Disease named entity recognition from biomedical literature using a novel convolutional neural network.

PubMed

Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

Mining consumer reviews to generate ratings of different product attributes while producing feature-based review-summary

NASA Astrophysics Data System (ADS)

Kangale, Akshay; Krishna Kumar, S.; Arshad Naeem, Mohd; Williams, Mark; Tiwari, M. K.

2016-10-01

With the massive growth of the internet, product reviews increasingly serve as an important source of information for customers to make choices online. Customers depend on these reviews to understand users' experience, and manufacturers rely on this user-generated content to capture user sentiments about their product. Therefore, it is in the best interest of both customers and manufacturers to have a portal where they can read a complete comprehensive summary of these reviews in minimum time. With this in mind, we arrived at our first objective which is to generate a feature-based review-summary. Our second objective is to develop a predictive model to know the next week's product sales based on numerical review ratings and textual features embedded in the reviews. When it comes to product features, every user has different priorities for different features. To capture this aspect of decision-making, we have designed a new mechanism to generate a numerical rating for every feature of the product individually. The data have been collected from a well-known commercial website for two different products. The validation of the model is carried out using a crowd-sourcing technique.

Contingent attentional capture across multiple feature dimensions in a temporal search task.

PubMed

Ito, Motohiro; Kawahara, Jun I

2016-01-01

The present study examined whether attention can be flexibly controlled to monitor two different feature dimensions (shape and color) in a temporal search task. Specifically, we investigated the occurrence of contingent attentional capture (i.e., interference from task-relevant distractors) and resulting set reconfiguration (i.e., enhancement of single task-relevant set). If observers can restrict searches to a specific value for each relevant feature dimension independently, the capture and reconfiguration effect should only occur when the single relevant distractor in each dimension appears. Participants identified a target letter surrounded by a non-green square or a non-square green frame. The results revealed contingent attentional capture, as target identification accuracy was lower when the distractor contained a target-defining feature than when it contained a nontarget feature. Resulting set reconfiguration was also obtained in that accuracy was superior when the current target's feature (e.g., shape) corresponded to the defining feature of the present distractor (shape) than when the current target's feature did not match the distractor's feature (color). This enhancement was not due to perceptual priming. The present study demonstrated that the principles of contingent attentional capture and resulting set reconfiguration held even when multiple target feature dimensions were monitored. Copyright © 2015 Elsevier B.V. All rights reserved.

Contingent Attentional Capture

NASA Technical Reports Server (NTRS)

Remington, Roger; Folk, Charles L.

1994-01-01

Four experiments address the degree of top-down selectivity in attention capture by feature singletons through manipulations of the spatial relationship and featural similarity of target and distractor singletons in a modified spatial cuing paradigm. Contrary to previous studies, all four experiments show that when searching for a singleton target, an irrelevant featural singleton captures attention only when defined by the same feature value as the target. Experiments 2, 3, and 4 provide a potential explanation for this empirical discrepancy by showing that irrelevant singletons can produce distraction effects that are independent of shifts of spatial attention. The results further support the notion that attentional capture is contingent on top-down attention control settings but indicates that such settings can be instantiated at the level of feature values.

Modeling misidentification errors in capture-recapture studies using photographic identification of evolving marks

USGS Publications Warehouse

Yoshizaki, J.; Pollock, K.H.; Brownie, C.; Webster, R.A.

2009-01-01

Misidentification of animals is potentially important when naturally existing features (natural tags) are used to identify individual animals in a capture-recapture study. Photographic identification (photoID) typically uses photographic images of animals' naturally existing features as tags (photographic tags) and is subject to two main causes of identification errors: those related to quality of photographs (non-evolving natural tags) and those related to changes in natural marks (evolving natural tags). The conventional methods for analysis of capture-recapture data do not account for identification errors, and to do so requires a detailed understanding of the misidentification mechanism. Focusing on the situation where errors are due to evolving natural tags, we propose a misidentification mechanism and outline a framework for modeling the effect of misidentification in closed population studies. We introduce methods for estimating population size based on this model. Using a simulation study, we show that conventional estimators can seriously overestimate population size when errors due to misidentification are ignored, and that, in comparison, our new estimators have better properties except in cases with low capture probabilities (<0.2) or low misidentification rates (<2.5%). ?? 2009 by the Ecological Society of America.

Understanding Science: Studies of Communication and Information.

ERIC Educational Resources Information Center

Griffith, Belver C.

1989-01-01

Sets bibliometrics in the context of the sociology of science by tracing the influences of Robert Merton, Thomas Kuhn, and D. J. Price. Explores the discovery of strong empirical relationships among measured communication and information that capture important features of social process and cognitive change in science. (SR)

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application

PubMed Central

Schwei, Kelsey M; Kadolph, Christopher; Finamore, Joseph; Cancel, Efrain; McCarty, Catherine A; Okorie, Asha; Thomas, Kate L; Allen Pacheco, Jennifer; Pathak, Jyotishman; Ellis, Stephen B; Denny, Joshua C; Rasmussen, Luke V; Tromp, Gerard; Williams, Marc S; Vrabec, Tamara R; Brilliant, Murray H

2017-01-01

Background The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical. Objective The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system. Methods Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information. Results The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data. Conclusions This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities. PMID:28903894

Contingent capture of involuntary visual attention interferes with detection of auditory stimuli

PubMed Central

Kamke, Marc R.; Harris, Jill

2014-01-01

The involuntary capture of attention by salient visual stimuli can be influenced by the behavioral goals of an observer. For example, when searching for a target item, irrelevant items that possess the target-defining characteristic capture attention more strongly than items not possessing that feature. Such contingent capture involves a shift of spatial attention toward the item with the target-defining characteristic. It is not clear, however, if the associated decrements in performance for detecting the target item are entirely due to involuntary orienting of spatial attention. To investigate whether contingent capture also involves a non-spatial interference, adult observers were presented with streams of visual and auditory stimuli and were tasked with simultaneously monitoring for targets in each modality. Visual and auditory targets could be preceded by a lateralized visual distractor that either did, or did not, possess the target-defining feature (a specific color). In agreement with the contingent capture hypothesis, target-colored distractors interfered with visual detection performance (response time and accuracy) more than distractors that did not possess the target color. Importantly, the same pattern of results was obtained for the auditory task: visual target-colored distractors interfered with sound detection. The decrement in auditory performance following a target-colored distractor suggests that contingent capture involves a source of processing interference in addition to that caused by a spatial shift of attention. Specifically, we argue that distractors possessing the target-defining characteristic enter a capacity-limited, serial stage of neural processing, which delays detection of subsequently presented stimuli regardless of the sensory modality. PMID:24920945

Contingent capture of involuntary visual attention interferes with detection of auditory stimuli.

PubMed

Kamke, Marc R; Harris, Jill

2014-01-01

The involuntary capture of attention by salient visual stimuli can be influenced by the behavioral goals of an observer. For example, when searching for a target item, irrelevant items that possess the target-defining characteristic capture attention more strongly than items not possessing that feature. Such contingent capture involves a shift of spatial attention toward the item with the target-defining characteristic. It is not clear, however, if the associated decrements in performance for detecting the target item are entirely due to involuntary orienting of spatial attention. To investigate whether contingent capture also involves a non-spatial interference, adult observers were presented with streams of visual and auditory stimuli and were tasked with simultaneously monitoring for targets in each modality. Visual and auditory targets could be preceded by a lateralized visual distractor that either did, or did not, possess the target-defining feature (a specific color). In agreement with the contingent capture hypothesis, target-colored distractors interfered with visual detection performance (response time and accuracy) more than distractors that did not possess the target color. Importantly, the same pattern of results was obtained for the auditory task: visual target-colored distractors interfered with sound detection. The decrement in auditory performance following a target-colored distractor suggests that contingent capture involves a source of processing interference in addition to that caused by a spatial shift of attention. Specifically, we argue that distractors possessing the target-defining characteristic enter a capacity-limited, serial stage of neural processing, which delays detection of subsequently presented stimuli regardless of the sensory modality.

Early melanoma diagnosis with mobile imaging.

PubMed

Do, Thanh-Toan; Zhou, Yiren; Zheng, Haitian; Cheung, Ngai-Man; Koh, Dawn

2014-01-01

We research a mobile imaging system for early diagnosis of melanoma. Different from previous work, we focus on smartphone-captured images, and propose a detection system that runs entirely on the smartphone. Smartphone-captured images taken under loosely-controlled conditions introduce new challenges for melanoma detection, while processing performed on the smartphone is subject to computation and memory constraints. To address these challenges, we propose to localize the skin lesion by combining fast skin detection and fusion of two fast segmentation results. We propose new features to capture color variation and border irregularity which are useful for smartphone-captured images. We also propose a new feature selection criterion to select a small set of good features used in the final lightweight system. Our evaluation confirms the effectiveness of proposed algorithms and features. In addition, we present our system prototype which computes selected visual features from a user-captured skin lesion image, and analyzes them to estimate the likelihood of malignance, all on an off-the-shelf smartphone.

Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization

PubMed Central

Cruz-Roa, Angel; Díaz, Gloria; Romero, Eduardo; González, Fabio A.

2011-01-01

Histopathological images are an important resource for clinical diagnosis and biomedical research. From an image understanding point of view, the automatic annotation of these images is a challenging problem. This paper presents a new method for automatic histopathological image annotation based on three complementary strategies, first, a part-based image representation, called the bag of features, which takes advantage of the natural redundancy of histopathological images for capturing the fundamental patterns of biological structures, second, a latent topic model, based on non-negative matrix factorization, which captures the high-level visual patterns hidden in the image, and, third, a probabilistic annotation model that links visual appearance of morphological and architectural features associated to 10 histopathological image annotations. The method was evaluated using 1,604 annotated images of skin tissues, which included normal and pathological architectural and morphological features, obtaining a recall of 74% and a precision of 50%, which improved a baseline annotation method based on support vector machines in a 64% and 24%, respectively. PMID:22811960

Stream capture to form Red Pass, northern Soda Mountains, California

USGS Publications Warehouse

Miller, David; Mahan, Shannon

2014-01-01

Red Pass, a narrow cut through the Soda Mountains important for prehistoric and early historic travelers, is quite young geologically. Its history of downcutting to capture streams west of the Soda Mountains, thereby draining much of eastern Fort Irwin, is told by the contrast in alluvial fan sediments on either side of the pass. Old alluvial fan deposits (>500 ka) were shed westward off an intact ridge of the Soda Mountains but by middle Pleistocene time, intermediate-age alluvial fan deposits (~100 ka) were laid down by streams flowing east through the pass into Silurian Valley. The pass was probably formed by stream capture driven by high levels of groundwater on the west side. This is evidenced by widespread wetland deposits west of the Soda Mountains. Sapping and spring discharge into Silurian Valley over millennia formed a low divide in the mountains that eventually was overtopped and incised by a stream. Lessons include the importance of groundwater levels for stream capture and the relatively youthful appearance of this ~100-200 ka feature in the slowly changing Mojave Desert landscape.

Losing history: how extinctions prune features from the tree of life.

PubMed

Davies, T Jonathan

2015-02-19

Biodiversity provides many valuable services to humanity; however, rapid expansion of the human population has placed increasing pressure on natural systems, and it has been suggested that we may be entering a sixth mass extinction. There is an urgent need, therefore, to prioritize conservation efforts if we are to maintain the provisioning of such service in the future. Phylogenetic diversity (PD), the summed branch lengths that connect species on the tree-of-life, might provide a valuable metric for conservation prioritization because it has been argued to capture feature diversity. Frequently, PD is estimated in millions of years, and therefore implicitly assumes an evolutionary model in which features diverge gradually over time. Here, I explore the expected loss of feature diversity when this assumption is violated. If evolution tends to slow down over time, as might be the case following adaptive radiations, losses of feature diversity might be relatively small. However, if evolution occurs in rapid bursts, following a punctuated model, impacts of extinctions might be much greater. PD captures many important properties, but if we use it as a proxy for feature diversity, we first need to ensure that we have the correct evolutionary model. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Online coupled camera pose estimation and dense reconstruction from video

DOEpatents

Medioni, Gerard; Kang, Zhuoliang

2016-11-01

A product may receive each image in a stream of video image of a scene, and before processing the next image, generate information indicative of the position and orientation of an image capture device that captured the image at the time of capturing the image. The product may do so by identifying distinguishable image feature points in the image; determining a coordinate for each identified image feature point; and for each identified image feature point, attempting to identify one or more distinguishable model feature points in a three dimensional (3D) model of at least a portion of the scene that appears likely to correspond to the identified image feature point. Thereafter, the product may find each of the following that, in combination, produce a consistent projection transformation of the 3D model onto the image: a subset of the identified image feature points for which one or more corresponding model feature points were identified; and, for each image feature point that has multiple likely corresponding model feature points, one of the corresponding model feature points. The product may update a 3D model of at least a portion of the scene following the receipt of each video image and before processing the next video image base on the generated information indicative of the position and orientation of the image capture device at the time of capturing the received image. The product may display the updated 3D model after each update to the model.

An improved arteriovenous classification method for the early diagnostics of various diseases in retinal image.

PubMed

Xu, Xiayu; Ding, Wenxiang; Abràmoff, Michael D; Cao, Ruofan

2017-04-01

Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins. The proposed method was tested on the DRIVE dataset and achieved an overall accuracy of 0.923. This retinal artery and vein classification algorithm serves as a potentially important tool for the early diagnosis of various diseases, including diabetic retinopathy and cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Individual differences in working memory capacity predict learned control over attentional capture.

PubMed

Robison, Matthew K; Unsworth, Nash

2017-11-01

Although individual differences in working memory capacity (WMC) typically predict susceptibility to attentional capture in various paradigms (e.g., Stroop, antisaccade, flankers), it sometimes fails to correlate with the magnitude of attentional capture effects in visual search (e.g., Stokes, 2016), which is 1 of the most frequently studied tasks to study capture (Theeuwes, 2010). But some studies have shown that search modes can mitigate the effects of attentional capture (Leber & Egeth, 2006). Therefore, the present study examined whether or not the relationship between WMC and attentional capture changes as a function of the search modes available. In Experiment 1, WMC was unrelated to attentional capture, but only 1 search mode (singleton-detection) could be employed. In Experiment 2, greater WMC predicted smaller attentional capture effects, but only when multiple search modes (feature-search and singleton-detection) could be employed. Importantly this relationship was entirely independent of variation in attention control, which suggests that this effect is driven by WMC-related long-term memory differences (Cosman & Vecera, 2013a, 2013b). The present set of findings help to further our understanding of the nuanced ways in which memory and attention interact. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The role of top-down spatial attention in contingent attentional capture.

PubMed

Huang, Wanyi; Su, Yuling; Zhen, Yanfen; Qu, Zhe

2016-05-01

It is well known that attentional capture by an irrelevant salient item is contingent on top-down feature selection, but whether attentional capture may be modulated by top-down spatial attention remains unclear. Here, we combined behavioral and ERP measurements to investigate the contribution of top-down spatial attention to attentional capture under modified spatial cueing paradigms. Each target stimulus was preceded by a peripheral circular cue array containing a spatially uninformative color singleton cue. We varied target sets but kept the cue array unchanged among different experimental conditions. When participants' task was to search for a colored letter in the target array that shared the same peripheral locations with the cue array, attentional capture by the peripheral color cue was reflected by both a behavioral spatial cueing effect and a cue-elicited N2pc component. When target arrays were presented more centrally, both the behavioral and N2pc effects were attenuated but still significant. The attenuated cue-elicited N2pc was found even when participants focused their attention on the fixed central location to identify a colored letter among an RSVP letter stream. By contrast, when participants were asked to identify an outlined or larger target, neither the behavioral spatial cueing effect nor the cue-elicited N2pc was observed, regardless of whether the target and cue arrays shared same locations or not. These results add to the evidence that attentional capture by salient stimuli is contingent upon feature-based task sets, and further indicate that top-down spatial attention is important but may not be necessary for contingent attentional capture. © 2016 Society for Psychophysiological Research.

Unique sudden onsets capture attention even when observers are in feature-search mode.

PubMed

Spalek, Thomas M; Yanko, Matthew R; Poiese, Paola; Lagroix, Hayley E P

2012-01-01

Two sources of attentional capture have been proposed: stimulus-driven (exogenous) and goal-oriented (endogenous). A resolution between these modes of capture has not been straightforward. Even such a clearly exogenous event as the sudden onset of a stimulus can be said to capture attention endogenously if observers operate in singleton-detection mode rather than feature-search mode. In four experiments we show that a unique sudden onset captures attention even when observers are in feature-search mode. The displays were rapid serial visual presentation (RSVP) streams of differently coloured letters with the target letter defined by a specific colour. Distractors were four #s, one of the target colour, surrounding one of the non-target letters. Capture was substantially reduced when the onset of the distractor array was not unique because it was preceded by other sets of four grey # arrays in the RSVP stream. This provides unambiguous evidence that attention can be captured both exogenously and endogenously within a single task.

Distinct roles of the intraparietal sulcus and temporoparietal junction in attentional capture from distractor features: An individual differences approach.

PubMed

Painter, David R; Dux, Paul E; Mattingley, Jason B

2015-07-01

Setting attention for an elementary visual feature, such as color or motion, results in greater spatial attentional "capture" from items with target compared with distractor features. Thus, capture is contingent on feature-based control settings. Neuroimaging studies suggest that this contingent attentional capture involves interactions between dorsal and ventral frontoparietal networks. To examine the distinct causal influences of these networks on contingent capture, we applied continuous theta-burst stimulation (cTBS) to alter neural excitability within the dorsal intraparietal sulcus (IPS), the ventral temporoparietal junction (TPJ) and a control site, visual area MT. Participants undertook an attentional capture task before and after stimulation, in which they made speeded responses to color-defined targets that were preceded by spatial cues in the target or distractor color. Cues appeared either at the target location (valid) or at a non-target location (invalid). Reaction times were slower for targets preceded by invalid compared with valid cues, demonstrating spatial attentional capture. Cues with the target color captured attention to a greater extent than those with the distractor color, consistent with contingent capture. Effects of cTBS were not evident at the group level, but emerged instead from analyses of individual differences. Target capture magnitude was positively correlated pre- and post-stimulation for all three cortical sites, suggesting that cTBS did not influence target capture. Conversely, distractor capture was positively correlated pre- and post-stimulation of MT, but uncorrelated for IPS and TPJ, suggesting that stimulation of IPS and TPJ selectively disrupted distractor capture. Additionally, the effects of IPS stimulation were predicted by pre-stimulation attentional capture, whereas the effects of TPJ stimulation were predicted by pre-stimulation distractor suppression. The results are consistent with the existence of distinct neural circuits underlying target and distractor capture, as well as distinct roles for the IPS and TPJ. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exercise Sensing and Pose Recovery Inference Tool (ESPRIT) - A Compact Stereo-based Motion Capture Solution For Exercise Monitoring

NASA Technical Reports Server (NTRS)

Lee, Mun Wai

2015-01-01

Crew exercise is important during long-duration space flight not only for maintaining health and fitness but also for preventing adverse health problems, such as losses in muscle strength and bone density. Monitoring crew exercise via motion capture and kinematic analysis aids understanding of the effects of microgravity on exercise and helps ensure that exercise prescriptions are effective. Intelligent Automation, Inc., has developed ESPRIT to monitor exercise activities, detect body markers, extract image features, and recover three-dimensional (3D) kinematic body poses. The system relies on prior knowledge and modeling of the human body and on advanced statistical inference techniques to achieve robust and accurate motion capture. In Phase I, the company demonstrated motion capture of several exercises, including walking, curling, and dead lifting. Phase II efforts focused on enhancing algorithms and delivering an ESPRIT prototype for testing and demonstration.

Reliable Communication Models in Interdependent Critical Infrastructure Networks

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

Lee, Sangkeun; Chinthavali, Supriya; Shankar, Mallikarjun

Modern critical infrastructure networks are becoming increasingly interdependent where the failures in one network may cascade to other dependent networks, causing severe widespread national-scale failures. A number of previous efforts have been made to analyze the resiliency and robustness of interdependent networks based on different models. However, communication network, which plays an important role in today's infrastructures to detect and handle failures, has attracted little attention in the interdependency studies, and no previous models have captured enough practical features in the critical infrastructure networks. In this paper, we study the interdependencies between communication network and other kinds of critical infrastructuremore » networks with an aim to identify vulnerable components and design resilient communication networks. We propose several interdependency models that systematically capture various features and dynamics of failures spreading in critical infrastructure networks. We also discuss several research challenges in building reliable communication solutions to handle failures in these models.« less

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY.

PubMed

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2009-08-07

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY

PubMed Central

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2010-01-01

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application. PMID:21197416

Arabic OCR: toward a complete system

NASA Astrophysics Data System (ADS)

El-Bialy, Ahmed M.; Kandil, Ahmed H.; Hashish, Mohamed; Yamany, Sameh M.

1999-12-01

Latin and Chinese OCR systems have been studied extensively in the literature. Yet little work was performed for Arabic character recognition. This is due to the technical challenges found in the Arabic text. Due to its cursive nature, a powerful and stable text segmentation is needed. Also; features capturing the characteristics of the rich Arabic character representation are needed to build the Arabic OCR. In this paper a novel segmentation technique which is font and size independent is introduced. This technique can segment the cursive written text line even if the line suffers from small skewness. The technique is not sensitive to the location of the centerline of the text line and can segment different font sizes and type (for different character sets) occurring on the same line. Features extraction is considered one of the most important phases of the text reading system. Ideally, the features extracted from a character image should capture the essential characteristics of this character that are independent of the font type and size. In such ideal case, the classifier stores a single prototype per character. However, it is practically challenging to find such ideal set of features. In this paper, a set of features that reflect the topological aspects of Arabia characters is proposed. These proposed features integrated with a topological matching technique introduce an Arabic text reading system that is semi Omni.

Oculomotor capture by colour singletons depends on intertrial priming.

PubMed

Becker, Stefanie I

2010-10-12

In visual search, an irrelevant colour singleton captures attention when the colour of the distractor changes across trials (e.g., from red to green), but not when the colour remains constant (Becker, 2007). The present study shows that intertrial changes of the distractor colour also modulate oculomotor capture: an irrelevant colour singleton distractor was only selected more frequently than the inconspicuous nontargets (1) when its features had switched (compared to the previous trial), or (2) when the distractor had been presented at the same position as the target on the previous trial. These results throw doubt on the notion that colour distractors capture attention and the eyes because of their high feature contrast, which is available at an earlier point in time than information about specific feature values. Instead, attention and eye movements are apparently controlled by a system that operates on feature-specific information, and gauges the informativity of nominally irrelevant features. Copyright © 2010 Elsevier Ltd. All rights reserved.

Discontinuous Galerkin methods for modeling Hurricane storm surge

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

When Does Feature Search Fail to Protect Against Attentional Capture?

PubMed Central

Graves, Tashina; Egeth, Howard E.

2016-01-01

When participants search for a shape (e.g., a circle) among a set of homogenous shapes (e.g., triangles) they are subject to distraction by color singletons that are more salient than the target. However, when participants search for a shape among heterogeneous shapes, the presence of a non-target color singleton does not slow responses to the target. Attempts have been made to explain these results from both bottom-up and top-down perspectives. What both accounts have in common is that they do not predict the occurrence of attentional capture on typical feature search displays. Here, we present a case where manipulating selection history, rather than the displays themselves, leads to attentional capture on feature search trials. The ability to map specific colors to the target and distractor appears to be what enables resistance to capture during feature search. PMID:27504073

Terrain detection and classification using single polarization SAR

DOEpatents

Chow, James G.; Koch, Mark W.

2016-01-19

The various technologies presented herein relate to identifying manmade and/or natural features in a radar image. Two radar images (e.g., single polarization SAR images) can be captured for a common scene. The first image is captured at a first instance and the second image is captured at a second instance, whereby the duration between the captures are of sufficient time such that temporal decorrelation occurs for natural surfaces in the scene, and only manmade surfaces, e.g., a road, produce correlated pixels. A LCCD image comprising the correlated and decorrelated pixels can be generated from the two radar images. A median image can be generated from a plurality of radar images, whereby any features in the median image can be identified. A superpixel operation can be performed on the LCCD image and the median image, thereby enabling a feature(s) in the LCCD image to be classified.

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application.

PubMed

Peissig, Peggy; Schwei, Kelsey M; Kadolph, Christopher; Finamore, Joseph; Cancel, Efrain; McCarty, Catherine A; Okorie, Asha; Thomas, Kate L; Allen Pacheco, Jennifer; Pathak, Jyotishman; Ellis, Stephen B; Denny, Joshua C; Rasmussen, Luke V; Tromp, Gerard; Williams, Marc S; Vrabec, Tamara R; Brilliant, Murray H

2017-09-13

The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical. The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system. Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information. The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data. This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities. ©Peggy Peissig, Kelsey M Schwei, Christopher Kadolph, Joseph Finamore, Efrain Cancel, Catherine A McCarty, Asha Okorie, Kate L Thomas, Jennifer Allen Pacheco, Jyotishman Pathak, Stephen B Ellis, Joshua C Denny, Luke V Rasmussen, Gerard Tromp, Marc S Williams, Tamara R Vrabec, Murray H Brilliant. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.09.2017.

A Static Color Discontinuity Can Capture Spatial Attention when the Target Is an Abrupt-Onset Singleton

ERIC Educational Resources Information Center

Burnham, Bryan R.; Neely, James H.

2008-01-01

C. L. Folk, R. W. Remington, and J. C. Johnston's (1992) contingent involuntary orienting hypothesis states that a salient visual feature will involuntarily capture attention only when the observer's attentional set includes similar features. In four experiments, when the target's relevant feature was its being an abruptly onset singleton,…

Interactions between space-based and feature-based attention.

PubMed

Leonard, Carly J; Balestreri, Angela; Luck, Steven J

2015-02-01

Although early research suggested that attention to nonspatial features (i.e., red) was confined to stimuli appearing at an attended spatial location, more recent research has emphasized the global nature of feature-based attention. For example, a distractor sharing a target feature may capture attention even if it occurs at a task-irrelevant location. Such findings have been used to argue that feature-based attention operates independently of spatial attention. However, feature-based attention may nonetheless interact with spatial attention, yielding larger feature-based effects at attended locations than at unattended locations. The present study tested this possibility. In 2 experiments, participants viewed a rapid serial visual presentation (RSVP) stream and identified a target letter defined by its color. Target-colored distractors were presented at various task-irrelevant locations during the RSVP stream. We found that feature-driven attentional capture effects were largest when the target-colored distractor was closer to the attended location. These results demonstrate that spatial attention modulates the strength of feature-based attention capture, calling into question the prior evidence that feature-based attention operates in a global manner that is independent of spatial attention.

The Importance of Capturing Topographic Features for Modeling Groundwater Flow and Transport in Mountainous Watersheds

NASA Astrophysics Data System (ADS)

Wang, C.; Gomez-Velez, J. D.; Wilson, J. L.

2017-12-01

Groundwater plays a key role in runoff generation and stream water chemistry from reach to watershed scales. The spatial distribution of ridges and streams can influence the spatial patterns of groundwater recharge and drainage, specially in mountainous terrains where these features are more prominent. However, typical modeling efforts simplify or ignore some of these features due to computational limitations without a systematic investigation of the implications for flow and transport within the watershed. In this study, we investigate the effect of capturing key topographic features on modeled groundwater flow and transport characteristics in a mountainous watershed. We build model scenarios of different topographic complexity levels (TCLs) to capture different levels of representation of streams and ridges in the model. Modeled baseflow and groundwater mean residence time (MRT) are used to quantify the differences among TCLs. Our results show that capturing the streams and ridges has a significant influence on simulated groundwater flow and transport patterns. Topographic complexity controls the proportion of baseflow generated from local, intermediate, and regional flow paths, thus influencing the amount and MRT of basefow flowing into streams of different Horton-Strahler orders. We further simulate the concentration of solute exported into streams from subsurface chemical weathering. The concentration of chemical weathering products in streams is less sensitive to model TCL due to the thermodynamic constraint on the equilibrium concentration of the chemical weathering. We also tested the influence of geology on the effect of TCL. The effect of TCL is consistent under different geological conditions; however, it is enhanced in models with low hydraulic conductivity because more of the flow is forced into shallow and local flow paths. All of these changes can affect our ability to interpret environmental tracer data and predict bio- and geo-chemical evolution of stream water in mountainous watersheds.

Identifying a "default" visual search mode with operant conditioning.

PubMed

Kawahara, Jun-ichiro

2010-09-01

The presence of a singleton in a task-irrelevant domain can impair visual search. This impairment, known as the attentional capture depends on the set of participants. When narrowly searching for a specific feature (the feature search mode), only matching stimuli capture attention. When searching broadly (the singleton detection mode), any oddball captures attention. The present study examined which strategy represents the "default" mode using an operant conditioning approach in which participants were trained, in the absence of explicit instructions, to search for a target in an ambiguous context in which one of two modes was available. The results revealed that participants behaviorally adopted the singleton detection as the default mode but reported using the feature search mode. Conscious strategies did not eliminate capture. These results challenge the view that a conscious set always modulates capture, suggesting that the visual system tends to rely on stimulus salience to deploy attention.

Value-Driven Attentional Capture is Modulated by Spatial Context

PubMed Central

Anderson, Brian A.

2014-01-01

When stimuli are associated with reward outcome, their visual features acquire high attentional priority such that stimuli possessing those features involuntarily capture attention. Whether a particular feature is predictive of reward, however, will vary with a number of contextual factors. One such factor is spatial location: for example, red berries are likely to be found in low-lying bushes, whereas yellow bananas are likely to be found on treetops. In the present study, I explore whether the attentional priority afforded to reward-associated features is modulated by such location-based contingencies. The results demonstrate that when a stimulus feature is associated with a reward outcome in one spatial location but not another, attentional capture by that feature is selective to when it appears in the rewarded location. This finding provides insight into how reward learning effectively modulates attention in an environment with complex stimulus–reward contingencies, thereby supporting efficient foraging. PMID:26069450

Capturing attention is not that simple: different mechanisms for stimulus-driven and contingent capture.

PubMed

Liao, Hsin-I; Yeh, Su-Ling

2013-11-01

Attentional orienting can be involuntarily directed to task-irrelevant stimuli, but it remains unsolved whether such attentional capture is contingent on top-down settings or could be purely stimulus-driven. We propose that attentional capture depends on the stimulus property because transient and static features are processed differently; thus, they might be modulated differently by top-down controls. To test this hybrid account, we adopted a spatial cuing paradigm in which a noninformative onset or color cue preceded an onset or color target with various stimulus onset asynchronies (SOAs). Results showed that the onset cue captured attention regardless of target type at short-but not long-SOAs. In contrast, the color cue captured attention at short and long SOAs, but only with a color target. The overall pattern of results corroborates our hypothesis, suggesting that different mechanisms are at work for stimulus-driven capture (by onset) and contingent capture (by color). Stimulus-driven capture elicits reflexive involuntary orienting, and contingent capture elicits voluntary feature-based enhancement.

Sensor-oriented feature usability evaluation in fingerprint segmentation

NASA Astrophysics Data System (ADS)

Li, Ying; Yin, Yilong; Yang, Gongping

2013-06-01

Existing fingerprint segmentation methods usually process fingerprint images captured by different sensors with the same feature or feature set. We propose to improve the fingerprint segmentation result in view of an important fact that images from different sensors have different characteristics for segmentation. Feature usability evaluation, which means to evaluate the usability of features to find the personalized feature or feature set for different sensors to improve the performance of segmentation. The need for feature usability evaluation for fingerprint segmentation is raised and analyzed as a new issue. To address this issue, we present a decision-tree-based feature-usability evaluation method, which utilizes a C4.5 decision tree algorithm to evaluate and pick the best suitable feature or feature set for fingerprint segmentation from a typical candidate feature set. We apply the novel method on the FVC2002 database of fingerprint images, which are acquired by four different respective sensors and technologies. Experimental results show that the accuracy of segmentation is improved, and time consumption for feature extraction is dramatically reduced with selected feature(s).

Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

USGS Publications Warehouse

Yoshizaki, J.; Brownie, C.; Pollock, K.H.; Link, W.A.

2011-01-01

Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture-recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored. ?? 2009 Springer Science+Business Media, LLC.

Factors Affecting Acceptance & Use of ReWIND: Validating the Extended Unified Theory of Acceptance and Use of Technology

ERIC Educational Resources Information Center

Nair, Pradeep Kumar; Ali, Faizan; Leong, Lim Chee

2015-01-01

Purpose: This study aims to explain the factors affecting students' acceptance and usage of a lecture capture system (LCS)--ReWIND--in a Malaysian university based on the extended unified theory of acceptance and use of technology (UTAUT2) model. Technological advances have become an important feature of universities' plans to improve the…

Skill Acquisition: Compilation of Weak-Method Problem Solutions.

DTIC Science & Technology

1985-08-12

difference largely disappears by the fourth day when they are still working - with Perverse EMACS. Compared to Day 1 on EMACS. there is large postive ...This reinforces the idea that production representation captures significant features of our procedural knowledge and that differences between...memory load is certainly consistent with the working memory plus production system hypothesis. Immediate Feedback The importance of immediate

The Role of Relational Information in Contingent Capture

ERIC Educational Resources Information Center

Becker, Stefanie I.; Folk, Charles L.; Remington, Roger W.

2010-01-01

On the contingent capture account, top-down attentional control settings restrict involuntary attentional capture to items that match the features of the search target. Attention capture is involuntary, but contingent on goals and intentions. The observation that only target-similar items can capture attention has usually been taken to show that…

Using Anisotropic 3D Minkowski Functionals for Trabecular Bone Characterization and Biomechanical Strength Prediction in Proximal Femur Specimens

PubMed Central

Nagarajan, Mahesh B.; De, Titas; Lochmüller, Eva-Maria; Eckstein, Felix; Wismüller, Axel

2017-01-01

The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach to characterize local structure properties of trabecular bone micro-architecture in ex vivo proximal femur specimens, as visualized on multi-detector CT, for purposes of biomechanical bone strength prediction. To this end, volumetric AMFs were computed locally for each voxel of volumes of interest (VOI) extracted from the femoral head of 146 specimens. The local anisotropy captured by such AMFs was quantified using a fractional anisotropy measure; the magnitude and direction of anisotropy at every pixel was stored in histograms that served as a feature vectors that characterized the VOIs. A linear multi-regression analysis algorithm was used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction performance was obtained from the fractional anisotropy histogram of AMF Euler Characteristic (RMSE = 1.01 ± 0.13), which was significantly better than MDCT-derived mean BMD (RMSE = 1.12 ± 0.16, p<0.05). We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding regional trabecular bone quality and contribute to improved bone strength prediction, which is important for improving the clinical assessment of osteoporotic fracture risk. PMID:29170581

Effective Fingerprint Quality Estimation for Diverse Capture Sensors

PubMed Central

Xie, Shan Juan; Yoon, Sook; Shin, Jinwook; Park, Dong Sun

2010-01-01

Recognizing the quality of fingerprints in advance can be beneficial for improving the performance of fingerprint recognition systems. The representative features to assess the quality of fingerprint images from different types of capture sensors are known to vary. In this paper, an effective quality estimation system that can be adapted for different types of capture sensors is designed by modifying and combining a set of features including orientation certainty, local orientation quality and consistency. The proposed system extracts basic features, and generates next level features which are applicable for various types of capture sensors. The system then uses the Support Vector Machine (SVM) classifier to determine whether or not an image should be accepted as input to the recognition system. The experimental results show that the proposed method can perform better than previous methods in terms of accuracy. In the meanwhile, the proposed method has an ability to eliminate residue images from the optical and capacitive sensors, and the coarse images from thermal sensors. PMID:22163632

Size matters: large objects capture attention in visual search.

PubMed

Proulx, Michael J

2010-12-23

Can objects or events ever capture one's attention in a purely stimulus-driven manner? A recent review of the literature set out the criteria required to find stimulus-driven attentional capture independent of goal-directed influences, and concluded that no published study has satisfied that criteria. Here visual search experiments assessed whether an irrelevantly large object can capture attention. Capture of attention by this static visual feature was found. The results suggest that a large object can indeed capture attention in a stimulus-driven manner and independent of displaywide features of the task that might encourage a goal-directed bias for large items. It is concluded that these results are either consistent with the stimulus-driven criteria published previously or alternatively consistent with a flexible, goal-directed mechanism of saliency detection.

Separation of Benign and Malicious Network Events for Accurate Malware Family Classification

DTIC Science & Technology

2015-09-28

use Kullback - Leibler (KL) divergence [15] to measure the information ...related work in an important aspect concerning the order of events. We use n-grams to capture the order of events, which exposes richer information about...DISCUSSION Using n-grams on higher level network events helps under- stand the underlying operation of the malware, and provides a good feature set

Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

NASA Astrophysics Data System (ADS)

Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

2012-10-01

Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

The non-storm time corrugated upper thermosphere: What is beyond MSIS?

NASA Astrophysics Data System (ADS)

Liu, Huixin; Thayer, Jeff; Zhang, Yongliang; Lee, Woo Kyoung

2017-06-01

Observations in the recent decade have revealed many thermospheric density corrugations/perturbations under nonstorm conditions (Kp < 2). They are generally not captured by empirical models like Mass Spectrometer Incoherent Scatter (MSIS) but are operationally important for long-term orbital evolution of Low Earth Orbiting satellites and theoretically for coupling processes in the atmosphere-ionosphere system. We review these density corrugations by classifying them into three types which are driven respectively by the lower atmosphere, ionosphere, and solar wind/magnetosphere. Model capabilities in capturing these features are discussed. A summary table of these corrugations is included to provide a quick guide on their magnitudes, occurring latitude, local time, and season.

Discriminative segmentation of microscopic cellular images.

PubMed

Cheng, Li; Ye, Ning; Yu, Weimiao; Cheah, Andre

2011-01-01

Microscopic cellular images segmentation has become an important routine procedure in modern biological research, due to the rapid advancement of fluorescence probes and robotic microscopes in recent years. In this paper we advocate a discriminative learning approach for cellular image segmentation. In particular, three new features are proposed to capture the appearance, shape and context information, respectively. Experiments are conducted on three different cellular image datasets. Despite the significant disparity among these datasets, the proposed approach is demonstrated to perform reasonably well. As expected, for a particular dataset, some features turn out to be more suitable than others. Interestingly, we observe that a further gain can often be obtained on top of using the "good" features, by also retaining those features that perform poorly. This might be due to the complementary nature of these features, as well as the capacity of our approach to better integrate and exploit different sources of information.

'Insect aquaplaning' on a superhydrophilic hairy surface: how Heliamphora nutans Benth. pitcher plants capture prey.

PubMed

Bauer, Ulrike; Scharmann, Mathias; Skepper, Jeremy; Federle, Walter

2013-02-22

Trichomes are a common feature of plants and perform important and diverse functions. Here, we show that the inward-pointing hairs on the inner wall of insect-trapping Heliamphora nutans pitchers are highly wettable, causing water droplets to spread rapidly across the surface. Wetting strongly enhanced the slipperiness and increased the capture rate for ants from 29 to 88 per cent. Force measurements and tarsal ablation experiments revealed that wetting affected the insects' adhesive pads but not the claws, similar to the 'aquaplaning' mechanism of (unrelated) Asian Nepenthes pitcher plants. The inward-pointing trichomes provided much higher traction when insects were pulled outwards. The wetness-dependent capture mechanisms of H. nutans and Nepenthes pitchers present a striking case of functional convergence, whereas the use of wettable trichomes constitutes a previously unknown mechanism to make plant surfaces slippery.

‘Insect aquaplaning’ on a superhydrophilic hairy surface: how Heliamphora nutans Benth. pitcher plants capture prey

PubMed Central

Bauer, Ulrike; Scharmann, Mathias; Skepper, Jeremy; Federle, Walter

2013-01-01

Trichomes are a common feature of plants and perform important and diverse functions. Here, we show that the inward-pointing hairs on the inner wall of insect-trapping Heliamphora nutans pitchers are highly wettable, causing water droplets to spread rapidly across the surface. Wetting strongly enhanced the slipperiness and increased the capture rate for ants from 29 to 88 per cent. Force measurements and tarsal ablation experiments revealed that wetting affected the insects' adhesive pads but not the claws, similar to the ‘aquaplaning’ mechanism of (unrelated) Asian Nepenthes pitcher plants. The inward-pointing trichomes provided much higher traction when insects were pulled outwards. The wetness-dependent capture mechanisms of H. nutans and Nepenthes pitchers present a striking case of functional convergence, whereas the use of wettable trichomes constitutes a previously unknown mechanism to make plant surfaces slippery. PMID:23256197

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties.

PubMed

Jacobs, Richard H A H; Haak, Koen V; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed-and presumably for this reason-the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities-including the aesthetic appreciation-are sufficiently universal to be predicted-with reasonable accuracy-based on the computed feature content of the textures.

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties

PubMed Central

Jacobs, Richard H. A. H.; Haak, Koen V.; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W.

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed—and presumably for this reason—the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities—including the aesthetic appreciation—are sufficiently universal to be predicted—with reasonable accuracy—based on the computed feature content of the textures. PMID:27493628

Reward-associated features capture attention in the absence of awareness: Evidence from object-substitution masking.

PubMed

Harris, Joseph A; Donohue, Sarah E; Schoenfeld, Mircea A; Hopf, Jens-Max; Heinze, Hans-Jochen; Woldorff, Marty G

2016-08-15

Reward-associated visual features have been shown to capture visual attention, evidenced in faster and more accurate behavioral performance, as well as in neural responses reflecting lateralized shifts of visual attention to those features. Specifically, the contralateral N2pc event-related-potential (ERP) component that reflects attentional shifting exhibits increased amplitude in response to task-relevant targets containing a reward-associated feature. In the present study, we examined the automaticity of such reward-association effects using object-substitution masking (OSM) in conjunction with MEG measures of visual attentional shifts. In OSM, a visual-search array is presented, with the target item to be detected indicated by a surrounding mask (here, four surrounding squares). Delaying the offset of the target-surrounding four-dot mask relative to the offset of the rest of the target/distracter array disrupts the viewer's awareness of the target (masked condition), whereas simultaneous offsets do not (unmasked condition). Here we manipulated whether the color of the OSM target was or was not of a previously reward-associated color. By tracking reward-associated enhancements of behavior and the N2pc in response to masked targets containing a previously rewarded or unrewarded feature, the automaticity of attentional capture by reward could be probed. We found an enhanced N2pc response to targets containing a previously reward-associated color feature. Moreover, this enhancement of the N2pc by reward did not differ between masking conditions, nor did it differ as a function of the apparent visibility of the target within the masked condition. Overall, these results underscore the automaticity of attentional capture by reward-associated features, and demonstrate the ability of feature-based reward associations to shape attentional capture and allocation outside of perceptual awareness. Copyright © 2016 Elsevier Inc. All rights reserved.

Stochastic Nature in Cellular Processes

NASA Astrophysics Data System (ADS)

Liu, Bo; Liu, Sheng-Jun; Wang, Qi; Yan, Shi-Wei; Geng, Yi-Zhao; Sakata, Fumihiko; Gao, Xing-Fa

2011-11-01

The importance of stochasticity in cellular processes is increasingly recognized in both theoretical and experimental studies. General features of stochasticity in gene regulation and expression are briefly reviewed in this article, which include the main experimental phenomena, classification, quantization and regulation of noises. The correlation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methods that can capture effects of intrinsic and extrinsic noise are described.

Contingent capture can occur at specific feature values: behavioral and electrophysiological evidence.

PubMed

Jiao, Jun; Zhao, Guang; Wang, Qi; Zhang, Kan; Li, Hong; Sun, Hong-Jin; Liu, Qiang

2013-02-01

The notion that attentional top-down control can be tuned to a stimulus feature is widely accepted. Although previous studies suggested that the stimulus-driven attentional capture could be contingent on top-down attentional control settings, it was uncertain whether contingent capture can occur at a specific feature value. Three experiments were conducted to address this issue using both behavioral and ERPs measures. Participants were required to respond to one color singleton in the search display (target) but refrain from responding to the search display containing another color singleton (nontarget). When target and nontarget belonged to different color categories (Experiment 1), only the target-color cue and within category irrelevant-color cue elicited the significant cue validity effect (i.e. RTs were shorter when the target was presented at the same location as the preceding cue rather than at a different location); they also lead to a robust N2pc effect, indicative of attention-capture. In addition, these two cue types had similar attention-capturing capacity. However, when target and nontarget belonged to the same color category (Experiments 2 and 3), only the target-color cue elicited the significant cue validity effect and the robust N2pc effect. The same within category irrelevant-color cue no longer elicited the cue validity effect, and the N2pc effect was also attenuated. Present findings suggest that contingent capture can occur at a specific feature value. Copyright © 2012 Elsevier B.V. All rights reserved.

Autonomous spatially adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

NASA Astrophysics Data System (ADS)

Theunissen, Raf; Kadosh, Jesse S.; Allen, Christian B.

2015-06-01

Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in the number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfoil and the boundary layer characterisation of a flat plate.

Temporary satellite capture of comets by Jupiter

NASA Astrophysics Data System (ADS)

Emel'yanenko, N. Yu.

2012-05-01

This paper studies the dynamical evolution of 97 Jupiter-family comets over an 800-year time period. More than two hundred encounters with Jupiter are investigated, with the observed comets moving during a certain period of time in an elliptic jovicentric orbit. In most cases this is an ordinary temporary satellite capture of a comet in Everhart's sense, not associated with a transition of the small body into Jupiter's family of satellites. The phenomenon occurs outside the Hill sphere with comets with a high Tisserand constant relative to Jupiter; the comets' orbits have a small inclination to the ecliptic plane. An analysis of 236 encounters has allowed the determination within the planar pair two-body problem of a region of orbits in the plane ( a, e) whose semimajor axes and eccentricities contribute to the phenomenon under study. Comets with orbits belonging to this region experience a temporary satellite capture during some of their encounters; the jovicentric distance function has several minima; and the encounters are characterized by reversions of the line of apsides and some others features of their combination that are intrinsic to comets in this region. Therefore, this region is called a region of comets with specific features in their encounters with Jupiter. Twenty encounters (out of 236), whereby the comet enters an elliptic jovicentric orbit in the Hill sphere, are identified and investigated. The size and shape of the elliptic heliocentric orbits enabling this transition are determined. It is found that in 11 encounters the motion of small bodies in the Hill sphere has features the most important of which is multiple minima of the jovicentric distance function. The study of these 20 encounters has allowed the introduction of the concept of temporary gravitational capture of a small body into the Hill sphere. An analysis of variations in the Tisserand constant in these (20) encounters of the observable comets shows that their motion is unstable in Hill's sense.

