducting energy gap but with its energy increasing in proportion to T_{c} and its intensity increasing sharply below T_{c}. This unexpected feature needs to be reconciled with d-wave superconductivity. Here, we present a quantitative analysis of ARPES data from Bi_{2}Sr_{2}CaCu_{2}O_{8+δ} (Bi2212) using Eliashberg equations to show that the qp scattering rate due to the forward scattering impurities far from the Cu-O planes is modified by the energy gap below T_{c} and shows up as the LEF. This is also a necessary step to analyze ARPES data to reveal the spectrum of fluctuations promoting superconductivity.

Comparison between flood prone areas' geomorphic features in the Abruzzo region

NASA Astrophysics Data System (ADS)

Orlando, D.; Giglioni, M.; Magnaldi, S.

2017-07-01

Flood risk maps are one of the main non-structural measures for risk mitigation, but, as the risk knowledge degree is directly proportional to the community interest and financial capability, many sites are devoid of flood inundation areas studies. Recently many authors have investigated the capability of flood prone areas individuation with geomorphological DIGITAL ELEVATION MODEL(DEM) based approaches. These approaches highlight the role of geomorphic features derived from DEM, in this case slope, curvature, elevation, and topographic wetness index, to preliminary inundated areas' identification, without using hydraulic simulations. The present studies aim to analyze the geomorphic features of different hazard levels that lie under the identified inundated areas that have been carried out by the Abruzzo Region Basin Authority. The Aterno-Pescara and Foro river basins have been investigated. The results show that the characteristics of the flooded areas can be clearly distinguished from those of the entire basin,however, the difficultly of geomorphic features in individuatingthe areas of different hazard classifications is obvious.

Automatic Spatio-Temporal Flow Velocity Measurement in Small Rivers Using Thermal Image Sequences

NASA Astrophysics Data System (ADS)

Lin, D.; Eltner, A.; Sardemann, H.; Maas, H.-G.

2018-05-01

An automatic spatio-temporal flow velocity measurement approach, using an uncooled thermal camera, is proposed in this paper. The basic principle of the method is to track visible thermal features at the water surface in thermal camera image sequences. Radiometric and geometric calibrations are firstly implemented to remove vignetting effects in thermal imagery and to get the interior orientation parameters of the camera. An object-based unsupervised classification approach is then applied to detect the interest regions for data referencing and thermal feature tracking. Subsequently, GCPs are extracted to orient the river image sequences and local hot points are identified as tracking features. Afterwards, accurate dense tracking outputs are obtained using pyramidal Lucas-Kanade method. To validate the accuracy potential of the method, measurements obtained from thermal feature tracking are compared with reference measurements taken by a propeller gauge. Results show a great potential of automatic flow velocity measurement in small rivers using imagery from a thermal camera.

Tissue classification using depth-dependent ultrasound time series analysis: in-vitro animal study

NASA Astrophysics Data System (ADS)

Imani, Farhad; Daoud, Mohammad; Moradi, Mehdi; Abolmaesumi, Purang; Mousavi, Parvin

2011-03-01

Time series analysis of ultrasound radio-frequency (RF) signals has been shown to be an effective tissue classification method. Previous studies of this method for tissue differentiation at high and clinical-frequencies have been reported. In this paper, analysis of RF time series is extended to improve tissue classification at the clinical frequencies by including novel features extracted from the time series spectrum. The primary feature examined is the Mean Central Frequency (MCF) computed for regions of interest (ROIs) in the tissue extending along the axial axis of the transducer. In addition, the intercept and slope of a line fitted to the MCF-values of the RF time series as a function of depth have been included. To evaluate the accuracy of the new features, an in vitro animal study is performed using three tissue types: bovine muscle, bovine liver, and chicken breast, where perfect two-way classification is achieved. The results show statistically significant improvements over the classification accuracies with previously reported features.

Robust Point Set Matching for Partial Face Recognition.

PubMed

Weng, Renliang; Lu, Jiwen; Tan, Yap-Peng

2016-03-01

Over the past three decades, a number of face recognition methods have been proposed in computer vision, and most of them use holistic face images for person identification. In many real-world scenarios especially some unconstrained environments, human faces might be occluded by other objects, and it is difficult to obtain fully holistic face images for recognition. To address this, we propose a new partial face recognition approach to recognize persons of interest from their partial faces. Given a pair of gallery image and probe face patch, we first detect keypoints and extract their local textural features. Then, we propose a robust point set matching method to discriminatively match these two extracted local feature sets, where both the textural information and geometrical information of local features are explicitly used for matching simultaneously. Finally, the similarity of two faces is converted as the distance between these two aligned feature sets. Experimental results on four public face data sets show the effectiveness of the proposed approach.

Applying manifold learning techniques to the CAESAR database

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Patrick, James; Arnold, Gregory; Ferrara, Matthew

2010-04-01

Understanding and organizing data is the first step toward exploiting sensor phenomenology for dismount tracking. What image features are good for distinguishing people and what measurements, or combination of measurements, can be used to classify the dataset by demographics including gender, age, and race? A particular technique, Diffusion Maps, has demonstrated the potential to extract features that intuitively make sense [1]. We want to develop an understanding of this tool by validating existing results on the Civilian American and European Surface Anthropometry Resource (CAESAR) database. This database, provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International, is a rich dataset which includes 40 traditional, anthropometric measurements of 4400 human subjects. If we could specifically measure the defining features for classification, from this database, then the future question will then be to determine a subset of these features that can be measured from imagery. This paper briefly describes the Diffusion Map technique, shows potential for dimension reduction of the CAESAR database, and describes interesting problems to be further explored.

Steerable dyadic wavelet transform and interval wavelets for enhancement of digital mammography

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Koren, Iztok; Yang, Wuhai; Taylor, Fred J.

1995-04-01

This paper describes two approaches for accomplishing interactive feature analysis by overcomplete multiresolution representations. We show quantitatively that transform coefficients, modified by an adaptive non-linear operator, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. Our results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. We design a filter bank representing a steerable dyadic wavelet transform that can be used for multiresolution analysis along arbitrary orientations. Digital mammograms are enhanced by orientation analysis performed by a steerable dyadic wavelet transform. Arbitrary regions of interest (ROI) are enhanced by Deslauriers-Dubuc interpolation representations on an interval. We demonstrate that our methods can provide radiologists with an interactive capability to support localized processing of selected (suspicion) areas (lesions). Features extracted from multiscale representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology can improve changes of early detection while requiring less time to evaluate mammograms for most patients.

A model of proto-object based saliency

PubMed Central

Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

2013-01-01

Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

Cytologic aspects of an interesting case of medullary thyroid carcinoma coexisting with Hashimoto's thyroiditis.

PubMed

Patel, Bidish K; Roy, Arun; Badhe, Bhawana A; Siddaraju, Neelaiah

2016-01-01

Among primary thyroid neoplasms, papillary thyroid carcinoma (PTC) and primary thyroid lymphoma (PTL) are known to coexist and are pathogenetically linked with Hashimoto's thyroiditis (HT). However, HT occurring in association with medullary thyroid carcinoma (MTC) is rarely documented. We report here an interesting case. A 34-year-old female with a solitary thyroid nodule underwent fine needle aspiration cytology (FNAC) that was interpreted as "MTC with admixed reactive lymphoid cells, derived possibly from a pretracheal lymph node." Total thyroidectomy specimen showed "MTC with coexisting HT." At a later stage, a follow-up FNAC from the recurrent thyroid swelling showed features consistent with HT. As an academic exercise, the initial smears on which a diagnosis of MTC was offered were reviewed to look for evidence of coexisting HT that showed scanty and patchy aggregates of reactive lymphoid cells without Hürthle cells. Our case highlights an unusual instance of MTC in concurrence with HT that can create a tricky situation for cytopathologists.

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MedlinePlus

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Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Particle on a torus knot: Constrained dynamics and semi-classical quantization in a magnetic field

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

Das, Praloy, E-mail: praloydasdurgapur@gmail.com; Pramanik, Souvik, E-mail: souvick.in@gmail.com; Ghosh, Subir, E-mail: subirghosh20@gmail.com

2016-11-15

Kinematics and dynamics of a particle moving on a torus knot poses an interesting problem as a constrained system. In the first part of the paper we have derived the modified symplectic structure or Dirac brackets of the above model in Dirac’s Hamiltonian framework, both in toroidal and Cartesian coordinate systems. This algebra has been used to study the dynamics, in particular small fluctuations in motion around a specific torus. The spatial symmetries of the system have also been studied. In the second part of the paper we have considered the quantum theory of a charge moving in a torusmore » knot in the presence of a uniform magnetic field along the axis of the torus in a semiclassical quantization framework. We exploit the Einstein–Brillouin–Keller (EBK) scheme of quantization that is appropriate for multidimensional systems. Embedding of the knot on a specific torus is inherently two dimensional that gives rise to two quantization conditions. This shows that although the system, after imposing the knot condition reduces to a one dimensional system, even then it has manifested non-planar features which shows up again in the study of fractional angular momentum. Finally we compare the results obtained from EBK (multi-dimensional) and Bohr–Sommerfeld (single dimensional) schemes. The energy levels and fractional spin depend on the torus knot parameters that specifies its non-planar features. Interestingly, we show that there can be non-planar corrections to the planar anyon-like fractional spin.« less

Informal settlement classification using point-cloud and image-based features from UAV data

NASA Astrophysics Data System (ADS)

Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

2017-03-01

Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Furthermore, it is of interest to analyse which fundamental attributes are suitable for describing these objects in different geographic locations. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. UAV datasets from informal settlements in two different countries are compared in order to identify salient features for specific objects in heterogeneous urban environments. Findings show that the integration of 2D and 3D features leads to an overall accuracy of 91.6% and 95.2% respectively for informal settlements in Kigali, Rwanda and Maldonado, Uruguay.

What Do We Learn from Binding Features? Evidence for Multilevel Feature Integration

ERIC Educational Resources Information Center

Colzato, Lorenza S.; Raffone, Antonino; Hommel, Bernhard

2006-01-01

Four experiments were conducted to investigate the relationship between the binding of visual features (as measured by their after-effects on subsequent binding) and the learning of feature-conjunction probabilities. Both binding and learning effects were obtained, but they did not interact. Interestingly, (shape-color) binding effects…

Modification in band gap of zirconium complexes

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

Sharma, Mayank, E-mail: mayank30134@gmail.com; Singh, J.; Chouhan, S.

2016-05-06

The optical properties of zirconium complexes with amino acid based Schiff bases are reported here. The zirconium complexes show interesting stereo chemical features, which are applicable in organometallic and organic synthesis as well as in catalysis. The band gaps of both Schiff bases and zirconium complexes were obtained by UV-Visible spectroscopy. It was found that the band gap of zirconium complexes has been modified after adding zirconium compound to the Schiff bases.

A Novel Recommendation System to Match College Events and Groups to Students

NASA Astrophysics Data System (ADS)

Qazanfari, K.; Youssef, A.; Keane, K.; Nelson, J.

2017-10-01

With the recent increase in data online, discovering meaningful opportunities can be time-consuming and complicated for many individuals. To overcome this data overload challenge, we present a novel text-content-based recommender system as a valuable tool to predict user interests. To that end, we develop a specific procedure to create user models and item feature-vectors, where items are described in free text. The user model is generated by soliciting from a user a few keywords and expanding those keywords into a list of weighted near-synonyms. The item feature-vectors are generated from the textual descriptions of the items, using modified tf-idf values of the users’ keywords and their near-synonyms. Once the users are modeled and the items are abstracted into feature vectors, the system returns the maximum-similarity items as recommendations to that user. Our experimental evaluation shows that our method of creating the user models and item feature-vectors resulted in higher precision and accuracy in comparison to well-known feature-vector-generating methods like Glove and Word2Vec. It also shows that stemming and the use of a modified version of tf-idf increase the accuracy and precision by 2% and 3%, respectively, compared to non-stemming and the standard tf-idf definition. Moreover, the evaluation results show that updating the user model from usage histories improves the precision and accuracy of the system. This recommender system has been developed as part of the Agnes application, which runs on iOS and Android platforms and is accessible through the Agnes website.

Effects of advertisements on smokers’ interest in trying e-cigarettes: the roles of product comparison and visual cues

PubMed Central

Pepper, Jessica K; Emery, Sherry L; Ribisl, Kurt M; Southwell, Brian G; Brewer, Noel T

2014-01-01

Introduction Electronic cigarettes (e-cigarettes) are battery-powered nicotine delivery devices that have become popular among smokers. We conducted an experiment to understand adult smokers’ responses to e-cigarette advertisements and investigate the impact of ads’ arguments and imagery. Methods A US national sample of smokers who had never tried e-cigarettes (n=3253) participated in a between-subjects experiment. Smokers viewed an online advertisement promoting e-cigarettes using one of three comparison types (emphasising similarity to regular cigarettes, differences or neither) with one of three images, for nine conditions total. Smokers then indicated their interest in trying e-cigarettes. Results Ads that emphasised differences between e-cigarettes and regular cigarettes elicited more interest than ads without comparisons (p<0.01), primarily due to claims about e-cigarettes’ lower cost, greater healthfulness and utility for smoking cessation. However, ads that emphasised the similarities of the products did not differ from ads without comparisons. Ads showing a person using an e-cigarette created more interest than ads showing a person without an e-cigarette (p<0.01). Conclusions Interest in trying e-cigarettes was highest after viewing ads with messages about differences between regular and electronic cigarettes and ads showing product use. If e-cigarettes prove to be harmful or ineffective cessation devices, regulators might restrict images of e-cigarette use in advertising, and public health messages should not emphasise differences between regular and electronic cigarettes. To inform additional regulations, future research should seek to identify what advertising messages and features appeal to youth. PMID:24935896

Trispectrum from co-dimension 2(n) Galileons

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

Fasiello, Matteo, E-mail: mrf65@case.edu

2013-12-01

A generalized theory of multi-field Galileons has been recently put forward. This model stems from the ongoing effort to embed generic Galileon theories within brane constructions. Such an approach has proved very useful in connecting interesting and essential features of these theories with geometric properties of the branes embedding. We investigate the cosmological implications of a very restrictive multi-field Galileon theory whose leading interaction is solely quartic in the scalar field π and lends itself nicely to an interesting cosmology. The bispectrum is characterized by a naturally small amplitude (f{sub NL}∼<1) and an equilateral shape-function. The trispectrum of curvature fluctuationsmore » has features which are quite distinctive with respect to their P(X,φ) counterpart. We also show that, despite an absent cubic Lagrangian in the full theory, non-Gaussianities in this model cannot produce the combination of a small bispectrum alongside with a large trispectrum. We further expand on this point to draw a lesson on what having a symmetry in the full background independent theory entails at the level of fluctuations and vice-versa.« less

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

NASA Technical Reports Server (NTRS)

Zhang, Yuhan; Lu, Dr. Thomas

2010-01-01

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

Person-independent facial expression analysis by fusing multiscale cell features

NASA Astrophysics Data System (ADS)

Zhou, Lubing; Wang, Han

2013-03-01

Automatic facial expression recognition is an interesting and challenging task. To achieve satisfactory accuracy, deriving a robust facial representation is especially important. A novel appearance-based feature, the multiscale cell local intensity increasing patterns (MC-LIIP), to represent facial images and conduct person-independent facial expression analysis is presented. The LIIP uses a decimal number to encode the texture or intensity distribution around each pixel via pixel-to-pixel intensity comparison. To boost noise resistance, MC-LIIP carries out comparison computation on the average values of scalable cells instead of individual pixels. The facial descriptor fuses region-based histograms of MC-LIIP features from various scales, so as to encode not only textural microstructures but also the macrostructures of facial images. Finally, a support vector machine classifier is applied for expression recognition. Experimental results on the CK+ and Karolinska directed emotional faces databases show the superiority of the proposed method.

Formation of Martian Gullies by the Action of Liquid Water Flowing Under Current Martian Environmental Conditions

NASA Technical Reports Server (NTRS)

Heldmann, J. L.; Toon, O. B.; Pollard, W. H.; Mellon, M. T.; Pitlick, J.; McKay, C. P.; Andersen, D. T.

2005-01-01

Images from the Mars Orbiter Camera (MOC) on the Mars Global Surveyor (MGS) spacecraft show geologically young small-scale features resembling terrestrial water-carved gullies. An improved understanding of these features has the potential to reveal important information about the hydrological system on Mars, which is of general interest to the planetary science community as well as the field of astrobiology and the search for life on Mars. The young geologic age of these gullies is often thought to be a paradox because liquid water is unstable at the Martian surface. Current temperatures and pressures are generally below the triple point of water (273 K, 6.1 mbar) so that liquid water will spontaneously boil and/or freeze. We therefore examine the flow of water on Mars to determine what conditions are consistent with the observed features of the gullies.

Nonequilibrium critical behavior of model statistical systems and methods for the description of its features

NASA Astrophysics Data System (ADS)

Prudnikov, V. V.; Prudnikov, P. V.; Mamonova, M. V.

2017-11-01

This paper reviews features in critical behavior of far-from-equilibrium macroscopic systems and presents current methods of describing them by referring to some model statistical systems such as the three-dimensional Ising model and the two-dimensional XY model. The paper examines the critical relaxation of homogeneous and structurally disordered systems subjected to abnormally strong fluctuation effects involved in ordering processes in solids at second-order phase transitions. Interest in such systems is due to the aging properties and fluctuation-dissipation theorem violations predicted for and observed in systems slowly evolving from a nonequilibrium initial state. It is shown that these features of nonequilibrium behavior show up in the magnetic properties of magnetic superstructures consisting of alternating nanoscale-thick magnetic and nonmagnetic layers and can be observed not only near the film’s critical ferromagnetic ordering temperature Tc, but also over the wide temperature range T ⩽ Tc.

GAFFE: a gaze-attentive fixation finding engine.

PubMed

Rajashekar, U; van der Linde, I; Bovik, A C; Cormack, L K

2008-04-01

The ability to automatically detect visually interesting regions in images has many practical applications, especially in the design of active machine vision and automatic visual surveillance systems. Analysis of the statistics of image features at observers' gaze can provide insights into the mechanisms of fixation selection in humans. Using a foveated analysis framework, we studied the statistics of four low-level local image features: luminance, contrast, and bandpass outputs of both luminance and contrast, and discovered that image patches around human fixations had, on average, higher values of each of these features than image patches selected at random. Contrast-bandpass showed the greatest difference between human and random fixations, followed by luminance-bandpass, RMS contrast, and luminance. Using these measurements, we present a new algorithm that selects image regions as likely candidates for fixation. These regions are shown to correlate well with fixations recorded from human observers.

Discriminative region extraction and feature selection based on the combination of SURF and saliency

NASA Astrophysics Data System (ADS)

Deng, Li; Wang, Chunhong; Rao, Changhui

2011-08-01

The objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.

Scanning electron microscope cathodoluminescence imaging of subgrain boundaries, twins and planar deformation features in quartz

NASA Astrophysics Data System (ADS)

Hamers, M. F.; Pennock, G. M.; Drury, M. R.

2017-04-01

The study of deformation features has been of great importance to determine deformation mechanisms in quartz. Relevant microstructures in both growth and deformation processes include dislocations, subgrains, subgrain boundaries, Brazil and Dauphiné twins and planar deformation features (PDFs). Dislocations and twin boundaries are most commonly imaged using a transmission electron microscope (TEM), because these cannot directly be observed using light microscopy, in contrast to PDFs. Here, we show that red-filtered cathodoluminescence imaging in a scanning electron microscope (SEM) is a useful method to visualise subgrain boundaries, Brazil and Dauphiné twin boundaries. Because standard petrographic thin sections can be studied in the SEM, the observed structures can be directly and easily correlated to light microscopy studies. In contrast to TEM preparation methods, SEM techniques are non-destructive to the area of interest on a petrographic thin section.

Effect of Heterogeneous Interest Similarity on the Spread of Information in Mobile Social Networks

NASA Astrophysics Data System (ADS)

Zhao, Narisa; Sui, Guoqin; Yang, Fan

2018-06-01

Mobile social networks (MSNs) are important platforms for spreading news. The fact that individuals usually forward information aligned with their own interests inevitably changes the dynamics of information spread. Thereby, first we present a theoretical model based on the discrete Markov chain and mean field theory to evaluate the effect of interest similarity on the information spread in MSNs. Meanwhile, individuals' interests are heterogeneous and vary with time. These two features result in interest shift behavior, and both features are considered in our model. A leveraging simulation demonstrates the accuracy of our model. Moreover, the basic reproduction number R0 is determined. Further extensive numerical analyses based on the model indicate that interest similarity has a critical impact on information spread at the early spreading stage. Specifically, the information always spreads more quickly and widely if the interest similarity between an individual and the information is higher. Finally, five actual data sets from Sina Weibo illustrate the validity of the model.

Interest rates in quantum finance: Caps, swaptions and bond options

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.

2010-01-01

The prices of the main interest rate options in the financial markets, derived from the Libor (London Interbank Overnight Rate), are studied in the quantum finance model of interest rates. The option prices show new features for the Libor Market Model arising from the fact that, in the quantum finance formulation, all the different Libor payments are coupled and (imperfectly) correlated. Black’s caplet formula for quantum finance is given an exact path integral derivation. The coupon and zero coupon bond options as well as the Libor European and Asian swaptions are derived in the framework of quantum finance. The approximate Libor option prices are derived using the volatility expansion. The BGM-Jamshidian (Gatarek et al. (1996) [1], Jamshidian (1997) [2]) result for the Libor swaption prices is obtained as the limiting case when all the Libors are exactly correlated. A path integral derivation is given of the approximate BGM-Jamshidian approximate price.

Optimizing Radiometric Processing and Feature Extraction of Drone Based Hyperspectral Frame Format Imagery for Estimation of Yield Quantity and Quality of a Grass Sward

NASA Astrophysics Data System (ADS)

Näsi, R.; Viljanen, N.; Oliveira, R.; Kaivosoja, J.; Niemeläinen, O.; Hakala, T.; Markelin, L.; Nezami, S.; Suomalainen, J.; Honkavaara, E.

2018-04-01

Light-weight 2D format hyperspectral imagers operable from unmanned aerial vehicles (UAV) have become common in various remote sensing tasks in recent years. Using these technologies, the area of interest is covered by multiple overlapping hypercubes, in other words multiview hyperspectral photogrammetric imagery, and each object point appears in many, even tens of individual hypercubes. The common practice is to calculate hyperspectral orthomosaics utilizing only the most nadir areas of the images. However, the redundancy of the data gives potential for much more versatile and thorough feature extraction. We investigated various options of extracting spectral features in the grass sward quantity evaluation task. In addition to the various sets of spectral features, we used photogrammetry-based ultra-high density point clouds to extract features describing the canopy 3D structure. Machine learning technique based on the Random Forest algorithm was used to estimate the fresh biomass. Results showed high accuracies for all investigated features sets. The estimation results using multiview data provided approximately 10 % better results than the most nadir orthophotos. The utilization of the photogrammetric 3D features improved estimation accuracy by approximately 40 % compared to approaches where only spectral features were applied. The best estimation RMSE of 239 kg/ha (6.0 %) was obtained with multiview anisotropy corrected data set and the 3D features.

An Object-Oriented Approach for Analyzing CALIPSO's Profile Observations

NASA Astrophysics Data System (ADS)

Trepte, C. R.

2016-12-01

The CALIPSO satellite mission is a pioneering international partnership between NASA and the French Space Agency, CNES. Since launch on 28 April 2006, CALIPSO has been acquiring near-continuous lidar profile observations of clouds and aerosols in the Earth's atmosphere. Many studies have profitably used these observations to advance our understanding of climate, weather and air quality. For the most part, however, these studies have considered CALIPSO profile measurements independent from one another and have not related each to neighboring or family observations within a cloud element or aerosol feature. In this presentation we describe an alternative approach that groups measurements into objects visually identified from CALIPSO browse images. The approach makes use of the Visualization of CALIPSO (VOCAL) software tool that enables a user to outline a region of interest and save coordinates into a database. The selected features or objects can then be analyzed to explore spatial correlations over the feature's domain and construct bulk statistical properties for each structure. This presentation will show examples that examine cirrus and dust layers and will describe how this object-oriented approach can provide added insight into physical processes beyond conventional statistical treatments. It will further show results with combined measurements from other A-Train sensors to highlight advantages of viewing features in this manner.

Factors in life science textbooks that may deter girls' interest in science

NASA Astrophysics Data System (ADS)

Potter, Ellen F.; Rosser, Sue V.

In order to examine factors that may deter girls' interest in science, five seventh-grade life science textbooks were analyzed for sexism in language, images, and curricular content, and for features of activities that have been found to be useful for motivating girls. Although overt sexism was not apparent, subtle forms of sexism in the selection of language, images, and curricular content were found. Activities had some features useful to girls, but other features were seldom included. Teachers may wish to use differences that were found among texts as one basis for text selection.

A delphi exercise to identify characteristic features of gout - opinions from patients and physicians, the first stage in developing new classification criteria.

PubMed

Prowse, Rebecca L; Dalbeth, Nicola; Kavanaugh, Arthur; Adebajo, Adewale O; Gaffo, Angelo L; Terkeltaub, Robert; Mandell, Brian F; Suryana, Bagus P P; Goldenstein-Schainberg, Claudia; Diaz-Torne, Cèsar; Khanna, Dinesh; Lioté, Frederic; Mccarthy, Geraldine; Kerr, Gail S; Yamanaka, Hisashi; Janssens, Hein; Baraf, Herbert F; Chen, Jiunn-Horng; Vazquez-Mellado, Janitzia; Harrold, Leslie R; Stamp, Lisa K; Van De Laar, Mart A; Janssen, Matthijs; Doherty, Michael; Boers, Maarten; Edwards, N Lawrence; Gow, Peter; Chapman, Peter; Khanna, Puja; Helliwell, Philip S; Grainger, Rebecca; Schumacher, H Ralph; Neogi, Tuhina; Jansen, Tim L; Louthrenoo, Worawit; Sivera, Francisca; Taylor, William J; Alten, Rieke

2013-04-01

To identify a comprehensive list of features that might discriminate between gout and other rheumatic musculoskeletal conditions, to be used subsequently for a case-control study to develop and test new classification criteria for gout. Two Delphi exercises were conducted using Web-based questionnaires: one with physicians from several countries who had an interest in gout and one with patients from New Zealand who had gout. Physicians rated a list of potentially discriminating features that were identified by literature review and expert opinion, and patients rated a list of features that they generated themselves. Agreement was defined by the RAND/UCLA disagreement index. Forty-four experienced physicians and 9 patients responded to all iterations. For physicians, 71 items were identified by literature review and 15 more were suggested by physicians. The physician survey showed agreement for 26 discriminatory features and 15 as not discriminatory. The patients identified 46 features of gout, for which there was agreement on 25 items as being discriminatory and 7 items as not discriminatory. Patients and physicians agreed upon several key features of gout. Physicians emphasized objective findings, imaging, and patterns of symptoms, whereas patients emphasized severity, functional results, and idiographic perception of symptoms.

Computer-aided classification of Alzheimer's disease based on support vector machine with combination of cerebral image features in MRI

NASA Astrophysics Data System (ADS)

Jongkreangkrai, C.; Vichianin, Y.; Tocharoenchai, C.; Arimura, H.; Alzheimer's Disease Neuroimaging Initiative

2016-03-01

Several studies have differentiated Alzheimer's disease (AD) using cerebral image features derived from MR brain images. In this study, we were interested in combining hippocampus and amygdala volumes and entorhinal cortex thickness to improve the performance of AD differentiation. Thus, our objective was to investigate the useful features obtained from MRI for classification of AD patients using support vector machine (SVM). T1-weighted MR brain images of 100 AD patients and 100 normal subjects were processed using FreeSurfer software to measure hippocampus and amygdala volumes and entorhinal cortex thicknesses in both brain hemispheres. Relative volumes of hippocampus and amygdala were calculated to correct variation in individual head size. SVM was employed with five combinations of features (H: hippocampus relative volumes, A: amygdala relative volumes, E: entorhinal cortex thicknesses, HA: hippocampus and amygdala relative volumes and ALL: all features). Receiver operating characteristic (ROC) analysis was used to evaluate the method. AUC values of five combinations were 0.8575 (H), 0.8374 (A), 0.8422 (E), 0.8631 (HA) and 0.8906 (ALL). Although “ALL” provided the highest AUC, there were no statistically significant differences among them except for “A” feature. Our results showed that all suggested features may be feasible for computer-aided classification of AD patients.

Analysis of iris surface features in populations of diverse ancestry

PubMed Central

Edwards, Melissa; Cha, David; Krithika, S.; Johnson, Monique; Parra, Esteban J.

2016-01-01

There are many textural elements that can be found in the human eye, including Fuchs’ crypts, Wolfflin nodules, pigment spots, contraction furrows and conjunctival melanosis. Although iris surface features have been well-studied in populations of European ancestry, the worldwide distribution of these traits is poorly understood. In this paper, we develop a new method of characterizing iris features from photographs of the iris. We then apply this method to a diverse sample of East Asian, European and South Asian ancestry. All five iris features showed significant differences in frequency between the three populations, indicating that iris features are largely population dependent. Although none of the features were correlated with each other in the East and South Asian groups, Fuchs’ crypts were significantly correlated with contraction furrows and pigment spots and contraction furrows were significantly associated with pigment spots in the European group. The genetic marker SEMA3A rs10235789 was significantly associated with Fuchs’ crypt grade in the European, East Asian and South Asian samples and a borderline association between TRAF3IP1 rs3739070 and contraction furrow grade was found in the European sample. The study of iris surface features in diverse populations may provide valuable information of forensic, biomedical and ophthalmological interest. PMID:26909168

Significance of MPEG-7 textural features for improved mass detection in mammography.

PubMed

Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

2006-01-01

The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

Different Strokes for Different Folks: How Individual Interest Moderates the Effects of Situational Factors on Task Interest

ERIC Educational Resources Information Center

Durik, Amanda M.; Harackiewicz, Judith M.

2007-01-01

Individual interest was examined as a moderator of effects of situational factors designed to catch and hold task interest. In Study 1, 96 college students learned a math technique with materials enhanced with collative features (catch) versus not. Catch promoted motivation among participants with low individual interest in math (IIM) but hampered…

Density functional theory for prediction of far-infrared vibrational frequencies: molecular crystals of astrophysical interest

NASA Astrophysics Data System (ADS)

Ennis, C.; Auchettl, R.; Appadoo, D. R. T.; Robertson, E. G.

2017-11-01

Solid-state density functional theory code has been implemented for the structure optimization of crystalline methanol, acetaldehyde and acetic acid and for the calculation of infrared frequencies. The results are compared to thin film spectra obtained from low-temperature experiments performed at the Australian Synchrotron. Harmonic frequency calculations of the internal modes calculated at the B3LYP-D3/m-6-311G(d) level shows higher deviation from infrared experiment than more advanced theory applied to the gas phase. Importantly for the solid-state, the simulation of low-frequency molecular lattice modes closely resembles the observed far-infrared features after application of a 0.92 scaling factor. This allowed experimental peaks to be assigned to specific translation and libration modes, including acetaldehyde and acetic acid lattice features for the first time. These frequency calculations have been performed without the need for supercomputing resources that are required for large molecular clusters using comparable levels of theory. This new theoretical approach will find use for the rapid characterization of intermolecular interactions and bonding in crystals, and the assignment of far-infrared spectra for crystalline samples such as pharmaceuticals and molecular ices. One interesting application may be for the detection of species of prebiotic interest on the surfaces of Kuiper-Belt and Trans-Neptunian Objects. At such locations, the three small organic molecules studied here could reside in their crystalline phase. The far-infrared spectra for their low-temperature solid phases are collected under planetary conditions, allowing us to compile and assign their most intense spectral features to assist future far-infrared surveys of icy Solar system surfaces.

Student Performance in Measuring Distance with Wavelengths in Various Settings

NASA Astrophysics Data System (ADS)

White, Gary

2015-04-01

When physics students are asked to measure the distance between two fixed locations using a pre-defined wavelength as a ruler, there is a surprising failure rate, at least partially due to the fact that the ``ruler'' to be used is not fixed in length (see ``Is a Simple Measurement Task a Roadblock to Student Understanding of Wave Phenomena?,'' by and references therein). I will show some data from introductory classes (algebra- and calculus-based) that replicate this result, and also show some interesting features when comparing a setting involving slinkies with a setting involving surface waves on water.

Three-dimensional {Co(3+)-Zn2+} and {Co(3+)-Cd2+} networks originated from carboxylate-rich building blocks: syntheses, structures, and heterogeneous catalysis.

PubMed

Kumar, Girijesh; Gupta, Rajeev

2013-10-07

The present work shows the utilization of Co(3+) complexes appended with either para- or meta-arylcarboxylic acid groups as the molecular building blocks for the construction of three-dimensional {Co(3+)-Zn(2+)} and {Co(3+)-Cd(2+)} heterobimetallic networks. The structural characterizations of these networks show several interesting features including well-defined pores and channels. These networks function as heterogeneous and reusable catalysts for the regio- and stereoselective ring-opening reactions of various epoxides and size-selective cyanation reactions of assorted aldehydes.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images.

PubMed

Rakotomamonjy, Alain; Petitjean, Caroline; Salaün, Mathieu; Thiberville, Luc

2014-06-01

To assess the feasibility of lung cancer diagnosis using fibered confocal fluorescence microscopy (FCFM) imaging technique and scattering features for pattern recognition. FCFM imaging technique is a new medical imaging technique for which interest has yet to be established for diagnosis. This paper addresses the problem of lung cancer detection using FCFM images and, as a first contribution, assesses the feasibility of computer-aided diagnosis through these images. Towards this aim, we have built a pattern recognition scheme which involves a feature extraction stage and a classification stage. The second contribution relies on the features used for discrimination. Indeed, we have employed the so-called scattering transform for extracting discriminative features, which are robust to small deformations in the images. We have also compared and combined these features with classical yet powerful features like local binary patterns (LBP) and their variants denoted as local quinary patterns (LQP). We show that scattering features yielded to better recognition performances than classical features like LBP and their LQP variants for the FCFM image classification problems. Another finding is that LBP-based and scattering-based features provide complementary discriminative information and, in some situations, we empirically establish that performance can be improved when jointly using LBP, LQP and scattering features. In this work we analyze the joint capability of FCFM images and scattering features for lung cancer diagnosis. The proposed method achieves a good recognition rate for such a diagnosis problem. It also performs well when used in conjunction with other features for other classical medical imaging classification problems. Copyright © 2014 Elsevier B.V. All rights reserved.

Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.

PubMed

Venkataraman, Vinay; Turaga, Pavan

2016-12-01

This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

Integration of real time kinematic satellite navigation with ground-penetrating radar surveys

USDA-ARS?s Scientific Manuscript database

Precision agriculture, environmental mapping, and construction benefit from subsurface imaging by revealing the spatial variability of underground features. Features surveyed of agricultural interest are bedrock depth, soil horizon thicknesses, and buried–object features such as drainage pipe. For t...

WiFi-based person identification

NASA Astrophysics Data System (ADS)

Yuan, Jing

2016-10-01

There has been increased interest in WIFI devices equipped with multiple antennas, which brings various wireless sensing applications such as localization, gesture identification and motion tracking. WIFI-based sensing has a lot of benefits such as device Free, which has shown great potential in smart scenarios. In this paper, we present WIP, a system that can distinguish a person from a small group of people. We prove that Channel State Information (CSI) can identify a person's gait. From the related-work, different people have different gait features. Thus the CSI-based gait features can be used to identify a person. We then proposed a machine-learning model-ANN to classify different person. The results show that ANN has a good performance in our scenario.

Risky forward interest rates and swaptions: Quantum finance model and empirical results

NASA Astrophysics Data System (ADS)

Baaquie, Belal Ehsan; Yu, Miao; Bhanap, Jitendra

2018-02-01

Risk free forward interest rates (Diebold and Li, 2006 [1]; Jamshidian, 1991 [2 ]) - and their realization by US Treasury bonds as the leading exemplar - have been studied extensively. In Baaquie (2010), models of risk free bonds and their forward interest rates based on the quantum field theoretic formulation of the risk free forward interest rates have been discussed, including the empirical evidence supporting these models. The quantum finance formulation of risk free forward interest rates is extended to the case of risky forward interest rates. The examples of the Singapore and Malaysian forward interest rates are used as specific cases. The main feature of the quantum finance model is that the risky forward interest rates are modeled both a) as a stand-alone case as well as b) being driven by the US forward interest rates plus a spread - having its own term structure -above the US forward interest rates. Both the US forward interest rates and the term structure for the spread are modeled by a two dimensional Euclidean quantum field. As a precursor to the evaluation of put option of the Singapore coupon bond, the quantum finance model for swaptions is tested using empirical study of swaptions for the US Dollar -showing that the model is quite accurate. A prediction for the market price of the put option for the Singapore coupon bonds is obtained. The quantum finance model is generalized to study the Malaysian case and the Malaysian forward interest rates are shown to have anomalies absent for the US and Singapore case. The model's prediction for a Malaysian interest rate swap is obtained.

SU-F-R-18: Updates to the Computational Environment for Radiological Research for Image Analysis

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

Apte, Aditya P.; Deasy, Joseph O.

2016-06-15

Purpose: To present new tools in CERR for Texture Analysis and Visualization. Method: (1) Quantitative Image Analysis: We added the ability to compute Haralick texture features based on local neighbourhood. The Texture features depend on many parameters used in their derivation. For example: (a) directionality, (b) quantization of image, (c) patch-size for the neighborhood, (d) handling of the edge voxels within the region of interest, (e) Averaging co-occurance matrix vs texture features for different directions etc. A graphical user interface was built to set these parameters and then visualize their impact on the resulting texture maps. The entire functionality wasmore » written in Matlab. Array indexing was used to speed up the texture calculation. The computation speed is very competitive with the ITK library. Moreover, our implementation works with multiple CPUs and the computation time can be further reduced by using multiple processor threads. In order to reduce the Haralick texture maps into scalar features, we propose the use of Texture Volume Histograms. This lets users make use of the entire distribution of texture values within the region of interest rather than using just the mean and the standard deviations. (2) Qualitative/Visualization tools: The derived texture maps are stored as a new scan (derived) within CERR’s planC data structure. A display that compares various scans was built to show the raw image and the derived texture maps side-by-side. These images are positionally linked and can be navigated together. CERR’s graphics handling was updated and sped-up to be compatible with the newer Matlab versions. As a result, the users can use (a) different window levels and colormaps for different viewports, (b) click-and-drag or use mouse scroll-wheel to navigate slices. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics and Outcomes modeling.« less

Genotype-environment interaction and sociology: contributions and complexities.

PubMed

Seabrook, Jamie A; Avison, William R

2010-05-01

Genotype-environment interaction (G x E) refers to situations in which genetic effects connected to a phenotype are dependent upon variability in the environment, or when genes modify an organism's sensitivity to particular environmental features. Using a typology suggested in the G x E literature, we provide an overview of recent papers that show how social context can trigger a genetic vulnerability, compensate for a genetic vulnerability, control behaviors for which a genetic vulnerability exists, and improve adaptation via proximal causes. We argue that to improve their understanding of social structure, sociologists can take advantage of research in behavior genetics by assessing the impact of within-group variance of various health outcomes and complex human behaviors that are explainable by genotype, environment and their interaction. Insights from life course sociology can aid in ensuring that the dynamic nature of the environment in G x E has been accounted for. Identification of an appropriate entry point for sociologists interested in G x E research could begin with the choice of an environmental feature of interest, a genetic factor of interest, and/or behavior of interest. Optimizing measurement in order to capture the complexity of G x E is critical. Examining the interaction between poorly measured environmental factors and well measured genetic variables will overestimate the effects of genetic variables while underestimating the effect of environmental influences, thereby distorting the interaction between genotype and environment. Although the expense of collecting environmental data is very high, reliable and precise measurement of an environmental pathogen enhances a study's statistical power. Copyright 2010 Elsevier Ltd. All rights reserved.

Complete genome sequence of Marivirga tractuosa type strain (H-43).

PubMed

Pagani, Ioanna; Chertkov, Olga; Lapidus, Alla; Lucas, Susan; Del Rio, Tijana Glavina; Tice, Hope; Copeland, Alex; Cheng, Jan-Fang; Nolan, Matt; Saunders, Elizabeth; Pitluck, Sam; Held, Brittany; Goodwin, Lynne; Liolios, Konstantinos; Ovchinikova, Galina; Ivanova, Natalia; Mavromatis, Konstantinos; Pati, Amrita; Chen, Amy; Palaniappan, Krishna; Land, Miriam; Hauser, Loren; Jeffries, Cynthia D; Detter, John C; Han, Cliff; Tapia, Roxanne; Ngatchou-Djao, Olivier D; Rohde, Manfred; Göker, Markus; Spring, Stefan; Sikorski, Johannes; Woyke, Tanja; Bristow, Jim; Eisen, Jonathan A; Markowitz, Victor; Hugenholtz, Philip; Klenk, Hans-Peter; Kyrpides, Nikos C

2011-04-29

Marivirga tractuosa (Lewin 1969) Nedashkovskaya et al. 2010 is the type species of the genus Marivirga, which belongs to the family Flammeovirgaceae. Members of this genus are of interest because of their gliding motility. The species is of interest because representative strains show resistance to several antibiotics, including gentamicin, kanamycin, neomycin, polymixin and streptomycin. This is the first complete genome sequence of a member of the family Flammeovirgaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 4,511,574 bp long chromosome and the 4,916 bp plasmid with their 3,808 protein-coding and 49 RNA genes are a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Complete genome sequence of Marivirga tractuosa type strain (H-43T)

PubMed Central

Pagani, Ioanna; Chertkov, Olga; Lapidus, Alla; Lucas, Susan; Del Rio, Tijana Glavina; Tice, Hope; Copeland, Alex; Cheng, Jan-Fang; Nolan, Matt; Saunders, Elizabeth; Pitluck, Sam; Held, Brittany; Goodwin, Lynne; Liolios, Konstantinos; Ovchinikova, Galina; Ivanova, Natalia; Mavromatis, Konstantinos; Pati, Amrita; Chen, Amy; Palaniappan, Krishna; Land, Miriam; Hauser, Loren; Jeffries, Cynthia D.; Detter, John C.; Han, Cliff; Tapia, Roxanne; Ngatchou-Djao, Olivier D.; Rohde, Manfred; Göker, Markus; Spring, Stefan; Sikorski, Johannes; Woyke, Tanja; Bristow, Jim; Eisen, Jonathan A.; Markowitz, Victor; Hugenholtz, Philip; Klenk, Hans-Peter; Kyrpides, Nikos C.

2011-01-01

Marivirga tractuosa (Lewin 1969) Nedashkovskaya et al. 2010 is the type species of the genus Marivirga, which belongs to the family Flammeovirgaceae. Members of this genus are of interest because of their gliding motility. The species is of interest because representative strains show resistance to several antibiotics, including gentamicin, kanamycin, neomycin, polymixin and streptomycin. This is the first complete genome sequence of a member of the family Flammeovirgaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 4,511,574 bp long chromosome and the 4,916 bp plasmid with their 3,808 protein-coding and 49 RNA genes are a part of the Genomic Encyclopedia of Bacteria and Archaea project. PMID:21677852

Bacterial Inclusion Bodies: Discovering Their Better Half.

PubMed

Rinas, Ursula; Garcia-Fruitós, Elena; Corchero, José Luis; Vázquez, Esther; Seras-Franzoso, Joaquin; Villaverde, Antonio

2017-09-01

Bacterial inclusion bodies (IBs) are functional, non-toxic amyloids occurring in recombinant bacteria showing analogies with secretory granules of the mammalian endocrine system. The scientific interest in these mesoscale protein aggregates has been historically masked by their status as a hurdle in recombinant protein production. However, progressive understanding of how the cell handles the quality of recombinant polypeptides and the main features of their intriguing molecular organization has stimulated the interest in inclusion bodies and spurred their use in diverse technological fields. The engineering and tailoring of IBs as functional protein particles for materials science and biomedicine is a good example of how formerly undesired bacterial byproducts can be rediscovered as promising functional materials for a broad spectrum of applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cooperative SIS epidemics can lead to abrupt outbreaks

NASA Astrophysics Data System (ADS)

Ghanbarnejad, Fakhteh; Chen, Li; Cai, Weiran; Grassberger, Peter

2015-03-01

In this paper, we study spreading of two cooperative SIS epidemics in mean field approximations and also within an agent based framework. Therefore we investigate dynamics on different topologies like Erdos-Renyi networks and regular lattices. We show that cooperativity of two diseases can lead to strongly first order outbreaks, while the dynamics still might present some scaling laws typical for second order phase transitions. We argue how topological network features might be related to this interesting hybrid behaviors.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

PubMed Central

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

2016-01-01

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

Measuring the Interestingness of Articles in a Limited User Environment Prospectus

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

Pon, Raymond K.

2007-04-18

Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to a user. For example, if the article is old or yields little new information, the article would be uninteresting. Relevancy scores do not take into account what makes an article interesting, which would vary from user to user. Although methods such as collaborative filtering have been shown to be effective in recommendation systems, in a limited user environment there are not enough users that would make collaborative filtering effective. I presentmore » a general framework for defining and measuring the ''interestingness'' of articles, called iScore, incorporating user-feedback including tracking multiple topics of interest as well as finding interesting entities or phrases in a complex relationship network. I propose and have shown the validity of the following: 1. Filtering based on only topic relevancy is insufficient for identifying interesting articles. 2. No single feature can characterize the interestingness of an article for a user. It is the combination of multiple features that yields higher quality results. For each user, these features have different degrees of usefulness for predicting interestingness. 3. Through user-feedback, a classifier can combine features to predict interestingness for the user. 4. Current evaluation corpora, such as TREC, do not capture all aspects of personalized news filtering systems necessary for system evaluation. 5. Focusing on only specific evolving user interests instead of all topics allows for more efficient resource utilization while yielding high quality recommendation results. 6. Multiple profile vectors yield significantly better results than traditional methods, such as the Rocchio algorithm, for identifying interesting articles. Additionally, the addition of tracking multiple topics as a new feature in iScore, can improve iScore's classification performance. 7. Multiple topic tracking yields better results than the best results from the last TREC adaptive filtering run. As future work, I will address the following hypothesis: Entities and the relationship among these entities using current information extraction technology can be utilized to identify entities of interest and relationships of interest, using a scheme such as PageRank. And I will address one of the following two hypotheses: 1. By addressing the multiple reading roles that a single user may have, classification results can be improved. 2. By tailoring the operating parameters of MTT, better classification results can be achieved.« less

Enclosure Transform for Interest Point Detection From Speckle Imagery.

PubMed

Yongjian Yu; Jue Wang

2017-03-01

We present a fast enclosure transform (ET) to localize complex objects of interest from speckle imagery. This approach explores the spatial confinement on regional features from a sparse image feature representation. Unrelated, broken ridge features surrounding an object are organized collaboratively, giving rise to the enclosureness of the object. Three enclosure likelihood measures are constructed, consisting of the enclosure force, potential energy, and encloser count. In the transform domain, the local maxima manifest the locations of objects of interest, for which only the intrinsic dimension is known a priori. The discrete ET algorithm is computationally efficient, being on the order of O(MN) using N measuring distances across an image of M ridge pixels. It involves easy and few parameter settings. We demonstrate and assess the performance of ET on the automatic detection of the prostate locations from supra-pubic ultrasound images. ET yields superior results in terms of positive detection rate, accuracy and coverage.

Systems and methods for predicting materials properties

DOEpatents

Ceder, Gerbrand; Fischer, Chris; Tibbetts, Kevin; Morgan, Dane; Curtarolo, Stefano

2007-11-06

Systems and methods for predicting features of materials of interest. Reference data are analyzed to deduce relationships between the input data sets and output data sets. Reference data includes measured values and/or computed values. The deduced relationships can be specified as equations, correspondences, and/or algorithmic processes that produce appropriate output data when suitable input data is used. In some instances, the output data set is a subset of the input data set, and computational results may be refined by optionally iterating the computational procedure. To deduce features of a new material of interest, a computed or measured input property of the material is provided to an equation, correspondence, or algorithmic procedure previously deduced, and an output is obtained. In some instances, the output is iteratively refined. In some instances, new features deduced for the material of interest are added to a database of input and output data for known materials.

Intelligence, Surveillance, and Reconnaissance Fusion for Coalition Operations

DTIC Science & Technology

2008-07-01

classification of the targets of interest. The MMI features extracted in this manner have two properties that provide a sound justification for...are generalizations of well- known feature extraction methods such as Principal Components Analysis (PCA) and Independent Component Analysis (ICA...augment (without degrading performance) a large class of generic fusion processes. Ontologies Classifications Feature extraction Feature analysis

Palmprint verification using Lagrangian decomposition and invariant interest points

NASA Astrophysics Data System (ADS)

Gupta, P.; Rattani, A.; Kisku, D. R.; Hwang, C. J.; Sing, J. K.

2011-06-01

This paper presents a palmprint based verification system using SIFT features and Lagrangian network graph technique. We employ SIFT for feature extraction from palmprint images whereas the region of interest (ROI) which has been extracted from wide palm texture at the preprocessing stage, is considered for invariant points extraction. Finally, identity is established by finding permutation matrix for a pair of reference and probe palm graphs drawn on extracted SIFT features. Permutation matrix is used to minimize the distance between two graphs. The propsed system has been tested on CASIA and IITK palmprint databases and experimental results reveal the effectiveness and robustness of the system.

Volunteers Help Decide Where to Point Mars Camera

NASA Image and Video Library

2015-07-22

This series of images from NASA's Mars Reconnaissance Orbiter successively zooms into "spider" features -- or channels carved in the surface in radial patterns -- in the south polar region of Mars. In a new citizen-science project, volunteers will identify features like these using wide-scale images from the orbiter. Their input will then help mission planners decide where to point the orbiter's high-resolution camera for more detailed views of interesting terrain. Volunteers will start with images from the orbiter's Context Camera (CTX), which provides wide views of the Red Planet. The first two images in this series are from CTX; the top right image zooms into a portion of the image at left. The top right image highlights the geological spider features, which are carved into the terrain in the Martian spring when dry ice turns to gas. By identifying unusual features like these, volunteers will help the mission team choose targets for the orbiter's High Resolution Imaging Science Experiment (HiRISE) camera, which can reveal more detail than any other camera ever put into orbit around Mars. The final image is this series (bottom right) shows a HiRISE close-up of one of the spider features. http://photojournal.jpl.nasa.gov/catalog/PIA19823

Effects of advertisements on smokers' interest in trying e-cigarettes: the roles of product comparison and visual cues.

PubMed

Pepper, Jessica K; Emery, Sherry L; Ribisl, Kurt M; Southwell, Brian G; Brewer, Noel T

2014-07-01

Electronic cigarettes (e-cigarettes) are battery-powered nicotine delivery devices that have become popular among smokers. We conducted an experiment to understand adult smokers' responses to e-cigarette advertisements and investigate the impact of ads' arguments and imagery. A U.S. national sample of smokers who had never tried e-cigarettes (n=3253) participated in a between-subjects experiment. Smokers viewed an online advertisement promoting e-cigarettes using one of three comparison types (emphasising similarity to regular cigarettes, differences or neither) with one of three images, for nine conditions total. Smokers then indicated their interest in trying e-cigarettes. Ads that emphasised differences between e-cigarettes and regular cigarettes elicited more interest than ads without comparisons (p<0.01), primarily due to claims about e-cigarettes' lower cost, greater healthfulness and utility for smoking cessation. However, ads that emphasised the similarities of the products did not differ from ads without comparisons. Ads showing a person using an e-cigarette created more interest than ads showing a person without an e-cigarette (p<0.01). Interest in trying e-cigarettes was highest after viewing ads with messages about differences between regular and electronic cigarettes and ads showing product use. If e-cigarettes prove to be harmful or ineffective cessation devices, regulators might restrict images of e-cigarette use in advertising, and public health messages should not emphasise differences between regular and electronic cigarettes. To inform additional regulations, future research should seek to identify what advertising messages and features appeal to youth. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Arecibo radar imagery of Mars: II. Chryse-Xanthe, polar caps, and other regions

NASA Astrophysics Data System (ADS)

Harmon, John K.; Nolan, Michael C.

2017-01-01

We conclude our radar imaging survey of Mars, which maps spatial variations in depolarized radar reflectivity using Arecibo S-band (λ12.6 cm) observations from 2005-2012. Whereas our earlier paper (Harmon et al., 2012, Arecibo radar imagery of Mars: the major volcanic provinces. Icarus 220, 990-1030) covered the volcanic regions of Tharsis, Elysium, and Amazonis, this paper includes non-volcanic regions where hydrologic and impact processes can be the dominant resurfacing agents affecting radar backscatter. Many of the more prominent and interesting radar-bright features outside the major volcanic provinces are located in and around Chryse Planitia and Xanthe Terra. These features are identified with: a basin in northeast Lunae Planum containing the combined deposits from Maja Vallis and Ganges Catena outflows; channel outwash plains in western and southern Chryse basin; plateaus bordering chasma/chaos zones, where surface modification may have resulted from hydrologic action associated with incipient chaos formation; and some bright-ejecta craters in Chryse basin, of a type otherwise rare on Mars. Dark-halo craters have also been identified in Chryse and elsewhere that are similar to those seen in the volcanic provinces. Although the cratered highlands are relatively radar-bland, they do exhibit some bright depolarized features; these include eroded crater rims, several unusual ejecta flows and impact melts, and terrain-softened plains. The rims of large impact basins (Hellas, Argyre, Isidis) show a variety of radar-bright features provisionally identified with massif slopes, erosion sediments, eroded pyroclastics, impact melts, and glacial deposits. The interiors of these basins are largely radar-dark, which is consistent with coverage by rock-free sediments. Tempe Terra and Acheron Fossae show bright features possibly associated with rift volcanism or eroded tectonic structures, and northwest Tempe Terra shows one very bright feature associated with glacial or other ice processes in the dichotomy boundary region. The first delay-Doppler images of the radar-bright features from the north and south polar icecaps are presented. Both poles show the circular polarization inversion and high reflectivity characteristic of coherent volume backscatter from relatively clean ice. The south polar feature is primarily backscatter from the residual CO2 icecap (with a lesser contribution from the polar layered deposits), whose finite optical depth probably accounts for the feature's strong S/X-band wavelength dependence. Conversely, the north polar radar feature appears to be mostly backscatter from the H2O-ice-rich polar layered deposits rather than from the thin residual H2O cap. The north polar region shows additional radar-bright features from Korolev Crater and a few other outlying circumpolar ice deposits.

Computational Models of Laryngeal Aerodynamics: Potentials and Numerical Costs.

PubMed

Sadeghi, Hossein; Kniesburges, Stefan; Kaltenbacher, Manfred; Schützenberger, Anne; Döllinger, Michael

2018-02-07

Human phonation is based on the interaction between tracheal airflow and laryngeal dynamics. This fluid-structure interaction is based on the energy exchange between airflow and vocal folds. Major challenges in analyzing the phonatory process in-vivo are the small dimensions and the poor accessibility of the region of interest. For improved analysis of the phonatory process, numerical simulations of the airflow and the vocal fold dynamics have been suggested. Even though most of the models reproduced the phonatory process fairly well, development of comprehensive larynx models is still a subject of research. In the context of clinical application, physiological accuracy and computational model efficiency are of great interest. In this study, a simple numerical larynx model is introduced that incorporates the laryngeal fluid flow. It is based on a synthetic experimental model with silicone vocal folds. The degree of realism was successively increased in separate computational models and each model was simulated for 10 oscillation cycles. Results show that relevant features of the laryngeal flow field, such as glottal jet deflection, develop even when applying rather simple static models with oscillating flow rates. Including further phonatory components such as vocal fold motion, mucosal wave propagation, and ventricular folds, the simulations show phonatory key features like intraglottal flow separation and increased flow rate in presence of ventricular folds. The simulation time on 100 CPU cores ranged between 25 and 290 hours, currently restricting clinical application of these models. Nevertheless, results show high potential of numerical simulations for better understanding of phonatory process. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

PubMed Central

Gajic, Dragoljub; Djurovic, Zeljko; Gligorijevic, Jovan; Di Gennaro, Stefano; Savic-Gajic, Ivana

2015-01-01

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved. PMID:25852534

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

Wang, Shaobu; Lu, Shuai; Zhou, Ning

In interconnected power systems, dynamic model reduction can be applied on generators outside the area of interest to mitigate the computational cost with transient stability studies. This paper presents an approach of deriving the reduced dynamic model of the external area based on dynamic response measurements, which comprises of three steps, dynamic-feature extraction, attribution and reconstruction (DEAR). In the DEAR approach, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highestmore » similarity, forming a suboptimal ‘basis’ of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original external system. Network model is un-changed in the DEAR method. Tests on several IEEE standard systems show that the proposed method gets better reduction ratio and response errors than the traditional coherency aggregation methods.« less

Perceived Importance of Wellness Features at a Cancer Center: Patient and Staff Perspectives.

PubMed

Tinner, Michelle; Crovella, Paul; Rosenbaum, Paula F

2018-01-01

Determine the relative impact of 11 building wellness features on preference and on the ability to deliver/receive quality care for two groups: patients and caregivers. The impact of building features that promote wellness is of increasing interest to the building owners, designers, and occupants. This study performed a postoccupancy evaluation of two user groups at a healthcare facility with specific wellness features. Seventy-six staff and 62 patients of a cancer center were polled separately to determine their preferences in 11 categories. Results showed that all wellness features were viewed favorably by the two groups, with natural lighting, views of nature, and thermal comfort as top categories for both. The t-test comparisons were performed, and significant differences ( p < .05) between the two groups were found for three of the features (views of nature, art and murals, and indoor plants). Discussion of these differences and the interaction of competing design goals (thermal comfort, views of nature, natural light, and desire for privacy) are included. Designers and owners will want to consider the preferred use of roof gardens, art and murals, and indoor plants for patient spaces, where their relative value is greater. Access to private and quiet spaces is the top need for caregivers. Ease of movement, thermal comfort, and natural light were top needs for patients.

Digital auscultation analysis for heart murmur detection.

PubMed

Delgado-Trejos, Edilson; Quiceno-Manrique, A F; Godino-Llorente, J I; Blanco-Velasco, M; Castellanos-Dominguez, G

2009-02-01

This work presents a comparison of different approaches for the detection of murmurs from phonocardiographic signals. Taking into account the variability of the phonocardiographic signals induced by valve disorders, three families of features were analyzed: (a) time-varying & time-frequency features; (b) perceptual; and (c) fractal features. With the aim of improving the performance of the system, the accuracy of the system was tested using several combinations of the aforementioned families of parameters. In the second stage, the main components extracted from each family were combined together with the goal of improving the accuracy of the system. The contribution of each family of features extracted was evaluated by means of a simple k-nearest neighbors classifier, showing that fractal features provide the best accuracy (97.17%), followed by time-varying & time-frequency (95.28%), and perceptual features (88.7%). However, an accuracy around 94% can be reached just by using the two main features of the fractal family; therefore, considering the difficulties related to the automatic intrabeat segmentation needed for spectral and perceptual features, this scheme becomes an interesting alternative. The conclusion is that fractal type features were the most robust family of parameters (in the sense of accuracy vs. computational load) for the automatic detection of murmurs. This work was carried out using a database that contains 164 phonocardiographic recordings (81 normal and 83 records with murmurs). The database was segmented to extract 360 representative individual beats (180 per class).

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

NASA Astrophysics Data System (ADS)

Kato, Noriji; Fukui, Motofumi; Isozaki, Takashi

2009-02-01

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

Decorrelation of the true and estimated classifier errors in high-dimensional settings.

PubMed

Hanczar, Blaise; Hua, Jianping; Dougherty, Edward R

2007-01-01

The aim of many microarray experiments is to build discriminatory diagnosis and prognosis models. Given the huge number of features and the small number of examples, model validity which refers to the precision of error estimation is a critical issue. Previous studies have addressed this issue via the deviation distribution (estimated error minus true error), in particular, the deterioration of cross-validation precision in high-dimensional settings where feature selection is used to mitigate the peaking phenomenon (overfitting). Because classifier design is based upon random samples, both the true and estimated errors are sample-dependent random variables, and one would expect a loss of precision if the estimated and true errors are not well correlated, so that natural questions arise as to the degree of correlation and the manner in which lack of correlation impacts error estimation. We demonstrate the effect of correlation on error precision via a decomposition of the variance of the deviation distribution, observe that the correlation is often severely decreased in high-dimensional settings, and show that the effect of high dimensionality on error estimation tends to result more from its decorrelating effects than from its impact on the variance of the estimated error. We consider the correlation between the true and estimated errors under different experimental conditions using both synthetic and real data, several feature-selection methods, different classification rules, and three error estimators commonly used (leave-one-out cross-validation, k-fold cross-validation, and .632 bootstrap). Moreover, three scenarios are considered: (1) feature selection, (2) known-feature set, and (3) all features. Only the first is of practical interest; however, the other two are needed for comparison purposes. We will observe that the true and estimated errors tend to be much more correlated in the case of a known feature set than with either feature selection or using all features, with the better correlation between the latter two showing no general trend, but differing for different models.

The Effect of Resolution on Detecting Visually Salient Preattentive Features

DTIC Science & Technology

2015-06-01

resolutions in descending order (a–e). The plot compiles the areas of interest displayed in the images and each symbol represents 1 of the images. Data...to particular regions in a scene by highly salient 2 features, for example, the color of the flower discussed in the previous example. These...descending order (a–e). The plot compiles the areas of interest displayed in the images and each symbol represents 1 of the images. Data clusters

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography.

PubMed

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

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.

Multisensor satellite observations of meso- and submesoscale surface circulation in the Liguro-Provençal Basin

NASA Astrophysics Data System (ADS)

Karimova, Svetlana; Alvera-Azcarate, Aida

2017-04-01

Despite great efforts being paid to studying circulation of the Western Mediterranean Basin and the factors triggering bioproductivity of its marine ecosystem, the evidence provided by satellite imagery has not been fully analysed yet. In the present paper, we concentrate our attention on mesoscale and submesoscale circulation features of the Liguro-Provençal Basin captured by satellite radiometer, spectroradiometer, and radar images. Using such a dataset makes it possible to observe the circulation features from a wide spatial range, from the basin scale through mesoscale to the scales of a few kilometers. Mesoscale features in this study are being mostly observed with thermal infrared imagery retrieved by AVHRR and AATSR sensors. Special attention in the work was paid to an analysis of the data coming from a geostationary satellite, namely ones provided by SEVIRI. Due to their uniquely high temporal resolution, such imagery allows observing circulation features in their evolution. During the winter blooming events, surface circulation at meso- to submesoscales in the region of interest was additionally highlighted by images obtained in the visible range. Full spatial resolution images provided by Envisat MERIS, Sentinel-2 MSI, and Landsat TM/ETM+/OLI made the greatest contribution to this part. The smallest scales (namely submesoscale) are being observed with synthetic aperture radar (SAR) imagery provided by Envisat ASAR and Sentinel-1 SAR. During an analysis of SAR images, it was noted that there was strikingly great amount of biogenic surfactants on the water surface in the region of interest. Apparently, low biological productivity typical for the Western Mediterranean ecosystem is not a limiting factor for the formation of surfactant films seen in SAR imagery. This finding though requires further consideration in some other researches, and hereafter we just benefited from the presence of surfactants, because they behave as good tracers of surface currents. Even though the region of interest belongs to the areas with low mean eddy kinetic energy, analysis of the images listed above revealed that the Liguro-Provençal Basin was showing a surprisingly high eddy activity among submesoscale and mesoscale features. However, the typical size of eddies in this area was smaller than that in the southern part of the Western Mediterranean. The general impression retrieved from the observations performed is that the main contributors to generation of observed mesoscale vortical structures are (i) the instability of the main currents in the region of interest and especially frontal instability at the Liguro-Provençal front and (ii) instabilities caused by the coastline inhomogeneity, especially in the eastern part of the Basin. Submesoscale eddy activity seems to be developed to its full extent during the periods when the mesoscale activity in the region of interest is not so prominent. This study is supported by the University of Liege and the EU in the context of the FP7-PEOPLE-COFUND-BeIPD project. Satellite imagery is provided by the European Space Agency.

RelFinder: Revealing Relationships in RDF Knowledge Bases

NASA Astrophysics Data System (ADS)

Heim, Philipp; Hellmann, Sebastian; Lehmann, Jens; Lohmann, Steffen; Stegemann, Timo

The Semantic Web has recently seen a rise of large knowledge bases (such as DBpedia) that are freely accessible via SPARQL endpoints. The structured representation of the contained information opens up new possibilities in the way it can be accessed and queried. In this paper, we present an approach that extracts a graph covering relationships between two objects of interest. We show an interactive visualization of this graph that supports the systematic analysis of the found relationships by providing highlighting, previewing, and filtering features.

Dynamic response functions, helical gaps, and fractional charges in quantum wires

NASA Astrophysics Data System (ADS)

Meng, Tobias; Pedder, Christopher J.; Tiwari, Rakesh P.; Schmidt, Thomas L.

We show how experimentally accessible dynamic response functions can discriminate between helical gaps due to magnetic field, and helical gaps driven by electron-electron interactions (''umklapp gaps''). The latter are interesting since they feature gapped quasiparticles of fractional charge e / 2 , and - when coupled to a standard superconductor - an 8 π-Josephson effect and topological zero energy states bound to interfaces. National Research Fund, Luxembourg (ATTRACT 7556175), Deutsche Forschungsgemeinschaft (GRK 1621 and SFB 1143), Swiss National Science Foundation.

A large and aggressive fibromatosis in the axilla: a rare case report and review of the literature.

PubMed

Duan, Mingyue; Xing, Hua; Wang, Keren; Niu, Chunbo; Jiang, Chengwei; Zhang, Lijuan; Ezzat, Shereen; Zhang, Le

2018-01-01

Aggressive fibromatosis (AF) is a rare benign tumor, which occurs in the deep part of bone and muscle fibrous tissue. Clinical and pathological features can be challenging for definitive diagnosis. Here, we report a rare case of a large AF in the axilla. Interestingly, 18 F-fluorodeoxyglucose-positron emission tomography/computed tomography showed significant increase in standard uptake value. Surgical resection yielded a spindle cell tumor likely of fibromatosis origin which was positive for β-catenin expression.

Propagation dynamics for a spatially periodic integrodifference competition model

NASA Astrophysics Data System (ADS)

Wu, Ruiwen; Zhao, Xiao-Qiang

2018-05-01

In this paper, we study the propagation dynamics for a class of integrodifference competition models in a periodic habitat. An interesting feature of such a system is that multiple spreading speeds can be observed, which biologically means different species may have different spreading speeds. We show that the model system admits a single spreading speed, and it coincides with the minimal wave speed of the spatially periodic traveling waves. A set of sufficient conditions for linear determinacy of the spreading speed is also given.

Dynamics of the Brazil-Malvinas Confluence: Energy Conversions

NASA Astrophysics Data System (ADS)

Francisco, C. P. F.; da Silveira, I. C. A.; Campos, E. J. D.

2011-03-01

In this work, we investigated the mesoscale dynamics of the Brazil-Malvinas Confluence (BMC) region. Particularly, we were interested in the role of geophysical instability in the formation and development of the mesoscale features commonly observed in this region. We dynamically analyzed the results of numerical simulations of the BMC region conducted with 'Hybrid Coordinate Ocean Model' (HYCOM). We quantified the effect of barotropic and baroclinic energy conversions in the modeled flow and showed the dominance of the latter in the region.

Toward a Best-Practice Protocol for Assessment of Sensory Features in ASD

ERIC Educational Resources Information Center

Schaaf, Roseann C.; Lane, Alison E.

2015-01-01

Sensory difficulties are a commonly occurring feature of autism spectrum disorders and are now included as one manifestation of the "restricted, repetitive patterns of behavior, interests, or activities" diagnostic criteria of the DSM5 necessitating guidelines for comprehensive assessment of these features. To facilitate the development…

Speech Music Discrimination Using Class-Specific Features

DTIC Science & Technology

2004-08-01

Speech Music Discrimination Using Class-Specific Features Thomas Beierholm...between speech and music . Feature extraction is class-specific and can therefore be tailored to each class meaning that segment size, model orders...interest. Some of the applications of audio signal classification are speech/ music classification [1], acoustical environmental classification [2][3

Courseware Components and Features: Preferences of Faculty in the Human Sciences

ERIC Educational Resources Information Center

Causin, Gina Fe G.; Robertson, Lona J.; Ryan, Bill

2008-01-01

This project gathered information on the important components and features of distance education courseware identified by faculty teaching in the Great Plains Interactive Distance Education Alliance. Respondents indicated that they were most interested in features that helped with course management, allowed them to update and post course materials…

Cataract formation associated with ocular toxocariasis.

PubMed

Ahn, Seong Joon; Woo, Se Joon; Hyon, Joon Young; Park, Kyu Hyung

2013-06-01

To report the clinical features of cataracts in eyes with ocular toxocariasis. Department of Ophthalmology, Seoul National University Bundang Hosptal, Seongnam, South Korea. Retrospective observational case series. The clinical diagnosis of ocular toxocariasis was based on the following characteristic features: retinal granuloma with or without ocular inflammation and positive results in serum antibody enzyme-linked immunosorbent assay. Patients younger than 60 years who presented with a unilateral cataract and were diagnosed with ocular toxocariasis between January 2009 and January 2012 were included. Demographic and ocular examination data for all patients showing atypical cataract features were collected. All cataracts were documented with anterior segment photography. Seven of 83 patients (8.4%) presented with an atypical cataract in the eye with ocular toxocariasis only. The mean patient age was 49.7 years ± 8.3 (SD) (range 38 to 59 years). All patients had small, round, white lens opacities resembling retinal granulomas. The granuloma-like opacities were located primarily in the lens midperiphery and in the subcapsular level. The lens opacity migrated in 1 patient. Ocular toxocariasis can cause a cataract with distinctive clinical features. These cataracts show a granuloma-like opacity primarily in the posterior subcapsular level; the opacity can migrate. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2013 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

An Efficient Algorithm for Server Thermal Fault Diagnosis Based on Infrared Image

NASA Astrophysics Data System (ADS)

Liu, Hang; Xie, Ting; Ran, Jian; Gao, Shan

2017-10-01

It is essential for a data center to maintain server security and stability. Long-time overload operation or high room temperature may cause service disruption even a server crash, which would result in great economic loss for business. Currently, the methods to avoid server outages are monitoring and forecasting. Thermal camera can provide fine texture information for monitoring and intelligent thermal management in large data center. This paper presents an efficient method for server thermal fault monitoring and diagnosis based on infrared image. Initially thermal distribution of server is standardized and the interest regions of the image are segmented manually. Then the texture feature, Hu moments feature as well as modified entropy feature are extracted from the segmented regions. These characteristics are applied to analyze and classify thermal faults, and then make efficient energy-saving thermal management decisions such as job migration. For the larger feature space, the principal component analysis is employed to reduce the feature dimensions, and guarantee high processing speed without losing the fault feature information. Finally, different feature vectors are taken as input for SVM training, and do the thermal fault diagnosis after getting the optimized SVM classifier. This method supports suggestions for optimizing data center management, it can improve air conditioning efficiency and reduce the energy consumption of the data center. The experimental results show that the maximum detection accuracy is 81.5%.

Feature tracking for automated volume of interest stabilization on 4D-OCT images

NASA Astrophysics Data System (ADS)

Laves, Max-Heinrich; Schoob, Andreas; Kahrs, Lüder A.; Pfeiffer, Tom; Huber, Robert; Ortmaier, Tobias

2017-03-01

A common representation of volumetric medical image data is the triplanar view (TV), in which the surgeon manually selects slices showing the anatomical structure of interest. In addition to common medical imaging such as MRI or computed tomography, recent advances in the field of optical coherence tomography (OCT) have enabled live processing and volumetric rendering of four-dimensional images of the human body. Due to the region of interest undergoing motion, it is challenging for the surgeon to simultaneously keep track of an object by continuously adjusting the TV to desired slices. To select these slices in subsequent frames automatically, it is necessary to track movements of the volume of interest (VOI). This has not been addressed with respect to 4DOCT images yet. Therefore, this paper evaluates motion tracking by applying state-of-the-art tracking schemes on maximum intensity projections (MIP) of 4D-OCT images. Estimated VOI location is used to conveniently show corresponding slices and to improve the MIPs by calculating thin-slab MIPs. Tracking performances are evaluated on an in-vivo sequence of human skin, captured at 26 volumes per second. Among investigated tracking schemes, our recently presented tracking scheme for soft tissue motion provides highest accuracy with an error of under 2.2 voxels for the first 80 volumes. Object tracking on 4D-OCT images enables its use for sub-epithelial tracking of microvessels for image-guidance.

TGFβ signaling supports survival and metastasis of endometrial cancer cells

PubMed Central

Lei, XiuFen; Wang, Long; Yang, Junhua; Sun, Lu-Zhe

2009-01-01

The association of mutation of the transforming growth factor beta (TGFβ) type II receptor (RII) with microsatellite instability revealed a significant molecular mechanism of tumorigenesis and tumor progression in gastrointestinal carcinomas with DNA replication error. However, mutation of RII is rare in other types of carcinomas with microsatellite instability including endometrial adenocarcinoma suggesting that TGFβ receptor signaling may be necessary for tumor progression. To test this hypothesis, we abrogated TGFβ signaling with ectopic expression of a dominant-negative RII (DNRII) in human endometrial carcinoma HEC-1-A cells with microsatellite instability. Our study showed that over-expression of DNRII blocked the TGFβ signaling, inhibited anchorage-dependent and -independent growth, and stimulated apoptosis in vitro. Interestingly, the expression of DNRII expression showed little effect on tumor growth of subcutaneously inoculated cells in vivo. On the other hand, the DNRII cells showed more epithelial features whereas the control cells showed more mesenchymal features suggesting a reversal of autocrine TGFβ-induced epithelial–mesenchymal transition (EMT). Consistent with these findings, DNRII cells were much less migratory and invasive in vitro and metastatic in vivo than the control cells. Therefore, an intact TGFβ signaling pathway appears necessary for the metastatic phenotypes of this carcinoma model. PMID:20622970

Speleothems from Mawsmai and Krem Phyllut caves, Meghalaya, India: some evidences on biogenic activities

NASA Astrophysics Data System (ADS)

Baskar, Sushmitha; Baskar, R.; Lee, Natuschka; Theophilus, P. K.

2009-05-01

The Mawsmai cave and Krem Phyllut caves, East Khasi hills, Meghalaya, India has so far not yet attracted the attention of geomicrobiologists. Observations and hypotheses on the possible influence of identified microorganisms for speleothem formations in Meghalaya are reported for the first time. XRD studies identified calcite in speleothems and gypsum in cave wall deposits as the dominant minerals. SEM-EDAX showed interesting microfabric features showing strong resemblance with fossilised bacteria, calcified filaments, needle calcite and numerous nano scale calcite crystals, highly weathered and disintegrated crystals of calcite, that point towards a significant microbial influence in its genesis. Thin section petrography showed laminated stromatolitic features. The microorganisms identified by conventional isolation and further evaluation of isolates by molecular techniques include Bacillus cereus, Bacillus mycoides, Bacillus licheniformis, Micrococcus luteus, and Actinomycetes. Microscopic observations also showed unidentifiable cocci and four unidentifiable strains of CaSO4 (gypsum) precipitating bacteria. Experimental studies confirmed that these bacteria are able to precipitate calcium minerals (calcite, gypsum, minor amounts of dolomite) in the laboratory. These results allow us to postulate that species like these may contribute to active biogenic influence in the cave formations at Meghalaya.

Drifting behaviour as an alternative reproductive strategy for social insect workers

PubMed Central

Blacher, Pierre; Yagound, Boris; Lecoutey, Emmanuel; Devienne, Paul; Chameron, Stéphane; Châline, Nicolas

2013-01-01

Restricted reproduction is traditionally posited as the defining feature of eusocial insect workers. The discovery of worker reproduction in foreign colonies challenges this view and suggests that workers’ potential to pursue selfish interests may be higher than previously believed. However, whether such reproductive behaviour truly relies on a reproductive decision is still unknown. Workers’ reproductive decisions thus need to be investigated to assess the extent of workers’ reproductive options. Here, we show in the bumblebee Bombus terrestris that drifting is a distinct strategy by which fertile workers circumvent competition in their nest and reproduce in foreign colonies. By monitoring workers’ movements between colonies, we show that drifting is a remarkably dynamic behaviour, widely expressed by both fertile and infertile workers. We demonstrate that a high fertility is, however, central in determining the propensity of workers to enter foreign colonies as well as their subsequent reproduction in host colonies. Moreover, our study shows that the drifting of fertile workers reflects complex decision-making processes associated with in-nest reproductive competition. This novel finding therefore adds to our modern conception of cooperation by showing the previously overlooked importance of alternative strategies which enable workers to assert their reproductive interests. PMID:24068358

Homozygous variegate porphyria presenting with developmental and language delay in childhood.

PubMed

Pinder, V A E; Holden, S T; Deshpande, C; Siddiqui, A; Mellerio, J E; Wraige, E; Powell, A M

2013-10-01

Variegate porphyria is an autosomal dominant disorder that usually presents with photosensitivity and acute neurological crises in adulthood. It is caused by heterozygous mutations in the protoporphyrinogen oxidase gene (PPOX). A rarer variant, homozygous variegate porphyria (HVP), presents in childhood with recurrent skin blisters and scarring. More variable features of HVP are short stature, brachydactyly, nystagmus, epilepsy, developmental delay and mental retardation. We describe a child who presented with nystagmus, developmental delay and ataxia, combined with a photosensitive eruption. Analysis of porphyrins in plasma, urine and stool supported a clinical diagnosis of HVP. DNA from the patient showed that he is compound heterozygous for two novel missense mutations in the PPOX coding region: c.169G>C (p.Gly57Arg) and c.1259C>G (Pro420Arg). Interestingly, cranial magnetic resonance imaging showed an absence of myelin, a feature not previously reported in HVP, which expands the differential diagnosis of childhood hypomyelinating leucoencephalopathies. © 2013 British Association of Dermatologists.

Comparison between PRP, PRGF and PRF: lights and shadows in three similar but different protocols.

PubMed

Giannini, S; Cielo, A; Bonanome, L; Rastelli, C; Derla, C; Corpaci, F; Falisi, G

2015-01-01

The main goal of the modern surgery is to get a low invasiveness and a high rate of clinical healing: in the last years, it has been introduced the concept of a "regenerative surgery", and many techniques has been widely described in the literature. The most used are PRP, PRGF and PRF techniques. Aim of this research is to compare the three protocol of PRP, PRF and PRGF in their essential features, so to suggest to the practitioners the best blood product to use in the regenerative surgery. Among the advantages that shows the PRF, compared to PRP and PRGF, we can cite a greater simplicity of production for the absence of manipulation that leads to a reduced possibility of alteration of the protocol due to an error of the operator. The special texture of the PRF and its biological features shows clearly an interesting surgical versatility and all the characteristics that can support a faster tissues regeneration and high-quality clinical outcomes.

Satellite Image Analysis along the Kuala Selangor to Sabak Bernam Rural Tourism Routes

NASA Astrophysics Data System (ADS)

Ibrahim, I.; Zakariya, K.; Wahab, N. A.

2018-02-01

This research focuses on the analysis of land cover map using satellite imagery along the rural routes. The aim of this research is to study the landscape features that can be seen by the tourists around the rural routes. The objectives of the study are twofold: (i) to analyse the land cover types along the rural routes and (ii) to create a tourist map along the rural routes. The method adopted was to use Supervised Classification by creating multiple polygons to ensure that each information is sufficient to create appropriate spectral signatures. The finding shows that 80% of the landscape features along the Point of Interest (POI) are paddy field. According to the analysis using the indicators criteria for choosing the rural routes, this research shows that this area has the potential to be part of a tourism area because it has many historical and cultural elements that can be exposed to tourists. Future research will be a factor analysis on the significance of the criteria to rural tourism attraction.

Cheating Heisenberg: Achieving certainty in wideband spectrography

NASA Astrophysics Data System (ADS)

Fulop, Sean

2003-10-01

The spectrographic analysis of sound has been with us some 58 years, and one of the key properties of the process is the trade-off in resolution between the time and frequency dimensions in the computed graph. While spectrography has greatly advanced the development of phonetics, the uncertainty principle has always been a source of frustration to phoneticians because so many of the interesting features of speech must be observed by computing Fourier spectra over very short time frames-i.e., using a ``wideband'' spectrogram. Since the uncertainty relation between time and frequency is unbreakable, the only option for improvement is to make a new kind of spectrogram that does not graph time and frequency. An algorithm is described and demonstrated which computes a new kind of spectrogram in which Fourier transform frequency is replaced by the channelized instantaneous frequency, and time is adjusted by the local group delay. The theory behind this procedure was clarified in Nelson [J. Acoust. Soc. Am. 110, 2575-2592 (2001)]. The resulting wideband spectrograms show dramatically improved resolution of speech features, which will be demonstrated with sample figures. It is thus suggested that phoneticians should be more interested in the instantaneous frequency spectrum than in the Fourier transform.

Groups of adjacent contour segments for object detection.

PubMed

Ferrari, V; Fevrier, L; Jurie, F; Schmid, C

2008-01-01

We present a family of scale-invariant local shape features formed by chains of k connected, roughly straight contour segments (kAS), and their use for object class detection. kAS are able to cleanly encode pure fragments of an object boundary, without including nearby clutter. Moreover, they offer an attractive compromise between information content and repeatability, and encompass a wide variety of local shape structures. We also define a translation and scale invariant descriptor encoding the geometric configuration of the segments within a kAS, making kAS easy to reuse in other frameworks, for example as a replacement or addition to interest points. Software for detecting and describing kAS is released on lear.inrialpes.fr/software. We demonstrate the high performance of kAS within a simple but powerful sliding-window object detection scheme. Through extensive evaluations, involving eight diverse object classes and more than 1400 images, we 1) study the evolution of performance as the degree of feature complexity k varies and determine the best degree; 2) show that kAS substantially outperform interest points for detecting shape-based classes; 3) compare our object detector to the recent, state-of-the-art system by Dalal and Triggs [4].

Deciphering Front-Side Complex Formation in SN2 Reactions via Dynamics Mapping.

PubMed

Szabó, István; Olasz, Balázs; Czakó, Gábor

2017-07-06

Due to their importance in organic chemistry, the atomistic understanding of bimolecular nucleophilic substitution (S N 2) reactions shows exponentially growing interest. In this publication, the effect of front-side complex (FSC) formation is uncovered via quasi-classical trajectory computations combined with a novel analysis method called trajectory orthogonal projection (TOP). For both F - + CH 3 Y [Y = Cl,I] reactions, the lifetime distributions of the F - ···YCH 3 front-side complex revealed weakly trapped nucleophiles (F - ). However, only the F - + CH 3 I reaction features strongly trapped nucleophiles in the front-side region of the prereaction well. Interestingly, both back-side and front-side attack show propensity to long-lived FSC formation. Spatial distributions of the nucleophile demonstrate more prominent FSC formation in case of the F - + CH 3 I reaction compared to F - + CH 3 Cl. The presence of front-side intermediates and the broad spatial distribution in the back-side region may explain the indirect nature of the F - + CH 3 I reaction.

Rural medicine interest groups at McMaster University: a pilot study.

PubMed

Blau, Elaine M; Aird, Pamela; Dolovich, Lisa; Burns, Sheri; del Pilar-Chacon, Marie

2009-01-01

Although rural medicine interest groups (RMIGs) are prevalent in Canadian medical schools, there is little research on their contribution to rural education, training and careers. We explored 2 broad questions by means of an electronic survey to people who were RMIG participants at McMaster University from 2002 to 2007: 1) What are the experiences of undergraduate trainees in an RMIG? 2) What are the features of RMIGs that contribute to an interest in rural medicine? The survey itself contained 35 questions broken down into sections detailing demographics, involvement in RMIGs, RMIG features, core and elective experiences, careers and Canadian Resident Matching Service. Of the 63 participants who completed the survey, 13 (20.6%) were in postgraduate training and 50 (79.4%) were in undergraduate training. The mean (standard deviation) age of participants was 28.4 (6.5) years and 71.9% percent were female. Respondents indicated that rural placements had the most influence on their choice of specialty and rural interest. Of all the features and activities of the RMIG, rural medicine special events contributed the most to an interest in rural medicine (e.g., "rural medicine days"). At McMaster University, the responses of participants suggested that RMIG participation had more influence on career choice than did the medical school attended. Communities, government organizations, residency programs and others interested in improving access to rural physicians, will note the importance of RMIGs and the importance survey respondents gave to rural medicine special events and rural electives.

Earth observations during STS-58

NASA Image and Video Library

1993-10-22

STS058-88-017 (18 Oct-1 Nov 1993) --- The eye-catching "bullseye" of the Richat Structure adds interest to the barren Gres de Chinguetti Plateau in central Mauretania, northwest Africa. It represents domally uplifted, layered (sedimentary) rocks that have been eroded by water and wind into the present shape. Desert sands have invaded the feature from the south. The origin of the structure is unknown. It is not an impact structure, because field work showed that strata are undisturbed and flat-lying in the middle of the feature, and no shock-altered rock could be found. There is no evidence for a salt dome or shale diapir, nor is there any geophysical evidence for an underlying dome of dense igneous rock having about the same density as the sedimentary layers.

Mutual information-based facial expression recognition

NASA Astrophysics Data System (ADS)

Hazar, Mliki; Hammami, Mohamed; Hanêne, Ben-Abdallah

2013-12-01

This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.

First-principles investigation of structural, elastic, lattice dynamical and thermodynamic properties of lithium sulfur under pressure

NASA Astrophysics Data System (ADS)

Saib, S.; Bouarissa, N.

2017-10-01

In this study we report on the influence of hydrostatic pressure on structural, elastic, lattice dynamical and thermal properties of Li2S in the anti-fluorite structure using ab initio pseudopotential approach based on the density functional perturbation theory. Our results are found to be in good agreement with those existing in the literature. The present phonon dispersion spectra, dielectric constants and Born effective charges may be seen as the first investigation for the material under load. The pressure dependence of all features of interest has been examined and discussed. Besides, the temperature dependence of the lattice parameter and bulk modulus is predicted. The generalized elastic stability criteria showed that the material of interest is mechanically unstable for pressures beyond 55 GPa.

Motion-seeded object-based attention for dynamic visual imagery

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak; Kim, Kyungnam

2017-05-01

This paper† describes a novel system that finds and segments "objects of interest" from dynamic imagery (video) that (1) processes each frame using an advanced motion algorithm that pulls out regions that exhibit anomalous motion, and (2) extracts the boundary of each object of interest using a biologically-inspired segmentation algorithm based on feature contours. The system uses a series of modular, parallel algorithms, which allows many complicated operations to be carried out by the system in a very short time, and can be used as a front-end to a larger system that includes object recognition and scene understanding modules. Using this method, we show 90% accuracy with fewer than 0.1 false positives per frame of video, which represents a significant improvement over detection using a baseline attention algorithm.

Complex correlation approach for high frequency financial data

NASA Astrophysics Data System (ADS)

Wilinski, Mateusz; Ikeda, Yuichi; Aoyama, Hideaki

2018-02-01

We propose a novel approach that allows the calculation of a Hilbert transform based complex correlation for unevenly spaced data. This method is especially suitable for high frequency trading data, which are of a particular interest in finance. Its most important feature is the ability to take into account lead-lag relations on different scales, without knowing them in advance. We also present results obtained with this approach while working on Tokyo Stock Exchange intraday quotations. We show that individual sectors and subsectors tend to form important market components which may follow each other with small but significant delays. These components may be recognized by analysing eigenvectors of complex correlation matrix for Nikkei 225 stocks. Interestingly, sectorial components are also found in eigenvectors corresponding to the bulk eigenvalues, traditionally treated as noise.

Near-Infrared [Fe II] and H2 Study of the Galactic Supernova Remnants

NASA Astrophysics Data System (ADS)

Lee, Yong-Hyun; Koo, Bon-Chul; Lee, Jae-Joon; Jaffe, Daniel T.; Burton, Michael G.; Ryder, Stuart D.

2018-01-01

We have searched for near-infrared (NIR) [Fe II] (1.644 μm) and H2 1-0 S(1) (2.122 μm) emission features associated with Galactic supernova remnants (SNRs) using the narrow-band imaging surveys UWIFE / UWISH2 (UKIRT Widefield Infrared Survey for [Fe II] / H2). Both surveys cover about 180 square degrees of the first Galactic quadrant (7° < l < 65° -1.3° < b < +1.3°), and a total of 79 SNRs are falling in the survey area. We have found 19 [Fe II]- and 19 H2-emitting SNRs, giving a detection rate of 24%. Eleven SNRs show both emission features. Some of the SNRs show bright, complex, and interesting structures that have never been reported in previous studies. The brightest SNR in the both emission is W49B, contributing ~70% of the total [Fe II] luminosity of the detected SNRs. The total [Fe II] luminosity, however, is considerably less than what we would expect from the SN rate of our Galaxy.Among the SNRs showing both [Fe II] and H2 emission lines, some SNRs show the “[Fe II]-H2 reversal” phenomenon, i.e., the H2 emission features are detected outside the [Fe II] emission boundary. We carried out high resolution (R~40,000) NIR H- and K-band spectroscopy of the five SNRs showing the [Fe II]-H2 reversal (G11.2-0.3, KES 73, W44, 3C 396, W49B) using IGRINS (Immersion GRating INfrared Spectrograph). Various ro-vibrational H2 lines have been detected, which are used to derive the kinematic distances to the SNRs and to investigate the origin of the H2 emission. The detected H2 lines show broad line width (> 10 km s-1) and line flux ratios of thermal excitation. We discuss the origin of the extended H2 emission features beyond the the [Fe II] emission boundary.