A Comprehensive Observational Coding Scheme for Analyzing Instrumental, Affective, and Relational Communication in Health Care Contexts

PubMed Central

SIMINOFF, LAURA A.; STEP, MARY M.

2011-01-01

Many observational coding schemes have been offered to measure communication in health care settings. These schemes fall short of capturing multiple functions of communication among providers, patients, and other participants. After a brief review of observational communication coding, the authors present a comprehensive scheme for coding communication that is (a) grounded in communication theory, (b) accounts for instrumental and relational communication, and (c) captures important contextual features with tailored coding templates: the Siminoff Communication Content & Affect Program (SCCAP). To test SCCAP reliability and validity, the authors coded data from two communication studies. The SCCAP provided reliable measurement of communication variables including tailored content areas and observer ratings of speaker immediacy, affiliation, confirmation, and disconfirmation behaviors. PMID:21213170

Image segmentation using association rule features.

PubMed

Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

2002-01-01

A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

Fast and highly efficient SO2 capture by TMG immobilized on hierarchical micro-meso-macroporous AlPO-5/cordierite honeycomb ceramic materials.

PubMed

Xu, Jin; Zha, Xiaoling; Wu, Yumei; Ke, Qingping; Yu, Weifang

2016-05-11

SO2 capacity of the obtained TMG-AlPO-5/cordierite honeycomb ceramic (CHC) adsorbent was measured to be 1.13 mol per mol TMG. More importantly, compared with literature reported supported ionic liquids, it is featured by a significantly improved adsorption rate (t0.9 reduced from >30 min to ∼0.1 min) and negligible pressure drop.

Camera trap placement and the potential for bias due to trails and other features

PubMed Central

Forrester, Tavis D.

2017-01-01

Camera trapping has become an increasingly widespread tool for wildlife ecologists, with large numbers of studies relying on photo capture rates or presence/absence information. It is increasingly clear that camera placement can directly impact this kind of data, yet these biases are poorly understood. We used a paired camera design to investigate the effect of small-scale habitat features on species richness estimates, and capture rate and detection probability of several mammal species in the Shenandoah Valley of Virginia, USA. Cameras were deployed at either log features or on game trails with a paired camera at a nearby random location. Overall capture rates were significantly higher at trail and log cameras compared to their paired random cameras, and some species showed capture rates as much as 9.7 times greater at feature-based cameras. We recorded more species at both log (17) and trail features (15) than at their paired control cameras (13 and 12 species, respectively), yet richness estimates were indistinguishable after 659 and 385 camera nights of survey effort, respectively. We detected significant increases (ranging from 11–33%) in detection probability for five species resulting from the presence of game trails. For six species detection probability was also influenced by the presence of a log feature. This bias was most pronounced for the three rodents investigated, where in all cases detection probability was substantially higher (24.9–38.2%) at log cameras. Our results indicate that small-scale factors, including the presence of game trails and other features, can have significant impacts on species detection when camera traps are employed. Significant biases may result if the presence and quality of these features are not documented and either incorporated into analytical procedures, or controlled for in study design. PMID:29045478

Camera trap placement and the potential for bias due to trails and other features.

PubMed

Kolowski, Joseph M; Forrester, Tavis D

2017-01-01

Camera trapping has become an increasingly widespread tool for wildlife ecologists, with large numbers of studies relying on photo capture rates or presence/absence information. It is increasingly clear that camera placement can directly impact this kind of data, yet these biases are poorly understood. We used a paired camera design to investigate the effect of small-scale habitat features on species richness estimates, and capture rate and detection probability of several mammal species in the Shenandoah Valley of Virginia, USA. Cameras were deployed at either log features or on game trails with a paired camera at a nearby random location. Overall capture rates were significantly higher at trail and log cameras compared to their paired random cameras, and some species showed capture rates as much as 9.7 times greater at feature-based cameras. We recorded more species at both log (17) and trail features (15) than at their paired control cameras (13 and 12 species, respectively), yet richness estimates were indistinguishable after 659 and 385 camera nights of survey effort, respectively. We detected significant increases (ranging from 11-33%) in detection probability for five species resulting from the presence of game trails. For six species detection probability was also influenced by the presence of a log feature. This bias was most pronounced for the three rodents investigated, where in all cases detection probability was substantially higher (24.9-38.2%) at log cameras. Our results indicate that small-scale factors, including the presence of game trails and other features, can have significant impacts on species detection when camera traps are employed. Significant biases may result if the presence and quality of these features are not documented and either incorporated into analytical procedures, or controlled for in study design.

The Roles of Feature-Specific Task Set and Bottom-Up Salience in Attentional Capture: An ERP Study

ERIC Educational Resources Information Center

Eimer, Martin; Kiss, Monika; Press, Clare; Sauter, Disa

2009-01-01

We investigated the roles of top-down task set and bottom-up stimulus salience for feature-specific attentional capture. Spatially nonpredictive cues preceded search arrays that included a color-defined target. For target-color singleton cues, behavioral spatial cueing effects were accompanied by cue-induced N2pc components, indicative of…

Ongoing River Capture in the Amazon via Secondary Channel Flow

NASA Astrophysics Data System (ADS)

Goldberg, S. L.; Stokes, M.; Perron, J. T.

2017-12-01

The Rio Casiquiare in South America is a secondary channel that originates as a distributary of the Rio Orinoco and flows into the Rio Negro as a tributary to form a perennial connection between the Amazon and Orinoco basins, the largest and fourth-largest rivers on Earth by discharge. This unusual configuration is the result of an incomplete and ongoing river capture in which the Rio Negro is actively capturing the upper Rio Orinoco. This rarely observed intermediate stage of capture illuminates important mechanisms that drive river capture in lowland settings, both in the Amazon basin and elsewhere. In particular, we show that the capture of the Rio Orinoco by the Rio Casiquiare is driven by a combination of headward incision of a rapidly eroding tributary of the Rio Negro, sedimentation in the Rio Orinoco downstream of the bifurcation, and seasonal inundation of a low-relief divide. The initiation of the bifurcation by headward erosion caused an increase in discharge to the Rio Casiquiare while the corresponding loss of discharge to the downstream Rio Orinoco has led to observable sedimentation within the main channel. Unlike most ephemeral secondary channels, the Rio Casiquiare appears to be growing, suggesting that the present bifurcation is an unstable feature that will eventually lead to the complete capture of the upper Rio Orinoco by the Rio Casiquiare. This capture is the latest major event in the late Cenozoic drainage evolution of South America in response to Andean tectonism, and is an example of the lateral expansion of the Amazon basin through river capture following integration and entrenchment of the transcontinental Amazon River. The Rio Casiquiare provides a snapshot of an intermediate, transient state of bifurcation and inter-basin flow via a secondary channel during lowland river capture.

A novel design of dual-channel optical system of star-tracker based on non-blind area PAL system

NASA Astrophysics Data System (ADS)

Luo, Yujie; Bai, Jian

2016-07-01

Star-tracker plays an important role in satellite navigation. Considering the satellites on near-Earth orbit, the system usually has two optical systems: one for observing the profile of Earth and the other for capturing the positions of stars. In this paper, we demonstrate a novel kind of dual-channel optical observation system of star-tracker with non-blind area PAL imaging system based on dichroic filter, which can combine both different observation channels into an integrated structure and realize the feature of miniaturization. According to the practical usage of star-tracker and the features of dichroic filter, we set the ultraviolet band as the PAL channel to observe the Earth with the FOV ranging from 40°-60°, and set the visible band as the front imaging channel to capture the stars far away from this system with the FOV ranging from 0°-20°. Consequently, the rays of both channels are converged on the same image plane, improving the efficiency of pixels of detector and reducing the weight and size of whole star-tracker system.

Feature integration and spatial attention: common processes for endogenous and exogenous orienting.

PubMed

Henderickx, David; Maetens, Kathleen; Soetens, Eric

2010-05-01

Briand (J Exp Psychol Hum Percept Perform 24:1243-1256, 1998) and Briand and Klein (J Exp Psychol Hum Percept Perform 13:228-241, 1987) demonstrated that spatial cueing effects are larger for detecting conjunction of features than for detecting simple features when spatial attention is oriented exogenously, and not when attention is oriented endogenously. Their results were interpreted as if only exogenous attention affects the posterior spatial attention system that performs the feature binding function attributed to spatial attention by Treisman's feature integration theory (FIT; 1980). In a series of 6 experiments, we attempted to replicate Briand's findings. Manipulations of distractor string size and symmetry of stimulus presentation left and right from fixation were implemented in Posner's cueing paradigm. The data indicate that both exogenous and endogenous cueing address the same attentional mechanism needed for feature binding. The results also limit the generalisability of Briand's proposal concerning the role of exogenous attention in feature integration. Furthermore, the importance to control the effect of unintended attentional capture in a cueing task is demonstrated.

Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models.

PubMed

AlDahoul, Nouar; Md Sabri, Aznul Qalid; Mansoor, Ali Mohammed

2018-01-01

Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly susceptible to dynamical events such as illumination changes, camera jitter, and variations in object sizes. On the other hand, the proposed feature learning approaches are cheaper and easier because highly abstract and discriminative features can be produced automatically without the need of expert knowledge. In this paper, we utilize automatic feature learning methods which combine optical flow and three different deep models (i.e., supervised convolutional neural network (S-CNN), pretrained CNN feature extractor, and hierarchical extreme learning machine) for human detection in videos captured using a nonstatic camera on an aerial platform with varying altitudes. The models are trained and tested on the publicly available and highly challenging UCF-ARG aerial dataset. The comparison between these models in terms of training, testing accuracy, and learning speed is analyzed. The performance evaluation considers five human actions (digging, waving, throwing, walking, and running). Experimental results demonstrated that the proposed methods are successful for human detection task. Pretrained CNN produces an average accuracy of 98.09%. S-CNN produces an average accuracy of 95.6% with soft-max and 91.7% with Support Vector Machines (SVM). H-ELM has an average accuracy of 95.9%. Using a normal Central Processing Unit (CPU), H-ELM's training time takes 445 seconds. Learning in S-CNN takes 770 seconds with a high performance Graphical Processing Unit (GPU).

Design and implementation of a contactless multiple hand feature acquisition system

NASA Astrophysics Data System (ADS)

Zhao, Qiushi; Bu, Wei; Wu, Xiangqian; Zhang, David

2012-06-01

In this work, an integrated contactless multiple hand feature acquisition system is designed. The system can capture palmprint, palm vein, and palm dorsal vein images simultaneously. Moreover, the images are captured in a contactless manner, that is, users need not to touch any part of the device when capturing. Palmprint is imaged under visible illumination while palm vein and palm dorsal vein are imaged under near infrared (NIR) illumination. The capturing is controlled by computer and the whole process is less than 1 second, which is sufficient for online biometric systems. Based on this device, this paper also implements a contactless hand-based multimodal biometric system. Palmprint, palm vein, palm dorsal vein, finger vein, and hand geometry features are extracted from the captured images. After similarity measure, the matching scores are fused using weighted sum fusion rule. Experimental results show that although the verification accuracy of each uni-modality is not as high as that of state-of-the-art, the fusion result is superior to most of the existing hand-based biometric systems. This result indicates that the proposed device is competent in the application of contactless multimodal hand-based biometrics.

Value-modulated oculomotor capture by task-irrelevant stimuli is a consequence of early competition on the saccade map.

PubMed

Pearson, Daniel; Osborn, Raphaella; Whitford, Thomas J; Failing, Michel; Theeuwes, Jan; Le Pelley, Mike E

2016-10-01

Recent research has shown that reward learning can modulate oculomotor and attentional capture by physically salient and task-irrelevant distractor stimuli, even when directing gaze to those stimuli is directly counterproductive to receiving reward. This value-modulated oculomotor capture effect may reflect biased competition in the oculomotor system, such that the relationship between a stimulus feature and reward enhances that feature's representation on an internal priority map. However, it is also possible that this effect is a result of reward reducing the threshold for a saccade to be made to salient items. Here, we demonstrate value-modulated oculomotor capture when two reward-associated distractor stimuli are presented simultaneously in the same search display. The influence of reward on oculomotor capture is found to be most prominent at the shortest saccade latencies. We conclude that the value-modulated oculomotor capture effect is a consequence of biased competition on the saccade priority map and cannot be explained by a general reduction in saccadic threshold.

3D fingerprint imaging system based on full-field fringe projection profilometry

NASA Astrophysics Data System (ADS)

Huang, Shujun; Zhang, Zonghua; Zhao, Yan; Dai, Jie; Chen, Chao; Xu, Yongjia; Zhang, E.; Xie, Lili

2014-01-01

As an unique, unchangeable and easily acquired biometrics, fingerprint has been widely studied in academics and applied in many fields over the years. The traditional fingerprint recognition methods are based on the obtained 2D feature of fingerprint. However, fingerprint is a 3D biological characteristic. The mapping from 3D to 2D loses 1D information and causes nonlinear distortion of the captured fingerprint. Therefore, it is becoming more and more important to obtain 3D fingerprint information for recognition. In this paper, a novel 3D fingerprint imaging system is presented based on fringe projection technique to obtain 3D features and the corresponding color texture information. A series of color sinusoidal fringe patterns with optimum three-fringe numbers are projected onto a finger surface. From another viewpoint, the fringe patterns are deformed by the finger surface and captured by a CCD camera. 3D shape data of the finger can be obtained from the captured fringe pattern images. This paper studies the prototype of the 3D fingerprint imaging system, including principle of 3D fingerprint acquisition, hardware design of the 3D imaging system, 3D calibration of the system, and software development. Some experiments are carried out by acquiring several 3D fingerprint data. The experimental results demonstrate the feasibility of the proposed 3D fingerprint imaging system.

Capture by colour: evidence for dimension-specific singleton capture.

PubMed

Harris, Anthony M; Becker, Stefanie I; Remington, Roger W

2015-10-01

Previous work on attentional capture has shown the attentional system to be quite flexible in the stimulus properties it can be set to respond to. Several different attentional "modes" have been identified. Feature search mode allows attention to be set for specific features of a target (e.g., red). Singleton detection mode sets attention to respond to any discrepant item ("singleton") in the display. Relational search sets attention for the relative properties of the target in relation to the distractors (e.g., redder, larger). Recently, a new attentional mode was proposed that sets attention to respond to any singleton within a particular feature dimension (e.g., colour; Folk & Anderson, 2010). We tested this proposal against the predictions of previously established attentional modes. In a spatial cueing paradigm, participants searched for a colour target that was randomly either red or green. The nature of the attentional control setting was probed by presenting an irrelevant singleton cue prior to the target display and assessing whether it attracted attention. In all experiments, the cues were red, green, blue, or a white stimulus rapidly rotated (motion cue). The results of three experiments support the existence of a "colour singleton set," finding that all colour cues captured attention strongly, while motion cues captured attention only weakly or not at all. Notably, we also found that capture by motion cues in search for colour targets was moderated by their frequency; rare motion cues captured attention (weakly), while frequent motion cues did not.

Analysis of precision and accuracy in a simple model of machine learning

NASA Astrophysics Data System (ADS)

Lee, Julian

2017-12-01

Machine learning is a procedure where a model for the world is constructed from a training set of examples. It is important that the model should capture relevant features of the training set, and at the same time make correct prediction for examples not included in the training set. I consider the polynomial regression, the simplest method of learning, and analyze the accuracy and precision for different levels of the model complexity.

High-frequency health data and spline functions.

PubMed

Martín-Rodríguez, Gloria; Murillo-Fort, Carlos

2005-03-30

Seasonal variations are highly relevant for health service organization. In general, short run movements of medical magnitudes are important features for managers in this field to make adequate decisions. Thus, the analysis of the seasonal pattern in high-frequency health data is an appealing task. The aim of this paper is to propose procedures that allow the analysis of the seasonal component in this kind of data by means of spline functions embedded into a structural model. In the proposed method, useful adaptions of the traditional spline formulation are developed, and the resulting procedures are capable of capturing periodic variations, whether deterministic or stochastic, in a parsimonious way. Finally, these methodological tools are applied to a series of daily emergency service demand in order to capture simultaneous seasonal variations in which periods are different.

A dilation-driven vortex flow in sheared granular materials explains a rheometric anomaly.

PubMed

Krishnaraj, K P; Nott, Prabhu R

2016-02-11

Granular flows occur widely in nature and industry, yet a continuum description that captures their important features is yet not at hand. Recent experiments on granular materials sheared in a cylindrical Couette device revealed a puzzling anomaly, wherein all components of the stress rise nearly exponentially with depth. Here we show, using particle dynamics simulations and imaging experiments, that the stress anomaly arises from a remarkable vortex flow. For the entire range of fill heights explored, we observe a single toroidal vortex that spans the entire Couette cell and whose sense is opposite to the uppermost Taylor vortex in a fluid. We show that the vortex is driven by a combination of shear-induced dilation, a phenomenon that has no analogue in fluids, and gravity flow. Dilatancy is an important feature of granular mechanics, but not adequately incorporated in existing models.

Novel Silica Nanostructured Platforms with Engineered Surface Functionality and Spherical Morphology for Low-Cost High-Efficiency Carbon Capture

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

Lai, Cheng-Yu; Radu, Daniela R.; Pizzi, Nicholas

Carbon capture is an integral part of the CO 2 mitigation efforts, and encompasses, among other measures, the demonstration of effective and inexpensive CO 2 capture technologies. The project demonstrated a novel platform—the amine-functionalized stellate mesoporous silica nanosphere (MSN)—for effective CO 2 absorption. The reported CO 2 absorption data are superior to the performance of other reported silica matrices utilized for carbon capture, featuring an amount of over 4 milimoles CO 2/g sorbent at low temperatures (in the range of 30-45 ºC), selected for simulating the temperature of actual flue gas. The reported platform is highly resilient, showing recyclability andmore » 85 % mass conservation of sorbent upon nine tested cycles. Importantly, the stellate MSNs show high CO 2 selectivity at room temperature, indicating that the presence of nitrogen in flue gas will not impair the CO 2 absorption performance. The results could lead to a simple and inexpensive new technology for CO 2 mitigation which could be implemented as measure of CO 2 mitigation in current fossil-fuel burning plants in the form of solid sorbent.« less

Using the critical incident technique to define a minimal data set for requirements elicitation in public health.

PubMed

Olvingson, Christina; Hallberg, Niklas; Timpka, Toomas; Greenes, Robert A

2002-12-18

The introduction of computer-based information systems (ISs) in public health provides enhanced possibilities for service improvements and hence also for improvement of the population's health. Not least, new communication systems can help in the socialization and integration process needed between the different professions and geographical regions. Therefore, development of ISs that truly support public health practices require that technical, cognitive, and social issues be taken into consideration. A notable problem is to capture 'voices' of all potential users, i.e., the viewpoints of different public health practitioners. Failing to capture these voices will result in inefficient or even useless systems. The aim of this study is to develop a minimal data set for capturing users' voices on problems experienced by public health professionals in their daily work and opinions about how these problems can be solved. The issues of concern thus captured can be used both as the basis for formulating the requirements of ISs for public health professionals and to create an understanding of the use context. Further, the data can help in directing the design to the features most important for the users.

Predicting protein amidation sites by orchestrating amino acid sequence features

NASA Astrophysics Data System (ADS)

Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

2017-08-01

Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.

Recent Development of an Earth Science App - FieldMove Clino

NASA Astrophysics Data System (ADS)

Vaughan, Alan; Collins, Nathan; Krus, Mike; Rourke, Peter

2014-05-01

As geological modelling and analysis move into 3D digital space, it becomes increasingly important to be able to rapidly integrate new data with existing databases, without the potential degradation caused by repeated manual transcription of numeric, graphical and meta-data. Digital field mapping offers significant benefits when compared with traditional paper mapping techniques, in that it can directly and interactively feed and be guided by downstream geological modelling and analysis. One of the most important pieces of equipment used by the field geologists is the compass clinometer. Midland Valley's development team have recently release their highly anticipated FieldMove Clino App. FieldMove Clino is a digital compass-clinometer for data capture on a smartphone. The app allows the user to use their phone as a traditional hand-held bearing compass, as well as a digital compass-clinometer for rapidly measuring and capturing the georeferenced location and orientation of planar and linear features in the field. The user can also capture and store digital photographs and text notes. FieldMove Clino supports online Google Maps as well as offline maps, so that the user can import their own georeferenced basemaps. Data can be exported as comma-separated values (.csv) or Move™ (.mve) files and then imported directly into FieldMove™, Move™ or other applications. Midland Valley is currently pioneering tablet-based mapping and, along with its industrial and academic partners, will be using the application in field based projects throughout this year and will be integrating feedback in further developments of this technology.

Neuronal network model of interictal and recurrent ictal activity

NASA Astrophysics Data System (ADS)

Lopes, M. A.; Lee, K.-E.; Goltsev, A. V.

2017-12-01

We propose a neuronal network model which undergoes a saddle node on an invariant circle bifurcation as the mechanism of the transition from the interictal to the ictal (seizure) state. In the vicinity of this transition, the model captures important dynamical features of both interictal and ictal states. We study the nature of interictal spikes and early warnings of the transition predicted by this model. We further demonstrate that recurrent seizures emerge due to the interaction between two networks.

Two-dimensional wavelet transform feature extraction for porous silicon chemical sensors.

PubMed

Murguía, José S; Vergara, Alexander; Vargas-Olmos, Cecilia; Wong, Travis J; Fonollosa, Jordi; Huerta, Ramón

2013-06-27

Designing reliable, fast responding, highly sensitive, and low-power consuming chemo-sensory systems has long been a major goal in chemo-sensing. This goal, however, presents a difficult challenge because having a set of chemo-sensory detectors exhibiting all these aforementioned ideal conditions are still largely un-realizable to-date. This paper presents a unique perspective on capturing more in-depth insights into the physicochemical interactions of two distinct, selectively chemically modified porous silicon (pSi) film-based optical gas sensors by implementing an innovative, based on signal processing methodology, namely the two-dimensional discrete wavelet transform. Specifically, the method consists of using the two-dimensional discrete wavelet transform as a feature extraction method to capture the non-stationary behavior from the bi-dimensional pSi rugate sensor response. Utilizing a comprehensive set of measurements collected from each of the aforementioned optically based chemical sensors, we evaluate the significance of our approach on a complex, six-dimensional chemical analyte discrimination/quantification task problem. Due to the bi-dimensional aspects naturally governing the optical sensor response to chemical analytes, our findings provide evidence that the proposed feature extractor strategy may be a valuable tool to deepen our understanding of the performance of optically based chemical sensors as well as an important step toward attaining their implementation in more realistic chemo-sensing applications. Copyright © 2013 Elsevier B.V. All rights reserved.

Hubble Captures Detailed Image of Uranus Atmosphere

NASA Image and Video Library

1998-08-02

NASA Hubble Space Telescope peered deep into Uranus atmosphere to see clear and hazy layers created by a mixture of gases. Using infrared filters, Hubble captured detailed features of three layers of Uranus atmosphere.

Phlebotomine sandflies (Diptera, Phlebotomidae) of Lanzarote Island (Canary Islands, Spain): Ecological survey and evaluation of the risk of Leishmania transmission.

PubMed

Morillas-Márquez, Francisco; Díaz-Sáez, Victoriano; Morillas-Mancilla, María Jesús; Corpas-López, Victoriano; Merino-Espinosa, Gemma; Gijón-Robles, Patricia; Martín-Sánchez, Joaquina

2017-04-01

Phlebotomine sandflies are natural vectors of Leishmania spp. and their expansion throughout has been evidenced in the last few years due to the global warming and changes in human behavior, worsening leishmaniasis problem. However, phlebotomine sandflies have been captured in small numbers on the Canary Islands, particularly on the island of Lanzarote, where only one limited survey was carried out almost thirty years ago. The proximity of this island to Morocco, in addition to the high number of tourists, sometimes accompanied by their dogs, from leishmaniasis endemic regions, highlights the importance of studying the sandfly fauna on this island in order to determine the transmission risk of leishmaniasis Thirty-eight sampling sites spread across the island were studied, and ecological features were gathered to identify the ecological traits associated to the presence of sandflies. Only 85 sandfly specimens were captured (1.18/m 2 ) with the following species distribution: Sergentomyia minuta (0.15 specimens/m 2 ), which was reported for the first time on this island, and S. fallax (1.03/m 2 ). Sandfly captured were achieved in only 7 out of 38 stations. No specimen of the Phlebotomus genus was captured and given that none of the species captured has been demonstrated vectors of human pathogenic Leishmania and considering that they were captured in low frequency and density, it can be concluded that the current leishmaniasis transmission risk is null. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of Sorting System for Fishes by Feed-forward Neural Networks Using Rotation Invariant Features

NASA Astrophysics Data System (ADS)

Shiraishi, Yuhki; Takeda, Fumiaki

In this research, we have developed a sorting system for fishes, which is comprised of a conveyance part, a capturing image part, and a sorting part. In the conveyance part, we have developed an independent conveyance system in order to separate one fish from an intertwined group of fishes. After the image of the separated fish is captured in the capturing part, a rotation invariant feature is extracted using two-dimensional fast Fourier transform, which is the mean value of the power spectrum with the same distance from the origin in the spectrum field. After that, the fishes are classified by three-layered feed-forward neural networks. The experimental results show that the developed system classifies three kinds of fishes captured in various angles with the classification ratio of 98.95% for 1044 captured images of five fishes. The other experimental results show the classification ratio of 90.7% for 300 fishes by 10-fold cross validation method.

Clinical evaluation of pacemaker automatic capture management and atrioventricular interval extension algorithm.

PubMed

Chen, Ke-ping; Xu, Geng; Wu, Shulin; Tang, Baopeng; Wang, Li; Zhang, Shu

2013-03-01

The present study was to assess the accuracy of automatic atrial and ventricular capture management (ACM and VCM) in determining pacing threshold and the performance of a second-generation automatic atrioventricular (AV) interval extension algorithm for reducing unnecessary ventricular pacing. A total of 398 patients at 32 centres who received an EnPulse dual-chamber pacing/dual-chamber adaptive rate pacing pacemaker (Medtronic, Minneapolis, MN, USA) were enrolled. The last amplitude thresholds as measured by ACM and VCM prior to the 6-month follow-up were compared with manually measured thresholds. Device diagnostics were used to evaluate ACM and VCM and the percentage of ventricular pacing with and without the AV extension algorithm. Modelling was performed to assess longevity gains relating to the use of automaticity features. Atrial and ventricular capture management performed accurately and reliably provided complete capture management in 97% of studied patients. The AV interval extension algorithm reduced the median per cent of right ventricular pacing in patients with sinus node dysfunction from 99.7 to 1.5% at 6-month follow-up and in patients with intermittent AV block (excluding persistent 3° AV block) from 99.9 to 50.2%. On the basis of validated modelling, estimated device longevity could potentially be extended by 1.9 years through the use of the capture management and AV interval extension features. Both ACM and VCM features reliably measured thresholds in nearly all patients; the AV extension algorithm significantly reduced ventricular pacing; and the use of pacemaker automaticity features potentially extends device longevity.

Acceptance and Use of Lecture Capture System (LCS) in Executive Business Studies: Extending UTAUT2

ERIC Educational Resources Information Center

Farooq, Muhammad Shoaib; Salam, Maimoona; Jaafar, Norizan; Fayolle, Alain; Ayupp, Kartinah; Radovic-Markovic, Mirjana; Sajid, Ali

2017-01-01

Purpose: Adoption of latest technological advancements (e.g. lecture capture system) is a hallmark of market-driven private universities. Among many other distinguishing features, lecture capture system (LCS) is the one which is being offered to enhance the flexibility of learning environment for attracting executive business students. Majority of…

Face verification system for Android mobile devices using histogram based features

NASA Astrophysics Data System (ADS)

Sato, Sho; Kobayashi, Kazuhiro; Chen, Qiu

2016-07-01

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

Quantifying the Onset and Progression of Plant Senescence by Color Image Analysis for High Throughput Applications

PubMed Central

Cai, Jinhai; Okamoto, Mamoru; Atieno, Judith; Sutton, Tim; Li, Yongle; Miklavcic, Stanley J.

2016-01-01

Leaf senescence, an indicator of plant age and ill health, is an important phenotypic trait for the assessment of a plant’s response to stress. Manual inspection of senescence, however, is time consuming, inaccurate and subjective. In this paper we propose an objective evaluation of plant senescence by color image analysis for use in a high throughput plant phenotyping pipeline. As high throughput phenotyping platforms are designed to capture whole-of-plant features, camera lenses and camera settings are inappropriate for the capture of fine detail. Specifically, plant colors in images may not represent true plant colors, leading to errors in senescence estimation. Our algorithm features a color distortion correction and image restoration step prior to a senescence analysis. We apply our algorithm to two time series of images of wheat and chickpea plants to quantify the onset and progression of senescence. We compare our results with senescence scores resulting from manual inspection. We demonstrate that our procedure is able to process images in an automated way for an accurate estimation of plant senescence even from color distorted and blurred images obtained under high throughput conditions. PMID:27348807

Characteristics of covert and overt visual orienting: Evidence from attentional and oculomotor capture

NASA Technical Reports Server (NTRS)

Wu, Shu-Chieh; Remington, Roger W.

2003-01-01

Five visual search experiments found oculomotor and attentional capture consistent with predictions of contingent orienting, contrary to claims that oculomotor capture is purely stimulus driven. Separate saccade and attend-only conditions contained a color target appearing either singly, with an onset or color distractor, or both. In singleton mode, onsets produced oculomotor and attentional capture. In feature mode, capture was absent or greatly reduced, providing evidence for top-down modulation of both types of capture. Although attentional capture by color abstractors was present throughout, oculomotor capture by color occurred only when accompanied by transient change, providing evidence for a dissociation between oculomotor and attentional capture. Oculomotor and attentional capture appear to be mediated by top-down attentional control settings, but transient change may be necessary for oculomotor capture. ((c) 2003 APA, all rights reserved).

Energy Capture and Use in Plants and Bacteria. Final Technical Report

DOE R&D Accomplishments Database

Boyer, P. D.

1993-12-31

The project has centered on elucidation of the mechanism of ATP synthase. The metabolic importance of ATP and the complexity of the ATP synthase have made the problem particularly important and challenging. The development of the binding change mechanism depended upon our recognition of features that were novel in bioenergetics and indeed to the field of enzymology. One important feature of mechanism is that the principal way that energy input from transmembrane proton movement is coupled to ATP formation is to drive conformational changes that cause the release of ATP readily formed and tightly bound at a catalytic site. Another is that three equivalent catalytic sites on the enzyme show strong catalytic cooperativity as they proceed sequentially through different conformations. A more speculative features is that this cooperativity and energy coupling involve a rotational movement of minor subunits relative to the catalytic subunits. During this period these studies have extended and clarified aspects of the synthase mechanism. During assessments of interactions of Mg{sup 2+} and ADP with the synthase we recognized unexpectedly that whether ADP and P{sub i}, or their complexes with Mg{sup 2+} served as substrates for ATP formation by photophosphorylation was not known. Our studies showed that MgADP and free P{sub i} act as substrates.

Adapting Local Features for Face Detection in Thermal Image.

PubMed

Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro

2017-11-27

A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

Perceptual Learning Induces Persistent Attentional Capture by Nonsalient Shapes.

PubMed

Qu, Zhe; Hillyard, Steven A; Ding, Yulong

2017-02-01

Visual attention can be attracted automatically by salient simple features, but whether and how nonsalient complex stimuli such as shapes may capture attention in humans remains unclear. Here, we present strong electrophysiological evidence that a nonsalient shape presented among similar shapes can provoke a robust and persistent capture of attention as a consequence of extensive training in visual search (VS) for that shape. Strikingly, this attentional capture that followed perceptual learning (PL) was evident even when the trained shape was task-irrelevant, was presented outside the focus of top-down spatial attention, and was undetected by the observer. Moreover, this attentional capture persisted for at least 3-5 months after training had been terminated. This involuntary capture of attention was indexed by electrophysiological recordings of the N2pc component of the event-related brain potential, which was localized to ventral extrastriate visual cortex, and was highly predictive of stimulus-specific improvement in VS ability following PL. These findings provide the first evidence that nonsalient shapes can capture visual attention automatically following PL and challenge the prominent view that detection of feature conjunctions requires top-down focal attention. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Featured Image: Fireball After a Temporary Capture?

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-06-01

This image of a fireball was captured in the Czech Republic by cameras at a digital autonomous observatory in the village of Kunak. This observatory is part of a network of stations known as the European Fireball Network, and this particular meteoroid detection, labeled EN130114, is notable because it has the lowest initial velocity of any natural object ever observed by the network. Led by David Clark (University of Western Ontario), the authors of a recent study speculate that before this meteoroid impacted Earth, it may have been a Temporarily Captured Orbiter (TCO). TCOs are near-Earth objects that make a few orbits of Earth before returning to heliocentric orbits. Only one has ever been observed to date, and though they are thought to make up 0.1% of all meteoroids, EN130114 is the first event ever detected that exhibits conclusive behavior of a TCO. For more information on EN130114 and why TCOs are important to study, check out the paper below!CitationDavid L. Clark et al 2016 AJ 151 135. doi:10.3847/0004-6256/151/6/135

Distractor-Induced Blindness: A Special Case of Contingent Attentional Capture?

PubMed Central

Winther, Gesche N.; Niedeggen, Michael

2017-01-01

The detection of a salient visual target embedded in a rapid serial visual presentation (RSVP) can be severely affected if target-like distractors are presented previously. This phenomenon, known as distractor-induced blindness (DIB), shares the prerequisites of contingent attentional capture (Folk, Remington, & Johnston, 1992). In both, target processing is transiently impaired by the presentation of distractors defined by similar features. In the present study, we investigated whether the speeded response to a target in the DIB paradigm can be described in terms of a contingent attentional capture process. In the first experiments, multiple distractors were embedded in the RSVP stream. Distractors either shared the target’s visual features (Experiment 1A) or differed from them (Experiment 1B). Congruent with hypotheses drawn from contingent attentional capture theory, response times (RTs) were exclusively impaired in conditions with target-like distractors. However, RTs were not impaired if only one single target-like distractor was presented (Experiment 2). If attentional capture directly contributed to DIB, the single distractor should be sufficient to impair target processing. In conclusion, DIB is not due to contingent attentional capture, but may rely on a central suppression process triggered by multiple distractors. PMID:28439320

A novel metadata management model to capture consent for record linkage in longitudinal research studies.

PubMed

McMahon, Christiana; Denaxas, Spiros

2017-11-06

Informed consent is an important feature of longitudinal research studies as it enables the linking of the baseline participant information with administrative data. The lack of standardized models to capture consent elements can lead to substantial challenges. A structured approach to capturing consent-related metadata can address these. a) Explore the state-of-the-art for recording consent; b) Identify key elements of consent required for record linkage; and c) Create and evaluate a novel metadata management model to capture consent-related metadata. The main methodological components of our work were: a) a systematic literature review and qualitative analysis of consent forms; b) the development and evaluation of a novel metadata model. We qualitatively analyzed 61 manuscripts and 30 consent forms. We extracted data elements related to obtaining consent for linkage. We created a novel metadata management model for consent and evaluated it by comparison with the existing standards and by iteratively applying it to case studies. The developed model can facilitate the standardized recording of consent for linkage in longitudinal research studies and enable the linkage of external participant data. Furthermore, it can provide a structured way of recording consent-related metadata and facilitate the harmonization and streamlining of processes.

A rapid approach for automated comparison of independently derived stream networks

USGS Publications Warehouse

Stanislawski, Larry V.; Buttenfield, Barbara P.; Doumbouya, Ariel T.

2015-01-01

This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster and more reliable than earlier methods. Methods are tested on 30 subbasins distributed across different terrain and climate conditions of the conterminous United States. CLC values for the 30 subbasins indicate 44–83% of the features match between the two datasets, with the majority of the mismatching features comprised of first-order features. Relatively lower CLC values result from subbasins with less than about 1.5 degrees of slope. The primary difference between the two datasets may be explained by different data capture criteria. First-order, headwater tributaries derived from the flow-accumulation model are captured more comprehensively through drainage area and terrain conditions, whereas capture of headwater features in the NHD is cartographically constrained by tributary length. The addition of missing headwaters to the NHD, as guided by the elevation-derived channels, can substantially improve the scientific value of the NHD.

A new approach to modeling the influence of image features on fixation selection in scenes

PubMed Central

Nuthmann, Antje; Einhäuser, Wolfgang

2015-01-01

Which image characteristics predict where people fixate when memorizing natural images? To answer this question, we introduce a new analysis approach that combines a novel scene-patch analysis with generalized linear mixed models (GLMMs). Our method allows for (1) directly describing the relationship between continuous feature value and fixation probability, and (2) assessing each feature's unique contribution to fixation selection. To demonstrate this method, we estimated the relative contribution of various image features to fixation selection: luminance and luminance contrast (low-level features); edge density (a mid-level feature); visual clutter and image segmentation to approximate local object density in the scene (higher-level features). An additional predictor captured the central bias of fixation. The GLMM results revealed that edge density, clutter, and the number of homogenous segments in a patch can independently predict whether image patches are fixated or not. Importantly, neither luminance nor contrast had an independent effect above and beyond what could be accounted for by the other predictors. Since the parcellation of the scene and the selection of features can be tailored to the specific research question, our approach allows for assessing the interplay of various factors relevant for fixation selection in scenes in a powerful and flexible manner. PMID:25752239

Cortical processing of dynamic sound envelope transitions.

PubMed

Zhou, Yi; Wang, Xiaoqin

2010-12-08

Slow envelope fluctuations in the range of 2-20 Hz provide important segmental cues for processing communication sounds. For a successful segmentation, a neural processor must capture envelope features associated with the rise and fall of signal energy, a process that is often challenged by the interference of background noise. This study investigated the neural representations of slowly varying envelopes in quiet and in background noise in the primary auditory cortex (A1) of awake marmoset monkeys. We characterized envelope features based on the local average and rate of change of sound level in envelope waveforms and identified envelope features to which neurons were selective by reverse correlation. Our results showed that envelope feature selectivity of A1 neurons was correlated with the degree of nonmonotonicity in their static rate-level functions. Nonmonotonic neurons exhibited greater feature selectivity than monotonic neurons in quiet and in background noise. The diverse envelope feature selectivity decreased spike-timing correlation among A1 neurons in response to the same envelope waveforms. As a result, the variability, but not the average, of the ensemble responses of A1 neurons represented more faithfully the dynamic transitions in low-frequency sound envelopes both in quiet and in background noise.

MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis.

PubMed

Yang, Wanqi; Gao, Yang; Shi, Yinghuan; Cao, Longbing

2015-11-01

Learning about multiview data involves many applications, such as video understanding, image classification, and social media. However, when the data dimension increases dramatically, it is important but very challenging to remove redundant features in multiview feature selection. In this paper, we propose a novel feature selection algorithm, multiview rank minimization-based Lasso (MRM-Lasso), which jointly utilizes Lasso for sparse feature selection and rank minimization for learning relevant patterns across views. Instead of simply integrating multiple Lasso from view level, we focus on the performance of sample-level (sample significance) and introduce pattern-specific weights into MRM-Lasso. The weights are utilized to measure the contribution of each sample to the labels in the current view. In addition, the latent correlation across different views is successfully captured by learning a low-rank matrix consisting of pattern-specific weights. The alternating direction method of multipliers is applied to optimize the proposed MRM-Lasso. Experiments on four real-life data sets show that features selected by MRM-Lasso have better multiview classification performance than the baselines. Moreover, pattern-specific weights are demonstrated to be significant for learning about multiview data, compared with view-specific weights.

Attention-based image similarity measure with application to content-based information retrieval

NASA Astrophysics Data System (ADS)

Stentiford, Fred W. M.

2003-01-01

Whilst storage and capture technologies are able to cope with huge numbers of images, image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. This paper proposes a similarity measure that imposes only very weak assumptions on the nature of the features used in the recognition process. This approach does not make use of a pre-defined set of feature measurements which are extracted from a query image and used to match those from database images, but instead generates features on a trial and error basis during the calculation of the similarity measure. This has the significant advantage that features that determine similarity can match whatever image property is important in a particular region whether it be a shape, a texture, a colour or a combination of all three. It means that effort is expended searching for the best feature for the region rather than expecting that a fixed feature set will perform optimally over the whole area of an image and over every image in a database. The similarity measure is evaluated on a problem of distinguishing similar shapes in sets of black and white symbols.

Using Selective Drainage Methods to Extract Continuous Surface Flow from 1-Meter Lidar-Derived Digital Elevation Data

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

2010-01-01

Digital elevation data commonly are used to extract surface flow features. One source for high-resolution elevation data is light detection and ranging (lidar). Lidar can capture a vast amount of topographic detail because of its fine-scale ability to digitally capture the surface of the earth. Because elevation is a key factor in extracting surface flow features, high-resolution lidar-derived digital elevation models (DEMs) provide the detail needed to consistently integrate hydrography with elevation, land cover, structures, and other geospatial features. The U.S. Geological Survey has developed selective drainage methods to extract continuous surface flow from high-resolution lidar-derived digital elevation data. The lidar-derived continuous surface flow network contains valuable information for water resource management involving flood hazard mapping, flood inundation, and coastal erosion. DEMs used in hydrologic applications typically are processed to remove depressions by filling them. High-resolution DEMs derived from lidar can capture much more detail of the land surface than courser elevation data. Therefore, high-resolution DEMs contain more depressions because of obstructions such as roads, railroads, and other elevated structures. The filling of these depressions can significantly affect the DEM-derived surface flow routing and terrain characteristics in an adverse way. In this report, selective draining methods that modify the elevation surface to drain a depression through an obstruction are presented. If such obstructions are not removed from the elevation data, the filling of depressions to create continuous surface flow can cause the flow to spill over an obstruction in the wrong location. Using this modified elevation surface improves the quality of derived surface flow and retains more of the true surface characteristics by correcting large filled depressions. A reliable flow surface is necessary for deriving a consistently connected drainage network, which is important in understanding surface water movement and developing applications for surface water runoff, flood inundation, and erosion. Improved methods are needed to extract continuous surface flow features from high-resolution elevation data based on lidar.

Point-of-View Recording Devices for Intraoperative Neurosurgical Video Capture.

PubMed

Porras, Jose L; Khalid, Syed; Root, Brandon K; Khan, Imad S; Singer, Robert J

2016-01-01

The ability to record and stream neurosurgery is an unprecedented opportunity to further research, medical education, and quality improvement. Here, we appraise the ease of implementation of existing point-of-view devices when capturing and sharing procedures from the neurosurgical operating room and detail their potential utility in this context. Our neurosurgical team tested and critically evaluated features of the Google Glass and Panasonic HX-A500 cameras, including ergonomics, media quality, and media sharing in both the operating theater and the angiography suite. Existing devices boast several features that facilitate live recording and streaming of neurosurgical procedures. Given that their primary application is not intended for the surgical environment, we identified a number of concrete, yet improvable, limitations. The present study suggests that neurosurgical video capture and live streaming represents an opportunity to contribute to research, education, and quality improvement. Despite this promise, shortcomings render existing devices impractical for serious consideration. We describe the features that future recording platforms should possess to improve upon existing technology.

Dynamical Model of Drug Accumulation in Bacteria: Sensitivity Analysis and Experimentally Testable Predictions

DOE PAGES

Vesselinova, Neda; Alexandrov, Boian; Wall, Michael E.

2016-11-08

We present a dynamical model of drug accumulation in bacteria. The model captures key features in experimental time courses on ofloxacin accumulation: initial uptake; two-phase response; and long-term acclimation. In combination with experimental data, the model provides estimates of import and export rates in each phase, the time of entry into the second phase, and the decrease of internal drug during acclimation. Global sensitivity analysis, local sensitivity analysis, and Bayesian sensitivity analysis of the model provide information about the robustness of these estimates, and about the relative importance of different parameters in determining the features of the accumulation time coursesmore » in three different bacterial species: Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The results lead to experimentally testable predictions of the effects of membrane permeability, drug efflux and trapping (e.g., by DNA binding) on drug accumulation. A key prediction is that a sudden increase in ofloxacin accumulation in both E. coli and S. aureus is accompanied by a decrease in membrane permeability.« less

Dynamical Model of Drug Accumulation in Bacteria: Sensitivity Analysis and Experimentally Testable Predictions

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

Vesselinova, Neda; Alexandrov, Boian; Wall, Michael E.

We present a dynamical model of drug accumulation in bacteria. The model captures key features in experimental time courses on ofloxacin accumulation: initial uptake; two-phase response; and long-term acclimation. In combination with experimental data, the model provides estimates of import and export rates in each phase, the time of entry into the second phase, and the decrease of internal drug during acclimation. Global sensitivity analysis, local sensitivity analysis, and Bayesian sensitivity analysis of the model provide information about the robustness of these estimates, and about the relative importance of different parameters in determining the features of the accumulation time coursesmore » in three different bacterial species: Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The results lead to experimentally testable predictions of the effects of membrane permeability, drug efflux and trapping (e.g., by DNA binding) on drug accumulation. A key prediction is that a sudden increase in ofloxacin accumulation in both E. coli and S. aureus is accompanied by a decrease in membrane permeability.« less

Beyond parental control and authoritarian parenting style: understanding Chinese parenting through the cultural notion of training.

PubMed

Chao, R K

1994-08-01

This study addresses a paradox in the literature involving the parenting style of Asians: Chinese parenting has often been described as "controlling" or "authoritarian". These styles of parenting have been found to be predictive of poor school achievement among European-Americans, and yet the Chinese are performing quite well in school. This study suggests that the concepts of authoritative and authoritarian are somewhat ethnocentric and do not capture the important features of Chinese child rearing, especially for explaining their school success. Immigrant Chinese and European-American mothers of preschool-aged children were administered standard measures of parental control and authoritative-authoritarian parenting style as well as Chinese child-rearing items involving the concept of "training." After controlling for their education, and their scores on the standard measures, the Chinese mothers were found to score significantly higher on the "training" ideologies. This "training" concept has important features, beyond the authoritarian concept, that may explain Chinese school success.

Appearance-based human gesture recognition using multimodal features for human computer interaction

NASA Astrophysics Data System (ADS)

Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

2011-03-01

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

High-fidelity simulation of transcutaneous cardiac pacing: characteristics and limitations of available high-fidelity simulators, and description of an alternative two-mannequin model.

PubMed

Robitaille, Arnaud; Perron, Roger; Germain, Jean-François; Tanoubi, Issam; Georgescu, Mihai

2015-04-01

Transcutaneous cardiac pacing (TCP) is a potentially lifesaving technique that is part of the recommended treatment for symptomatic bradycardia. Transcutaneous cardiac pacing however is used uncommonly, and its successful application is not straightforward. Simulation could, therefore, play an important role in the teaching and assessment of TCP competence. However, even the highest-fidelity mannequins available on the market have important shortcomings, which limit the potential of simulation. Six criteria defining clinical competency in TCP were established and used as a starting point in the creation of an improved TCP simulator. The goal was a model that could be used to assess experienced clinicians, an objective that justifies the additional effort required by the increased fidelity. The proposed 2-mannequin model (TMM) combines a highly modified Human Patient Simulator with a SimMan 3G, the latter being used solely to provide the electrocardiography (ECG) tracing. The TMM improves the potential of simulation to assess experienced clinicians (1) by reproducing key features of TCP, like using the same multifunctional pacing electrodes used clinically, allowing dual ECG monitoring, and responding with upper body twitching when stimulated, but equally importantly (2) by reproducing key pitfalls of the technique, like allowing pacing electrode misplacement and reproducing false signs of ventricular capture, commonly, but erroneously, used clinically to establish that effective pacing has been achieved (like body twitching, electrical artifact on the ECG, and electrical capture without ventricular capture). The proposed TMM uses a novel combination of 2 high-fidelity mannequins to improve TCP simulation until upgraded mannequins become commercially available.

Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

PubMed

Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

2012-11-07

RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.

Contextually guided very-high-resolution imagery classification with semantic segments

NASA Astrophysics Data System (ADS)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

SIMS analysis of extended impact features on LDEF experiment

NASA Technical Reports Server (NTRS)

Amari, S.; Foote, J.; Jessberger, E. K.; Simon, C.; Stadermann, F. J.; Swan, P.; Walker, R.; Zinner, E.

1991-01-01

Discussed here are the first Secondary Ion Mass Spectroscopy (SIMS) analysis of projectile material deposited in extended impact features on Ge wafers from the trailing edge. Although most capture cells lost their plastic film covers, they contain extended impact features that apparently were produced by high velocity impacts when the plastic foils were still intact. Detailed optical scanning of all bare capture cells from the trailing edge revealed more than 100 impacts. Fifty-eight were selected by scanning electron microscope (SEM) inspection as prime candidates for SIMS analysis. Preliminary SIMS measurements were made on 15 impacts. More than half showed substantial enhancements of Mg, Al, Si, Ca, and Fe in the impact region, indicating micrometeorites as the projectiles.

Studying Electron-Capture on ^64Zn in Supernovae with the (t,^3He) Charge-Exchange Reaction

NASA Astrophysics Data System (ADS)

Hitt, G. W.; Austin, Sam M.; Bazin, D.; Gade, A.; Guess, C. J.; Galaviz-Redondo, D.; Shimbara, Y.; Tur, C.; Zegers, R. G. T.; Horoi, M.; Howard, M. E.; Smith, E. E.

2008-10-01

A secondary, 115 MeV/u triton beam has been developed at NSCL for use in (t,^3He) charge-exchange(CE) reaction studies. This (n,p)-type CE reaction is useful for extracting the full Gamow-Teller (GT) response of the nucleus, overcoming Q-value restrictions present in conventional beta-decay studies. The strength (B(GT)) in ^64Cu has been determined from the absolute cross section measurement of ^64Zn(t,^3He) near zero-degrees, exploiting an empirical proportionality between cross section and B(GT). The detailed features of the B(GT) distribution in a nucleus has an important impact on electron-capture (EC) rates in Type Ia and Core-Collapse supernovae. The measured B(GT) in ^64Cu is directly compared with the results of modern shell model interactions which are used to calculate the GT contribution to EC on nuclei in supernova simulations.

Race, socioeconomic status, and health: complexities, ongoing challenges, and research opportunities.

PubMed

Williams, David R; Mohammed, Selina A; Leavell, Jacinta; Collins, Chiquita

2010-02-01

This paper provides an overview of racial variations in health and shows that differences in socioeconomic status (SES) across racial groups are a major contributor to racial disparities in health. However, race reflects multiple dimensions of social inequality and individual and household indicators of SES capture relevant but limited aspects of this phenomenon. Research is needed that will comprehensively characterize the critical pathogenic features of social environments and identify how they combine with each other to affect health over the life course. Migration history and status are also important predictors of health and research is needed that will enhance understanding of the complex ways in which race, SES, and immigrant status combine to affect health. Fully capturing the role of race in health also requires rigorous examination of the conditions under which medical care and genetic factors can contribute to racial and SES differences in health. The paper identifies research priorities in all of these areas.

Distant supervision for neural relation extraction integrated with word attention and property features.

PubMed

Qu, Jianfeng; Ouyang, Dantong; Hua, Wen; Ye, Yuxin; Li, Ximing

2018-04-01

Distant supervision for neural relation extraction is an efficient approach to extracting massive relations with reference to plain texts. However, the existing neural methods fail to capture the critical words in sentence encoding and meanwhile lack useful sentence information for some positive training instances. To address the above issues, we propose a novel neural relation extraction model. First, we develop a word-level attention mechanism to distinguish the importance of each individual word in a sentence, increasing the attention weights for those critical words. Second, we investigate the semantic information from word embeddings of target entities, which can be developed as a supplementary feature for the extractor. Experimental results show that our model outperforms previous state-of-the-art baselines. Copyright © 2018 Elsevier Ltd. All rights reserved.

Representation of memories in the cortical-hippocampal system: Results from the application of population similarity analyses

PubMed Central

McKenzie, Sam; Keene, Chris; Farovik, Anja; Blandon, John; Place, Ryan; Komorowski, Robert; Eichenbaum, Howard

2016-01-01

Here we consider the value of neural population analysis as an approach to understanding how information is represented in the hippocampus and cortical areas and how these areas might interact as a brain system to support memory. We argue that models based on sparse coding of different individual features by single neurons in these areas (e.g., place cells, grid cells) are inadequate to capture the complexity of experience represented within this system. By contrast, population analyses of neurons with denser coding and mixed selectivity reveal new and important insights into the organization of memories. Furthermore, comparisons of the organization of information in interconnected areas suggest a model of hippocampal-cortical interactions that mediates the fundamental features of memory. PMID:26748022

Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness.

PubMed

Balcarras, Matthew; Ardid, Salva; Kaping, Daniel; Everling, Stefan; Womelsdorf, Thilo

2016-02-01

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image analysis.

Automated cloud classification using a ground based infra-red camera and texture analysis techniques

NASA Astrophysics Data System (ADS)

Rumi, Emal; Kerr, David; Coupland, Jeremy M.; Sandford, Andrew P.; Brettle, Mike J.

2013-10-01

Clouds play an important role in influencing the dynamics of local and global weather and climate conditions. Continuous monitoring of clouds is vital for weather forecasting and for air-traffic control. Convective clouds such as Towering Cumulus (TCU) and Cumulonimbus clouds (CB) are associated with thunderstorms, turbulence and atmospheric instability. Human observers periodically report the presence of CB and TCU clouds during operational hours at airports and observatories; however such observations are expensive and time limited. Robust, automatic classification of cloud type using infrared ground-based instrumentation offers the advantage of continuous, real-time (24/7) data capture and the representation of cloud structure in the form of a thermal map, which can greatly help to characterise certain cloud formations. The work presented here utilised a ground based infrared (8-14 μm) imaging device mounted on a pan/tilt unit for capturing high spatial resolution sky images. These images were processed to extract 45 separate textural features using statistical and spatial frequency based analytical techniques. These features were used to train a weighted k-nearest neighbour (KNN) classifier in order to determine cloud type. Ground truth data were obtained by inspection of images captured simultaneously from a visible wavelength colour camera at the same installation, with approximately the same field of view as the infrared device. These images were classified by a trained cloud observer. Results from the KNN classifier gave an encouraging success rate. A Probability of Detection (POD) of up to 90% with a Probability of False Alarm (POFA) as low as 16% was achieved.

Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review.

PubMed

Issenberg, S Barry; McGaghie, William C; Petrusa, Emil R; Lee Gordon, David; Scalese, Ross J

2005-01-01

1969 to 2003, 34 years. Simulations are now in widespread use in medical education and medical personnel evaluation. Outcomes research on the use and effectiveness of simulation technology in medical education is scattered, inconsistent and varies widely in methodological rigor and substantive focus. Review and synthesize existing evidence in educational science that addresses the question, 'What are the features and uses of high-fidelity medical simulations that lead to most effective learning?'. The search covered five literature databases (ERIC, MEDLINE, PsycINFO, Web of Science and Timelit) and employed 91 single search terms and concepts and their Boolean combinations. Hand searching, Internet searches and attention to the 'grey literature' were also used. The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality. Four screening criteria were used to reduce the initial pool of 670 journal articles to a focused set of 109 studies: (a) elimination of review articles in favor of empirical studies; (b) use of a simulator as an educational assessment or intervention with learner outcomes measured quantitatively; (c) comparative research, either experimental or quasi-experimental; and (d) research that involves simulation as an educational intervention. Data were extracted systematically from the 109 eligible journal articles by independent coders. Each coder used a standardized data extraction protocol. Qualitative data synthesis and tabular presentation of research methods and outcomes were used. Heterogeneity of research designs, educational interventions, outcome measures and timeframe precluded data synthesis using meta-analysis. Coding accuracy for features of the journal articles is high. The extant quality of the published research is generally weak. The weight of the best available evidence suggests that high-fidelity medical simulations facilitate learning under the right conditions. These include the following: providing feedback--51 (47%) journal articles reported that educational feedback is the most important feature of simulation-based medical education; repetitive practice--43 (39%) journal articles identified repetitive practice as a key feature involving the use of high-fidelity simulations in medical education; curriculum integration--27 (25%) journal articles cited integration of simulation-based exercises into the standard medical school or postgraduate educational curriculum as an essential feature of their effective use; range of difficulty level--15 (14%) journal articles address the importance of the range of task difficulty level as an important variable in simulation-based medical education; multiple learning strategies--11 (10%) journal articles identified the adaptability of high-fidelity simulations to multiple learning strategies as an important factor in their educational effectiveness; capture clinical variation--11 (10%) journal articles cited simulators that capture a wide variety of clinical conditions as more useful than those with a narrow range; controlled environment--10 (9%) journal articles emphasized the importance of using high-fidelity simulations in a controlled environment where learners can make, detect and correct errors without adverse consequences; individualized learning--10 (9%) journal articles highlighted the importance of having reproducible, standardized educational experiences where learners are active participants, not passive bystanders; defined outcomes--seven (6%) journal articles cited the importance of having clearly stated goals with tangible outcome measures that will more likely lead to learners mastering skills; simulator validity--four (3%) journal articles provided evidence for the direct correlation of simulation validity with effective learning. While research in this field needs improvement in terms of rigor and quality, high-fidelity medical simulations are educationally effective and simulation-based education complements medical education in patient care settings.

Qualitative dynamics semantics for SBGN process description.

PubMed

Rougny, Adrien; Froidevaux, Christine; Calzone, Laurence; Paulevé, Loïc

2016-06-16

Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far. We propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F. The proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.

Tidal regime of intact planetoid capture model for the Earth-Moon system: Does it relate to the archean sedimentary rock record?

NASA Technical Reports Server (NTRS)

Malcuit, Robert J.; Winters, Ronald R.

1993-01-01

Regardless of one's favorite model for the origin of the Earth-Moon system (fission, coformation, tidal capture, giant-impact) the early history of lunar orbital evolution would produce significant thermal and earth and ocean tidal effects on the primitive earth. Three of the above lunar origin models (fission, coformation, giant-impact) feature a circular orbit which undergoes a progressive increase in orbital radius from the time of origin to the present time. In contrast, a tidal capture model places the moon in an elliptical orbit undergoing progressive circularization from the time of capture (for model purposes about 3.9 billion years ago) for at least a few 10(exp 8) years following the capture event. Once the orbit is circularized, the subsequent tidal history for a tidal capture scenario is similar to that for other models of lunar origin and features a progressive increase in orbital radius to the current state of the lunar orbit. This elliptical orbit phase, if it occurred, should have left a distinctive signature in the terrestrial and lunar rock records. Depositional events would be associated terrestrial shorelines characterized by abnormally high, but progressively decreasing, ocean tidal amplitudes and ranges associated with such an orbital evolution. Several rock units in the age range 3.6-2.5 billion years before present are reported to have a major tidal component. Examples are the Warrawoona, Fortescue, and Hamersley Groups of Western Australia and the Pangola and Witwatersand Supergroups of South Africa. Detailed study of the features of these tidal sequences may be helpful in deciphering the style of lunar orbital evolution during the Archean Eon.

Method and Apparatus for Automated Isolation of Nucleic Acids from Small Cell Samples

NASA Technical Reports Server (NTRS)

Sundaram, Shivshankar; Prabhakarpandian, Balabhaskar; Pant, Kapil; Wang, Yi

2014-01-01

RNA isolation is a ubiquitous need, driven by current emphasis on microarrays and miniaturization. With commercial systems requiring 100,000 to 1,000,000 cells for successful isolation, there is a growing need for a small-footprint, easy-to-use device that can harvest nucleic acids from much smaller cell samples (1,000 to 10,000 cells). The process of extraction of RNA from cell cultures is a complex, multi-step one, and requires timed, asynchronous operations with multiple reagents/buffers. An added complexity is the fragility of RNA (subject to degradation) and its reactivity to surface. A novel, microfluidics-based, integrated cartridge has been developed that can fully automate the complex process of RNA isolation (lyse, capture, and elute RNA) from small cell culture samples. On-cartridge cell lysis is achieved using either reagents or high-strength electric fields made possible by the miniaturized format. Traditionally, silica-based, porous-membrane formats have been used for RNA capture, requiring slow perfusion for effective capture. In this design, high efficiency capture/elution are achieved using a microsphere-based "microfluidized" format. Electrokinetic phenomena are harnessed to actively mix microspheres with the cell lysate and capture/elution buffer, providing important advantages in extraction efficiency, processing time, and operational flexibility. Successful RNA isolation was demonstrated using both suspension (HL-60) and adherent (BHK-21) cells. Novel features associated with this development are twofold. First, novel designs that execute needed processes with improved speed and efficiency were developed. These primarily encompass electric-field-driven lysis of cells. The configurations include electrode-containing constructs, or an "electrode-less" chip design, which is easy to fabricate and mitigates fouling at the electrode surface; and the "fluidized" extraction format based on electrokinetically assisted mixing and contacting of microbeads in a shape-optimized chamber. A secondary proprietary feature is in the particular layout integrating these components to perform the desired operation of RNA isolation. Apart from a novel functional capability, advantages of the innovation include reduced or eliminated use of toxic reagents, and operator-independent extraction of RNA.

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

Comparison of image features calculated in different dimensions for computer-aided diagnosis of lung nodules

NASA Astrophysics Data System (ADS)

Xu, Ye; Lee, Michael C.; Boroczky, Lilla; Cann, Aaron D.; Borczuk, Alain C.; Kawut, Steven M.; Powell, Charles A.

2009-02-01

Features calculated from different dimensions of images capture quantitative information of the lung nodules through one or multiple image slices. Previously published computer-aided diagnosis (CADx) systems have used either twodimensional (2D) or three-dimensional (3D) features, though there has been little systematic analysis of the relevance of the different dimensions and of the impact of combining different dimensions. The aim of this study is to determine the importance of combining features calculated in different dimensions. We have performed CADx experiments on 125 pulmonary nodules imaged using multi-detector row CT (MDCT). The CADx system computed 192 2D, 2.5D, and 3D image features of the lesions. Leave-one-out experiments were performed using five different combinations of features from different dimensions: 2D, 3D, 2.5D, 2D+3D, and 2D+3D+2.5D. The experiments were performed ten times for each group. Accuracy, sensitivity and specificity were used to evaluate the performance. Wilcoxon signed-rank tests were applied to compare the classification results from these five different combinations of features. Our results showed that 3D image features generate the best result compared with other combinations of features. This suggests one approach to potentially reducing the dimensionality of the CADx data space and the computational complexity of the system while maintaining diagnostic accuracy.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

On the generality of the displaywide contingent orienting hypothesis: can a visual onset capture attention without top-down control settings for displaywide onset?

PubMed

Yeh, Su-Ling; Liao, Hsin-I

2010-10-01

The contingent orienting hypothesis (Folk, Remington, & Johnston, 1992) states that attentional capture is contingent on top-down control settings induced by task demands. Past studies supporting this hypothesis have identified three kinds of top-down control settings: for target-specific features, for the strategy to search for a singleton, and for visual features in the target display as a whole. Previously, we have found stimulus-driven capture by onset that was not contingent on the first two kinds of settings (Yeh & Liao, 2008). The current study aims to test the third kind: the displaywide contingent orienting hypothesis (Gibson & Kelsey, 1998). Specifically, we ask whether an onset stimulus can still capture attention in the spatial cueing paradigm when attentional control settings for the displaywide onset of the target are excluded by making all letters in the target display emerge from placeholders. Results show that a preceding uninformative onset cue still captured attention to its location in a stimulus-driven fashion, whereas a color cue captured attention only when it was contingent on the setting for displaywide color. These results raise doubts as to the generality of the displaywide contingent orienting hypothesis and help delineate the boundary conditions on this hypothesis. Copyright © 2010 Elsevier B.V. All rights reserved.

Comparing Wavelengths

NASA Image and Video Library

2015-12-12

This side-by-side rendering of the Sun at the same time in two different wavelengths of extreme ultraviolet light helps to visualize the differing features visible in each wavelength (Dec. 10-11, 2015). Most prominently, we can see much finer strands of plasma looping above the surface in the 171 Angstrom wavelength (gold) than in the 304 Angstrom wavelength (red), which captures cooler plasma closer to the Sun's surface. SDO observes the Sun in 10 different wavelengths with each one capturing somewhat different features at various temperatures and elevations above the Sun. http://photojournal.jpl.nasa.gov/catalog/PIA20214

Context and competition in the capture of visual attention.

PubMed

Hickey, Clayton; Theeuwes, Jan

2011-10-01

Competition-based models of visual attention propose that perceptual ambiguity is resolved through inhibition, which is stronger when objects share a greater number of neural receptive fields (RFs). According to this theory, the misallocation of attention to a salient distractor--that is, the capture of attention--can be indexed in RF-scaled interference costs. We used this pattern to investigate distractor-related costs in visual search across several manipulations of temporal context. Distractor costs are generally larger under circumstances in which the distractor can be defined by features that have recently characterised the target, suggesting that capture occurs in these trials. However, our results show that search for a target in the presence of a salient distractor also produces RF-scaled costs when the features defining the target and distractor do not vary from trial to trial. Contextual differences in distractor costs appear to reflect something other than capture, perhaps a qualitative difference in the type of attentional mechanism deployed to the distractor.

From tiger to panda: animal head detection.

PubMed

Zhang, Weiwei; Sun, Jian; Tang, Xiaoou

2011-06-01

Robust object detection has many important applications in real-world online photo processing. For example, both Google image search and MSN live image search have integrated human face detector to retrieve face or portrait photos. Inspired by the success of such face filtering approach, in this paper, we focus on another popular online photo category--animal, which is one of the top five categories in the MSN live image search query log. As a first attempt, we focus on the problem of animal head detection of a set of relatively large land animals that are popular on the internet, such as cat, tiger, panda, fox, and cheetah. First, we proposed a new set of gradient oriented feature, Haar of Oriented Gradients (HOOG), to effectively capture the shape and texture features on animal head. Then, we proposed two detection algorithms, namely Bruteforce detection and Deformable detection, to effectively exploit the shape feature and texture feature simultaneously. Experimental results on 14,379 well labeled animals images validate the superiority of the proposed approach. Additionally, we apply the animal head detector to improve the image search result through text based online photo search result filtering.

Forecasting air quality time series using deep learning.

PubMed

Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.

Time-Series Approaches for Forecasting the Number of Hospital Daily Discharged Inpatients.

PubMed

Ting Zhu; Li Luo; Xinli Zhang; Yingkang Shi; Wenwu Shen

2017-03-01

For hospitals where decisions regarding acceptable rates of elective admissions are made in advance based on expected available bed capacity and emergency requests, accurate predictions of inpatient bed capacity are especially useful for capacity reservation purposes. As given, the remaining unoccupied beds at the end of each day, bed capacity of the next day can be obtained by examining the forecasts of the number of discharged patients during the next day. The features of fluctuations in daily discharges like trend, seasonal cycles, special-day effects, and autocorrelation complicate decision optimizing, while time-series models can capture these features well. This research compares three models: a model combining seasonal regression and ARIMA, a multiplicative seasonal ARIMA (MSARIMA) model, and a combinatorial model based on MSARIMA and weighted Markov Chain models in generating forecasts of daily discharges. The models are applied to three years of discharge data of an entire hospital. Several performance measures like the direction of the symmetry value, normalized mean squared error, and mean absolute percentage error are utilized to capture the under- and overprediction in model selection. The findings indicate that daily discharges can be forecast by using the proposed models. A number of important practical implications are discussed, such as the use of accurate forecasts in discharge planning, admission scheduling, and capacity reservation.

Quality of Life for Diverse Older Adults in Assisted Living: The Centrality of Control.

PubMed

Koehn, Sharon D; Mahmood, Atiya N; Stott-Eveneshen, Sarah

This pilot project asked: How do ethnically diverse older adult residents of assisted living (AL) facilities in British Columbia (BC) experience quality of life? And, what role, if any, do organizational and physical environmental features play in influencing how quality of life is experienced? The study was conducted at three AL sites in BC: two ethnoculturally targeted and one nontargeted. Environmental audits at each site captured descriptive data on policies, fees, rules, staffing, meals, and activities, and the built environment of the AL building and neighborhood. Using a framework that understands the quality of life of older adults to be contingent on their capability to pursue 5 conceptual attributes-attachment, role, enjoyment, security, and control-we conducted 3 focus groups with residents (1 per site) and 6 interviews with staff (2 per site). Attributes were linked to the environmental features captured in the audits. All dimensions of the environment, especially organizational, influence tenants' capability to attain the attributes of quality of life, most importantly control. Although many tenants accept the trade-off between increased safety and diminished control that accompanies a move into AL, more could be done to minimize that loss. Social workers can advocate for the necessary multi-sectoral changes.

Corresponding-states behavior of SPC/E-based modified (bent and hybrid) water models

NASA Astrophysics Data System (ADS)

Weiss, Volker C.

2017-02-01

The remarkable and sometimes anomalous properties of water can be traced back at the molecular level to the tetrahedral coordination of molecules due to the ability of a water molecule to form four hydrogen bonds to its neighbors; this feature allows for the formation of a network that greatly influences the thermodynamic behavior. Computer simulations are becoming increasingly important for our understanding of water. Molecular models of water, such as SPC/E, are needed for this purpose, and they have proved to capture many important features of real water. Modifications of the SPC/E model have been proposed, some changing the H-O-H angle (bent models) and others increasing the importance of dispersion interactions (hybrid models), to study the structural features that set water apart from other polar fluids and from simple fluids such as argon. Here, we focus on the properties at liquid-vapor equilibrium and study the coexistence curve, the interfacial tension, and the vapor pressure in a corresponding-states approach. In particular, we calculate Guggenheim's ratio for the reduced apparent enthalpy of vaporization and Guldberg's ratio for the reduced normal boiling point. This analysis offers additional insight from a more macroscopic, thermodynamic perspective and augments that which has already been learned at the molecular level from simulations. In the hybrid models, the relative importance of dispersion interactions is increased, which turns the modified water into a Lennard-Jones-like fluid. Consequently, in a corresponding-states framework, the typical behavior of simple fluids, such as argon, is seen to be approached asymptotically. For the bent models, decreasing the bond angle turns the model essentially into a polar diatomic fluid in which the particles form linear molecular arrangements; as a consequence, characteristic features of the corresponding-states behavior of hydrogen halides emerge.

Towards an Interoperability Ontology for Software Development Tools

DTIC Science & Technology

2003-03-01

The description of feature models was tied to the introduction of the Feature-Oriented Domain Analysis ( FODA *) [KANG90] approach in the late eighties...Feature-oriented domain analysis ( FODA ) is a domain analysis method developed at the Software...ese obstacles was to construct a “pilot” ontology that is extensible. We applied the Feature-Oriented Domain Analysis approach to capture the

Deep visual-semantic for crowded video understanding

NASA Astrophysics Data System (ADS)

Deng, Chunhua; Zhang, Junwen

2018-03-01

Visual-semantic features play a vital role for crowded video understanding. Convolutional Neural Networks (CNNs) have experienced a significant breakthrough in learning representations from images. However, the learning of visualsemantic features, and how it can be effectively extracted for video analysis, still remains a challenging task. In this study, we propose a novel visual-semantic method to capture both appearance and dynamic representations. In particular, we propose a spatial context method, based on the fractional Fisher vector (FV) encoding on CNN features, which can be regarded as our main contribution. In addition, to capture temporal context information, we also applied fractional encoding method on dynamic images. Experimental results on the WWW crowed video dataset demonstrate that the proposed method outperform the state of the art.

Distance error correction for time-of-flight cameras

NASA Astrophysics Data System (ADS)

Fuersattel, Peter; Schaller, Christian; Maier, Andreas; Riess, Christian

2017-06-01

The measurement accuracy of time-of-flight cameras is limited due to properties of the scene and systematic errors. These errors can accumulate to multiple centimeters which may limit the applicability of these range sensors. In the past, different approaches have been proposed for improving the accuracy of these cameras. In this work, we propose a new method that improves two important aspects of the range calibration. First, we propose a new checkerboard which is augmented by a gray-level gradient. With this addition it becomes possible to capture the calibration features for intrinsic and distance calibration at the same time. The gradient strip allows to acquire a large amount of distance measurements for different surface reflectivities, which results in more meaningful training data. Second, we present multiple new features which are used as input to a random forest regressor. By using random regression forests, we circumvent the problem of finding an accurate model for the measurement error. During application, a correction value for each individual pixel is estimated with the trained forest based on a specifically tailored feature vector. With our approach the measurement error can be reduced by more than 40% for the Mesa SR4000 and by more than 30% for the Microsoft Kinect V2. In our evaluation we also investigate the impact of the individual forest parameters and illustrate the importance of the individual features.

Sex-chromosome turnovers: the hot-potato model.

PubMed

Blaser, Olivier; Neuenschwander, Samuel; Perrin, Nicolas

2014-01-01

Sex-determining systems often undergo high rates of turnover but for reasons that remain largely obscure. Two recent evolutionary models assign key roles, respectively, to sex-antagonistic (SA) mutations occurring on autosomes and to deleterious mutations accumulating on sex chromosomes. These two models capture essential but distinct key features of sex-chromosome evolution; accordingly, they make different predictions and present distinct limitations. Here we show that a combination of features from the two models has the potential to generate endless cycles of sex-chromosome transitions: SA alleles accruing on a chromosome after it has been co-opted for sex induce an arrest of recombination; the ensuing accumulation of deleterious mutations will soon make a new transition ineluctable. The dynamics generated by these interactions share several important features with empirical data, namely, (i) that patterns of heterogamety tend to be conserved during transitions and (ii) that autosomes are not recruited randomly, with some chromosome pairs more likely than others to be co-opted for sex.

New Science in Plain Sight: Optical Manifestations of Coupled Subauroral Features Documented by Citizen Scientists

NASA Astrophysics Data System (ADS)

MacDonald, E.; Heavner, M.; Kosar, B.; Case, N.; Donovan, E.; Spanswick, E.; Nishimura, Y.; Gallardo-Lacourt, B.

2017-12-01

Aurora has been observed and recorded by people for thousands of years. Recently, citizen scientists captured features of aurora-like arc events not previously described in the literature at subauroral latitudes. Amateur photo sequences show unusual flow, unstable composition changes, and field aligned structures. Observations from the Swarm satellite crossing the arc reveals thermal enhancement, density depletion, and strong westward ion flow. These signatures resemble features previously described from in situ observation however the optical manifestation is surprising and contains rich, unstable signatures as well. The relevant observations have presented important implications on a variety of open questions, including the fundamental definition of aurora, and limitations of jargon and subfield distinctions. This paper covers the discovery, its context, and the significant implications for the application of public participation measurement modes to the natural sciences whereby they can form a disruptive gap to expose new observing perspectives. Photo Credit: Notanee Bourassa, Alberta Aurora Chasers

A bioinspired redox relay that mimics radical interactions of the Tyr-His pairs of photosystem II

NASA Astrophysics Data System (ADS)

Megiatto, Jackson D., Jr.; Méndez-Hernández, Dalvin D.; Tejeda-Ferrari, Marely E.; Teillout, Anne-Lucie; Llansola-Portolés, Manuel J.; Kodis, Gerdenis; Poluektov, Oleg G.; Rajh, Tijana; Mujica, Vladimiro; Groy, Thomas L.; Gust, Devens; Moore, Thomas A.; Moore, Ana L.

2014-05-01

In water-oxidizing photosynthetic organisms, light absorption generates a powerfully oxidizing chlorophyll complex (P680•+) in the photosystem II reaction centre. This is reduced via an electron transfer pathway from the manganese-containing water-oxidizing catalyst, which includes an electron transfer relay comprising a tyrosine (Tyr)-histidine (His) pair that features a hydrogen bond between a phenol group and an imidazole group. By rapidly reducing P680•+, the relay is thought to mitigate recombination reactions, thereby ensuring a high quantum yield of water oxidation. Here, we show that an artificial reaction centre that features a benzimidazole-phenol model of the Tyr-His pair mimics both the short-internal hydrogen bond in photosystem II and, using electron paramagnetic resonance spectroscopy, the thermal relaxation that accompanies proton-coupled electron transfer. Although this artificial system is much less complex than the natural one, theory suggests that it captures the essential features that are important in the function of the relay.

The Role of Near-Fault Relief in Creating and Maintaining Strike-Slip Landscape Features

NASA Astrophysics Data System (ADS)

Harbert, S.; Duvall, A. R.; Tucker, G. E.

2016-12-01

Geomorphic landforms, such as shutter ridges, offset river terraces, and deflected stream channels, are often used to assess the activity and slip rates of strike-slip faults. However, in some systems, such as parts of the Marlborough Fault System (South Island, NZ), an active strike-slip fault does not leave a strong landscape signature. Here we explore the factors that dampen or enhance the landscape signature of strike-slip faulting using the Channel-Hillslope Integrated Landscape Development model (CHILD). We focus on variables affecting the length of channel offsets, which enhance the signature of strike-slip motion, and the frequency of stream captures, which eliminate offsets and reduce this signature. We model a strike-slip fault that passes through a mountain ridge, offsetting streams that drain across this fault. We use this setup to test the response of channel offset length and capture frequency to fault characteristics, such as slip rate and ratio of lateral to vertical motion, and to landscape characteristics, such as relief contrasts controlled by erodibility. Our experiments show that relief downhill of the fault, whether generated by differential uplift across the fault or by an erodibility contrast, has the strongest effect on offset length and capture frequency. This relief creates shutter ridges, which block and divert streams while being advected along a fault. Shutter ridges and the streams they divert have long been recognized as markers of strike-slip motion. Our results show specifically that the height of shutter ridges is most responsible for the degree to which they create long channel offsets by preventing stream captures. We compare these results to landscape metrics in the Marlborough Fault System, where shutter ridges are common and often lithologically controlled. We compare shutter ridge length and height to channel offset length in order to assess the influence of relief on offset channel features in a real landscape. Based on our model and field results, we conclude that vertical relief is important for generating and preserving offset features that are viewed as characteristic of a strike-slip fault. Therefore, the geomorphic expression of a fault may be dependent on characteristics of the surrounding landscape rather than primarily a function of the nature of slip on the fault.

Judgments at Gaze Value: Gaze Cuing in Banner Advertisements, Its Effect on Attention Allocation and Product Judgments.

PubMed

Palcu, Johanna; Sudkamp, Jennifer; Florack, Arnd

2017-01-01

Banner advertising is a popular means of promoting products and brands online. Although banner advertisements are often designed to be particularly attention grabbing, they frequently go unnoticed. Applying an eye-tracking procedure, the present research aimed to (a) determine whether presenting human faces (static or animated) in banner advertisements is an adequate tool for capturing consumers' attention and thus overcoming the frequently observed phenomenon of banner blindness, (b) to examine whether the gaze of a featured face possesses the ability to direct consumers' attention toward specific elements (i.e., the product) in an advertisement, and (c) to establish whether the gaze direction of an advertised face influences consumers subsequent evaluation of the advertised product. We recorded participants' eye gaze while they viewed a fictional online shopping page displaying banner advertisements that featured either no human face or a human face that was either static or animated and involved different gaze directions (toward or away from the advertised product). Moreover, we asked participants to subsequently evaluate a set of products, one of which was the product previously featured in the banner advertisement. Results showed that, when advertisements included a human face, participants' attention was more attracted by and they looked longer at animated compared with static banner advertisements. Moreover, when a face gazed toward the product region, participants' likelihood of looking at the advertised product increased regardless of whether the face was animated or not. Most important, gaze direction influenced subsequent product evaluations; that is, consumers indicated a higher intention to buy a product when it was previously presented in a banner advertisement that featured a face that gazed toward the product. The results suggest that while animation in banner advertising constitutes a salient feature that captures consumers' visual attention, gaze cuing can be an effective tool for driving viewers' attention toward specific elements in the advertisement and even shaping consumers' intentions to purchase the advertised product.

Judgments at Gaze Value: Gaze Cuing in Banner Advertisements, Its Effect on Attention Allocation and Product Judgments

PubMed Central

Palcu, Johanna; Sudkamp, Jennifer; Florack, Arnd

2017-01-01

Banner advertising is a popular means of promoting products and brands online. Although banner advertisements are often designed to be particularly attention grabbing, they frequently go unnoticed. Applying an eye-tracking procedure, the present research aimed to (a) determine whether presenting human faces (static or animated) in banner advertisements is an adequate tool for capturing consumers’ attention and thus overcoming the frequently observed phenomenon of banner blindness, (b) to examine whether the gaze of a featured face possesses the ability to direct consumers’ attention toward specific elements (i.e., the product) in an advertisement, and (c) to establish whether the gaze direction of an advertised face influences consumers subsequent evaluation of the advertised product. We recorded participants’ eye gaze while they viewed a fictional online shopping page displaying banner advertisements that featured either no human face or a human face that was either static or animated and involved different gaze directions (toward or away from the advertised product). Moreover, we asked participants to subsequently evaluate a set of products, one of which was the product previously featured in the banner advertisement. Results showed that, when advertisements included a human face, participants’ attention was more attracted by and they looked longer at animated compared with static banner advertisements. Moreover, when a face gazed toward the product region, participants’ likelihood of looking at the advertised product increased regardless of whether the face was animated or not. Most important, gaze direction influenced subsequent product evaluations; that is, consumers indicated a higher intention to buy a product when it was previously presented in a banner advertisement that featured a face that gazed toward the product. The results suggest that while animation in banner advertising constitutes a salient feature that captures consumers’ visual attention, gaze cuing can be an effective tool for driving viewers’ attention toward specific elements in the advertisement and even shaping consumers’ intentions to purchase the advertised product. PMID:28626436

Heterogeneity wavelet kinetics from DCE-MRI for classifying gene expression based breast cancer recurrence risk.

PubMed

Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; Mies, Carolyn; Feldman, Michael; Rosen, Mark; Kontos, Despina

2013-01-01

Breast tumors are heterogeneous lesions. Intra-tumor heterogeneity presents a major challenge for cancer diagnosis and treatment. Few studies have worked on capturing tumor heterogeneity from imaging. Most studies to date consider aggregate measures for tumor characterization. In this work we capture tumor heterogeneity by partitioning tumor pixels into subregions and extracting heterogeneity wavelet kinetic (HetWave) features from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to obtain the spatiotemporal patterns of the wavelet coefficients and contrast agent uptake from each partition. Using a genetic algorithm for feature selection, and a logistic regression classifier with leave one-out cross validation, we tested our proposed HetWave features for the task of classifying breast cancer recurrence risk. The classifier based on our features gave an ROC AUC of 0.78, outperforming previously proposed kinetic, texture, and spatial enhancement variance features which give AUCs of 0.69, 0.64, and 0.65, respectively.

Anion-activated, thermoreversible gelation system for the capture, release, and visual monitoring of CO2

NASA Astrophysics Data System (ADS)

Zhang, Xin; Lee, Songyi; Liu, Yifan; Lee, Minji; Yin, Jun; Sessler, Jonathan L.; Yoon, Juyoung

2014-04-01

Carbon dioxide (CO2) is an important green house gas. This is providing an incentive to develop new strategies to detect and capture CO2. Achieving both functions within a single molecular system represents an unmet challenge in terms of molecular design and could translate into enhanced ease of use. Here, we report an anion-activated chemosensor system, NAP-chol 1, that permits dissolved CO2 to be detected in organic media via simple color changes or through ratiometric differences in fluorescence intensity. NAP-chol 1 also acts as a super gelator for DMSO. The resulting gel is transformed into a homogeneous solution upon exposure to fluoride anions. Bubbling with CO2 regenerates the gel. Subsequent flushing with N2 or heating serves to release the CO2 and reform the sol form. This series of transformations is reversible and can be followed by easy-to-discern color changes. Thus, NAP-chol 1 allows for the capture and release of CO2 gas while acting as a three mode sensing system. In particular, it permits CO2 to be detected through reversible sol-gel transitions, simple changes in color, or ratiometric monitoring of the differences in the fluorescence features.

Characterization of Unsteady Flow Structures Near Landing-Edge Slat. Part 2; 2D Computations

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi; Choudhari, Meelan M.; Jenkins, Luther N.

2004-01-01

In our previous computational studies of a generic high-lift configuration, quasi-laminar (as opposed to fully turbulent) treatment of the slat cove region proved to be an effective approach for capturing the unsteady dynamics of the cove flow field. Combined with acoustic propagation via Ffowes Williams and Hawkings formulation, the quasi-laminar simulations captured some important features of the slat cove noise measured with microphone array techniques. However. a direct assessment of the computed cove flow field was not feasible due to the unavailability of off-surface flow measurements. To remedy this shortcoming, we have undertaken a combined experiment and computational study aimed at characterizing the flow structures and fluid mechanical processes within the slat cove region. Part I of this paper outlines the experimental aspects of this investigation focused on the 30P30N high-lift configuration; the present paper describes the accompanying computational results including a comparison between computation and experiment at various angles of attack. Even through predictions of the time-averaged flow field agree well with the measured data, the study indicates the need for further refinement of the zonal turbulence approach in order to capture the full dynamics of the cove's fluctuating flow field.

Bayesian inference in camera trapping studies for a class of spatial capture-recapture models

USGS Publications Warehouse

Royle, J. Andrew; Karanth, K. Ullas; Gopalaswamy, Arjun M.; Kumar, N. Samba

2009-01-01

We develop a class of models for inference about abundance or density using spatial capture-recapture data from studies based on camera trapping and related methods. The model is a hierarchical model composed of two components: a point process model describing the distribution of individuals in space (or their home range centers) and a model describing the observation of individuals in traps. We suppose that trap- and individual-specific capture probabilities are a function of distance between individual home range centers and trap locations. We show that the models can be regarded as generalized linear mixed models, where the individual home range centers are random effects. We adopt a Bayesian framework for inference under these models using a formulation based on data augmentation. We apply the models to camera trapping data on tigers from the Nagarahole Reserve, India, collected over 48 nights in 2006. For this study, 120 camera locations were used, but cameras were only operational at 30 locations during any given sample occasion. Movement of traps is common in many camera-trapping studies and represents an important feature of the observation model that we address explicitly in our application.

Arsia Mons Ripples

NASA Image and Video Library

2012-02-17

This image captured by NASA 2001 Mars Odyssey spacecraft shows a series of low, concentric ridges is located to the west of Arsia Mons. The origin of these features is unknown, and there are no similar features at the other Tharsis volcanoes.

Methodology to develop crash modification functions for road safety treatments with fully specified and hierarchical models.

PubMed

Chen, Yongsheng; Persaud, Bhagwant

2014-09-01

Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components - fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multi-exposure high dynamic range image synthesis with camera shake correction

NASA Astrophysics Data System (ADS)

Li, Xudong; Chen, Yongfu; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Machine vision plays an important part in industrial online inspection. Owing to the nonuniform illuminance conditions and variable working distances, the captured image tends to be over-exposed or under-exposed. As a result, when processing the image such as crack inspection, the algorithm complexity and computing time increase. Multiexposure high dynamic range (HDR) image synthesis is used to improve the quality of the captured image, whose dynamic range is limited. Inevitably, camera shake will result in ghost effect, which blurs the synthesis image to some extent. However, existed exposure fusion algorithms assume that the input images are either perfectly aligned or captured in the same scene. These assumptions limit the application. At present, widely used registration based on Scale Invariant Feature Transform (SIFT) is usually time consuming. In order to rapidly obtain a high quality HDR image without ghost effect, we come up with an efficient Low Dynamic Range (LDR) images capturing approach and propose a registration method based on ORiented Brief (ORB) and histogram equalization which can eliminate the illumination differences between the LDR images. The fusion is performed after alignment. The experiment results demonstrate that the proposed method is robust to illumination changes and local geometric distortion. Comparing with other exposure fusion methods, our method is more efficient and can produce HDR images without ghost effect by registering and fusing four multi-exposure images.

Active fluid mixing with magnetic microactuators for capture of salmonella

NASA Astrophysics Data System (ADS)

Hanasoge, S.; Owen, D.; Ballard, M.; Mills, Z.; Xu, J.; Erickson, M.; Hesketh, P. J.; Alexeev, A.

2016-05-01

Detection of low concentrations of bacteria in food samples is a challenging process. Key to this process is the separation of the target from the food matrix. We demonstrate magnetic beads and magnetic micro-cilia based microfluidic mixing and capture, which are particularly useful for pre-concentrating the target. The first method we demonstrate makes use of magnetic microbeads held on to NiFe discs on the surface of the substrate. These beads are rotated around the magnetic discs by rotating the external magnetic field. The second method we demonstrate shows the use of cilia which extends into the fluid and is manipulated by a rotating external field. Magnetic micro-features were fabricated by evaporating NiFe alloy at room temperature, on to patterned photoresist. The high magnetic permeability of NiFe allows for maximum magnetic force on the features. The magnetic features were actuated using an external rotating magnet up to frequencies of 50Hz. We demonstrate active mixing produced by the microbeads and the cilia in a microchannel. Also, we demonstrate the capture of target species in a sample using microbeads.

Blended particle filters for large-dimensional chaotic dynamical systems

PubMed Central

Majda, Andrew J.; Qi, Di; Sapsis, Themistoklis P.

2014-01-01

A major challenge in contemporary data science is the development of statistically accurate particle filters to capture non-Gaussian features in large-dimensional chaotic dynamical systems. Blended particle filters that capture non-Gaussian features in an adaptively evolving low-dimensional subspace through particles interacting with evolving Gaussian statistics on the remaining portion of phase space are introduced here. These blended particle filters are constructed in this paper through a mathematical formalism involving conditional Gaussian mixtures combined with statistically nonlinear forecast models compatible with this structure developed recently with high skill for uncertainty quantification. Stringent test cases for filtering involving the 40-dimensional Lorenz 96 model with a 5-dimensional adaptive subspace for nonlinear blended filtering in various turbulent regimes with at least nine positive Lyapunov exponents are used here. These cases demonstrate the high skill of the blended particle filter algorithms in capturing both highly non-Gaussian dynamical features as well as crucial nonlinear statistics for accurate filtering in extreme filtering regimes with sparse infrequent high-quality observations. The formalism developed here is also useful for multiscale filtering of turbulent systems and a simple application is sketched below. PMID:24825886

Semantic concept-enriched dependence model for medical information retrieval.

PubMed

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

Evaluation of wavelet spectral features in pathological detection and discrimination of yellow rust and powdery mildew in winter wheat with hyperspectral reflectance data

NASA Astrophysics Data System (ADS)

Shi, Yue; Huang, Wenjiang; Zhou, Xianfeng

2017-04-01

Hyperspectral absorption features are important indicators of characterizing plant biophysical variables for the automatic diagnosis of crop diseases. Continuous wavelet analysis has proven to be an advanced hyperspectral analysis technique for extracting absorption features; however, specific wavelet features (WFs) and their relationship with pathological characteristics induced by different infestations have rarely been summarized. The aim of this research is to determine the most sensitive WFs for identifying specific pathological lesions from yellow rust and powdery mildew in winter wheat, based on 314 hyperspectral samples measured in field experiments in China in 2002, 2003, 2005, and 2012. The resultant WFs could be used as proxies to capture the major spectral absorption features caused by infestation of yellow rust or powdery mildew. Multivariate regression analysis based on these WFs outperformed conventional spectral features in disease detection; meanwhile, a Fisher discrimination model exhibited considerable potential for generating separable clusters for each infestation. Optimal classification returned an overall accuracy of 91.9% with a Kappa of 0.89. This paper also emphasizes the WFs and their relationship with pathological characteristics in order to provide a foundation for the further application of this approach in monitoring winter wheat diseases at the regional scale.

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.