Process- and Domain-Specificity in Regions Engaged for Face Processing: An fMRI Study of Perceptual Differentiation

PubMed Central

Collins, Heather R.; Zhu, Xun; Bhatt, Ramesh S.; Clark, Jonathan D.; Joseph, Jane E.

2015-01-01

The degree to which face-specific brain regions are specialized for different kinds of perceptual processing is debated. The present study parametrically varied demands on featural, first-order configural or second-order configural processing of faces and houses in a perceptual matching task to determine the extent to which the process of perceptual differentiation was selective for faces regardless of processing type (domain-specific account), specialized for specific types of perceptual processing regardless of category (process-specific account), engaged in category-optimized processing (i.e., configural face processing or featural house processing) or reflected generalized perceptual differentiation (i.e. differentiation that crosses category and processing type boundaries). Regions of interest were identified in a separate localizer run or with a similarity regressor in the face-matching runs. The predominant principle accounting for fMRI signal modulation in most regions was generalized perceptual differentiation. Nearly all regions showed perceptual differentiation for both faces and houses for more than one processing type, even if the region was identified as face-preferential in the localizer run. Consistent with process-specificity, some regions showed perceptual differentiation for first-order processing of faces and houses (right fusiform face area and occipito-temporal cortex, and right lateral occipital complex), but not for featural or second-order processing. Somewhat consistent with domain-specificity, the right inferior frontal gyrus showed perceptual differentiation only for faces in the featural matching task. The present findings demonstrate that the majority of regions involved in perceptual differentiation of faces are also involved in differentiation of other visually homogenous categories. PMID:22849402

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, D. R.; van Dyk, S. D., Makowiecki, W.; Stauffer, J.; Song, I.; Ro, J.; Fajardo-Acosta, S.; Hoard, D. W.; Wachter, S.

2011-11-01

We present the Spitzer Atlas of Stellar Spectra (SASS), which includes 159 stellar spectra (5 to 32 micron; R about 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, like blue stragglers and certain pulsating variables. All the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, dominated by Hydrogen lines around A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases PAH features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Rotation invariant fast features for large-scale recognition

NASA Astrophysics Data System (ADS)

Takacs, Gabriel; Chandrasekhar, Vijay; Tsai, Sam; Chen, David; Grzeszczuk, Radek; Girod, Bernd

2012-10-01

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

A robust automated left ventricle region of interest localization technique using a cardiac cine MRI atlas

NASA Astrophysics Data System (ADS)

Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Region of interest detection is a precursor to many medical image processing and analysis applications, including segmentation, registration and other image manipulation techniques. The optimal region of interest is often selected manually, based on empirical knowledge and features of the image dataset. However, if inconsistently identified, the selected region of interest may greatly affect the subsequent image analysis or interpretation steps, in turn leading to incomplete assessment during computer-aided diagnosis or incomplete visualization or identification of the surgical targets, if employed in the context of pre-procedural planning or image-guided interventions. Therefore, the need for robust, accurate and computationally efficient region of interest localization techniques is prevalent in many modern computer-assisted diagnosis and therapy applications. Here we propose a fully automated, robust, a priori learning-based approach that provides reliable estimates of the left and right ventricle features from cine cardiac MR images. The proposed approach leverages the temporal frame-to-frame motion extracted across a range of short axis left ventricle slice images with small training set generated from les than 10% of the population. This approach is based on histogram of oriented gradients features weighted by local intensities to first identify an initial region of interest depicting the left and right ventricles that exhibits the greatest extent of cardiac motion. This region is correlated with the homologous region that belongs to the training dataset that best matches the test image using feature vector correlation techniques. Lastly, the optimal left ventricle region of interest of the test image is identified based on the correlation of known ground truth segmentations associated with the training dataset deemed closest to the test image. The proposed approach was tested on a population of 100 patient datasets and was validated against the ground truth region of interest of the test images manually annotated by experts. This tool successfully identified a mask around the LV and RV and furthermore the minimal region of interest around the LV that fully enclosed the left ventricle from all testing datasets, yielding a 98% overlap with their corresponding ground truth. The achieved mean absolute distance error between the two contours that normalized by the radius of the ground truth is 0.20 +/- 0.09.

The impact of interference on short-term memory for visual orientation.

PubMed

Rademaker, Rosanne L; Bloem, Ilona M; De Weerd, Peter; Sack, Alexander T

2015-12-01

Visual short-term memory serves as an efficient buffer for maintaining no longer directly accessible information. How robust are visual memories against interference? Memory for simple visual features has proven vulnerable to distractors containing conflicting information along the relevant stimulus dimension, leading to the idea that interacting feature-specific channels at an early stage of visual processing support memory for simple visual features. Here we showed that memory for a single randomly orientated grating was susceptible to interference from a to-be-ignored distractor grating presented midway through a 3-s delay period. Memory for the initially presented orientation became noisier when it differed from the distractor orientation, and response distributions were shifted toward the distractor orientation (by ∼3°). Interestingly, when the distractor was rendered task-relevant by making it a second memory target, memory for both retained orientations showed reduced reliability as a function of increased orientation differences between them. However, the degree to which responses to the first grating shifted toward the orientation of the task-relevant second grating was much reduced. Finally, using a dichoptic display, we demonstrated that these systematic biases caused by a consciously perceived distractor disappeared once the distractor was presented outside of participants' awareness. Together, our results show that visual short-term memory for orientation can be systematically biased by interfering information that is consciously perceived. (c) 2015 APA, all rights reserved).

Feature Tracking for High Speed AFM Imaging of Biopolymers.

PubMed

Hartman, Brett; Andersson, Sean B

2018-03-31

The scanning speed of atomic force microscopes continues to advance with some current commercial microscopes achieving on the order of one frame per second and at least one reaching 10 frames per second. Despite the success of these instruments, even higher frame rates are needed with scan ranges larger than are currently achievable. Moreover, there is a significant installed base of slower instruments that would benefit from algorithmic approaches to increasing their frame rate without requiring significant hardware modifications. In this paper, we present an experimental demonstration of high speed scanning on an existing, non-high speed instrument, through the use of a feedback-based, feature-tracking algorithm that reduces imaging time by focusing on features of interest to reduce the total imaging area. Experiments on both circular and square gratings, as well as silicon steps and DNA strands show a reduction in imaging time by a factor of 3-12 over raster scanning, depending on the parameters chosen.

Retinal identification based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform.

PubMed

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-07-18

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

PubMed Central

Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

2013-01-01

Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

3D porous polyurethanes featured by different mechanical properties: Characterization and interaction with skeletal muscle cells.

PubMed

Vannozzi, Lorenzo; Ricotti, Leonardo; Santaniello, Tommaso; Terencio, Tercio; Oropesa-Nunez, Reinier; Canale, Claudio; Borghi, Francesca; Menciassi, Arianna; Lenardi, Cristina; Gerges, Irini

2017-11-01

The fabrication of biomaterials for interaction with muscle cells has attracted significant interest in the last decades. However, 3D porous scaffolds featured by a relatively low stiffness (almost matching the natural muscle one) and highly stable in response to cyclic loadings are not available at present, in this context. This work describes 3D polyurethane-based porous scaffolds featured by different mechanical properties. Biomaterial stiffness was finely tuned by varying the cross-linking degree of the starting foam. Compression tests revealed, for the softest material formulation, stiffness values close to the ones possessed by natural skeletal muscles. The materials were also characterized in terms of local nanoindenting, rheometric properties and long-term stability through cyclic compressions, in a strain range reflecting the contraction extent of natural muscles. Preliminary in vitro tests revealed a preferential adhesion of C2C12 skeletal muscle cells over the softer, rougher and more porous structures. All the material formulations showed low cytotoxicity. Copyright © 2017 Elsevier Ltd. All rights reserved.

a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

NASA Astrophysics Data System (ADS)

Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

2017-09-01

Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

Cluster Analysis of Weighted Bipartite Networks: A New Copula-Based Approach

PubMed Central

Chessa, Alessandro; Crimaldi, Irene; Riccaboni, Massimo; Trapin, Luca

2014-01-01

In this work we are interested in identifying clusters of “positional equivalent” actors, i.e. actors who play a similar role in a system. In particular, we analyze weighted bipartite networks that describes the relationships between actors on one side and features or traits on the other, together with the intensity level to which actors show their features. We develop a methodological approach that takes into account the underlying multivariate dependence among groups of actors. The idea is that positions in a network could be defined on the basis of the similar intensity levels that the actors exhibit in expressing some features, instead of just considering relationships that actors hold with each others. Moreover, we propose a new clustering procedure that exploits the potentiality of copula functions, a mathematical instrument for the modelization of the stochastic dependence structure. Our clustering algorithm can be applied both to binary and real-valued matrices. We validate it with simulations and applications to real-world data. PMID:25303095

Automated Depression Analysis Using Convolutional Neural Networks from Speech.

PubMed

He, Lang; Cao, Cui

2018-05-28

To help clinicians to efficiently diagnose the severity of a person's depression, the affective computing community and the artificial intelligence field have shown a growing interest in designing automated systems. The speech features have useful information for the diagnosis of depression. However, manually designing and domain knowledge are still important for the selection of the feature, which makes the process labor consuming and subjective. In recent years, deep-learned features based on neural networks have shown superior performance to hand-crafted features in various areas. In this paper, to overcome the difficulties mentioned above, we propose a combination of hand-crafted and deep-learned features which can effectively measure the severity of depression from speech. In the proposed method, Deep Convolutional Neural Networks (DCNN) are firstly built to learn deep-learned features from spectrograms and raw speech waveforms. Then we manually extract the state-of-the-art texture descriptors named median robust extended local binary patterns (MRELBP) from spectrograms. To capture the complementary information within the hand-crafted features and deep-learned features, we propose joint fine-tuning layers to combine the raw and spectrogram DCNN to boost the depression recognition performance. Moreover, to address the problems with small samples, a data augmentation method was proposed. Experiments conducted on AVEC2013 and AVEC2014 depression databases show that our approach is robust and effective for the diagnosis of depression when compared to state-of-the-art audio-based methods. Copyright © 2018. Published by Elsevier Inc.

Combined texture feature analysis of segmentation and classification of benign and malignant tumour CT slices.

PubMed

Padma, A; Sukanesh, R

2013-01-01

A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.

A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

PubMed

Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

2017-06-09

Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of the Relevance of a Web-Based "Ask an Expert" Feature: StratSoy and Soy and Human Health Queries.

ERIC Educational Resources Information Center

Wool, D. L.; Kanfer, A. G.; Michaels, J.; Thompson, S.; Morris, S. A.; Hasler, C. M.

2000-01-01

A study of the "Ask an Expert" feature of StratSoy, a Web-based information system, surveyed 50 users and 48 using it for the first time. Topic areas of interest and web site features desired by respondents were identified. (JOW)

Distinctive Features of Japanese Education. NIER Occasional Paper 01/91.

ERIC Educational Resources Information Center

National Inst. for Educational Research, Tokyo (Japan).

For the past decade there has been a surge of international interest in Japanese education in the wake of its economic and technological successes. This paper discusses eight distinctive features of Japanese education, identifying their advantages and disadvantages and how they have been brought about. These eight features of Japanese schooling…

Select Features in "Sibelius 6" for Music Educators

ERIC Educational Resources Information Center

Thompson, Douglas Earl

2012-01-01

Select features of interest to music educators are spotlighted in "Sibelius 6" (version 6.2.0 build 88) and presented under three headings: (a) Worksheets, (2) Plug-Ins, and (3) Potpourri. Guidance is given for accessing these features, and the commentary suggests their application in the music education classroom. (Contains 3 figures.)

Deep learning with convolutional neural networks for EEG decoding and visualization

PubMed Central

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

An Inquiry into the Structure of Situational Interests

ERIC Educational Resources Information Center

Azevedo, Flávio S.

2018-01-01

I advance theoretically and empirically grounded arguments for broadening how we frame and understand situational interests. A situational interest refers to the short-term spike in a person's attention and participation in an activity and it is triggered in the interactions between the person and environment features (e.g., novelty and surprise).…

Past Project Expo Sites

EPA Pesticide Factsheets

This page provides information for Project Expo sites that were featured at the LMOP Conferences in 2013 and 2014. Project Expo sites were featured as being interested in identifying project partners for the development of an LFG energy project.

Textural features for radar image analysis

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

1981-01-01

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

A Review of the Content and Format of Transgender-Related Webpages

PubMed Central

Horvath, Keith J.; Iantaffi, Alex; Grey, Jeremy A.; Bockting, Walter

2013-01-01

Transgender persons represent a highly diverse group of individuals who have been historically underserved, despite being disproportionately at risk for HIV (human immunodeficiency virus) and other health conditions. Despite the need for more research on transgender health issues, no review of online transgender-related resources has been conducted. The purpose of this study was to broadly characterize (1) the types of transgender-related webpages that appear as a result of keyword searches, and (2) the extent to which webpages differ in content and format depending on whether the intended audience for the webpage was transgender individuals, health professionals, or the general population. An online search using 28 keywords yielded 204 eligible webpages, of which 58% targeted transgendered individuals, 23% targeted health professionals, and 39% targeted the general public. The highest percentage of webpages appeared to be operated and/or created by transgender individuals or groups (46%), followed by for-profit businesses (17%). The majority of mental health (80%), HIV-related (89%), and primary care (100%) webpages targeted health professionals. Although various features are available that may increase user interest in and perceived credibility of a webpage, the results show that many of these features were underutilized. There appears to be significant opportunity to develop web resources that directly target unique subgroups within the transgender community to improve their health outcomes, increase the visibility of features that increase user interest and perceived credibility of webpages, and possibly train transgender individuals to seek relevant online information. PMID:22007970

Developmental plasticity and language: A comparative perspective

PubMed Central

Griebel, Ulrike; Pepperberg, Irene; Oller, D. Kimbrough

2016-01-01

The growing field of evo-devo is increasingly demonstrating the complexity of steps involved in genetic, intracellular regulatory, and extracellular environmental control of the development of phenotypes. A key result of such work is an account for the remarkable plasticity of organismal form in many species based on relatively minor changes in regulation of highly conserved genes and genetic processes. Accounting for behavioral plasticity is of similar potential interest but has received far less attention. Of particular interest is plasticity in communication systems, where human language represents an ultimate target for research. The present paper considers plasticity of language capabilities in a comparative framework, focusing attention on examples of a remarkable fact: Whereas there exist design features of mature human language that have never been observed to occur in nonhumans in the wild, many of these features can be developed to notable extents when nonhumans are enculturated through human training (especially with intensive social interaction). These examples of enculturated developmental plasticity across extremely diverse taxa suggest, consistent with the evo-devo theme of highly conserved processes in evolution, that human language is founded in part on cognitive capabilities that are indeed ancient and that even modern humans show self-organized emergence of many language capabilities in the context of rich enculturation, built on the special social/ecological history of the hominin line. Human culture can thus be seen as a regulatory system encouraging language development in the context of a cognitive background with many highly conserved features. PMID:27003391

Developmental Plasticity and Language: A Comparative Perspective.

PubMed

Griebel, Ulrike; Pepperberg, Irene M; Oller, D Kimbrough

2016-04-01

The growing field of evo-devo is increasingly demonstrating the complexity of steps involved in genetic, intracellular regulatory, and extracellular environmental control of the development of phenotypes. A key result of such work is an account for the remarkable plasticity of organismal form in many species based on relatively minor changes in regulation of highly conserved genes and genetic processes. Accounting for behavioral plasticity is of similar potential interest but has received far less attention. Of particular interest is plasticity in communication systems, where human language represents an ultimate target for research. The present paper considers plasticity of language capabilities in a comparative framework, focusing attention on examples of a remarkable fact: Whereas there exist design features of mature human language that have never been observed to occur in non-humans in the wild, many of these features can be developed to notable extents when non-humans are enculturated through human training (especially with intensive social interaction). These examples of enculturated developmental plasticity across extremely diverse taxa suggest, consistent with the evo-devo theme of highly conserved processes in evolution, that human language is founded in part on cognitive capabilities that are indeed ancient and that even modern humans show self-organized emergence of many language capabilities in the context of rich enculturation, built on the special social/ecological history of the hominin line. Human culture can thus be seen as a regulatory system encouraging language development in the context of a cognitive background with many highly conserved features. Copyright © 2016 Cognitive Science Society, Inc.

Automated Extraction of Flow Features

NASA Technical Reports Server (NTRS)

Dorney, Suzanne (Technical Monitor); Haimes, Robert

2005-01-01

Computational Fluid Dynamics (CFD) simulations are routinely performed as part of the design process of most fluid handling devices. In order to efficiently and effectively use the results of a CFD simulation, visualization tools are often used. These tools are used in all stages of the CFD simulation including pre-processing, interim-processing, and post-processing, to interpret the results. Each of these stages requires visualization tools that allow one to examine the geometry of the device, as well as the partial or final results of the simulation. An engineer will typically generate a series of contour and vector plots to better understand the physics of how the fluid is interacting with the physical device. Of particular interest are detecting features such as shocks, re-circulation zones, and vortices (which will highlight areas of stress and loss). As the demand for CFD analyses continues to increase the need for automated feature extraction capabilities has become vital. In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like; isc-surface, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snapshot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments). Methods must be developed to abstract the feature of interest and display it in a manner that physically makes sense.

Automated Extraction of Flow Features

NASA Technical Reports Server (NTRS)

Dorney, Suzanne (Technical Monitor); Haimes, Robert

2004-01-01

Computational Fluid Dynamics (CFD) simulations are routinely performed as part of the design process of most fluid handling devices. In order to efficiently and effectively use the results of a CFD simulation, visualization tools are often used. These tools are used in all stages of the CFD simulation including pre-processing, interim-processing, and post-processing, to interpret the results. Each of these stages requires visualization tools that allow one to examine the geometry of the device, as well as the partial or final results of the simulation. An engineer will typically generate a series of contour and vector plots to better understand the physics of how the fluid is interacting with the physical device. Of particular interest are detecting features such as shocks, recirculation zones, and vortices (which will highlight areas of stress and loss). As the demand for CFD analyses continues to increase the need for automated feature extraction capabilities has become vital. In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like; iso-surface, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snapshot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for (co-processing environments). Methods must be developed to abstract the feature of interest and display it in a manner that physically makes sense.

Viewing death on television increases the appeal of advertised products.

PubMed

Dar-Nimrod, Ilan

2012-01-01

References to death abound in many television programs accessible to most people. Terror Management Theory postulates that existential anxiety, which death reminders activate, may reinforce materialistic tendencies. The current article explores the effect of a death reminder in television shows on the desirability of advertised products. Consistent with Terror Management Theory's predictions, in two studies participants show greater desire for products, which were advertised immediately following clips from programs that featured a death scene, compared with programs that did not. Cognitive accessibility of death predicted the appeal difference while changes in affect or interest in the show did not. The findings are discussed in light on affective and existential theories which make opposite predictions. Implications and future directions are considered.

Viewing Death on Television Increases the Appeal of Advertised Products

PubMed Central

DAR-NIMROD, ILAN

2012-01-01

References to death abound in many television programs accessible to most people. Terror Management Theory (TMT) postulates that existential anxiety, which death reminders activate, may reinforce materialistic tendencies. The current paper explores the effect of a death reminder in television shows on the desirability of advertised products. Consistent with TMT's predictions, in two studies participants show greater desire for products, which were advertised immediately following clips from programs that featured a death scene, compared with programs that did not. Cognitive accessibility of death predicted the appeal difference while changes in affect or interest in the show did not. The findings are discussed in light on affective and existential theories which make opposite predictions. Implications and future directions are considered. PMID:22468421

Deep learning decision fusion for the classification of urban remote sensing data

NASA Astrophysics Data System (ADS)

Abdi, Ghasem; Samadzadegan, Farhad; Reinartz, Peter

2018-01-01

Multisensor data fusion is one of the most common and popular remote sensing data classification topics by considering a robust and complete description about the objects of interest. Furthermore, deep feature extraction has recently attracted significant interest and has become a hot research topic in the geoscience and remote sensing research community. A deep learning decision fusion approach is presented to perform multisensor urban remote sensing data classification. After deep features are extracted by utilizing joint spectral-spatial information, a soft-decision made classifier is applied to train high-level feature representations and to fine-tune the deep learning framework. Next, a decision-level fusion classifies objects of interest by the joint use of sensors. Finally, a context-aware object-based postprocessing is used to enhance the classification results. A series of comparative experiments are conducted on the widely used dataset of 2014 IEEE GRSS data fusion contest. The obtained results illustrate the considerable advantages of the proposed deep learning decision fusion over the traditional classifiers.

Stimulus Dependency of Object-Evoked Responses in Human Visual Cortex: An Inverse Problem for Category Specificity

PubMed Central

Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

2012-01-01

Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200–250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components. PMID:22363479

Stimulus dependency of object-evoked responses in human visual cortex: an inverse problem for category specificity.

PubMed

Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

2012-01-01

Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200-250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components.

Personalized features for attention detection in children with Attention Deficit Hyperactivity Disorder.

PubMed

Fahimi, Fatemeh; Guan, Cuntai; Wooi Boon Goh; Kai Keng Ang; Choon Guan Lim; Tih Shih Lee

2017-07-01

Measuring attention from electroencephalogram (EEG) has found applications in the treatment of Attention Deficit Hyperactivity Disorder (ADHD). It is of great interest to understand what features in EEG are most representative of attention. Intensive research has been done in the past and it has been proven that frequency band powers and their ratios are effective features in detecting attention. However, there are still unanswered questions, like, what features in EEG are most discriminative between attentive and non-attentive states? Are these features common among all subjects or are they subject-specific and must be optimized for each subject? Using Mutual Information (MI) to perform subject-specific feature selection on a large data set including 120 ADHD children, we found that besides theta beta ratio (TBR) which is commonly used in attention detection and neurofeedback, the relative beta power and theta/(alpha+beta) (TBAR) are also equally significant and informative for attention detection. Interestingly, we found that the relative theta power (which is also commonly used) may not have sufficient discriminative information itself (it is informative only for 3.26% of ADHD children). We have also demonstrated that although these features (relative beta power, TBR and TBAR) are the most important measures to detect attention on average, different subjects have different set of most discriminative features.

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Calhoun, Vince D.

2013-01-01

Extraction of relevant features from multitask functional MRI (fMRI) data in order to identify potential biomarkers for disease, is an attractive goal. In this paper, we introduce a novel feature-based framework, which is sensitive and accurate in detecting group differences (e.g. controls vs. patients) by proposing three key ideas. First, we integrate two goal-directed techniques: coefficient-constrained independent component analysis (CC-ICA) and principal component analysis with reference (PCA-R), both of which improve sensitivity to group differences. Secondly, an automated artifact-removal method is developed for selecting components of interest derived from CC-ICA, with an average accuracy of 91%. Finally, we propose a strategy for optimal feature/component selection, aiming to identify optimal group-discriminative brain networks as well as the tasks within which these circuits are engaged. The group-discriminating performance is evaluated on 15 fMRI feature combinations (5 single features and 10 joint features) collected from 28 healthy control subjects and 25 schizophrenia patients. Results show that a feature from a sensorimotor task and a joint feature from a Sternberg working memory (probe) task and an auditory oddball (target) task are the top two feature combinations distinguishing groups. We identified three optimal features that best separate patients from controls, including brain networks consisting of temporal lobe, default mode and occipital lobe circuits, which when grouped together provide improved capability in classifying group membership. The proposed framework provides a general approach for selecting optimal brain networks which may serve as potential biomarkers of several brain diseases and thus has wide applicability in the neuroimaging research community. PMID:19457398

Integrating Dimension Reduction and Out-of-Sample Extension in Automated Classification of Ex Vivo Human Patellar Cartilage on Phase Contrast X-Ray Computed Tomography

PubMed Central

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

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns. PMID:25710875

Improved initial guess with semi-subpixel level accuracy in digital image correlation by feature-based method

NASA Astrophysics Data System (ADS)

Zhang, Yunlu; Yan, Lei; Liou, Frank

2018-05-01

The quality initial guess of deformation parameters in digital image correlation (DIC) has a serious impact on convergence, robustness, and efficiency of the following subpixel level searching stage. In this work, an improved feature-based initial guess (FB-IG) scheme is presented to provide initial guess for points of interest (POIs) inside a large region. Oriented FAST and Rotated BRIEF (ORB) features are semi-uniformly extracted from the region of interest (ROI) and matched to provide initial deformation information. False matched pairs are eliminated by the novel feature guided Gaussian mixture model (FG-GMM) point set registration algorithm, and nonuniform deformation parameters of the versatile reproducing kernel Hilbert space (RKHS) function are calculated simultaneously. Validations on simulated images and real-world mini tensile test verify that this scheme can robustly and accurately compute initial guesses with semi-subpixel level accuracy in cases with small or large translation, deformation, or rotation.

Task-induced frequency modulation features for brain-computer interfacing.

PubMed

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects' intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects' intents with an accuracy comparable to task-induced amplitude modulation. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

Homo erectus in Salkhit, Mongolia?

PubMed

Lee, Sang-Hee

2015-08-01

In 2006, a skullcap was discovered in Salkhit, Mongolia. The Salkhit skullcap has a mostly complete frontal, two partially complete parietals, and nasals. No chronometric dating has been published yet, and suggested dates range from early Middle Pleistocene to terminal Late Pleistocene. While no chronometric date has been published, the presence of archaic features has led to a potential affiliation with archaic hominin species. If it is indeed Homo erectus or archaic Homo sapiens, Salkhit implies a much earlier spread of hominins farther north and inland Asia than previously thought. In this paper, the nature of the archaic features in Salkhit is investigated. The Salkhit skullcap morphology and metrics were compared with Middle and Late Pleistocene hominin fossils from northeast Asia: Zhoukoudian Locality 1, Dali, and Zhoukoudian Upper Cave. Results show an interesting pattern: on one hand, the archaic features that Salkhit shares with the Zhoukoudian Locality 1 sample also are shared with other later hominins; on the other hand, Salkhit is different from the Middle Pleistocene materials in the same way later hominins differ from the Middle Pleistocene sample, in having a broader frontal and thinner supraorbital region. This may reflect encephalization and gracilization, a modernization trend found in many places. It is concluded that the archaic features observed in Salkhit are regionally predominant features rather than diagnostic features of an archaic species. Copyright © 2015 Elsevier GmbH. All rights reserved.

Patscanui: an intuitive web interface for searching patterns in DNA and protein data.

PubMed

Blin, Kai; Wohlleben, Wolfgang; Weber, Tilmann

2018-05-02

Patterns in biological sequences frequently signify interesting features in the underlying molecule. Many tools exist to search for well-known patterns. Less support is available for exploratory analysis, where no well-defined patterns are known yet. PatScanUI (https://patscan.secondarymetabolites.org/) provides a highly interactive web interface to the powerful generic pattern search tool PatScan. The complex PatScan-patterns are created in a drag-and-drop aware interface allowing researchers to do rapid prototyping of the often complicated patterns useful to identifying features of interest.

Observation of strong Kondo like features and co-tunnelling in superparamagnetic GdCl3 filled 1D nanomagnets

NASA Astrophysics Data System (ADS)

Ncube, S.; Coleman, C.; de Sousa, A. S.; Nie, C.; Lonchambon, P.; Flahaut, E.; Strydom, A.; Bhattacharyya, S.

2018-06-01

Filling of carbon nanotubes has been tailored over years to modify the exceptional properties of the 1-dimensional conductor for magnetic property based applications. Hence, such a system exploits the spin and charge property of the electron, analogous to a quantum conductor coupled to magnetic impurities, which poses an interesting scenario for the study of Kondo physics and related phenomena. We report on the electronic transport properties of MWNTs filled with GdCl3 nanomagnets, which clearly show the co-existence of Kondo correlation and cotunelling within the superparamagnetic limit. The Fermi liquid description of the Kondo effect and the interpolation scheme are fitted to the resistance-temperature dependence yielding the onset of the Kondo scattering temperature and a Kondo temperature for this nanocomposite, respectively. Cotunneling of conduction electrons interfering with a Kondo type interaction has been verified from the exponential decay of the intensity of the fano shaped nonzero bias anomalous conductance peaks, which also show strong resonant features observed only in GdCl3 filled MWNT devices. Hence, these features are explained in terms of magnetic coherence and spin-flip effects along with the competition between the Kondo effect and co-tunneling. This study raises a new possibility of tailoring magnetic interactions for spintronic applications in carbon nanotube systems.

DDAH2 mRNA expression is inversely associated with some cardiovascular risk-related features in healthy young adults.

PubMed

Puchau, Blanca; Hermsdorff, Helen Hermana M; Zulet, M Angeles; Martínez, J Alfredo

2009-01-01

The purpose of this study was to evaluate whether the mRNA expression profiles of three genes (PRMT1, DDAH2 and NOS3) are related to ADMA metabolism and signalling, and the potential relationships with anthropometrical, biochemical, lifestyle and inflammatory indicators in healthy young adults. An emphasis on the putative effect of different mRNA expression on cardiovascular risk-related features was paid. Anthropometrical measurements as well as lifestyle features were analyzed in 120 healthy young adults. Fasting blood samples were collected for the measurement of glucose and lipid profiles as well as the concentrations of selected inflammatory markers. Profiles of mRNA expression were assessed for PRMT1, DDAH2 and NOS3 genes from peripheral blood mononuclear cells. Regarding inflammatory biomarkers, DDAH2 was inversely associated with IL-6 and TNF-alpha. Moreover, subjects in the highest quintile of DDAH2 mRNA expression showed a reduced risk to have higher values of waist circumference, and to be more prone to show higher values of HDL-c. Interestingly, DDAH2 gene expression seemed to be related with some anthropometrical, biochemical, lifestyle and inflammatory indicators linked to cardiovascular risk in apparently healthy young adults, emerging as a potential disease marker.

An experimental pilot study of response to invalidation in young women with features of borderline personality disorder.

PubMed

Woodberry, Kristen A; Gallo, Kaitlin P; Nock, Matthew K

2008-01-15

One of the leading biosocial theories of borderline personality disorder (BPD) suggests that individuals with BPD have biologically based abnormalities in emotion regulation contributing to more intense and rapid responses to emotional stimuli, in particular, invalidation [Linehan, M.M., 1993. Cognitive-Behavioral Treatment of Borderline Personality Disorder. Guilford, New York.]. This study used a 2 by 2 experimental design to test whether young women with features of BPD actually show increased physiological arousal in response to invalidation. Twenty-three women ages 18 to 29 who endorsed high levels of BPD symptoms and 18 healthy controls were randomly assigned to hear either a validating or invalidating comment during a frustrating task. Although we found preliminary support for differential response to these stimuli in self-report of valence, we found neither self-report nor physiological evidence of hyperarousal in the BPD features group, either at baseline or in response to invalidation. Interestingly, the BPD features group reported significantly lower comfort with emotion, and comfort was significantly associated with affective valence but not arousal. We discuss implications for understanding and responding to the affective intensity of this population.

MPEG content summarization based on compressed domain feature analysis

NASA Astrophysics Data System (ADS)

Sugano, Masaru; Nakajima, Yasuyuki; Yanagihara, Hiromasa

2003-11-01

This paper addresses automatic summarization of MPEG audiovisual content on compressed domain. By analyzing semantically important low-level and mid-level audiovisual features, our method universally summarizes the MPEG-1/-2 contents in the form of digest or highlight. The former is a shortened version of an original, while the latter is an aggregation of important or interesting events. In our proposal, first, the incoming MPEG stream is segmented into shots and the above features are derived from each shot. Then the features are adaptively evaluated in an integrated manner, and finally the qualified shots are aggregated into a summary. Since all the processes are performed completely on compressed domain, summarization is achieved at very low computational cost. The experimental results show that news highlights and sports highlights in TV baseball games can be successfully extracted according to simple shot transition models. As for digest extraction, subjective evaluation proves that meaningful shots are extracted from content without a priori knowledge, even if it contains multiple genres of programs. Our method also has the advantage of generating an MPEG-7 based description such as summary and audiovisual segments in the course of summarization.

On the probability density function and characteristic function moments of image steganalysis in the log prediction error wavelet subband

NASA Astrophysics Data System (ADS)

Bao, Zhenkun; Li, Xiaolong; Luo, Xiangyang

2017-01-01

Extracting informative statistic features is the most essential technical issue of steganalysis. Among various steganalysis methods, probability density function (PDF) and characteristic function (CF) moments are two important types of features due to the excellent ability for distinguishing the cover images from the stego ones. The two types of features are quite similar in definition. The only difference is that the PDF moments are computed in the spatial domain, while the CF moments are computed in the Fourier-transformed domain. Then, the comparison between PDF and CF moments is an interesting question of steganalysis. Several theoretical results have been derived, and CF moments are proved better than PDF moments in some cases. However, in the log prediction error wavelet subband of wavelet decomposition, some experiments show that the result is opposite and lacks a rigorous explanation. To solve this problem, a comparison result based on the rigorous proof is presented: the first-order PDF moment is proved better than the CF moment, while the second-order CF moment is better than the PDF moment. It tries to open the theoretical discussion on steganalysis and the question of finding suitable statistical features.

A Serious Games Platform for Cognitive Rehabilitation with Preliminary Evaluation.

PubMed

Rego, Paula Alexandra; Rocha, Rui; Faria, Brígida Mónica; Reis, Luís Paulo; Moreira, Pedro Miguel

2017-01-01

In recent years Serious Games have evolved substantially, solving problems in diverse areas. In particular, in Cognitive Rehabilitation, Serious Games assume a relevant role. Traditional cognitive therapies are often considered repetitive and discouraging for patients and Serious Games can be used to create more dynamic rehabilitation processes, holding patients' attention throughout the process and motivating them during their road to recovery. This paper reviews Serious Games and user interfaces in rehabilitation area and details a Serious Games platform for Cognitive Rehabilitation that includes a set of features such as: natural and multimodal user interfaces and social features (competition, collaboration, and handicapping) which can contribute to augment the motivation of patients during the rehabilitation process. The web platform was tested with healthy subjects. Results of this preliminary evaluation show the motivation and the interest of the participants by playing the games.

Mortality Prediction Model of Septic Shock Patients Based on Routinely Recorded Data

PubMed Central

Carrara, Marta; Baselli, Giuseppe; Ferrario, Manuela

2015-01-01

We studied the problem of mortality prediction in two datasets, the first composed of 23 septic shock patients and the second composed of 73 septic subjects selected from the public database MIMIC-II. For each patient we derived hemodynamic variables, laboratory results, and clinical information of the first 48 hours after shock onset and we performed univariate and multivariate analyses to predict mortality in the following 7 days. The results show interesting features that individually identify significant differences between survivors and nonsurvivors and features which gain importance only when considered together with the others in a multivariate regression model. This preliminary study on two small septic shock populations represents a novel contribution towards new personalized models for an integration of multiparameter patient information to improve critical care management of shock patients. PMID:26557154

Ultra high molecular weight polyethylene: Optical features at millimeter wavelengths

NASA Astrophysics Data System (ADS)

D'Alessandro, G.; Paiella, A.; Coppolecchia, A.; Castellano, M. G.; Colantoni, I.; de Bernardis, P.; Lamagna, L.; Masi, S.

2018-05-01

The next generation of experiments for the measurement of the Cosmic Microwave Background (CMB) requires more and more the use of advanced materials, with specific physical and structural properties. An example is the material used for receiver's cryostat windows and internal lenses. The large throughput of current CMB experiments requires a large diameter (of the order of 0.5 m) of these parts, resulting in heavy structural and optical requirements on the material to be used. Ultra High Molecular Weight (UHMW) polyethylene (PE) features high resistance to traction and good transmissivity in the frequency range of interest. In this paper, we discuss the possibility of using UHMW PE for windows and lenses in experiments working at millimeter wavelengths, by measuring its optical properties: emissivity, transmission and refraction index. Our measurements show that the material is well suited to this purpose.

Characterizing region of interest in image using MPEG-7 visual descriptors

NASA Astrophysics Data System (ADS)

Ryu, Min-Sung; Park, Soo-Jun; Won, Chee Sun

2005-08-01

In this paper, we propose a region-based image retrieval system using EHD (Edge Histogram Descriptor) and CLD (Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., 4x4) non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between EHD and CLD, we need to take an 8x8 inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.

Electronic band structure of 4d and 5d transition metal trichalcogenides

NASA Astrophysics Data System (ADS)

Sugita, Yusuke; Miyake, Takashi; Motome, Yukitoshi

2018-05-01

Transition metal trichalcogenides (TMTs), a family of van der Waals materials, have gained increasing interests from the discovery of magnetism in few-layer forms. Although TMTs with 3d transition metal elements have been studied extensively, much less is explored for the 4d and 5d cases, where the interesting interplay between electron correlations and the relativistic spin-orbit coupling is expected. Using ab initio calculations, we here investigate the electronic property of TMTs with 4d and 5d transition metal elements. We show that the band structures exhibit multiple node-like features near the Fermi level. These are the remnant of multiple Dirac cones that were recently discovered in the monolayer cases. Our results indicate that the peculiar two-dimensional multiple Dirac cones are concealed even in the layered bulk systems.

The Photospheric Footprints of Coronal Hole Jets

NASA Astrophysics Data System (ADS)

Muglach, Karin

2016-10-01

Coronal jets are transient, collimated ejections of plasma that are a common feature of solar X-ray and EUV image sequences. Of special interest are jets in coronal holes due to their possible contribution to the solar wind outflow. From a sample of 35 jet events I will investigate the photospheric signatures at the footpoints of these jets. White light images from the HMI on board SDO are used to derive the plane-of-sky flow field using local correlation tracking, and HMI magnetograms show the development of the magnetic flux. Both the evolution of the magnetic field and flows allow one to study the photospheric driver of these jets. One particularly interesting example demonstrates that the untwisting jet involves a tiny filament whose eruption is most likely triggered by the emergence of a small magnetic bipole close to one of its legs.

Magnetic resonance image segmentation using multifractal techniques

NASA Astrophysics Data System (ADS)

Yu, Yue-e.; Wang, Fang; Liu, Li-lin

2015-11-01

In order to delineate target region for magnetic resonance image (MRI) with diseases, the classical multifractal spectrum (MFS)-segmentation method and latest multifractal detrended fluctuation spectrum (MF-DFS)-based segmentation method are employed in our study. One of our main conclusions from experiments is that both of the two multifractal-based methods are workable for handling MRIs. The best result is obtained by MF-DFS-based method using Lh10 as local characteristic. The anti-noises experiments also suppot the conclusion. This interest finding shows that the features can be better represented by the strong fluctuations instead of the weak fluctuations for the MRIs. By comparing the multifractal nature between lesion and non-lesion area on the basis of the segmentation results, an interest finding is that the gray value's fluctuation in lesion area is much severer than that in non-lesion area.

'Blueberry' Triplets Born in Rock

NASA Technical Reports Server (NTRS)

2004-01-01

This microscopic image, taken at the outcrop region dubbed 'Berry Bowl' near the Mars Exploration Rover Opportunity's landing site, shows the sphere-like grains or 'blueberries' that fill Berry Bowl. Of particular interest is the blueberry triplet, which indicates that these geologic features grew in pre-existing wet sediments. Other sphere-like grains that form in the air, such as impact spherules or ejected volcanic material called lapilli, are unlikely to fuse along a line and form triplets. This image was taken by the rover's microscopic imager on the 46th martian day, or sol, of its mission.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

NASA Astrophysics Data System (ADS)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

Magnetohydrodynamic modelling of exploding foil initiators

NASA Astrophysics Data System (ADS)

Neal, William

2015-06-01

Magnetohydrodynamic (MHD) codes are currently being developed, and used, to predict the behaviour of electrically-driven flyer-plates. These codes are of particular interest to the design of exploding foil initiator (EFI) detonators but there is a distinct lack of comparison with high-fidelity experimental data. This study aims to compare a MHD code with a collection of temporally and spatially resolved diagnostics including PDV, dual-axis imaging and streak imaging. The results show the code's excellent representation of the flyer-plate launch and highlight features within the experiment that the model fails to capture.

Vortex rope instabilities in a model of conical draft tube

NASA Astrophysics Data System (ADS)

Skripkin, Sergey; Tsoy, Mikhail; Kuibin, Pavel; Shtork, Sergey

2017-10-01

We report on experimental studies of the formation of vortex ropes in a laboratory simplified model of hydroturbine draft tube. Work is focused on the observation of various flow patterns at the different rotational speed of turbine runner at fixed flow rate. The measurements involve high-speed visualization and pressure pulsations recordings. Draft tube wall pressure pulsations are registered by pressure transducer for different flow regimes. Vortex rope precession frequency were calculated using FFT transform. The experiments showed interesting features of precessing vortex rope like twin spiral and formation of vortex ring.

Equilibration and nonclassicality of a double-well potential

NASA Astrophysics Data System (ADS)

Campbell, Steve; de Chiara, Gabriele; Paternostro, Mauro

2016-01-01

A double well loaded with bosonic atoms represents an ideal candidate to simulate some of the most interesting aspects in the phenomenology of thermalisation and equilibration. Here we report an exhaustive analysis of the dynamics and steady state properties of such a system locally in contact with different temperature reservoirs. We show that thermalisation only occurs ‘accidentally’. We further examine the nonclassical features and energy fluxes implied by the dynamics of the double-well system, thus exploring its finite-time thermodynamics in relation to the settlement of nonclassical correlations between the wells.

Event-driven visual attention for the humanoid robot iCub

PubMed Central

Rea, Francesco; Metta, Giorgio; Bartolozzi, Chiara

2013-01-01

Fast reaction to sudden and potentially interesting stimuli is a crucial feature for safe and reliable interaction with the environment. Here we present a biologically inspired attention system developed for the humanoid robot iCub. It is based on input from unconventional event-driven vision sensors and an efficient computational method. The resulting system shows low-latency and fast determination of the location of the focus of attention. The performance is benchmarked against an instance of the state of the art in robotics artificial attention system used in robotics. Results show that the proposed system is two orders of magnitude faster that the benchmark in selecting a new stimulus to attend. PMID:24379753

Improved explanation of human intelligence using cortical features with second order moments and regression.

PubMed

Park, Hyunjin; Yang, Jin-ju; Seo, Jongbum; Choi, Yu-yong; Lee, Kun-ho; Lee, Jong-min

2014-04-01

Cortical features derived from magnetic resonance imaging (MRI) provide important information to account for human intelligence. Cortical thickness, surface area, sulcal depth, and mean curvature were considered to explain human intelligence. One region of interest (ROI) of a cortical structure consisting of thousands of vertices contained thousands of measurements, and typically, one mean value (first order moment), was used to represent a chosen ROI, which led to a potentially significant loss of information. We proposed a technological improvement to account for human intelligence in which a second moment (variance) in addition to the mean value was adopted to represent a chosen ROI, so that the loss of information would be less severe. Two computed moments for the chosen ROIs were analyzed with partial least squares regression (PLSR). Cortical features for 78 adults were measured and analyzed in conjunction with the full-scale intelligence quotient (FSIQ). Our results showed that 45% of the variance of the FSIQ could be explained using the combination of four cortical features using two moments per chosen ROI. Our results showed improvement over using a mean value for each ROI, which explained 37% of the variance of FSIQ using the same set of cortical measurements. Our results suggest that using additional second order moments is potentially better than using mean values of chosen ROIs for regression analysis to account for human intelligence. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessing blood flow, microvasculature, erythema and redness in hypertrophic scars: A cross sectional study showing different features that require precise definitions.