A dimension reduction strategy for improving the efficiency of computer-aided detection for CT colonography

NASA Astrophysics Data System (ADS)

Song, Bowen; Zhang, Guopeng; Wang, Huafeng; Zhu, Wei; Liang, Zhengrong

2013-02-01

Various types of features, e.g., geometric features, texture features, projection features etc., have been introduced for polyp detection and differentiation tasks via computer aided detection and diagnosis (CAD) for computed tomography colonography (CTC). Although these features together cover more information of the data, some of them are statistically highly-related to others, which made the feature set redundant and burdened the computation task of CAD. In this paper, we proposed a new dimension reduction method which combines hierarchical clustering and principal component analysis (PCA) for false positives (FPs) reduction task. First, we group all the features based on their similarity using hierarchical clustering, and then PCA is employed within each group. Different numbers of principal components are selected from each group to form the final feature set. Support vector machine is used to perform the classification. The results show that when three principal components were chosen from each group we can achieve an area under the curve of receiver operating characteristics of 0.905, which is as high as the original dataset. Meanwhile, the computation time is reduced by 70% and the feature set size is reduce by 77%. It can be concluded that the proposed method captures the most important information of the feature set and the classification accuracy is not affected after the dimension reduction. The result is promising and further investigation, such as automatically threshold setting, are worthwhile and are under progress.

Imaging of gout: an overview.

PubMed

Dalbeth, Nicola; Doyle, Anthony J

2012-12-01

The diverse clinical states and sites of pathology in gout provide challenges when considering the features apparent on imaging. Ideally, an imaging modality should capture all aspects of disease including monosodium urate crystal deposition, acute inflammation, tophus, tissue remodelling and complications of disease. The modalities used in gout include conventional radiography, ultrasonography, magnetic resonance imaging, computed tomography and dual-energy computed tomography. This review discusses the role of each of these imaging modalities in gout, focussing on the imaging characteristics, role in gout diagnosis and role for disease monitoring. Ultrasonography and dual-energy computed tomography are particularly promising methods for both non-invasive diagnosis and monitoring of disease. The observation that ultrasonographic appearances of monosodium urate crystal deposition can be observed in patients with hyperuricaemia but no other clinical features of gout raises important questions about disease definitions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Neutron cross section measurements at n-TOF for ADS related studies

NASA Astrophysics Data System (ADS)

Mastinu, P. F.; Abbondanno, U.; Aerts, G.; Álvarez, H.; Alvarez-Velarde, F.; Andriamonje, S.; Andrzejewski, J.; Assimakopoulos, P.; Audouin, L.; Badurek, G.; Bustreo, N.; aumann, P.; vá, F. Be; Berthoumieux, E.; Calviño, F.; Cano-Ott, D.; Capote, R.; Carrillo de Albornoz, A.; Cennini, P.; Chepel, V.; Chiaveri, E.; Colonna, N.; Cortes, G.; Couture, A.; Cox, J.; Dahlfors, M.; David, S.; Dillmann, I.; Dolfini, R.; Domingo-Pardo, C.; Dridi, W.; Duran, I.; Eleftheriadis, C.; Embid-Segura, M.; Ferrant, L.; Ferrari, A.; Ferreira-Marques, R.; itzpatrick, L.; Frais-Kölbl, H.; Fujii, K.; Furman, W.; Guerrero, C.; Goncalves, I.; Gallino, R.; Gonzalez-Romero, E.; Goverdovski, A.; Gramegna, F.; Griesmayer, E.; Gunsing, F.; Haas, B.; Haight, R.; Heil, M.; Herrera-Martinez, A.; Igashira, M.; Isaev, S.; Jericha, E.; Kadi, Y.; Käppeler, F.; Karamanis, D.; Karadimos, D.; Kerveno, M.; Ketlerov, V.; Koehler, P.; Konovalov, V.; Kossionides, E.; Krti ka, M.; Lamboudis, C.; Leeb, H.; Lindote, A.; Lopes, I.; Lozano, M.; Lukic, S.; Marganiec, J.; Marques, L.; Marrone, S.; Massimi, C.; Mengoni, A.; Milazzo, P. M.; Moreau, C.; Mosconi, M.; Neves, F.; Oberhummer, H.; O'Brien, S.; Oshima, M.; Pancin, J.; Papachristodoulou, C.; Papadopoulos, C.; Paradela, C.; Patronis, N.; Pavlik, A.; Pavlopoulos, P.; Perrot, L.; Plag, R.; Plompen, A.; Plukis, A.; Poch, A.; Pretel, C.; Quesada, J.; Rauscher, T.; Reifarth, R.; Rosetti, M.; Rubbia, C.; Rudolf, G.; Rullhusen, P.; Salgado, J.; Sarchiapone, L.; Savvidis, I.; Stephan, C.; Tagliente, G.; Tain, J. L.; Tassan-Got, L.; Tavora, L.; Terlizzi, R.; Vannini, G.; Vaz, P.; Ventura, A.; Villamarin, D.; Vincente, M. C.; Vlachoudis, V.; Vlastou, R.; Voss, F.; Walter, S.; Wendler, H.; Wiescherand, M.; Wisshak, K.

2006-05-01

A neutron Time-of-Flight facility (n_TOF) is available at CERN since 2001. The innovative features of the neutron beam, in particular the high instantaneous flux, the wide energy range, the high resolution and the low background, make this facility unique for measurements of neutron induced reactions relevant to the field of Emerging Nuclear Technologies, as well as to Nuclear Astrophysics and Fundamental Nuclear Physics. The scientific motivations that have led to the construction of this new facility are here presented. The main characteristics of the n_TOF neutron beam are described, together with the features of the experimental apparata used for cross-section measurements. The main results of the first measurement campaigns are presented. Preliminary results of capture cross-section measurements of minor actinides, important to ADS project for nuclear waste transmutation, are finally discussed.

Using Conversation Topics for Predicting Therapy Outcomes in Schizophrenia

PubMed Central

Howes, Christine; Purver, Matthew; McCabe, Rose

2013-01-01

Previous research shows that aspects of doctor-patient communication in therapy can predict patient symptoms, satisfaction and future adherence to treatment (a significant problem with conditions such as schizophrenia). However, automatic prediction has so far shown success only when based on low-level lexical features, and it is unclear how well these can generalize to new data, or whether their effectiveness is due to their capturing aspects of style, structure or content. Here, we examine the use of topic as a higher-level measure of content, more likely to generalize and to have more explanatory power. Investigations show that while topics predict some important factors such as patient satisfaction and ratings of therapy quality, they lack the full predictive power of lower-level features. For some factors, unsupervised methods produce models comparable to manual annotation. PMID:23943658

Real-time marker-free motion capture system using blob feature analysis

NASA Astrophysics Data System (ADS)

Park, Chang-Joon; Kim, Sung-Eun; Kim, Hong-Seok; Lee, In-Ho

2005-02-01

This paper presents a real-time marker-free motion capture system which can reconstruct 3-dimensional human motions. The virtual character of the proposed system mimics the motion of an actor in real-time. The proposed system captures human motions by using three synchronized CCD cameras and detects the root and end-effectors of an actor such as a head, hands, and feet by exploiting the blob feature analysis. And then, the 3-dimensional positions of end-effectors are restored and tracked by using Kalman filter. At last, the positions of the intermediate joint are reconstructed by using anatomically constrained inverse kinematics algorithm. The proposed system was implemented under general lighting conditions and we confirmed that the proposed system could reconstruct motions of a lot of people wearing various clothes in real-time stably.

3D reconstruction based on light field images

NASA Astrophysics Data System (ADS)

Zhu, Dong; Wu, Chunhong; Liu, Yunluo; Fu, Dongmei

2018-04-01

This paper proposed a method of reconstructing three-dimensional (3D) scene from two light field images capture by Lytro illium. The work was carried out by first extracting the sub-aperture images from light field images and using the scale-invariant feature transform (SIFT) for feature registration on the selected sub-aperture images. Structure from motion (SFM) algorithm is further used on the registration completed sub-aperture images to reconstruct the three-dimensional scene. 3D sparse point cloud was obtained in the end. The method shows that the 3D reconstruction can be implemented by only two light field camera captures, rather than at least a dozen times captures by traditional cameras. This can effectively solve the time-consuming, laborious issues for 3D reconstruction based on traditional digital cameras, to achieve a more rapid, convenient and accurate reconstruction.

Movement mysteries unveiled: spatial ecology of juvenile green sea turtles

USGS Publications Warehouse

Shaver, Donna J.; Hart, Kristen M.; Fujisaki, Ikuko; Rubio, Cynthia; Sartain-Iverson, Autumn R.; Lutterschmidt, William I.

2013-01-01

Locations of important foraging areas are not well defined for many marine species. Unraveling these mysteries is vital to develop conservation strategies for these species, many of which are threatened or endangered. Satellite-tracking is a tool that can reveal movement patterns at both broad and fine spatial scales, in all marine environments. This chapter presents records of the longest duration track of an individual juvenile green turtle (434 days) and highest number of tracking days in any juvenile green turtle study (5483 tracking days) published to date. In this chapter, we use spatial modeling techniques to describe movements and identify foraging areas for juvenile green turtles (Chelonia mydas) captured in a developmental habitat in south Texas, USA. Some green turtles established residency in the vicinity of their capture and release site, but most used a specific habitat feature (i.e., a jettied pass) to travel between the Gulf of Mexico and a nearby bay. Still others moved southward within the Gulf of Mexico into Mexican coastal waters, likely in response to decreasing water temperatures. These movements to waters off the coast of Mexico highlight the importance of international cooperation in restoration efforts undertaken on behalf of this imperiled species.

A holographic model for the fractional quantum Hall effect

NASA Astrophysics Data System (ADS)

Lippert, Matthew; Meyer, René; Taliotis, Anastasios

2015-01-01

Experimental data for fractional quantum Hall systems can to a large extent be explained by assuming the existence of a Γ0(2) modular symmetry group commuting with the renormalization group flow and hence mapping different phases of two-dimensional electron gases into each other. Based on this insight, we construct a phenomenological holographic model which captures many features of the fractional quantum Hall effect. Using an -invariant Einstein-Maxwell-axio-dilaton theory capturing the important modular transformation properties of quantum Hall physics, we find dyonic diatonic black hole solutions which are gapped and have a Hall conductivity equal to the filling fraction, as expected for quantum Hall states. We also provide several technical results on the general behavior of the gauge field fluctuations around these dyonic dilatonic black hole solutions: we specify a sufficient criterion for IR normalizability of the fluctuations, demonstrate the preservation of the gap under the action, and prove that the singularity of the fluctuation problem in the presence of a magnetic field is an accessory singularity. We finish with a preliminary investigation of the possible IR scaling solutions of our model and some speculations on how they could be important for the observed universality of quantum Hall transitions.

Nutrition warnings as front-of-pack labels: influence of design features on healthfulness perception and attentional capture.

PubMed

Cabrera, Manuel; Machín, Leandro; Arrúa, Alejandra; Antúnez, Lucía; Curutchet, María Rosa; Giménez, Ana; Ares, Gastón

2017-12-01

Warnings are a new directive front-of-pack (FOP) nutrition labelling scheme that highlights products with high content of key nutrients. The design of warnings influences their ability to catch consumers' attention and to clearly communicate their intended meaning, which are key determinants of their effectiveness. The aim of the present work was to evaluate the influence of design features of warnings as a FOP nutrition labelling scheme on perceived healthfulness and attentional capture. Five studies with a total of 496 people were carried out. In the first study, the association of colour and perceived healthfulness was evaluated in an online survey in which participants had to rate their perceived healthfulness of eight colours. In the second study, the influence of colour, shape and textual information on perceived healthfulness was evaluated using choice-conjoint analysis. The third study focused on implicit associations between two design features (shape and colour) on perceived healthfulness. The fourth and fifth studies used visual search to evaluate the influence of colour, size and position of the warnings on attentional capture. Perceived healthfulness was significantly influenced by shape, colour and textual information. Colour was the variable with the largest contribution to perceived healthfulness. Colour, size and position of the warnings on the labels affected attentional capture. Results from the experiments provide recommendations for the design of warnings to identify products with unfavourable nutrient profile.

Image-based non-contact monitoring of skin texture changed by piloerection for emotion estimation

NASA Astrophysics Data System (ADS)

Uchida, Mihiro; Akaho, Rina; Ogawa, Keiko; Tsumura, Norimichi

2018-02-01

In this paper, we find the effective feature values of skin textures captured by non-contact camera to monitor piloerection on the skin for emotion estimation. Recently, emotion estimation is required for service robots to interact with human more naturally. There are a lot of researches of estimating emotion and additional methods are required to improve emotion estimation because using only a few methods may not give enough information for emotion estimation. In the previous study, it is necessary to fix a device on the subject's arm for detecting piloerection, but the contact monitoring can be stress itself and distract the subject from concentrating in the stimuli and evoking strong emotion. So, we focused on the piloerection as the object obtained with non-contact methods. The piloerection is observed as goose bumps on the skin when the subject is emotionally moved, scared and so on. This phenomenon is caused by contraction of arrector pili muscles with the activation of sympathetic nervous system. This piloerection changes skin texture. Skin texture is important in the cosmetic industry to evaluate skin condition. Therefore, we thought that it will be effective to evaluate the condition of skin texture for emotion estimation. The evaluations were performed by extracting the effective feature values from skin textures captured with a high resolution camera. The effective feature values should have high correlation with the degree of piloerection. In this paper, we found that standard deviation of short-line inclination angles in the texture is well correlated with the degree of piloerection.

Detailed seafloor habitat mapping to enhance marine-resource management

USGS Publications Warehouse

Zawada, David G.; Hart, Kristen M.

2010-01-01

Pictures of the seafloor capture important information about the sediments, exposed geologic features, submerged aquatic vegetation, and animals found in a given habitat. With the emergence of marine protected areas (MPAs) as a favored tactic for preserving coral reef resources, knowledge of essential habitat components is paramount to designing effective management strategies. Surprisingly, detailed information on seafloor habitat components is not available in many areas that are being considered for MPA designation or that are already designated as MPAs. A task of the U.S. Geological Survey Coral Reef Ecosystem STudies (USGS CREST) project is addressing this issue.

Simple dynamical models capturing the key features of the Central Pacific El Niño.

PubMed

Chen, Nan; Majda, Andrew J

2016-10-18

The Central Pacific El Niño (CP El Niño) has been frequently observed in recent decades. The phenomenon is characterized by an anomalous warm sea surface temperature (SST) confined to the central Pacific and has different teleconnections from the traditional El Niño. Here, simple models are developed and shown to capture the key mechanisms of the CP El Niño. The starting model involves coupled atmosphere-ocean processes that are deterministic, linear, and stable. Then, systematic strategies are developed for incorporating several major mechanisms of the CP El Niño into the coupled system. First, simple nonlinear zonal advection with no ad hoc parameterization of the background SST gradient is introduced that creates coupled nonlinear advective modes of the SST. Secondly, due to the recent multidecadal strengthening of the easterly trade wind, a stochastic parameterization of the wind bursts including a mean easterly trade wind anomaly is coupled to the simple atmosphere-ocean processes. Effective stochastic noise in the wind burst model facilitates the intermittent occurrence of the CP El Niño with realistic amplitude and duration. In addition to the anomalous warm SST in the central Pacific, other major features of the CP El Niño such as the rising branch of the anomalous Walker circulation being shifted to the central Pacific and the eastern Pacific cooling with a shallow thermocline are all captured by this simple coupled model. Importantly, the coupled model succeeds in simulating a series of CP El Niño that lasts for 5 y, which resembles the two CP El Niño episodes during 1990-1995 and 2002-2006.

Effect of the electric field ratio on electroosmotic flow patterns in cross-shaped microchannels by the lattice-Boltzmann Method

NASA Astrophysics Data System (ADS)

Socias, Alvaro; Oyarzun, Diego; Guzman, Amador

2014-11-01

The electroosmotic flow (EOF) pattern characteristics in cross-shaped microchannels flow are important features when either suppressing or enhancing flow features for injection and separation or mixing of multiple species are the wanted objectives. There are situations in EOF in cross-shaped microchannels where the fluid flows toward unexpected and unwanted directions under a given external electric field that depends of both the applied electric field and lengths of the different channels. This article describes the effect of the electric field ratio, defined as the ratio between longitudinal nominal electric field ELong = (VE-VW) /(LW + LE) and the nominal electric field E a = (VS-VE) /(VS + VE) , where E, S and W define the east, south and west directions of the cross-shaped microchannel; V is the externally applied voltage and L is the length, on the EOF characteristics in a cross-shaped microchannel. We use the lattice-Boltzmann method (LBM) for solving the discretized Boltzmann Transport Equation (BTE) describing the coupled processes of hydrodynamics and electrodynamic. Our numerical simulations allow us to determine the EOF pattern for a wide range of the electric field ratio and Ea such that inverted flow features are captured and described, which are very important to determine for flow separation or mixing.

NATIONAL PREPAREDNESS: Technologies to Secure Federal Buildings

DTIC Science & Technology

2002-04-25

Medium, some resistance based on sensitivity of eye Facial recognition Facial features are captured and compared Dependent on lighting, positioning...two primary types of facial recognition technology used to create templates: 1. Local feature analysis—Dozens of images from regions of the face are...an adjacent feature. Attachment I—Access Control Technologies: Biometrics Facial Recognition How the technology works

Student Perceptions of Online Tutoring Videos

ERIC Educational Resources Information Center

Sligar, Steven R.; Pelletier, Christopher D.; Bonner, Heidi Stone; Coghill, Elizabeth; Guberman, Daniel; Zeng, Xiaoming; Newman, Joyce J.; Muller, Dorothy; Dennis, Allen

2017-01-01

Online tutoring is made possible by using videos to replace or supplement face to face services. The purpose of this research was to examine student reactions to the use of lecture capture technology in a university tutoring setting and to assess student knowledge of some features of Tegrity lecture capture software. A survey was administered to…

Informative Feature Selection for Object Recognition via Sparse PCA

DTIC Science & Technology

2011-04-07

constraint on images collected from low-power camera net- works instead of high-end photography is that establishing wide-baseline feature correspondence of...variable selection tool for selecting informative features in the object images captured from low-resolution cam- era sensor networks. Firstly, we...More examples can be found in Figure 4 later. 3. Identifying Informative Features Classical PCA is a well established tool for the analysis of high

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

An investigation to improve the Menhaden fishery prediction and detection model through the application of ERTS-A data

NASA Technical Reports Server (NTRS)

Maughan, P. M. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Preliminary analyses indicate that several important relationships have been observed utilizing ERTS-1 imagery. Of most significance is that in the Mississippi Sound, as elsewhere, considerable detail exists as to turbidity patterns in the water column. Simple analysis is complicated by the apparent interaction between actual turbidity, turbidity induced by shoal water, and actual imaging of the bottom in extreme shoal water. A statistical approach is being explored which shows promise of at least partially separating these effects so that partitioning of true turbid plumes can be accomplished. This partitioning is of great importance to this program in that supportive data seem to indicate that menhaden occur more frequently in turbid areas. In this connection four individual captures have been associated with a major turbid feature imaged on 6 August. If a significant relationship between imaged turbid features and catch distribution can be established, for example by graphic and/or numeric analysis, it will represent a major advancement for short term prediction of commercially accessible menhaden.

Shapes, scents and sounds: quantifying the full multi-sensory basis of conceptual knowledge.

PubMed

Hoffman, Paul; Lambon Ralph, Matthew A

2013-01-01

Contemporary neuroscience theories assume that concepts are formed through experience in multiple sensory-motor modalities. Quantifying the contribution of each modality to different object categories is critical to understanding the structure of the conceptual system and to explaining category-specific knowledge deficits. Verbal feature listing is typically used to elicit this information but has a number of drawbacks: sensory knowledge often cannot easily be translated into verbal features and many features are experienced in multiple modalities. Here, we employed a more direct approach in which subjects rated their knowledge of objects in each sensory-motor modality separately. Compared with these ratings, feature listing over-estimated the importance of visual form and functional knowledge and under-estimated the contributions of other sensory channels. An item's sensory rating proved to be a better predictor of lexical-semantic processing speed than the number of features it possessed, suggesting that ratings better capture the overall quantity of sensory information associated with a concept. Finally, the richer, multi-modal rating data not only replicated the sensory-functional distinction between animals and non-living things but also revealed novel distinctions between different types of artefact. Hierarchical cluster analyses indicated that mechanical devices (e.g., vehicles) were distinct from other non-living objects because they had strong sound and motion characteristics, making them more similar to animals in this respect. Taken together, the ratings align with neuroscience evidence in suggesting that a number of distinct sensory processing channels make important contributions to object knowledge. Multi-modal ratings for 160 objects are provided as supplementary materials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Compact and controlled microfluidic mixing and biological particle capture

NASA Astrophysics Data System (ADS)

Ballard, Matthew; Owen, Drew; Mills, Zachary Grant; Hesketh, Peter J.; Alexeev, Alexander

2016-11-01

We use three-dimensional simulations and experiments to develop a multifunctional microfluidic device that performs rapid and controllable microfluidic mixing and specific particle capture. Our device uses a compact microfluidic channel decorated with magnetic features. A rotating magnetic field precisely controls individual magnetic microbeads orbiting around the features, enabling effective continuous-flow mixing of fluid streams over a compact mixing region. We use computer simulations to elucidate the underlying physical mechanisms that lead to effective mixing and compare them with experimental mixing results. We study the effect of various system parameters on microfluidic mixing to design an efficient micromixer. We also experimentally and numerically demonstrate that orbiting microbeads can effectively capture particles transported by the fluid, which has major implications in pre-concentration and detection of biological particles including various cells and bacteria, with applications in areas such as point-of-care diagnostics, biohazard detection, and food safety. Support from NSF and USDA is gratefully acknowledged.

Can an auditory multi-feature optimal paradigm be used for the study of processes associated with attention capture in passive listeners?

PubMed

Tavakoli, Paniz; Campbell, Kenneth

2016-10-01

A rarely occurring and highly relevant auditory stimulus occurring outside of the current focus of attention can cause a switching of attention. Such attention capture is often studied in oddball paradigms consisting of a frequently occurring "standard" stimulus which is changed at odd times to form a "deviant". The deviant may result in the capturing of attention. An auditory ERP, the P3a, is often associated with this process. To collect a sufficient amount of data is however very time-consuming. A more multi-feature "optimal" paradigm has been proposed but it is not known if it is appropriate for the study of attention capture. An optimal paradigm was run in which 6 different rare deviants (p=.08) were separated by a standard stimulus (p=.50) and compared to results when 4 oddball paradigms were also run. A large P3a was elicited by some of the deviants in the optimal paradigm but not by others. However, very similar results were observed when separate oddball paradigms were run. The present study indicates that the optimal paradigm provides a very time-saving method to study attention capture and the P3a. Copyright © 2016 Elsevier B.V. All rights reserved.

Median Robust Extended Local Binary Pattern for Texture Classification.

PubMed

Liu, Li; Lao, Songyang; Fieguth, Paul W; Guo, Yulan; Wang, Xiaogang; Pietikäinen, Matti

2016-03-01

Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image noise and is unable to capture macrostructure information. To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Different from the traditional LBP and many LBP variants, MRELBP compares regional image medians rather than raw image intensities. A multiscale LBP type descriptor is computed by efficiently comparing image medians over a novel sampling scheme, which can capture both microstructure and macrostructure texture information. A comprehensive evaluation on benchmark data sets reveals MRELBP's high performance-robust to gray scale variations, rotation changes and noise-but at a low computational cost. MRELBP produces the best classification scores of 99.82%, 99.38%, and 99.77% on three popular Outex test suites. More importantly, MRELBP is shown to be highly robust to image noise, including Gaussian noise, Gaussian blur, salt-and-pepper noise, and random pixel corruption.

A dictionary of behavioral motifs reveals clusters of genes affecting Caenorhabditis elegans locomotion.

PubMed

Brown, André E X; Yemini, Eviatar I; Grundy, Laura J; Jucikas, Tadas; Schafer, William R

2013-01-08

Visible phenotypes based on locomotion and posture have played a critical role in understanding the molecular basis of behavior and development in Caenorhabditis elegans and other model organisms. However, it is not known whether these human-defined features capture the most important aspects of behavior for phenotypic comparison or whether they are sufficient to discover new behaviors. Here we show that four basic shapes, or eigenworms, previously described for wild-type worms, also capture mutant shapes, and that this representation can be used to build a dictionary of repetitive behavioral motifs in an unbiased way. By measuring the distance between each individual's behavior and the elements in the motif dictionary, we create a fingerprint that can be used to compare mutants to wild type and to each other. This analysis has revealed phenotypes not previously detected by real-time observation and has allowed clustering of mutants into related groups. Behavioral motifs provide a compact and intuitive representation of behavioral phenotypes.

The effect of capturing the correct turbulence dissipation rate in BHR

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

Schwarzkopf, John Dennis; Ristorcelli, Raymond

In this manuscript, we discuss the shortcoming of a quasi-equilibrium assumption made in the BHR closure model. Turbulence closure models generally assume fully developed turbulence, which is not applicable to 1) non-equilibrium turbulence (e.g. change in mean pressure gradient) or 2) laminar-turbulence transition flows. Based on DNS data, we show that the current BHR dissipation equation [modeled based on the fully developed turbulence phenomenology] does not capture important features of nonequilibrium flows. To demonstrate our thesis, we use the BHR equations to predict a non-equilibrium flow both with the BHR dissipation and the dissipation from DNS. We find that themore » prediction can be substantially improved, both qualitatively and quantitatively, with the correct dissipation rate. We conclude that a new set of nonequilibrium phenomenological assumptions must be used to develop a new model equation for the dissipation to accurately predict the turbulence time scale used by other models.« less

Non-linear corrections to the time-covariance function derived from a multi-state chemical master equation.

PubMed

Scott, M

2012-08-01

The time-covariance function captures the dynamics of biochemical fluctuations and contains important information about the underlying kinetic rate parameters. Intrinsic fluctuations in biochemical reaction networks are typically modelled using a master equation formalism. In general, the equation cannot be solved exactly and approximation methods are required. For small fluctuations close to equilibrium, a linearisation of the dynamics provides a very good description of the relaxation of the time-covariance function. As the number of molecules in the system decrease, deviations from the linear theory appear. Carrying out a systematic perturbation expansion of the master equation to capture these effects results in formidable algebra; however, symbolic mathematics packages considerably expedite the computation. The authors demonstrate that non-linear effects can reveal features of the underlying dynamics, such as reaction stoichiometry, not available in linearised theory. Furthermore, in models that exhibit noise-induced oscillations, non-linear corrections result in a shift in the base frequency along with the appearance of a secondary harmonic.

Race, Socioeconomic Status and Health: Complexities, Ongoing Challenges and Research Opportunities

PubMed Central

Williams, David R.; Mohammed, Selina A.; Leavell, Jacinta; Collins, Chiquita

2012-01-01

This paper provides an overview of racial variations in health and shows that differences in socioeconomic status (SES) across racial groups are a major contributor to racial disparities in health. However, race reflects multiple dimensions of social inequality and individual and household indicators of SES capture relevant but limited aspects of this phenomenon. Research is needed that will comprehensively characterize the critical pathogenic features of social environments and identify how they combine with each other to affect health over the life course. Migration history and status are also important predictors of health and research is needed that will enhance understanding of the complex ways in which race, SES, and immigrant status combine to affect health. Fully capturing the role of race in health also requires rigorous examination of the conditions under which medical care and genetic factors can contribute to racial and SES differences in health. The paper identifies research priorities in all of these areas. PMID:20201869

A new method for sperm characterization for infertility treatment: hypothesis testing by using combination of watershed segmentation and graph theory.

PubMed

Shojaedini, Seyed Vahab; Heydari, Masoud

2014-10-01

Shape and movement features of sperms are important parameters for infertility study and treatment. In this article, a new method is introduced for characterization sperms in microscopic videos. In this method, first a hypothesis framework is defined to distinguish sperms from other particles in captured video. Then decision about each hypothesis is done in following steps: Selecting some primary regions as candidates for sperms by watershed-based segmentation, pruning of some false candidates during successive frames using graph theory concept and finally confirming correct sperms by using their movement trajectories. Performance of the proposed method is evaluated on real captured images belongs to semen with high density of sperms. The obtained results show the proposed method may detect 97% of sperms in presence of 5% false detections and track 91% of moving sperms. Furthermore, it can be shown that better characterization of sperms in proposed algorithm doesn't lead to extracting more false sperms compared to some present approaches.

Design principles of nuclear receptor signaling: how complex networking improves signal transduction

PubMed Central

Kolodkin, Alexey N; Bruggeman, Frank J; Plant, Nick; Moné, Martijn J; Bakker, Barbara M; Campbell, Moray J; van Leeuwen, Johannes P T M; Carlberg, Carsten; Snoep, Jacky L; Westerhoff, Hans V

2010-01-01

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of ‘design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic ‘nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. PMID:21179018

Development and initial evaluation of an enhanced measure of boundary flexibility for the work and family domains.

PubMed

Matthews, Russell A; Barnes-Farrell, Janet L

2010-07-01

This manuscript reports the development of a measure of work and family domain boundary flexibility. Building on previous research, we propose an expanded definition of boundary flexibility that includes two components-flexibility-ability and flexibility-willingness-and we develop a measure designed to capture this more comprehensive definition of boundary flexibility. Flexibility-ability is conceptualized as an individual's perception of personal and situational constraints that affect boundary management, and flexibility-willingness is conceptualized as an individual difference variable that captures the motivation to engage in boundary flexing. An additional feature of domain boundaries, permeability, is also examined. Data are presented from two studies. Study 1 (N = 244) describes the development of a multiscale measure that extends current conceptual definitions of boundary flexibility. Study 2 (N = 225) describes the refinement and evaluation of this measure. Confirmatory factor analysis, reliability evidence, interscale correlations, and correlations with important work-family constructs (e.g., domain centrality, work-family conflict) provide initial construct validity evidence for the measure.

Experimental study of hydraulics and sediment capture efficiency in catchbasins.

PubMed

Tang, Yangbo; Zhu, David Z; Rajaratnam, N; van Duin, Bert

2016-12-01

Catchbasins (also known as gully pot in the UK and Australia) are used to receive surface runoff and drain the stormwater into storm sewers. The recent interest in catchbasins is to improve their effectiveness in removing sediments in stormwater. An experimental study was conducted to examine the hydraulic features and sediment capture efficiency in catchbasins, with and without a bottom sump. A sump basin is found to increase the sediment capture efficiency significantly. The effect of inlet control devices, which are commonly used to control the amount of flow into the downstream storm sewer system, is also studied. These devices will increase the water depth in the catchbasin and increase the sediment capture efficiency. Equations are developed for predicting the sediment capture efficiency in catchbasins.

A Clustering Graph Generator

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

Winlaw, Manda; De Sterck, Hans; Sanders, Geoffrey

In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps tomore » understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.« less

Value-driven attentional capture in the auditory domain.

PubMed

Anderson, Brian A

2016-01-01

It is now well established that the visual attention system is shaped by reward learning. When visual features are associated with a reward outcome, they acquire high priority and can automatically capture visual attention. To date, evidence for value-driven attentional capture has been limited entirely to the visual system. In the present study, I demonstrate that previously reward-associated sounds also capture attention, interfering more strongly with the performance of a visual task. This finding suggests that value-driven attention reflects a broad principle of information processing that can be extended to other sensory modalities and that value-driven attention can bias cross-modal stimulus competition.

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.

Pathological speech signal analysis and classification using empirical mode decomposition.

PubMed

Kaleem, Muhammad; Ghoraani, Behnaz; Guergachi, Aziz; Krishnan, Sridhar

2013-07-01

Automated classification of normal and pathological speech signals can provide an objective and accurate mechanism for pathological speech diagnosis, and is an active area of research. A large part of this research is based on analysis of acoustic measures extracted from sustained vowels. However, sustained vowels do not reflect real-world attributes of voice as effectively as continuous speech, which can take into account important attributes of speech such as rapid voice onset and termination, changes in voice frequency and amplitude, and sudden discontinuities in speech. This paper presents a methodology based on empirical mode decomposition (EMD) for classification of continuous normal and pathological speech signals obtained from a well-known database. EMD is used to decompose randomly chosen portions of speech signals into intrinsic mode functions, which are then analyzed to extract meaningful temporal and spectral features, including true instantaneous features which can capture discriminative information in signals hidden at local time-scales. A total of six features are extracted, and a linear classifier is used with the feature vector to classify continuous speech portions obtained from a database consisting of 51 normal and 161 pathological speakers. A classification accuracy of 95.7 % is obtained, thus demonstrating the effectiveness of the methodology.

Image processing and machine learning in the morphological analysis of blood cells.

PubMed

Rodellar, J; Alférez, S; Acevedo, A; Molina, A; Merino, A

2018-05-01

This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears. The basics of the 3 core elements (segmentation, quantitative features, and classification) are outlined, and recent literature is discussed. Although red blood cells are a significant part of this context, this study focuses on malignant lymphoid cells and blast cells. There is no doubt that these technologies may help the cytologist to perform efficient, objective, and fast morphological analysis of blood cells. They may also help in the interpretation of some morphological features and may serve as learning and survey tools. Although research is still needed, it is important to define screening strategies to exploit the potential of image-based automatic recognition systems integrated in the daily routine of laboratories along with other analysis methodologies. © 2018 John Wiley & Sons Ltd.

New approaches to investigating social gestures in autism spectrum disorder

PubMed Central

2012-01-01

The combination of economic games and human neuroimaging presents the possibility of using economic probes to identify biomarkers for quantitative features of healthy and diseased cognition. These probes span a range of important cognitive functions, but one new use is in the domain of reciprocating social exchange with other humans - a capacity perturbed in a number of psychopathologies. We summarize the use of a reciprocating exchange game to elicit neural and behavioral signatures for subjects diagnosed with autism spectrum disorder (ASD). Furthermore, we outline early efforts to capture features of social exchange in computational models and use these to identify quantitative behavioral differences between subjects with ASD and matched controls. Lastly, we summarize a number of subsequent studies inspired by the modeling results, which suggest new neural and behavioral signatures that could be used to characterize subtle deficits in information processing during interactions with other humans. PMID:22958572

Modelling temporal networks of human face-to-face contacts with public activity and individual reachability

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qing; Cui, Jing; Zhang, Shu-Min; Zhang, Qi; Li, Xiang

2016-02-01

Modelling temporal networks of human face-to-face contacts is vital both for understanding the spread of airborne pathogens and word-of-mouth spreading of information. Although many efforts have been devoted to model these temporal networks, there are still two important social features, public activity and individual reachability, have been ignored in these models. Here we present a simple model that captures these two features and other typical properties of empirical face-to-face contact networks. The model describes agents which are characterized by an attractiveness to slow down the motion of nearby people, have event-triggered active probability and perform an activity-dependent biased random walk in a square box with periodic boundary. The model quantitatively reproduces two empirical temporal networks of human face-to-face contacts which are testified by their network properties and the epidemic spread dynamics on them.

Imaging Techniques for Dense 3D reconstruction of Swimming Aquatic Life using Multi-view Stereo

NASA Astrophysics Data System (ADS)

Daily, David; Kiser, Jillian; McQueen, Sarah

2016-11-01

Understanding the movement characteristics of how various species of fish swim is an important step to uncovering how they propel themselves through the water. Previous methods have focused on profile capture methods or sparse 3D manual feature point tracking. This research uses an array of 30 cameras to automatically track hundreds of points on a fish as they swim in 3D using multi-view stereo. Blacktip sharks, sting rays, puffer fish, turtles and more were imaged in collaboration with the National Aquarium in Baltimore, Maryland using the multi-view stereo technique. The processes for data collection, camera synchronization, feature point extraction, 3D reconstruction, 3D alignment, biological considerations, and lessons learned will be presented. Preliminary results of the 3D reconstructions will be shown and future research into mathematically characterizing various bio-locomotive maneuvers will be discussed.

Optimal Design of Experiments by Combining Coarse and Fine Measurements

NASA Astrophysics Data System (ADS)

Lee, Alpha A.; Brenner, Michael P.; Colwell, Lucy J.

2017-11-01

In many contexts, it is extremely costly to perform enough high-quality experimental measurements to accurately parametrize a predictive quantitative model. However, it is often much easier to carry out large numbers of experiments that indicate whether each sample is above or below a given threshold. Can many such categorical or "coarse" measurements be combined with a much smaller number of high-resolution or "fine" measurements to yield accurate models? Here, we demonstrate an intuitive strategy, inspired by statistical physics, wherein the coarse measurements are used to identify the salient features of the data, while the fine measurements determine the relative importance of these features. A linear model is inferred from the fine measurements, augmented by a quadratic term that captures the correlation structure of the coarse data. We illustrate our strategy by considering the problems of predicting the antimalarial potency and aqueous solubility of small organic molecules from their 2D molecular structure.

On the importance of cotranscriptional RNA structure formation

PubMed Central

Lai, Daniel; Proctor, Jeff R.; Meyer, Irmtraud M.

2013-01-01

The expression of genes, both coding and noncoding, can be significantly influenced by RNA structural features of their corresponding transcripts. There is by now mounting experimental and some theoretical evidence that structure formation in vivo starts during transcription and that this cotranscriptional folding determines the functional RNA structural features that are being formed. Several decades of research in bioinformatics have resulted in a wide range of computational methods for predicting RNA secondary structures. Almost all state-of-the-art methods in terms of prediction accuracy, however, completely ignore the process of structure formation and focus exclusively on the final RNA structure. This review hopes to bridge this gap. We summarize the existing evidence for cotranscriptional folding and then review the different, currently used strategies for RNA secondary-structure prediction. Finally, we propose a range of ideas on how state-of-the-art methods could be potentially improved by explicitly capturing the process of cotranscriptional structure formation. PMID:24131802

Human Body Parts Tracking and Kinematic Features Assessment Based on RSSI and Inertial Sensor Measurements

PubMed Central

Blumrosen, Gaddi; Luttwak, Ami

2013-01-01

Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts' displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs. PMID:23979481

Human body parts tracking and kinematic features assessment based on RSSI and inertial sensor measurements.

PubMed

Blumrosen, Gaddi; Luttwak, Ami

2013-08-23

Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts' displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs.

Free-Form Region Description with Second-Order Pooling.

PubMed

Carreira, João; Caseiro, Rui; Batista, Jorge; Sminchisescu, Cristian

2015-06-01

Semantic segmentation and object detection are nowadays dominated by methods operating on regions obtained as a result of a bottom-up grouping process (segmentation) but use feature extractors developed for recognition on fixed-form (e.g. rectangular) patches, with full images as a special case. This is most likely suboptimal. In this paper we focus on feature extraction and description over free-form regions and study the relationship with their fixed-form counterparts. Our main contributions are novel pooling techniques that capture the second-order statistics of local descriptors inside such free-form regions. We introduce second-order generalizations of average and max-pooling that together with appropriate non-linearities, derived from the mathematical structure of their embedding space, lead to state-of-the-art recognition performance in semantic segmentation experiments without any type of local feature coding. In contrast, we show that codebook-based local feature coding is more important when feature extraction is constrained to operate over regions that include both foreground and large portions of the background, as typical in image classification settings, whereas for high-accuracy localization setups, second-order pooling over free-form regions produces results superior to those of the winning systems in the contemporary semantic segmentation challenges, with models that are much faster in both training and testing.

A METHODOLOGY FOR INTEGRATING IMAGES AND TEXT FOR OBJECT IDENTIFICATION

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

Paulson, Patrick R.; Hohimer, Ryan E.; Doucette, Peter J.

2006-02-13

Often text and imagery contain information that must be combined to solve a problem. One approach begins with transforming the raw text and imagery into a common structure that contains the critical information in a usable form. This paper presents an application in which the imagery of vehicles and the text from police reports were combined to demonstrate the power of data fusion to correctly identify the target vehicle--e.g., a red 2002 Ford truck identified in a police report--from a collection of diverse vehicle images. The imagery was abstracted into a common signature by first capturing the conceptual models ofmore » the imagery experts in software. Our system then (1) extracted fundamental features (e.g., wheel base, color), (2) made inferences about the information (e.g., it’s a red Ford) and then (3) translated the raw information into an abstract knowledge signature that was designed to both capture the important features and account for uncertainty. Likewise, the conceptual models of text analysis experts were instantiated into software that was used to generate an abstract knowledge signature that could be readily compared to the imagery knowledge signature. While this experiment primary focus was to demonstrate the power of text and imagery fusion for a specific example it also suggested several ways that text and geo-registered imagery could be combined to help solve other types of problems.« less

Gaze Estimation for Off-Angle Iris Recognition Based on the Biometric Eye Model

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

Karakaya, Mahmut; Barstow, Del R; Santos-Villalobos, Hector J

Iris recognition is among the highest accuracy biometrics. However, its accuracy relies on controlled high quality capture data and is negatively affected by several factors such as angle, occlusion, and dilation. Non-ideal iris recognition is a new research focus in biometrics. In this paper, we present a gaze estimation method designed for use in an off-angle iris recognition framework based on the ANONYMIZED biometric eye model. Gaze estimation is an important prerequisite step to correct an off-angle iris images. To achieve the accurate frontal reconstruction of an off-angle iris image, we first need to estimate the eye gaze direction frommore » elliptical features of an iris image. Typically additional information such as well-controlled light sources, head mounted equipment, and multiple cameras are not available. Our approach utilizes only the iris and pupil boundary segmentation allowing it to be applicable to all iris capture hardware. We compare the boundaries with a look-up-table generated by using our biologically inspired biometric eye model and find the closest feature point in the look-up-table to estimate the gaze. Based on the results from real images, the proposed method shows effectiveness in gaze estimation accuracy for our biometric eye model with an average error of approximately 3.5 degrees over a 50 degree range.« less

Irrelevant learned reward associations disrupt voluntary spatial attention.

PubMed

MacLean, Mary H; Diaz, Gisella K; Giesbrecht, Barry

2016-10-01

Attention can be guided involuntarily by physical salience and by non-salient, previously learned reward associations that are currently task-irrelevant. Attention can be guided voluntarily by current goals and expectations. The current study examined, in two experiments, whether irrelevant reward associations could disrupt current, goal-driven, voluntary attention. In a letter-search task, attention was directed voluntarily (i.e., cued) on half the trials by a cue stimulus indicating the hemifield in which the target letter would appear with 100 % accuracy. On the other half of the trials, a cue stimulus was presented, but it did not provide information about the target hemifield (i.e., uncued). On both cued and uncued trials, attention could be involuntarily captured by the presence of a task-irrelevant, and physically non-salient, color, either within the cued or the uncued hemifield. Importantly, one week prior to the letter search task, the irrelevant color had served as a target feature that was predictive of reward in a separate training task. Target identification accuracy was better on cued compared to uncued trials. However, this effect was reduced when the irrelevant, and physically non-salient, reward-associated feature was present in the uncued hemifield. This effect was not observed in a second, control experiment in which the irrelevant color was not predictive of reward during training. Our results indicate that involuntary, value-driven capture can disrupt the voluntary control of spatial attention.

Transactive memory systems scale for couples: development and validation

PubMed Central

Hewitt, Lauren Y.; Roberts, Lynne D.

2015-01-01

People in romantic relationships can develop shared memory systems by pooling their cognitive resources, allowing each person access to more information but with less cognitive effort. Research examining such memory systems in romantic couples largely focuses on remembering word lists or performing lab-based tasks, but these types of activities do not capture the processes underlying couples’ transactive memory systems, and may not be representative of the ways in which romantic couples use their shared memory systems in everyday life. We adapted an existing measure of transactive memory systems for use with romantic couples (TMSS-C), and conducted an initial validation study. In total, 397 participants who each identified as being a member of a romantic relationship of at least 3 months duration completed the study. The data provided a good fit to the anticipated three-factor structure of the components of couples’ transactive memory systems (specialization, credibility and coordination), and there was reasonable evidence of both convergent and divergent validity, as well as strong evidence of test–retest reliability across a 2-week period. The TMSS-C provides a valuable tool that can quickly and easily capture the underlying components of romantic couples’ transactive memory systems. It has potential to help us better understand this intriguing feature of romantic relationships, and how shared memory systems might be associated with other important features of romantic relationships. PMID:25999873

Tool Measures Depths of Defects on a Case Tang Joint

NASA Technical Reports Server (NTRS)

Ream, M. Bryan; Montgomery, Ronald B.; Mecham, Brent A.; Keirstead, Bums W.

2005-01-01

A special-purpose tool has been developed for measuring the depths of defects on an O-ring seal surface. The surface lies in a specially shaped ringlike fitting, called a capture feature tang, located on an end of a cylindrical segment of a case that contains a solid-fuel booster rocket motor for launching a space shuttle. The capture feature tang is a part of a tang-and-clevis, O-ring joint between the case segment and a similar, adjacent cylindrical case segment. When the segments are joined, the tang makes an interference fit with the clevis and squeezes the O-ring at the side of the gap.

Small mammal communities of high elevation central Appalachian wetlands

Treesearch

Karen E. Francl; Steven B. Castleberry; W. Mark Ford

2004-01-01

We surveyed small mammal assemblages at 20 high-elevation wetlands in West Virginia and Maryland and examined relationships among mammal capture rates, richness and evenness and landscape features at multiple spatial scales. In 24,693 trap nights we captured 1451 individuals of 12 species. Small mammal species richness increased with wetland size and was negatively...

Quasiparticle self-consistent GW study of cuprates: electronic structure, model parameters, and the two-band theory for Tc

PubMed Central

Jang, Seung Woo; Kotani, Takao; Kino, Hiori; Kuroki, Kazuhiko; Han, Myung Joon

2015-01-01

Despite decades of progress, an understanding of unconventional superconductivity still remains elusive. An important open question is about the material dependence of the superconducting properties. Using the quasiparticle self-consistent GW method, we re-examine the electronic structure of copper oxide high-Tc materials. We show that QSGW captures several important features, distinctive from the conventional LDA results. The energy level splitting between and is significantly enlarged and the van Hove singularity point is lowered. The calculated results compare better than LDA with recent experimental results from resonant inelastic xray scattering and angle resolved photoemission experiments. This agreement with the experiments supports the previously suggested two-band theory for the material dependence of the superconducting transition temperature, Tc. PMID:26206417

Histological features of the gastrointestinal tract of wild Indonesian shortfin eel, Anguilla bicolor bicolor (McClelland, 1844), captured in Peninsular Malaysia.