PubMed

Jaspers, M E H; Stekelenburg, C M; Simons, J M; Brouwer, K M; Vlig, M; van den Kerckhove, E; Middelkoop, E; van Zuijlen, P P M

2017-08-01

In hypertrophic scar assessment, laser Doppler imaging (LDI), colorimetry and subjective assessment (POSAS) can be used to evaluate blood flow, erythema and redness, respectively. In addition, the microvasculature (i.e. presence of microvessels) can be determined by immunohistochemistry. These measurement techniques are frequently used in clinical practice and/or in research to evaluate treatment response and monitor scar development. However, until now it has not been tested to what extent the outcomes of these techniques are associated, whilst the outcome terms are frequently used interchangeably or replaced by the umbrella term 'vascularization'. This is confusing, as every technique seems to measure a specific feature. Therefore, we evaluated the correlations of the four measurement techniques. We included 32 consecutive patients, aged ≥18 years, who underwent elective resection of a hypertrophic scar. Pre-operatively, we performed LDI (measuring blood flow), colorimetry (measuring erythema) and the POSAS (subjective redness) within the predefined scar area of interest (∼1.5cm). Subsequently, the scar was excised and the area of interest was sent for immunohistochemistry, to determine the presence of microvessels. Only a statistically significant correlation was found between erythema values (colorimetry) and subjective redness assessment (POSAS) (r=0.403, p=0.030). We found no correlations between the outcomes of LDI, immunohistochemistry and colorimetry. Blood flow, the presence of microvessels and erythema appear to be different hypertrophic scar features because they show an absence of correlation. Therefore, in the field of scar assessment, these outcome terms cannot be used interchangeably. In addition, we conclude that the term 'vascularization' does not seem appropriate to serve as an umbrella term. The use of precise definitions in research as well as in clinical practice is recommended. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

A Lively Class Section for the Adult Education Second-Language Course.

ERIC Educational Resources Information Center

Carton, Dana

1983-01-01

Exercises with numbers designed to hold the interest of a heterogeneous group of adult students are described. They include games about age, counting, and cards. Meaningful content and active, interested participation are features of the techniques. (MSE)

A New Approach to Automated Labeling of Internal Features of Hardwood Logs Using CT Images

Treesearch

Daniel L. Schmoldt; Pei Li; A. Lynn Abbott

1996-01-01

The feasibility of automatically identifying internal features of hardwood logs using CT imagery has been established previously. Features of primary interest are bark, knots, voids, decay, and clear wood. Our previous approach: filtered original CT images, applied histogram segmentation, grew volumes to extract 3-d regions, and applied a rule base, with Dempster-...

Survey of elemental specificity in positron annihilation peak shapes

NASA Astrophysics Data System (ADS)

Myler, U.; Simpson, P. J.

1997-12-01

Recently the detailed interpretation of positron-annihilation γ-ray peak shapes has proven to be of interest with respect to their chemical specificity. In this contribution, we show highly resolved spectra for a number of different elements. To this purpose, annihilation spectra with strongly reduced background intensities were recorded in the two detector geometry, using a variable-energy positron beam. Division of the subsequently normalized spectra by a standard spectrum (in our case the spectrum of pure silicon) yields quotient spectra, which display features characteristic of the sample material. First we ascertain that the specific spectrum of an element is conserved in different chemical compounds, demonstrated here by identical oxygen spectra obtained from both SiO2/Si and MgO/Mg. Second, we show highly resolved spectra for a number of different elements (Fe...Zn, Ag, Ir...Au). We show that the characteristic features in these spectra vary in a systematic fashion with the atomic number of the element and can be tentatively identified with particular orbitals. Finally, for 26 different elements we compare the maximum intensity in the quotient spectra with the relative atomic density in the corresponding element. To our knowledge, this is the most comprehensive survey of such data made to date.

Ankle fractures have features of an osteoporotic fracture.

PubMed

Lee, K M; Chung, C Y; Kwon, S S; Won, S H; Lee, S Y; Chung, M K; Park, M S

2013-11-01

We report the bone attenuation of ankle joint measured on computed tomography (CT) and the cause of injury in patients with ankle fractures. The results showed age- and gender-dependent low bone attenuation and low-energy trauma in elderly females, which suggest the osteoporotic features of ankle fractures. This study was performed to investigate the osteoporotic features of ankle fracture in terms of bone attenuation and cause of injury. One hundred ninety-four patients (mean age 51.0 years, standard deviation 15.8 years; 98 males and 96 females) with ankle fracture were included. All patients underwent CT examination, and causes of injury (high/low-energy trauma) were recorded. Mean bone attenuations of the talus, medial malleolus, lateral malleolus, and distal tibial metaphysis were measured on CT images. Patients were divided into younger age (<50 years) and older age (≥50 years) groups, and mean bone attenuation and causes of injury were compared between the two groups in each gender. Proportion of low-energy trauma was higher in the older age group than in the younger age group, but the difference was only significant in female gender (p = 0.011). The older age group showed significantly lower bone attenuation in the talus, medial malleolus, lateral malleolus, and distal tibial metaphysis than the younger age group in both genders. The older age group showed more complex pattern of fractures than the younger age group. With increasing age, bone attenuations tended to decrease and the difference of bone attenuation between the genders tended to increase in the talus, medial malleolus, lateral malleolus, and distal tibial metaphysis. Ankle fracture had features of osteoporotic fracture that is characterized by age- and gender-dependent low bone attenuation. Ankle fracture should not be excluded from the clinical and research interest as well as from the benefit of osteoporosis management.

THE SPITZER ATLAS OF STELLAR SPECTRA (SASS)

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

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech

2010-12-15

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 {mu}m; R {approx} 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, themore » spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.« less

The Spitzer Atlas of Stellar Spectra (SASS)

NASA Astrophysics Data System (ADS)

Ardila, David R.; Van Dyk, Schuyler D.; Makowiecki, Wojciech; Stauffer, John; Song, Inseok; Rho, Jeonghee; Fajardo-Acosta, Sergio; Hoard, D. W.; Wachter, Stefanie

2010-12-01

We present the Spitzer Atlas of Stellar Spectra, which includes 159 stellar spectra (5-32 μm R ~ 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general stellar spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest spectral types. Most supergiant spectra in the Atlas present evidence of circumstellar gas and/or dust. The sample includes five M supergiant spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse spectra, dominated by circumstellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of spectral type for most luminosity classes.

Measuring the Interestingness of Articles in a Limited User Environment

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

Pon, Raymond K.

Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to a user. For example, if the article is old or yields little new information, the article would be uninteresting. Relevancy scores do not take into account what makes an article interesting, which varies from user to user. Although methods such as collaborative filtering have been shown to be effective in recommendation systems, in a limited user environment, there are not enough users that would make collaborative filtering effective. A general framework,more » called iScore, is presented for defining and measuring the 'interestingness' of articles, incorporating user-feedback. iScore addresses various aspects of what makes an article interesting, such as topic relevancy, uniqueness, freshness, source reputation, and writing style. It employs various methods to measure these features and uses a classifier operating on these features to recommend articles. The basic iScore configuration is shown to improve recommendation results by as much as 20%. In addition to the basic iScore features, additional features are presented to address the deficiencies of existing feature extractors, such as one that tracks multiple topics, called MTT, and a version of the Rocchio algorithm that learns its parameters online as it processes documents, called eRocchio. The inclusion of both MTT and eRocchio into iScore is shown to improve iScore recommendation results by as much as 3.1% and 5.6%, respectively. Additionally, in TREC11 Adaptive Filter Task, eRocchio is shown to be 10% better than the best filter in the last run of the task. In addition to these two major topic relevancy measures, other features are also introduced that employ language models, phrases, clustering, and changes in topics to improve recommendation results. These additional features are shown to improve recommendation results by iScore by up to 14%. Due to varying reasons that users hold regarding why an article is interesting, an online feature selection method in naive Bayes is also introduced. Online feature selection can improve recommendation results in iScore by up to 18.9%. In summary, iScore in its best configuration can outperform traditional IR techniques by as much as 50.7%. iScore and its components are evaluated in the news recommendation task using three datasets from Yahoo! News, actual users, and Digg. iScore and its components are also evaluated in the TREC Adaptive Filter task using the Reuters RCV1 corpus.« less

MO-DE-207B-04: Impact of Reconstruction Field of View On Radiomics Features in Computed Tomography (CT) Using a Texture Phantom

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

Shafiq ul Hassan, M; Zhang, G; Oliver, J

Purpose: To investigate the impact of reconstruction Field of View on Radiomics features in computed tomography (CT) using a texture phantom. Methods: A rectangular Credence Cartridge Radiomics (CCR) phantom, composed of 10 different cartridges, was scanned on four different CT scanners from two manufacturers. A pre-defined scanning protocol was adopted for consistency. The slice thickness and reconstruction interval of 1.5 mm was used on all scanners. The reconstruction FOV was varied to result a voxel size ranging from 0.38 to 0.98 mm. A spherical region of interest (ROI) was contoured on the shredded rubber cartridge from CCR phantom CT scans.more » Ninety three Radiomics features were extracted from ROI using an in-house program. These include 10 shape, 22 intensity, 26 GLCM, 11 GLZSM, 11 RLM, 5 NGTDM and 8 fractal dimensional features. To evaluate the Interscanner variability across three scanners, a coefficient of variation (COV) was calculated for each feature group. Each group was further classified according to the COV by calculating the percentage of features in each of the following categories: COV≤ 5%, between 5 and 10% and ≥ 10%. Results: Shape features were the most robust, as expected, because of the spherical contouring of ROI. Intensity features were the second most robust with 54.5 to 64% of features with COV < 5%. GLCM features ranged from 31 to 35% for the same category. RLM features were sensitive to specific scanner and 5% variability was 9 to 54%. Almost all GLZM and NGTDM features showed COV ≥10% among the scanners. The dependence of fractal dimensions features on FOV was not consistent across different scanners. Conclusion: We concluded that reconstruction FOV greatly influence Radiomics features. The GLZSM and NGTDM are highly sensitive to FOV. funded in part by Grant NIH/NCI R01CA190105-01.« less

Investigation of kinematic features for dismount detection and tracking

NASA Astrophysics Data System (ADS)

Narayanaswami, Ranga; Tyurina, Anastasia; Diel, David; Mehra, Raman K.; Chinn, Janice M.

2012-05-01

With recent changes in threats and methods of warfighting and the use of unmanned aircrafts, ISR (Intelligence, Surveillance and Reconnaissance) activities have become critical to the military's efforts to maintain situational awareness and neutralize the enemy's activities. The identification and tracking of dismounts from surveillance video is an important step in this direction. Our approach combines advanced ultra fast registration techniques to identify moving objects with a classification algorithm based on both static and kinematic features of the objects. Our objective was to push the acceptable resolution beyond the capability of industry standard feature extraction methods such as SIFT (Scale Invariant Feature Transform) based features and inspired by it, SURF (Speeded-Up Robust Feature). Both of these methods utilize single frame images. We exploited the temporal component of the video signal to develop kinematic features. Of particular interest were the easily distinguishable frequencies characteristic of bipedal human versus quadrupedal animal motion. We examine limits of performance, frame rates and resolution required for human, animal and vehicles discrimination. A few seconds of video signal with the acceptable frame rate allow us to lower resolution requirements for individual frames as much as by a factor of five, which translates into the corresponding increase of the acceptable standoff distance between the sensor and the object of interest.

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

NASA Astrophysics Data System (ADS)

Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

2005-04-01

Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

Nonaggressive systemic mastocytosis (SM) without skin lesions associated with insect-induced anaphylaxis shows unique features versus other indolent SM.

PubMed

Alvarez-Twose, Iván; Zanotti, Roberta; González-de-Olano, David; Bonadonna, Patrizia; Vega, Arantza; Matito, Almudena; Sánchez-Muñoz, Laura; Morgado, José Mário; Perbellini, Omar; García-Montero, Andrés; De Matteis, Giovanna; Teodósio, Cristina; Rossini, Maurizio; Jara-Acevedo, María; Schena, Donatella; Mayado, Andrea; Zamò, Alberto; Mollejo, Manuela; Sánchez-López, Paula; Cabañes, Nieves; Orfao, Alberto; Escribano, Luis

2014-02-01

Indolent systemic mastocytosis (ISM) without skin lesions (ISMs(-)) shows a higher prevalence in males, lower serum baseline tryptase levels, and KIT mutation more frequently restricted to bone marrow (BM) mast cells (MCs) than ISM with skin lesions (ISMs(+)). Interestingly, in almost one-half of ISMs(-) patients, MC-mediator release episodes are triggered exclusively by insects. We aimed to determine the clinical and laboratory features of ISMs(-) associated with insect-induced anaphylaxis (insectISMs(-)) versus other patients with ISM. A total of 335 patients presenting with MC activation syndrome, including 143 insectISMs(-), 72 ISMs(-) triggered by other factors (otherISMs(-)), 56 ISMs(+), and 64 nonclonal MC activation syndrome, were studied. Compared with otherISMs(-) and ISMs(+) patients, insectISMs(-) cases showed marked male predominance (78% vs 53% and 46%; P < .001), a distinct pattern of MC-related symptoms, and significantly lower median serum baseline tryptase levels (22.4 vs 28.7 and 45.8 μg/L; P ≤ .009). Moreover, insectISMs(-) less frequently presented BM MC aggregates (46% vs 70% and 81%; P ≤ .001), and they systematically showed MC-restricted KIT mutation. ISMs(-) patients with anaphylaxis triggered exclusively by insects display clinical and laboratory features that are significantly different from other ISM cases, including other ISMs(-) and ISMs(+) patients, suggesting that they represent a unique subgroup of ISM with a particularly low BM MC burden in the absence of adverse prognostic factors. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Texture classification of normal tissues in computed tomography using Gabor filters

NASA Astrophysics Data System (ADS)

Dettori, Lucia; Bashir, Alia; Hasemann, Julie

2007-03-01

The research presented in this article is aimed at developing an automated imaging system for classification of normal tissues in medical images obtained from Computed Tomography (CT) scans. Texture features based on a bank of Gabor filters are used to classify the following tissues of interests: liver, spleen, kidney, aorta, trabecular bone, lung, muscle, IP fat, and SQ fat. The approach consists of three steps: convolution of the regions of interest with a bank of 32 Gabor filters (4 frequencies and 8 orientations), extraction of two Gabor texture features per filter (mean and standard deviation), and creation of a Classification and Regression Tree-based classifier that automatically identifies the various tissues. The data set used consists of approximately 1000 DIACOM images from normal chest and abdominal CT scans of five patients. The regions of interest were labeled by expert radiologists. Optimal trees were generated using two techniques: 10-fold cross-validation and splitting of the data set into a training and a testing set. In both cases, perfect classification rules were obtained provided enough images were available for training (~65%). All performance measures (sensitivity, specificity, precision, and accuracy) for all regions of interest were at 100%. This significantly improves previous results that used Wavelet, Ridgelet, and Curvelet texture features, yielding accuracy values in the 85%-98% range The Gabor filters' ability to isolate features at different frequencies and orientations allows for a multi-resolution analysis of texture essential when dealing with, at times, very subtle differences in the texture of tissues in CT scans.

Shape and Color Features for Object Recognition Search

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Duong, Vu A.; Stubberud, Allen R.

2012-01-01

A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

Towards an Optimal Interest Point Detector for Measurements in Ultrasound Images

NASA Astrophysics Data System (ADS)

Zukal, Martin; Beneš, Radek; Číka, Petr; Říha, Kamil

2013-12-01

This paper focuses on the comparison of different interest point detectors and their utilization for measurements in ultrasound (US) images. Certain medical examinations are based on speckle tracking which strongly relies on features that can be reliably tracked frame to frame. Only significant features (interest points) resistant to noise and brightness changes within US images are suitable for accurate long-lasting tracking. We compare three interest point detectors - Harris-Laplace, Difference of Gaussian (DoG) and Fast Hessian - and identify the most suitable one for use in US images on the basis of an objective criterion. Repeatability rate is assumed to be an objective quality measure for comparison. We have measured repeatability in images corrupted by different types of noise (speckle noise, Gaussian noise) and for changes in brightness. The Harris-Laplace detector outperformed its competitors and seems to be a sound option when choosing a suitable interest point detector for US images. However, it has to be noted that Fast Hessian and DoG detectors achieved better results in terms of processing speed.

Seeing More Than Human: Autism and Anthropomorphic Theory of Mind.

PubMed

Atherton, Gray; Cross, Liam

2018-01-01

Theory of mind (ToM) is defined as the process of taking another's perspective. Anthropomorphism can be seen as the extension of ToM to non-human entities. This review examines the literature concerning ToM and anthropomorphism in relation to individuals with Autism Spectrum Disorder (ASD), specifically addressing the questions of how and why those on the spectrum both show an increased interest for anthropomorphism and may even show improved ToM abilities when judging the mental states of anthropomorphic characters. This review highlights that while individuals with ASD traditionally show deficits on a wide range of ToM tests, such as recognizing facial emotions, such ToM deficits may be ameliorated if the stimuli presented is cartoon or animal-like rather than in human form. Individuals with ASD show a greater interest in anthropomorphic characters and process the features of these characters using methods typically reserved for human stimuli. Personal accounts of individuals with ASD also suggest they may identify more closely with animals than other humans. It is shown how the social motivations hypothesized to underlie the anthropomorphizing of non-human targets may lead those on the spectrum to seek social connections and therefore gain ToM experience and expertise amongst unlikely sources.

Seeing More Than Human: Autism and Anthropomorphic Theory of Mind

PubMed Central

Atherton, Gray; Cross, Liam

2018-01-01

Theory of mind (ToM) is defined as the process of taking another’s perspective. Anthropomorphism can be seen as the extension of ToM to non-human entities. This review examines the literature concerning ToM and anthropomorphism in relation to individuals with Autism Spectrum Disorder (ASD), specifically addressing the questions of how and why those on the spectrum both show an increased interest for anthropomorphism and may even show improved ToM abilities when judging the mental states of anthropomorphic characters. This review highlights that while individuals with ASD traditionally show deficits on a wide range of ToM tests, such as recognizing facial emotions, such ToM deficits may be ameliorated if the stimuli presented is cartoon or animal-like rather than in human form. Individuals with ASD show a greater interest in anthropomorphic characters and process the features of these characters using methods typically reserved for human stimuli. Personal accounts of individuals with ASD also suggest they may identify more closely with animals than other humans. It is shown how the social motivations hypothesized to underlie the anthropomorphizing of non-human targets may lead those on the spectrum to seek social connections and therefore gain ToM experience and expertise amongst unlikely sources. PMID:29755383

Combined 18F-Fluciclovine PET/MRI Shows Potential for Detection and Characterization of High-Risk Prostate Cancer.

PubMed

Elschot, Mattijs; Selnæs, Kirsten M; Sandsmark, Elise; Krüger-Stokke, Brage; Størkersen, Øystein; Giskeødegård, Guro F; Tessem, May-Britt; Moestue, Siver A; Bertilsson, Helena; Bathen, Tone F

2018-05-01

The objective of this study was to investigate whether quantitative imaging features derived from combined 18 F-fluciclovine PET/multiparametric MRI show potential for detection and characterization of primary prostate cancer. Methods: Twenty-eight patients diagnosed with high-risk prostate cancer underwent simultaneous 18 F-fluciclovine PET/MRI before radical prostatectomy. Volumes of interest (VOIs) for prostate tumors, benign prostatic hyperplasia (BPH) nodules, prostatitis, and healthy tissue were delineated on T2-weighted images, using histology as a reference. Tumor VOIs were marked as high-grade (≥Gleason grade group 3) or not. MRI and PET features were extracted on the voxel and VOI levels. Partial least-squared discriminant analysis (PLS-DA) with double leave-one-patient-out cross-validation was performed to distinguish tumors from benign tissue (BPH, prostatitis, or healthy tissue) and high-grade tumors from other tissue (low-grade tumors or benign tissue). The performance levels of PET, MRI, and combined PET/MRI features were compared using the area under the receiver-operating-characteristic curve (AUC). Results: Voxel and VOI features were extracted from 40 tumor VOIs (26 high-grade), 36 BPH VOIs, 6 prostatitis VOIs, and 37 healthy-tissue VOIs. PET/MRI performed better than MRI and PET alone for distinguishing tumors from benign tissue (AUCs of 87%, 81%, and 83%, respectively, at the voxel level and 96%, 93%, and 93%, respectively, at the VOI level) and high-grade tumors from other tissue (AUCs of 85%, 79%, and 81%, respectively, at the voxel level and 93%, 93%, and 91%, respectively, at the VOI level). T2-weighted MRI, diffusion-weighted MRI, and PET features were the most important for classification. Conclusion: Combined 18 F-fluciclovine PET/multiparametric MRI shows potential for improving detection and characterization of high-risk prostate cancer, in comparison to MRI and PET alone. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Exact and approximate graph matching using random walks.

PubMed

Gori, Marco; Maggini, Marco; Sarti, Lorenzo

2005-07-01

In this paper, we propose a general framework for graph matching which is suitable for different problems of pattern recognition. The pattern representation we assume is at the same time highly structured, like for classic syntactic and structural approaches, and of subsymbolic nature with real-valued features, like for connectionist and statistic approaches. We show that random walk based models, inspired by Google's PageRank, give rise to a spectral theory that nicely enhances the graph topological features at node level. As a straightforward consequence, we derive a polynomial algorithm for the classic graph isomorphism problem, under the restriction of dealing with Markovian spectrally distinguishable graphs (MSD), a class of graphs that does not seem to be easily reducible to others proposed in the literature. The experimental results that we found on different test-beds of the TC-15 graph database show that the defined MSD class "almost always" covers the database, and that the proposed algorithm is significantly more efficient than top scoring VF algorithm on the same data. Most interestingly, the proposed approach is very well-suited for dealing with partial and approximate graph matching problems, derived for instance from image retrieval tasks. We consider the objects of the COIL-100 visual collection and provide a graph-based representation, whose node's labels contain appropriate visual features. We show that the adoption of classic bipartite graph matching algorithms offers a straightforward generalization of the algorithm given for graph isomorphism and, finally, we report very promising experimental results on the COIL-100 visual collection.

Semi-automated surface mapping via unsupervised classification

NASA Astrophysics Data System (ADS)

D'Amore, M.; Le Scaon, R.; Helbert, J.; Maturilli, A.

2017-09-01

Due to the increasing volume of the returned data from space mission, the human search for correlation and identification of interesting features becomes more and more unfeasible. Statistical extraction of features via machine learning methods will increase the scientific output of remote sensing missions and aid the discovery of yet unknown feature hidden in dataset. Those methods exploit algorithm trained on features from multiple instrument, returning classification maps that explore intra-dataset correlation, allowing for the discovery of unknown features. We present two applications, one for Mercury and one for Vesta.

Interesting Features in Spirit's Uphill View

NASA Technical Reports Server (NTRS)

2004-01-01

Planetary scientists got excited when they saw this imagery coming in from NASA's Mars Exploration Rover Spirit because they could see hints of rock strata and other interesting geologic features ahead. In the middle of this image, from upper left to the lower right, lies a trough that resembles a small ravine. To the right of that and a little way up the hill, beyond a rock-strewn surface, sits a small rounded ridge. Fine horizontal streaks, just perceptible in this image, suggest possible layering in the bedrock. Above that are rock features that appear to drape across the slopes. Scientists are discussing whether to take the rover closer or select other interesting targets for further study. This view looks eastward from the 'West Spur' of the 'Columbia Hills,' where Spirit has been conducting scientific investigations. It is a mosaic of several frames Spirit took with its panoramic camera on the rover's 229th martian day, or sol, (Aug. 24, 2004). The field of view is 48 degrees from left to right. The image is presented in a cylindrical projection with geometrical seam correction.

Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.

PubMed

Kang, Keunsoo; Kim, Joomyeong; Chung, Jae Hoon; Lee, Daeyoup

2011-09-01

The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called 'trace code', and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named 'multi-functional CRM', suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species.

3D Polyaniline Architecture by Concurrent Inorganic and Organic Acid Doping for Superior and Robust High Rate Supercapacitor Performance

NASA Astrophysics Data System (ADS)

Gawli, Yogesh; Banerjee, Abhik; Dhakras, Dipti; Deo, Meenal; Bulani, Dinesh; Wadgaonkar, Prakash; Shelke, Manjusha; Ogale, Satishchandra

2016-02-01

A good high rate supercapacitor performance requires a fine control of morphological (surface area and pore size distribution) and electrical properties of the electrode materials. Polyaniline (PANI) is an interesting material in supercapacitor context because it stores energy Faradaically. However in conventional inorganic (e.g. HCl) acid doping, the conductivity is high but the morphological features are undesirable. On the other hand, in weak organic acid (e.g. phytic acid) doping, interesting and desirable 3D connected morphological features are attained but the conductivity is poorer. Here the synergy of the positive quality factors of these two acid doping approaches is realized by concurrent and optimized strong-inorganic (HCl) and weak-organic (phytic) acid doping, resulting in a molecular composite material that renders impressive and robust supercapacitor performance. Thus, a nearly constant high specific capacitance of 350 F g-1 is realized for the optimised case of binary doping over the entire range of 1 A g-1 to 40 A g-1 with stability of 500 cycles at 40 A g-1. Frequency dependant conductivity measurements show that the optimized co-doped case is more metallic than separately doped materials. This transport property emanates from the unique 3D single molecular character of such system.

Automated detection of microaneurysms using robust blob descriptors

NASA Astrophysics Data System (ADS)

Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

2013-03-01

Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

A Lightweight Anonymous Authentication Protocol with Perfect Forward Secrecy for Wireless Sensor Networks.

PubMed

Xiong, Ling; Peng, Daiyuan; Peng, Tu; Liang, Hongbin; Liu, Zhicai

2017-11-21

Due to their frequent use in unattended and hostile deployment environments, the security in wireless sensor networks (WSNs) has attracted much interest in the past two decades. However, it remains a challenge to design a lightweight authentication protocol for WSNs because the designers are confronted with a series of desirable security requirements, e.g., user anonymity, perfect forward secrecy, resistance to de-synchronization attack. Recently, the authors presented two authentication schemes that attempt to provide user anonymity and to resist various known attacks. Unfortunately, in this work we shall show that user anonymity of the two schemes is achieved at the price of an impractical search operation-the gateway node may search for every possible value. Besides this defect, they are also prone to smart card loss attacks and have no provision for perfect forward secrecy. As our main contribution, a lightweight anonymous authentication scheme with perfect forward secrecy is designed, and what we believe the most interesting feature is that user anonymity, perfect forward secrecy, and resistance to de-synchronization attack can be achieved at the same time. As far as we know, it is extremely difficult to meet these security features simultaneously only using the lightweight operations, such as symmetric encryption/decryption and hash functions.

Three-dimensional sensor system using multistripe laser and stereo camera for environment recognition of mobile robots

NASA Astrophysics Data System (ADS)

Kim, Min Young; Cho, Hyung Suck; Kim, Jae H.

2002-10-01

In recent years, intelligent autonomous mobile robots have drawn tremendous interests as service robots for serving human or industrial robots for replacing human. To carry out the task, robots must be able to sense and recognize 3D space that they live or work. In this paper, we deal with the topic related to 3D sensing system for the environment recognition of mobile robots. For this, the structured lighting is basically utilized for a 3D visual sensor system because of the robustness on the nature of the navigation environment and the easy extraction of feature information of interest. The proposed sensing system is classified into a trinocular vision system, which is composed of the flexible multi-stripe laser projector, and two cameras. The principle of extracting the 3D information is based on the optical triangulation method. With modeling the projector as another camera and using the epipolar constraints which the whole cameras makes, the point-to-point correspondence between the line feature points in each image is established. In this work, the principle of this sensor is described in detail, and a series of experimental tests is performed to show the simplicity and efficiency and accuracy of this sensor system for 3D the environment sensing and recognition.

A Lightweight Anonymous Authentication Protocol with Perfect Forward Secrecy for Wireless Sensor Networks

PubMed Central

Peng, Daiyuan; Peng, Tu; Liang, Hongbin; Liu, Zhicai

2017-01-01

Due to their frequent use in unattended and hostile deployment environments, the security in wireless sensor networks (WSNs) has attracted much interest in the past two decades. However, it remains a challenge to design a lightweight authentication protocol for WSNs because the designers are confronted with a series of desirable security requirements, e.g., user anonymity, perfect forward secrecy, resistance to de-synchronization attack. Recently, the authors presented two authentication schemes that attempt to provide user anonymity and to resist various known attacks. Unfortunately, in this work we shall show that user anonymity of the two schemes is achieved at the price of an impractical search operation—the gateway node may search for every possible value. Besides this defect, they are also prone to smart card loss attacks and have no provision for perfect forward secrecy. As our main contribution, a lightweight anonymous authentication scheme with perfect forward secrecy is designed, and what we believe the most interesting feature is that user anonymity, perfect forward secrecy, and resistance to de-synchronization attack can be achieved at the same time. As far as we know, it is extremely difficult to meet these security features simultaneously only using the lightweight operations, such as symmetric encryption/decryption and hash functions. PMID:29160861

3D Polyaniline Architecture by Concurrent Inorganic and Organic Acid Doping for Superior and Robust High Rate Supercapacitor Performance.

PubMed

Gawli, Yogesh; Banerjee, Abhik; Dhakras, Dipti; Deo, Meenal; Bulani, Dinesh; Wadgaonkar, Prakash; Shelke, Manjusha; Ogale, Satishchandra

2016-02-12

A good high rate supercapacitor performance requires a fine control of morphological (surface area and pore size distribution) and electrical properties of the electrode materials. Polyaniline (PANI) is an interesting material in supercapacitor context because it stores energy Faradaically. However in conventional inorganic (e.g. HCl) acid doping, the conductivity is high but the morphological features are undesirable. On the other hand, in weak organic acid (e.g. phytic acid) doping, interesting and desirable 3D connected morphological features are attained but the conductivity is poorer. Here the synergy of the positive quality factors of these two acid doping approaches is realized by concurrent and optimized strong-inorganic (HCl) and weak-organic (phytic) acid doping, resulting in a molecular composite material that renders impressive and robust supercapacitor performance. Thus, a nearly constant high specific capacitance of 350 F g(-1) is realized for the optimised case of binary doping over the entire range of 1 A g(-1) to 40 A g(-1) with stability of 500 cycles at 40 A g(-1). Frequency dependant conductivity measurements show that the optimized co-doped case is more metallic than separately doped materials. This transport property emanates from the unique 3D single molecular character of such system.

Motorcycles on the Move

ERIC Educational Resources Information Center

McIntosh, Phyllis

2013-01-01

Motorcycles are the subject of this feature article, which explores such topics as the history of motorcycles, types of motorcycles, special interest motorcycle clubs, motorcycle rallies, the Harley-Davidson company, and Rolling Thunder. A list of websites of interest and a glossary of "motorcycle jargon" are included.

From High Intellectual Potential to Asperger Syndrome: Evidence for Differences and a Fundamental Overlap-A Systematic Review.

PubMed

Boschi, Aurélie; Planche, Pascale; Hemimou, Cherhazad; Demily, Caroline; Vaivre-Douret, Laurence

2016-01-01

Background: An increasing number of clinicians point to similar clinical features between some children with High Intellectual Potential (HIP or "Giftedness" = Total IQ > 2 SD ), and children with Autism Spectrum Disorder (ASD) without intellectual or language delay, formerly diagnosed with Asperger Syndrome. Some of these common features are social interaction impairments, special interests, and in some cases high-verbal abilities. The aim of this article is to determine whether these similarities exist at more fundamental levels, other than clinical, and to explore the literature in order to provide empirical support for an overlap between ASD and HIP. Method: First, comparative studies between ASD and HIP children were sought. Because of a lack of data, the respective characteristics of ASD and HIP subjects were explored by a cross-sectional review of different areas of research. Emphasis was placed on psychometric and cognitive evaluations, experimental and developmental assessments, and neurobiological research, following a "bottom-up" procedure. Results: This review highlights the existence of similarities in the neurocognitive, developmental and neurobiological domains between these profiles, which require further study. In addition, the conclusions of several studies show that there are differences between HIP children with a homogeneous Intellectual Quotient profile and children with a heterogeneous Intellectual Quotient profile. Conclusion: HIP seems to cover different developmental profiles, one of which might share features with ASD. A new line of investigation providing a possible starting-point for future research is proposed. Its implications, interesting from both clinical and research perspectives, are discussed.

From High Intellectual Potential to Asperger Syndrome: Evidence for Differences and a Fundamental Overlap—A Systematic Review

PubMed Central

Boschi, Aurélie; Planche, Pascale; Hemimou, Cherhazad; Demily, Caroline; Vaivre-Douret, Laurence

2016-01-01

Background: An increasing number of clinicians point to similar clinical features between some children with High Intellectual Potential (HIP or “Giftedness” = Total IQ > 2 SD), and children with Autism Spectrum Disorder (ASD) without intellectual or language delay, formerly diagnosed with Asperger Syndrome. Some of these common features are social interaction impairments, special interests, and in some cases high-verbal abilities. The aim of this article is to determine whether these similarities exist at more fundamental levels, other than clinical, and to explore the literature in order to provide empirical support for an overlap between ASD and HIP. Method: First, comparative studies between ASD and HIP children were sought. Because of a lack of data, the respective characteristics of ASD and HIP subjects were explored by a cross-sectional review of different areas of research. Emphasis was placed on psychometric and cognitive evaluations, experimental and developmental assessments, and neurobiological research, following a “bottom-up” procedure. Results: This review highlights the existence of similarities in the neurocognitive, developmental and neurobiological domains between these profiles, which require further study. In addition, the conclusions of several studies show that there are differences between HIP children with a homogeneous Intellectual Quotient profile and children with a heterogeneous Intellectual Quotient profile. Conclusion: HIP seems to cover different developmental profiles, one of which might share features with ASD. A new line of investigation providing a possible starting-point for future research is proposed. Its implications, interesting from both clinical and research perspectives, are discussed. PMID:27812341

Autistic savants. [correction of artistic].

PubMed

Hou, C; Miller, B L; Cummings, J L; Goldberg, M; Mychack, P; Bottino, V; Benson, D F

2000-01-01

The objectives of this study were to examine common patterns in the lives and artwork of five artistic savants previously described and to report on the clinical, neuropsychological, and neuroimaging findings from one newly diagnosed artistic savant. The artistic savant syndrome has been recognized for centuries, although its neuroanatomic basis remains a mystery. The cardinal features, strengths, and weaknesses of the work of these six savants were analyzed and compared with those of children with autism in whom artistic talent was absent. An anatomic substrate for these behaviors was considered in the context of newly emerging theories related to paradoxical functional facilitation, visual thinking, and multiple intelligences. The artists had features of "pervasive developmental disorder," including impairment in social interaction and communication as well as restricted repetitive and stereotyped patterns of behavior, interest, and activities. All six demonstrated a strong preference for a single art medium and showed a restricted variation in artistic themes. None understood art theory. Some autistic features contributed to their success, including attention to visual detail, a tendency toward ritualistic compulsive repetition, the ability to focus on one topic at the expense of other interests, and intact memory and visuospatial skills. The artistic savant syndrome remains rare and mysterious in origin. Savants exhibit extraordinary visual talents along with profound linguistic and social impairment. The intense focus on and ability to remember visual detail contributes to the artistic product of the savant. The anatomic substrate for the savant syndrome may involve loss of function in the left temporal lobe with enhanced function of the posterior neocortex.

Can technical characteristics predict clinical performance in PET/CT imaging? A correlation study for thyroid cancer diagnosis

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Menychtas, Dimitrios; Georgakopoulos, Alexandros; Pianou, Nikoletta; Metaxas, Marinos; Chatziioannou, Sofia

2013-03-01

The purpose of this study was to determine whether image characteristics could be used to predict the outcome of ROC studies in PET/CT imaging. Patients suspected for recurrent thyroid cancer underwent a standard whole body (WB) examination and an additional high-resolution head-and-neck (HN) F18-FDG PET/CT scan. The value of the latter was determined with an ROC study, the results of which showed that the WB+HN combination was better than WB alone for thyroid cancer detection and diagnosis. Following the ROC experiment, the WB and HN images of confirmed benign or malignant thyroid disease were analyzed and first and second order textural features were determined. Features included minimum, mean, and maximum intensity, as well as contrast in regions of interest encircling the thyroid lesions. Lesion size and standard uptake values (SUV) were also determined. Bivariate analysis was applied to determine relationships between WB and HN features and between observer ROC responses and the various feature values. The two sets showed significant associations in the values of SUV, contrast, and lesion size. They were completely different when the intensities were considered; no relationship was found between the WB minimum, maximum, and mean ROI values and their HN counterparts. SUV and contrast were the strongest predictors of ROC performance on PET/CT examinations of thyroid cancer. The high resolution HN images seem to enhance these relationships but without a single dramatic effect as was projected from the ROC results. A combination of features from both WB and HN datasets may possibly be a more robust predictor of ROC performance.

Statistical performance of image cytometry for DNA, lipids, cytokeratin, & CD45 in a model system for circulation tumor cell detection.

PubMed

Futia, Gregory L; Schlaepfer, Isabel R; Qamar, Lubna; Behbakht, Kian; Gibson, Emily A

2017-07-01

Detection of circulating tumor cells (CTCs) in a blood sample is limited by the sensitivity and specificity of the biomarker panel used to identify CTCs over other blood cells. In this work, we present Bayesian theory that shows how test sensitivity and specificity set the rarity of cell that a test can detect. We perform our calculation of sensitivity and specificity on our image cytometry biomarker panel by testing on pure disease positive (D + ) populations (MCF7 cells) and pure disease negative populations (D - ) (leukocytes). In this system, we performed multi-channel confocal fluorescence microscopy to image biomarkers of DNA, lipids, CD45, and Cytokeratin. Using custom software, we segmented our confocal images into regions of interest consisting of individual cells and computed the image metrics of total signal, second spatial moment, spatial frequency second moment, and the product of the spatial-spatial frequency moments. We present our analysis of these 16 features. The best performing of the 16 features produced an average separation of three standard deviations between D + and D - and an average detectable rarity of ∼1 in 200. We performed multivariable regression and feature selection to combine multiple features for increased performance and showed an average separation of seven standard deviations between the D + and D - populations making our average detectable rarity of ∼1 in 480. Histograms and receiver operating characteristics (ROC) curves for these features and regressions are presented. We conclude that simple regression analysis holds promise to further improve the separation of rare cells in cytometry applications. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Anatomical curve identification

PubMed Central

Bowman, Adrian W.; Katina, Stanislav; Smith, Joanna; Brown, Denise

2015-01-01

Methods for capturing images in three dimensions are now widely available, with stereo-photogrammetry and laser scanning being two common approaches. In anatomical studies, a number of landmarks are usually identified manually from each of these images and these form the basis of subsequent statistical analysis. However, landmarks express only a very small proportion of the information available from the images. Anatomically defined curves have the advantage of providing a much richer expression of shape. This is explored in the context of identifying the boundary of breasts from an image of the female torso and the boundary of the lips from a facial image. The curves of interest are characterised by ridges or valleys. Key issues in estimation are the ability to navigate across the anatomical surface in three-dimensions, the ability to recognise the relevant boundary and the need to assess the evidence for the presence of the surface feature of interest. The first issue is addressed by the use of principal curves, as an extension of principal components, the second by suitable assessment of curvature and the third by change-point detection. P-spline smoothing is used as an integral part of the methods but adaptations are made to the specific anatomical features of interest. After estimation of the boundary curves, the intermediate surfaces of the anatomical feature of interest can be characterised by surface interpolation. This allows shape variation to be explored using standard methods such as principal components. These tools are applied to a collection of images of women where one breast has been reconstructed after mastectomy and where interest lies in shape differences between the reconstructed and unreconstructed breasts. They are also applied to a collection of lip images where possible differences in shape between males and females are of interest. PMID:26041943

A Dimensionally Aligned Signal Projection for Classification of Unintended Radiated Emissions

DOE PAGES

Vann, Jason Michael; Karnowski, Thomas P.; Kerekes, Ryan; ...

2017-04-24

Characterization of unintended radiated emissions (URE) from electronic devices plays an important role in many research areas from electromagnetic interference to nonintrusive load monitoring to information system security. URE can provide insights for applications ranging from load disaggregation and energy efficiency to condition-based maintenance of equipment-based upon detected fault conditions. URE characterization often requires subject matter expertise to tailor transforms and feature extractors for the specific electrical devices of interest. We present a novel approach, named dimensionally aligned signal projection (DASP), for projecting aligned signal characteristics that are inherent to the physical implementation of many commercial electronic devices. These projectionsmore » minimize the need for an intimate understanding of the underlying physical circuitry and significantly reduce the number of features required for signal classification. We present three possible DASP algorithms that leverage frequency harmonics, modulation alignments, and frequency peak spacings, along with a two-dimensional image manipulation method for statistical feature extraction. To demonstrate the ability of DASP to generate relevant features from URE, we measured the conducted URE from 14 residential electronic devices using a 2 MS/s collection system. Furthermore, a linear discriminant analysis classifier was trained using DASP generated features and was blind tested resulting in a greater than 90% classification accuracy for each of the DASP algorithms and an accuracy of 99.1% when DASP features are used in combination. Furthermore, we show that a rank reduced feature set of the combined DASP algorithms provides a 98.9% classification accuracy with only three features and outperforms a set of spectral features in terms of general classification as well as applicability across a broad number of devices.« less

Task-induced frequency modulation features for brain-computer interfacing

NASA Astrophysics Data System (ADS)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

A Dimensionally Aligned Signal Projection for Classification of Unintended Radiated Emissions

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

Vann, Jason Michael; Karnowski, Thomas P.; Kerekes, Ryan

Characterization of unintended radiated emissions (URE) from electronic devices plays an important role in many research areas from electromagnetic interference to nonintrusive load monitoring to information system security. URE can provide insights for applications ranging from load disaggregation and energy efficiency to condition-based maintenance of equipment-based upon detected fault conditions. URE characterization often requires subject matter expertise to tailor transforms and feature extractors for the specific electrical devices of interest. We present a novel approach, named dimensionally aligned signal projection (DASP), for projecting aligned signal characteristics that are inherent to the physical implementation of many commercial electronic devices. These projectionsmore » minimize the need for an intimate understanding of the underlying physical circuitry and significantly reduce the number of features required for signal classification. We present three possible DASP algorithms that leverage frequency harmonics, modulation alignments, and frequency peak spacings, along with a two-dimensional image manipulation method for statistical feature extraction. To demonstrate the ability of DASP to generate relevant features from URE, we measured the conducted URE from 14 residential electronic devices using a 2 MS/s collection system. Furthermore, a linear discriminant analysis classifier was trained using DASP generated features and was blind tested resulting in a greater than 90% classification accuracy for each of the DASP algorithms and an accuracy of 99.1% when DASP features are used in combination. Furthermore, we show that a rank reduced feature set of the combined DASP algorithms provides a 98.9% classification accuracy with only three features and outperforms a set of spectral features in terms of general classification as well as applicability across a broad number of devices.« less

Controlling the ferroelectric and resistive switching properties of a BiFeO3 thin film prepared using sub-5 nm dimension nanoparticles.

PubMed

Shirolkar, Mandar M; Li, Jieni; Dong, Xiaolei; Li, Ming; Wang, Haiqian

2017-10-04

In recent years, BiFeO 3 has attracted significant attention as an interesting multiferroic material in the exploration of fundamental science and development of novel applications. Our previous study (Phys. Chem. Chem. Phys.18, 2016, 25409) highlighted the interesting physicochemical features of BiFeO 3 of sub-5 nm dimension. The study also accentuated the existence of weak ferroelectricity at sub-5 nm dimensions in BiFeO 3 . Based on this feature, we have prepared thin films using sub-5 nm BiFeO 3 nanoparticles and explored various physicochemical properties of the thin film. We report that during the formation of the thin film, the nanoparticles aggregated; particularly, annihilation of their nanotwinning nature was observed. Qualitatively, the Gibbs free energy change ΔG governed the abovementioned processes. The thin film exhibited an R3c phase and enhanced Bi-O-Fe coordination as compared to the sub-5 nm nanoparticles. Raman spectroscopy under the influence of a magnetic field shows a magnetoelectric effect, spin phonon coupling, and magnetic anisotropy. We report room-temperature ferroelectric behavior in the thin film, which enhances with the application of a magnetic field; this confirms the multiferroic nature of the thin film. The thin film shows polarization switching ability at multiple voltages and read-write operation at low bias (±0.5 V). Furthermore, the thin film shows negative differential-complementary resistive switching behavior in the nano-microampere current range. We report nearly stable 1-bit operation for 10 2 cycles, 10 5 voltage pulses, and 10 5 s, demonstrating the paradigm device applications. The observed results thus show that the thin films prepared using sub-5 nm BiFeO 3 nanoparticles are a promising candidate for future spintronics and memory applications. The reported approach can also be pertinent to explore the physicochemical properties and develop potential applications of several other nanoparticles.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

Jiang, Zhihong; Zhang, Yubao; Wang, Hui; Li, Pei

2013-02-01

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.

Pseudopotential calculations of AlSb under pressure

NASA Astrophysics Data System (ADS)

Algarni, H.; Al-Hagan, O. A.; Bouarissa, N.; Khan, M. A.; Alhuwaymel, T. F.

2018-02-01

The dependence on hydrostatic pressure of the electronic and optical properties of zinc-blende AlSb semiconducting material in the pressure range of 0-20 kbar has been reported using a pseudopotential approach. At zero pressure, our findings showed that the electron and heavy hole effective masses are 0.11 and 0.38 m0, respectively. Moreover, our results yielded values of 3.3289 and 11.08 for refractive index and high frequency dielectric constant, respectively. These results are found to be in good accord with experiment. Upon compression, all physical parameters of interest showed a monotonic behavior. The pressure-induced energy shifts for the optical transition related to band-gaps indicated that AlSb remains an indirect (D-X) band-gap semiconductor at pressures from 0 to 20 kbar. The trend in all features of interest versus pressure has been presented and discussed. It is found that the lattice parameter is reduced from 0.61355 to 0.60705 nm when pressure is raised from 0 to 20 kbar. The present investigation may be useful for mid-infrared lasers applications, detectors and communication devices.

Some of the most interesting CASP11 targets through the eyes of their authors

PubMed Central

Kryshtafovych, Andriy; Moult, John; Baslé, Arnaud; Burgin, Alex; Craig, Timothy K.; Edwards, Robert A.; Fass, Deborah; Hartmann, Marcus D.; Korycinski, Mateusz; Lewis, Richard J.; Lorimer, Donald; Lupas, Andrei N.; Newman, Janet; Peat, Thomas S.; Piepenbrink, Kurt H.; Prahlad, Janani; van Raaij, Mark J.; Rohwer, Forest; Segall, Anca M.; Seguritan, Victor; Sundberg, Eric J.; Singh, Abhimanyu K.; Wilson, Mark A.

2015-01-01

ABSTRACT The Critical Assessment of protein Structure Prediction (CASP) experiment would not have been possible without the prediction targets provided by the experimental structural biology community. In this article, selected crystallographers providing targets for the CASP11 experiment discuss the functional and biological significance of the target proteins, highlight their most interesting structural features, and assess whether these features were correctly reproduced in the predictions submitted to CASP11. Proteins 2016; 84(Suppl 1):34–50. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:26473983

The Starship Philosophy: Its Heritage and Competitors

NASA Astrophysics Data System (ADS)

Ashworth, S.

The distinctive features of the astronautical philosophy characteristic of the current surge of interest in interstellar spaceflight are examined and contrasted with the conflicting features of more Earthbound philosophies in order to elucidate the presentday place and past heritage of the astronautical philosophy in human thought.

Preliminary evaluation of the 15 October 1972 ERTS-1 imagery of east central Ohio (scene 1034-15415)

NASA Technical Reports Server (NTRS)

Pettyjohn, W. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Results of a general, physical interpretation of ERTS-1 imagery of east central Ohio are presented. Special emphasis is placed upon geologic features, such as linear features and hydrologic features. Man-made features are included as a matter of interest and image location. The interpretation is compared to available maps of the area and from this an assessment that ERTS-1 is potentially useful for updating and producing geological maps.

3D local feature BKD to extract road information from mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

2017-08-01

Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

Supervised Learning Applied to Air Traffic Trajectory Classification

NASA Technical Reports Server (NTRS)

Bosson, Christabelle S.; Nikoleris, Tasos

2018-01-01

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Profiling of Intracellular Metabolites: An Approach to Understanding the Characteristic Physiology of Mycobacterium leprae

PubMed Central

Miyamoto, Yuji; Mukai, Tetsu; Matsuoka, Masanori; Kai, Masanori; Maeda, Yumi; Makino, Masahiko

2016-01-01

Mycobacterium leprae is the causative agent of leprosy and also known to possess unique features such as inability to proliferate in vitro. Among the cellular components of M. leprae, various glycolipids present on the cell envelope are well characterized and some of them are identified to be pathogenic factors responsible for intracellular survival in host cells, while other intracellular metabolites, assumed to be associated with basic physiological feature, remain largely unknown. In the present study, to elucidate the comprehensive profile of intracellular metabolites, we performed the capillary electrophoresis-mass spectrometry (CE-MS) analysis on M. leprae and compared to that of M. bovis BCG. Interestingly, comparison of these two profiles showed that, in M. leprae, amino acids and their derivatives are significantly accumulated, but most of intermediates related to central carbon metabolism markedly decreased, implying that M. leprae possess unique metabolic features. The present study is the first report demonstrating the unique profiles of M. leprae metabolites and these insights might contribute to understanding undefined metabolism of M. leprae as well as pathogenic characteristics related to the manifestation of the disease. PMID:27479467

Using spectral information in forensic imaging.

PubMed

Miskelly, Gordon M; Wagner, John H

2005-12-20

Improved detection of forensic evidence by combining narrow band photographic images taken at a range of wavelengths is dependent on the substance of interest having a significantly different spectrum from the underlying substrate. While some natural substances such as blood have distinctive spectral features which are readily distinguished from common colorants, this is not true for visualization agents commonly used in forensic science. We now show that it is possible to select reagents with narrow spectral features that lead to increased visibility using digital cameras and computer image enhancement programs even if their coloration is much less intense to the unaided eye than traditional reagents. The concept is illustrated by visualising latent fingermarks on paper with the zinc complex of Ruhemann's Purple, cyanoacrylate-fumed fingerprints with Eu(tta)(3)(phen), and soil prints with 2,6-bis(benzimidazol-2-yl)-4-[4'-(dimethylamino)phenyl]pyridine [BBIDMAPP]. In each case background correction is performed at one or two wavelengths bracketing the narrow absorption or emission band of these compounds. However, compounds with sharp spectral features would also lead to improved detection using more advanced algorithms such as principal component analysis.

Characterization and recognition of mixed emotional expressions in thermal face image

NASA Astrophysics Data System (ADS)

Saha, Priya; Bhattacharjee, Debotosh; De, Barin K.; Nasipuri, Mita

2016-05-01

Facial expressions in infrared imaging have been introduced to solve the problem of illumination, which is an integral constituent of visual imagery. The paper investigates facial skin temperature distribution on mixed thermal facial expressions of our created face database where six are basic expressions and rest 12 are a mixture of those basic expressions. Temperature analysis has been performed on three facial regions of interest (ROIs); periorbital, supraorbital and mouth. Temperature variability of the ROIs in different expressions has been measured using statistical parameters. The temperature variation measurement in ROIs of a particular expression corresponds to a vector, which is later used in recognition of mixed facial expressions. Investigations show that facial features in mixed facial expressions can be characterized by positive emotion induced facial features and negative emotion induced facial features. Supraorbital is a useful facial region that can differentiate basic expressions from mixed expressions. Analysis and interpretation of mixed expressions have been conducted with the help of box and whisker plot. Facial region containing mixture of two expressions is generally less temperature inducing than corresponding facial region containing basic expressions.

Controlling destructive quantum interference in tunneling junctions comprising self-assembled monolayers via bond topology and functional groups† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c8sc00165k

PubMed Central

Zhang, Yanxi; Ye, Gang; Soni, Saurabh; Qiu, Xinkai; Krijger, Theodorus L.; Jonkman, Harry T.; Carlotti, Marco; Sauter, Eric; Zharnikov, Michael

2018-01-01

Quantum interference effects (QI) are of interest in nano-scale devices based on molecular tunneling junctions because they can affect conductance exponentially through minor structural changes. However, their utilization requires the prediction and deterministic control over the position and magnitude of QI features, which remains a significant challenge. In this context, we designed and synthesized three benzodithiophenes based molecular wires; one linearly-conjugated, one cross-conjugated and one cross-conjugated quinone. Using eutectic Ga–In (EGaIn) and CP-AFM, we compared them to a well-known anthraquinone in molecular junctions comprising self-assembled monolayers (SAMs). By combining density functional theory and transition voltage spectroscopy, we show that the presence of an interference feature and its position can be controlled independently by manipulating bond topology and electronegativity. This is the first study to separate these two parameters experimentally, demonstrating that the conductance of a tunneling junction depends on the position and depth of a QI feature, both of which can be controlled synthetically. PMID:29896382

Neutron Tomography and X-ray Tomography as Tools for the Morphological Investigation of Non-mammalian Synapsids

NASA Astrophysics Data System (ADS)

Laaß, Michael; Schillinger, Burkhard; Werneburg, Ingmar

As having evolved on the stem line of mammals, the taxonomy and phylogeny of therapsids (Synapsida) are of special interest with respect to early mammalian evolution. Due to the fact that in most cases soft tissue of fossil vertebrates is not preserved, species can only be distinguished by diagnosis of morphological features of the skeleton. Moreover, investigations of vertebrate fossils are often obstructed, because internal cranial anatomy is usually hidden and parts of the fossils may be embedded in stone matrix. As a consequence, most species of non-mammalian synapsids were only defined on the basis of external skeletal features. Our investigations on Diictodon skulls (Therapsida, Anomodontia) show that non-destructive methods are very useful to clearly distinguish fossil species. We, therefore, propose using modern non-destructive techniques such as neutron tomography, synchrotron tomography, and micro-computed tomography (μCT) as standard tools for the investigation and virtual reconstruction of fossils and to include features of the internal cranial anatomy into morphological descriptions and phylogenetic analyses of fossil vertebrates.

Investigating Mars: Russell Crater

NASA Image and Video Library

2017-08-01

This image shows individual dunes on the floor of Russell Crater. These dunes are in the southern part of the dune field. Russell Crater is located in Noachis Terra. A spectacular dune ridge and other dune forms on the crater floor have caused extensive imaging. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! https://photojournal.jpl.nasa.gov/catalog/PIA21799

Profiling of Intracellular Metabolites: An Approach to Understanding the Characteristic Physiology of Mycobacterium leprae.

PubMed

Miyamoto, Yuji; Mukai, Tetsu; Matsuoka, Masanori; Kai, Masanori; Maeda, Yumi; Makino, Masahiko

2016-08-01

Mycobacterium leprae is the causative agent of leprosy and also known to possess unique features such as inability to proliferate in vitro. Among the cellular components of M. leprae, various glycolipids present on the cell envelope are well characterized and some of them are identified to be pathogenic factors responsible for intracellular survival in host cells, while other intracellular metabolites, assumed to be associated with basic physiological feature, remain largely unknown. In the present study, to elucidate the comprehensive profile of intracellular metabolites, we performed the capillary electrophoresis-mass spectrometry (CE-MS) analysis on M. leprae and compared to that of M. bovis BCG. Interestingly, comparison of these two profiles showed that, in M. leprae, amino acids and their derivatives are significantly accumulated, but most of intermediates related to central carbon metabolism markedly decreased, implying that M. leprae possess unique metabolic features. The present study is the first report demonstrating the unique profiles of M. leprae metabolites and these insights might contribute to understanding undefined metabolism of M. leprae as well as pathogenic characteristics related to the manifestation of the disease.

Parenting, relational aggression, and borderline personality features: associations over time in a Russian longitudinal sample.

PubMed

Nelson, David A; Coyne, Sarah M; Swanson, Savannah M; Hart, Craig H; Olsen, Joseph A

2014-08-01

Crick, Murray-Close, and Woods (2005) encouraged the study of relational aggression as a developmental precursor to borderline personality features in children and adolescents. A longitudinal study is needed to more fully explore this association, to contrast potential associations with physical aggression, and to assess generalizability across various cultural contexts. In addition, parenting is of particular interest in the prediction of aggression or borderline personality disorder. Early aggression and parenting experiences may differ in their long-term prediction of aggression or borderline features, which may have important implications for early intervention. The currrent study incorporated a longitudinal sample of preschool children (84 boys, 84 girls) living in intact, two-parent biological households in Voronezh, Russia. Teachers provided ratings of children's relational and physical aggression in preschool. Mothers and fathers also self-reported their engagement in authoritative, authoritarian, permissive, and psychological controlling forms of parenting with their preschooler. A decade later, 70.8% of the original child participants consented to a follow-up study in which they completed self-reports of relational and physical aggression and borderline personality features. The multivariate results of this study showed that preschool relational aggression in girls predicted adolescent relational aggression. Preschool aversive parenting (i.e., authoritarian, permissive, and psychologically controlling forms) significantly predicted aggression and borderline features in adolescent females. For adolescent males, preschool authoritative parenting served as a protective factor against aggression and borderline features, whereas authoritarian parenting was a risk factor for later aggression.

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis

PubMed Central

Lee, Seong-Whan

2014-01-01

Recently, there have been great interests for computer-aided diagnosis of Alzheimer’s disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tissue volumes from MRI, and mean signal intensities from PET, in this paper, we propose a deep learning-based latent feature representation with a stacked auto-encoder (SAE). We believe that there exist latent non-linear complicated patterns inherent in the low-level features such as relations among features. Combining the latent information with the original features helps build a robust model in AD/MCI classification, with high diagnostic accuracy. Furthermore, thanks to the unsupervised characteristic of the pre-training in deep learning, we can benefit from the target-unrelated samples to initialize parameters of SAE, thus finding optimal parameters in fine-tuning with the target-related samples, and further enhancing the classification performances across four binary classification problems: AD vs. healthy normal control (HC), MCI vs. HC, AD vs. MCI, and MCI converter (MCI-C) vs. MCI non-converter (MCI-NC). In our experiments on ADNI dataset, we validated the effectiveness of the proposed method, showing the accuracies of 98.8, 90.7, 83.7, and 83.3 % for AD/HC, MCI/HC, AD/MCI, and MCI-C/MCI-NC classification, respectively. We believe that deep learning can shed new light on the neuroimaging data analysis, and our work presented the applicability of this method to brain disease diagnosis. PMID:24363140

New implementation of a shear-force microscope suitable to study topographical features over wide areas

NASA Astrophysics Data System (ADS)

Ustione, A.; Cricenti, A.; Piacentini, M.; Felici, A. C.

2006-09-01

A new implementation of a shear-force microscope is described that uses a shear-force detection system to perform topographical imaging of large areas (˜1×1mm2). This implementation finds very interesting application in the study of archeological or artistic samples. Three dc motors are used to move a sample during a scan, allowing the probe tip to follow the surface and to face height differences of several tens of micrometers. This large-area topographical imaging mode exploits new subroutines that were added to the existing homemade software; these subroutines were created in Microsoft VISUAL BASIC 6.0 programming language. With this new feature our shear-force microscope can be used to study topographical details over large areas of archaeological samples in a nondestructive way. We show results detecting worn reliefs over a coin.

A comprehensive overview of the applications of artificial life.

PubMed

Kim, Kyung-Joong; Cho, Sung-Bae

2006-01-01

We review the applications of artificial life (ALife), the creation of synthetic life on computers to study, simulate, and understand living systems. The definition and features of ALife are shown by application studies. ALife application fields treated include robot control, robot manufacturing, practical robots, computer graphics, natural phenomenon modeling, entertainment, games, music, economics, Internet, information processing, industrial design, simulation software, electronics, security, data mining, and telecommunications. In order to show the status of ALife application research, this review primarily features a survey of about 180 ALife application articles rather than a selected representation of a few articles. Evolutionary computation is the most popular method for designing such applications, but recently swarm intelligence, artificial immune network, and agent-based modeling have also produced results. Applications were initially restricted to the robotics and computer graphics, but presently, many different applications in engineering areas are of interest.

Learning discriminative features from RGB-D images for gender and ethnicity identification

NASA Astrophysics Data System (ADS)

Azzakhnini, Safaa; Ballihi, Lahoucine; Aboutajdine, Driss

2016-11-01

The development of sophisticated sensor technologies gave rise to an interesting variety of data. With the appearance of affordable devices, such as the Microsoft Kinect, depth-maps and three-dimensional data became easily accessible. This attracted many computer vision researchers seeking to exploit this information in classification and recognition tasks. In this work, the problem of face classification in the context of RGB images and depth information (RGB-D images) is addressed. The purpose of this paper is to study and compare some popular techniques for gender recognition and ethnicity classification to understand how much depth data can improve the quality of recognition. Furthermore, we investigate which combination of face descriptors, feature selection methods, and learning techniques is best suited to better exploit RGB-D images. The experimental results show that depth data improve the recognition accuracy for gender and ethnicity classification applications in many use cases.

The dielectric signature of glass density

NASA Astrophysics Data System (ADS)

Rams-Baron, M.; Wojnarowska, Z.; Knapik-Kowalczuk, J.; Jurkiewicz, K.; Burian, A.; Wojtyniak, M.; Pionteck, J.; Jaworska, M.; Rodríguez-Tinoco, C.; Paluch, M.

2017-09-01

At present, we are witnessing a renewed interest in the properties of densified glasses prepared by isobaric cooling of a liquid at elevated pressure. As high-pressure densification emerges as a promising approach in the development of glasses with customized features, understanding and controlling their unique properties represent a contemporary scientific and technological goal. The results presented herein indicate that the applied high-pressure preparation route leads to a glassy state with higher density (˜1%) and a reduced free volume of about 7%. We show that these subtle structural changes remarkably influence the dielectric response and spectral features of β-relaxation in etoricoxib glass. Our study, combining dynamical and structural techniques, reveal that β-relaxation in etoricoxib is extremely sensitive to the variations in molecular packing and can be used to probe the changes in glass density. Such connection is technologically relevant and may advance further progress in the field.

Constructing networks with correlation maximization methods.

PubMed

Mellor, Joseph C; Wu, Jie; Delisi, Charles

2004-01-01

Problems of inference in systems biology are ideally reduced to formulations which can efficiently represent the features of interest. In the case of predicting gene regulation and pathway networks, an important feature which describes connected genes and proteins is the relationship between active and inactive forms, i.e. between the "on" and "off" states of the components. While not optimal at the limits of resolution, these logical relationships between discrete states can often yield good approximations of the behavior in larger complex systems, where exact representation of measurement relationships may be intractable. We explore techniques for extracting binary state variables from measurement of gene expression, and go on to describe robust measures for statistical significance and information that can be applied to many such types of data. We show how statistical strength and information are equivalent criteria in limiting cases, and demonstrate the application of these measures to simple systems of gene regulation.

A Relational Encoding of a Conceptual Model with Multiple Temporal Dimensions

NASA Astrophysics Data System (ADS)

Gubiani, Donatella; Montanari, Angelo

The theoretical interest and the practical relevance of a systematic treatment of multiple temporal dimensions is widely recognized in the database and information system communities. Nevertheless, most relational databases have no temporal support at all. A few of them provide a limited support, in terms of temporal data types and predicates, constructors, and functions for the management of time values (borrowed from the SQL standard). One (resp., two) temporal dimensions are supported by historical and transaction-time (resp., bitemporal) databases only. In this paper, we provide a relational encoding of a conceptual model featuring four temporal dimensions, namely, the classical valid and transaction times, plus the event and availability times. We focus our attention on the distinctive technical features of the proposed temporal extension of the relation model. In the last part of the paper, we briefly show how to implement it in a standard DBMS.

Thermal characterization of QSH crashes in RFX-mod

NASA Astrophysics Data System (ADS)

Fassina, Alessandro; Gobbin, Marco; Franz, Paolo; Marrelli, Lionello; Ruzzon, Alberto

2012-10-01

QSH (Quasi Single Helicity) states have gained a growing interest in RFP research since they show improved confinement and transport features with respect to standard discharges. However, ITBs associated with QSH states can be obtained only in a transient way, and in general with a shorter lifetime with respect to that of the QSH phase [1]. In this work the analysis has essentially the purpose of confirming, with TS data, the Te dynamics seen with the double filter, multichord SXR spectrometer in [1]: TS data allow a better spatial definition of temperature profile and a more reliable description of plasma edge. Te profile features in rising and crashing phases are determined via ensemble averaging, possible precursors of thermal crashes are identified, while q(r) behavior is studied identifying the thermal structures associated with rational surfaces. [4pt] [1] Ruzzon et al, 39th EPS Conference, P2.023

Rimmed vacuoles in Becker muscular dystrophy have similar features with inclusion myopathies.

PubMed

Momma, Kazunari; Noguchi, Satoru; Malicdan, May Christine V; Hayashi, Yukiko K; Minami, Narihiro; Kamakura, Keiko; Nonaka, Ikuya; Nishino, Ichizo

2012-01-01

Rimmed vacuoles in myofibers are thought to be due to the accumulation of autophagic vacuoles, and can be characteristic in certain myopathies with protein inclusions in myofibers. In this study, we performed a detailed clinical, molecular, and pathological characterization of Becker muscular dystrophy patients who have rimmed vacuoles in muscles. Among 65 Becker muscular dystrophy patients, we identified 12 patients who have rimmed vacuoles and 11 patients who have deletions in exons 45-48 in DMD gene. All patients having rimmed vacuoles showed milder clinical features compared to those without rimmed vacuoles. Interestingly, the rimmed vacuoles in Becker muscular dystrophy muscles seem to represent autophagic vacuoles and are also associated with polyubiquitinated protein aggregates. These findings support the notion that rimmed vacuoles can appear in Becker muscular dystrophy, and may be related to the chronic changes in muscle pathology induced by certain mutations in the DMD gene.

Comparative NEXAFS study of the selected icefish hard tissues and hydroxyapatite

NASA Astrophysics Data System (ADS)

Petrova, O. V.; Nekipelov, S. V.; Sivkov, D. V.; Mingaleva, A. E.; Nikolaev, A.; Frank-Kamenetskaya, O. V.; Bazhenov, V. V.; Vyalikh, D. V.; Molodtsov, S. L.; Sivkov, V. N.; Ehrlich, H.

2017-11-01

The structure of native Champsocephalus gunnari icefish otoliths, scales, teeth, bones and pristine hydroxyapatite (HA) were examined using Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy. NEXAFS Cls-absorption spectra of the selected icefish hard tissues indicate that otoliths contain anion [CO3]2-. NEXAFS P2p-spectra clearly indicate the absence of phosphorus atoms only within otoliths and scales samples. However, the icefish teeth and bones P2p-spectra demonstrate identical spectral feature typical for the HA. NEXAFS Ca2p-spectra of the icefish hard tissues studied also shows features, which are in good correspondence with HA spectra. Interestingly, there is a red shift ≈ 0.1 eV of the 2p1/2,3/2 → 3d transition energies in NEXAFS Ca2p-spectra of teethes and bones of the C. gunnari in comparison to HA.

Analysis of macrolinguistic aspects of narratives from individuals with Alzheimer's disease, mild cognitive impairment, and no cognitive impairment.

PubMed

Toledo, Cíntia Matsuda; Aluísio, Sandra Maria; Dos Santos, Leandro Borges; Brucki, Sonia Maria Dozzi; Trés, Eduardo Sturzeneker; de Oliveira, Maira Okada; Mansur, Letícia Lessa

2018-01-01

The depiction of features in discourse production promotes accurate diagnosis and helps to establish the therapeutic intervention in cognitive impairment and dementia. We aimed to identify alterations in the macrolinguistic aspects of discourse using a new computational tool. Sixty individuals, aged 60 years and older, were distributed in three different groups: mild Alzheimer's disease (mAD), amnestic mild cognitive impairment, and healthy controls. A narrative created by individuals was analyzed through the Coh-Metrix-Dementia program, extracting the features of interest automatically. mAD showed worse overall performance compared to the other groups: less informative discourse, greater impairment in global coherence, greater modalization, and inferior narrative structure. It was not possible to discriminate between amnestic mild cognitive impairment and healthy controls. Our results are in line with the literature, verifying a pathological change in the macrostructure of discourse in mAD.

ARC-1980-A80-7034

NASA Image and Video Library

1980-11-12

Range : 660,000 kilometers (400,000 miles) Time : 5:05 am PST This Voyager 1 picture of Mimas shows a large impact structure at 110 degrees W Long., located on that face of the moon which leads Mimas in its orbit. The feature, about 130 kilometers in diameter (80 miles), is more than 1/4 the diameter of the entire moon. This is a particularly interesting feature in view of its large diameter compared with the size of the satellite, and may have the largest crater diameter/satillite diameter ratio in the solar system. The crater has a raised rim and central peak, typical of large impact structures on terrestrial planets. Additional smaller craters, 15-45 kilometers in diameter, can be seen scattered across the surface, particularly alon the terminator. Mimas is one of the smaller Saturnian satellites with a low density implying its chief component is ice.

Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

PubMed

Li, Xiaolu; Liang, Yu

2015-05-20

Analysis of light detection and ranging (LiDAR) intensity data to extract surface features is of great interest in remote sensing research. One potential application of LiDAR intensity data is target classification. A new bidirectional reflectance distribution function (BRDF) model is derived for target characterization of rough and smooth surfaces. Based on the geometry of our coaxial full-waveform LiDAR system, the integration method is improved through coordinate transformation to establish the relationship between the BRDF model and intensity data of LiDAR. A series of experiments using typical urban building materials are implemented to validate the proposed BRDF model and integration method. The fitting results show that three parameters extracted from the proposed BRDF model can distinguish the urban building materials from perspectives of roughness, specular reflectance, and diffuse reflectance. A comprehensive analysis of these parameters will help characterize surface features in a physically rigorous manner.

Frederick Novy and the 1901 San Francisco plague commission investigation.

PubMed

Kazanjian, Powel

2012-11-15

The 1900 San Francisco plague is a significant event in which citizens, physicians, and public health officials denied a diagnosis of plague on economic, political, and social grounds. To resolve the controversy, Surgeon General Walter Wyman appointed an independent federal commission of university-based experts to investigate whether plague was present. I use the activities of Frederick Novy, the commission bacteriologist and professor at the University of Michigan, to explore one circumstance in which bacteriology attempted to redefine traditional conceptions of disease during the early germ era. Novy showed plague was present in the city but without its characteristic clinical features and devastating epidemiological pattern. Physicians who understood plague by its classic features, however, contested Novy's scientific evidence. His bacteriologic redefinition had no special authority to prevail over opposing conceptions about plague; it was accepted and acted upon once it served the overall interest of the city--to avert a trade embargo.

When Interpolation-Induced Reflection Artifact Meets Time-Frequency Analysis.

PubMed

Lin, Yu-Ting; Flandrin, Patrick; Wu, Hau-Tieng

2016-10-01

While extracting the temporal dynamical features based on the time-frequency analyses, like the reassignment and synchrosqueezing transform, attracts more and more interest in biomedical data analysis, we should be careful about artifacts generated by interpolation schemes, in particular when the sampling rate is not significantly higher than the frequency of the oscillatory component we are interested in. We formulate the problem called the reflection effect and provide a theoretical justification of the statement. We also show examples in the anesthetic depth analysis with clear but undesirable artifacts. The artifact associated with the reflection effect exists not only theoretically but practically as well. Its influence is pronounced when we apply the time-frequency analyses to extract the time-varying dynamics hidden inside the signal. We have to carefully deal with the artifact associated with the reflection effect by choosing a proper interpolation scheme.

Resonant tunneling diode based on band gap engineered graphene antidot structures

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

Palla, Penchalaiah, E-mail: penchalaiah.palla@vit.ac.in; Ethiraj, Anita S.; Raina, J. P.

The present work demonstrates the operation and performance of double barrier Graphene Antidot Resonant Tunnel Diode (DBGA-RTD). Non-Equilibrium Green’s Function (NEGF) frame work with tight-binding Hamiltonian and 2-D Poisson equations were solved self-consistently for device study. The interesting feature in this device is that it is an all graphene RTD with band gap engineered graphene antidot tunnel barriers. Another interesting new finding is that it shows negative differential resistance (NDR), which involves the resonant tunneling in the graphene quantum well through both the electron and hole bound states. The Graphene Antidot Lattice (GAL) barriers in this device efficiently improved themore » Peak to Valley Ratio to approximately 20 even at room temperature. A new fitting model is developed for the number of antidots and their corresponding effective barrier width, which will help in determining effective barrier width of any size of actual antidot geometry.« less

ScMO(BO3) (M = Ca and Cd): new Sc-based oxyborates featuring interesting edge-sharing sandwich-like chains and UV cut-off edges.

PubMed

Ma, Ruru; Xu, Dongdong; Yang, Yun; Su, Xin; Lei, Binghua; Yang, Zhihua; Pan, Shilie

2017-11-07

Two new isostructural rare-earth oxyborates ScMO(BO 3 ) (M = Ca and Cd) with a three-dimensional (3D) cationic framework and parallel arranged [BO 3 ] triangles have been synthesized by the flux method. In the 3D cationic framework, an interesting sandwich-like basic building unit (BBU) is constructed by two [Ca(1)O 4 ] 6- chains and two [Sc(1)O 4 ] 5- chains. ScMO(BO 3 ) melt incongruently, which shows that title compounds can be grown by the flux method. The UV cut-off edges for ScCaO(BO 3 ) and ScCdO(BO 3 ) are 230 and 249 nm, respectively. In addition, the first-principles calculations are performed to gain further insights into the relationship between the microscopic electronic structures and associated optical properties.

Improved binding affinity and interesting selectivities of aminopyrimidine-bearing carbohydrate receptors in comparison with their aminopyridine analogues.

PubMed

Lippe, Jan; Seichter, Wilhelm; Mazik, Monika

2015-12-28

Due to the problems with the exact prediction of the binding properties of an artificial carbohydrate receptor, the identification of characteristic structural features, having the ability to influence the binding properties in a predictable way, is of high importance. The purpose of our investigation was to examine whether the previously observed higher affinity of 2-aminopyrimidine-bearing carbohydrate receptors in comparison with aminopyridine substituted analogues represents a general tendency of aminopyrimidine-bearing compounds. Systematic binding studies on new compounds consisting of 2-aminopyrimidine groups confirmed such a tendency and allowed the identification of interesting structure-activity relationships. Receptors having different symmetries showed systematic preferences for specific glycosides, which are remarkable for such simple receptor systems. Particularly suitable receptor architectures for the recognition of selected glycosides were identified and represent a valuable base for further developments in this field.

Self-appraisals and episodic memory: Different psychological factors related to patient versus informant reports of apathy in severe traumatic brain injury.

PubMed

Arnould, Annabelle; Rochat, Lucien; Azouvi, Philippe; van der Linden, Martial

2018-01-09

Apathy is a core feature in patients with traumatic brain injury (TBI). The psychological processes underlying apathy are still unclear, and the few studies conducted on this subject have essentially focused on cognitive processes and informant reports of apathetic manifestations. The aims of the present study were to examine self-reports versus informant reports of diminished initiative/interest, as well as their relationship with different cognitive factors (attention/executive mechanisms, episodic memory, and multitasking) and personal identity factors (self-esteem and self-efficacy beliefs). To this end, 74 participants (38 patients with severe TBI matched with 36 control participants) were given three questionnaires to assess self-esteem, general self-efficacy beliefs, and anxio-depressive symptoms and five tasks to assess cognitive processes, including real-life multitasking. In addition, a questionnaire that assessed self-awareness of functional competencies and a questionnaire that assessed lack of initiative/interest were administered to each participant and their relatives. The main results showed that patients demonstrated an awareness of their lack of initiative/interest and that self-reported lack of initiative/interest was best predicted by low general self-efficacy beliefs and self-esteem, whereas informant-reported lack of initiative/interest was predicted by episodic memory difficulties. These results shed new light on the psychological processes related to apathetic manifestations, as well as the differing perspectives and lived experiences of patients and external observers in the TBI population, which opens interesting prospects for psychological interventions.

SU-F-R-31: Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease

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

Choi, W; Riyahi, S; Lu, W

Purpose: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. Methods: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor). 27 texture features (9 from intensity histogram, 8 from grey-level co-occurrence matrix [GLCM] and 10 from grey-level run-length matrix [GLRM])more » were extracted from [normal lung-GTV]. To measure the variability of a feature F, the relative difference D=|Fref -Fsim|/Fref*100% was calculated, where Fref was for the entire normal lung and Fsim was for [normal lung-GTV]. A feature was considered as robust if the largest non-outlier (Q3+1.5*IQR) D was less than 5%, and considered as not correlated with normal lung volume when their Pearson correlation was lower than 0.50. Results: Only 11 features were robust. All first-order intensity-histogram features (mean, max, etc.) were robust, while most higher-order features (skewness, kurtosis, etc.) were unrobust. Only two of the GLCM and four of the GLRM features were robust. Larger GTV resulted greater feature variation, this was particularly true for unrobust features. All robust features were not correlated with normal lung volume while three unrobust features showed high correlation. Excessive variations were observed in two low grey-level run features and were later identified to be from one patient with local lung diseases (atelectasis) in the normal lung. There was no dependence on GTV location. Conclusion: We identified 11 robust normal lung CT texture features that can be further examined for the prediction of radiation-induced lung disease. Interestingly, low grey-level run features identified normal lung diseases. This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

Identifying the optimal segmentors for mass classification in mammograms

NASA Astrophysics Data System (ADS)

Zhang, Yu; Tomuro, Noriko; Furst, Jacob; Raicu, Daniela S.

2015-03-01

In this paper, we present the results of our investigation on identifying the optimal segmentor(s) from an ensemble of weak segmentors, used in a Computer-Aided Diagnosis (CADx) system which classifies suspicious masses in mammograms as benign or malignant. This is an extension of our previous work, where we used various parameter settings of image enhancement techniques to each suspicious mass (region of interest (ROI)) to obtain several enhanced images, then applied segmentation to each image to obtain several contours of a given mass. Each segmentation in this ensemble is essentially a "weak segmentor" because no single segmentation can produce the optimal result for all images. Then after shape features are computed from the segmented contours, the final classification model was built using logistic regression. The work in this paper focuses on identifying the optimal segmentor(s) from an ensemble mix of weak segmentors. For our purpose, optimal segmentors are those in the ensemble mix which contribute the most to the overall classification rather than the ones that produced high precision segmentation. To measure the segmentors' contribution, we examined weights on the features in the derived logistic regression model and computed the average feature weight for each segmentor. The result showed that, while in general the segmentors with higher segmentation success rates had higher feature weights, some segmentors with lower segmentation rates had high classification feature weights as well.

What automated age estimation of hand and wrist MRI data tells us about skeletal maturation in male adolescents.

PubMed

Urschler, Martin; Grassegger, Sabine; Štern, Darko

2015-01-01

Age estimation of individuals is important in human biology and has various medical and forensic applications. Recent interest in MR-based methods aims to investigate alternatives for established methods involving ionising radiation. Automatic, software-based methods additionally promise improved estimation objectivity. To investigate how informative automatically selected image features are regarding their ability to discriminate age, by exploring a recently proposed software-based age estimation method for MR images of the left hand and wrist. One hundred and two MR datasets of left hand images are used to evaluate age estimation performance, consisting of bone and epiphyseal gap volume localisation, computation of one age regression model per bone mapping image features to age and fusion of individual bone age predictions to a final age estimate. Quantitative results of the software-based method show an age estimation performance with a mean absolute difference of 0.85 years (SD = 0.58 years) to chronological age, as determined by a cross-validation experiment. Qualitatively, it is demonstrated how feature selection works and which image features of skeletal maturation are automatically chosen to model the non-linear regression function. Feasibility of automatic age estimation based on MRI data is shown and selected image features are found to be informative for describing anatomical changes during physical maturation in male adolescents.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

CCD-Based Skinning Injury Recognition on Potato Tubers (Solanum tuberosum L.): A Comparison between Visible and Biospeckle Imaging

PubMed Central

Gao, Yingwang; Geng, Jinfeng; Rao, Xiuqin; Ying, Yibin

2016-01-01

Skinning injury on potato tubers is a kind of superficial wound that is generally inflicted by mechanical forces during harvest and postharvest handling operations. Though skinning injury is pervasive and obstructive, its detection is very limited. This study attempted to identify injured skin using two CCD (Charge Coupled Device) sensor-based machine vision technologies, i.e., visible imaging and biospeckle imaging. The identification of skinning injury was realized via exploiting features extracted from varied ROIs (Region of Interests). The features extracted from visible images were pixel-wise color and texture features, while region-wise BA (Biospeckle Activity) was calculated from biospeckle imaging. In addition, the calculation of BA using varied numbers of speckle patterns were compared. Finally, extracted features were implemented into classifiers of LS-SVM (Least Square Support Vector Machine) and BLR (Binary Logistic Regression), respectively. Results showed that color features performed better than texture features in classifying sound skin and injured skin, especially for injured skin stored no less than 1 day, with the average classification accuracy of 90%. Image capturing and processing efficiency can be speeded up in biospeckle imaging, with captured 512 frames reduced to 125 frames. Classification results obtained based on the feature of BA were acceptable for early skinning injury stored within 1 day, with the accuracy of 88.10%. It is concluded that skinning injury can be recognized by visible and biospeckle imaging during different stages. Visible imaging has the aptitude in recognizing stale skinning injury, while fresh injury can be discriminated by biospeckle imaging. PMID:27763555

CCD-Based Skinning Injury Recognition on Potato Tubers (Solanum tuberosum L.): A Comparison between Visible and Biospeckle Imaging.

PubMed

Gao, Yingwang; Geng, Jinfeng; Rao, Xiuqin; Ying, Yibin

2016-10-18

Skinning injury on potato tubers is a kind of superficial wound that is generally inflicted by mechanical forces during harvest and postharvest handling operations. Though skinning injury is pervasive and obstructive, its detection is very limited. This study attempted to identify injured skin using two CCD (Charge Coupled Device) sensor-based machine vision technologies, i.e., visible imaging and biospeckle imaging. The identification of skinning injury was realized via exploiting features extracted from varied ROIs (Region of Interests). The features extracted from visible images were pixel-wise color and texture features, while region-wise BA (Biospeckle Activity) was calculated from biospeckle imaging. In addition, the calculation of BA using varied numbers of speckle patterns were compared. Finally, extracted features were implemented into classifiers of LS-SVM (Least Square Support Vector Machine) and BLR (Binary Logistic Regression), respectively. Results showed that color features performed better than texture features in classifying sound skin and injured skin, especially for injured skin stored no less than 1 day, with the average classification accuracy of 90%. Image capturing and processing efficiency can be speeded up in biospeckle imaging, with captured 512 frames reduced to 125 frames. Classification results obtained based on the feature of BA were acceptable for early skinning injury stored within 1 day, with the accuracy of 88.10%. It is concluded that skinning injury can be recognized by visible and biospeckle imaging during different stages. Visible imaging has the aptitude in recognizing stale skinning injury, while fresh injury can be discriminated by biospeckle imaging.

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Detection of reflecting surfaces by a statistical model

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Chee-Hung H.

2009-02-01

Remote sensing is widely used assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, current research on automated feature extraction is ignorant of contextual information. As a result, the fidelity of populating attributes corresponding to interesting features and objects cannot be satisfied. In this paper, we present an exploration on meaningful object extraction integrating reflecting surfaces. Detection of specular reflecting surfaces can be useful in target identification and then can be applied to environmental monitoring, disaster prediction and analysis, military, and counter-terrorism. Our method is based on a statistical model to capture the statistical properties of specular reflecting surfaces. And then the reflecting surfaces are detected through cluster analysis.

Non-specific filtering of beta-distributed data.

PubMed

Wang, Xinhui; Laird, Peter W; Hinoue, Toshinori; Groshen, Susan; Siegmund, Kimberly D

2014-06-19

Non-specific feature selection is a dimension reduction procedure performed prior to cluster analysis of high dimensional molecular data. Not all measured features are expected to show biological variation, so only the most varying are selected for analysis. In DNA methylation studies, DNA methylation is measured as a proportion, bounded between 0 and 1, with variance a function of the mean. Filtering on standard deviation biases the selection of probes to those with mean values near 0.5. We explore the effect this has on clustering, and develop alternate filter methods that utilize a variance stabilizing transformation for Beta distributed data and do not share this bias. We compared results for 11 different non-specific filters on eight Infinium HumanMethylation data sets, selected to span a variety of biological conditions. We found that for data sets having a small fraction of samples showing abnormal methylation of a subset of normally unmethylated CpGs, a characteristic of the CpG island methylator phenotype in cancer, a novel filter statistic that utilized a variance-stabilizing transformation for Beta distributed data outperformed the common filter of using standard deviation of the DNA methylation proportion, or its log-transformed M-value, in its ability to detect the cancer subtype in a cluster analysis. However, the standard deviation filter always performed among the best for distinguishing subgroups of normal tissue. The novel filter and standard deviation filter tended to favour features in different genome contexts; for the same data set, the novel filter always selected more features from CpG island promoters and the standard deviation filter always selected more features from non-CpG island intergenic regions. Interestingly, despite selecting largely non-overlapping sets of features, the two filters did find sample subsets that overlapped for some real data sets. We found two different filter statistics that tended to prioritize features with different characteristics, each performed well for identifying clusters of cancer and non-cancer tissue, and identifying a cancer CpG island hypermethylation phenotype. Since cluster analysis is for discovery, we would suggest trying both filters on any new data sets, evaluating the overlap of features selected and clusters discovered.

Long-range dependence and multifractality in the term structure of LIBOR interest rates

NASA Astrophysics Data System (ADS)

Cajueiro, Daniel O.; Tabak, Benjamin M.

2007-01-01

In this paper we present evidence of long-range dependence in LIBOR interest rates. We study a data set from 2000 to 2005, for six different currencies and various maturities. Empirical results suggest that the degree of long-range dependence decreases with maturity, with the exception of interest rates on Japanese Yen and on Indonesian Rupiah. Furthermore, interest rates have a multifractal nature and the degree of multifractality is much stronger for Indonesia (emerging market). These findings suggest that interest rates derivatives should take these features into account. Furthermore, fixed income risk and portfolio management should incorporate long-range dependence in the modeling of interest rates.

Mature orbital teratoma with an ectopic tooth and primary anophthalmos.

PubMed

Chawla, Bhavna; Chauhan, Kanchan; Kashyap, Seema

2013-02-01

To describe the clinicopathologic features and management of an unusual case of orbital teratoma. A 7-year-old girl presented with a history of an orbital mass since birth. CT scan showed a large mass lesion involving the right orbit, with absence of the eyeball. An ectopic tooth was identified within the tumor. Lid-sparing exenteration surgery was performed. Histopathologic examination of the excised mass showed presence of elements from all three germ layers, consistent with a diagnosis of mature orbital teratoma. Normal ocular structures were not identified on histopathology. At one year follow-up, there was no tumor recurrence. We report an extremely rare and interesting case of a mature orbital teratoma, which was associated with primary anophthalmos and an ectopic tooth.

What shakes the FX tree? Understanding currency dominance, dependence, and dynamics (Keynote Address)

NASA Astrophysics Data System (ADS)

Johnson, Neil F.; McDonald, Mark; Suleman, Omer; Williams, Stacy; Howison, Sam

2005-05-01

There is intense interest in understanding the stochastic and dynamical properties of the global Foreign Exchange (FX) market, whose daily transactions exceed one trillion US dollars. This is a formidable task since the FX market is characterized by a web of fluctuating exchange rates, with subtle inter-dependencies which may change in time. In practice, traders talk of particular currencies being 'in play' during a particular period of time -- yet there is no established machinery for detecting such important information. Here we apply the construction of Minimum Spanning Trees (MSTs) to the FX market, and show that the MST can capture important features of the global FX dynamics. Moreover, we show that the MST can help identify momentarily dominant and dependent currencies.

U-shaped relationship between current and pitch in helicene molecules

NASA Astrophysics Data System (ADS)

Guo, Yan-Dong; Yan, Xiao-Hong; Xiao, Yang; Liu, Chun-Sheng

2015-11-01

The helicene is constructed by twisted benzene or other aromatic rings, exhibiting a helical structure. Using first-principles calculations, we investigate the electronic transport of helicenes under stretching or compressing. Interestingly, a U-shaped curve of the current against d (the pitch of a helicene) is observed. Further analysis shows that, it is the result of the nonmonotonic change of HOMO-LUMO gap with d. The change of overlap between orbitals induced by conformational deformation is found to be the underlying mechanism. Moreover, the U-curve phenomenon is an intrinsic feature of the helicene molecules, being robust to the electrode materials or doping. This U-curve behavior is expected to be extended to helical graphene or other related structures, showing great application potential.

U-shaped relationship between current and pitch in helicene molecules.

PubMed

Guo, Yan-Dong; Yan, Xiao-Hong; Xiao, Yang; Liu, Chun-Sheng

2015-11-19

The helicene is constructed by twisted benzene or other aromatic rings, exhibiting a helical structure. Using first-principles calculations, we investigate the electronic transport of helicenes under stretching or compressing. Interestingly, a U-shaped curve of the current against d (the pitch of a helicene) is observed. Further analysis shows that, it is the result of the nonmonotonic change of HOMO-LUMO gap with d. The change of overlap between orbitals induced by conformational deformation is found to be the underlying mechanism. Moreover, the U-curve phenomenon is an intrinsic feature of the helicene molecules, being robust to the electrode materials or doping. This U-curve behavior is expected to be extended to helical graphene or other related structures, showing great application potential.

JOVIAL/Ada Microprocessor Study.