PubMed

Nasruddin, Nurrul Shaqinah; Azmai, Mohammad Noor Amal; Ismail, Ahmad; Saad, Mohd Zamri; Daud, Hassan Mohd; Zulkifli, Syaizwan Zahmir

2014-01-01

This study was conducted to record the histological features of the gastrointestinal tract of wild Indonesian shortfin eel, Anguilla bicolor bicolor (McClelland, 1844), captured in Peninsular Malaysia. The gastrointestinal tract was segmented into the oesophagus, stomach, and intestine. Then, the oesophagus was divided into five (first to fifth), the stomach into two (cardiac and pyloric), and the intestine into four segments (anterior, intermediate, posterior, and rectum) for histological examinations. The stomach had significantly taller villi and thicker inner circular muscles compared to the intestine and oesophagus. The lamina propria was thickest in stomach, significantly when compared with oesophagus, but not with the intestine. However, the intestine showed significantly thicker outer longitudinal muscle while gastric glands were observed only in the stomach. The histological features were closely associated with the functions of the different segments of the gastrointestinal tract. In conclusion, the histological features of the gastrointestinal tract of A. b. bicolor are consistent with the feeding habit of a carnivorous fish.

Remote sensing image segmentation using local sparse structure constrained latent low rank representation

NASA Astrophysics Data System (ADS)

Tian, Shu; Zhang, Ye; Yan, Yimin; Su, Nan; Zhang, Junping

2016-09-01

Latent low-rank representation (LatLRR) has been attached considerable attention in the field of remote sensing image segmentation, due to its effectiveness in exploring the multiple subspace structures of data. However, the increasingly heterogeneous texture information in the high spatial resolution remote sensing images, leads to more severe interference of pixels in local neighborhood, and the LatLRR fails to capture the local complex structure information. Therefore, we present a local sparse structure constrainted latent low-rank representation (LSSLatLRR) segmentation method, which explicitly imposes the local sparse structure constraint on LatLRR to capture the intrinsic local structure in manifold structure feature subspaces. The whole segmentation framework can be viewed as two stages in cascade. In the first stage, we use the local histogram transform to extract the texture local histogram features (LHOG) at each pixel, which can efficiently capture the complex and micro-texture pattern. In the second stage, a local sparse structure (LSS) formulation is established on LHOG, which aims to preserve the local intrinsic structure and enhance the relationship between pixels having similar local characteristics. Meanwhile, by integrating the LSS and the LatLRR, we can efficiently capture the local sparse and low-rank structure in the mixture of feature subspace, and we adopt the subspace segmentation method to improve the segmentation accuracy. Experimental results on the remote sensing images with different spatial resolution show that, compared with three state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

Noise Reduction in Brainwaves by Using Both EEG Signals and Frontal Viewing Camera Images

PubMed Central

Bang, Jae Won; Choi, Jong-Suk; Park, Kang Ryoung

2013-01-01

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have been used in various applications, including human–computer interfaces, diagnosis of brain diseases, and measurement of cognitive status. However, EEG signals can be contaminated with noise caused by user's head movements. Therefore, we propose a new method that combines an EEG acquisition device and a frontal viewing camera to isolate and exclude the sections of EEG data containing these noises. This method is novel in the following three ways. First, we compare the accuracies of detecting head movements based on the features of EEG signals in the frequency and time domains and on the motion features of images captured by the frontal viewing camera. Second, the features of EEG signals in the frequency domain and the motion features captured by the frontal viewing camera are selected as optimal ones. The dimension reduction of the features and feature selection are performed using linear discriminant analysis. Third, the combined features are used as inputs to support vector machine (SVM), which improves the accuracy in detecting head movements. The experimental results show that the proposed method can detect head movements with an average error rate of approximately 3.22%, which is smaller than that of other methods. PMID:23669713

Features of Heart Rate Variability Capture Regulatory Changes During Kangaroo Care in Preterm Infants.

PubMed

Kommers, Deedee R; Joshi, Rohan; van Pul, Carola; Atallah, Louis; Feijs, Loe; Oei, Guid; Bambang Oetomo, Sidarto; Andriessen, Peter

2017-03-01

To determine whether heart rate variability (HRV) can serve as a surrogate measure to track regulatory changes during kangaroo care, a period of parental coregulation distinct from regulation within the incubator. Nurses annotated the starting and ending times of kangaroo care for 3 months. The pre-kangaroo care, during-kangaroo care, and post-kangaroo care data were retrieved in infants with at least 10 accurately annotated kangaroo care sessions. Eight HRV features (5 in the time domain and 3 in the frequency domain) were used to visually and statistically compare the pre-kangaroo care and during-kangaroo care periods. Two of these features, capturing the percentage of heart rate decelerations and the extent of heart rate decelerations, were newly developed for preterm infants. A total of 191 kangaroo care sessions were investigated in 11 preterm infants. Despite clinically irrelevant changes in vital signs, 6 of the 8 HRV features (SD of normal-to-normal intervals, root mean square of the SD, percentage of consecutive normal-to-normal intervals that differ by >50 ms, SD of heart rate decelerations, high-frequency power, and low-frequency/high-frequency ratio) showed a visible and statistically significant difference (P <.01) between stable periods of kangaroo care and pre-kangaroo care. HRV was reduced during kangaroo care owing to a decrease in the extent of transient heart rate decelerations. HRV-based features may be clinically useful for capturing the dynamic changes in autonomic regulation in response to kangaroo care and other changes in environment and state. Copyright © 2016 Elsevier Inc. All rights reserved.

How Structure Defines Affinity in Protein-Protein Interactions

PubMed Central

Erijman, Ariel; Rosenthal, Eran; Shifman, Julia M.

2014-01-01

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins. PMID:25329579

Anion-activated, thermoreversible gelation system for the capture, release, and visual monitoring of CO2

PubMed Central

Zhang, Xin; Lee, Songyi; Liu, Yifan; Lee, Minji; Yin, Jun; Sessler, Jonathan L.; Yoon, Juyoung

2014-01-01

Carbon dioxide (CO2) is an important green house gas. This is providing an incentive to develop new strategies to detect and capture CO2. Achieving both functions within a single molecular system represents an unmet challenge in terms of molecular design and could translate into enhanced ease of use. Here, we report an anion-activated chemosensor system, NAP-chol 1, that permits dissolved CO2 to be detected in organic media via simple color changes or through ratiometric differences in fluorescence intensity. NAP-chol 1 also acts as a super gelator for DMSO. The resulting gel is transformed into a homogeneous solution upon exposure to fluoride anions. Bubbling with CO2 regenerates the gel. Subsequent flushing with N2 or heating serves to release the CO2 and reform the sol form. This series of transformations is reversible and can be followed by easy-to-discern color changes. Thus, NAP-chol 1 allows for the capture and release of CO2 gas while acting as a three mode sensing system. In particular, it permits CO2 to be detected through reversible sol-gel transitions, simple changes in color, or ratiometric monitoring of the differences in the fluorescence features. PMID:24699626

Resonance and Capture of Jupiter Comets

NASA Astrophysics Data System (ADS)

Koon, W. S.; Lo, M. W.; Marsden, J. E.; Ross, S. D.

A number of Jupiter family comets such as Oterma and Gehrels 3 make a rapid transition from heliocentric orbits outside the orbit of Jupiter to heliocentric orbits inside the orbit of Jupiter and vice versa. During this transition, the comet can be captured temporarily by Jupiter for one to several orbits around Jupiter. The interior heliocentric orbit is typically close to the 3:2 resonance while the exterior heliocentric orbit is near the 2:3 resonance. An important feature of the dynamics of these comets is that during the transition, the orbit passes close to the libration points L_1 and L_2, two of the equilibrium points for the restricted three-body problem for the Sun-Jupiter system. Studying the libration point invariant manifold structures for L_1 and L_2 is a starting point for understanding the capture and resonance transition of these comets. For example, the recently discovered heteroclinic connection between pairs of unstable periodic orbits (one around the L_1 and the other around L_2) implies a complicated dynamics for comets in a certain energy range. Furthermore, the stable and unstable invariant manifold `tubes' associated to libration point periodic orbits, of which the heteroclinic connections are a part, are phase space conduits transporting material to and from Jupiter and between the interior and exterior of Jupiter's orbit.

Ultrafast dynamics of defect-assisted electron-hole recombination in monolayer MoS2.

PubMed

Wang, Haining; Zhang, Changjian; Rana, Farhan

2015-01-14

In this Letter, we present nondegenerate ultrafast optical pump-probe studies of the carrier recombination dynamics in MoS2 monolayers. By tuning the probe to wavelengths much longer than the exciton line, we make the probe transmission sensitive to the total population of photoexcited electrons and holes. Our measurement reveals two distinct time scales over which the photoexcited electrons and holes recombine; a fast time scale that lasts ∼ 2 ps and a slow time scale that lasts longer than ∼ 100 ps. The temperature and the pump fluence dependence of the observed carrier dynamics are consistent with defect-assisted recombination as being the dominant mechanism for electron-hole recombination in which the electrons and holes are captured by defects via Auger processes. Strong Coulomb interactions in two-dimensional atomic materials, together with strong electron and hole correlations in two-dimensional metal dichalcogenides, make Auger processes particularly effective for carrier capture by defects. We present a model for carrier recombination dynamics that quantitatively explains all features of our data for different temperatures and pump fluences. The theoretical estimates for the rate constants for Auger carrier capture are in good agreement with the experimentally determined values. Our results underscore the important role played by Auger processes in two-dimensional atomic materials.

Capturing strain localization behind a geosynthetic-reinforced soil wall

NASA Astrophysics Data System (ADS)

Lai, Timothy Y.; Borja, Ronaldo I.; Duvernay, Blaise G.; Meehan, Richard L.

2003-04-01

This paper presents the results of finite element (FE) analyses of shear strain localization that occurred in cohesionless soils supported by a geosynthetic-reinforced retaining wall. The innovative aspects of the analyses include capturing of the localized deformation and the accompanying collapse mechanism using a recently developed embedded strong discontinuity model. The case study analysed, reported in previous publications, consists of a 3.5-m tall, full-scale reinforced wall model deforming in plane strain and loaded by surcharge at the surface to failure. Results of the analysis suggest strain localization developing from the toe of the wall and propagating upward to the ground surface, forming a curved failure surface. This is in agreement with a well-documented failure mechanism experienced by the physical wall model showing internal failure surfaces developing behind the wall as a result of the surface loading. Important features of the analyses include mesh sensitivity studies and a comparison of the localization properties predicted by different pre-localization constitutive models, including a family of three-invariant elastoplastic constitutive models appropriate for frictional/dilatant materials. Results of the analysis demonstrate the potential of the enhanced FE method for capturing a collapse mechanism characterized by the presence of a failure, or slip, surface through earthen materials.

Determining the saliency of feature measurements obtained from images of sedimentary organic matter for use in its classification

NASA Astrophysics Data System (ADS)

Weller, Andrew F.; Harris, Anthony J.; Ware, J. Andrew; Jarvis, Paul S.

2006-11-01

The classification of sedimentary organic matter (OM) images can be improved by determining the saliency of image analysis (IA) features measured from them. Knowing the saliency of IA feature measurements means that only the most significant discriminating features need be used in the classification process. This is an important consideration for classification techniques such as artificial neural networks (ANNs), where too many features can lead to the 'curse of dimensionality'. The classification scheme adopted in this work is a hybrid of morphologically and texturally descriptive features from previous manual classification schemes. Some of these descriptive features are assigned to IA features, along with several others built into the IA software (Halcon) to ensure that a valid cross-section is available. After an image is captured and segmented, a total of 194 features are measured for each particle. To reduce this number to a more manageable magnitude, the SPSS AnswerTree Exhaustive CHAID (χ 2 automatic interaction detector) classification tree algorithm is used to establish each measurement's saliency as a classification discriminator. In the case of continuous data as used here, the F-test is used as opposed to the published algorithm. The F-test checks various statistical hypotheses about the variance of groups of IA feature measurements obtained from the particles to be classified. The aim is to reduce the number of features required to perform the classification without reducing its accuracy. In the best-case scenario, 194 inputs are reduced to 8, with a subsequent multi-layer back-propagation ANN recognition rate of 98.65%. This paper demonstrates the ability of the algorithm to reduce noise, help overcome the curse of dimensionality, and facilitate an understanding of the saliency of IA features as discriminators for sedimentary OM classification.

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments

PubMed Central

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Storrs, Katherine R.; Mur, Marieke

2017-01-01

Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs’ performance compares to that of non-computational “conceptual” models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., “eye”) and category labels (e.g., “animal”) for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features other than object parts perform relatively poorly, perhaps because DNNs more comprehensively capture the colors, textures and contours which matter to human object perception. However, categorical models outperform DNNs, suggesting that further work may be needed to bring high-level semantic representations in DNNs closer to those extracted by humans. Modern DNNs explain similarity judgments remarkably well considering they were not trained on this task, and are promising models for many aspects of human cognition. PMID:29062291

Style-based classification of Chinese ink and wash paintings

NASA Astrophysics Data System (ADS)

Sheng, Jiachuan; Jiang, Jianmin

2013-09-01

Following the fact that a large collection of ink and wash paintings (IWP) is being digitized and made available on the Internet, their automated content description, analysis, and management are attracting attention across research communities. While existing research in relevant areas is primarily focused on image processing approaches, a style-based algorithm is proposed to classify IWPs automatically by their authors. As IWPs do not have colors or even tones, the proposed algorithm applies edge detection to locate the local region and detect painting strokes to enable histogram-based feature extraction and capture of important cues to reflect the styles of different artists. Such features are then applied to drive a number of neural networks in parallel to complete the classification, and an information entropy balanced fusion is proposed to make an integrated decision for the multiple neural network classification results in which the entropy is used as a pointer to combine the global and local features. Evaluations via experiments support that the proposed algorithm achieves good performances, providing excellent potential for computerized analysis and management of IWPs.

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Clustering method for counting passengers getting in a bus with single camera

NASA Astrophysics Data System (ADS)

Yang, Tao; Zhang, Yanning; Shao, Dapei; Li, Ying

2010-03-01

Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.

Predictive Ensemble Decoding of Acoustical Features Explains Context-Dependent Receptive Fields.

PubMed

Yildiz, Izzet B; Mesgarani, Nima; Deneve, Sophie

2016-12-07

A primary goal of auditory neuroscience is to identify the sound features extracted and represented by auditory neurons. Linear encoding models, which describe neural responses as a function of the stimulus, have been primarily used for this purpose. Here, we provide theoretical arguments and experimental evidence in support of an alternative approach, based on decoding the stimulus from the neural response. We used a Bayesian normative approach to predict the responses of neurons detecting relevant auditory features, despite ambiguities and noise. We compared the model predictions to recordings from the primary auditory cortex of ferrets and found that: (1) the decoding filters of auditory neurons resemble the filters learned from the statistics of speech sounds; (2) the decoding model captures the dynamics of responses better than a linear encoding model of similar complexity; and (3) the decoding model accounts for the accuracy with which the stimulus is represented in neural activity, whereas linear encoding model performs very poorly. Most importantly, our model predicts that neuronal responses are fundamentally shaped by "explaining away," a divisive competition between alternative interpretations of the auditory scene. Neural responses in the auditory cortex are dynamic, nonlinear, and hard to predict. Traditionally, encoding models have been used to describe neural responses as a function of the stimulus. However, in addition to external stimulation, neural activity is strongly modulated by the responses of other neurons in the network. We hypothesized that auditory neurons aim to collectively decode their stimulus. In particular, a stimulus feature that is decoded (or explained away) by one neuron is not explained by another. We demonstrated that this novel Bayesian decoding model is better at capturing the dynamic responses of cortical neurons in ferrets. Whereas the linear encoding model poorly reflects selectivity of neurons, the decoding model can account for the strong nonlinearities observed in neural data. Copyright © 2016 Yildiz et al.

A gait retraining system using augmented-reality to modify footprint parameters: Effects on lower-limb sagittal-plane kinematics.

PubMed

Bennour, Sami; Ulrich, Baptiste; Legrand, Thomas; Jolles, Brigitte M; Favre, Julien

2018-01-03

Improving lower-limb flexion/extension angles during walking is important for the treatment of numerous pathologies. Currently, these gait retraining procedures are mostly qualitative, often based on visual assessment and oral instructions. This study aimed to propose an alternative method combining motion capture and display of target footprints on the floor. The second objectives were to determine the error in footprint modifications and the effects of footprint modifications on lower-limb flexion/extension angles. An augmented-reality system made of an optoelectronic motion capture device and video projectors displaying target footprints on the floor was designed. 10 young healthy subjects performed a series of 27 trials, consisting of increased and decreased amplitudes in stride length, step width and foot progression angle. 11 standard features were used to describe and compare lower-limb flexion/extension angles among footprint modifications. Subjects became accustomed to walk on target footprints in less than 10 min, with mean (± SD) precision of 0.020 ± 0.002 m in stride length, 0.022 ± 0.006 m in step width, and 2.7 ± 0.6° in progression angle. Modifying stride length had significant effects on 3/3 hip, 2/4 knee and 4/4 ankle features. Similarly, step width and progression angle modifications affected 2/3 and 1/3 hip, 2/4 and 1/4 knee as well as 3/4 and 2/4 ankle features, respectively. In conclusion, this study introduced an augmented-reality method allowing healthy subjects to modify their footprint parameters rapidly and precisely. Walking with modified footprints changed lower-limb sagittal-plane kinematics. Further research is needed to design rehabilitation protocols for specific pathologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic emotional expression analysis from eye area

NASA Astrophysics Data System (ADS)

Akkoç, Betül; Arslan, Ahmet

2015-02-01

Eyes play an important role in expressing emotions in nonverbal communication. In the present study, emotional expression classification was performed based on the features that were automatically extracted from the eye area. Fırst, the face area and the eye area were automatically extracted from the captured image. Afterwards, the parameters to be used for the analysis through discrete wavelet transformation were obtained from the eye area. Using these parameters, emotional expression analysis was performed through artificial intelligence techniques. As the result of the experimental studies, 6 universal emotions consisting of expressions of happiness, sadness, surprise, disgust, anger and fear were classified at a success rate of 84% using artificial neural networks.

Designing attractive models via automated identification of chaotic and oscillatory dynamical regimes.

PubMed

Silk, Daniel; Kirk, Paul D W; Barnes, Chris P; Toni, Tina; Rose, Anna; Moon, Simon; Dallman, Margaret J; Stumpf, Michael P H

2011-10-04

Chaos and oscillations continue to capture the interest of both the scientific and public domains. Yet despite the importance of these qualitative features, most attempts at constructing mathematical models of such phenomena have taken an indirect, quantitative approach, for example, by fitting models to a finite number of data points. Here we develop a qualitative inference framework that allows us to both reverse-engineer and design systems exhibiting these and other dynamical behaviours by directly specifying the desired characteristics of the underlying dynamical attractor. This change in perspective from quantitative to qualitative dynamics, provides fundamental and new insights into the properties of dynamical systems.

Pancreatic cancer study based on full field OCT and dynamic full field OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Apelian, Clement; Camus, Marine; Prat, Frederic; Boccara, A. Claude

2017-02-01

Pancreatic cancer is one of the most feared cancer types due to high death rates and the difficulty to perform surgery. This cancer outcome could benefit from recent technological developments for diagnosis. We used a combination of standard Full Field OCT and Dynamic Full Field OCT to capture both morphological features and metabolic functions of rodents pancreas in normal and cancerous conditions with and without chemotherapy. Results were compared to histology to evaluate the performances and the specificities of the method. The comparison highlighted the importance of a number of endogenous markers like immune cells, fibrous development, architecture and more.

Study on data acquisition system based on reconfigurable cache technology

NASA Astrophysics Data System (ADS)

Zhang, Qinchuan; Li, Min; Jiang, Jun

2018-03-01

Waveform capture rate is one of the key features of digital acquisition systems, which represents the waveform processing capability of the system in a unit time. The higher the waveform capture rate is, the larger the chance to capture elusive events is and the more reliable the test result is. First, this paper analyzes the impact of several factors on the waveform capture rate of the system, then the novel technology based on reconfigurable cache is further proposed to optimize system architecture, and the simulation results show that the signal-to-noise ratio of signal, capacity, and structure of cache have significant effects on the waveform capture rate. Finally, the technology is demonstrated by the engineering practice, and the results show that the waveform capture rate of the system is improved substantially without significant increase of system's cost, and the technology proposed has a broad application prospect.

Textural Analysis and Substrate Classification in the Nearshore Region of Lake Superior Using High-Resolution Multibeam Bathymetry

NASA Astrophysics Data System (ADS)

Dennison, Andrew G.

Classification of the seafloor substrate can be done with a variety of methods. These methods include Visual (dives, drop cameras); mechanical (cores, grab samples); acoustic (statistical analysis of echosounder returns). Acoustic methods offer a more powerful and efficient means of collecting useful information about the bottom type. Due to the nature of an acoustic survey, larger areas can be sampled, and by combining the collected data with visual and mechanical survey methods provide greater confidence in the classification of a mapped region. During a multibeam sonar survey, both bathymetric and backscatter data is collected. It is well documented that the statistical characteristic of a sonar backscatter mosaic is dependent on bottom type. While classifying the bottom-type on the basis on backscatter alone can accurately predict and map bottom-type, i.e a muddy area from a rocky area, it lacks the ability to resolve and capture fine textural details, an important factor in many habitat mapping studies. Statistical processing of high-resolution multibeam data can capture the pertinent details about the bottom-type that are rich in textural information. Further multivariate statistical processing can then isolate characteristic features, and provide the basis for an accurate classification scheme. The development of a new classification method is described here. It is based upon the analysis of textural features in conjunction with ground truth sampling. The processing and classification result of two geologically distinct areas in nearshore regions of Lake Superior; off the Lester River,MN and Amnicon River, WI are presented here, using the Minnesota Supercomputer Institute's Mesabi computing cluster for initial processing. Processed data is then calibrated using ground truth samples to conduct an accuracy assessment of the surveyed areas. From analysis of high-resolution bathymetry data collected at both survey sites is was possible to successfully calculate a series of measures that describe textural information about the lake floor. Further processing suggests that the features calculated capture a significant amount of statistical information about the lake floor terrain as well. Two sources of error, an anomalous heave and refraction error significantly deteriorated the quality of the processed data and resulting validate results. Ground truth samples used to validate the classification methods utilized for both survey sites, however, resulted in accuracy values ranging from 5 -30 percent at the Amnicon River, and between 60-70 percent for the Lester River. The final results suggest that this new processing methodology does adequately capture textural information about the lake floor and does provide an acceptable classification in the absence of significant data quality issues.

The Visual Hemifield Asymmetry in the Spatial Blink during Singleton Search and Feature Search

ERIC Educational Resources Information Center

Burnham, Bryan R.; Rozell, Cassandra A.; Kasper, Alex; Bianco, Nicole E.; Delliturri, Antony

2011-01-01

The present study examined a visual field asymmetry in the contingent capture of attention that was previously observed by Du and Abrams (2010). In our first experiment, color singleton distractors that matched the color of a to-be-detected target produced a stronger capture of attention when they appeared in the left visual hemifield than in the…

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Scopolamine Reduces Electrophysiological Indices of Distractor Suppression: Evidence from a Contingent Capture Task

PubMed Central

Laube, Inga; Matthews, Natasha; Dean, Angela J.; O’Connell, Redmond G.; Mattingley, Jason B.; Bellgrove, Mark A.

2017-01-01

Limited resources for the in-depth processing of external stimuli make it necessary to select only relevant information from our surroundings and to ignore irrelevant stimuli. Attentional mechanisms facilitate this selection via top-down modulation of stimulus representations in the brain. Previous research has indicated that acetylcholine (ACh) modulates this influence of attention on stimulus processing. However, the role of muscarinic receptors as well as the specific mechanism of cholinergic modulation remains unclear. Here we investigated the influence of ACh on feature-based, top-down control of stimulus processing via muscarinic receptors by using a contingent capture paradigm which specifically tests attentional shifts toward uninformative cue stimuli which display one of the target defining features In a double-blind, placebo controlled study we measured the impact of the muscarinic receptor antagonist scopolamine on behavioral and electrophysiological measures of contingent attentional capture. The results demonstrated all the signs of functional contingent capture, i.e., attentional shifts toward cued locations reflected in increased amplitudes of N1 and N2Pc components, under placebo conditions. However, scopolamine did not affect behavioral or electrophysiological measures of contingent capture. Instead, scopolamine reduced the amplitude of the distractor-evoked Pd component which has recently been associated with active suppression of irrelevant distractor information. The findings suggest a general cholinergic modulation of top-down control during distractor processing. PMID:29270112

Development of a general-purpose, integrated knowledge capture and delivery system

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

Roberts, A.G.; Freer, E.B.

1991-01-01

KATIE (Knowledge-Based Assistant for Troubleshooting Industrial Equipment) was first conceived as a solution for maintenance problems. In the area of process control, maintenance technicians have become responsible for increasingly complicated equipment and an overwhelming amount of associated information. The sophisticated distributed control systems have proven to be such a drastic change for technicians that they are forced to rely on the engineer for troubleshooting guidance. Because it is difficult for a knowledgeable engineer to be readily available for troubleshooting,maintenance personnel wish to capture the information provided by the engineer. The solution provided has two stages. First, a specific complicated systemmore » was chosen as a test case. An effort was made to gather all available system information in some form. Second, a method of capturing and delivering this collection of information was developed. Several features were desired for this knowledge capture/delivery system (KATIE). Creation of the knowledge base needed to be independent of the delivery system. The delivery path need to be as simple as possible for the technician, and the capture, or authoring, system could provide very sophisticated features. It was decided that KATIE should be as general as possible, not internalizing specifics about the first implementation. The knowledge bases created needed to be completely separate from KATIE needed to have a modular structure so that each type of information (rules, procedures, manuals, symptoms) could be encapsulated individually.« less

Collinearity Impairs Local Element Visual Search

ERIC Educational Resources Information Center

Jingling, Li; Tseng, Chia-Huei

2013-01-01

In visual searches, stimuli following the law of good continuity attract attention to the global structure and receive attentional priority. Also, targets that have unique features are of high feature contrast and capture attention in visual search. We report on a salient global structure combined with a high orientation contrast to the…

Putting Parameters in Their Proper Place

ERIC Educational Resources Information Center

Montrul, Silvina; Yoon, James

2009-01-01

Seeing the logical problem of second language acquisition as that of primarily selecting and re-assembling bundles of features anew, Lardiere proposes to dispense with the deductive learning approach and its broad range of consequences subsumed under the concept of parameters. While we agree that feature assembly captures more precisely the…

Software Review: A program for testing capture-recapture data for closure

USGS Publications Warehouse

Stanley, Thomas R.; Richards, Jon D.

2005-01-01

Capture-recapture methods are widely used to estimate population parameters of free-ranging animals. Closed-population capture-recapture models, which assume there are no additions to or losses from the population over the period of study (i.e., the closure assumption), are preferred for population estimation over the open-population models, which do not assume closure, because heterogeneity in detection probabilities can be accounted for and this improves estimates. In this paper we introduce CloseTest, a new Microsoft® Windows-based program that computes the Otis et al. (1978) and Stanley and Burnham (1999) closure tests for capture-recapture data sets. Information on CloseTest features and where to obtain the program are provided.

Feature-based memory-driven attentional capture: visual working memory content affects visual attention.

PubMed

Olivers, Christian N L; Meijer, Frank; Theeuwes, Jan

2006-10-01

In 7 experiments, the authors explored whether visual attention (the ability to select relevant visual information) and visual working memory (the ability to retain relevant visual information) share the same content representations. The presence of singleton distractors interfered more strongly with a visual search task when it was accompanied by an additional memory task. Singleton distractors interfered even more when they were identical or related to the object held in memory, but only when it was difficult to verbalize the memory content. Furthermore, this content-specific interaction occurred for features that were relevant to the memory task but not for irrelevant features of the same object or for once-remembered objects that could be forgotten. Finally, memory-related distractors attracted more eye movements but did not result in longer fixations. The results demonstrate memory-driven attentional capture on the basis of content-specific representations. Copyright 2006 APA.

3D palmprint data fast acquisition and recognition

NASA Astrophysics Data System (ADS)

Wang, Xiaoxu; Huang, Shujun; Gao, Nan; Zhang, Zonghua

2014-11-01

This paper presents a fast 3D (Three-Dimension) palmprint capturing system and develops an efficient 3D palmprint feature extraction and recognition method. In order to fast acquire accurate 3D shape and texture of palmprint, a DLP projector triggers a CCD camera to realize synchronization. By generating and projecting green fringe pattern images onto the measured palm surface, 3D palmprint data are calculated from the fringe pattern images. The periodic feature vector can be derived from the calculated 3D palmprint data, so undistorted 3D biometrics is obtained. Using the obtained 3D palmprint data, feature matching test have been carried out by Gabor filter, competition rules and the mean curvature. Experimental results on capturing 3D palmprint show that the proposed acquisition method can fast get 3D shape information of palmprint. Some initial experiments on recognition show the proposed method is efficient by using 3D palmprint data.

Gross feature recognition of Anatomical Images based on Atlas grid (GAIA): Incorporating the local discrepancy between an atlas and a target image to capture the features of anatomic brain MRI.

PubMed

Qin, Yuan-Yuan; Hsu, Johnny T; Yoshida, Shoko; Faria, Andreia V; Oishi, Kumiko; Unschuld, Paul G; Redgrave, Graham W; Ying, Sarah H; Ross, Christopher A; van Zijl, Peter C M; Hillis, Argye E; Albert, Marilyn S; Lyketsos, Constantine G; Miller, Michael I; Mori, Susumu; Oishi, Kenichi

2013-01-01

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas-image misregistration, is used to capture the anatomical features of target images. As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

Quantifying the Contribution of Wind-Driven Linear Response to the Seasonal and Interannual Variability of Amoc Volume Transports Across 26.5ºN

NASA Astrophysics Data System (ADS)

Shimizu, K.; von Storch, J. S.; Haak, H.; Nakayama, K.; Marotzke, J.

2014-12-01

Surface wind stress is considered to be an important forcing of the seasonal and interannual variability of Atlantic Meridional Overturning Circulation (AMOC) volume transports. A recent study showed that even linear response to wind forcing captures observed features of the mean seasonal cycle. However, the study did not assess the contribution of wind-driven linear response in realistic conditions against the RAPID/MOCHA array observation or Ocean General Circulation Model (OGCM) simulations, because it applied a linear two-layer model to the Atlantic assuming constant upper layer thickness and density difference across the interface. Here, we quantify the contribution of wind-driven linear response to the seasonal and interannual variability of AMOC transports by comparing wind-driven linear simulations under realistic continuous stratification against the RAPID observation and OCGM (MPI-OM) simulations with 0.4º resolution (TP04) and 0.1º resolution (STORM). All the linear and MPI-OM simulations capture more than 60% of the variance in the observed mean seasonal cycle of the Upper Mid-Ocean (UMO) and Florida Strait (FS) transports, two components of the upper branch of the AMOC. The linear and TP04 simulations also capture 25-40% of the variance in the observed transport time series between Apr 2004 and Oct 2012; the STORM simulation does not capture the observed variance because of the stochastic signal in both datasets. Comparison of half-overlapping 12-month-long segments reveals some periods when the linear and TP04 simulations capture 40-60% of the observed variance, as well as other periods when the simulations capture only 0-20% of the variance. These results show that wind-driven linear response is a major contributor to the seasonal and interannual variability of the UMO and FS transports, and that its contribution varies in an interannual timescale, probably due to the variability of stochastic processes.

Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model Descriptor Consistent Between Processes

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

Allgood, G.O.; Dress, W.B.; Kercel, S.W.

1999-05-10

A major problem with cavitation in pumps and other hydraulic devices is that there is no effective method for detecting or predicting its inception. The traditional approach is to declare the pump in cavitation when the total head pressure drops by some arbitrary value (typically 3o/0) in response to a reduction in pump inlet pressure. However, the pump is already cavitating at this point. A method is needed in which cavitation events are captured as they occur and characterized by their process dynamics. The object of this research was to identify specific features of cavitation that could be used asmore » a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor was based on the physics of the phenomena, capturing the salient features of the process dynamics. An important element of this concept is the development and formulation of the extended process feature vector @) or model vector. Thk model-based descriptor encodes the specific information that describes the phenomena and its dynamics and is formulated as a data structure consisting of several elements. The first is a descriptive model abstracting the phenomena. The second is the parameter list associated with the functional model. The third is a figure of merit, a single number between [0,1] representing a confidence factor that the functional model and parameter list actually describes the observed data. Using this as a basis and applying it to the cavitation problem, any given location in a flow loop will have this data structure, differing in value but not content. The extended process feature vector is formulated as follows: E`> [ , {parameter Iist}, confidence factor]. (1) For this study, the model that characterized cavitation was a chirped-exponentially decaying sinusoid. Using the parameters defined by this model, the parameter list included frequency, decay, and chirp rate. Based on this, the process feature vector has the form: @=> [, {01 = a, ~= b, ~ = c}, cf = 0.80]. (2) In this experiment a reversible catastrophe was examined. The reason for this is that the same catastrophe could be repeated to ensure the statistical significance of the data.« less

Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning.

PubMed

Khajehnejad, Moein; Saatlou, Forough Habibollahi; Mohammadzade, Hoda

2017-08-20

Alzheimer's disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer's disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests; therefore, an efficient approach for accurate prediction of the condition of the brain through the classification of magnetic resonance imaging (MRI) images is greatly beneficial and yet very challenging. In this paper, a novel approach is proposed for the diagnosis of very early stages of AD through an efficient classification of brain MRI images, which uses label propagation in a manifold-based semi-supervised learning framework. We first apply voxel morphometry analysis to extract some of the most critical AD-related features of brain images from the original MRI volumes and also gray matter (GM) segmentation volumes. The features must capture the most discriminative properties that vary between a healthy and Alzheimer-affected brain. Next, we perform a principal component analysis (PCA)-based dimension reduction on the extracted features for faster yet sufficiently accurate analysis. To make the best use of the captured features, we present a hybrid manifold learning framework which embeds the feature vectors in a subspace. Next, using a small set of labeled training data, we apply a label propagation method in the created manifold space to predict the labels of the remaining images and classify them in the two groups of mild Alzheimer's and normal condition (MCI/NC). The accuracy of the classification using the proposed method is 93.86% for the Open Access Series of Imaging Studies (OASIS) database of MRI brain images, providing, compared to the best existing methods, a 3% lower error rate.

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

PubMed

Daberdaku, Sebastian; Ferrari, Carlo

2018-02-06

The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein-Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction task, and that optimality strongly depends on the class of proteins whose interface we want to characterise. We postulate that different protein classes should be treated separately and that it is necessary to identify an optimal set of features for each protein class.

Capturing and stitching images with a large viewing angle and low distortion properties for upper gastrointestinal endoscopy

NASA Astrophysics Data System (ADS)

Liu, Ya-Cheng; Chung, Chien-Kai; Lai, Jyun-Yi; Chang, Han-Chao; Hsu, Feng-Yi

2013-06-01

Upper gastrointestinal endoscopies are primarily performed to observe the pathologies of the esophagus, stomach, and duodenum. However, when an endoscope is pushed into the esophagus or stomach by the physician, the organs behave similar to a balloon being gradually inflated. Consequently, their shapes and depth-of-field of images change continually, preventing thorough examination of the inflammation or anabrosis position, which delays the curing period. In this study, a 2.9-mm image-capturing module and a convoluted mechanism was incorporated into the tube like a standard 10- mm upper gastrointestinal endoscope. The scale-invariant feature transform (SIFT) algorithm was adopted to implement disease feature extraction on a koala doll. Following feature extraction, the smoothly varying affine stitching (SVAS) method was employed to resolve stitching distortion problems. Subsequently, the real-time splice software developed in this study was embedded in an upper gastrointestinal endoscope to obtain a panoramic view of stomach inflammation in the captured images. The results showed that the 2.9-mm image-capturing module can provide approximately 50 verified images in one spin cycle, a viewing angle of 120° can be attained, and less than 10% distortion can be achieved in each image. Therefore, these methods can solve the problems encountered when using a standard 10-mm upper gastrointestinal endoscope with a single camera, such as image distortion, and partial inflammation displays. The results also showed that the SIFT algorithm provides the highest correct matching rate, and the SVAS method can be employed to resolve the parallax problems caused by stitching together images of different flat surfaces.

Lack of consistent hormonal responses to capture during the breeding season of the bearded dragon, Pogona barbata.

PubMed

Cree, A; Amey, A P; Whittier, J M

2000-06-01

The bearded dragon (Pogona barbata: Agamidae) is a diurnal, oviparous, multi-clutching lizard from Australia. We examined plasma hormonal responses to capture in males and females during the spring breeding season. Corticosterone concentrations at capture (0 h; < or =3 min after capture) were low (males: 1.81+/-0.63 ng/ml; females 2. 23+/-0.47 ng/ml) and within sexes were unrelated to the time of the day, snout-vent length or, in females, reproductive condition (vitellogenic, gravid, assumed spent). Corticosterone concentrations at capture were significantly and inversely correlated with body condition in males, but not in females. Unexpectedly, neither sex showed significant changes in mean concentrations of corticosterone at 3.5 or 24 h after capture compared with 0 h values. Corticosterone concentrations at 3.5 h after capture did not differ between dragons bled at capture or not. Concentrations of progesterone in both the sexes did not change between 0 h and 3.5 or 24 h after capture. Testosterone concentrations in males at capture were moderate (10.1+/-2.2 ng/ml), and unchanged at 3.5 h after capture. The adrenocortical axis of adult bearded dragons in the breeding season seems remarkably unresponsive to capture compared with many other reptiles. Low adrenocortical responses to capture may be a feature of reptiles known to adjust well to captivity.

Quasiparticle self-consistent GW study of cuprates: electronic structure, model parameters, and the two-band theory for Tc.

PubMed

Jang, Seung Woo; Kotani, Takao; Kino, Hiori; Kuroki, Kazuhiko; Han, Myung Joon

2015-07-24

Despite decades of progress, an understanding of unconventional superconductivity still remains elusive. An important open question is about the material dependence of the superconducting properties. Using the quasiparticle self-consistent GW method, we re-examine the electronic structure of copper oxide high-Tc materials. We show that QSGW captures several important features, distinctive from the conventional LDA results. The energy level splitting between d(x(2)-y(2)) and d(3z(2)-r(2)) is significantly enlarged and the van Hove singularity point is lowered. The calculated results compare better than LDA with recent experimental results from resonant inelastic xray scattering and angle resolved photoemission experiments. This agreement with the experiments supports the previously suggested two-band theory for the material dependence of the superconducting transition temperature, Tc.

Thermodynamic assessment of microencapsulated sodium carbonate slurry for carbon capture

DOE PAGES

Stolaroff, Joshuah K.; Bourcier, William L.

2014-01-01

Micro-encapsulated Carbon Sorbents (MECS) are a new class of carbon capture materials consisting of a CO₂- absorbing liquid solvent contained within solid, CO₂-permeable, polymer shells. MECS enhance the rate of CO₂ absorption for solvents with slow kinetics and prevent solid precipitates from scaling and fouling equipment, two factors that have previously limited the use of sodium carbonate solution for carbon capture. Here, we examine the thermodynamics of sodium carbonate slurries for carbon capture. We model the vapour-liquid-solid equilibria of sodium carbonate and find several features that can contribute to an energy-efficient capture process: very high CO₂ pressures in stripping conditions,more » relatively low water vapour pressures in stripping conditions, and good swing capacity. The potential energy savings compared with an MEA system are discussed.« less

Sacra Fossae

NASA Image and Video Library

2015-11-17

The steep sided depressions in this image captured by NASA 2001 Mars Odyssey spacecraft are fault bounded tectonic features called graben. These depressions are part of a large region of graben called Sacra Fossae. Sacra Fossae is located on the western margin of Lunae Planum. Orbit Number: 60829 Latitude: 18.2961 Longitude: 287.711 Instrument: VIS Captured: 2015-08-31 10:01 http://photojournal.jpl.nasa.gov/catalog/PIA20094

CCProf: exploring conformational change profile of proteins

PubMed Central

Chang, Che-Wei; Chou, Chai-Wei; Chang, Darby Tien-Hao

2016-01-01

In many biological processes, proteins have important interactions with various molecules such as proteins, ions or ligands. Many proteins undergo conformational changes upon these interactions, where regions with large conformational changes are critical to the interactions. This work presents the CCProf platform, which provides conformational changes of entire proteins, named conformational change profile (CCP) in the context. CCProf aims to be a platform where users can study potential causes of novel conformational changes. It provides 10 biological features, including conformational change, potential binding target site, secondary structure, conservation, disorder propensity, hydropathy propensity, sequence domain, structural domain, phosphorylation site and catalytic site. All these information are integrated into a well-aligned view, so that researchers can capture important relevance between different biological features visually. The CCProf contains 986 187 protein structure pairs for 3123 proteins. In addition, CCProf provides a 3D view in which users can see the protein structures before and after conformational changes as well as binding targets that induce conformational changes. All information (e.g. CCP, binding targets and protein structures) shown in CCProf, including intermediate data are available for download to expedite further analyses. Database URL: http://zoro.ee.ncku.edu.tw/ccprof/ PMID:27016699

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

PubMed

Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J

2016-11-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons

PubMed Central

Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.

2016-01-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647

Capturing Students' Abstraction While Solving Organic Reaction Mechanism Problems across a Semester

ERIC Educational Resources Information Center

Weinrich, M. L.; Sevian, H.

2017-01-01

Students often struggle with solving mechanism problems in organic chemistry courses. They frequently focus on surface features, have difficulty attributing meaning to symbols, and do not recognize tasks that are different from the exact tasks practiced. To be more successful, students need to be able to extract salient features, map similarities…

Modeling Age Differences in Infant Category Learning

ERIC Educational Resources Information Center

Shultz, Thomas R.; Cohen, Leslie B.

2004-01-01

We used an encoder version of cascade correlation to simulate Younger and Cohen's (1983, 1986) finding that 10-month-olds recover attention on the basis of correlations among stimulus features, but 4- and 7-month-olds recover attention on the basis of stimulus features. We captured these effects by varying the score threshold parameter in cascade…

ORNL Lightweighting Research Featured on MotorWeek

ScienceCinema

None

2018-06-06

PBS MotorWeek, television's longest running automotive series, featured ORNL lightweighting research for vehicle applications in an episode that aired in early April 2014. The crew captured footage of research including development of new metal alloys, additive manufacturing, carbon fiber production, advanced batteries, power electronics components, and neutron imaging applications for materials evaluation.

Histological Features of the Gastrointestinal Tract of Wild Indonesian Shortfin Eel, Anguilla bicolor bicolor (McClelland, 1844), Captured in Peninsular Malaysia

PubMed Central

Nasruddin, Nurrul Shaqinah; Azmai, Mohammad Noor Amal; Ismail, Ahmad; Saad, Mohd Zamri; Daud, Hassan Mohd; Zulkifli, Syaizwan Zahmir

2014-01-01

This study was conducted to record the histological features of the gastrointestinal tract of wild Indonesian shortfin eel, Anguilla bicolor bicolor (McClelland, 1844), captured in Peninsular Malaysia. The gastrointestinal tract was segmented into the oesophagus, stomach, and intestine. Then, the oesophagus was divided into five (first to fifth), the stomach into two (cardiac and pyloric), and the intestine into four segments (anterior, intermediate, posterior, and rectum) for histological examinations. The stomach had significantly taller villi and thicker inner circular muscles compared to the intestine and oesophagus. The lamina propria was thickest in stomach, significantly when compared with oesophagus, but not with the intestine. However, the intestine showed significantly thicker outer longitudinal muscle while gastric glands were observed only in the stomach. The histological features were closely associated with the functions of the different segments of the gastrointestinal tract. In conclusion, the histological features of the gastrointestinal tract of A. b. bicolor are consistent with the feeding habit of a carnivorous fish. PMID:25587561

MolabIS--an integrated information system for storing and managing molecular genetics data.

PubMed

Truong, Cong V C; Groeneveld, Linn F; Morgenstern, Burkhard; Groeneveld, Eildert

2011-10-31

Long-term sample storage, tracing of data flow and data export for subsequent analyses are of great importance in genetics studies. Therefore, molecular labs do need a proper information system to handle an increasing amount of data from different projects. We have developed a molecular labs information management system (MolabIS). It was implemented as a web-based system allowing the users to capture original data at each step of their workflow. MolabIS provides essential functionality for managing information on individuals, tracking samples and storage locations, capturing raw files, importing final data from external files, searching results, accessing and modifying data. Further important features are options to generate ready-to-print reports and convert sequence and microsatellite data into various data formats, which can be used as input files in subsequent analyses. Moreover, MolabIS also provides a tool for data migration. MolabIS is designed for small-to-medium sized labs conducting Sanger sequencing and microsatellite genotyping to store and efficiently handle a relative large amount of data. MolabIS not only helps to avoid time consuming tasks but also ensures the availability of data for further analyses. The software is packaged as a virtual appliance which can run on different platforms (e.g. Linux, Windows). MolabIS can be distributed to a wide range of molecular genetics labs since it was developed according to a general data model. Released under GPL, MolabIS is freely available at http://www.molabis.org.