DTIC Science & Technology

1982-04-01

Study Final Technical Report interesting feature of the nodes is that they provide multiple virtual terminals, so it is possible to monitor several...Terminal Interface Tasking Except ion Handling A more elaborate system could allow such features as spooling, background jobs or multiple users. To a large...Another editor feature is the buffer. Buffers may hold small amounts of text or entire text objects. They allow multiple files to be edited simultaneously

Highest-Resolution View of 'Face on Mars'

NASA Technical Reports Server (NTRS)

2001-01-01

A key aspect of the Mars Global Surveyor (MGS) Extended Mission is the opportunity to turn the spacecraft and point the Mars Orbiter Camera (MOC) at specific features of interest. A chance to point the spacecraft comes about ten times a week. Throughout the Primary Mission (March 1999 - January 2001), nearly all MGS operations were conducted with the spacecraft pointing 'nadir'--that is, straight down. In this orientation, opportunities to hit a specific small feature of interest were in some cases rare, and in other cases non-existent. In April 1998, nearly a year before MGS reached its Primary Mission mapping orbit, several tests of the spacecraft's ability to be pointed at specific features was conducted with great success (e.g., Mars Pathfinder landing site, Viking 1 site, and Cydonia landforms). When the Mars Polar Lander was lost in December 1999, this capability was again employed to search for the missing lander. Following the lander search activities, a plan to conduct similar off-nadir observations during the MGS Extended Mission was put into place. The Extended Mission began February 1, 2001. On April 8, 2001, the first opportunity since April 1998 arose to turn the spacecraft and point the MOC at the popular 'Face on Mars' feature.

Viking orbiter images acquired in 1976 showed that one of thousands of buttes, mesas, ridges, and knobs in the transition zone between the cratered uplands of western Arabia Terra and the low, northern plains of Mars looked somewhat like a human face. The feature was subsequently popularized as a potential 'alien artifact' in books, tabloids, radio talk shows, television, and even a major motion picture. Given the popularity of this landform, a new high-resolution view was targeted by pointing the spacecraft off-nadir on April 8, 2001. On that date at 20:54 UTC (8:54 p.m., Greenwich time zone), the MGS was rolled 24.8o to the left so that it was looking at the 'face' 165 km to the side from a distance of about 450 km. The resulting image has a resolution of about 2 meters (6.6 feet) per pixel. If present on Mars, objects the size of typical passenger jet airplanes would be distinguishable in an image of this scale. The large 'face' picture covers an area about 3.6 kilometers (2.2 miles) on a side. Sunlight illuminates the images from the left/lower left.

Identification of ghost artifact using texture analysis in pediatric spinal cord diffusion tensor images.

PubMed

Alizadeh, Mahdi; Conklin, Chris J; Middleton, Devon M; Shah, Pallav; Saksena, Sona; Krisa, Laura; Finsterbusch, Jürgen; Faro, Scott H; Mulcahey, M J; Mohamed, Feroze B

2018-04-01

Ghost artifacts are a major contributor to degradation of spinal cord diffusion tensor images. A multi-stage post-processing pipeline was designed, implemented and validated to automatically remove ghost artifacts arising from reduced field of view diffusion tensor imaging (DTI) of the pediatric spinal cord. A total of 12 pediatric subjects including 7 healthy subjects (mean age=11.34years) with no evidence of spinal cord injury or pathology and 5 patients (mean age=10.96years) with cervical spinal cord injury were studied. Ghost/true cords, labeled as region of interests (ROIs), in non-diffusion weighted b0 images were segmented automatically using mathematical morphological processing. Initially, 21 texture features were extracted from each segmented ROI including 5 first-order features based on the histogram of the image (mean, variance, skewness, kurtosis and entropy) and 16s-order feature vector elements, incorporating four statistical measures (contrast, correlation, homogeneity and energy) calculated from co-occurrence matrices in directions of 0°, 45°, 90° and 135°. Next, ten features with a high value of mutual information (MI) relative to the pre-defined target class and within the features were selected as final features which were input to a trained classifier (adaptive neuro-fuzzy interface system) to separate the true cord from the ghost cord. The implemented pipeline was successfully able to separate the ghost artifacts from true cord structures. The results obtained from the classifier showed a sensitivity of 91%, specificity of 79%, and accuracy of 84% in separating the true cord from ghost artifacts. The results show that the proposed method is promising for the automatic detection of ghost cords present in DTI images of the spinal cord. This step is crucial towards development of accurate, automatic DTI spinal cord post processing pipelines. Copyright © 2017 Elsevier Inc. All rights reserved.

TRANSAT-- method for detecting the conserved helices of functional RNA structures, including transient, pseudo-knotted and alternative structures.

PubMed

Wiebe, Nicholas J P; Meyer, Irmtraud M

2010-06-24

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment.

Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

PubMed

Feng, Zhichao; Rong, Pengfei; Cao, Peng; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei

2018-04-01

To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • Although conventional CT is useful for diagnosis of SRMs, it has limitations. • Machine-learning based CT texture analysis facilitate differentiation of small AMLwvf from RCC. • The highest accuracy of SVM-RFE+SMOTE classifier reached 93.9 %. • Texture analysis combined with machine-learning methods might spare unnecessary surgery for AMLwvf.

Pedestrian Detection in Far-Infrared Daytime Images Using a Hierarchical Codebook of SURF

PubMed Central

Besbes, Bassem; Rogozan, Alexandrina; Rus, Adela-Maria; Bensrhair, Abdelaziz; Broggi, Alberto

2015-01-01

One of the main challenges in intelligent vehicles concerns pedestrian detection for driving assistance. Recent experiments have showed that state-of-the-art descriptors provide better performances on the far-infrared (FIR) spectrum than on the visible one, even in daytime conditions, for pedestrian classification. In this paper, we propose a pedestrian detector with on-board FIR camera. Our main contribution is the exploitation of the specific characteristics of FIR images to design a fast, scale-invariant and robust pedestrian detector. Our system consists of three modules, each based on speeded-up robust feature (SURF) matching. The first module allows generating regions-of-interest (ROI), since in FIR images of the pedestrian shapes may vary in large scales, but heads appear usually as light regions. ROI are detected with a high recall rate with the hierarchical codebook of SURF features located in head regions. The second module consists of pedestrian full-body classification by using SVM. This module allows one to enhance the precision with low computational cost. In the third module, we combine the mean shift algorithm with inter-frame scale-invariant SURF feature tracking to enhance the robustness of our system. The experimental evaluation shows that our system outperforms, in the FIR domain, the state-of-the-art Haar-like Adaboost-cascade, histogram of oriented gradients (HOG)/linear SVM (linSVM) and MultiFtrpedestrian detectors, trained on the FIR images. PMID:25871724

Fast-tracking implementation through trial design: the case of buprenorphine treatment in Victoria.

PubMed

Bammer, Gabriele; Ritter, Alison; Kutin, Jozica J; Lintzeris, Nicholas

2009-02-01

We investigated how a randomised controlled trial (RCT) could be designed to incorporate features known or thought likely to enhance the uptake of the new treatment into clinical practice post-trial. Between 1999 and 2001, we trialled buprenorphine treatment for heroin dependence in community settings throughout Victoria, using 28 experienced methadone prescribers and 34 pharmacists across 19 sites. In this case study, we describe how we incorporated seven features considered important in treatment uptake: skilled and experienced practitioners, government and policy support, incentives to prescribe the new treatment, specialist support services, clinical guidelines, training programs and patient involvement and information. We also present information showing that uptake of buprenorphine treatment was substantially boosted in Victoria compared with other Australian jurisdictions immediately after the trial in 2001 and that this increase was sustained until at least 2006. While we cannot prove that our trial design was responsible for the increased uptake of buprenorphine treatment in Victoria, we do show that design has been a neglected aspect of clinical trials in terms of enhancing post-trial uptake of the treatment being tested. Those interested in closing the 'know-do' gap between research and practice may wish to further explore this very promising lead. Imaginative linking of features known to enhance treatment uptake to pressing research questions may lead to new information on efficacy, as well as getting valuable drugs into the treatment system more rapidly.

A New Scheme to Characterize and Identify Protein Ubiquitination Sites.

PubMed

Nguyen, Van-Nui; Huang, Kai-Yao; Huang, Chien-Hsun; Lai, K Robert; Lee, Tzong-Yi

2017-01-01

Protein ubiquitination, involving the conjugation of ubiquitin on lysine residue, serves as an important modulator of many cellular functions in eukaryotes. Recent advancements in proteomic technology have stimulated increasing interest in identifying ubiquitination sites. However, most computational tools for predicting ubiquitination sites are focused on small-scale data. With an increasing number of experimentally verified ubiquitination sites, we were motivated to design a predictive model for identifying lysine ubiquitination sites for large-scale proteome dataset. This work assessed not only single features, such as amino acid composition (AAC), amino acid pair composition (AAPC) and evolutionary information, but also the effectiveness of incorporating two or more features into a hybrid approach to model construction. The support vector machine (SVM) was applied to generate the prediction models for ubiquitination site identification. Evaluation by five-fold cross-validation showed that the SVM models learned from the combination of hybrid features delivered a better prediction performance. Additionally, a motif discovery tool, MDDLogo, was adopted to characterize the potential substrate motifs of ubiquitination sites. The SVM models integrating the MDDLogo-identified substrate motifs could yield an average accuracy of 68.70 percent. Furthermore, the independent testing result showed that the MDDLogo-clustered SVM models could provide a promising accuracy (78.50 percent) and perform better than other prediction tools. Two cases have demonstrated the effective prediction of ubiquitination sites with corresponding substrate motifs.

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

The discrete one-sided Lipschitz condition for convex scalar conservation laws

NASA Technical Reports Server (NTRS)

Brenier, Yann; Osher, Stanley

1986-01-01

Physical solutions to convex scalar conservation laws satisfy a one-sided Lipschitz condition (OSLC) that enforces both the entropy condition and their variation boundedness. Consistency with this condition is therefore desirable for a numerical scheme and was proved for both the Godunov and the Lax-Friedrichs scheme--also, in a weakened version, for the Roe scheme, all of them being only first order accurate. A new, fully second order scheme is introduced here, which is consistent with the OSLC. The modified equation is considered and shows interesting features. Another second order scheme is then considered and numerical results are discussed.

Properties of highly frustrated magnetic molecules studied by the finite-temperature Lanczos method

NASA Astrophysics Data System (ADS)

Schnack, J.; Wendland, O.

2010-12-01

The very interesting magnetic properties of frustrated magnetic molecules are often hardly accessible due to the prohibitive size of the related Hilbert spaces. The finite-temperature Lanczos method is able to treat spin systems for Hilbert space sizes up to 109. Here we first demonstrate for exactly solvable systems that the method is indeed accurate. Then we discuss the thermal properties of one of the biggest magnetic molecules synthesized to date, the icosidodecahedron with antiferromagnetically coupled spins of s = 1/2. We show how genuine quantum features such as the magnetization plateau behave as a function of temperature.

Analysis of drugs-of-abuse and explosives using terahertz time-domain and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Burnett, Andrew; Fan, Wenhui; Upadhya, Prashanth; Cunningham, John; Linfield, Edmund; Davies, Giles; Edwards, Howell; Munshi, Tasnim; O'Neil, Andrew

2006-02-01

We demonstrate that, through coherent measurement of the transmitted terahertz electric fields, broadband (0.3-8THz) time-domain spectroscopy can be used to measure far-infrared vibrational modes of a range of illegal drugs and high explosives that are of interest to the forensic and security services. Our results show that these absorption features are highly sensitive to the structural and spatial arrangement of the molecules. Terahertz frequency spectra are also compared with high-resolution low-frequency Raman spectra to assist in understanding the low frequency inter- and intra-molecular vibrational modes of the molecules.

Bacterial Magnetosome: A Novel Biogenetic Magnetic Targeted Drug Carrier with Potential Multifunctions

PubMed Central

Sun, Jianbo; Li, Ying; Liang, Xing-Jie; Wang, Paul C.

2012-01-01

Bacterial magnetosomes (BMs) synthesized by magnetotactic bacteria have recently drawn great interest due to their unique features. BMs are used experimentally as carriers for antibodies, enzymes, ligands, nucleic acids, and chemotherapeutic drugs. In addition to the common attractive properties of magnetic carriers, BMs also show superiority as targeting nanoscale drug carriers, which is hardly matched by artificial magnetic particles. We are presenting the potential applications of BMs as drug carriers by introducing the drug-loading methods and strategies and the recent research progress of BMs which has contributed to the application of BMs as drug carriers. PMID:22448162

In silico studies on tryparedoxin peroxidase of Leishmania infantum: structural aspects.

PubMed

Singh, Bishal Kumar; Dubey, Vikash Kumar

2009-09-01

Tryparedoxin peroxidase (TryP) is a key enzyme of the trypanothione-dependent metabolism for removal of oxidative stress in leishmania. These enzymes function as antioxidants through their peroxidase and peroxynitrite reductase activities. Inhibitors of this enzyme are presumed to be antilesihmania drugs and structural studies are prerequisite of rational drug design. We have constructed three dimensional structure of TryP of Leishmania infantum using comparative modeling. Structural analysis reveals several interesting features. Moreover, it shows remarkable structural difference with human host glutathione peroxidase, an enzyme involved in similar function and TryP from Leishmania major.

The Morphosyntax of Discontinuous Exponence

ERIC Educational Resources Information Center

Campbell, Amy Melissa

2012-01-01

This thesis offers a systematic treatment of discontinuous exponence, a pattern of inflection in which a single feature or a set of features bundled in syntax is expressed by multiple, distinct morphemes. This pattern is interesting and theoretically relevant because it represents a deviation from the expected one-to-one relationship between…

Activity Participation and Sensory Features among Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Little, Lauren M.; Ausderau, Karla; Sideris, John; Baranek, Grace T.

2015-01-01

Sensory features are highly prevalent among children with autism spectrum disorders (ASD) and have been shown to cluster into four patterns of response, including hyperresponsiveness, hyporesponsiveness, enhanced perception, and sensory interests, repetitions and seeking behaviors. Given the lack of large-scale research on the differential effects…

A Clearer View of Vista Features

ERIC Educational Resources Information Center

Descy, Don E.

2008-01-01

In this article, the author discusses some features of Windows Vista that may be of interest to teachers and/or their students. These are: (1) User Account Control; (2) Windows Firewall; (3) Windows Backup; (4) Parental Controls; (5) Windows Sidebar and Gadgets; (6) Instant Search; and (7) Windows ReadyBoost.

75 FR 29766 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-27

...-member renal cancer cell lines in the Tumor Cell Line Repository of the Urologic Oncology Branch (UOB... genetic features are well characterized: This cell line is part of NCI Urologic Oncology Branch's Tumor... Oncology Branch, is seeking statements of capability or interest from parties interested in collaborative...

Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

PubMed

Romeo, Valeria; Maurea, Simone; Cuocolo, Renato; Petretta, Mario; Mainenti, Pier Paolo; Verde, Francesco; Coppola, Milena; Dell'Aversana, Serena; Brunetti, Arturo

2018-01-17

Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest. To assess the diagnostic efficacy of TA-derived parameters extracted from MR images in characterizing LRA, LPA, and NAL using a machine-learning approach. Retrospective, observational study. Sixty MR examinations, including 20 LRA, 20 LPA, and 20 NAL. Unenhanced T 1 -weighted in-phase (IP) and out-of-phase (OP) as well as T 2 -weighted (T 2 -w) MR images acquired at 3T. Adrenal lesions were manually segmented, placing a spherical volume of interest on IP, OP, and T 2 -w images. Different selection methods were trained and tested using the J48 machine-learning classifiers. The feature selection method that obtained the highest diagnostic performance using the J48 classifier was identified; the diagnostic performance was also compared with that of a senior radiologist by means of McNemar's test. A total of 138 TA-derived features were extracted; among these, four features were selected, extracted from the IP (Short_Run_High_Gray_Level_Emphasis), OP (Mean_Intensity and Maximum_3D_Diameter), and T 2 -w (Standard_Deviation) images; the J48 classifier obtained a diagnostic accuracy of 80%. The expert radiologist obtained a diagnostic accuracy of 73%. McNemar's test did not show significant differences in terms of diagnostic performance between the J48 classifier and the expert radiologist. Machine learning conducted on MR TA-derived features is a potential tool to characterize adrenal lesions. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Effects of face feature and contour crowding in facial expression adaptation.

PubMed

Liu, Pan; Montaser-Kouhsari, Leila; Xu, Hong

2014-12-01

Prolonged exposure to a visual stimulus, such as a happy face, biases the perception of subsequently presented neutral face toward sad perception, the known face adaptation. Face adaptation is affected by visibility or awareness of the adapting face. However, whether it is affected by discriminability of the adapting face is largely unknown. In the current study, we used crowding to manipulate discriminability of the adapting face and test its effect on face adaptation. Instead of presenting flanking faces near the target face, we shortened the distance between facial features (internal feature crowding), and reduced the size of face contour (external contour crowding), to introduce crowding. We are interested in whether internal feature crowding or external contour crowding is more effective in inducing crowding effect in our first experiment. We found that combining internal feature and external contour crowding, but not either of them alone, induced significant crowding effect. In Experiment 2, we went on further to investigate its effect on adaptation. We found that both internal feature crowding and external contour crowding reduced its facial expression aftereffect (FEA) significantly. However, we did not find a significant correlation between discriminability of the adapting face and its FEA. Interestingly, we found a significant correlation between discriminabilities of the adapting and test faces. Experiment 3 found that the reduced adaptation aftereffect in combined crowding by the external face contour and the internal facial features cannot be decomposed into the effects from the face contour and facial features linearly. It thus suggested a nonlinear integration between facial features and face contour in face adaptation.

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.

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

A Robust Linear Feature-Based Procedure for Automated Registration of Point Clouds

PubMed Central

Poreba, Martyna; Goulette, François

2015-01-01

With the variety of measurement techniques available on the market today, fusing multi-source complementary information into one dataset is a matter of great interest. Target-based, point-based and feature-based methods are some of the approaches used to place data in a common reference frame by estimating its corresponding transformation parameters. This paper proposes a new linear feature-based method to perform accurate registration of point clouds, either in 2D or 3D. A two-step fast algorithm called Robust Line Matching and Registration (RLMR), which combines coarse and fine registration, was developed. The initial estimate is found from a triplet of conjugate line pairs, selected by a RANSAC algorithm. Then, this transformation is refined using an iterative optimization algorithm. Conjugates of linear features are identified with respect to a similarity metric representing a line-to-line distance. The efficiency and robustness to noise of the proposed method are evaluated and discussed. The algorithm is valid and ensures valuable results when pre-aligned point clouds with the same scale are used. The studies show that the matching accuracy is at least 99.5%. The transformation parameters are also estimated correctly. The error in rotation is better than 2.8% full scale, while the translation error is less than 12.7%. PMID:25594589

Western Arcadia Planitia

NASA Image and Video Library

2003-03-13

This is a Mars Odyssey visible color image of an unnamed crater in western Arcadia Planitia (near 39 degrees N, 179 degrees E). The crater shows a number of interesting internal and external features that suggest that it has undergone substantial modification since it formed. These features include concentric layers and radial streaks of brighter, redder materials inside the crater, and a heavily degraded rim and ejecta blanket. The patterns inside the crater suggest that material has flowed or slumped towards the center. Other craters with features like this have been seen at both northern and southern mid latitudes The distribution of these kinds of craters suggests the possible influence of surface or subsurface ice in the formation of these enigmatic features. The image was taken on September 29, 2002 during late northern spring. This is an approximate true color image, generated from a long strip of visible red (654 nm), green (540 nm), and blue (425 nm) filter images that were calibrated using a combination of pre-flight measurements and Hubble images of Mars. The colors appear perhaps a bit darker than one might expect; this is most likely because the images were acquired in late afternoon (roughly 4:40 p.m. local solar time) and the low Sun angle results in an overall darker surface. http://photojournal.jpl.nasa.gov/catalog/PIA04263

The drug target genes show higher evolutionary conservation than non-target genes.

PubMed

Lv, Wenhua; Xu, Yongdeng; Guo, Yiying; Yu, Ziqi; Feng, Guanglong; Liu, Panpan; Luan, Meiwei; Zhu, Hongjie; Liu, Guiyou; Zhang, Mingming; Lv, Hongchao; Duan, Lian; Shang, Zhenwei; Li, Jin; Jiang, Yongshuai; Zhang, Ruijie

2016-01-26

Although evidence indicates that drug target genes share some common evolutionary features, there have been few studies analyzing evolutionary features of drug targets from an overall level. Therefore, we conducted an analysis which aimed to investigate the evolutionary characteristics of drug target genes. We compared the evolutionary conservation between human drug target genes and non-target genes by combining both the evolutionary features and network topological properties in human protein-protein interaction network. The evolution rate, conservation score and the percentage of orthologous genes of 21 species were included in our study. Meanwhile, four topological features including the average shortest path length, betweenness centrality, clustering coefficient and degree were considered for comparison analysis. Then we got four results as following: compared with non-drug target genes, 1) drug target genes had lower evolutionary rates; 2) drug target genes had higher conservation scores; 3) drug target genes had higher percentages of orthologous genes and 4) drug target genes had a tighter network structure including higher degrees, betweenness centrality, clustering coefficients and lower average shortest path lengths. These results demonstrate that drug target genes are more evolutionarily conserved than non-drug target genes. We hope that our study will provide valuable information for other researchers who are interested in evolutionary conservation of drug targets.

Features of a Health-Oriented Education Program during Daily Commutes: A Qualitative Study.

PubMed

Ramezankhani, Ali; Heydarabadi, Akbar Babaei; Ghaffari, Mohtasham; Mehrabi, Yadollah; Kazemi, Sadegh

2016-06-01

Today, despite scientific advances, many people spend more time and distance between home and their workplaces because of various economic and population reasons. The aim of this study was to identify features of an appropriate health education program during commutes for factory staff at Ardakan county (Yazd province, Iran). This qualitative study was conducted via the phenomenological method in 2014. The population of this study was members of the staff of Ardakan Steel Company. Nineteen specialists and 11 members of the factory's staff were invited to participate in the study, and data were collected using semi-structured interviews. The interviews took 20 to 40 minutes, and their content was analyzed using content analysis. Extraction of codes and themes and their placement in this study showed that an educational program during commutes should have nine features to have the desired effectiveness, i.e., the program must be audience-oriented, repeatable, participatory, technology-based, combinational, supportive, and motivational and interesting. Also, the program should have environmental and organizational support, and it must be evaluated for its effectiveness. Considering appropriate features of a health education program in educational situations, especially interventions related to daily commutes, is very important because the effectiveness of such health-oriented educational programs must be ensured.

The interpretation of polycrystalline coherent inelastic neutron scattering from aluminium

PubMed Central

Roach, Daniel L.; Ross, D. Keith; Gale, Julian D.; Taylor, Jon W.

2013-01-01

A new approach to the interpretation and analysis of coherent inelastic neutron scattering from polycrystals (poly-CINS) is presented. This article describes a simulation of the one-phonon coherent inelastic scattering from a lattice model of an arbitrary crystal system. The one-phonon component is characterized by sharp features, determined, for example, by boundaries of the (Q, ω) regions where one-phonon scattering is allowed. These features may be identified with the same features apparent in the measured total coherent inelastic cross section, the other components of which (multiphonon or multiple scattering) show no sharp features. The parameters of the model can then be relaxed to improve the fit between model and experiment. This method is of particular interest where no single crystals are available. To test the approach, the poly-CINS has been measured for polycrystalline aluminium using the MARI spectrometer (ISIS), because both lattice dynamical models and measured dispersion curves are available for this material. The models used include a simple Lennard-Jones model fitted to the elastic constants of this material plus a number of embedded atom method force fields. The agreement obtained suggests that the method demonstrated should be effective in developing models for other materials where single-crystal dispersion curves are not available. PMID:24282332

Optimum ArFi laser bandwidth for 10nm node logic imaging performance

NASA Astrophysics Data System (ADS)

Alagna, Paolo; Zurita, Omar; Timoshkov, Vadim; Wong, Patrick; Rechtsteiner, Gregory; Baselmans, Jan; Mailfert, Julien

2015-03-01

Lithography process window (PW) and CD uniformity (CDU) requirements are being challenged with scaling across all device types. Aggressive PW and yield specifications put tight requirements on scanner performance, especially on focus budgets resulting in complicated systems for focus control. In this study, an imec N10 Logic-type test vehicle was used to investigate the E95 bandwidth impact on six different Metal 1 Logic features. The imaging metrics that track the impact of light source E95 bandwidth on performance of hot spots are: process window (PW), line width roughness (LWR), and local critical dimension uniformity (LCDU). In the first section of this study, the impact of increasing E95 bandwidth was investigated to observe the lithographic process control response of the specified logic features. In the second section, a preliminary assessment of the impact of lower E95 bandwidth was performed. The impact of lower E95 bandwidth on local intensity variability was monitored through the CDU of line end features and the LWR power spectral density (PSD) of line/space patterns. The investigation found that the imec N10 test vehicle (with OPC optimized for standard E95 bandwidth of300fm) features exposed at 200fm showed pattern specific responses, suggesting areas of potential interest for further investigation.

Ligand-based and structure-based approaches in identifying ideal pharmacophore against c-Jun N-terminal kinase-3.

PubMed

Kumar, B V S Suneel; Kotla, Rohith; Buddiga, Revanth; Roy, Jyoti; Singh, Sardar Shamshair; Gundla, Rambabu; Ravikumar, Muttineni; Sarma, Jagarlapudi A R P

2011-01-01

Structure and ligand based pharmacophore modeling and docking studies carried out using diversified set of c-Jun N-terminal kinase-3 (JNK3) inhibitors are presented in this paper. Ligand based pharmacophore model (LBPM) was developed for 106 inhibitors of JNK3 using a training set of 21 compounds to reveal structural and chemical features necessary for these molecules to inhibit JNK3. Hypo1 consisted of two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), and a hydrophobic (HY) feature with a correlation coefficient (r²) of 0.950. This pharmacophore model was validated using test set containing 85 inhibitors and had a good r² of 0.846. All the molecules were docked using Glide software and interestingly, all the docked conformations showed hydrogen bond interactions with important hinge region amino acids (Gln155 and Met149)and these interactions were compared with Hypo1 features. The results of ligand based pharmacophore model (LBPM)and docking studies are validated each other. The structure based pharmacophore model (SBPM) studies have identified additional features, two hydrogen bond donors and one hydrogen bond acceptor. The combination of these methodologies is useful in designing ideal pharmacophore which provides a powerful tool for the discovery of novel and selective JNK3 inhibitors.

Raman spectroscopy fingerprint of stainless steel-MWCNTs nanocomposite processed by ball-milling

NASA Astrophysics Data System (ADS)

dos Reis, Marcos Allan Leite; Barbosa Neto, Newton Martins; de Sousa, Mário Edson Santos; Araujo, Paulo T.; Simões, Sónia; Vieira, Manuel F.; Viana, Filomena; Loayza, Cristhian R. L.; Borges, Diego J. A.; Cardoso, Danyella C. S.; Assunção, Paulo D. C.; Braga, Eduardo M.

2018-01-01

Stainless steel 304L alloy powder and multiwalled carbon nanotubes were mixed by ball-milling under ambient atmosphere and in a broad range of milling times, which spans from 0 to 120 min. Here, we provided spectroscopic signatures for several distinct composites produced, to show that the Raman spectra present interesting splittings of the D-band feature into two main sub-bands, D-left and D-right, together with several other secondary features. The G-band feature also presents multiple splittings that are related to the outer and inner diameter distributions intrinsic to the multiwalled carbon nanotube samples. A discussion about the second order 2D-band (also known as G'-band) is also provided. The results reveal that the multiple spectral features observed in the D-band are related to an increased chemical functionalization. A lower content of amorphous carbon at 60 and 90 min of milling time is verified and the G-band frequencies associated to the tubes in the outer diameters distribution is upshifted, which suggests that doping induced by strain is taking place in the milled samples. The results indicate that Raman spectroscopy can be a powerful tool for a fast and non-destructive characterization of carbon nanocomposites used in powder metallurgy manufacturing processes.

Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation

NASA Astrophysics Data System (ADS)

He, Qiang; Schultz, Richard R.; Wang, Yi; Camargo, Aldo; Martel, Florent

2008-01-01

In traditional super-resolution methods, researchers generally assume that accurate subpixel image registration parameters are given a priori. In reality, accurate image registration on a subpixel grid is the single most critically important step for the accuracy of super-resolution image reconstruction. In this paper, we introduce affine invariant features to improve subpixel image registration, which considerably reduces the number of mismatched points and hence makes traditional image registration more efficient and more accurate for super-resolution video enhancement. Affine invariant interest points include those corners that are invariant to affine transformations, including scale, rotation, and translation. They are extracted from the second moment matrix through the integration and differentiation covariance matrices. Our tests are based on two sets of real video captured by a small Unmanned Aircraft System (UAS) aircraft, which is highly susceptible to vibration from even light winds. The experimental results from real UAS surveillance video show that affine invariant interest points are more robust to perspective distortion and present more accurate matching than traditional Harris/SIFT corners. In our experiments on real video, all matching affine invariant interest points are found correctly. In addition, for the same super-resolution problem, we can use many fewer affine invariant points than Harris/SIFT corners to obtain good super-resolution results.

Some of the most interesting CASP11 targets through the eyes of their authors.

PubMed

Kryshtafovych, Andriy; Moult, John; Baslé, Arnaud; Burgin, Alex; Craig, Timothy K; Edwards, Robert A; Fass, Deborah; Hartmann, Marcus D; Korycinski, Mateusz; Lewis, Richard J; Lorimer, Donald; Lupas, Andrei N; Newman, Janet; Peat, Thomas S; Piepenbrink, Kurt H; Prahlad, Janani; van Raaij, Mark J; Rohwer, Forest; Segall, Anca M; Seguritan, Victor; Sundberg, Eric J; Singh, Abhimanyu K; Wilson, Mark A; Schwede, Torsten

2016-09-01

The Critical Assessment of protein Structure Prediction (CASP) experiment would not have been possible without the prediction targets provided by the experimental structural biology community. In this article, selected crystallographers providing targets for the CASP11 experiment discuss the functional and biological significance of the target proteins, highlight their most interesting structural features, and assess whether these features were correctly reproduced in the predictions submitted to CASP11. Proteins 2016; 84(Suppl 1):34-50. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Computational approaches for predicting biomedical research collaborations.

PubMed

Zhang, Qing; Yu, Hong

2014-01-01

Biomedical research is increasingly collaborative, and successful collaborations often produce high impact work. Computational approaches can be developed for automatically predicting biomedical research collaborations. Previous works of collaboration prediction mainly explored the topological structures of research collaboration networks, leaving out rich semantic information from the publications themselves. In this paper, we propose supervised machine learning approaches to predict research collaborations in the biomedical field. We explored both the semantic features extracted from author research interest profile and the author network topological features. We found that the most informative semantic features for author collaborations are related to research interest, including similarity of out-citing citations, similarity of abstracts. Of the four supervised machine learning models (naïve Bayes, naïve Bayes multinomial, SVMs, and logistic regression), the best performing model is logistic regression with an ROC ranging from 0.766 to 0.980 on different datasets. To our knowledge we are the first to study in depth how research interest and productivities can be used for collaboration prediction. Our approach is computationally efficient, scalable and yet simple to implement. The datasets of this study are available at https://github.com/qingzhanggithub/medline-collaboration-datasets.

The Edge of Jupiter

NASA Image and Video Library

2017-04-19

This enhanced color Jupiter image, taken by the JunoCam imager on NASA's Juno spacecraft, showcases several interesting features on the apparent edge (limb) of the planet. Prior to Juno's fifth flyby over Jupiter's mysterious cloud tops, members of the public voted on which targets JunoCam should image. This picture captures not only a fascinating variety of textures in Jupiter's atmosphere, it also features three specific points of interest: "String of Pearls," "Between the Pearls," and "An Interesting Band Point." Also visible is what's known as the STB Spectre, a feature in Jupiter's South Temperate Belt where multiple atmospheric conditions appear to collide. JunoCam images of Jupiter sometimes appear to have an odd shape. This is because the Juno spacecraft is so close to Jupiter that it cannot capture the entire illuminated area in one image -- the sides get cut off. Juno acquired this image on March 27, 2017, at 2:12 a.m. PDT (5:12 a.m. EDT), as the spacecraft performed a close flyby of Jupiter. When the image was taken, the spacecraft was about 12,400 miles (20,000 kilometers) from the planet. This enhanced color image was created by citizen scientist Bjorn Jonsson. https://photojournal.jpl.nasa.gov/catalog/PIA21389

Using classification models for the generation of disease-specific medications from biomedical literature and clinical data repository.

PubMed

Wang, Liqin; Haug, Peter J; Del Fiol, Guilherme

2017-05-01

Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the challenge remains when those extracted associations contained much noise. It is unreliable to determine the relevance of the association by simply setting up arbitrary cut-off points on multiple scores of relevance; and it would be expensive to ask human experts to manually review a large number of associations. We propose that machine-learning-based classification can be used to separate the signal from the noise, and to provide a feasible approach to create and maintain disease-specific vocabularies. We initially focused on disease-medication associations for the purpose of simplicity. For a disease of interest, we extracted potentially treatment-related drug concepts from biomedical literature citations and from a local clinical data repository. Each concept was associated with multiple measures of relevance (i.e., features) such as frequency of occurrence. For the machine purpose of learning, we formed nine datasets for three diseases with each disease having two single-source datasets and one from the combination of previous two datasets. All the datasets were labeled using existing reference standards. Thereafter, we conducted two experiments: (1) to test if adding features from the clinical data repository would improve the performance of classification achieved using features from the biomedical literature only, and (2) to determine if classifier(s) trained with known medication-disease data sets would be generalizable to new disease(s). Simple logistic regression and LogitBoost were two classifiers identified as the preferred models separately for the biomedical-literature datasets and combined datasets. The performance of the classification using combined features provided significant improvement beyond that using biomedical-literature features alone (p-value<0.001). The performance of the classifier built from known diseases to predict associated concepts for new diseases showed no significant difference from the performance of the classifier built and tested using the new disease's dataset. It is feasible to use classification approaches to automatically predict the relevance of a concept to a disease of interest. It is useful to combine features from disparate sources for the task of classification. Classifiers built from known diseases were generalizable to new diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated Fluid Feature Extraction from Transient Simulations

NASA Technical Reports Server (NTRS)

Haimes, Robert

2000-01-01

In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense.

Supernova Remnants in the UWIFE and UWISH2 Surveys

NASA Astrophysics Data System (ADS)

Lee, Yong-Hyun; Koo, Bon-Chul; Lee, Jae-Joon

2016-06-01

We have searched for near-infrared [Fe II] (1.644 µm) and H2 1-0 S(1) (2.122 µm) emission features associated with Galactic supernova remnants (SNRs) using the narrow-band imaging surveys UWIFE/ UWISH2 (UKIRT Widefield Infrared Survey for [Fe II] / H2). Both surveys cover about 180 square degrees of the first Galactic quadrant (7° < l < 62°; -1.5° < b < +1.5°), and a total of 79 SNRs are falling in the survey area among the currently known 294 Galactic SNRs. The images show diffuse structures as deep as the surface brightness limit of 10-19 W m-2 arcsec-2 which is comparable with a 5σ detection limit of point sources of 18 mag. In order to inspect the narrow-band features, we subtracted H and K-band continuum images obtained from the UKIDSS GPS (UKIRT Infrared Deep Sky Survey of the Galactic Plane) from the [Fe II] and H2 narrow-band images, respectively. By this time, we have found 19 [Fe II]- and 18 H2-emitting SNRs, and these are likely to increase in future as we inspect the images in more detail. Some of the SNRs show bright, complex, and interesting structures that have never been reported in previous studies. Since [Fe II] and H2 lines trace dense atomic and molecular gases associated with SNR shocks, our results can help us understand the environment and evolution of individual SNRs. Among the SNRs showing both [Fe II] and H2 emission lines, some SNRs show the “[Fe II]-H2 reversal” phenomenon, i.e., the H2 emission features are detected outside the [Fe II] emission boundary. This is opposite to the standard picture: If the shocks are driven by the same blast wave, we expect the H2 filaments to be closer to the explosion center than the [Fe II] filaments. In this presentation, we show several examples of such SNRs detected in our study, and present high resolution (R ˜ 40,000) H and K-band spectra of H2 emission features obtained by using IGRINS (Immersion Grating Infrared Spectrograph).

Supernova Remnants in the UWIFE and UWISH2 Surveys

NASA Astrophysics Data System (ADS)

Lee, Yong-Hyun

2016-06-01

We have searched for near-infrared [Fe II] (1.644 μm) and H2 1-0 S(1) (2.122 μm) emission features associated with Galactic supernova remnants (SNRs) using the narrow-band imaging surveys UWIFE/ UWISH2 (UKIRT Widefield Infrared Survey for [Fe II] / H2 ). Both surveys cover about 180 square degrees of the first Galactic quadrant (7 {circ} < l < 62 {circ} ; -1.5 {circ} < b < +1.5 {circ} ), and a total of 79 SNRs are falling in the survey area among the currently known 294 Galactic SNRs. The images show diffuse structures as deep as the surface brightness limit of 10^(-19) W m^(-2) arcsec^(-2) which is comparable with a 5σ detection limit of point sources of 18 mag. In order to inspect the narrow-band features, we subtracted H and K-band continuum images obtained from the UKIDSS GPS (UKIRT Infrared Deep Sky Survey of the Galactic Plane) from the [Fe II] and H2 narrow-band images, respectively. By this time, we have found 19 [Fe II]- and 18 H2 -emitting SNRs, and these are likely to increase in future as we inspect the images in more detail. Some of the SNRs show bright, complex, and interesting structures that have never been reported in previous studies. Since [Fe II] and H2 lines trace dense atomic and molecular gases associated with SNR shocks, our results can help us understand the environment and evolution of individual SNRs. Among the SNRs showing both [Fe II] and H2 emission lines, some SNRs show the “[Fe II]-H2 reversal” phenomenon, i.e., the H2 emission features are detected outside the [Fe II] emission boundary. This is opposite to the standard picture: If the shocks are driven by the same blast wave, we expect the H2 filaments to be closer to the explosion center than the [Fe II] filaments. In this presentation, we show several examples of such SNRs detected in our study, and present high resolution (R 40,000) H and K-band spectra of H2 emission features obtained by using IGRINS (Immersion Grating Infrared Spectrograph).

Assessing the effects of habitat patches ensuring propagule supply and different costs inclusion in marine spatial planning through multivariate analyses.

PubMed

Appolloni, L; Sandulli, R; Vetrano, G; Russo, G F

2018-05-15

Marine Protected Areas are considered key tools for conservation of coastal ecosystems. However, many reserves are characterized by several problems mainly related to inadequate zonings that often do not protect high biodiversity and propagule supply areas precluding, at the same time, economic important zones for local interests. The Gulf of Naples is here employed as a study area to assess the effects of inclusion of different conservation features and costs in reserve design process. In particular eight scenarios are developed using graph theory to identify propagule source patches and fishing and exploitation activities as costs-in-use for local population. Scenarios elaborated by MARXAN, software commonly used for marine conservation planning, are compared using multivariate analyses (MDS, PERMANOVA and PERMDISP) in order to assess input data having greatest effects on protected areas selection. MARXAN is heuristic software able to give a number of different correct results, all of them near to the best solution. Its outputs show that the most important areas to be protected, in order to ensure long-term habitat life and adequate propagule supply, are mainly located around the Gulf islands. In addition through statistical analyses it allowed us to prove that different choices on conservation features lead to statistically different scenarios. The presence of propagule supply patches forces MARXAN to select almost the same areas to protect decreasingly different MARXAN results and, thus, choices for reserves area selection. The multivariate analyses applied here to marine spatial planning proved to be very helpful allowing to identify i) how different scenario input data affect MARXAN and ii) what features have to be taken into account in study areas characterized by peculiar biological and economic interests. Copyright © 2018 Elsevier Ltd. All rights reserved.

New Life for Astronomical Instruments of the Past at the Astronomical Observatory of Taras Shevchenko

NASA Astrophysics Data System (ADS)

Kazantseva, Liliya

2012-09-01

Astronomical instruments of the past are certainly valuable artifacts of the history of science and education. Like other collections of scientific equipment, they also demonstrate i) development of scientific and technical ideas, ii) technological features of the historical period, iii) professional features of artists or companies -- manufacturers, and iv) national and local specificity of production. However, astronomical instruments are also devices made for observations of rare phenomena -- solar eclipses, transits of planets of the solar disk, etc. Instruments used to study these rare events were very different for each event, since the science changed quickly between events. The Astronomical Observatory of Kyiv National Taras Shevchenko University has a collection of tools made by leading European and local shops from the early nineteenth century. These include tools for optically observing the first artificial Earth satellites, photography, chronometry, and meteorology. In addition, it has assembled a library of descriptions of astronomical instruments and makers'price-lists. Of particular interest are the large stationary tools that are still active in their pavilions. Almost every instrument has a long interesting history. Museification of astronomical instruments gives them a second life, expanding educational programs and tracing the development of astronomy in general and scientific institution and region in particular. It would be advisable to first create a regional database of these rare astronomical instruments (which is already being done in Ukraine), then a common global database. By combining all the historical information about astronomical instruments with the advantages of the Internet, you can show the full evolution of an astronomical instrument with all its features. Time is relentless, and much is destroyed, badly kept and thrown in the garbage. We need time to protect, capture, and tell about it.

Disease Prediction based on Functional Connectomes using a Scalable and Spatially-Informed Support Vector Machine

PubMed Central

Watanabe, Takanori; Kessler, Daniel; Scott, Clayton; Angstadt, Michael; Sripada, Chandra

2014-01-01

Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D “connectome space,” offering an additional layer of interpretability that could provide new insights about various disease processes. PMID:24704268

Nanoconfinement: an effective way to enhance PVDF piezoelectric properties.

PubMed

Cauda, Valentina; Stassi, Stefano; Bejtka, Katarzyna; Canavese, Giancarlo

2013-07-10

The dimensional confinement and oriented crystallization are both key factors in determining the piezoelectric properties of a polymeric nanostructured material. Here we prepare arrays of one-dimensional polymeric nanowires showing piezoelectric features by template-wetting two distinct polymers into anodic porous alumina (APA) membranes. In particular, poly(vinylidene fluoride), PVDF, and its copolymer poly(vinylidene fluoride-trifluoroethylene), PVTF, are obtained in commercially available APA, showing a final diameter of about 200 nm and several micrometers in length, reflecting the templating matrix features. We show that the crystallization of both polymers into a ferroelectric phase is directed by the nanotemplate confinement. Interestingly, the PVDF nanowires mainly crystallize into the β-phase in the nanoporous matrix, whereas the reference thin film of PVDF crystallizes in the α nonpolar phase. In the case of the PVTF nanowires, needle-like crystals oriented perpendicularly to the APA channel walls are observed, giving insight on the molecular orientation of the polymer within the nanowire structure. A remarkable piezoelectric behavior of both 1-D polymeric nanowires is observed, upon recording ferroelectric polarization, hysteresis, and displacement loops. In particular, an outstanding piezoelectric effect is observed for the PVDF nanowires with respect to the polymeric thin film, considering that no poling was carried out. Current versus voltage (I-V) characteristics showed a consistent switching behavior of the ferroelectric polar domains, thus revealing the importance of the confined and oriented crystallization of the polymer in monodimensional nanoarchitectures.

An international standard for observation data

NASA Astrophysics Data System (ADS)

Cox, Simon

2010-05-01

A generic information model for observations and related features supports data exchange both within and between different scientific and technical communities. Observations and Measurements (O&M) formalizes a neutral terminology for observation data and metadata. It was based on a model developed for medical observations, and draws on experience from geology and mineral exploration, in-situ monitoring, remote sensing, intelligence, biodiversity studies, ocean observations and climate simulations. Hundreds of current deployments of Sensor Observation Services (SOS), covering multiple disciplines, provide validation of the O&M model. A W3C Incubator group on 'Semantic Sensor Networks' is now using O&M as one of the bases for development of a formal ontology for sensor networks. O&M defines the information describing observation acts and their results, including the following key terms: observation, result, observed-property, feature-of-interest, procedure, phenomenon-time, and result-time. The model separates of the (meta-)data associated with the observation procedure, the observed feature, and the observation event itself. Observation results may take various forms, including scalar quantities, categories, vectors, grids, or any data structure required to represent the value of some property of some observed feature. O&M follows the ISO/TC 211 General Feature Model so non-geometric properties must be associated with typed feature instances. This requires formalization of information that may be trivial when working within some earth-science sub-disciplines (e.g. temperature, pressure etc. are associated with the atmosphere or ocean, and not just a location) but is critical to cross-disciplinary applications. It also allows the same structure and terminology to be used for in-situ, ex-situ and remote sensing observations, as well as for simulations. For example: a stream level observation is an in-situ monitoring application where the feature-of-interest is a reach, the observed property is water-level, and the result is a time-series of heights; stream quality is usually determined by ex-situ observation where the feature-of-interest is a specimen that is recovered from the stream, the observed property is water-quality, and the result is a set of measures of various parameters, or an assessment derived from these; on the other hand, distribution of surface temperature of a water body is typically determined through remote-sensing, where at observation time the procedure is located distant from the feature-of-interest, and the result is an image or grid. Observations usually involve sampling of an ultimate feature-of-interest. In the environmental sciences common sampling strategies are used. Spatial sampling is classified primarily by topological dimension (point, curve, surface, volume) and is supported by standard processing and visualisation tools. Specimens are used for ex-situ processing in most disciplines. Sampling features are often part of complexes (e.g. specimens are sub-divided; specimens are retrieved from points along a transect; sections are taken across tracts), so relationships between instances must be recorded. And observational campaigns involve collections of sampling features. The sampling feature model is a core part of O&M, and application experience has shown that describing the relationships between sampling features and observations is generally critical to successful use of the model. O&M was developed through Open Geospatial Consortium (OGC) as part of the Sensor Web Enablement (SWE) initiative. Other SWE standards include SensorML, SOS, Sensor Planning Service (SPS). The OGC O&M standard (Version 1) had two parts: part 1 describes observation events, and part 2 provides a schema sampling features. A revised version of O&M (Version 2) is to be published in a single document as ISO 19156. O&M Version 1 included an XML encoding for data exchange, which is used as the payload for SOS responses. The new version will provide a UML model only. Since an XML encoding may be generated following a rule, such as that presented in ISO 19136 (GML 3.2), it is not included in the standard directly. O&M Version 2 thus supports multiple physical implementations and versions.

Mathematics Professional Development: Critical Features for Developing Leadership Skills and Building Teachers' Capacity

ERIC Educational Resources Information Center

Koellner, Karen; Jacobs, Jennifer; Borko, Hilda

2011-01-01

This article focuses on three features of professional development (PD) programs that play an important role in developing leadership skills and building teachers' capacity: (1) fostering a professional learning community, (2) developing teachers' mathematical knowledge for teaching, and (3) adapting PD to support local needs and interests. We…

Relationship between Attitude toward Target Language Culture Instruction and Pragmatic Comprehension Development

ERIC Educational Resources Information Center

Rafieyan, Vahid; Majid, Norazman Bin Abdul; Eng, Lin Siew

2013-01-01

Familiarity with the cultural features of the target language society and interest in learning those cultural features are the key factors to determine language learners' level of pragmatic comprehension. To investigate this issue, this study attempted to assess the relationship between attitude toward incorporating target language culture into…

Publishing Magazines: To Meet Reader Needs and Interests.

ERIC Educational Resources Information Center

Palmer, Lane M.

A series of lectures presented by "Farm Journal's" editor-in-chief Lane Palmer to the advanced agricultural writing course of the University of Wisconsin's Department of Agricultural Journalism in the spring of 1970 formed the basis for this publication. The purpose of the lectures was to stimulate student interest in feature writing and magazine…

Examining Kindergarten Students' Use of and Interest in Informational Text

ERIC Educational Resources Information Center

Hall, Anna H.; Matthew Boyer, D.; Beschorner, Elizabeth A.

2017-01-01

This article describes a dual-case study that was conducted to examine the effects of The Tools Approach on kindergarten students' use of and interest in informational text. Children in one teacher's kindergarten classroom during two subsequent years participated in a writing intervention which included learning about text features, conducting…

Controversy, Trials, and Crime--Oh My!

ERIC Educational Resources Information Center

Rott, Kim

2006-01-01

Teenagers' innate interest with the justice system is one of the reasons that so many high school literary classics teem with criminals, controversial issues, and trials. Novels such as "To Kill a Mockingbird," "A Separate Peace," "The Crucible," and "Twelve Angry Men" feature high-impact trials. In the author's desire to tap into this interest,…

Automatic change detection: does the auditory system use representations of individual stimulus features or gestalts?

PubMed

Deacon, D; Nousak, J M; Pilotti, M; Ritter, W; Yang, C M

1998-07-01

The effects of global and feature-specific probabilities of auditory stimuli were manipulated to determine their effects on the mismatch negativity (MMN) of the human event-related potential. The question of interest was whether the automatic comparison of stimuli indexed by the MMN was performed on representations of individual stimulus features or on gestalt representations of their combined attributes. The design of the study was such that both feature and gestalt representations could have been available to the comparator mechanism generating the MMN. The data were consistent with the interpretation that the MMN was generated following an analysis of stimulus features.

A Mapping Study on Mobile Games for Patients of Chronic Diseases.

PubMed

de Sá, Kévin Cardoso; Martins, Márcio Garcia; da Costa, Cristiano André; Barbosa, Jorge Luis Victoria; da Rosa Righi, Rodrigo

2017-09-01

There is a growing interest of using technologies to propose solutions for healthcare issues. One of such issues is the incidence of chronic diseases, which are responsible for a considerable proportion of worldwide mortality. It is possible to prevent the development of such diseases using tools and methods that instruct the population. To achieve this, mobile games provide a powerful environment for teaching different subjects to user, without them actively knowing that they are learning new concepts. Despite the growing interest of using mobile games in healthcare, more specifically by patients with chronic diseases, in the best of our knowledge there are no studies that address the current research being published in the area. To close this gap, we carried out a systematic mapping study to synthesize an overview of the area. Five databases were searched and more than 1200 studies were analyzed and filtered. Among them, 17 met the the inclusion and exclusion criteria defined in this work. The results show that there is still room for research in this area, since the studies focus on a younger audience rather than proposing solutions for all ages. Furthermore, the number of chronic conditions being addressed is still small, obesity and diabetes are prevalent. Besides, the full capacity of game features that foster learning through games are not being employed, the majority of games proposed by the articles encompass less than half of these features.

3D Polyaniline Architecture by Concurrent Inorganic and Organic Acid Doping for Superior and Robust High Rate Supercapacitor Performance

PubMed Central

Gawli, Yogesh; Banerjee, Abhik; Dhakras, Dipti; Deo, Meenal; Bulani, Dinesh; Wadgaonkar, Prakash; Shelke, Manjusha; Ogale, Satishchandra

2016-01-01

A good high rate supercapacitor performance requires a fine control of morphological (surface area and pore size distribution) and electrical properties of the electrode materials. Polyaniline (PANI) is an interesting material in supercapacitor context because it stores energy Faradaically. However in conventional inorganic (e.g. HCl) acid doping, the conductivity is high but the morphological features are undesirable. On the other hand, in weak organic acid (e.g. phytic acid) doping, interesting and desirable 3D connected morphological features are attained but the conductivity is poorer. Here the synergy of the positive quality factors of these two acid doping approaches is realized by concurrent and optimized strong-inorganic (HCl) and weak-organic (phytic) acid doping, resulting in a molecular composite material that renders impressive and robust supercapacitor performance. Thus, a nearly constant high specific capacitance of 350 F g−1 is realized for the optimised case of binary doping over the entire range of 1 A g−1 to 40 A g−1 with stability of 500 cycles at 40 A g−1. Frequency dependant conductivity measurements show that the optimized co-doped case is more metallic than separately doped materials. This transport property emanates from the unique 3D single molecular character of such system. PMID:26867570

Jacobian-free approximate solvers for hyperbolic systems: Application to relativistic magnetohydrodynamics

NASA Astrophysics Data System (ADS)

Castro, Manuel J.; Gallardo, José M.; Marquina, Antonio

2017-10-01

We present recent advances in PVM (Polynomial Viscosity Matrix) methods based on internal approximations to the absolute value function, and compare them with Chebyshev-based PVM solvers. These solvers only require a bound on the maximum wave speed, so no spectral decomposition is needed. Another important feature of the proposed methods is that they are suitable to be written in Jacobian-free form, in which only evaluations of the physical flux are used. This is particularly interesting when considering systems for which the Jacobians involve complex expressions, e.g., the relativistic magnetohydrodynamics (RMHD) equations. On the other hand, the proposed Jacobian-free solvers have also been extended to the case of approximate DOT (Dumbser-Osher-Toro) methods, which can be regarded as simple and efficient approximations to the classical Osher-Solomon method, sharing most of it interesting features and being applicable to general hyperbolic systems. To test the properties of our schemes a number of numerical experiments involving the RMHD equations are presented, both in one and two dimensions. The obtained results are in good agreement with those found in the literature and show that our schemes are robust and accurate, running stable under a satisfactory time step restriction. It is worth emphasizing that, although this work focuses on RMHD, the proposed schemes are suitable to be applied to general hyperbolic systems.

Out-of-time-ordered measurements as a probe of quantum dynamics

NASA Astrophysics Data System (ADS)

Bordia, Pranjal; Alet, Fabien; Hosur, Pavan

2018-03-01

Probing the out-of-equilibrium dynamics of quantum matter has gained renewed interest owing to immense experimental progress in artificial quantum systems. Dynamical quantum measures such as the growth of entanglement entropy and out-of-time-ordered correlators (OTOCs) have been shown to provide great insight by exposing subtle quantum features invisible to traditional measures such as mass transport. However, measuring them in experiments requires either identical copies of the system, an ancilla qubit coupled to the whole system, or many measurements on a single copy, thereby making scalability extremely complex and hence, severely limiting their potential. Here, we introduce an alternative quantity, the out-of-time-ordered measurement (OTOM), which involves measuring a single observable on a single copy of the system, while retaining the distinctive features of the OTOCs. We show, theoretically, that OTOMs are closely related to OTOCs in a doubled system with the same quantum statistical properties as the original system. Using exact diagonalization, we numerically simulate classical mass transport, as well as quantum dynamics through computations of the OTOC, the OTOM, and the entanglement entropy in quantum spin chain models in various interesting regimes (including chaotic and many-body localized systems). Our results demonstrate that an OTOM can successfully reveal subtle aspects of quantum dynamics hidden to classical measures and, crucially, provide experimental access to them.

The YeastGenome app: the Saccharomyces Genome Database at your fingertips.

PubMed

Wong, Edith D; Karra, Kalpana; Hitz, Benjamin C; Hong, Eurie L; Cherry, J Michael

2013-01-01

The Saccharomyces Genome Database (SGD) is a scientific database that provides researchers with high-quality curated data about the genes and gene products of Saccharomyces cerevisiae. To provide instant and easy access to this information on mobile devices, we have developed YeastGenome, a native application for the Apple iPhone and iPad. YeastGenome can be used to quickly find basic information about S. cerevisiae genes and chromosomal features regardless of internet connectivity. With or without network access, you can view basic information and Gene Ontology annotations about a gene of interest by searching gene names and gene descriptions or by browsing the database within the app to find the gene of interest. With internet access, the app provides more detailed information about the gene, including mutant phenotypes, references and protein and genetic interactions, as well as provides hyperlinks to retrieve detailed information by showing SGD pages and views of the genome browser. SGD provides online help describing basic ways to navigate the mobile version of SGD, highlights key features and answers frequently asked questions related to the app. The app is available from iTunes (http://itunes.com/apps/yeastgenome). The YeastGenome app is provided freely as a service to our community, as part of SGD's mission to provide free and open access to all its data and annotations.

Inorganic anion-dependent assembly of zero-, one-, two- and three-dimensional Cu(II)/Ag(I) complexes under the guidance of the HSAB theory: Synthesis, structure, and magnetic property

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

Liu, Yaru; Xing, Zhiyan; Zhang, Xiao

To systematically explore the influence of inorganic anions on building coordination complexes, five novel complexes based on 1-(benzotriazole-1-methyl)−2-propylimidazole (bpmi), [Cu(bpmi){sub 2}(Ac){sub 2}]·H{sub 2}O (1), [Cu(bpmi){sub 2}(H{sub 2}O){sub 2}]·2NO{sub 3}·2H{sub 2}O (2), [Cu(bpmi)(N{sub 3}){sub 2}] (3), [Ag(bpmi)(NO{sub 3})] (4) and [Cu{sub 3}(bpmi){sub 2}(SCN){sub 4}(DMF)] (5) (Ac{sup −}=CH{sub 3}COO{sup −}, DMF=N,N-Dimethylformamide) are synthesized through rationally introducing Cu(II) salts and Ag(I) salt with different inorganic anions. X-ray single-crystal analyses reveal that these complexes show interesting structural features from mononuclear (1), one-dimensional (2 and 3), two-dimensional (4) to three-dimensional (5) under the influence of inorganic anions with different basicities. The structural variation can bemore » explained by the hard-soft-acid-base (HSAB) theory. Magnetic susceptibility measurement indicates that complex 3 exhibits an antiferromagnetic coupling between adjacent Cu(II) ions. - Graphical abstract: Five new Cu(II)/Ag(I) complexes show interesting structural features from mononuclear, one-dimension, two-dimension to three-dimension under the influence of inorganic anions. The structural variation can be explained by the HSAB theory. - Highlights: • Five inorganic anion-dependent complexes are synthesized. • Structural variation can be explained by the hard-soft-acid-base (HSAB) theory. • The magnetic property of complex has been studied.« less

Development and Testing of Geo-Processing Models for the Automatic Generation of Remediation Plan and Navigation Data to Use in Industrial Disaster Remediation

NASA Astrophysics Data System (ADS)

Lucas, G.; Lénárt, C.; Solymosi, J.

2015-08-01

This paper introduces research done on the automatic preparation of remediation plans and navigation data for the precise guidance of heavy machinery in clean-up work after an industrial disaster. The input test data consists of a pollution extent shapefile derived from the processing of hyperspectral aerial survey data from the Kolontár red mud disaster. Three algorithms were developed and the respective scripts were written in Python. The first model aims at drawing a parcel clean-up plan. The model tests four different parcel orientations (0, 90, 45 and 135 degree) and keeps the plan where clean-up parcels are less numerous considering it is an optimal spatial configuration. The second model drifts the clean-up parcel of a work plan both vertically and horizontally following a grid pattern with sampling distance of a fifth of a parcel width and keep the most optimal drifted version; here also with the belief to reduce the final number of parcel features. The last model aims at drawing a navigation line in the middle of each clean-up parcel. The models work efficiently and achieve automatic optimized plan generation (parcels and navigation lines). Applying the first model we demonstrated that depending on the size and geometry of the features of the contaminated area layer, the number of clean-up parcels generated by the model varies in a range of 4% to 38% from plan to plan. Such a significant variation with the resulting feature numbers shows that the optimal orientation identification can result in saving work, time and money in remediation. The various tests demonstrated that the model gains efficiency when 1/ the individual features of contaminated area present a significant orientation with their geometry (features are long), 2/ the size of pollution extent features becomes closer to the size of the parcels (scale effect). The second model shows only 1% difference with the variation of feature number; so this last is less interesting for planning optimization applications. Last model rather simply fulfils the task it was designed for by drawing navigation lines.

Using Simplistic Shape/Surface Models to Predict Brightness in Estimation Filters

NASA Astrophysics Data System (ADS)

Wetterer, C.; Sheppard, D.; Hunt, B.

The prerequisite for using brightness (radiometric flux intensity) measurements in an estimation filter is to have a measurement function that accurately predicts a space objects brightness for variations in the parameters of interest. These parameters include changes in attitude and articulations of particular components (e.g. solar panel east-west offsets to direct sun-tracking). Typically, shape models and bidirectional reflectance distribution functions are combined to provide this forward light curve modeling capability. To achieve precise orbit predictions with the inclusion of shape/surface dependent forces such as radiation pressure, relatively complex and sophisticated modeling is required. Unfortunately, increasing the complexity of the models makes it difficult to estimate all those parameters simultaneously because changes in light curve features can now be explained by variations in a number of different properties. The classic example of this is the connection between the albedo and the area of a surface. If, however, the desire is to extract information about a single and specific parameter or feature from the light curve, a simple shape/surface model could be used. This paper details an example of this where a complex model is used to create simulated light curves, and then a simple model is used in an estimation filter to extract out a particular feature of interest. In order for this to be successful, however, the simple model must be first constructed using training data where the feature of interest is known or at least known to be constant.

Improving cervical region of interest by eliminating vaginal walls and cotton-swabs for automated image analysis

NASA Astrophysics Data System (ADS)

Venkataraman, Sankar; Li, Wenjing

2008-03-01

Image analysis for automated diagnosis of cervical cancer has attained high prominence in the last decade. Automated image analysis at all levels requires a basic segmentation of the region of interest (ROI) within a given image. The precision of the diagnosis is often reflected by the precision in detecting the initial region of interest, especially when some features outside the ROI mimic the ones within the same. Work described here discusses algorithms that are used to improve the cervical region of interest as a part of automated cervical image diagnosis. A vital visual aid in diagnosing cervical cancer is the aceto-whitening of the cervix after the application of acetic acid. Color and texture are used to segment acetowhite regions within the cervical ROI. Vaginal walls along with cottonswabs sometimes mimic these essential features leading to several false positives. Work presented here is focused towards detecting in-focus vaginal wall boundaries and then extrapolating them to exclude vaginal walls from the cervical ROI. In addition, discussed here is a marker-controlled watershed segmentation that is used to detect cottonswabs from the cervical ROI. A dataset comprising 50 high resolution images of the cervix acquired after 60 seconds of acetic acid application were used to test the algorithm. Out of the 50 images, 27 benefited from a new cervical ROI. Significant improvement in overall diagnosis was observed in these images as false positives caused by features outside the actual ROI mimicking acetowhite region were eliminated.

Basic Radar Altimetry Toolbox and Radar Altimetry Tutorial: Tools for all Altimetry Users

NASA Astrophysics Data System (ADS)

Rosmorduc, Vinca; Benveniste, J.; Breebaart, L.; Bronner, E.; Dinardo, S.; Earith, D.; Lucas, B. M.; Maheu, C.; Niejmeier, S.; Picot, N.

2013-09-01

The Basic Radar Altimetry Toolbox is an "all- altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data, including the next mission to be launched, Saral.It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. Nearly 2000 people downloaded it (January 2012), with many "newcomers" to altimetry among them. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 to 4. Others are under development, some are in discussion for the future.The Basic Radar Altimetry Toolbox is able:- to read most distributed radar altimetry data, including the one from future missions like Saral, Jason-3- to perform some processing, data editing and statistic, - and to visualize the results.It can be used at several levels/several ways, including as an educational tool, with the graphical user interface.As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data.BRAT is developed under contract with ESA and CNES. It is available at http://www.altimetry.info and http://earth.esa.int/brat/It has been available from April 2007, and had been demonstrated during training courses and scientific meetings. More than 2000 people downloaded it (as of end of September 2012), with many "newcomers" to altimetry among them, and teachers/students. Users' feedbacks, developments in altimetry, and practice, showed that new interesting features could be added. Some have been added and/or improved in version 2 and 3. Others are envisioned, some are in discussion.

Mineralogical Analysis of the Oppia Quadrangle of Asteroid (4) Vesta: Evidence for Occurrence of Moderate-Reflectance Hydrated Minerals

NASA Technical Reports Server (NTRS)

Tosi, F.; Frigeri, A.; Combe, J.-Ph.; Zambon, F.; De Sanctis, M. C.; Ammannito, E.; Longobardo, A.; Hoffmann, M.; Nathues, A.; Garry, W. B.;

Geomorphology, tectonics, and exploration

NASA Technical Reports Server (NTRS)

Sabins, F. F., Jr.

1985-01-01

Explorationists interpret satellite images for tectonic features and patterns that may be clues to mineral and energy deposits. The tectonic features of interest range in scale from regional (sedimentary basins, fold belts) to local (faults, fractures) and are generally expressed as geomorphic features in remote sensing images. Explorationists typically employ classic concepts of geomorphology and landform analysis for their interpretations, which leads to the question - Are there new and evolving concepts in geomorphology that may be applicable to tectonic analyses of images?

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers.

PubMed

Mougiakakou, Stavroula G; Valavanis, Ioannis K; Nikita, Alexandra; Nikita, Konstantina S

2007-09-01

The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed. Number of regions of interests (ROIs) corresponding to C1-C4 have been defined by experienced radiologists in non-enhanced liver CT images. For each ROI, five distinct sets of texture features were extracted using first order statistics, spatial gray level dependence matrix, gray level difference method, Laws' texture energy measures, and fractal dimension measurements. Two different ECs were constructed and compared. The first one consists of five multilayer perceptron neural networks (NNs), each using as input one of the computed texture feature sets or its reduced version after genetic algorithm-based feature selection. The second EC comprised five different primary classifiers, namely one multilayer perceptron NN, one probabilistic NN, and three k-nearest neighbor classifiers, each fed with the combination of the five texture feature sets or their reduced versions. The final decision of each EC was extracted by using appropriate voting schemes, while bootstrap re-sampling was utilized in order to estimate the generalization ability of the CAD architectures based on the available relatively small-sized data set. The best mean classification accuracy (84.96%) is achieved by the second EC using a fused feature set, and the weighted voting scheme. The fused feature set was obtained after appropriate feature selection applied to specific subsets of the original feature set. The comparative assessment of the various CAD architectures shows that combining three types of classifiers with a voting scheme, fed with identical feature sets obtained after appropriate feature selection and fusion, may result in an accurate system able to assist differential diagnosis of focal liver lesions from non-enhanced CT images.

Fast Exact Search in Hamming Space With Multi-Index Hashing.

PubMed

Norouzi, Mohammad; Punjani, Ali; Fleet, David J

2014-06-01

There is growing interest in representing image data and feature descriptors using compact binary codes for fast near neighbor search. Although binary codes are motivated by their use as direct indices (addresses) into a hash table, codes longer than 32 bits are not being used as such, as it was thought to be ineffective. We introduce a rigorous way to build multiple hash tables on binary code substrings that enables exact k-nearest neighbor search in Hamming space. The approach is storage efficient and straight-forward to implement. Theoretical analysis shows that the algorithm exhibits sub-linear run-time behavior for uniformly distributed codes. Empirical results show dramatic speedups over a linear scan baseline for datasets of up to one billion codes of 64, 128, or 256 bits.

Kinetic market models with single commodity having price fluctuations

NASA Astrophysics Data System (ADS)

Chatterjee, A.; Chakrabarti, B. K.

2006-12-01

We study here numerically the behavior of an ideal gas like model of markets having only one non-consumable commodity. We investigate the behavior of the steady-state distributions of money, commodity and total wealth, as the dynamics of trading or exchange of money and commodity proceeds, with local (in time) fluctuations in the price of the commodity. These distributions are studied in markets with agents having uniform and random saving factors. The self-organizing features in money distribution are similar to the cases without any commodity (or with consumable commodities), while the commodity distribution shows an exponential decay. The wealth distribution shows interesting behavior: gamma like distribution for uniform saving propensity and has the same power-law tail, as that of the money distribution, for a market with agents having random saving propensity.

Topologically Nontrivial Magnon Bands in Artificial Square Spin Ices with Dzyaloshinskii-Moriya Interaction

NASA Astrophysics Data System (ADS)

Iacocca, Ezio; Heinonen, Olle

2017-09-01

Systems that exhibit topologically protected edge states are interesting both from a fundamental point of view as well as for potential applications, the latter because of the absence of backscattering and robustness to perturbations. It is desirable to be able to control and manipulate such edge states. Here, we show that artificial square ices can incorporate both features: an interfacial Dzyaloshinskii-Moriya interaction gives rise to topologically nontrivial magnon bands, and the equilibrium state of the spin ice is reconfigurable with different configurations having different magnon dispersions and topology. The topology is found to develop as odd-symmetry bulk and edge magnon bands approach each other so that constructive band inversion occurs in reciprocal space. Our results show that topologically protected bands are supported in square spin ices.

[Max Weber's illness--sociologic aspects of the depressive structure].

PubMed

Frommer, J; Frommer, S

1993-05-01

Between 1897 and 1902 the economist and sociologist Max Weber from Heidelberg suffered from a severe depressive crisis with multiple recurrences of its symptomatology in the following years. The biographic background of the disease process is examined. Questions regarding the specific diagnosis are discussed. Furthermore, his work shows that Weber was indirectly deeply concerned with the cultural, historical and social background conditions of depressive experience and behavior in the context of his study on Protestantic Ethics and the Spirit of Capitalism. Weber's definition of modern society as an iron cage, determined by Occidental Rationalism, shows that this cultural background demands a great amount of role conformity from the individual. Weber's theoretical approach should spark interest in the current psychopathological discussion of the characteristic structural features of a depressed personality.

Dissimilarity representations in lung parenchyma classification

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; de Bruijne, Marleen

2009-02-01

A good problem representation is important for a pattern recognition system to be successful. The traditional approach to statistical pattern recognition is feature representation. More specifically, objects are represented by a number of features in a feature vector space, and classifiers are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal, healthy tissue. Two dissimilarity representation approaches as well as different histogram dissimilarity measures are considered. The approaches are evaluated on a set of 168 CT ROIs using normal density based classifiers all showing good performance. Compared to using histogram dissimilarity directly as distance in a emph{k} nearest neighbor classifier, which achieves a classification accuracy of 92.9%, the best dissimilarity representation based classifier is significantly better with a classification accuracy of 97.0% (text{emph{p" border="0" class="imgtopleft"> = 0.046).

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

PubMed

Okumura, Eiichiro; Kawashita, Ikuo; Ishida, Takayuki

2017-08-01

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

An Efficient Method to Detect Mutual Overlap of a Large Set of Unordered Images for Structure-From

NASA Astrophysics Data System (ADS)

Wang, X.; Zhan, Z. Q.; Heipke, C.

2017-05-01

Recently, low-cost 3D reconstruction based on images has become a popular focus of photogrammetry and computer vision research. Methods which can handle an arbitrary geometric setup of a large number of unordered and convergent images are of particular interest. However, determining the mutual overlap poses a considerable challenge. We propose a new method which was inspired by and improves upon methods employing random k-d forests for this task. Specifically, we first derive features from the images and then a random k-d forest is used to find the nearest neighbours in feature space. Subsequently, the degree of similarity between individual images, the image overlaps and thus images belonging to a common block are calculated as input to a structure-from-motion (sfm) pipeline. In our experiments we show the general applicability of the new method and compare it with other methods by analyzing the time efficiency. Orientations and 3D reconstructions were successfully conducted with our overlap graphs by sfm. The results show a speed-up of a factor of 80 compared to conventional pairwise matching, and of 8 and 2 compared to the VocMatch approach using 1 and 4 CPU, respectively.

Using Ontologies for the Online Recognition of Activities of Daily Living†

PubMed Central

2018-01-01

The recognition of activities of daily living is an important research area of interest in recent years. The process of activity recognition aims to recognize the actions of one or more people in a smart environment, in which a set of sensors has been deployed. Usually, all the events produced during each activity are taken into account to develop the classification models. However, the instant in which an activity started is unknown in a real environment. Therefore, only the most recent events are usually used. In this paper, we use statistics to determine the most appropriate length of that interval for each type of activity. In addition, we use ontologies to automatically generate features that serve as the input for the supervised learning algorithms that produce the classification model. The features are formed by combining the entities in the ontology, such as concepts and properties. The results obtained show a significant increase in the accuracy of the classification models generated with respect to the classical approach, in which only the state of the sensors is taken into account. Moreover, the results obtained in a simulation of a real environment under an event-based segmentation also show an improvement in most activities. PMID:29662011

We're mass communicating: podcasting as outreach

NASA Astrophysics Data System (ADS)

Nugent, Carolyn R.

2015-11-01

The New York Times (July 18th, 2015) called podcasting "that rarest thing in the technology industry"; a subset of media showing sustained growth. That same article quotes an Edison Research report that found that roughly 1/5 Americans have listened to a podcast in the last month. The most popular podcasts receive a million downloads per episode, and over all podcasts, the median number of downloads per episode is ~150 (Libsyn statistics). The popularity and easy accessibility of podcasts make them an ideal vehicle for outreach.There are several excellent podcasts covering planetary science, including Planetary Radio, produced by the Planetary Society, StarTalk Radio, several official NASA podcasts, and individual efforts such as Al Grauer's "Travelers in the Night" and Jane Jones' "What's up".Spacepod is a weekly podcast on space exploration that launched in August 2015. Episodes feature an expert guest discussing an interesting aspect of their job for a general audience. Episodes have an intimate, conversational feel, letting the audience "hang out" with space scientists and engineers. Spacepod has shown strong growth since launch, and was featured in iTunes' "New and Noteworthy" section. Episodes can be found at www.listentospacepod.com, and the show tweets @listen2spacepod.

Digital Device Architecture and the Safe Use of Flash Devices in Munitions

NASA Technical Reports Server (NTRS)

Katz, Richard B.; Flowers, David; Bergevin, Keith

2017-01-01

Flash technology is being utilized in fuzed munition applications and, based on the development of digital logic devices in the commercial world, usage of flash technology will increase. Digital devices of interest to designers include flash-based microcontrollers and field programmable gate arrays (FPGAs). Almost a decade ago, a study was undertaken to determine if flash-based microcontrollers could be safely used in fuzes and, if so, how should such devices be applied. The results were documented in the Technical Manual for the Use of Logic Devices in Safety Features. This paper will first review the Technical Manual and discuss the rationale behind the suggested architectures for microcontrollers and a brief review of the concern about data retention in flash cells. An architectural feature in the microcontroller under study will be discussed and its use will show how to screen for weak or failed cells during manufacture, storage, or immediately prior to use. As was done for microcontrollers a decade ago, architectures for a flash-based FPGA will be discussed, showing how it can be safely used in fuzes. Additionally, architectures for using non-volatile (including flash-based) storage will be discussed for SRAM-based FPGAs.

Orientation is different: Interaction between contour integration and feature contrasts in visual search.

PubMed

Jingling, Li; Tseng, Chia-Huei; Zhaoping, Li

2013-09-10

Salient items usually capture attention and are beneficial to visual search. Jingling and Tseng (2013), nevertheless, have discovered that a salient collinear column can impair local visual search. The display used in that study had 21 rows and 27 columns of bars, all uniformly horizontal (or vertical) except for one column of bars orthogonally oriented to all other bars, making this unique column of collinear (or noncollinear) bars salient in the display. Observers discriminated an oblique target bar superimposed on one of the bars either in the salient column or in the background. Interestingly, responses were slower for a target in a salient collinear column than in the background. This opens a theoretical question of how contour integration interacts with salience computation, which is addressed here by an examination of how salience modulated the search impairment from the collinear column. We show that the collinear column needs to have a high orientation contrast with its neighbors to exert search interference. A collinear column of high contrast in color or luminance did not produce the same impairment. Our results show that orientation-defined salience interacted with collinear contour differently from other feature dimensions, which is consistent with the neuronal properties in V1.

The behavioral and neural binding phenomena during visuomotor integration of angry facial expressions.

PubMed

Coll, Sélim Yahia; Ceravolo, Leonardo; Frühholz, Sascha; Grandjean, Didier

2018-05-02

Different parts of our brain code the perceptual features and actions related to an object, causing a binding problem, in which the brain has to integrate information related to an event without any interference regarding the features and actions involved in other concurrently processed events. Using a paradigm similar to Hommel, who revealed perception-action bindings, we showed that emotion could bind with motor actions when relevant, and in specific conditions, irrelevant for the task. By adapting our protocol to a functional Magnetic Resonance Imaging paradigm we investigated, in the present study, the neural bases of the emotion-action binding with task-relevant angry faces. Our results showed that emotion bound with motor responses. This integration revealed increased activity in distributed brain areas involved in: (i) memory, including the hippocampi; (ii) motor actions with the precentral gyri; (iii) and emotion processing with the insula. Interestingly, increased activations in the cingulate gyri and putamen, highlighted their potential key role in the emotion-action binding, due to their involvement in emotion processing, motor actions, and memory. The present study confirmed our previous results and point out for the first time the functional brain activity related to the emotion-action association.

The 2D analytic signal for envelope detection and feature extraction on ultrasound images.

PubMed

Wachinger, Christian; Klein, Tassilo; Navab, Nassir

2012-08-01

The fundamental property of the analytic signal is the split of identity, meaning the separation of qualitative and quantitative information in form of the local phase and the local amplitude, respectively. Especially the structural representation, independent of brightness and contrast, of the local phase is interesting for numerous image processing tasks. Recently, the extension of the analytic signal from 1D to 2D, covering also intrinsic 2D structures, was proposed. We show the advantages of this improved concept on ultrasound RF and B-mode images. Precisely, we use the 2D analytic signal for the envelope detection of RF data. This leads to advantages for the extraction of the information-bearing signal from the modulated carrier wave. We illustrate this, first, by visual assessment of the images, and second, by performing goodness-of-fit tests to a Nakagami distribution, indicating a clear improvement of statistical properties. The evaluation is performed for multiple window sizes and parameter estimation techniques. Finally, we show that the 2D analytic signal allows for an improved estimation of local features on B-mode images. Copyright © 2012 Elsevier B.V. All rights reserved.

Proteases and protease inhibitors of urinary extracellular vesicles in diabetic nephropathy.

PubMed

Musante, Luca; Tataruch, Dorota; Gu, Dongfeng; Liu, Xinyu; Forsblom, Carol; Groop, Per-Henrik; Holthofer, Harry

2015-01-01

Diabetic nephropathy (DN) is one of the major complications of diabetes mellitus (DM), leads to chronic kidney disease (CKD), and, ultimately, is the main cause for end-stage kidney disease (ESKD). Beyond urinary albumin, no reliable biomarkers are available for accurate early diagnostics. Urinary extracellular vesicles (UEVs) have recently emerged as an interesting source of diagnostic and prognostic disease biomarkers. Here we used a protease and respective protease inhibitor array to profile urines of type 1 diabetes patients at different stages of kidney involvement. Urine samples were divided into groups based on the level of albuminuria and UEVs isolated by hydrostatic dialysis and screened for relative changes of 34 different proteases and 32 protease inhibitors, respectively. Interestingly, myeloblastin and its natural inhibitor elafin showed an increase in the normo- and microalbuminuric groups. Similarly, a characteristic pattern was observed in the array of protease inhibitors, with a marked increase of cystatin B, natural inhibitor of cathepsins L, H, and B as well as of neutrophil gelatinase-associated Lipocalin (NGAL) in the normoalbuminuric group. This study shows for the first time the distinctive alterations in comprehensive protease profiles of UEVs in diabetic nephropathy and uncovers intriguing mechanistic, prognostic, and diagnostic features of kidney damage in diabetes.

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

PubMed Central

Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

2018-01-01

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function. PMID:29320526

Linked Scatter Plots, A Powerful Exploration Tool For Very Large Sets of Spectra

NASA Astrophysics Data System (ADS)

Carbon, Duane Francis; Henze, Christopher

2015-08-01

We present a new tool, based on linked scatter plots, that is designed to efficiently explore very large spectrum data sets such as the SDSS, APOGEE, LAMOST, GAIA, and RAVE data sets.The tool works in two stages: the first uses batch processing and the second runs interactively. In the batch stage, spectra are processed through our data pipeline which computes the depths relative to the local continuum at preselected feature wavelengths. These depths, and any additional available variables such as local S/N level, magnitudes, colors, positions, and radial velocities, are the basic measured quantities used in the interactive stage.The interactive stage employs the NASA hyperwall, a configuration of 128 workstation displays (8x16 array) controlled by a parallelized software suite running on NASA's Pleiades supercomputer. Each hyperwall panel is used to display a fully linked 2-D scatter plot showing the depth of feature A vs the depth of feature B for all of the spectra. A and B change from panel to panel. The relationships between the various (A,B) strengths and any distinctive clustering, as well as unique outlier groupings, are visually apparent when examining and inter-comparing the different panels on the hyperwall. In addition, the data links between the scatter plots allow the user to apply a logical algebra to the measurements. By graphically selecting the objects in any interesting region of any 2-D plot on the hyperwall, the tool immediately and clearly shows how the selected objects are distributed in all the other 2-D plots. The selection process may be repeated multiple times and, at each step, the selections can represent a sequence of logical constraints on the measurements, revealing those objects which satisfy all the constraints thus far. The spectra of the selected objects may be examined at any time on a connected workstation display.Using over 945,000,000 depth measurements from 569,738 SDSS DR10 stellar spectra, we illustrate how to quickly isolate and examine such interesting stellar subsets as EMP stars, C-rich EMP stars, and CV stars.

Ultrastructural characterisation of the olfactory mucosa of the armadillo Dasypus hybridus (Dasypodidae, Xenarthra)

PubMed Central

FERRARI, C. C.; CARMANCHAHI, P. D.; ALDANA MARCOS, H. J.; AFFANNI, J. M.

2000-01-01

The ultrastructure of the olfactory mucosa of the armadillo Dasypus hybridus was studied. A comparison with the olfactory mucosa of another armadillo (Chaetophractus villosus) was made. The olfactory mucosa of D. hybridus shows many features which are similar to those of other mammals. Interestingly, it differs from the olfactory mucosa of the armadillo C. villosus. A suggestion is made that these differences may be due to differences in the digging habits of these species. In Dasypus, the supporting cells (SCs) showed dense vacuoles, multivesicular bodies and lysosome-like bodies probably related with the endocytotic system. The SCs show a dense network of SER presumably associated with xenobiotic mechanisms. The olfactory receptor neurons exhibit lysosome-like bodies and multivesicular bodies in their perikarya. These organelles suggest the presence of an endocytotic system. Duct cells of Bowman's glands exhibit secretory activities. Bowman's glands are compound-branched tubulo-acinar mixed glands with merocrine secretory mechanisms. PMID:10739023

Analysis of psycho-physiological features of a subject in simple tests with the registration of electroencephalograms

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya; Zhuravlev, Maxim; Kulanin, Roman; Protasov, Pavel; Efremova, Tatiana

2018-04-01

In this paper we found a correlation between the characteristics of a person revealed in classical psychological testing on the basis of Schulte tables, and its neurophysiological features of the functioning of the brain obtained from the time-frequency analysis of EEG. The results obtained are interesting from the point of view of the choice of training strategies for a particular individual. We believe that the obtained results are of interest for fundamental science and applied works of psychological testing and diagnostics. The study of such forming strategies on EEG data can be automated and do not require the work of highly skilled psychologists.

Profiling plasma extracellular vesicle by pluronic block-copolymer based enrichment method unveils features associated with breast cancer aggression, metastasis and invasion

PubMed Central

Rosenow, Matthew; Xiao, Nick; Spetzler, David

2018-01-01

ABSTRACT Extracellular vesicle (EV)-based liquid biopsies have been proposed to be a readily obtainable biological substrate recently for both profiling and diagnostics purposes. Development of a fast and reliable preparation protocol to enrich such small particles could accelerate the discovery of informative, disease-related biomarkers. Though multiple EV enrichment protocols are available, in terms of efficiency, reproducibility and simplicity, precipitation-based methods are most amenable to studies with large numbers of subjects. However, the selectivity of the precipitation becomes critical. Here, we present a simple plasma EV enrichment protocol based on pluronic block copolymer. The enriched plasma EV was able to be verified by multiple platforms. Our results showed that the particles enriched from plasma by the copolymer were EV size vesicles with membrane structure; proteomic profiling showed that EV-related proteins were significantly enriched, while high-abundant plasma proteins were significantly reduced in comparison to other precipitation-based enrichment methods. Next-generation sequencing confirmed the existence of various RNA species that have been observed in EVs from previous studies. Small RNA sequencing showed enriched species compared to the corresponding plasma. Moreover, plasma EVs enriched from 20 advanced breast cancer patients and 20 age-matched non-cancer controls were profiled by semi-quantitative mass spectrometry. Protein features were further screened by EV proteomic profiles generated from four breast cancer cell lines, and then selected in cross-validation models. A total of 60 protein features that highly contributed in model prediction were identified. Interestingly, a large portion of these features were associated with breast cancer aggression, metastasis as well as invasion, consistent with the advanced clinical stage of the patients. In summary, we have developed a plasma EV enrichment method with improved precipitation selectivity and it might be suitable for larger-scale discovery studies. PMID:29696079

Chemical name extraction based on automatic training data generation and rich feature set.

PubMed

Yan, Su; Spangler, W Scott; Chen, Ying

2013-01-01

The automation of extracting chemical names from text has significant value to biomedical and life science research. A major barrier in this task is the difficulty of getting a sizable and good quality data to train a reliable entity extraction model. Another difficulty is the selection of informative features of chemical names, since comprehensive domain knowledge on chemistry nomenclature is required. Leveraging random text generation techniques, we explore the idea of automatically creating training sets for the task of chemical name extraction. Assuming the availability of an incomplete list of chemical names, called a dictionary, we are able to generate well-controlled, random, yet realistic chemical-like training documents. We statistically analyze the construction of chemical names based on the incomplete dictionary, and propose a series of new features, without relying on any domain knowledge. Compared to state-of-the-art models learned from manually labeled data and domain knowledge, our solution shows better or comparable results in annotating real-world data with less human effort. Moreover, we report an interesting observation about the language for chemical names. That is, both the structural and semantic components of chemical names follow a Zipfian distribution, which resembles many natural languages.

Identification of vegetable diseases using neural network

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Tang, Jianjun; Li, Yao

2007-02-01

Vegetables are widely planted all over China, but they often suffer from the some diseases. A method of major technical and economical importance is introduced in this paper, which explores the feasibility of implementing fast and reliable automatic identification of vegetable diseases and their infection grades from color and morphological features of leaves. Firstly, leaves are plucked from clustered plant and pictures of the leaves are taken with a CCD digital color camera. Secondly, color and morphological characteristics are obtained by standard image processing techniques, for examples, Otsu thresholding method segments the region of interest, image opening following closing algorithm removes noise, Principal Components Analysis reduces the dimension of the original features. Then, a recently proposed boosting algorithm AdaBoost. M2 is applied to RBF networks for diseases classification based on the above features, where the kernel function of RBF networks is Gaussian form with argument taking Euclidean distance of the input vector from a center. Our experiment performs on the database collected by Chinese Academy of Agricultural Sciences, and result shows that Boosting RBF Networks classifies the 230 cucumber leaves into 2 different diseases (downy-mildew and angular-leaf-spot), and identifies the infection grades of each disease according to the infection degrees.

Knowledge Discovery in Literature Data Bases

NASA Astrophysics Data System (ADS)

Albrecht, Rudolf; Merkl, Dieter

The concept of knowledge discovery as defined through ``establishing previously unknown and unsuspected relations of features in a data base'' is, cum grano salis, relatively easy to implement for data bases containing numerical data. Increasingly we find at our disposal data bases containing scientific literature. Computer assisted detection of unknown relations of features in such data bases would be extremely valuable and would lead to new scientific insights. However, the current representation of scientific knowledge in such data bases is not conducive to computer processing. Any correlation of features still has to be done by the human reader, a process which is plagued by ineffectiveness and incompleteness. On the other hand we note that considerable progress is being made in an area where reading all available material is totally prohibitive: the World Wide Web. Robots and Web crawlers mine the Web continuously and construct data bases which allow the identification of pages of interest in near real time. An obvious step is to categorize and classify the documents in the text data base. This can be used to identify papers worth reading, or which are of unexpected cross-relevance. We show the results of first experiments using unsupervised classification based on neural networks.

Rheology as a Tool to Predict the Release of Alpha-Lipoic Acid from Emulsions Used for the Prevention of Skin Aging

PubMed Central

Isaac, Vera Lucia Borges; Chiari-Andréo, Bruna Galdorfini; Marto, Joana Marques; Moraes, Jemima Daniela Dias; Leone, Beatriz Alves; Corrêa, Marcos Antonio; Ribeiro, Helena Margarida

2015-01-01

The availability of an active substance through the skin depends basically on two consecutive steps: the release of this substance from the vehicle and its subsequent permeation through the skin. Hence, studies on the specific properties of vehicles, such as their rheological behavior, are of great interest in the field of dermatological products. Recent studies have shown the influence of the rheological features of a vehicle on the release of drugs and active compounds from the formulation. In this context, the aim of this study was to evaluate the influence of the rheological features of two different emulsion formulations on the release of alpha-lipoic acid. Alpha-lipoic acid (ALA) was chosen for this study because of its antioxidant characteristics, which could be useful for the prevention of skin diseases and aging. The rheological and mechanical behavior and the in vitro release profile were assayed. The results showed that rheological features, such as viscosity, thixotropy, and compliance, strongly influenced the release of ALA from the emulsion and that the presence of a hydrophilic polymer in one of the emulsions was an important factor affecting the rheology and, therefore, the release of ALA. PMID:26788510

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory.

PubMed

Keshmiri, Soheil; Sumioka, Hidenubo; Yamazaki, Ryuji; Ishiguro, Hiroshi

2018-01-01

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli.

Topic segmentation via community detection in complex networks

NASA Astrophysics Data System (ADS)

de Arruda, Henrique F.; Costa, Luciano da F.; Amancio, Diego R.