MolabIS - An integrated information system for storing and managing molecular genetics data

PubMed Central

2011-01-01

Background Long-term sample storage, tracing of data flow and data export for subsequent analyses are of great importance in genetics studies. Therefore, molecular labs do need a proper information system to handle an increasing amount of data from different projects. Results We have developed a molecular labs information management system (MolabIS). It was implemented as a web-based system allowing the users to capture original data at each step of their workflow. MolabIS provides essential functionality for managing information on individuals, tracking samples and storage locations, capturing raw files, importing final data from external files, searching results, accessing and modifying data. Further important features are options to generate ready-to-print reports and convert sequence and microsatellite data into various data formats, which can be used as input files in subsequent analyses. Moreover, MolabIS also provides a tool for data migration. Conclusions MolabIS is designed for small-to-medium sized labs conducting Sanger sequencing and microsatellite genotyping to store and efficiently handle a relative large amount of data. MolabIS not only helps to avoid time consuming tasks but also ensures the availability of data for further analyses. The software is packaged as a virtual appliance which can run on different platforms (e.g. Linux, Windows). MolabIS can be distributed to a wide range of molecular genetics labs since it was developed according to a general data model. Released under GPL, MolabIS is freely available at http://www.molabis.org. PMID:22040322

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets

PubMed Central

Kutchukian, Peter S.; Li, Jing; Tudor, Matthew

2017-01-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound’s high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data. PMID:28182661

Measurement of glucose concentration by image processing of thin film slides

NASA Astrophysics Data System (ADS)

Piramanayagam, Sankaranaryanan; Saber, Eli; Heavner, David

2012-02-01

Measurement of glucose concentration is important for diagnosis and treatment of diabetes mellitus and other medical conditions. This paper describes a novel image-processing based approach for measuring glucose concentration. A fluid drop (patient sample) is placed on a thin film slide. Glucose, present in the sample, reacts with reagents on the slide to produce a color dye. The color intensity of the dye formed varies with glucose at different concentration levels. Current methods use spectrophotometry to determine the glucose level of the sample. Our proposed algorithm uses an image of the slide, captured at a specific wavelength, to automatically determine glucose concentration. The algorithm consists of two phases: training and testing. Training datasets consist of images at different concentration levels. The dye-occupied image region is first segmented using a Hough based technique and then an intensity based feature is calculated from the segmented region. Subsequently, a mathematical model that describes a relationship between the generated feature values and the given concentrations is obtained. During testing, the dye region of a test slide image is segmented followed by feature extraction. These two initial steps are similar to those done in training. However, in the final step, the algorithm uses the model (feature vs. concentration) obtained from the training and feature generated from test image to predict the unknown concentration. The performance of the image-based analysis was compared with that of a standard glucose analyzer.

Characterizing nanoscale topography of the aortic heart valve basement membrane for tissue engineering heart valve scaffold design.

PubMed

Brody, Sarah; Anilkumar, Thapasimuthu; Liliensiek, Sara; Last, Julie A; Murphy, Christopher J; Pandit, Abhay

2006-02-01

A fully effective prosthetic heart valve has not yet been developed. A successful tissue-engineered valve prosthetic must contain a scaffold that fully supports valve endothelial cell function. Recently, topographic features of scaffolds have been shown to influence the behavior of a variety of cell types and should be considered in rational scaffold design and fabrication. The basement membrane of the aortic valve endothelium provides important parameters for tissue engineering scaffold design. This study presents a quantitative characterization of the topographic features of the native aortic valve endothelial basement membrane; topographical features were measured, and quantitative data were generated using scanning electron microscopy (SEM), atomic force microscopy (AFM), transmission electron microscopy (TEM), and light microscopy. Optimal conditions for basement membrane isolation were established. Histological, immunohistochemical, and TEM analyses following decellularization confirmed basement membrane integrity. SEM and AFM photomicrographs of isolated basement membrane were captured and quantitatively analyzed. The basement membrane of the aortic valve has a rich, felt-like, 3-D nanoscale topography, consisting of pores, fibers, and elevations. All features measured were in the sub-100 nm range. No statistical difference was found between the fibrosal and ventricular surfaces of the cusp. These data provide a rational starting point for the design of extracellular scaffolds with nanoscale topographic features that mimic those found in the native aortic heart valve basement membrane.

Characterizing Nanoscale Topography of the Aortic Heart Valve Basement Membrane for Tissue Engineering Heart Valve Scaffold Design

PubMed Central

BRODY, SARAH; ANILKUMAR, THAPASIMUTHU; LILIENSIEK, SARA; LAST, JULIE A.; MURPHY, CHRISTOPHER J.; PANDIT, ABHAY

2016-01-01

A fully effective prosthetic heart valve has not yet been developed. A successful tissue-engineered valve prosthetic must contain a scaffold that fully supports valve endothelial cell function. Recently, topographic features of scaffolds have been shown to influence the behavior of a variety of cell types and should be considered in rational scaffold design and fabrication. The basement membrane of the aortic valve endothelium provides important parameters for tissue engineering scaffold design. This study presents a quantitative characterization of the topographic features of the native aortic valve endothelial basement membrane; topographical features were measured, and quantitative data were generated using scanning electron microscopy (SEM), atomic force microscopy (AFM), transmission electron microscopy (TEM), and light microscopy. Optimal conditions for basement membrane isolation were established. Histological, immunohistochemical, and TEM analyses following decellularization confirmed basement membrane integrity. SEM and AFM photomicrographs of isolated basement membrane were captured and quantitatively analyzed. The basement membrane of the aortic valve has a rich, felt-like, 3-D nanoscale topography, consisting of pores, fibers, and elevations. All features measured were in the sub-100 nm range. No statistical difference was found between the fibrosal and ventricular surfaces of the cusp. These data provide a rational starting point for the design of extracellular scaffolds with nanoscale topographic features that mimic those found in the native aortic heart valve basement membrane. PMID:16548699

System, Apparatus, and Method for Active Debris Removal

NASA Technical Reports Server (NTRS)

Hickey, Christopher J. (Inventor); Spehar, Peter T. (Inventor); Griffith, Sr., Anthony D. (Inventor); Kohli, Rajiv (Inventor); Burns, Susan H. (Inventor); Gruber, David J. (Inventor); Lee, David E. (Inventor); Robinson, Travis M. (Inventor); Damico, Stephen J. (Inventor); Smith, Jason T. (Inventor)

2017-01-01

Systems, apparatuses, and methods for removal of orbital debris are provided. In one embodiment, an apparatus includes a spacecraft control unit configured to guide and navigate the apparatus to a target. The apparatus also includes a dynamic object characterization unit configured to characterize movement, and a capture feature, of the target. The apparatus further includes a capture and release unit configured to capture a target and deorbit or release the target. The collection of these apparatuses is then employed as multiple, independent and individually operated vehicles launched from a single launch vehicle for the purpose of disposing of multiple debris objects.

Hands-Free Image Capture, Data Tagging and Transfer Using Google Glass: A Pilot Study for Improved Wound Care Management

PubMed Central

Aldaz, Gabriel; Shluzas, Lauren Aquino; Pickham, David; Eris, Ozgur; Sadler, Joel; Joshi, Shantanu; Leifer, Larry

2015-01-01

Chronic wounds, including pressure ulcers, compromise the health of 6.5 million Americans and pose an annual estimated burden of $25 billion to the U.S. health care system. When treating chronic wounds, clinicians must use meticulous documentation to determine wound severity and to monitor healing progress over time. Yet, current wound documentation practices using digital photography are often cumbersome and labor intensive. The process of transferring photos into Electronic Medical Records (EMRs) requires many steps and can take several days. Newer smartphone and tablet-based solutions, such as Epic Haiku, have reduced EMR upload time. However, issues still exist involving patient positioning, image-capture technique, and patient identification. In this paper, we present the development and assessment of the SnapCap System for chronic wound photography. Through leveraging the sensor capabilities of Google Glass, SnapCap enables hands-free digital image capture, and the tagging and transfer of images to a patient’s EMR. In a pilot study with wound care nurses at Stanford Hospital (n=16), we (i) examined feature preferences for hands-free digital image capture and documentation, and (ii) compared SnapCap to the state of the art in digital wound care photography, the Epic Haiku application. We used the Wilcoxon Signed-ranks test to evaluate differences in mean ranks between preference options. Preferred hands-free navigation features include barcode scanning for patient identification, Z(15) = -3.873, p < 0.001, r = 0.71, and double-blinking to take photographs, Z(13) = -3.606, p < 0.001, r = 0.71. In the comparison between SnapCap and Epic Haiku, the SnapCap System was preferred for sterile image-capture technique, Z(16) = -3.873, p < 0.001, r = 0.68. Responses were divided with respect to image quality and overall ease of use. The study’s results have contributed to the future implementation of new features aimed at enhancing mobile hands-free digital photography for chronic wound care. PMID:25902061

ASI aurora search: an attempt of intelligent image processing for circular fisheye lens.

PubMed

Yang, Xi; Gao, Xinbo; Song, Bin; Wang, Nannan; Yang, Dong

2018-04-02

The circular fisheye lens exhibits an approximately 180° angular field-of-view (FOV), which is much larger than that of an ordinary lens. Thus, images captured with a circular fisheye lens are distributed non-uniformly with spherical deformation. Along with the fast development of deep neural networks for normal images, how to apply it to achieve intelligent image processing for a circular fisheye lens is a new task of significant importance. In this paper, we take the aurora images captured with all-sky-imagers (ASI) as a typical example. By analyzing the imaging principle of ASI and the magnetic characteristics of the aurora, a deformed region division (DRD) scheme is proposed to replace the region proposals network (RPN) in the advanced mask regional convolutional neural network (Mask R-CNN) framework. Thus, each image can be regarded as a "bag" of deformed regions represented with CNN features. After clustering all CNN features to generate a vocabulary, each deformed region is quantified to its nearest center for indexing. On the stage of an online search, a similarity score is computed by measuring the distances between regions in the query image and all regions in the data set, and the image with the highest value is outputted as the top rank search result. Experimental results show that the proposed method greatly improves the search accuracy and efficiency, demonstrating that it is a valuable attempt of intelligent image processing for circular fisheye lenses.

End-to-End Multimodal Emotion Recognition Using Deep Neural Networks

NASA Astrophysics Data System (ADS)

Tzirakis, Panagiotis; Trigeorgis, George; Nicolaou, Mihalis A.; Schuller, Bjorn W.; Zafeiriou, Stefanos

2017-12-01

Automatic affect recognition is a challenging task due to the various modalities emotions can be expressed with. Applications can be found in many domains including multimedia retrieval and human computer interaction. In recent years, deep neural networks have been used with great success in determining emotional states. Inspired by this success, we propose an emotion recognition system using auditory and visual modalities. To capture the emotional content for various styles of speaking, robust features need to be extracted. To this purpose, we utilize a Convolutional Neural Network (CNN) to extract features from the speech, while for the visual modality a deep residual network (ResNet) of 50 layers. In addition to the importance of feature extraction, a machine learning algorithm needs also to be insensitive to outliers while being able to model the context. To tackle this problem, Long Short-Term Memory (LSTM) networks are utilized. The system is then trained in an end-to-end fashion where - by also taking advantage of the correlations of the each of the streams - we manage to significantly outperform the traditional approaches based on auditory and visual handcrafted features for the prediction of spontaneous and natural emotions on the RECOLA database of the AVEC 2016 research challenge on emotion recognition.

Abundance, survival, recruitment and effectiveness of sterilization of free-roaming dogs: A capture and recapture study in Brazil

PubMed Central

Struchiner, Claudio José; Werneck, Guilherme Loureiro; Teixeira Neto, Rafael Gonçalves; Tonelli, Gabriel Barbosa; de Carvalho Júnior, Clóvis Gomes; Ribeiro, Renata Aparecida Nascimento; da Silva, Eduardo Sérgio

2017-01-01

The existence of free-roaming dogs raises important issues in animal welfare and in public health. A proper understanding of these animals’ ecology is useful as a necessary input to plan strategies to control these populations. The present study addresses the population dynamics and the effectiveness of the sterilization of unrestricted dogs using capture and recapture procedures suitable for open animal populations. Every two months, over a period of 14 months, we captured, tagged, released and recaptured dogs in two regions in a city in the southeast region of Brazil. In one of these regions the animals were also sterilized. Both regions had similar social, environmental and demographic features. We estimated the presence of 148 females and 227 males during the period of study. The average dog:man ratio was 1 dog for each 42 and 51 human beings, in the areas without and with sterilization, respectively. The animal population size increased in both regions, due mainly to the abandonment of domestic dogs. Mortality rate decreased throughout the study period. Survival probabilities did not differ between genders, but males entered the population in higher numbers. There were no differences in abundance, survival and recruitment between the regions, indicating that sterilization did not affect the population dynamics. Our findings indicate that the observed animal dynamics were influenced by density-independent factors, and that sterilization might not be a viable and effective strategy in regions where availability of resources is low and animal abandonment rates are high. Furthermore, the high demographic turnover rates observed render the canine free-roaming population younger, thus more susceptible to diseases, especially to rabies and leishmaniasis. We conclude by stressing the importance of implementing educational programs to promote responsible animal ownership and effective strategies against abandonment practices. PMID:29091961

Abundance, survival, recruitment and effectiveness of sterilization of free-roaming dogs: A capture and recapture study in Brazil.

PubMed

Belo, Vinícius Silva; Struchiner, Claudio José; Werneck, Guilherme Loureiro; Teixeira Neto, Rafael Gonçalves; Tonelli, Gabriel Barbosa; de Carvalho Júnior, Clóvis Gomes; Ribeiro, Renata Aparecida Nascimento; da Silva, Eduardo Sérgio

2017-01-01

The existence of free-roaming dogs raises important issues in animal welfare and in public health. A proper understanding of these animals' ecology is useful as a necessary input to plan strategies to control these populations. The present study addresses the population dynamics and the effectiveness of the sterilization of unrestricted dogs using capture and recapture procedures suitable for open animal populations. Every two months, over a period of 14 months, we captured, tagged, released and recaptured dogs in two regions in a city in the southeast region of Brazil. In one of these regions the animals were also sterilized. Both regions had similar social, environmental and demographic features. We estimated the presence of 148 females and 227 males during the period of study. The average dog:man ratio was 1 dog for each 42 and 51 human beings, in the areas without and with sterilization, respectively. The animal population size increased in both regions, due mainly to the abandonment of domestic dogs. Mortality rate decreased throughout the study period. Survival probabilities did not differ between genders, but males entered the population in higher numbers. There were no differences in abundance, survival and recruitment between the regions, indicating that sterilization did not affect the population dynamics. Our findings indicate that the observed animal dynamics were influenced by density-independent factors, and that sterilization might not be a viable and effective strategy in regions where availability of resources is low and animal abandonment rates are high. Furthermore, the high demographic turnover rates observed render the canine free-roaming population younger, thus more susceptible to diseases, especially to rabies and leishmaniasis. We conclude by stressing the importance of implementing educational programs to promote responsible animal ownership and effective strategies against abandonment practices.

Standardized observation of neighbourhood disorder: does it work in Canada?

PubMed Central

2010-01-01

Background There is a growing body of evidence that where you live is important to your health. Despite numerous previous studies investigating the relationship between neighbourhood deprivation (and structure) and residents' health, the precise nature of this relationship remains unclear. Relatively few investigations have relied on direct observation of neighbourhoods, while those that have were developed primarily in US settings. Evaluation of the transferability of such tools to other contexts is an important first step before applying such instruments to the investigation of health and well-being. This study evaluated the performance of a systematic social observational (SSO) tool (adapted from previous studies of American and British neighbourhoods) in a Canadian urban context. Methods This was a mixed-methods study. Quantitative SSO ratings and qualitative descriptions of 176 block faces were obtained in six Toronto neighbourhoods (4 low-income, and 2 middle/high-income) by trained raters. Exploratory factor analysis was conducted with the quantitative SSO ratings. Content analysis consisted of independent coding of qualitative data by three members of the research team to yield common themes and categories. Results Factor analysis identified three factors (physical decay/disorder, social accessibility, recreational opportunities), but only 'physical decay/disorder' reflected previous findings in the literature. Qualitative results (based on raters' fieldwork experiences) revealed the tool's shortcomings in capturing important features of the neighbourhoods under study, and informed interpretation of the quantitative findings. Conclusions This study tested the performance of an SSO tool in a Canadian context, which is an important initial step before applying it to the study of health and disease. The tool demonstrated important shortcomings when applied to six diverse Toronto neighbourhoods. The study's analyses challenge previously held assumptions (e.g. social 'disorder') regarding neighbourhood social and built environments. For example, neighbourhood 'order' has traditionally been assumed to be synonymous with a certain degree of homogeneity, however the neighbourhoods under study were characterized by high degrees of heterogeneity and low levels of disorder. Heterogeneity was seen as an appealing feature of a block face. Employing qualitative techniques with SSO represents a unique contribution, enhancing both our understanding of the quantitative ratings obtained and of neighbourhood characteristics that are not currently captured by such instruments. PMID:20146821

The Effects of Goal Relevance and Perceptual Features on Emotional Items and Associative Memory

PubMed Central

Mao, Wei B.; An, Shu; Yang, Xiao F.

2017-01-01

Showing an emotional item in a neutral background scene often leads to enhanced memory for the emotional item and impaired associative memory for background details. Meanwhile, both top–down goal relevance and bottom–up perceptual features played important roles in memory binding. We conducted two experiments and aimed to further examine the effects of goal relevance and perceptual features on emotional items and associative memory. By manipulating goal relevance (asking participants to categorize only each item image as living or non-living or to categorize each whole composite picture consisted of item image and background scene as natural scene or manufactured scene) and perceptual features (controlling visual contrast and visual familiarity) in two experiments, we found that both high goal relevance and salient perceptual features (high salience of items vs. high familiarity of items) could promote emotional item memory, but they had different effects on associative memory for emotional items and neutral backgrounds. Specifically, high goal relevance and high perceptual-salience of items could jointly impair the associative memory for emotional items and neutral backgrounds, while the effect of item familiarity on associative memory for emotional items would be modulated by goal relevance. High familiarity of items could increase associative memory for negative items and neutral backgrounds only in the low goal relevance condition. These findings suggest the effect of emotion on associative memory is not only related to attentional capture elicited by emotion, but also can be affected by goal relevance and perceptual features of stimulus. PMID:28790943

The Effects of Goal Relevance and Perceptual Features on Emotional Items and Associative Memory.

PubMed

Mao, Wei B; An, Shu; Yang, Xiao F

2017-01-01

Showing an emotional item in a neutral background scene often leads to enhanced memory for the emotional item and impaired associative memory for background details. Meanwhile, both top-down goal relevance and bottom-up perceptual features played important roles in memory binding. We conducted two experiments and aimed to further examine the effects of goal relevance and perceptual features on emotional items and associative memory. By manipulating goal relevance (asking participants to categorize only each item image as living or non-living or to categorize each whole composite picture consisted of item image and background scene as natural scene or manufactured scene) and perceptual features (controlling visual contrast and visual familiarity) in two experiments, we found that both high goal relevance and salient perceptual features (high salience of items vs. high familiarity of items) could promote emotional item memory, but they had different effects on associative memory for emotional items and neutral backgrounds. Specifically, high goal relevance and high perceptual-salience of items could jointly impair the associative memory for emotional items and neutral backgrounds, while the effect of item familiarity on associative memory for emotional items would be modulated by goal relevance. High familiarity of items could increase associative memory for negative items and neutral backgrounds only in the low goal relevance condition. These findings suggest the effect of emotion on associative memory is not only related to attentional capture elicited by emotion, but also can be affected by goal relevance and perceptual features of stimulus.

Setting semantics: conceptual set can determine the physical properties that capture attention.

PubMed

Goodhew, Stephanie C; Kendall, William; Ferber, Susanne; Pratt, Jay

2014-08-01

The ability of a stimulus to capture visuospatial attention depends on the interplay between its bottom-up saliency and its relationship to an observer's top-down control set, such that stimuli capture attention if they match the predefined properties that distinguish a searched-for target from distractors (Folk, Remington, & Johnston, Journal of Experimental Psychology: Human Perception & Performance, 18, 1030-1044 1992). Despite decades of research on this phenomenon, however, the vast majority has focused exclusively on matches based on low-level physical properties. Yet if contingent capture is indeed a "top-down" influence on attention, then semantic content should be accessible and able to determine which physical features capture attention. Here we tested this prediction by examining whether a semantically defined target could create a control set for particular features. To do this, we had participants search to identify a target that was differentiated from distractors by its meaning (e.g., the word "red" among color words all written in black). Before the target array, a cue was presented, and it was varied whether the cue appeared in the physical color implied by the target word. Across three experiments, we found that cues that embodied the meaning of the word produced greater cuing than cues that did not. This suggests that top-down control sets activate content that is semantically associated with the target-defining property, and this content in turn has the ability to exogenously orient attention.

Do little interactions get lost in dark random forests?

PubMed

Wright, Marvin N; Ziegler, Andreas; König, Inke R

2016-03-31

Random forests have often been claimed to uncover interaction effects. However, if and how interaction effects can be differentiated from marginal effects remains unclear. In extensive simulation studies, we investigate whether random forest variable importance measures capture or detect gene-gene interactions. With capturing interactions, we define the ability to identify a variable that acts through an interaction with another one, while detection is the ability to identify an interaction effect as such. Of the single importance measures, the Gini importance captured interaction effects in most of the simulated scenarios, however, they were masked by marginal effects in other variables. With the permutation importance, the proportion of captured interactions was lower in all cases. Pairwise importance measures performed about equal, with a slight advantage for the joint variable importance method. However, the overall fraction of detected interactions was low. In almost all scenarios the detection fraction in a model with only marginal effects was larger than in a model with an interaction effect only. Random forests are generally capable of capturing gene-gene interactions, but current variable importance measures are unable to detect them as interactions. In most of the cases, interactions are masked by marginal effects and interactions cannot be differentiated from marginal effects. Consequently, caution is warranted when claiming that random forests uncover interactions.

Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity

PubMed Central

Albantakis, Larissa; Hintze, Arend; Koch, Christof; Adami, Christoph; Tononi, Giulio

2014-01-01

Natural selection favors the evolution of brains that can capture fitness-relevant features of the environment's causal structure. We investigated the evolution of small, adaptive logic-gate networks (“animats”) in task environments where falling blocks of different sizes have to be caught or avoided in a ‘Tetris-like’ game. Solving these tasks requires the integration of sensor inputs and memory. Evolved networks were evaluated using measures of information integration, including the number of evolved concepts and the total amount of integrated conceptual information. The results show that, over the course of the animats' adaptation, i) the number of concepts grows; ii) integrated conceptual information increases; iii) this increase depends on the complexity of the environment, especially on the requirement for sequential memory. These results suggest that the need to capture the causal structure of a rich environment, given limited sensors and internal mechanisms, is an important driving force for organisms to develop highly integrated networks (“brains”) with many concepts, leading to an increase in their internal complexity. PMID:25521484

Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

PubMed

Wilson, Paul; Larminie, Christopher; Smith, Rona

2016-01-01

To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

Texture as a basis for acoustic classification of substrate in the nearshore region

NASA Astrophysics Data System (ADS)

Dennison, A.; Wattrus, N. J.

2016-12-01

Segmentation and classification of substrate type from two locations in Lake Superior, are predicted using multivariate statistical processing of textural measures derived from shallow-water, high-resolution multibeam bathymetric data. During a multibeam sonar survey, both bathymetric and backscatter data are collected. It is well documented that the statistical characteristic of a sonar backscatter mosaic is dependent on substrate type. While classifying the bottom-type on the basis on backscatter alone can accurately predict and map bottom-type, it lacks the ability to resolve and capture fine textural details, an important factor in many habitat mapping studies. Statistical processing can capture the pertinent details about the bottom-type that are rich in textural information. Further multivariate statistical processing can then isolate characteristic features, and provide the basis for an accurate classification scheme. Preliminary results from an analysis of bathymetric data and ground-truth samples collected from the Amnicon River, Superior, Wisconsin, and the Lester River, Duluth, Minnesota, demonstrate the ability to process and develop a novel classification scheme of the bottom type in two geomorphologically distinct areas.

Information recovery through image sequence fusion under wavelet transformation

NASA Astrophysics Data System (ADS)

He, Qiang

2010-04-01

Remote sensing is widely applied to provide information of areas with limited ground access with applications such as to assess the destruction from natural disasters and to plan relief and recovery operations. However, the data collection of aerial digital images is constrained by bad weather, atmospheric conditions, and unstable camera or camcorder. Therefore, how to recover the information from the low-quality remote sensing images and how to enhance the image quality becomes very important for many visual understanding tasks, such like feature detection, object segmentation, and object recognition. The quality of remote sensing imagery can be improved through meaningful combination of the employed images captured from different sensors or from different conditions through information fusion. Here we particularly address information fusion to remote sensing images under multi-resolution analysis in the employed image sequences. The image fusion is to recover complete information by integrating multiple images captured from the same scene. Through image fusion, a new image with high-resolution or more perceptive for human and machine is created from a time series of low-quality images based on image registration between different video frames.

Modeling association among demographic parameters in analysis of open population capture-recapture data.

PubMed

Link, William A; Barker, Richard J

2005-03-01

We present a hierarchical extension of the Cormack-Jolly-Seber (CJS) model for open population capture-recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis-Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Age Mediation of Frontoparietal Activation during Visual Feature Search

PubMed Central

Madden, David J.; Parks, Emily L.; Davis, Simon W.; Diaz, Michele T.; Potter, Guy G.; Chou, Ying-hui; Chen, Nan-kuei; Cabeza, Roberto

2014-01-01

Activation of frontal and parietal brain regions is associated with attentional control during visual search. We used fMRI to characterize age-related differences in frontoparietal activation in a highly efficient feature search task, detection of a shape singleton. On half of the trials, a salient distractor (a color singleton) was present in the display. The hypothesis was that frontoparietal activation mediated the relation between age and attentional capture by the salient distractor. Participants were healthy, community-dwelling individuals, 21 younger adults (19 – 29 years of age) and 21 older adults (60 – 87 years of age). Top-down attention, in the form of target predictability, was associated with an improvement in search performance that was comparable for younger and older adults. The increase in search reaction time (RT) associated with the salient distractor (attentional capture), standardized to correct for generalized age-related slowing, was greater for older adults than for younger adults. On trials with a color singleton distractor, search RT increased as a function of increasing activation in frontal regions, for both age groups combined, suggesting increased task difficulty. Mediational analyses disconfirmed the hypothesized model, in which frontal activation mediated the age-related increase in attentional capture, but supported an alternative model in which age was a mediator of the relation between frontal activation and capture. PMID:25102420

Context-dependent control of attention capture: Evidence from proportion congruent effects.

PubMed

Crump, Matthew J C; Milliken, Bruce; Leboe-McGowan, Jason; Leboe-McGowan, Launa; Gao, Xiaoqing

2018-06-01

There are several independent demonstrations that attentional phenomena can be controlled in a context-dependent manner by cues associated with differing attentional control demands. The present set of experiments provide converging evidence that attention-capture phenomena can be modulated in a context-dependent fashion. We determined whether methods from the proportion congruent literature (listwide and item- and context-specific proportion congruent designs) that are known to modulate distractor interference effects in Stroop and flanker tasks are capable of modulating attention capture by salient feature singletons. Across experiments we found evidence that attention capture can be modulated by listwide, item-specific, and context-specific manipulations of proportion congruent. We discuss challenges associated with interpreting results from proportion congruent studies but propose that our findings converge with existing work that has demonstrated context-dependent control of attention capture. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Effects of Reduced Terrestrial LiDAR Point Density on High-Resolution Grain Crop Surface Models in Precision Agriculture

PubMed Central

Hämmerle, Martin; Höfle, Bernhard

2014-01-01

3D geodata play an increasingly important role in precision agriculture, e.g., for modeling in-field variations of grain crop features such as height or biomass. A common data capturing method is LiDAR, which often requires expensive equipment and produces large datasets. This study contributes to the improvement of 3D geodata capturing efficiency by assessing the effect of reduced scanning resolution on crop surface models (CSMs). The analysis is based on high-end LiDAR point clouds of grain crop fields of different varieties (rye and wheat) and nitrogen fertilization stages (100%, 50%, 10%). Lower scanning resolutions are simulated by keeping every n-th laser beam with increasing step widths n. For each iteration step, high-resolution CSMs (0.01 m2 cells) are derived and assessed regarding their coverage relative to a seamless CSM derived from the original point cloud, standard deviation of elevation and mean elevation. Reducing the resolution to, e.g., 25% still leads to a coverage of >90% and a mean CSM elevation of >96% of measured crop height. CSM types (maximum elevation or 90th-percentile elevation) react differently to reduced scanning resolutions in different crops (variety, density). The results can help to assess the trade-off between CSM quality and minimum requirements regarding equipment and capturing set-up. PMID:25521383

Aquatic prey capture in snakes: the link between morphology, behavior and hydrodynamics

NASA Astrophysics Data System (ADS)

Segall, Marion; Herrel, Anthony; Godoy-Diana, Ramiro; Funevol Team; Pmmh Team

2017-11-01

Natural selection favors animals that are the most successful in their fitness-related behaviors, such as foraging. Secondary adaptations pose the problem of re-adapting an already 'hypothetically optimized' phenotype to new constraints. When animals forage underwater, they face strong physical constraints, particularly when capturing a prey. The capture requires the predator to be fast and to generate a high acceleration to catch the prey. This involves two main constraints due to the surrounding fluid: drag and added mass. Both of these constraints are related to the shape of the animal. We experimentally explore the relationship between shape and performance in the context of an aquatic strike. As a model, we use 3D-printed snake heads of different shapes and frontal strike kinematics based on in vivo observations. By using direct force measurements, we compare the drag and added mass generated by aquatic and non-aquatic snake models during a strike. Our results show that drag is optimized in aquatic snakes. Added mass appears less important than drag for snakes during an aquatic strike. The flow features associated to the hydrodynamic forces measured allows us to propose a mechanism rendering the shape of the head of aquatic snakes well adapted to catch prey underwater. Region Ile de France and the doctoral school Frontieres du Vivant (FdV) - Programme Bettencourt.

The 2012 Atomic Mass Evaluation and the Mass Tables

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

Audi, G., E-mail: amdc.audi@gmail.com; Wang, M.; MPI-K, D-69117 Heidelberg

The new evaluation of the Atomic Masses, Ame2012, has just been released. It represents a major step in the history of the 60 year old Atomic Mass Evaluation based on the method developed by Wapstra. This new publication includes all material available to date. Some of the policies and procedures used in our evaluation are reported, together with an illustration of one specially difficult case, the energy available for the {sup 102}Pd double-electron capture. The observation of the mass surface reveals many important new features. We illustrate this statement by the double magicity of {sup 270}Hs at N = 162more » and Z = 108.« less

Moving beyond Watson-Crick models of coarse grained DNA dynamics.

PubMed

Linak, Margaret C; Tourdot, Richard; Dorfman, Kevin D

2011-11-28

DNA produces a wide range of structures in addition to the canonical B-form of double-stranded DNA. Some of these structures are stabilized by Hoogsteen bonds. We developed an experimentally parameterized, coarse-grained model that incorporates such bonds. The model reproduces many of the microscopic features of double-stranded DNA and captures the experimental melting curves for a number of short DNA hairpins, even when the open state forms complicated secondary structures. We demonstrate the utility of the model by simulating the folding of a thrombin aptamer, which contains G-quartets, and strand invasion during triplex formation. Our results highlight the importance of including Hoogsteen bonding in coarse-grained models of DNA.

Out of control: attentional selection for orientation is thwarted by properties of the underlying neural mechanisms.

PubMed

Du, Feng; Abrams, Richard A

2012-09-01

To avoid sensory overload, people are able to selectively attend to a particular color or direction of motion while ignoring irrelevant stimuli that differ from the desired one. We show here for the first time that it is also possible to selectively attend to a specific line orientation-but with an important caveat: orientations that are perpendicular to the target orientation cannot be suppressed. This effect reflects properties of the neural mechanisms selective for orientation and reveals the extent to which contingent capture is constrained not only by one's top-down goals but also by feature preferences of visual neurons. Copyright © 2012 Elsevier B.V. All rights reserved.

Incorporating heterogeneity into the transmission dynamics of a waterborne disease model.

PubMed

Collins, O C; Govinder, K S

2014-09-07

We formulate a mathematical model that captures the essential dynamics of waterborne disease transmission to study the effects of heterogeneity on the spread of the disease. The effects of heterogeneity on some important mathematical features of the model such as the basic reproduction number, type reproduction number and final outbreak size are analysed accordingly. We conduct a real-world application of this model by using it to investigate the heterogeneity in transmission in the recent cholera outbreak in Haiti. By evaluating the measure of heterogeneity between the administrative departments in Haiti, we discover a significant difference in the dynamics of the cholera outbreak between the departments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reward and attentional control in visual search.

PubMed

Yantis, Steven; Anderson, Brian A; Wampler, Emma K; Laurent, Patryk A

2012-01-01

It has long been known that the control of attention in visual search depends both on voluntary, top-down deployment according to context-specific goals, and on involuntary, stimulus-driven capture based on the physical conspicuity of perceptual objects. Recent evidence suggests that pairing target stimuli with reward can modulate the voluntary deployment of attention, but there is little evidence that reward modulates the involuntary deployment of attention to task-irrelevant distractors. We report several experiments that investigate the role of reward learning on attentional control. Each experiment involved a training phase and a test phase. In the training phase, different colors were associated with different amounts of monetary reward. In the test phase, color was not task-relevant and participants searched for a shape singleton; in most experiments no reward was delivered in the test phase. We first show that attentional capture by physically salient distractors is magnified by a previous association with reward. In subsequent experiments we demonstrate that physically inconspicuous stimuli previously associated with reward capture attention persistently during extinction--even several days after training. Furthermore, vulnerability to attentional capture by high-value stimuli is negatively correlated across individuals with working memory capacity and positively correlated with trait impulsivity. An analysis of intertrial effects reveals that value-driven attentional capture is spatially specific. Finally, when reward is delivered at test contingent on the task-relevant shape feature, recent reward history modulates value-driven attentional capture by the irrelevant color feature. The influence of learned value on attention may provide a useful model of clinical syndromes characterized by similar failures of cognitive control, including addiction, attention-deficit/hyperactivity disorder, and obesity.

Near-Ultraviolet Observations of CS 29497-030: New Constraints on Neutron-Capture Nucleosynthesis Processes

NASA Astrophysics Data System (ADS)

Ivans, Inese I.; Sneden, Christopher; Gallino, Roberto; Cowan, John J.; Preston, George W.

2005-07-01

Employing spectra obtained with the new Keck I HIRES near-UV-sensitive detector, we have performed a comprehensive chemical composition analysis of the binary blue metal-poor star CS 29497-030. Abundances for 29 elements and upper limits for an additional seven have been derived, concentrating on elements largely produced by means of neutron-capture nucleosynthesis. Included in our analysis are the two elements that define the termination point of the slow neutron-capture process, lead and bismuth. We determine an extremely high value of [Pb/Fe]=+3.65+/-0.07 (σ=0.13) from three features, supporting the single-feature result obtained in previous studies. We detect Bi for the first time in a metal-poor star. Our derived Bi/Pb ratio is in accord with those predicted from the most recent FRANEC calculations of the slow neutron-capture process in low-mass asymptotic giant branch (AGB) stars. We find that the neutron-capture elemental abundances of CS 29497-030 are best explained by an AGB model that also includes very significant amounts of pre-enrichment of rapid neutron-capture process material in the protostellar cloud out of which the CS 29497-030 binary system formed. Mass transfer is consistent with the observed [Nb/Zr]~0. Thus, CS 29497-030 is both an r+s and ``extrinsic AGB'' star. Furthermore, we find that the mass of the AGB model can be further constrained by the abundance of the light odd-element Na. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Reward and Attentional Control in Visual Search

PubMed Central

Anderson, Brian A.; Wampler, Emma K.; Laurent, Patryk A.

2015-01-01

It has long been known that the control of attention in visual search depends both on voluntary, top-down deployment according to context-specific goals, and on involuntary, stimulus-driven capture based on the physical conspicuity of perceptual objects. Recent evidence suggests that pairing target stimuli with reward can modulate the voluntary deployment of attention, but there is little evidence that reward modulates the involuntary deployment of attention to task-irrelevant distractors. We report several experiments that investigate the role of reward learning on attentional control. Each experiment involved a training phase and a test phase. In the training phase, different colors were associated with different amounts of monetary reward. In the test phase, color was not task-relevant and participants searched for a shape singleton; in most experiments no reward was delivered in the test phase. We first show that attentional capture by physically salient distractors is magnified by a previous association with reward. In subsequent experiments we demonstrate that physically inconspicuous stimuli previously associated with reward capture attention persistently during extinction—even several days after training. Furthermore, vulnerability to attentional capture by high-value stimuli is negatively correlated across individuals with working memory capacity and positively correlated with trait impulsivity. An analysis of intertrial effects reveals that value-driven attentional capture is spatially specific. Finally, when reward is delivered at test contingent on the task-relevant shape feature, recent reward history modulates value-driven attentional capture by the irrelevant color feature. The influence of learned value on attention may provide a useful model of clinical syndromes characterized by similar failures of cognitive control, including addiction, attention-deficit/hyperactivity disorder, and obesity. PMID:23437631

Detection of Emotional Faces: Salient Physical Features Guide Effective Visual Search

ERIC Educational Resources Information Center

Calvo, Manuel G.; Nummenmaa, Lauri

2008-01-01

In this study, the authors investigated how salient visual features capture attention and facilitate detection of emotional facial expressions. In a visual search task, a target emotional face (happy, disgusted, fearful, angry, sad, or surprised) was presented in an array of neutral faces. Faster detection of happy and, to a lesser extent,…

Your Divided Attention, Please! The Maintenance of Multiple Attentional Control Sets over Distinct Regions in Space

ERIC Educational Resources Information Center

Adamo, Maha; Pun, Carson; Pratt, Jay; Ferber, Susanne

2008-01-01

When non-informative peripheral cues precede a target defined by a specific feature, cues that share the critical feature will capture attention while cues that do not will be effectively ignored. We tested whether different attentional control sets can be simultaneously maintained over distinct regions of space. Participants were instructed to…

Extended behavioural device modelling and circuit simulation with Qucs-S

NASA Astrophysics Data System (ADS)

Brinson, M. E.; Kuznetsov, V.

2018-03-01

Current trends in circuit simulation suggest a growing interest in open source software that allows access to more than one simulation engine while simultaneously supporting schematic drawing tools, behavioural Verilog-A and XSPICE component modelling, and output data post-processing. This article introduces a number of new features recently implemented in the 'Quite universal circuit simulator - SPICE variant' (Qucs-S), including structure and fundamental schematic capture algorithms, at the same time highlighting their use in behavioural semiconductor device modelling. Particular importance is placed on the interaction between Qucs-S schematics, equation-defined devices, SPICE B behavioural sources and hardware description language (HDL) scripts. The multi-simulator version of Qucs is a freely available tool that offers extended modelling and simulation features compared to those provided by legacy circuit simulators. The performance of a number of Qucs-S modelling extensions are demonstrated with a GaN HEMT compact device model and data obtained from tests using the Qucs-S/Ngspice/Xyce ©/SPICE OPUS multi-engine circuit simulator.

ARIES: Acquisition of Requirements and Incremental Evolution of Specifications

NASA Technical Reports Server (NTRS)

Roberts, Nancy A.

1993-01-01

This paper describes a requirements/specification environment specifically designed for large-scale software systems. This environment is called ARIES (Acquisition of Requirements and Incremental Evolution of Specifications). ARIES provides assistance to requirements analysts for developing operational specifications of systems. This development begins with the acquisition of informal system requirements. The requirements are then formalized and gradually elaborated (transformed) into formal and complete specifications. ARIES provides guidance to the user in validating formal requirements by translating them into natural language representations and graphical diagrams. ARIES also provides ways of analyzing the specification to ensure that it is correct, e.g., testing the specification against a running simulation of the system to be built. Another important ARIES feature, especially when developing large systems, is the sharing and reuse of requirements knowledge. This leads to much less duplication of effort. ARIES combines all of its features in a single environment that makes the process of capturing a formal specification quicker and easier.

Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases

NASA Astrophysics Data System (ADS)

Belik, Vitaly; Geisel, Theo; Brockmann, Dirk

2011-08-01

We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: The Fractal Dimensions of Complex Networks

NASA Astrophysics Data System (ADS)

Guo, Long; Cai, XU

2009-08-01

It is shown that many real complex networks share distinctive features, such as the small-world effect and the heterogeneous property of connectivity of vertices, which are different from random networks and regular lattices. Although these features capture the important characteristics of complex networks, their applicability depends on the style of networks. To unravel the universal characteristics many complex networks have in common, we study the fractal dimensions of complex networks using the method introduced by Shanker. We find that the average 'density' (ρ(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df, which is defined as the fractal dimension, in some real complex networks. Furthermore, we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices. Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.

Information technology in the foxhole.

PubMed

Eyestone, S M

1995-08-01

The importance of digital data capture at the point of health care service within the military environment is highlighted. Current paper-based data capture does not allow for efficient data reuse throughout the medical support information domain. A simple, high-level process and data flow model is used to demonstrate the importance of data capture at point of service. The Department of Defense is developing a personal digital assistant, called MEDTAG, that accomplishes point of service data capture in the field using a prototype smart card as a data store in austere environments.

Grid point extraction and coding for structured light system

NASA Astrophysics Data System (ADS)

Song, Zhan; Chung, Ronald

2011-09-01

A structured light system simplifies three-dimensional reconstruction by illuminating a specially designed pattern to the target object, thereby generating a distinct texture on it for imaging and further processing. Success of the system hinges upon what features are to be coded in the projected pattern, extracted in the captured image, and matched between the projector's display panel and the camera's image plane. The codes have to be such that they are largely preserved in the image data upon illumination from the projector, reflection from the target object, and projective distortion in the imaging process. The features also need to be reliably extracted in the image domain. In this article, a two-dimensional pseudorandom pattern consisting of rhombic color elements is proposed, and the grid points between the pattern elements are chosen as the feature points. We describe how a type classification of the grid points plus the pseudorandomness of the projected pattern can equip each grid point with a unique label that is preserved in the captured image. We also present a grid point detector that extracts the grid points without the need of segmenting the pattern elements, and that localizes the grid points in subpixel accuracy. Extensive experiments are presented to illustrate that, with the proposed pattern feature definition and feature detector, more features points in higher accuracy can be reconstructed in comparison with the existing pseudorandomly encoded structured light systems.

Different developmental trajectories across feature types support a dynamic field model of visual working memory development

PubMed Central

Simmering, Vanessa R.; Miller, Hilary E.; Bohache, Kevin

2015-01-01

Research on visual working memory has focused on characterizing the nature of capacity limits as “slots” or “resources” based almost exclusively on adults’ performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to “slot” or “resource” explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children’s (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less-familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model—purportedly arising through experience—can capture differences across feature types. PMID:25737253

Kinematic parameters of signed verbs.

PubMed

Malaia, Evie; Wilbur, Ronnie B; Milkovic, Marina

2013-10-01

Sign language users recruit physical properties of visual motion to convey linguistic information. Research on American Sign Language (ASL) indicates that signers systematically use kinematic features (e.g., velocity, deceleration) of dominant hand motion for distinguishing specific semantic properties of verb classes in production ( Malaia & Wilbur, 2012a) and process these distinctions as part of the phonological structure of these verb classes in comprehension ( Malaia, Ranaweera, Wilbur, & Talavage, 2012). These studies are driven by the event visibility hypothesis by Wilbur (2003), who proposed that such use of kinematic features should be universal to sign language (SL) by the grammaticalization of physics and geometry for linguistic purposes. In a prior motion capture study, Malaia and Wilbur (2012a) lent support for the event visibility hypothesis in ASL, but there has not been quantitative data from other SLs to test the generalization to other languages. The authors investigated the kinematic parameters of predicates in Croatian Sign Language ( Hrvatskom Znakovnom Jeziku [HZJ]). Kinematic features of verb signs were affected both by event structure of the predicate (semantics) and phrase position within the sentence (prosody). The data demonstrate that kinematic features of motion in HZJ verb signs are recruited to convey morphological and prosodic information. This is the first crosslinguistic motion capture confirmation that specific kinematic properties of articulator motion are grammaticalized in other SLs to express linguistic features.

Different developmental trajectories across feature types support a dynamic field model of visual working memory development.

PubMed

Simmering, Vanessa R; Miller, Hilary E; Bohache, Kevin

2015-05-01

Research on visual working memory has focused on characterizing the nature of capacity limits as "slots" or "resources" based almost exclusively on adults' performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to "slot" or "resource" explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children's (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model-purportedly arising through experience-can capture differences across feature types.

A Review of the Structural Characteristics of Family Meals with Children in the United States12

PubMed Central

McCullough, Mary Beth; Robson, Shannon M; Stark, Lori J

2016-01-01

Family meals are associated with a range of positive outcomes among children and adolescents. There is inconsistency, however, in the way in which studies have defined and measured family meals. Therefore, a systematic review of the literature was conducted to determine how studies describe family meals with the use of structural characteristics. The current review focused on studies in the United States that included children ages 2–18 y. A total of 33 studies were identified that characterized family meals with the use of ≥1 of the following structural features: frequency or mean number of family meals per week, length of family meal, people present at meal, and where meals occurred. No study characterized family meals by using all 4 family meal features, whereas most studies (81%) characterized family meals by using frequency or mean number of meals per week. Findings not only provide an initial understanding of the structural features used to define family meals but also point to the importance of developing a more comprehensive, sensitive assessment that can accurately capture the complex and multidimensional nature of family meals. PMID:27422500

A Review of the Structural Characteristics of Family Meals with Children in the United States.

PubMed

McCullough, Mary Beth; Robson, Shannon M; Stark, Lori J

2016-07-01

Family meals are associated with a range of positive outcomes among children and adolescents. There is inconsistency, however, in the way in which studies have defined and measured family meals. Therefore, a systematic review of the literature was conducted to determine how studies describe family meals with the use of structural characteristics. The current review focused on studies in the United States that included children ages 2-18 y. A total of 33 studies were identified that characterized family meals with the use of ≥1 of the following structural features: frequency or mean number of family meals per week, length of family meal, people present at meal, and where meals occurred. No study characterized family meals by using all 4 family meal features, whereas most studies (81%) characterized family meals by using frequency or mean number of meals per week. Findings not only provide an initial understanding of the structural features used to define family meals but also point to the importance of developing a more comprehensive, sensitive assessment that can accurately capture the complex and multidimensional nature of family meals. © 2016 American Society for Nutrition.