2016-06-01

Many real systems have been modeled in terms of network concepts, and written texts are a particular example of information networks. In recent years, the use of network methods to analyze language has allowed the discovery of several interesting effects, including the proposition of novel models to explain the emergence of fundamental universal patterns. While syntactical networks, one of the most prevalent networked models of written texts, display both scale-free and small-world properties, such a representation fails in capturing other textual features, such as the organization in topics or subjects. We propose a novel network representation whose main purpose is to capture the semantical relationships of words in a simple way. To do so, we link all words co-occurring in the same semantic context, which is defined in a threefold way. We show that the proposed representations favor the emergence of communities of semantically related words, and this feature may be used to identify relevant topics. The proposed methodology to detect topics was applied to segment selected Wikipedia articles. We found that, in general, our methods outperform traditional bag-of-words representations, which suggests that a high-level textual representation may be useful to study the semantical features of texts.

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

PubMed

Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque

2017-01-01

Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).

Style-independent document labeling: design and performance evaluation

NASA Astrophysics Data System (ADS)

Mao, Song; Kim, Jong Woo; Thoma, George R.

2003-12-01

The Medical Article Records System or MARS has been developed at the U.S. National Library of Medicine (NLM) for automated data entry of bibliographical information from medical journals into MEDLINE, the premier bibliographic citation database at NLM. Currently, a rule-based algorithm (called ZoneCzar) is used for labeling important bibliographical fields (title, author, affiliation, and abstract) on medical journal article page images. While rules have been created for medical journals with regular layout types, new rules have to be manually created for any input journals with arbitrary or new layout types. Therefore, it is of interest to label any journal articles independent of their layout styles. In this paper, we first describe a system (called ZoneMatch) for automated generation of crucial geometric and non-geometric features of important bibliographical fields based on string-matching and clustering techniques. The rule based algorithm is then modified to use these features to perform style-independent labeling. We then describe a performance evaluation method for quantitatively evaluating our algorithm and characterizing its error distributions. Experimental results show that the labeling performance of the rule-based algorithm is significantly improved when the generated features are used.

Biophysical model of prokaryotic diversity in geothermal hot springs.

PubMed

Klales, Anna; Duncan, James; Nett, Elizabeth Janus; Kane, Suzanne Amador

2012-02-01

Recent studies of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than a single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. We present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms. © 2012 American Physical Society

Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations.

PubMed

Cao, Houwei; Savran, Arman; Verma, Ragini; Nenkova, Ani

2015-01-01

In this article we investigate what representations of acoustics and word usage are most suitable for predicting dimensions of affect|AROUSAL, VALANCE, POWER and EXPECTANCY|in spontaneous interactions. Our experiments are based on the AVEC 2012 challenge dataset. For lexical representations, we compare corpus-independent features based on psychological word norms of emotional dimensions, as well as corpus-dependent representations. We find that corpus-dependent bag of words approach with mutual information between word and emotion dimensions is by far the best representation. For the analysis of acoustics, we zero in on the question of granularity. We confirm on our corpus that utterance-level features are more predictive than word-level features. Further, we study more detailed representations in which the utterance is divided into regions of interest (ROI), each with separate representation. We introduce two ROI representations, which significantly outperform less informed approaches. In addition we show that acoustic models of emotion can be improved considerably by taking into account annotator agreement and training the model on smaller but reliable dataset. Finally we discuss the potential for improving prediction by combining the lexical and acoustic modalities. Simple fusion methods do not lead to consistent improvements over lexical classifiers alone but improve over acoustic models.

Topic segmentation via community detection in complex networks.

PubMed

de Arruda, Henrique F; Costa, Luciano da F; Amancio, Diego R

2016-06-01

Many real systems have been modeled in terms of network concepts, and written texts are a particular example of information networks. In recent years, the use of network methods to analyze language has allowed the discovery of several interesting effects, including the proposition of novel models to explain the emergence of fundamental universal patterns. While syntactical networks, one of the most prevalent networked models of written texts, display both scale-free and small-world properties, such a representation fails in capturing other textual features, such as the organization in topics or subjects. We propose a novel network representation whose main purpose is to capture the semantical relationships of words in a simple way. To do so, we link all words co-occurring in the same semantic context, which is defined in a threefold way. We show that the proposed representations favor the emergence of communities of semantically related words, and this feature may be used to identify relevant topics. The proposed methodology to detect topics was applied to segment selected Wikipedia articles. We found that, in general, our methods outperform traditional bag-of-words representations, which suggests that a high-level textual representation may be useful to study the semantical features of texts.

Investigating Mars: Russell Crater

NASA Image and Video Library

2017-08-04

This image shows the western part of the dune field on the floor of Russell Crater. Russell Crater is located in Noachis Terra. A spectacular dune ridge and other dune forms on the crater floor have caused extensive imaging. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! Orbit Number: 33970 Latitude: -54.3831 Longitude: 12.3712 Instrument: VIS Captured: 2009-08-11 09:20 https://photojournal.jpl.nasa.gov/catalog/PIA21802

Investigating Mars: Russell Crater

NASA Image and Video Library

2017-08-09

This image shows the central part of the dune field on the floor of Russell Crater. Russell Crater is located in Noachis Terra. A spectacular dune ridge and other dune forms on the crater floor have caused extensive imaging. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! Orbit Number: 34856 Latitude: -54.5757 Longitude: 12.8629 Instrument: VIS Captured: 2009-10-23 08:04 https://photojournal.jpl.nasa.gov/catalog/PIA21806

Investigating Mars: Russell Crater

NASA Image and Video Library

2017-07-31

This image shows a slice of the floor of Russell Crater. Russell Crater is located in Noachis Terra. The spectacular dune ridge and other dune forms on the crater floor have caused extensive imaging. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69,000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! Orbit Number: 6354 Latitude: -54.6188 Longitude: 12.9816 Instrument: VIS Captured: 2003-05-21 14:24 https://photojournal.jpl.nasa.gov/catalog/PIA21798

Language Evolution: Why Hockett's Design Features are a Non-Starter.

PubMed

Wacewicz, Sławomir; Żywiczyński, Przemysław

The set of design features developed by Charles Hockett in the 1950s and 1960s remains probably the most influential means of juxtaposing animal communication with human language. However, the general theoretical perspective of Hockett is largely incompatible with that of modern language evolution research. Consequently, we argue that his classificatory system-while useful for some descriptive purposes-is of very limited use as a theoretical framework for evolutionary linguistics. We see this incompatibility as related to the ontology of language, i.e. deriving from Hockett's interest in language as a product rather than a suite of sensorimotor, cognitive and social abilities that enable the use but also acquisition of language by biological creatures (the faculty of language ). After a reconstruction of Hockett's views on design features, we raise two criticisms: focus on the means at the expense of content and focus on the code itself rather than the cognitive abilities of its users . Finally, referring to empirical data, we illustrate some of the problems resulting from Hockett's approach by addressing three specific points-namely arbitrariness and semanticity , cultural transmission , and displacement -and show how the change of perspective allows to overcome those difficulties.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

Feature selection for examining behavior by pathology laboratories.

PubMed

Hawkins, S; Williams, G; Baxter, R

2001-08-01

Australia has a universal health insurance scheme called Medicare, which is managed by Australia's Health Insurance Commission. Medicare payments for pathology services generate voluminous transaction data on patients, doctors and pathology laboratories. The Health Insurance Commission (HIC) currently uses predictive models to monitor compliance with regulatory requirements. The HIC commissioned a project to investigate the generation of new features from the data. Feature generation has not appeared as an important step in the knowledge discovery in databases (KDD) literature. New interesting features for use in predictive modeling are generated. These features were summarized, visualized and used as inputs for clustering and outlier detection methods. Data organization and data transformation methods are described for the efficient access and manipulation of these new features.

An image-processing method to detect sub-optical features based on understanding noise in intensity measurements.

PubMed

Bhatia, Tripta

2018-07-01

Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.

Features extraction in anterior and posterior cruciate ligaments analysis.

PubMed

Zarychta, P

2015-12-01

The main aim of this research is finding the feature vectors of the anterior and posterior cruciate ligaments (ACL and PCL). These feature vectors have to clearly define the ligaments structure and make it easier to diagnose them. Extraction of feature vectors is obtained by analysis of both anterior and posterior cruciate ligaments. This procedure is performed after the extraction process of both ligaments. In the first stage in order to reduce the area of analysis a region of interest including cruciate ligaments (CL) is outlined in order to reduce the area of analysis. In this case, the fuzzy C-means algorithm with median modification helping to reduce blurred edges has been implemented. After finding the region of interest (ROI), the fuzzy connectedness procedure is performed. This procedure permits to extract the anterior and posterior cruciate ligament structures. In the last stage, on the basis of the extracted anterior and posterior cruciate ligament structures, 3-dimensional models of the anterior and posterior cruciate ligament are built and the feature vectors created. This methodology has been implemented in MATLAB and tested on clinical T1-weighted magnetic resonance imaging (MRI) slices of the knee joint. The 3D display is based on the Visualization Toolkit (VTK). Copyright © 2015 Elsevier Ltd. All rights reserved.

Challenges for psychiatric recruitment and training in Chile.

PubMed

Vicente, Benjamín; Rosel, Leonardo

2013-08-01

This paper aims to describe the current challenges to recruitment of psychiatrists in Chile, and investigate factors related to interest in psychiatry from medical students of the Chilean Biobío Region. An online survey was completed by 39 medical students currently performing the internship. This survey included questions regarding socio-demographic aspects, probability of choosing a medical speciality, influencing factors on the choice of the medical speciality, and personal features. Students were separated in two groups for the analysis based on their likelihood of choosing psychiatry as a career. A total of 35.9% of the respondents showed some degree of interest in psychiatry. Factors considered important by the respondents were academic opportunities, training vacancies, and balance between job and personal life. The low participation in the study does not allow the extrapolation of data to the national situation, and may represent response bias to those already interested in psychiatry as a career. However, Chile has an average psychiatrist rate per number of inhabitants for the region, but an uneven distribution of this resource. National policies must be focused on this issue in order to reduce the gap in mental healthcare.

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

Prognostic and predictive values of oncogenic BRAF, NRAS, c-KIT and MITF in cutaneous and mucous melanoma.

PubMed

Pracht, M; Mogha, A; Lespagnol, A; Fautrel, A; Mouchet, N; Le Gall, F; Paumier, V; Lefeuvre-Plesse, C; Rioux-Leclerc, N; Mosser, J; Oger, E; Adamski, H; Galibert, M-D; Lesimple, T

2015-08-01

Mutations of BRAF, NRAS and c-KIT oncogenes are preferentially described in certain histological subtypes of melanoma and linked to specific histopathological features. BRAF-, MEK- and KIT-inhibitors led to improvement in overall survival of patients harbouring mutated metastatic melanoma. To assess the prevalence and types of BRAF, NRAS, c-KIT and MITF mutations in cutaneous and mucous melanoma and to correlate mutation status with clinicopathological features and outcome. Clinicopathological features and mutation status of 108 samples and of 98 consecutive patients were, respectively, assessed in one retrospective and one prospective study. Clinicopathological features were correlated with mutation status and the predictive value of these mutations was studied. This work identified significant correlations between BRAF mutations and melanoma occurring on non-chronic sun-damaged skin and superficial spreading melanoma (P < 0.05) on one hand, and between NRAS mutations and nodular melanoma (P < 0.05) on the other hand. Younger age (P < 0.05), microscopic (P < 0.05) and macroscopic (P < 0.05) lymphatic involvement at diagnosis of primary melanoma were significantly linked to BRAF mutations. A mutated status was a positive predictive factor of a response to BRAF inhibitors (OR = 3.44). Mutated melanoma showed a significantly (P = 0.038) higher objective response rate to cytotoxic chemotherapy (26.3%) than wild-type tumours (6.7%). Clinical and pathological characteristics of the primary melanoma differed between wild-type and BRAF- or NRAS-mutated tumours. Patients with BRAF-mutated tumours were younger at diagnosis of primary melanoma. Patients carrying mutations showed better responses better to specific kinase inhibitors and interestingly also to systemic cytotoxic chemotherapy. © 2015 European Academy of Dermatology and Venereology.

Investigating Mars: Ascraeus Mons

NASA Image and Video Library

2017-09-08

This image shows part of the complex caldera at the summit of the volcano. Calderas are found at the tops of volcanoes and are the source region for magma that rises from an underground lava source to erupt at the surface. Volcanoes are formed by repeated flows from the central caldera. The final eruptions can pool within the summit caldera, leaving a flat surface as they cool. This image shows part of two of the summit calderas, each with a floor at different elevations. Calderas are also a location of collapse, creating rings of tectonic faults that form the caldera rim. Ascraeus Mons has several caldera features at its summit. The Odyssey spacecraft has spent over 15 years in orbit around Mars, circling the planet more than 69000 times. It holds the record for longest working spacecraft at Mars. THEMIS, the IR/VIS camera system, has collected data for the entire mission and provides images covering all seasons and lighting conditions. Over the years many features of interest have received repeated imaging, building up a suite of images covering the entire feature. From the deepest chasma to the tallest volcano, individual dunes inside craters and dune fields that encircle the north pole, channels carved by water and lava, and a variety of other feature, THEMIS has imaged them all. For the next several months the image of the day will focus on the Tharsis volcanoes, the various chasmata of Valles Marineris, and the major dunes fields. We hope you enjoy these images! Orbit Number: 63076 Latitude: 11.3749 Longitude: 255.364 Instrument: VIS Captured: 2016-03-03 11:14 https://photojournal.jpl.nasa.gov/catalog/PIA21830

3D Wavelet-Based Filter and Method

DOEpatents

Moss, William C.; Haase, Sebastian; Sedat, John W.

2008-08-12

A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

Improving Teaching through Continuous Learning: The Inquiry Process John Wooden Used to Become Coach of the Century

ERIC Educational Resources Information Center

Ermeling, Bradley Alan

2012-01-01

Past and contemporary scholars have emphasized the importance of job-embedded, systematic instructional inquiry for educators. A recent review of the literature highlights four key features shared by several well documented inquiry approaches for classroom teachers. Interestingly, another line of research suggests that these key features also…

Rett Syndrome: Of Girls and Mice--Lessons for Regression in Autism

ERIC Educational Resources Information Center

Glaze, Daniel G.

2004-01-01

Rett syndrome (RTT) is a neurodevelopmental disorder occurring almost exclusively in females. Regression is a defining feature of RTT. During the regression stage, RTT girls display many autistic features, such as loss of communication and social skills, poor eye contact, and lack of interest, and initially may be given the diagnosis of autism.…

Reflection spectra, 2.5-7 microns, of some solids of planetary interest

NASA Technical Reports Server (NTRS)

Fink, U.; Burk, S. D.

1973-01-01

Reflection spectra of 42 compounds of possible planetary interest were run from 2.5 to 7 microns. They were supplemented by some transmission spectra extending the wavelength coverage to 15 microns. The spectra were organized according to their constituent radicals and an attempt was made at the identification of the absorption features.

Faster than the Brighter-Light Beacon

ERIC Educational Resources Information Center

Baune, S.

2009-01-01

We analyse the motion of a spot of light projected onto a flat screen by a rotating source. We find that the motion of the spot has many interesting features such as spot splitting and superluminal effects. Our discussion is well suited for undergraduates and can be an interesting add-on in their curriculum, giving them new insights into the…

Unique features of a new nickel-hydrogen 2-cell CPV

NASA Technical Reports Server (NTRS)

Wheeler, James R.

1995-01-01

Two-cell nickel-hydrogen common pressure vessel (CPV) units with some unusual design features have been successfully built and tested. The features of interest are half-normal platinum loading for the negative electrodes, the use of rabbit-ear terminals for a CPV unit, and the incorporation of a wall wick. The units have a nominal capacity of 20 Ah and are 3.5 inches in diameter. Electric performance data are provided. The data support the growing viability of the two-cell CPV design concept.

Semi supervised Learning of Feature Hierarchies for Object Detection in a Video (Open Access)

DTIC Science & Technology

2013-10-03

dataset: PETS2009 Dataset, Oxford Town Center dataset [3], PNNL Parking Lot datasets [25] and CAVIAR cols1 dataset [1] for human detection. Be- sides, we...level features from TownCen- ter, ParkingLot, PETS09 and CAVIAR . As we can see that, the four set of features are visually very different from each other...information is more distinguished for detecting a person in the TownCen- ter than CAVIAR . Comparing figure 5(a) with 6(a), interest- ingly, the color

QED loop effects in the spacetime background of a Schwarzschild black hole

NASA Astrophysics Data System (ADS)

Emelyanov, Viacheslav A.

2017-12-01

The black-hole evaporation implies that the quantum-field propagators in a local Minkowski frame acquire a correction, which gives rise to this process. The modification of the propagators causes, in turn, non-trivial local effects due to the radiative/loop diagrams in non-linear QFTs. In particular, there should be imprints of the evaporation in QED, if one goes beyond the tree-level approximation. Of special interest in this respect is the region near the black-hole horizon, which, already at tree level, appears to show highly non-classical features, e.g., negative energy density and energy flux into the black hole.

Development of a cross-polarization scattering system for the measurement of internal magnetic fluctuations in the DIII-D tokamak

DOE PAGES

Rhodes, Terry L.; Peebles, William A.; Crocker, Neal A.; ...

2014-08-05

The design and performance of a new cross-polarization scattering (CPS) system for the localized measurement of internal magnetic fluctuations is presented. CPS is a process whereby magnetic fluctuations scatter incident electromagnetic radiation into a perpendicular polarization which is subsequently detected. A new CPS design that incorporates a unique scattering geometry was laboratory tested, optimized, and installed on the DIII-D tokamak. Plasma tests of signal-to-noise, polarization purity, and frequency response indicate proper functioning of the system. Lastly, CPS data show interesting features related to internal MHD perturbations known as sawteeth that are not observed on density fluctuations.

KSC-2012-5809

NASA Image and Video Library

2012-10-16

PORT CANAVERAL, Fla. – Bob Cabana, director of the Kennedy Space Center in Florida, spoke during opening ceremonies at the Historically Underutilized Business Zone, or HUBZone, Industry Day and Expo 2012. The event was hosted for business leaders who are interested in learning about government contracting opportunities and what local and national vendors have to offer. The expo was held in Cruise Terminal 4 at Port Canaveral, Fla. The annual trade show is sponsored by Kennedy's Prime Contractor Board, the U.S. Air Force 45th Space Wing and the Canaveral Port Authority. It featured about 175 large and small businesses and government exhibitors from Brevard County and across the nation. Photo credit: NASA/ Kim Shiflett

KSC-2012-5806

NASA Image and Video Library

2012-10-16

PORT CANAVERAL, Fla. – Bruce Deardoff, Canaveral Port Authority Commission chairman, spoke during opening ceremonies at the Historically Underutilized Business Zone, or HUBZone, Industry Day and Expo 2012. The event was hosted for business leaders who are interested in learning about government contracting opportunities and what local and national vendors have to offer. The expo was held in Cruise Terminal 4 at Port Canaveral, Fla. The annual trade show is sponsored by Kennedy's Prime Contractor Board, the U.S. Air Force 45th Space Wing and the Canaveral Port Authority. It featured about 175 large and small businesses and government exhibitors from Brevard County and across the nation. Photo credit: NASA/ Kim Shiflett

KSC-2012-5810

NASA Image and Video Library

2012-10-16

PORT CANAVERAL, Fla. – Bob Cabana, director of the Kennedy Space Center in Florida, spoke during opening ceremonies at the Historically Underutilized Business Zone, or HUBZone, Industry Day and Expo 2012. The event was hosted for business leaders who are interested in learning about government contracting opportunities and what local and national vendors have to offer. The expo was held in Cruise Terminal 4 at Port Canaveral, Fla. The annual trade show is sponsored by Kennedy's Prime Contractor Board, the U.S. Air Force 45th Space Wing and the Canaveral Port Authority. It featured about 175 large and small businesses and government exhibitors from Brevard County and across the nation. Photo credit: NASA/ Kim Shiflett

KSC-2012-5812

NASA Image and Video Library

2012-10-16

PORT CANAVERAL, Fla. – David Radzanowski, NASA chief of staff, spoke during opening ceremonies at the Historically Underutilized Business Zone, or HUBZone, Industry Day and Expo 2012. The event was hosted for business leaders who are interested in learning about government contracting opportunities and what local and national vendors have to offer. The expo was held in Cruise Terminal 4 at Port Canaveral, Fla. The annual trade show is sponsored by Kennedy's Prime Contractor Board, the U.S. Air Force 45th Space Wing and the Canaveral Port Authority. It featured about 175 large and small businesses and government exhibitors from Brevard County and across the nation. Photo credit: NASA/ Kim Shiflett

Optical researches for cyanobacteria bloom monitoring in Curonian Lagoon

NASA Astrophysics Data System (ADS)

Shirshin, Evgeny A.; Budylin, Gleb B.; Yakimov, Boris P.; Voloshina, Olga V.; Karabashev, Genrik S.; Evdoshenko, Marina A.; Fadeev, Victor V.

2016-04-01

Cyanobacteria bloom is a great ecological problem of Curonian Lagoon and Baltic Sea. The development of novel methods for the on-line control of cyanobacteria concentration and, moreover, for prediction of bloom spreading is of interest for monitoring the state of ecosystem. Here, we report the results of the joint application of hyperspectral measurements and remote sensing of Curonian Lagoon in July 2015 aimed at the assessment of cyanobacteria communities. We show that hyperspectral data allow on-line detection and qualitative estimation of cyanobacteria concentration, while the remote sensing data indicate the possibility of cyanobacteria bloom detection using the spectral features of upwelling irradiation.

Hybrid plasmonic systems: from optical transparencies to strong coupling and entanglement

NASA Astrophysics Data System (ADS)

Gray, Stephen K.

2018-02-01

Classical electrodynamics and quantum mechanical models of quantum dots and molecules interacting with plasmonic systems are discussed. Calculations show that just one quantum dot interacting with a plasmonic system can lead to interesting optical effects, including optical transparencies and more general Fano resonance features that can be tailored with ultrafast laser pulses. Such effects can occur in the limit of moderate coupling between quantum dot and plasmonic system. The approach to the strong coupling regime is also discussed. In cases with two or more quantum dots within a plasmonic system, the possibility of quantum entanglement mediated through the dissipative plasmonic structure arises.

Tuning topological phases in the XMnSb2 system via chemical substitution from first principles

NASA Astrophysics Data System (ADS)

Griffin, Sinead M.; Neaton, Jeffrey B.

New Dirac materials are sought for their interesting fundamental physics and for their potential technological applications. Protected symmetries offer a route to potential zero mass Dirac and Weyl fermions, and can lead unique transport properties and spectroscopic signatures. In this work, we use first-principles calculations to study the XMnSb2 family of materials and show how varying X changes the nature of bulk protected topological features in their electronic structure. We further discuss new design rules for predicting new topological materials suggested by our calculations. SG is supported by the Early Postdoc Mobility Fellowship of the SNF.

Detecting distant homologies on protozoans metabolic pathways using scientific workflows.

PubMed

da Cruz, Sérgio Manuel Serra; Batista, Vanessa; Silva, Edno; Tosta, Frederico; Vilela, Clarissa; Cuadrat, Rafael; Tschoeke, Diogo; Dávila, Alberto M R; Campos, Maria Luiza Machado; Mattoso, Marta

2010-01-01

Bioinformatics experiments are typically composed of programs in pipelines manipulating an enormous quantity of data. An interesting approach for managing those experiments is through workflow management systems (WfMS). In this work we discuss WfMS features to support genome homology workflows and present some relevant issues for typical genomic experiments. Our evaluation used Kepler WfMS to manage a real genomic pipeline, named OrthoSearch, originally defined as a Perl script. We show a case study detecting distant homologies on trypanomatids metabolic pathways. Our results reinforce the benefits of WfMS over script languages and point out challenges to WfMS in distributed environments.

Analysis of within Subjects Variability in Mouse Ultrasonic Vocalization: Pups Exhibit Inconsistent, State-Like Patterns of Call Production

PubMed Central

Rieger, Michael A.; Dougherty, Joseph D.

2016-01-01

Mice produce ultrasonic vocalizations (USV) in multiple communicative contexts, including adult social interaction (e.g., male to female courtship), as well as pup calls when separated from the dam. Assessment of pup USV has been widely applied in models of social and communicative disorders, dozens of which have shown alterations to this conserved behavior. However, features such as call production rate can vary substantially even within experimental groups and it is unclear to what extent aspects of USV represent stable trait-like influences or are vulnerable to an animal's state. To address this question, we have employed a mixed modeling approach to describe consistency in USV features across time, leveraging multiple large cohorts recorded from two strains, and across ages/times. We find that most features of pup USV show consistent patterns within a recording session, but inconsistent patterns across postnatal development. This supports the conclusion that pup USV is most strongly influenced by “state”-like variables. In contrast, adult USV call rate and call duration show higher consistency across sessions and may reflect a stable “trait.” However, spectral features of adult song such as the presence of pitch jumps do not show this level of consistency, suggesting that pitch modulation is more susceptible to factors affecting the animal's state at the time of recording. Overall, the utility of this work is three-fold. First, as variability necessarily affects the sensitivity of the assay to detect experimental perturbation, we hope the information provided here will be used to help researchers plan sufficiently powered experiments, as well as prioritize specific ages to study USV behavior and to decide which features to consider most strongly in analysis. Second, via the mouseTube platform, we have provided these hundreds of recordings and associated data to serve as a shared resource for other researchers interested in either benchmark data for these strains or in developing algorithms for studying features of mouse song. Finally, we hope that this work informs both interpretation of USV studies in models of developmental disorder, and helps to further research into understanding the neural processes that contribute to the production and predictability of USV behavior. PMID:27733819

Childhood and Current Autistic Features in Adolescents with Schizotypal Personality Disorder

PubMed Central

Esterberg, Michelle L.; Trotman, Hanan D.; Brasfield, Joy L.; Compton, Michael T.; Walker, Elaine F.

2008-01-01

The diagnostic boundaries between autistic- and schizophrenia-spectrum disorders have varied over the years, and some overlap in diagnostic criteria persists. The present study examined childhood and current signs of autistic disorder (AD) in adolescents with schizotypal personality disorder (SPD) or other personality disorders, as well as healthy controls. A structured interview was administered to rate participants’ current symptoms. Participants’ guardians were interviewed with the Autism Diagnostic Inventory-Revised (ADI-R), a clinical assessment of childhood and current autistic signs. Compared to both the other personality-disordered and healthy groups, adolescents with SPD were rated as having significantly more impairment on childhood and current social functioning, and having more unusual interests and behaviors. For the entire sample, impaired childhood social functioning and unusual interests and behaviors were associated with higher negative symptom scores. Current impairments in social functioning, unusual interests and behaviors, and communication were also linked with greater negative symptoms. However, neither childhood nor current autistic features significantly predicted later conversion to an Axis I psychotic disorder over the course of three years of follow-up. The findings indicate that past and current autistic signs are more common in adolescents with SPD, but neither current nor childhood autistic features are linked with conversion to psychosis. PMID:18554872

Aerodynamic Drag Scoping Work.

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

Voskuilen, Tyler; Erickson, Lindsay Crowl; Knaus, Robert C.

This memo summarizes the aerodynamic drag scoping work done for Goodyear in early FY18. The work is to evaluate the feasibility of using Sierra/Low-Mach (Fuego) for drag predictions of rolling tires, particularly focused on the effects of tire features such as lettering, sidewall geometry, rim geometry, and interaction with the vehicle body. The work is broken into two parts. Part 1 consisted of investigation of a canonical validation problem (turbulent flow over a cylinder) using existing tools with different meshes and turbulence models. Part 2 involved calculating drag differences over plate geometries with simple features (ridges and grooves) defined bymore » Goodyear of approximately the size of interest for a tire. The results of part 1 show the level of noise to be expected in a drag calculation and highlight the sensitivity of absolute predictions to model parameters such as mesh size and turbulence model. There is 20-30% noise in the experimental measurements on the canonical cylinder problem, and a similar level of variation between different meshes and turbulence models. Part 2 shows that there is a notable difference in the predicted drag on the sample plate geometries, however, the computational cost of extending the LES model to a full tire would be significant. This cost could be reduced by implementation of more sophisticated wall and turbulence models (e.g. detached eddy simulations - DES) and by focusing the mesh refinement on feature subsets with the goal of comparing configurations rather than absolute predictivity for the whole tire.« less

A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

PubMed

Frohlich, Holger; Claes, Kasper; De Wolf, Catherine; Van Damme, Xavier; Michel, Anne

2018-05-01

Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Noldus Catwalk system, in which footprints are automatically captured and stored. We present a - to our knowledge - first machine learning based approach for the Catwalk system, which comprises a step decomposition, definition and extraction of meaningful features, multivariate step sequence alignment, feature selection, and training of different classifiers (gradient boosting machine, random forest, and elastic net). Using animal-wise leave-one-out cross validation we demonstrate that with our method we can reliable separate movement patterns of a putative Parkinson's disease animal model and several control groups. Furthermore, we show that we can predict the time point after and the type of different brain lesions and can even forecast the brain region, where the intervention was applied. We provide an in-depth analysis of the features involved into our classifiers via statistical techniques for model interpretation. A machine learning method for automated analysis of data from the Noldus Catwalk system was established. Our works shows the ability of machine learning to discriminate pharmacologically relevant animal groups based on their walking behavior in a multivariate manner. Further interesting aspects of the approach include the ability to learn from past experiments, improve with more data arriving and to make predictions for single animals in future studies.

Palaeohydrology of a 3D-maze cave (Hermannshöhle, Lower Austria)

NASA Astrophysics Data System (ADS)

Schober, Andrea; Plan, Lukas

2013-04-01

The 4.4 km-long Hermannshöhle (located in Kirchberg/Wechsel, Lower Austria) is one of the largest caves in the Lower Austroalpine Unit. It is developed in an isolated block of carbonate marble, taking up only 140 x 160 m of ground area and 73 m of elevation difference. The cave is unusual in two respects: (a) its dense network of corridors is arranged in a three-dimensional maze and (b) the most outstanding macro- and micromorphologic features were caused by paragenesis. Speleothems are abundant throughout the cave comprising flowstones, dripstones, helictites, popcorn, calcite rafts, a shield, and moonmilk. Even though most passages are canyon-shaped, the cave shows exclusively phreatic features. Sediment fills are abundant as well, mostly covering the floor of passages to an unknown depth, containing mainly allochthonous material, i.e. schists and gneisses. Besides some vadose dripwater the cave is dry today. A conspicuous feature is the lack of a single water path and instead a maze with multiple flow paths formed. Another interesting feature is that one part of the cave developed below the nearby Ramsbach brook but is still dry. There are small ponors reported from the Ramsbach brook (which were observed during river regulation) indicating an actively draining karst system, which is not yet explored. The aim of this study was to enlighten the palaeohydrology of this cave using morphological and sedimentological observations as well as U/Th dating of speleothems. First results show that the palaeo-environment and the hydrologic setting of the Hermannshöhle were drastically different from today. Undersaturated water sourced from nearby non-karstic gneisses and schists gave rise to well-developed contact karst features. Surprisingly the palaeo flow direction deduced from indicators like scallops and sediment structures was opposite to the flow direction of the present nearby brooks (Rams- and Feistrizbach). Following pulses of clastic sediment input a distinct system of paragenetic canyons developed creating the unique maze character of the cave.

New Results on Hydration in M-Type Asteroids

NASA Astrophysics Data System (ADS)

Landsman, Zoe A.; Campins, Humberto; Pinilla-Alonso, Noemí; Emery, Joshua P.; Lorenzi, Vania

2014-11-01

The M-type asteroids are a taxonomic group considered to be a candidate source of iron meteorites due to spectral and albedo similarities; however, because the spectra of M-type asteroids lack strong diagnostic absorption features in the near-infrared (NIR), their composition is difficult to constrain. High-resolution NIR spectroscopy and radar studies have shown that a metallic interpretation is unlikely to be valid for the majority of M-types. Many show weak absorption features attributed to mafic silicates (Hardersen et al. 2005, 2011; Ockert-Bell et al. 2010; Fornasier et al. 2010). Radar results show evidence for elevated metal content on the surfaces of most M-type asteroids, but few are likely to be entirely metal (Shepard et al. 2010). Surprisingly, spectrophotometric studies in the 3-μm region have indicated that hydrated minerals are relatively common among the M-type population, confounding interpretations of M-types as highly thermally processed (Rivkin et al. 1995, 2000). The shape of the 3-μm band, diagnostic of hydrated and hydroxylated minerals, is relevant to an asteroid’s thermal history (Rivkin et al. 2002, Takir & Emery 2012). To characterize this region, we have conducted a 2 - 4 μm spectroscopic study of six M-type asteroids using SpeX at NASA’s Infrared Telescope Facility. In its LXD mode, SpeX allows us to investigate the 3-μm band at spectral resolutions unavailable during previously published studies. We report the presence of a 3-μm feature on all six asteroids, indicating hydrated minerals on the asteroids’ surfaces. We have also detected rotational variability of the 3-μm feature in asteroid (216) Kleopatra, which, interestingly, had been interpreted as “dry” in previous work (Rivkin et al. 2000). On all of our target asteroids, the 3-μm band depths are < 10%, and there is apparent variation in the shape of the feature among them. We discuss the impact of our results on interpretations of M-type asteroid composition.

Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro-connectome, particularly in the context of data fusion.

Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

DOE PAGES

Ferguson, Jared O.; Jablonowski, Christiane; Johansen, Hans; ...

2016-11-09

Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interactionmore » of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.« less

Geophysical Analysis of Young Monogenetic Volcanoes in the San Francisco Volcanic Field, Arizona

NASA Astrophysics Data System (ADS)

Rees, S.; Porter, R. C.; Riggs, N.

2017-12-01

The San Francisco Volcanic Field (SFVF), located in northern Arizona, USA, contains some of the youngest intracontinental volcanism within the United States and, given its recent eruptive history, presents an excellent opportunity to better understand how these systems behave. Geophysical techniques such as magnetics, paleomagnetics, and seismic refraction can be used to understand eruptive behavior and image shallow subsurface structures. As such, they present an opportunity to understand eruptive processes associated with the monogenetic volcanism that is common within the SFVF. These techniques are especially beneficial in areas where erosion has not exposed shallow eruptive features within the volcano. We focus on two volcanoes within the SFVF, Merriam Crater and Crater 120 for this work. These are thought to be some of the youngest volcanoes in the field and, as such, are well preserved. Aside from being young, they both exhibit interesting features such as multiple vents, apparent vent alignment, and lack of erosional features that are present at many of the other volcanoes in the SFVF, making them ideal for this work. Initial results show that shallow subsurface basaltic masses can be located using geophysical techniques. These masses are interpreted as dikes or lava flows that are covered by younger scoria. Propagating dikes drive eruptions at monogenetic volcanoes, which often appear in aligned clusters. Locating these features will further the understanding of how magma is transported and how eruptions may have progressed.

Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

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

Ferguson, Jared O.; Jablonowski, Christiane; Johansen, Hans

Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interactionmore » of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.« less

Learning deep similarity in fundus photography

NASA Astrophysics Data System (ADS)

Chudzik, Piotr; Al-Diri, Bashir; Caliva, Francesco; Ometto, Giovanni; Hunter, Andrew

2017-02-01

Similarity learning is one of the most fundamental tasks in image analysis. The ability to extract similar images in the medical domain as part of content-based image retrieval (CBIR) systems has been researched for many years. The vast majority of methods used in CBIR systems are based on hand-crafted feature descriptors. The approximation of a similarity mapping for medical images is difficult due to the big variety of pixel-level structures of interest. In fundus photography (FP) analysis, a subtle difference in e.g. lesions and vessels shape and size can result in a different diagnosis. In this work, we demonstrated how to learn a similarity function for image patches derived directly from FP image data without the need of manually designed feature descriptors. We used a convolutional neural network (CNN) with a novel architecture adapted for similarity learning to accomplish this task. Furthermore, we explored and studied multiple CNN architectures. We show that our method can approximate the similarity between FP patches more efficiently and accurately than the state-of- the-art feature descriptors, including SIFT and SURF using a publicly available dataset. Finally, we observe that our approach, which is purely data-driven, learns that features such as vessels calibre and orientation are important discriminative factors, which resembles the way how humans reason about similarity. To the best of authors knowledge, this is the first attempt to approximate a visual similarity mapping in FP.

Directed self-assembly of block copolymers for nanolithography: fabrication of isolated features and essential integrated circuit geometries.

PubMed

Stoykovich, Mark P; Kang, Huiman; Daoulas, Kostas Ch; Liu, Guoliang; Liu, Chi-Chun; de Pablo, Juan J; Müller, Marcus; Nealey, Paul F

2007-10-01

Self-assembling block copolymers are of interest for nanomanufacturing due to the ability to realize sub-100 nm dimensions, thermodynamic control over the size and uniformity and density of features, and inexpensive processing. The insertion point of these materials in the production of integrated circuits, however, is often conceptualized in the short term for niche applications using the dense periodic arrays of spots or lines that characterize bulk block copolymer morphologies, or in the long term for device layouts completely redesigned into periodic arrays. Here we show that the domain structure of block copolymers in thin films can be directed to assemble into nearly the complete set of essential dense and isolated patterns as currently defined by the semiconductor industry. These results suggest that block copolymer materials, with their intrinsically advantageous self-assembling properties, may be amenable for broad application in advanced lithography, including device layouts used in existing nanomanufacturing processes.

Ionospheric effects of the simultaneous occurrence of a solar proton event and relativistic electron precipitation as recorded by ground-based instruments at different latitudes

NASA Astrophysics Data System (ADS)

Shirochkov, A. V.; Makarova, L. N.; Sokolov, S. N.; Sheldon, W. R.

2004-08-01

The intense event of highly relativistic electron (HRE) precipitation of May 1992 has been analyzed using data from ground-based observations (riometers and VLF phase measurements). Special attention was given to some features of this event observed at high and very high geomagnetic latitudes, since this aspect of the event was not well documented in previous studies. A remarkable feature of the HRE event of May 1992 was the simultaneous occurrence of a strong solar proton event (SPE), although reliable evidence shows that the simultaneous appearance of SPE and HRE events is not unique. It was demonstrated that a meridian chain of riometers with high latitudinal resolution is an effective and low-cost (as compared with satellite observations) tool to separate the effects of solar proton and relativistic electrons in the lower ionosphere. A significant conclusion is that the polar cap area is free from relativistic electron precipitation. Other interesting aspects of this complex geophysical phenomenon are also discussed.

Admixture facilitates genetic adaptations to high altitude in Tibet

PubMed Central

Jeong, Choongwon; Alkorta-Aranburu, Gorka; Basnyat, Buddha; Neupane, Maniraj; Witonsky, David B.; Pritchard, Jonathan K.; Beall, Cynthia M.; Di Rienzo, Anna

2015-01-01

Admixture is recognized as a widespread feature of human populations, renewing interest in the possibility that genetic exchange can facilitate adaptations to new environments. Studies of Tibetans revealed candidates for high-altitude adaptations in the EGLN1 and EPAS1 genes, associated with lower hemoglobin concentration. However, the history of these variants or that of Tibetans remains poorly understood. Here, we analyze genotype data for the Nepalese Sherpa, and find that Tibetans are a mixture of ancestral populations related to the Sherpa and Han Chinese. EGLN1 and EPAS1 genes show a striking enrichment of high-altitude ancestry in the Tibetan genome, indicating that migrants from low altitude acquired adaptive alleles from the highlanders. Accordingly, the Sherpa and Tibetans share adaptive hemoglobin traits. This admixture-mediated adaptation shares important features with adaptive introgression. Therefore, we identify a novel mechanism, beyond selection on new mutations or on standing variation, through which populations can adapt to local environments. PMID:24513612

Recognizing characters of ancient manuscripts

NASA Astrophysics Data System (ADS)

Diem, Markus; Sablatnig, Robert

2010-02-01

Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.

Features of the energy structure of acoustic fields in the ocean with two-dimensional random inhomogeneities

NASA Astrophysics Data System (ADS)

Gulin, O. E.; Yaroshchuk, I. O.

2017-03-01

The paper is devoted to the analytic study and numerical simulation of mid-frequency acoustic signal propagation in a two-dimensional inhomogeneous random shallow-water medium. The study was carried out by the cross section method (local modes). We present original theoretical estimates for the behavior of the average acoustic field intensity and show that at different distances, the features of propagation loss behavior are determined by the intensity of fluctuations and their horizontal scale and depend on the initial regular parameters, such as the emission frequency and size of sound losses in the bottom. We establish analytically that for the considered waveguide and sound frequency parameters, mode coupling effect has a local character and weakly influences the statistics. We establish that the specific form of the spatial spectrum of sound velocity inhomogeneities for the statistical patterns of the field intensity is insignificant during observations in the range of shallow-water distances of practical interest.

Meaning of Missing Values in Eyewitness Recall and Accident Records

PubMed Central

Uttl, Bob; Kisinger, Kelly

2010-01-01

Background Eyewitness recalls and accident records frequently do not mention the conditions and behaviors of interest to researchers and lead to missing values and to uncertainty about the prevalence of these conditions and behaviors surrounding accidents. Missing values may occur because eyewitnesses report the presence but not the absence of obvious clues/accident features. We examined this possibility. Methodology/Principal Findings Participants watched car accident videos and were asked to recall as much information as they could remember about each accident. The results showed that eyewitnesses were far more likely to report the presence of present obvious clues than the absence of absent obvious clues even though they were aware of their absence. Conclusions One of the principal mechanisms causing missing values may be eyewitnesses' tendency to not report the absence of obvious features. We discuss the implications of our findings for both retrospective and prospective analyses of accident records, and illustrate the consequences of adopting inappropriate assumptions about the meaning of missing values using the Avaluator Avalanche Accident Prevention Card. PMID:20824054

Ultrasonographic Detection of Tooth Flaws

NASA Astrophysics Data System (ADS)

Bertoncini, C. A.; Hinders, M. K.; Ghorayeb, S. R.

2010-02-01

The goal of our work is to adapt pulse-echo ultrasound into a high resolution imaging modality for early detection of oral diseases and for monitoring treatment outcome. In this talk we discuss our preliminary results in the detection of: demineralization of the enamel and dentin, demineralization or caries under and around existing restorations, caries on occlusal and interproximal surfaces, cracks of enamel and dentin, calculus, and periapical lesions. In vitro immersion tank experiments are compared to results from a handpiece which uses a compliant delay line to couple the ultrasound to the tooth surface. Because the waveform echoes are complex, and in order to make clinical interpretation of ultrasonic waveform data in real time, it is necessary to automatically interpret the signals. We apply the dynamic wavelet fingerprint algorithms to identify and delineate echographic features that correspond to the flaws of interest in teeth. The resulting features show a clear distinction between flawed and unflawed waveforms collected with an ultrasonic handpiece on both phantom and human cadaver teeth.

Bi-model processing for early detection of breast tumor in CAD system

NASA Astrophysics Data System (ADS)

Mughal, Bushra; Sharif, Muhammad; Muhammad, Nazeer

2017-06-01

Early screening of skeptical masses in mammograms may reduce mortality rate among women. This rate can be further reduced upon developing the computer-aided diagnosis system with decrease in false assumptions in medical informatics. This method highlights the early tumor detection in digitized mammograms. For improving the performance of this system, a novel bi-model processing algorithm is introduced. It divides the region of interest into two parts, the first one is called pre-segmented region (breast parenchyma) and other is the post-segmented region (suspicious region). This system follows the scheme of the preprocessing technique of contrast enhancement that can be utilized to segment and extract the desired feature of the given mammogram. In the next phase, a hybrid feature block is presented to show the effective performance of computer-aided diagnosis. In order to assess the effectiveness of the proposed method, a database provided by the society of mammographic images is tested. Our experimental outcomes on this database exhibit the usefulness and robustness of the proposed method.

Molecular mechanisms involved in Bacillus subtilis biofilm formation

PubMed Central

Mielich-Süss, Benjamin; Lopez, Daniel

2014-01-01

Summary Biofilms are the predominant lifestyle of bacteria in natural environments, and they severely impact our societies in many different fashions. Therefore, biofilm formation is a topic of growing interest in microbiology, and different bacterial models are currently studied to better understand the molecular strategies that bacteria undergo to build biofilms. Among those, biofilms of the soil-dwelling bacterium Bacillus subtilis are commonly used for this purpose. Bacillus subtilis biofilms show remarkable architectural features that are a consequence of sophisticated programs of cellular specialization and cell-cell communication within the community. Many laboratories are trying to unravel the biological role of the morphological features of biofilms, as well as exploring the molecular basis underlying cellular differentiation. In this review, we present a general perspective of the current state of knowledge of biofilm formation in B. subtilis. In particular, a special emphasis is placed on summarizing the most recent discoveries in the field and integrating them into the general view of these truly sophisticated microbial communities. PMID:24909922

Spatial Coverage Planning and Optimization for Planetary Exploration

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.; Estlin, Tara; Chouinard, Caroline

2008-01-01

We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.