Automatic age and gender classification using supervised appearance model

NASA Astrophysics Data System (ADS)

Bukar, Ali Maina; Ugail, Hassan; Connah, David

2016-11-01

Age and gender classification are two important problems that recently gained popularity in the research community, due to their wide range of applications. Research has shown that both age and gender information are encoded in the face shape and texture, hence the active appearance model (AAM), a statistical model that captures shape and texture variations, has been one of the most widely used feature extraction techniques for the aforementioned problems. However, AAM suffers from some drawbacks, especially when used for classification. This is primarily because principal component analysis (PCA), which is at the core of the model, works in an unsupervised manner, i.e., PCA dimensionality reduction does not take into account how the predictor variables relate to the response (class labels). Rather, it explores only the underlying structure of the predictor variables, thus, it is no surprise if PCA discards valuable parts of the data that represent discriminatory features. Toward this end, we propose a supervised appearance model (sAM) that improves on AAM by replacing PCA with partial least-squares regression. This feature extraction technique is then used for the problems of age and gender classification. Our experiments show that sAM has better predictive power than the conventional AAM.

The Economics of Human Development and Social Mobility *

PubMed Central

Heckman, James J.; Mosso, Stefano

2014-01-01

This paper distills and extends recent research on the economics of human development and social mobility. It summarizes the evidence from diverse literatures on the importance of early life conditions in shaping multiple life skills and the evidence on critical and sensitive investment periods for shaping different skills. It presents economic models that rationalize the evidence and unify the treatment effect and family influence literatures. The evidence on the empirical and policy importance of credit constraints in forming skills is examined. There is little support for the claim that untargeted income transfer policies to poor families significantly boost child outcomes. Mentoring, parenting, and attachment are essential features of successful families and interventions to shape skills at all stages of childhood. The next wave of family studies will better capture the active role of the emerging autonomous child in learning and responding to the actions of parents, mentors and teachers. PMID:25346785

A decoy trap for breeding-season mallards in North Dakota

USGS Publications Warehouse

Sharp, D.E.; Lokemoen, J.T.

1987-01-01

A modified decoy trap was effective for capturing wild adult male and female mallards (Anas platyrhynchos) during the 1980-81 breeding seasons in North Dakota. Key features contributing to the trap's success included a central decoy cylinder, large capture compartments with spring-door openings, an adjustable trigger mechanism with a balanced door attachment that was resistant to trap movement, and the use of F1, wild-stock or game-farm female decoys.

Epithermal neutron beams from the 7 Li(p,n) reaction near the threshold for neutron capture therapy

NASA Astrophysics Data System (ADS)

Porras, I.; Praena, J.; Arias de Saavedra, F.; Pedrosa, M.; Esquinas, P.; L. Jiménez-Bonilla, P.

2016-11-01

Two applications for neutron capture therapy of epithermal neutron beams calculated from the 7Li ( p , n reaction are discussed. In particular, i) for a proton beam of 1920 keV of a 30 mA, a neutron beam of adequate features for BNCT is found at an angle of 80° from the forward direction; and ii) for a proton beam of 1910 keV, a neutron beam is obtained at the forward direction suitable for performing radiobiology experiments for the determination of the biological weighting factors of the fast dose component in neutron capture therapy.

The thiocyanate anion is a primary driver of carbon dioxide capture by ionic liquids

NASA Astrophysics Data System (ADS)

Chaban, Vitaly

2015-01-01

Carbon dioxide, CO2, capture by room-temperature ionic liquids (RTILs) is a vivid research area featuring both accomplishments and frustrations. This work employs the PM7-MD method to simulate adsorption of CO2 by 1,3-dimethylimidazolium thiocyanate at 300 K. The obtained result evidences that the thiocyanate anion plays a key role in gas capture, whereas the impact of the 1,3-dimethylimidazolium cation is mediocre. Decomposition of the computed wave function on the individual molecular orbitals confirms that CO2-SCN binding extends beyond just expected electrostatic interactions in the ion-molecular system and involves partial sharing of valence orbitals.

Simulating Thermal Cycling and Isothermal Deformation Response of Polycrystalline NiTi

NASA Technical Reports Server (NTRS)

Manchiraju, Sivom; Gaydosh, Darrell J.; Noebe, Ronald D.; Anderson, Peter M.

2011-01-01

A microstructure-based FEM model that couples crystal plasticity, crystallographic descriptions of the B2-B19' martensitic phase transformation, and anisotropic elasticity is used to simulate thermal cycling and isothermal deformation in polycrystalline NiTi (49.9at% Ni). The model inputs include anisotropic elastic properties, polycrystalline texture, DSC data, and a subset of isothermal deformation and load-biased thermal cycling data. A key experimental trend is captured.namely, the transformation strain during thermal cycling is predicted to reach a peak with increasing bias stress, due to the onset of plasticity at larger bias stress. Plasticity induces internal stress that affects both thermal cycling and isothermal deformation responses. Affected thermal cycling features include hysteretic width, two-way shape memory effect, and evolution of texture with increasing bias stress. Affected isothermal deformation features include increased hardening during loading and retained martensite after unloading. These trends are not captured by microstructural models that lack plasticity, nor are they all captured in a robust manner by phenomenological approaches. Despite this advance in microstructural modeling, quantitative differences exist, such as underprediction of open loop strain during thermal cycling.

Oculomotor guidance and capture by irrelevant faces.

PubMed

Devue, Christel; Belopolsky, Artem V; Theeuwes, Jan

2012-01-01

Even though it is generally agreed that face stimuli constitute a special class of stimuli, which are treated preferentially by our visual system, it remains unclear whether faces can capture attention in a stimulus-driven manner. Moreover, there is a long-standing debate regarding the mechanism underlying the preferential bias of selecting faces. Some claim that faces constitute a set of special low-level features to which our visual system is tuned; others claim that the visual system is capable of extracting the meaning of faces very rapidly, driving attentional selection. Those debates continue because many studies contain methodological peculiarities and manipulations that prevent a definitive conclusion. Here, we present a new visual search task in which observers had to make a saccade to a uniquely colored circle while completely irrelevant objects were also present in the visual field. The results indicate that faces capture and guide the eyes more than other animated objects and that our visual system is not only tuned to the low-level features that make up a face but also to its meaning.

Bumble Bee Fauna of Palouse Prairie: Survey of Native Bee Pollinators in a Fragmented Ecosystem

PubMed Central

Hatten, T. D.; Looney, C.; Strange, J. P.; Bosque-Pérez, N. A.

2013-01-01

Bumble bees, Bombus Latreille (Hymenoptera: Apidae:), are dominant pollinators in the northern hemisphere, providing important pollination services for commercial crops and innumerable wild plants. Nationwide declines in several bumble bee species and habitat losses in multiple ecosystems have raised concerns about conservation of this important group. In many regions, such as the Palouse Prairie, relatively little is known about bumble bee communities, despite their critical ecosystem functions. Pitfall trap surveys for ground beetles in Palouse prairie remnants conducted in 2002–2003 contained considerable by-catch of bumble bees. The effects of landscape context, remnant features, year, and season on bumble bee community composition were examined. Additionally, bees captured in 2002–2003 were compared with historic records for the region to assess changes in the presence of individual species. Ten species of bumble bee were captured, representing the majority of the species historically known from the region. Few detectable differences in bumble bee abundances were found among remnants. Community composition differed appreciably, however, based on season, landscape context, and elevation, resulting in different bee assemblages between western, low-lying remnants and eastern, higherelevation remnants. The results suggest that conservation of the still species-rich bumble bee fauna should take into account variability among prairie remnants, and further work is required to adequately explain bumble bee habitat associations on the Palouse. PMID:23902138

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

Is it growing exponentially fast? -- Impact of assuming exponential growth for characterizing and forecasting epidemics with initial near-exponential growth dynamics.

PubMed

Chowell, Gerardo; Viboud, Cécile

2016-10-01

The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing models that capture the baseline transmission characteristics in order to generate reliable epidemic forecasts. Improved models for epidemic forecasting could be achieved by identifying signature features of epidemic growth, which could inform the design of models of disease spread and reveal important characteristics of the transmission process. In particular, it is often taken for granted that the early growth phase of different growth processes in nature follow early exponential growth dynamics. In the context of infectious disease spread, this assumption is often convenient to describe a transmission process with mass action kinetics using differential equations and generate analytic expressions and estimates of the reproduction number. In this article, we carry out a simulation study to illustrate the impact of incorrectly assuming an exponential-growth model to characterize the early phase (e.g., 3-5 disease generation intervals) of an infectious disease outbreak that follows near-exponential growth dynamics. Specifically, we assess the impact on: 1) goodness of fit, 2) bias on the growth parameter, and 3) the impact on short-term epidemic forecasts. Designing transmission models and statistical approaches that more flexibly capture the profile of epidemic growth could lead to enhanced model fit, improved estimates of key transmission parameters, and more realistic epidemic forecasts.

Attentional capture under high perceptual load.

PubMed

Cosman, Joshua D; Vecera, Shaun P

2010-12-01

Attentional capture by abrupt onsets can be modulated by several factors, including the complexity, or perceptual load, of a scene. We have recently demonstrated that observers are less likely to be captured by abruptly appearing, task-irrelevant stimuli when they perform a search that is high, as opposed to low, in perceptual load (Cosman & Vecera, 2009), consistent with perceptual load theory. However, recent results indicate that onset frequency can influence stimulus-driven capture, with infrequent onsets capturing attention more often than did frequent onsets. Importantly, in our previous task, an abrupt onset was present on every trial, and consequently, attentional capture might have been affected by both onset frequency and perceptual load. In the present experiment, we examined whether onset frequency influences attentional capture under conditions of high perceptual load. When onsets were presented frequently, we replicated our earlier results; attentional capture by onsets was modulated under conditions of high perceptual load. Importantly, however, when onsets were presented infrequently, we observed robust capture effects. These results conflict with a strong form of load theory and, instead, suggest that exposure to the elements of a task (e.g., abrupt onsets) combines with high perceptual load to modulate attentional capture by task-irrelevant information.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

PubMed

Onken, Arno; Liu, Jian K; Karunasekara, P P Chamanthi R; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-11-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

PubMed Central

Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-01-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding. PMID:27814363

A feature based comparison of pen and swipe based signature characteristics.

PubMed

Robertson, Joshua; Guest, Richard

2015-10-01

Dynamic Signature Verification (DSV) is a biometric modality that identifies anatomical and behavioral characteristics when an individual signs their name. Conventionally signature data has been captured using pen/tablet apparatus. However, the use of other devices such as the touch-screen tablets has expanded in recent years affording the possibility of assessing biometric interaction on this new technology. To explore the potential of employing DSV techniques when a user signs or swipes with their finger, we report a study to correlate pen and finger generated features. Investigating the stability and correlation between a set of characteristic features recorded in participant's signatures and touch-based swipe gestures, a statistical analysis was conducted to assess consistency between capture scenarios. The results indicate that there is a range of static and dynamic features such as the rate of jerk, size, duration and the distance the pen traveled that can lead to interoperability between these two systems for input methods for use within a potential biometric context. It can be concluded that this data indicates that a general principle is that the same underlying constructional mechanisms are evident. Copyright © 2015 Elsevier B.V. All rights reserved.

Classification of Partial Discharge Signals by Combining Adaptive Local Iterative Filtering and Entropy Features

PubMed Central

Morison, Gordon; Boreham, Philip

2018-01-01

Electromagnetic Interference (EMI) is a technique for capturing Partial Discharge (PD) signals in High-Voltage (HV) power plant apparatus. EMI signals can be non-stationary which makes their analysis difficult, particularly for pattern recognition applications. This paper elaborates upon a previously developed software condition-monitoring model for improved EMI events classification based on time-frequency signal decomposition and entropy features. The idea of the proposed method is to map multiple discharge source signals captured by EMI and labelled by experts, including PD, from the time domain to a feature space, which aids in the interpretation of subsequent fault information. Here, instead of using only one permutation entropy measure, a more robust measure, called Dispersion Entropy (DE), is added to the feature vector. Multi-Class Support Vector Machine (MCSVM) methods are utilized for classification of the different discharge sources. Results show an improved classification accuracy compared to previously proposed methods. This yields to a successful development of an expert’s knowledge-based intelligent system. Since this method is demonstrated to be successful with real field data, it brings the benefit of possible real-world application for EMI condition monitoring. PMID:29385030

Combined influence of meso-scale circulation and bathymetry on the foraging behaviour of a diving predator, the king penguin (Aptenodytes patagonicus)

NASA Astrophysics Data System (ADS)

Scheffer, Annette; Trathan, Philip N.; Edmonston, Johnnie G.; Bost, Charles-André

2016-02-01

Investigating the responses of marine predators to environmental features is of key importance for understanding their foraging behaviour and reproductive success. In this study we examined the foraging behaviour of king penguins breeding at Kerguelen (southern Indian Ocean) in relation to oceanographic and bathymetric features within their foraging ambit. We used ARGOS and Global Positioning System tracking together with Time-Depth-Temperature-Recorders (TDR) to follow the at-sea movements of incubating and brooding king penguins. Combining the penguin behaviour with oceanographic data at the surface through satellite data and at depth through in-situ recordings by the TDRs enabled us to explore how these predators adjusted their horizontal and vertical foraging movements in response to their physical environment. Relating the observed behaviour and oceanographic patterns to local bathymetry lead to a comprehensive picture of the combined influence of bathymetry and meso-scale circulation on the foraging behaviour of king penguins. During both breeding stages king penguins foraged in the area to the south-east of Kerguelen, where they explored an influx of cold waters of southern origin interacting with the Kerguelen Plateau bathymetry. Foraging in the Polar Front and at the thermocline was associated with high prey capture rates. However, foraging trip orientation and water mass utilization suggested that bathymetrically entrained cold-water features provided the most favourable foraging locations. Our study explicitly reports the exploration of bathymetry-related oceanographic features by foraging king penguins. It confirms the presence of Areas of Ecological Significance for marine predators on the Kerguelen Plateau, and suggests the importance of further areas related to the cold-water flow along the shelf break of the Kerguelen Plateau.

Deep Optical Spectroscopy of Planetary Nebulae: The Search for Neutron-Capture Elements

NASA Astrophysics Data System (ADS)

Sterling, Nicholas C.; Garofali, K.; Dinerstein, H. L.; Hwang, S.; Redfield, S.

2013-01-01

We present deep, high-resolution (R=36,700) optical spectra of five planetary nebulae (PNe), taken with the 2D-coude echelle spectrograph on the 2.7-m Harlan J. Smith Telescope at McDonald Observatory. These observations are part of a larger optical survey of PNe, designed to unambiguously detect emission lines from neutron(n)-capture elements (atomic number Z>30). The abundances of these elements are of particular interest in PNe, since they can be produced by slow n-capture nucleosynthesis (the ``s-process'') during the asymptotic giant branch (AGB) stage of evolution of PN progenitor stars. The first large-scale investigation of n-capture element abundances in PNe (Sterling & Dinerstein 2008, ApJS, 174, 157) surveyed [Kr III] and [Se IV] transitions in the K band spectra of more than 80 PNe. However, the abundances derived from these data relied on ionization corrections that were often large and uncertain due to the detection of only one ion per element. Transitions of other Se and Kr ions, as well as many other trans-iron species, reside at optical wavelengths. High-resolution spectra are essential to unequivocally identify these lines and resolve potential blends with other species. The spectra we present are rich in emission features, with between 125 and 600 distinct lines detected in each PN. Emission from at least one Kr ion is detected in all five objects, and two (Hb 12 and J 900) exhibit emission from multiple Kr ions. We detected multiple Xe ions in J 900, as well as Se, Br, and Rb lines. Hb 12 also exhibits Xe emission, and the first detection of [Se II] in a PN to our knowledge. The spectra display a wealth of other emission lines, including permitted features of second-row elements and forbidden transitions of several iron-peak elements (e.g., Cr, Mn, Fe, Co, Ni, and Cu). Our survey makes it possible to derive more accurate Se and Kr abundances in PNe, and reveals the enrichment of other trans-iron elements. This enables more accurate s-process enrichment factors to be derived for PNe, providing important constraints to models of AGB nucleosynthesis and the chemical evolution of trans-iron nuclides. This research was supported by NSF awards AST-0708425 and AST-901432.

The Universality of the Rapid Neutron-capture Process Revealed by a Possible Disrupted Dwarf Galaxy Star

NASA Astrophysics Data System (ADS)

Casey, Andrew R.; Schlaufman, Kevin C.

2017-12-01

The rapid neutron-capture or r-process is thought to produce the majority of the heavy elements (Z> 30) in extremely metal-poor stars. The same process is also responsible for a significant fraction of the heavy elements in the Sun. This universality of the r-process is one of its characteristic features, as well as one of the most important clues to its astrophysical origin. We report the discovery of an extremely metal-poor field giant with [{Sr},{Ba}/{{H}}]≈ -6.0 and [{Sr},{Ba}/{Fe}]≈ -3.0, the lowest abundances of strontium and barium relative to iron ever observed. Despite its low abundances, the star 2MASS J151113.24-213003.0 has [{Sr}/{Ba}]=-0.11+/- 0.14, therefore its neutron-capture abundances are consistent with the main solar r-process pattern that has [{Sr}/{Ba}]=-0.25. It has been suggested that extremely low neutron-capture abundances are a characteristic of dwarf galaxies, and we find that this star is on a highly eccentric orbit with an apocenter ≳100 kpc that lies in the disk of satellites in the halo of the Milky Way. We show that other extremely metal-poor stars with low [Sr, Ba/H] and [Sr, Ba/Fe] plus solar [Sr/Ba] tend to have orbits with large apocenters, consistent with a dwarf galaxy origin for this class of object. The nucleosynthesis event that produced the neutron-capture elements in 2MASS J151113.24-213003.0 must produce both strontium and barium together in the solar ratio. We exclude contributions from the s-process in intermediate-mass asymptotic giant branch or fast-rotating massive metal-poor stars, pair-instability supernovae, the weak r-process, and neutron-star mergers. We argue that the event was a Pop III or extreme Pop II core-collapse supernova explosion. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

An ontology design pattern for surface water features

USGS Publications Warehouse

Sinha, Gaurav; Mark, David; Kolas, Dave; Varanka, Dalia; Romero, Boleslo E.; Feng, Chen-Chieh; Usery, E. Lynn; Liebermann, Joshua; Sorokine, Alexandre

2014-01-01

Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities exist due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology for other more context-dependent ontologies. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex or specialized surface water ontologies. A fundamental distinction is made in this ontology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is implemented in OWL, but Description Logic axioms and a detailed explanation is provided in this paper. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. Also provided is a discussion of why there is a need to complement the pattern with other ontologies, especially the previously developed Surface Network pattern. Finally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through an annotated geospatial dataset and sample queries using the classes of the Surface Water pattern.

Age mediation of frontoparietal activation during visual feature search.

PubMed

Madden, David J; Parks, Emily L; Davis, Simon W; Diaz, Michele T; Potter, Guy G; Chou, Ying-hui; Chen, Nan-kuei; Cabeza, Roberto

2014-11-15

Activation of frontal and parietal brain regions is associated with attentional control during visual search. We used fMRI to characterize age-related differences in frontoparietal activation in a highly efficient feature search task, detection of a shape singleton. On half of the trials, a salient distractor (a color singleton) was present in the display. The hypothesis was that frontoparietal activation mediated the relation between age and attentional capture by the salient distractor. Participants were healthy, community-dwelling individuals, 21 younger adults (19-29 years of age) and 21 older adults (60-87 years of age). Top-down attention, in the form of target predictability, was associated with an improvement in search performance that was comparable for younger and older adults. The increase in search reaction time (RT) associated with the salient distractor (attentional capture), standardized to correct for generalized age-related slowing, was greater for older adults than for younger adults. On trials with a color singleton distractor, search RT increased as a function of increasing activation in frontal regions, for both age groups combined, suggesting increased task difficulty. Mediational analyses disconfirmed the hypothesized model, in which frontal activation mediated the age-related increase in attentional capture, but supported an alternative model in which age was a mediator of the relation between frontal activation and capture. Copyright © 2014 Elsevier Inc. All rights reserved.

Preliminary experiments on quantification of skin condition

NASA Astrophysics Data System (ADS)

Kitajima, Kenzo; Iyatomi, Hitoshi

2014-03-01

In this study, we investigated a preliminary assessment method for skin conditions such as a moisturizing property and its fineness of the skin with an image analysis only. We captured a facial images from volunteer subjects aged between 30s and 60s by Pocket Micro (R) device (Scalar Co., Japan). This device has two image capturing modes; the normal mode and the non-reflection mode with the aid of the equipped polarization filter. We captured skin images from a total of 68 spots from subjects' face using both modes (i.e. total of 136 skin images). The moisture-retaining property of the skin and subjective evaluation score of the skin fineness in 5-point scale for each case were also obtained in advance as a gold standard (their mean and SD were 35.15 +/- 3.22 (μS) and 3.45 +/- 1.17, respectively). We extracted a total of 107 image features from each image and built linear regression models for estimating abovementioned criteria with a stepwise feature selection. The developed model for estimating the skin moisture achieved the MSE of 1.92 (μS) with 6 selected parameters, while the model for skin fineness achieved that of 0.51 scales with 7 parameters under the leave-one-out cross validation. We confirmed the developed models predicted the moisture-retaining property and fineness of the skin appropriately with only captured image.

Salient features of the dayside low latitude ionospheric response to the main phase step-I of the 17 March 2015 geomagnetic storm

NASA Astrophysics Data System (ADS)

Bagiya, Mala S.; Sunil, A. S.; Chakrabarty, D.; Sunda, Surendra

2017-10-01

Based on TEC observations by India's GPS Aided GEO Augmented Navigation (GAGAN) GPS network, we report the dayside low latitude ionospheric variations over the Indian region during the moderate main phase step-I of the 17 March 2015 geomagnetic storm. In addition, we assess the efficacy of GPS inferred TEC maps by International GNSS service (IGS) in capturing large scale diurnal features of equatorial ionization anomaly (EIA) over the Indian region during this period. Following the prompt penetration electric field (PPE) at ∼0605 UT, equatorial electrojet (EEJ) enhances by ∼55 nT over 75 ± 3oE longitudes where main phase step-I is coincided with local noon. Initial moderate EIA gradually strengthens with the storm commencement. Although GAGAN TEC exhibits more intense EIA evolution compare to IGS TEC maps, latitudinal extent of EIA are comparable in both. The enhanced EEJ reverses by ∼0918 UT under the effect of overshielding electric field, the later is accompanied by northward turning of interplanetary magnetic field (IMF) Bz. The weakening of well evolved EIA reflects in IGS TEC maps after ∼45 min of the overshielding occurrence. In contrary, GAGAN TEC shows the corresponding feature after ∼0115 h. Resurgence of EIA, following the PPE ∼1115 UT, shows up in GAGAN TEC but IGS TEC maps fails in capturing this feature. The observed low latitude TEC variations and EIA modulations are explained in terms of the varying storm time disturbance electric fields. The anomalies between the GAGAN TEC and IGS TEC maps are discussed in terms of the possible limitations of the IGS TEC maps in capturing storm time EIA variability over the Indian region.

Improving the performance of univariate control charts for abnormal detection and classification

NASA Astrophysics Data System (ADS)

Yiakopoulos, Christos; Koutsoudaki, Maria; Gryllias, Konstantinos; Antoniadis, Ioannis

2017-03-01

Bearing failures in rotating machinery can cause machine breakdown and economical loss, if no effective actions are taken on time. Therefore, it is of prime importance to detect accurately the presence of faults, especially at their early stage, to prevent sequent damage and reduce costly downtime. The machinery fault diagnosis follows a roadmap of data acquisition, feature extraction and diagnostic decision making, in which mechanical vibration fault feature extraction is the foundation and the key to obtain an accurate diagnostic result. A challenge in this area is the selection of the most sensitive features for various types of fault, especially when the characteristics of failures are difficult to be extracted. Thus, a plethora of complex data-driven fault diagnosis methods are fed by prominent features, which are extracted and reduced through traditional or modern algorithms. Since most of the available datasets are captured during normal operating conditions, the last decade a number of novelty detection methods, able to work when only normal data are available, have been developed. In this study, a hybrid method combining univariate control charts and a feature extraction scheme is introduced focusing towards an abnormal change detection and classification, under the assumption that measurements under normal operating conditions of the machinery are available. The feature extraction method integrates the morphological operators and the Morlet wavelets. The effectiveness of the proposed methodology is validated on two different experimental cases with bearing faults, demonstrating that the proposed approach can improve the fault detection and classification performance of conventional control charts.

Capture Their Attention: Capturing Lessons Using Screen Capture Software

ERIC Educational Resources Information Center

Drumheller, Kristina; Lawler, Gregg

2011-01-01

When students miss classes for university activities such as athletic and academic events, they inevitably miss important class material. Students can get notes from their peers or visit professors to find out what they missed, but when students miss new and challenging material these steps are sometimes not enough. Screen capture and recording…

Nanotextured PDMS Substrates for Enhanced Roughness and Aptamer Immobilization for Cancer Cell Capture

NASA Astrophysics Data System (ADS)

Islam, Muhymin; Mahmood, Arif; Bellah, Md.; Kim, Young-Tae; Iqbal, Samir

2014-03-01

Detection of circulating tumor cells (CTCs) in the early stages of cancer is requires very sensitive approach. Nanotextured polydimethylsiloxane (PDMS) substrates were fabricated by micro reactive ion etching (Micro-RIE) to have better control on surface morphology and to improve the affinity of PDMS surfaces to capture cancer cells using surface immobilized aptamers. The aptamers were specific to epidermal growth factor receptors (EGFR) present in cell membranes, and overexpressed in tumor cells. We also investigated the effect of nano-scale features on cell capturing by implementing various surfaces of different roughnesses. Three different recipes were used to prepare nanotextured PDMS by micro-RIE using oxygen (O2) and carbon tetrafluoride (CF4). The measured average roughness of three nanotextured PDMS surfaces were found to impact average densities of captured cells. In all cases, nanotextured PDMS facilitated cell capturing possibly due to increased effective surface area of roughened substrates at nanoscale. It was also observed that cell capture efficiency was higher for higher surface roughness. The nanotextured PDMS substrates are thus useful for cancer cytology devices.

A new capture fraction method to map how pumpage affects surface water flow.

PubMed

Leake, Stanley A; Reeves, Howard W; Dickinson, Jesse E

2010-01-01

All groundwater pumped is balanced by removal of water somewhere, initially from storage in the aquifer and later from capture in the form of increase in recharge and decrease in discharge. Capture that results in a loss of water in streams, rivers, and wetlands now is a concern in many parts of the United States. Hydrologists commonly use analytical and numerical approaches to study temporal variations in sources of water to wells for select points of interest. Much can be learned about coupled surface/groundwater systems, however, by looking at the spatial distribution of theoretical capture for select times of interest. Development of maps of capture requires (1) a reasonably well-constructed transient or steady state model of an aquifer with head-dependent flow boundaries representing surface water features or evapotranspiration and (2) an automated procedure to run the model repeatedly and extract results, each time with a well in a different location. This paper presents new methods for simulating and mapping capture using three-dimensional groundwater flow models and presents examples from Arizona, Oregon, and Michigan.

Contributions to Pursuit-Evasion Game Theory

NASA Astrophysics Data System (ADS)

Oyler, Dave Wilson

This dissertation studies adversarial conflicts among a group of agents moving in the plane, possibly among obstacles, where some agents are pursuers and others are evaders. The goal of the pursuers is to capture the evaders, where capture requires a pursuer to be either co-located with an evader, or in close proximity. The goal of the evaders is to avoid capture. These scenarios, where different groups compete to accomplish conflicting goals, are referred to as pursuit-evasion games, and the agents are called players. Games featuring one pursuer and one evader are analyzed using dominance, where a point in the plane is said to be dominated by a player if that player is able to reach the point before the opposing players, regardless of the opposing players' actions. Two generalizations of the Apollonius circle are provided. One solves games with environments containing obstacles, and the other provides an alternative solution method for the Homicidal Chauffeur game. Optimal pursuit and evasion strategies based on dominance are provided. One benefit of dominance analysis is that it extends to games with many players. Two foundational games are studied; one features multiple pursuers against a single evader, and the other features a single pursuer against multiple evaders. Both are solved using dominance through a reduction to single pursuer, single evader games. Another game featuring competing teams of pursuers is introduced, where an evader cooperates with friendly pursuers to rendezvous before being captured by adversaries. Next, the assumption of complete and perfect information is relaxed, and uncertainties in player speeds, player positions, obstacle locations, and cost functions are studied. The sensitivity of the dominance boundary to perturbations in parameters is provided, and probabilistic dominance is introduced. The effect of information is studied by comparing solutions of games with perfect information to games with uncertainty. Finally, a pursuit law is developed that requires minimal information and highlights a limitation of dominance regions. These contributions extend pursuit-evasion game theory to a number of games that have not previously been solved, and in some cases, the solutions presented are more amenable to implementation than previous methods.

Extreme Rainfall from Hurricane Harvey (2017): Intercomparisons of WRF Simulations and Polarimetric Radar Fields

NASA Astrophysics Data System (ADS)

Yang, L.; Smith, J. A.; Liu, M.; Baeck, M. L.; Chaney, M. M.; Su, Y.

2017-12-01

Hurricane Harvey made landfall on 25 August 2017 and produced more than a meter of rain during a four-day period over eastern Texas, making it the wettest tropical cyclone on record in the United States. Extreme rainfall from Harvey was predominantly related to the dynamics and structure of outer rain bands. In this study, we provide details of the extreme rainfall produced by Hurricane Harvey. The principal research questions that motivate this study are: (1) what are the key microphysical properties of extreme rainfall from landfalling tropical cyclones and (2) what are the capabilities and deficiencies of existing bulk microphysics parameterizations from the physical models in capturing them. Our analyses are centered on intercomparisons of high-resolution simulations using the Weather Research and Forecasting (WRF) model and polarimetric radar fields from KHGX (Houston, Texas) WSR-88D. The WRF simulations accurately capture the track and intensity of Hurricane Harvey. Multi-rainband structure and its key evolution features are also well represented in the simulations. Two microphysics parameterizations (WSM6 and WDM6) are tested in this study. Radar reflectivity and differential reflectivity fields simulated by the WRF model are compared with polarimetric radar observations. An important feature for the extreme rainfall from Hurricane Harvey is the sharp boundary of spatial rainfall accumulation along the coast (with torrential rainfall distributed over Houston and its surrounding inland areas). We will examine the role of land-sea contrasts in dictating storm structure and evolution from both WRF simulations and polarimetric radar fields. Implications for improving hurricane rainfall forecasts and estimates will be provided.

Networked high-speed auroral observations combined with radar measurements for multi-scale insights

NASA Astrophysics Data System (ADS)

Hirsch, M.; Semeter, J. L.

2015-12-01

Networks of ground-based instruments to study terrestrial aurora for the purpose of analyzing particle precipitation characteristics driving the aurora have been established. Additional funding is pouring into future ground-based auroral observation networks consisting of combinations of tossable, portable, and fixed installation ground-based legacy equipment. Our approach to this problem using the High Speed Tomography (HiST) system combines tightly-synchronized filtered auroral optical observations capturing temporal features of order 10 ms with supporting measurements from incoherent scatter radar (ISR). ISR provides a broader spatial context up to order 100 km laterally on one minute time scales, while our camera field of view (FOV) is chosen to be order 10 km at auroral altitudes in order to capture 100 m scale lateral auroral features. The dual-scale observations of ISR and HiST fine-scale optical observations may be coupled through a physical model using linear basis functions to estimate important ionospheric quantities such as electron number density in 3-D (time, perpendicular and parallel to the geomagnetic field).Field measurements and analysis using HiST and PFISR are presented from experiments conducted at the Poker Flat Research Range in central Alaska. Other multiscale configuration candidates include supplementing networks of all-sky cameras such as THEMIS with co-locations of HiST-like instruments to fuse wide FOV measurements with the fine-scale HiST precipitation characteristic estimates. Candidate models for this coupling include GLOW and TRANSCAR. Future extensions of this work may include incorporating line of sight total electron count estimates from ground-based networks of GPS receivers in a sensor fusion problem.

Integrating multi-omic features exploiting Chromosome Conformation Capture data.

PubMed

Merelli, Ivan; Tordini, Fabio; Drocco, Maurizio; Aldinucci, Marco; Liò, Pietro; Milanesi, Luciano

2015-01-01

The representation, integration, and interpretation of omic data is a complex task, in particular considering the huge amount of information that is daily produced in molecular biology laboratories all around the world. The reason is that sequencing data regarding expression profiles, methylation patterns, and chromatin domains is difficult to harmonize in a systems biology view, since genome browsers only allow coordinate-based representations, discarding functional clusters created by the spatial conformation of the DNA in the nucleus. In this context, recent progresses in high throughput molecular biology techniques and bioinformatics have provided insights into chromatin interactions on a larger scale and offer a formidable support for the interpretation of multi-omic data. In particular, a novel sequencing technique called Chromosome Conformation Capture allows the analysis of the chromosome organization in the cell's natural state. While performed genome wide, this technique is usually called Hi-C. Inspired by service applications such as Google Maps, we developed NuChart, an R package that integrates Hi-C data to describe the chromosomal neighborhood starting from the information about gene positions, with the possibility of mapping on the achieved graphs genomic features such as methylation patterns and histone modifications, along with expression profiles. In this paper we show the importance of the NuChart application for the integration of multi-omic data in a systems biology fashion, with particular interest in cytogenetic applications of these techniques. Moreover, we demonstrate how the integration of multi-omic data can provide useful information in understanding why genes are in certain specific positions inside the nucleus and how epigenetic patterns correlate with their expression.

Computational modeling of the human auditory periphery: Auditory-nerve responses, evoked potentials and hearing loss.

PubMed

Verhulst, Sarah; Altoè, Alessandro; Vasilkov, Viacheslav

2018-03-01

Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Assessment of Gait Characteristics in Total Knee Arthroplasty Patients Using a Hierarchical Partial Least Squares Method.

PubMed

Wang, Wei; Ackland, David C; McClelland, Jodie A; Webster, Kate E; Halgamuge, Saman

2018-01-01

Quantitative gait analysis is an important tool in objective assessment and management of total knee arthroplasty (TKA) patients. Studies evaluating gait patterns in TKA patients have tended to focus on discrete data such as spatiotemporal information, joint range of motion and peak values of kinematics and kinetics, or consider selected principal components of gait waveforms for analysis. These strategies may not have the capacity to capture small variations in gait patterns associated with each joint across an entire gait cycle, and may ultimately limit the accuracy of gait classification. The aim of this study was to develop an automatic feature extraction method to analyse patterns from high-dimensional autocorrelated gait waveforms. A general linear feature extraction framework was proposed and a hierarchical partial least squares method derived for discriminant analysis of multiple gait waveforms. The effectiveness of this strategy was verified using a dataset of joint angle and ground reaction force waveforms from 43 patients after TKA surgery and 31 healthy control subjects. Compared with principal component analysis and partial least squares methods, the hierarchical partial least squares method achieved generally better classification performance on all possible combinations of waveforms, with the highest classification accuracy . The novel hierarchical partial least squares method proposed is capable of capturing virtually all significant differences between TKA patients and the controls, and provides new insights into data visualization. The proposed framework presents a foundation for more rigorous classification of gait, and may ultimately be used to evaluate the effects of interventions such as surgery and rehabilitation.

Stochastic time series analysis of fetal heart-rate variability

NASA Astrophysics Data System (ADS)

Shariati, M. A.; Dripps, J. H.

1990-06-01

Fetal Heart Rate(FHR) is one of the important features of fetal biophysical activity and its long term monitoring is used for the antepartum(period of pregnancy before labour) assessment of fetal well being. But as yet no successful method has been proposed to quantitatively represent variety of random non-white patterns seen in FHR. Objective of this paper is to address this issue. In this study the Box-Jenkins method of model identification and diagnostic checking was used on phonocardiographic derived FHR(averaged) time series. Models remained exclusively autoregressive(AR). Kalman filtering in conjunction with maximum likelihood estimation technique forms the parametric estimator. Diagnosrics perfonned on the residuals indicated that a second order model may be adequate in capturing type of variability observed in 1 up to 2 mm data windows of FHR. The scheme may be viewed as a means of data reduction of a highly redundant information source. This allows a much more efficient transmission of FHR information from remote locations to places with facilities and expertise for doser analysis. The extracted parameters is aimed to reflect numerically the important FHR features. These are normally picked up visually by experts for their assessments. As a result long term FHR recorded during antepartum period could then be screened quantitatively for detection of patterns considered normal or abnonnal. 1.

An Innovative Approach for The Integration of Proteomics and Metabolomics Data In Severe Septic Shock Patients Stratified for Mortality.

PubMed

Cambiaghi, Alice; Díaz, Ramón; Martinez, Julia Bauzá; Odena, Antonia; Brunelli, Laura; Caironi, Pietro; Masson, Serge; Baselli, Giuseppe; Ristagno, Giuseppe; Gattinoni, Luciano; de Oliveira, Eliandre; Pastorelli, Roberta; Ferrario, Manuela

2018-04-27

In this work, we examined plasma metabolome, proteome and clinical features in patients with severe septic shock enrolled in the multicenter ALBIOS study. The objective was to identify changes in the levels of metabolites involved in septic shock progression and to integrate this information with the variation occurring in proteins and clinical data. Mass spectrometry-based targeted metabolomics and untargeted proteomics allowed us to quantify absolute metabolites concentration and relative proteins abundance. We computed the ratio D7/D1 to take into account their variation from day 1 (D1) to day 7 (D7) after shock diagnosis. Patients were divided into two groups according to 28-day mortality. Three different elastic net logistic regression models were built: one on metabolites only, one on metabolites and proteins and one to integrate metabolomics and proteomics data with clinical parameters. Linear discriminant analysis and Partial least squares Discriminant Analysis were also implemented. All the obtained models correctly classified the observations in the testing set. By looking at the variable importance (VIP) and the selected features, the integration of metabolomics with proteomics data showed the importance of circulating lipids and coagulation cascade in septic shock progression, thus capturing a further layer of biological information complementary to metabolomics information.

Climatology and variability of SST frontal activity in Eastern Pacific Ocean over the past decade

NASA Astrophysics Data System (ADS)

Wang, Y.; Yuan, Y.

2016-12-01

Distribution of sea surface temperature (SST) fronts are derived from high-resolution MODIS dataset in Eastern Pacific Ocean from 2003 to 2015. Daily distribution of frontal activities shows detailed feature and movement of front and the discontinuity of the track of front cause by cloud coverage. Monthly frontal probability is calculated to investigate corresponding climatology and variability. Frontal probability is generally higher along the coast and decreasing offshore. The frontal activity could extend few hundreds of kilometers near the major capes and central Pacific Ocean. SST gradient associated with front is changing over different latitude with stronger gradient near the mid-latitude and under major topographic effects near tropics. Corresponding results from empirical orthogonal functions (EOF) shows major variability of SST front is found in mid-latitude and central Pacific Ocean. The temporal variability captures a strong interannual and annual variability in those regions, while Intraannual variability are found more important at small scale near major capes and topographic features. The frontal variability is highly impacted by wind stress, upwelling, air-sea interaction, current, topography, eddy activity, El Nino along with other factors. And front plays an importance role in influencing the distribution of nutrients, the activity of fisheries and the development of ecosystems.

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture Remote Sensing

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Prior, H. L.

1984-01-01

It is believed that the increased spatial resolution will provide solutions to proportion estimation error due to mixed pixels, and the increased spectral resolution will provide for the identification of important agricultural features such as crop stage, and condition. The results of analyses conducted relative to these hypothesis from sample segments extracted from the 4-band Detroit scene and the 7-band Mississippi County, Arkansas engineering test scene are described. Several studies were conducted to evaluate the geometric and radiometric performance of the TM to determine data viability for the more pertinent investigations of TM utility. In most cases this requirement was more than sufficiently satisfied. This allowed the opportunity to take advantage of detailed ground observations for several of the sample segments to assess class separability and detection of other important features with TM. The results presented regarding these TM characteristics show that not only is the increased definition of the within scene variance captured by the increased spatial and spectral resolution, but that the mid-IR bands (5 and 7) are necessary for optimum crop type classification. Both qualitative and quantitative results are presented that describe the improvements gained with the TM both relative to the MSS and on its own merit.

Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.

PubMed

Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco

2017-06-27

Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.

Contributions of Microtubule Dynamic Instability and Rotational Diffusion to Kinetochore Capture.

PubMed

Blackwell, Robert; Sweezy-Schindler, Oliver; Edelmaier, Christopher; Gergely, Zachary R; Flynn, Patrick J; Montes, Salvador; Crapo, Ammon; Doostan, Alireza; McIntosh, J Richard; Glaser, Matthew A; Betterton, Meredith D

2017-02-07

Microtubule dynamic instability allows search and capture of kinetochores during spindle formation, an important process for accurate chromosome segregation during cell division. Recent work has found that microtubule rotational diffusion about minus-end attachment points contributes to kinetochore capture in fission yeast, but the relative contributions of dynamic instability and rotational diffusion are not well understood. We have developed a biophysical model of kinetochore capture in small fission-yeast nuclei using hybrid Brownian dynamics/kinetic Monte Carlo simulation techniques. With this model, we have studied the importance of dynamic instability and microtubule rotational diffusion for kinetochore capture, both to the lateral surface of a microtubule and at or near its end. Over a range of biologically relevant parameters, microtubule rotational diffusion decreased capture time, but made a relatively small contribution compared to dynamic instability. At most, rotational diffusion reduced capture time by 25%. Our results suggest that while microtubule rotational diffusion can speed up kinetochore capture, it is unlikely to be the dominant physical mechanism for typical conditions in fission yeast. In addition, we found that when microtubules undergo dynamic instability, lateral captures predominate even in the absence of rotational diffusion. Counterintuitively, adding rotational diffusion to a dynamic microtubule increases the probability of end-on capture. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Magnetically Actuated Cilia for Microfluidic Manipulation

NASA Astrophysics Data System (ADS)

Hanasoge, Srinivas; Owen, Drew; Ballard, Matt; Hesketh, Peter J.; Alexeev, Alexander; Woodruff School of Mechanical Engineering Collaboration; Petit InstituteBioengineering; Biosciences Collaboration

2015-11-01

We demonstrate magnetic micro-cilia based microfluidic mixing and capture techniques. For this, we use a simple and easy to fabricate high aspect ratio cilia, which are actuated magnetically. These micro-features are fabricated by evaporating NiFe alloy at room temperature, on to patterned photoresist. The evaporated alloy curls upwards when the seed layer is removed to release the cilia, thus making a free standing `C' shaped magnetic microstructure. This is actuated using an external electromagnet or a rotating magnet. The artificial cilia can be actuated upto 20Hz. We demonstrate the active mixing these cilia can produce in the microchannel. Also, we demonstrate the capture of target species in a sample using these fast oscillating cilia. The surface of the cilia is functionalized by streptavidin which binds to biotin labelled fluorescent microspheres and mimic the capture of bacteria. We show very high capture efficiencies by using these methods. These simple to fabricate micro cilia can easily be incorporated into many microfluidic systems which require high mixing and capture efficiencies.

Modeling association among demographic parameters in analysis of open population capture-recapture data

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2005-01-01

We present a hierarchical extension of the Cormack–Jolly–Seber (CJS) model for open population capture–recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis–Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Modeling error in assessment of mammographic image features for improved computer-aided mammography training: initial experience

NASA Astrophysics Data System (ADS)

Mazurowski, Maciej A.; Tourassi, Georgia D.

2011-03-01

In this study we investigate the hypothesis that there exist patterns in erroneous assessment of BI-RADS image features among radiology trainees when performing diagnostic interpretation of mammograms. We also investigate whether these error making patterns can be captured by individual user models. To test our hypothesis we propose a user modeling algorithm that uses the previous readings of a trainee to identify whether certain BI-RADS feature values (e.g. "spiculated" value for "margin" feature) are associated with higher than usual likelihood that the feature will be assessed incorrectly. In our experiments we used readings of 3 radiology residents and 7 breast imaging experts for 33 breast masses for the following BI-RADS features: parenchyma density, mass margin, mass shape and mass density. The expert readings were considered as the gold standard. Rule-based individual user models were developed and tested using the leave one-one-out crossvalidation scheme. Our experimental evaluation showed that the individual user models are accurate in identifying cases for which errors are more likely to be made. The user models captured regularities in error making for all 3 residents. This finding supports our hypothesis about existence of individual error making patterns in assessment of mammographic image features using the BI-RADS lexicon. Explicit user models identifying the weaknesses of each resident could be of great use when developing and adapting a personalized training plan to meet the resident's individual needs. Such approach fits well with the framework of adaptive computer-aided educational systems in mammography we have proposed before.

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.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography).

PubMed

Siegel, Nisan; Storrie, Brian; Bruce, Marc; Brooker, Gary

2015-02-07

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called "CINCH". An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution.

Development of the earth-moon system with implications for the geology of the early earth

NASA Technical Reports Server (NTRS)

Smith, J. V.

1976-01-01

Established facts regarding the basic features of the earth and the moon are reviewed, and some important problems involving the moon are discussed (extent of melting, time of crustal differentiation and nature of bombardment, bulk chemical composition, and nature and source of mare basins), with attention given to the various existing theories concerning these problems. Models of the development of the earth-moon system from the solar nebula are examined, with particular attention focused on those that use the concept of capture with disintegration. Impact processes in the early crust of the earth are briefly considered, with attention paid to Green's (1972) suggestion that Archaean greenstone belts may be the terrestrial equivalent of lunar maria.

Privacy-preserving discovery of topic-based events from social sensor signals: an experimental study on Twitter.

PubMed

Nguyen, Duc T; Jung, Jai E

2014-01-01

Social network services (e.g., Twitter and Facebook) can be regarded as social sensors which can capture a number of events in the society. Particularly, in terms of time and space, various smart devices have improved the accessibility to the social network services. In this paper, we present a social software platform to detect a number of meaningful events from information diffusion patterns on such social network services. The most important feature is to process the social sensor signal for understanding social events and to support users to share relevant information along the social links. The platform has been applied to fetch and cluster tweets from Twitter into relevant categories to reveal hot topics.

A simple computer-based measurement and analysis system of pulmonary auscultation sounds.

PubMed

Polat, Hüseyin; Güler, Inan

2004-12-01

Listening to various lung sounds has proven to be an important diagnostic tool for detecting and monitoring certain types of lung diseases. In this study a computer-based system has been designed for easy measurement and analysis of lung sound using the software package DasyLAB. The designed system presents the following features: it is able to digitally record the lung sounds which are captured with an electronic stethoscope plugged to a sound card on a portable computer, display the lung sound waveform for auscultation sites, record the lung sound into the ASCII format, acoustically reproduce the lung sound, edit and print the sound waveforms, display its time-expanded waveform, compute the Fast Fourier Transform (FFT), and display the power spectrum and spectrogram.

Two-Dimensional Self-Consistent Radio Frequency Plasma Simulations Relevant to the Gaseous Electronics Conference RF Reference Cell

PubMed Central

Lymberopoulos, Dimitris P.; Economou, Demetre J.

1995-01-01

Over the past few years multidimensional self-consistent plasma simulations including complex chemistry have been developed which are promising tools for furthering our understanding of reactive gas plasmas and for reactor design and optimization. These simulations must be benchmarked against experimental data obtained in well-characterized systems such as the Gaseous Electronics Conference (GEC) reference cell. Two-dimensional simulations relevant to the GEC Cell are reviewed in this paper with emphasis on fluid simulations. Important features observed experimentally, such as off-axis maxima in the charge density and hot spots of metastable species density near the electrode edges in capacitively-coupled GEC cells, have been captured by these simulations. PMID:29151756

Preface: Special Topic on Frontiers in Molecular Scale Electronics

NASA Astrophysics Data System (ADS)

Evers, Ferdinand; Venkataraman, Latha

2017-03-01

The electronic, mechanical, and thermoelectric properties of molecular scale devices have fascinated scientists across several disciplines in natural sciences and engineering. The interest is partially technological, driven by the fast miniaturization of integrated circuits that now have reached characteristic features at the nanometer scale. Equally important, a very strong incentive also exists to elucidate the fundamental aspects of structure-function relations for nanoscale devices, which utilize molecular building blocks as functional units. Thus motivated, a rich research field has established itself, broadly termed "Molecular Electronics," that hosts a plethora of activities devoted to this goal in chemistry, physics, and electrical engineering. This Special Topic on Frontiers of Molecular Scale Electronics captures recent theoretical and experimental advances in the field.

Neutron cross-sections for next generation reactors: new data from n_TOF.

PubMed

Colonna, N; Abbondanno, U; Aerts, G; Alvarez, H; Alvarez-Velarde, F; Andriamonje, S; Andrzejewski, J; Assimakopoulos, P; Audouin, L; Badurek, G; Baumann, P; Becvar, F; Berthoumieux, E; Calviani, M; Calviño, F; Cano-Ott, D; Capote, R; de Albornoz, A Carrillo; Cennini, P; Chepel, V; Chiaveri, E; Cortes, G; Couture, A; Cox, J; Dahlfors, M; David, S; Dillman, I; Dolfini, R; Domingo-Pardo, C; Dridi, W; Duran, I; Eleftheriadis, C; Ferrant, L; Ferrari, A; Ferreira-Marques, R; Frais-Koelbl, H; Fujii, K; Furman, W; Goncalves, I; González-Romero, E; Goverdovski, A; Gramegna, F; Griesmayer, E; Guerrero, C; Gunsing, F; Haas, B; Haight, R; Heil, M; Herrera-Martinez, A; Igashira, M; Isaev, S; Jericha, E; Käppeler, F; Kadi, Y; Karadimos, D; Karamanis, D; Kerveno, M; Ketlerov, V; Koehler, P; Konovalov, V; Kossionides, E; Krticka, M; Lampoudis, C; Leeb, H; Lindote, A; Lopes, I; Lozano, M; Lukic, S; Marganiec, J; Marques, L; Marrone, S; Martínez, T; Massimi, C; Mastinu, P; Mengoni, A; Milazzo, P M; Moreau, C; Mosconi, M; Neves, F; Oberhummer, H; O'Brien, S; Oshima, M; Pancin, J; Papachristodoulou, C; Papadopoulos, C; Paradela, C; Patronis, N; Pavlik, A; Pavlopoulos, P; Perrot, L; Pigni, M T; Plag, R; Plompen, A; Plukis, A; Poch, A; Pretel, C; Quesada, J; Rauscher, T; Reifarth, R; Rosetti, M; Rubbia, C; Rudolf, G; Rullhusen, P; Salgado, J; Sarchiapone, L; Savvidis, I; Stephan, C; Tagliente, G; Tain, J L; Tassan-Got, L; Tavora, L; Terlizzi, R; Vannini, G; Vaz, P; Ventura, A; Villamarin, D; Vicente, M C; Vlachoudis, V; Vlastou, R; Voss, F; Walter, S; Wendler, H; Wiescher, M; Wisshak, K

2010-01-01

In 2002, an innovative neutron time-of-flight facility started operation at CERN: n_TOF. The main characteristics that make the new facility unique are the high instantaneous neutron flux, high resolution and wide energy range. Combined with state-of-the-art detectors and data acquisition system, these features have allowed to collect high accuracy neutron cross-section data on a variety of isotopes, many of which radioactive, of interest for Nuclear Astrophysics and for applications to advanced reactor technologies. A review of the most important results on capture and fission reactions obtained so far at n_TOF is presented, together with plans for new measurements related to nuclear industry. Copyright 2010 Elsevier Ltd. All rights reserved.

iGRaND: an invariant frame for RGBD sensor feature detection and descriptor extraction with applications

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Brink, Kevin M.

2016-06-01

This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel local reference frame derived from the image gradient and depth normal (hence iGRaND) that is invariant to scale and viewpoint for Lambertian surfaces. Using this reference frame, Euclidean invariant feature components are computed at keypoints which fuse local geometric shape information with surface appearance information. The performance of the feature for real-time odometry is analyzed and its computational complexity and accuracy is compared with leading alternative 3D features.

GATOR: Requirements capturing of telephony features

NASA Technical Reports Server (NTRS)

Dankel, Douglas D., II; Walker, Wayne; Schmalz, Mark

1992-01-01

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues.

Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

NASA Astrophysics Data System (ADS)

Oustimov, Andrew; Gastounioti, Aimilia; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

We assess the feasibility of a parenchymal texture feature fusion approach, utilizing a convolutional neural network (ConvNet) architecture, to benefit breast cancer risk assessment. Hypothesizing that by capturing sparse, subtle interactions between localized motifs present in two-dimensional texture feature maps derived from mammographic images, a multitude of texture feature descriptors can be optimally reduced to five meta-features capable of serving as a basis on which a linear classifier, such as logistic regression, can efficiently assess breast cancer risk. We combine this methodology with our previously validated lattice-based strategy for parenchymal texture analysis and we evaluate the feasibility of this approach in a case-control study with 424 digital mammograms. In a randomized split-sample setting, we optimize our framework in training/validation sets (N=300) and evaluate its descriminatory performance in an independent test set (N=124). The discriminatory capacity is assessed in terms of the the area under the curve (AUC) of the receiver operator characteristic (ROC). The resulting meta-features exhibited strong classification capability in the test dataset (AUC = 0.90), outperforming conventional, non-fused, texture analysis which previously resulted in an AUC=0.85 on the same case-control dataset. Our results suggest that informative interactions between localized motifs exist and can be extracted and summarized via a fairly simple ConvNet architecture.

The Frozen Canyons of Pluto North Pole

NASA Image and Video Library

2016-02-27

This ethereal scene captured by NASA New Horizons spacecraft tells yet another story of Pluto diversity of geological and compositional features-this time in an enhanced color image of the north polar area.

Capturing the benefits of complete streets.

DOT National Transportation Integrated Search

2015-12-01

Anecdotal information indicates that private investment and property value increases are associated : with featured Complete Streets projects. However, to date, little research has been done to confirm : these benefits. Much of the relevant literatur...

Featured Image | Galaxy of Images

Science.gov Websites

our most popular images is that of renowned female scientist (and the first recipient of two Nobel cameras as the perfect way to capture summer memories. This adventurous female copilot attempts to

3D Representative Volume Element Reconstruction of Fiber Composites via Orientation Tensor and Substructure Features

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

Li, Yi; Chen, Wei; Xu, Hongyi

To provide a seamless integration of manufacturing processing simulation and fiber microstructure modeling, two new stochastic 3D microstructure reconstruction methods are proposed for two types of random fiber composites: random short fiber composites, and Sheet Molding Compounds (SMC) chopped fiber composites. A Random Sequential Adsorption (RSA) algorithm is first developed to embed statistical orientation information into 3D RVE reconstruction of random short fiber composites. For the SMC composites, an optimized Voronoi diagram based approach is developed for capturing the substructure features of SMC chopped fiber composites. The proposed methods are distinguished from other reconstruction works by providing a way ofmore » integrating statistical information (fiber orientation tensor) obtained from material processing simulation, as well as capturing the multiscale substructures of the SMC composites.« less

Evaluation of IgY capture ELISA for sensitive detection of alpha hemolysin of Staphylococcus aureus without staphylococcal protein A interference.

PubMed

Reddy, Prakash Kudumala; Shekar, Aravind; Kingston, Joseph Jeyabalaji; Sripathy, Murali Harishchandra; Batra, Harshvardhan

2013-05-31

Staphylococcal protein A (Spa) secreted by all Staphylococcus aureus strains is the major hindrance in development of specific immunoassays for detecting S. aureus antigens, because of its characteristic feature of binding to Fc region of most mammalian immunoglobulins and also to Fab region of certain classes of mammalian immunoglobulins. Immunoglobulin Y (IgY) is the avian equivalent of mammalian IgG which does not have any affinity to Spa. In the present study we report that using chicken egg yolk IgY over mammalian IgG as capture antibody prevents both soluble and surface bound protein A from causing false positives quantified by chicken anti-protein A antibodies. This was demonstrated by development of sandwich ELISA for detection of alpha hemolysin toxin from culture supernatants of S. aureus strains with anti alpha hemolysin IgY as capture and rabbit anti alpha hemolysin IgG as revealing antibody. This indirect sandwich ELISA was evaluated onto a large number of S. aureus isolates recovered from clinical sources for alpha hemolysin secretion. Results of sandwich ELISA were compared with PCR and Western blot analysis. The immunoassay is highly specific and has high sensitivity of detecting less than 1 ng/ml. This procedure is highly effective in eliminating Spa interference and can be extended to detection of other important superantigen toxins of S. aureus. Copyright © 2013 Elsevier B.V. All rights reserved.

Towards boron neutron capture therapy: the formulation and preliminary in vitro evaluation of liposomal vehicles for the therapeutic delivery of the dequalinium salt of bis-nido-carborane.

PubMed

Theodoropoulos, Dimitrios; Rova, Aikaterini; Smith, James R; Barbu, Eugen; Calabrese, Gianpiero; Vizirianakis, Ioannis S; Tsibouklis, John; Fatouros, Dimitrios G

2013-11-15

Liposomes of phosphatidylcholine or of dimyristoylphosphatidylcholine that incorporate bis-nido-carborane dequalinium salt are stable in physiologically relevant media and have in vitro toxicity profiles that appear to be compatible with potential therapeutic applications. These features render the structures suitable candidate boron-delivery vehicles for evaluation in the boron neutron capture therapy of cancer. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Survey of XOR as a Digital Obfuscation Technique in a Corpus of Real Data

DTIC Science & Technology

2014-01-17

changing nine byte key [30]. Even advanced malware, such as Stuxnet, Duqu , Flame, and Red October, were observed to use XOR as the basis of a simple...obfuscation algorithm to hide data that they were stealing [37]. Stuxnet uses a 31-byte key with XOR [15]. Duqu XORs data from its keylogger and sends it...back to its server [37]. Similar to Duqu , Flame employs XOR obfuscation techniques on captured data, but contains extensive data-capturing features

Graphene-based porous silica sheets impregnated with polyethyleneimine for superior CO2 capture.

PubMed

Yang, Shubin; Zhan, Liang; Xu, Xiaoyue; Wang, Yanli; Ling, Licheng; Feng, Xinliang

2013-04-18

It is demonstrated that graphene-based porous silica sheets can serve as an efficient carrier support for PEI via a simple nanocasting technology. The resulting materials possess thin nature, high PEI loading content and high thermal-conductivity. Such features are favorable for the efficient diffusion and adsorption of CO2 as well as the rapid thermal transfer during the CO2 capture process. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of a piecewise linear omnidirectional 3D image registration method

NASA Astrophysics Data System (ADS)

Bae, Hyunsoo; Kang, Wonjin; Lee, SukGyu; Kim, Youngwoo

2016-12-01

This paper proposes a new piecewise linear omnidirectional image registration method. The proposed method segments an image captured by multiple cameras into 2D segments defined by feature points of the image and then stitches each segment geometrically by considering the inclination of the segment in the 3D space. Depending on the intended use of image registration, the proposed method can be used to improve image registration accuracy or reduce the computation time in image registration because the trade-off between the computation time and image registration accuracy can be controlled for. In general, nonlinear image registration methods have been used in 3D omnidirectional image registration processes to reduce image distortion by camera lenses. The proposed method depends on a linear transformation process for omnidirectional image registration, and therefore it can enhance the effectiveness of the geometry recognition process, increase image registration accuracy by increasing the number of cameras or feature points of each image, increase the image registration speed by reducing the number of cameras or feature points of each image, and provide simultaneous information on shapes and colors of captured objects.

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

Potash, Peter J.; Bell, Eric B.; Harrison, Joshua J.

Predictive models for tweet deletion have been a relatively unexplored area of Twitter-related computational research. We first approach the deletion of tweets as a spam detection problem, applying a small set of handcrafted features to improve upon the current state-of-the- art in predicting deleted tweets. Next, we apply our approach to a dataset of deleted tweets that better reflects the current deletion rate. Since tweets are deleted for reasons beyond just the presence of spam, we apply topic modeling and text embeddings in order to capture the semantic content of tweets that can lead to tweet deletion. Our goal ismore » to create an effective model that has a low-dimensional feature space and is also language-independent. A lean model would be computationally advantageous processing high-volumes of Twitter data, which can reach 9,885 tweets per second. Our results show that a small set of spam-related features combined with word topics and character-level text embeddings provide the best f1 when trained with a random forest model. The highest precision of the deleted tweet class is achieved by a modification of paragraph2vec to capture author identity.« less

Prey-capture Strategies of Fish-hunting Cone Snails: Behavior, Neurobiology and Evolution

PubMed Central

Olivera, Baldomero M.; Seger, Jon; Horvath, Martin P.; Fedosov, Alexander

2015-01-01

The venomous fish-hunting cone snails (Conus) comprise eight distinct lineages evolved from ancestors that preyed on worms. In this article we attempt to reconstruct events resulting in this shift in food resource by closely examining patterns of behavior, biochemical agents (toxins) that facilitate prey capture, and the combinations of toxins present in extant species. The first sections introduce three different hunting behaviors associated with piscivory: “taser and tether”, “net engulfment”, and “strike and stalk”. The first two fish-hunting behaviors are clearly associated with distinct groups of venom components, called cabals, which act in concert to modify the behavior of prey in a specific manner. Derived fish-hunting behavior clearly also correlates with physical features of the radular tooth, the device that injects these biochemical components. Mapping behavior, biochemical components, and radular tooth features onto phylogenetic trees shows that fish-hunting behavior emerged at lease twice during evolution. The system presented here may be one of the best examples where diversity in structure, physiology and molecular features was initially driven by particular pathways selected through behavior. PMID:26397110

Balance in non-hydrostatic rotating stratified turbulence

NASA Astrophysics Data System (ADS)

McKiver, William J.; Dritschel, David G.

It is now well established that two distinct types of motion occur in geophysical turbulence: slow motions associated with potential vorticity advection and fast oscillations due to inertiamaster variable this is known as balance. In real geophysical flows, deviations from balance in the form of inertiaimbalance|N/f) where optimal potential vorticity balancenonlinear quasi-geostrophic balance’ procedure expands the equations of motion to second order in Rossby number but retains the exact (unexpanded) definition of potential vorticity. This proves crucial for obtaining an accurate estimate of balanced motions. In the analysis of rotating stratified turbulence at Ro1 and N/f1, this procedure captures a significantly greater fraction of the underlying balance than standard (linear) quasi-geostrophic balance (which is based on the linearized equations about a state of rest). Nonlinear quasi-geostrophic balance also compares well with optimal potential vorticity balance, which captures the greatest fraction of the underlying balance overall.More fundamentally, the results of these analyses indicate that balance dominates in carefully initialized simulations of freely decaying rotating stratified turbulence up to O(1) Rossby numbers when N/f1. The fluid motion exhibits important quasi-geostrophic features with, in particular, typical height-to-width scale ratios remaining comparable to f/N.

Impact of elicited mood on movement expressivity during a fitness task.

PubMed

Giraud, Tom; Focone, Florian; Isableu, Brice; Martin, Jean-Claude; Demulier, Virginie

2016-10-01

The purpose of the present study was to evaluate the impact of four mood conditions (control, positive, negative, aroused) on movement expressivity during a fitness task. Motion capture data from twenty individuals were recorded as they performed a predefined motion sequence. Moods were elicited using task-specific scenarii to keep a valid context. Movement qualities inspired by Effort-Shape framework (Laban & Ullmann, 1971) were computed (i.e., Impulsiveness, Energy, Directness, Jerkiness and Expansiveness). A reduced number of computed features from each movement quality was selected via Principal Component Analyses. Analyses of variance and Generalized Linear Mixed Models were used to identify movement characteristics discriminating the four mood conditions. The aroused mood condition was strongly associated with increased mean Energy compared to the three other conditions. The positive and negative mood conditions showed more subtle differences interpreted as a result of their moderate activation level. Positive mood was associated with more impulsive movements and negative mood was associated with more tense movements (i.e., reduced variability and increased Jerkiness). Findings evidence the key role of movement qualities in capturing motion signatures of moods and highlight the importance of task context in their interpretations. Copyright © 2016 Elsevier B.V. All rights reserved.

DeitY-TU face database: its design, multiple camera capturing, characteristics, and evaluation

NASA Astrophysics Data System (ADS)

Bhowmik, Mrinal Kanti; Saha, Kankan; Saha, Priya; Bhattacharjee, Debotosh

2014-10-01

The development of the latest face databases is providing researchers different and realistic problems that play an important role in the development of efficient algorithms for solving the difficulties during automatic recognition of human faces. This paper presents the creation of a new visual face database, named the Department of Electronics and Information Technology-Tripura University (DeitY-TU) face database. It contains face images of 524 persons belonging to different nontribes and Mongolian tribes of north-east India, with their anthropometric measurements for identification. Database images are captured within a room with controlled variations in illumination, expression, and pose along with variability in age, gender, accessories, make-up, and partial occlusion. Each image contains the combined primary challenges of face recognition, i.e., illumination, expression, and pose. This database also represents some new features: soft biometric traits such as mole, freckle, scar, etc., and facial anthropometric variations that may be helpful for researchers for biometric recognition. It also gives an equivalent study of the existing two-dimensional face image databases. The database has been tested using two baseline algorithms: linear discriminant analysis and principal component analysis, which may be used by other researchers as the control algorithm performance score.

Flotation preferentially selects saccate pollen during conifer pollination.

PubMed

Leslie, Andrew B

2010-10-01

• Among many species of living conifers the presence of pollen with air bladders (saccate pollen) is strongly associated with downward-facing ovules and the production of pollination drops. This combination of features enables saccate pollen grains captured in the pollination drop to float upwards into the ovule. Despite the importance of this mechanism in understanding reproduction in living conifers and in extinct seed plants with similar morphologies, experiments designed to test its effectiveness have yielded equivocal results. • In vitro and in vivo pollination experiments using saccate and nonsaccate pollen were performed using modeled ovules and two Pinus species during their natural pollination period. • Buoyant saccate pollen readily floated through aqueous droplets, separating these grains from nonbuoyant pollen and spores. Ovules that received saccate pollen, nonsaccate pollen or a mixture of both all showed larger amounts and higher proportions of saccate pollen inside ovules after drop secretion. • These results demonstrate that flotation is an effective mechanism of pollen capture and transport in gymnosperms, and suggest that the prevalence of saccate grains and downward-facing ovules in the evolutionary history of seed plants is a result of the widespread use of this mechanism.

The application of 3D Zernike moments for the description of "model-free" molecular structure, functional motion, and structural reliability.

PubMed

Grandison, Scott; Roberts, Carl; Morris, Richard J

2009-03-01

Protein structures are not static entities consisting of equally well-determined atomic coordinates. Proteins undergo continuous motion, and as catalytic machines, these movements can be of high relevance for understanding function. In addition to this strong biological motivation for considering shape changes is the necessity to correctly capture different levels of detail and error in protein structures. Some parts of a structural model are often poorly defined, and the atomic displacement parameters provide an excellent means to characterize the confidence in an atom's spatial coordinates. A mathematical framework for studying these shape changes, and handling positional variance is therefore of high importance. We present an approach for capturing various protein structure properties in a concise mathematical framework that allows us to compare features in a highly efficient manner. We demonstrate how three-dimensional Zernike moments can be employed to describe functions, not only on the surface of a protein but throughout the entire molecule. A number of proof-of-principle examples are given which demonstrate how this approach may be used in practice for the representation of movement and uncertainty.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

Posture recognition associated with lifting of heavy objects using Kinect and Adaboost

NASA Astrophysics Data System (ADS)

Raut, Sayli; Navaneethakrishna, M.; Ramakrishnan, S.

2017-12-01

Lifting of heavy objects is the common task in the industries. Recent statistics from the Bureau of Labour indicate, back injuries account for one of every five injuries in the workplace. Eighty per cent of these injuries occur to the lower back and are associated with manual materials handling tasks. According to the Industrial ergonomic safety manual, Squatting is the correct posture for lifting a heavy object. In this work, an attempt has been made to monitor posture of the workers during squat and stoop using 3D motion capture and machine learning techniques. For this, Microsoft Kinect V2 is used for capturing the depth data. Further, Dynamic Time Warping and Euclidian distance algorithms are used for extraction of features. Ada-boost algorithm is used for classification of stoop and squat. The results show that the 3D image data is large and complex to analyze. The application of nonlinear and linear metrics captures the variation in the lifting pattern. Additionally, the features extracted from this metric resulted in a classification accuracy of 85% and 81% respectively. This framework may be put-upon to alert the workers in the industrial ergonomic environments.

Artificially intelligent recognition of Arabic speaker using voice print-based local features

NASA Astrophysics Data System (ADS)

Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

2016-11-01

Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

Filament capturing with the multimaterial moment-of-fluid method*

DOE PAGES

Jemison, Matthew; Sussman, Mark; Shashkov, Mikhail

2015-01-15

A novel method for capturing two-dimensional, thin, under-resolved material configurations, known as “filaments,” is presented in the context of interface reconstruction. This technique uses a partitioning procedure to detect disconnected regions of material in the advective preimage of a cell (indicative of a filament) and makes use of the existing functionality of the Multimaterial Moment-of-Fluid interface reconstruction method to accurately capture the under-resolved feature, while exactly conserving volume. An algorithm for Adaptive Mesh Refinement in the presence of filaments is developed so that refinement is introduced only near the tips of filaments and where the Moment-of-Fluid reconstruction error is stillmore » large. Comparison to the standard Moment-of-Fluid method is made. As a result, it is demonstrated that using filament capturing at a given resolution yields gains in accuracy comparable to introducing an additional level of mesh refinement at significantly lower cost.« less

Optical surface profiling of orb-web spider capture silks.

PubMed

Kane, D M; Joyce, A M; Staib, G R; Herberstein, M E

2010-09-01

Much spider silk research to date has focused on its mechanical properties. However, the webs of many orb-web spiders have evolved for over 136 million years to evade visual detection by insect prey. It is therefore a photonic device in addition to being a mechanical device. Herein we use optical surface profiling of capture silks from the webs of adult female St Andrews cross spiders (Argiope keyserlingi) to successfully measure the geometry of adhesive silk droplets and to show a bowing in the aqueous layer on the spider capture silk between adhesive droplets. Optical surface profiling shows geometric features of the capture silk that have not been previously measured and contributes to understanding the links between the physical form and biological function. The research also demonstrates non-standard use of an optical surface profiler to measure the maximum width of a transparent micro-sized droplet (microlens).

Numerical Investigation of Vertical Plunging Jet Using a Hybrid Multifluid–VOF Multiphase CFD Solver

DOE PAGES

Shonibare, Olabanji Y.; Wardle, Kent E.

2015-06-28

A novel hybrid multiphase flow solver has been used to conduct simulations of a vertical plunging liquid jet. This solver combines a multifluid methodology with selective interface sharpening to enable simulation of both the initial jet impingement and the long-time entrained bubble plume phenomena. Models are implemented for variable bubble size capturing and dynamic switching of interface sharpened regions to capture transitions between the initially fully segregated flow types into the dispersed bubbly flow regime. It was found that the solver was able to capture the salient features of the flow phenomena under study and areas for quantitative improvement havemore » been explored and identified. In particular, a population balance approach is employed and detailed calibration of the underlying models with experimental data is required to enable quantitative prediction of bubble size and distribution to capture the transition between segregated and dispersed flow types with greater fidelity.« less

Hybrid Spreading Mechanisms and T Cell Activation Shape the Dynamics of HIV-1 Infection

PubMed Central

Zhang, Changwang; Zhou, Shi; Groppelli, Elisabetta; Pellegrino, Pierre; Williams, Ian; Borrow, Persephone; Chain, Benjamin M.; Jolly, Clare

2015-01-01

HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments’ influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies. PMID:25837979

Comparative A/B testing a mobile data acquisition app for hydrogeochemistry

NASA Astrophysics Data System (ADS)

Klump, Jens; Golodoniuc, Pavel; Reid, Nathan; Gray, David; Ross, Shawn

2015-04-01

In the context of a larger study on the Capricorn Orogen of Western Australia, the CSIRO Mineral Discovery Program is conducting a regional study of the hydrogeochemistry on water from agricultural and other bores. Over time, the sampling process was standardised and a form for capturing metadata and data from initial measurements was developed. In 2014 an extensive technology review was conducted with an aim to automate field data acquisition process. A prototype hydrogeochemistry data capture form was implemented as a mobile application for Windows Mobile devices. This version of the software was a standalone application with an interface to export data as CSV files. A second candidate version of the hydrogeochemistry data capture form was implemented as an Android mobile application in the FAIMS framework. FAIMS is a framework for mobile field data capture, originally developed by at the University of New South Wales for archaeological field data collection. A benefit of the FAIMS application was the ability to associate photographs taken with the device's embedded camera with the captured data. FAIMS also allows networked collaboration within a field team, using the mobile applications as asynchronous rich clients. The network infrastructure can be installed in the field ("FAIMS in a Box") to supply data synchronisation, backup and transfer. This aspect will be tested in the next field season. A benefit of the FAIMS application was the ability to associate photographs taken with the device's embedded camera with the captured data. Having two data capture applications available allowed us to conduct an A/B test, comparing two different implementations for the same task. Both applications were trialled in the field by different field crews and user feedback will be used to improve the usability of the app for the next field season. A key learning was that the ergonomics of the app is at paramount importance to gain the user acceptance. This extends from general fit with the standard procedures used in the field during data acquisition to self-descriptive and intuitive user interface features well aligned with the workflows and sequence of actions performed by a user that ultimately contributes to the implementation of a Collect-As-You-Go approach. In the Australian outback, issues such as absence of network connectivity, heat and sun glare may challenge the utility of tablet based applications in the field. Due to limitations of tablet use in the field we also consider the use of smart pens for data capture. A smart pen application based on Anoto forms and software by Formidable will be tested in the next field season.

New Finger Biometric Method Using Near Infrared Imaging

PubMed Central

Lee, Eui Chul; Jung, Hyunwoo; Kim, Daeyeoul

2011-01-01

In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified Gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting each feature using different methods, the modified Gaussian high-pass filter is fully convolved. Therefore, the extracted binary patterns of finger images include the multimodal features of veins and finger geometries. Experimental results show that the proposed method has an error rate of 0.13%. PMID:22163741

South Polar Surface

NASA Image and Video Library

2011-07-14

It is high summer as NASA 2001 Mars Odyssey spacecraft captures this image of the South Pole of Mars. The circular surface features may look like swiss cheese, but how they form, coalesce, and disappear is not fully understood.

Dawn LAMO Image 33

NASA Image and Video Library

2016-02-24

NASA Dawn spacecraft captured this view of a region in the mid-southern latitudes of Ceres. The largest crater in the scene is Fluusa. Fluusa has a densely cratered floor and therefore is interpreted as an old impact feature.

Influence of trap modifications and environmental predictors on capture success of southern flying squirrels

USGS Publications Warehouse

Jacques, Christopher N.; Zweep, James S.; Scheihing, Mary E.; Rechkemmer, Will T.; Jenkins, Sean E.; Klaver, Robert W.; Dubay, Shelli A.

2017-01-01

Sherman traps are the most commonly used live traps in studies of small mammals and have been successfully used in the capture of arboreal species such as the southern flying squirrel (Glaucomys volans). However, southern flying squirrels spend proportionately less time foraging on the ground, which necessitates above-ground trapping methods and modifications of capture protocols. Further, quantitative estimates of the factors affecting capture success of flying squirrel populations have focused solely on effects of trapping methodologies. We developed and evaluated the efficacy of a portable Sherman trap design for capturing southern flying squirrels during 2015–2016 at the Alice L. Kibbe Field Station, Illinois, USA. Additionally, we used logistic regression to quantify potential effects of time-dependent (e.g., weather) and time-independent (e.g., habitat, extrinsic) factors on capture success of southern flying squirrels. We recorded 165 capture events (119 F, 44 M, 2 unknown) using our modified Sherman trap design. Probability of capture success decreased 0.10/1° C increase in daily maximum temperature and by 0.09/unit increase (km/hr) in wind speed. Conversely, probability of capture success increased by 1.2/1° C increase in daily minimum temperature. The probability of capturing flying squirrels was negatively associated with trap orientation. When tree-mounted traps are required, our modified trap design is a safe, efficient, and cost-effective method of capturing animals when moderate weather (temp and wind speed) conditions prevail. Further, we believe that strategic placement of traps (e.g., northeast side of tree) and quantitative information on site-specific (e.g., trap location) characteristics (e.g., topographical features, slope, aspect, climatologic factors) could increase southern flying squirrel capture success. © 2017 The Wildlife Society.

Including pride and its group-based, relational, and contextual features in theories of contempt.

PubMed

Sullivan, Gavin Brent

2017-01-01

Sentiment includes emotional and enduring attitudinal features of contempt, but explaining contempt as a mixture of basic emotion system affects does not adequately address the family resemblance structure of the concept. Adding forms of individual, group-based, and widely shared arrogance and contempt is necessary to capture the complex mixed feelings of proud superiority when "looking down upon" and acting harshly towards others.

Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production

PubMed Central

2013-01-01

Background During cellulosic ethanol production, cellulose hydrolysis is achieved by synergistic action of cellulase enzyme complex consisting of multiple enzymes with different mode of actions. Enzymatic hydrolysis of cellulose is one of the bottlenecks in the commercialization of the process due to low hydrolysis rates and high cost of enzymes. A robust hydrolysis model that can predict hydrolysis profile under various scenarios can act as an important forecasting tool to improve the hydrolysis process. However, multiple factors affecting hydrolysis: cellulose structure and complex enzyme-substrate interactions during hydrolysis make it diffucult to develop mathematical kinetic models that can simulate hydrolysis in presence of multiple enzymes with high fidelity. In this study, a comprehensive hydrolysis model based on stochastic molecular modeling approch in which each hydrolysis event is translated into a discrete event is presented. The model captures the structural features of cellulose, enzyme properties (mode of actions, synergism, inhibition), and most importantly dynamic morphological changes in the substrate that directly affect the enzyme-substrate interactions during hydrolysis. Results Cellulose was modeled as a group of microfibrils consisting of elementary fibrils bundles, where each elementary fibril was represented as a three dimensional matrix of glucose molecules. Hydrolysis of cellulose was simulated based on Monte Carlo simulation technique. Cellulose hydrolysis results predicted by model simulations agree well with the experimental data from literature. Coefficients of determination for model predictions and experimental values were in the range of 0.75 to 0.96 for Avicel hydrolysis by CBH I action. Model was able to simulate the synergistic action of multiple enzymes during hydrolysis. The model simulations captured the important experimental observations: effect of structural properties, enzyme inhibition and enzyme loadings on the hydrolysis and degree of synergism among enzymes. Conclusions The model was effective in capturing the dynamic behavior of cellulose hydrolysis during action of individual as well as multiple cellulases. Simulations were in qualitative and quantitative agreement with experimental data. Several experimentally observed phenomena were simulated without the need for any additional assumptions or parameter changes and confirmed the validity of using the stochastic molecular modeling approach to quantitatively and qualitatively describe the cellulose hydrolysis. PMID:23638989

Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

NASA Astrophysics Data System (ADS)

Fayaz, S. M.; Rajanikant, G. K.

2014-07-01

Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

Clinical Named Entity Recognition Using Deep Learning Models.

PubMed

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER.

Hierarchical streamline bundles.

PubMed

Yu, Hongfeng; Wang, Chaoli; Shene, Ching-Kuang; Chen, Jacqueline H

2012-08-01

Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.

A large-scale dataset of solar event reports from automated feature recognition modules

NASA Astrophysics Data System (ADS)

Schuh, Michael A.; Angryk, Rafal A.; Martens, Petrus C.

2016-05-01

The massive repository of images of the Sun captured by the Solar Dynamics Observatory (SDO) mission has ushered in the era of Big Data for Solar Physics. In this work, we investigate the entire public collection of events reported to the Heliophysics Event Knowledgebase (HEK) from automated solar feature recognition modules operated by the SDO Feature Finding Team (FFT). With the SDO mission recently surpassing five years of operations, and over 280,000 event reports for seven types of solar phenomena, we present the broadest and most comprehensive large-scale dataset of the SDO FFT modules to date. We also present numerous statistics on these modules, providing valuable contextual information for better understanding and validating of the individual event reports and the entire dataset as a whole. After extensive data cleaning through exploratory data analysis, we highlight several opportunities for knowledge discovery from data (KDD). Through these important prerequisite analyses presented here, the results of KDD from Solar Big Data will be overall more reliable and better understood. As the SDO mission remains operational over the coming years, these datasets will continue to grow in size and value. Future versions of this dataset will be analyzed in the general framework established in this work and maintained publicly online for easy access by the community.

Morphology captures diet and locomotor types in rodents.

PubMed

Verde Arregoitia, Luis D; Fisher, Diana O; Schweizer, Manuel

2017-01-01

To understand the functional meaning of morphological features, we need to relate what we know about morphology and ecology in a meaningful, quantitative framework. Closely related species usually share more phenotypic features than distant ones, but close relatives do not necessarily have the same ecologies. Rodents are the most diverse group of living mammals, with impressive ecomorphological diversification. We used museum collections and ecological literature to gather data on morphology, diet and locomotion for 208 species of rodents from different bioregions to investigate how morphological similarity and phylogenetic relatedness are associated with ecology. After considering differences in body size and shared evolutionary history, we find that unrelated species with similar ecologies can be characterized by a well-defined suite of morphological features. Our results validate the hypothesized ecological relevance of the chosen traits. These cranial, dental and external (e.g. ears) characters predicted diet and locomotion and showed consistent differences among species with different feeding and substrate use strategies. We conclude that when ecological characters do not show strong phylogenetic patterns, we cannot simply assume that close relatives are ecologically similar. Museum specimens are valuable records of species' phenotypes and with the characters proposed here, morphology can reflect functional similarity, an important component of community ecology and macroevolution.

Clinical Named Entity Recognition Using Deep Learning Models

PubMed Central

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER. PMID:29854252

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method

USGS Publications Warehouse

Cheruvelil, Kendra Spence; Yuan, Shuai; Webster, Katherine E.; Tan, Pang-Ning; Lapierre, Jean-Francois; Collins, Sarah M.; Fergus, C. Emi; Scott, Caren E.; Norton Henry, Emily; Soranno, Patricia A.; Filstrup, Christopher T.; Wagner, Tyler

2017-01-01

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

Larger core size has superior technical and analytical accuracy in bladder tissue microarray.

PubMed

Eskaros, Adel Rh; Egloff, Shanna A Arnold; Boyd, Kelli L; Richardson, Joyce E; Hyndman, M Eric; Zijlstra, Andries

2017-03-01

The construction of tissue microarrays (TMAs) with cores from a large number of paraffin-embedded tissues (donors) into a single paraffin block (recipient) is an effective method of analyzing samples from many patient specimens simultaneously. For the TMA to be successful, the cores within it must capture the correct histologic areas from the donor blocks (technical accuracy) and maintain concordance with the tissue of origin (analytical accuracy). This can be particularly challenging for tissues with small histological features such as small islands of carcinoma in situ (CIS), thin layers of normal urothelial lining of the bladder, or cancers that exhibit intratumor heterogeneity. In an effort to create a comprehensive TMA of a bladder cancer patient cohort that accurately represents the tumor heterogeneity and captures the small features of normal and CIS, we determined how core size (0.6 vs 1.0 mm) impacted the technical and analytical accuracy of the TMA. The larger 1.0 mm core exhibited better technical accuracy for all tissue types at 80.9% (normal), 94.2% (tumor), and 71.4% (CIS) compared with 58.6%, 85.9%, and 63.8% for 0.6 mm cores. Although the 1.0 mm core provided better tissue capture, increasing the number of replicates from two to three allowed with the 0.6 mm core compensated for this reduced technical accuracy. However, quantitative image analysis of proliferation using both Ki67+ immunofluorescence counts and manual mitotic counts demonstrated that the 1.0 mm core size also exhibited significantly greater analytical accuracy (P=0.004 and 0.035, respectively, r 2 =0.979 and 0.669, respectively). Ultimately, our findings demonstrate that capturing two or more 1.0 mm cores for TMA construction provides superior technical and analytical accuracy over the smaller 0.6 mm cores, especially for tissues harboring small histological features or substantial heterogeneity.

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method.

PubMed

Cheruvelil, Kendra Spence; Yuan, Shuai; Webster, Katherine E; Tan, Pang-Ning; Lapierre, Jean-François; Collins, Sarah M; Fergus, C Emi; Scott, Caren E; Henry, Emily Norton; Soranno, Patricia A; Filstrup, Christopher T; Wagner, Tyler

2017-05-01

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question-How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km 2 ); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation-approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.

Atmospheric CO2 capture by algae: Negative carbon dioxide emission path.

PubMed

Moreira, Diana; Pires, José C M

2016-09-01

Carbon dioxide is one of the most important greenhouse gas, which concentration increase in the atmosphere is associated to climate change and global warming. Besides CO2 capture in large emission point sources, the capture of this pollutant from atmosphere may be required due to significant contribution of diffuse sources. The technologies that remove CO2 from atmosphere (creating a negative balance of CO2) are called negative emission technologies. Bioenergy with Carbon Capture and Storage may play an important role for CO2 mitigation. It represents the combination of bioenergy production and carbon capture and storage, keeping carbon dioxide in geological reservoirs. Algae have a high potential as the source of biomass, as they present high photosynthetic efficiencies and high biomass yields. Their biomass has a wide range of applications, which can improve the economic viability of the process. Thus, this paper aims to assess the atmospheric CO2 capture by algal cultures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neutron Capture Rates and the r-Process Abundance Pattern in Shocked Neutrino-Driven Winds

NASA Astrophysics Data System (ADS)

Barringer, Daniel; Surman, Rebecca

2009-10-01

The r-process is an important process in nucleosynthesis in which nuclei will undergo rapid neutron captures. Models of the r-process require nuclear data such as neutron capture rates for thousands of individual nuclei, many of which lie far from stability. Among the potential sites for the r-process, and the one that we investigate, is the shocked neutrino-driven wind in core-collapse supernovae. Here we examine the importance of the neutron capture rates of specific, individual nuclei in the second r-process abundance peak occurring at A ˜ 130 for a range of parameterized neutrino-driven wind trajectories. Of specific interest are the nuclei whose capture rates affect the abundances of nuclei outside of the A ˜ 130 peak. We found that increasing the neutron capture rate for a number of nuclei including ^135In, ^132Sn, ^133Sb, ^137Sb, and ^136Te can produce changes in the resulting abundance pattern of up to 13%.

Is attentional prioritisation of infant faces unique in humans?: Comparative demonstrations by modified dot-probe task in monkeys.

PubMed

Koda, Hiroki; Sato, Anna; Kato, Akemi

2013-09-01

Humans innately perceive infantile features as cute. The ethologist Konrad Lorenz proposed that the infantile features of mammals and birds, known as the baby schema (kindchenschema), motivate caretaking behaviour. As biologically relevant stimuli, newborns are likely to be processed specially in terms of visual attention, perception, and cognition. Recent demonstrations on human participants have shown visual attentional prioritisation to newborn faces (i.e., newborn faces capture visual attention). Although characteristics equivalent to those found in the faces of human infants are found in nonhuman primates, attentional capture by newborn faces has not been tested in nonhuman primates. We examined whether conspecific newborn faces captured the visual attention of two Japanese monkeys using a target-detection task based on dot-probe tasks commonly used in human visual attention studies. Although visual cues enhanced target detection in subject monkeys, our results, unlike those for humans, showed no evidence of an attentional prioritisation for newborn faces by monkeys. Our demonstrations showed the validity of dot-probe task for visual attention studies in monkeys and propose a novel approach to bridge the gap between human and nonhuman primate social cognition research. This suggests that attentional capture by newborn faces is not common to macaques, but it is unclear if nursing experiences influence their perception and recognition of infantile appraisal stimuli. We need additional comparative studies to reveal the evolutionary origins of baby-schema perception and recognition. Copyright © 2013 Elsevier B.V. All rights reserved.

Interactions between ecology, demography, capture stress, and profiles of corticosterone and glucose in a free-living population of Australian freshwater crocodiles.

PubMed

Jessop, Tim S; Tucker, Anton D; Limpus, Colin J; Whittier, Joan M

2003-06-01

In this study we examined three aspects pertaining to adrenocortical responsiveness in free-ranging Australian freshwater crocodiles (Crocodylus johnstoni). First, we examined the ability of freshwater crocodiles to produce corticosterone in response to a typical capture-stress protocol. A second objective addressed the relationship between capture stress, plasma glucose and corticosterone. Next we examined if variation in basal and capture-stress-induced levels of plasma corticosterone was linked to ecological or demographic factors for individuals in this free-ranging population. Blood samples obtained on three field trips were taken from a cross-sectional sample of the population. Crocodiles were bled once during four time categories at 0, 0.5, 6, and 10h post-capture. Plasma corticosterone increased significantly with time post-capture. Plasma glucose also significantly increased with duration of capture-stress and exhibited a positive and significant relationship with plasma corticosterone. Significant variation in basal or stress induced levels of corticosterone in crocodiles was not associated with any ecological or demographic factors including sex, age class or the year of capture that the crocodiles were sampled from. However, three immature males had basal levels of plasma corticosterone greater than 2 standard deviations above the mean. While crocodiles exhibited a pronounced adrenocortical and hyperglycaemic response to capture stress, limited variation in adrenocortical responsiveness due to ecological and demographic factors was not evident. This feature could arise in part because this population was sampled during a period of environmental benigness.

A new capture fraction method to map how pumpage affects surface water flow

USGS Publications Warehouse

Leake, S.A.; Reeves, H.W.; Dickinson, J.E.

2010-01-01

All groundwater pumped is balanced by removal of water somewhere, initially from storage in the aquifer and later from capture in the form of increase in recharge and decrease in discharge. Capture that results in a loss of water in streams, rivers, and wetlands now is a concern in many parts of the United States. Hydrologists commonly use analytical and numerical approaches to study temporal variations in sources of water to wells for select points of interest. Much can be learned about coupled surface/groundwater systems, however, by looking at the spatial distribution of theoretical capture for select times of interest. Development of maps of capture requires (1) a reasonably well-constructed transient or steady state model of an aquifer with head-dependent flow boundaries representing surface water features or evapotranspiration and (2) an automated procedure to run the model repeatedly and extract results, each time with a well in a different location. This paper presents new methods for simulating and mapping capture using three-dimensional groundwater flow models and presents examples from Arizona, Oregon, and Michigan. Journal compilation ?? 2010 National Ground Water Association. No claim to original US government works.

Robust visual tracking via multiple discriminative models with object proposals

NASA Astrophysics Data System (ADS)

Zhang, Yuanqiang; Bi, Duyan; Zha, Yufei; Li, Huanyu; Ku, Tao; Wu, Min; Ding, Wenshan; Fan, Zunlin

2018-04-01

Model drift is an important reason for tracking failure. In this paper, multiple discriminative models with object proposals are used to improve the model discrimination for relieving this problem. Firstly, the target location and scale changing are captured by lots of high-quality object proposals, which are represented by deep convolutional features for target semantics. And then, through sharing a feature map obtained by a pre-trained network, ROI pooling is exploited to wrap the various sizes of object proposals into vectors of the same length, which are used to learn a discriminative model conveniently. Lastly, these historical snapshot vectors are trained by different lifetime models. Based on entropy decision mechanism, the bad model owing to model drift can be corrected by selecting the best discriminative model. This would improve the robustness of the tracker significantly. We extensively evaluate our tracker on two popular benchmarks, the OTB 2013 benchmark and UAV20L benchmark. On both benchmarks, our tracker achieves the best performance on precision and success rate compared with the state-of-the-art trackers.

Automatic crack detection and classification method for subway tunnel safety monitoring.

PubMed

Zhang, Wenyu; Zhang, Zhenjiang; Qi, Dapeng; Liu, Yun

2014-10-16

Cracks are an important indicator reflecting the safety status of infrastructures. This paper presents an automatic crack detection and classification methodology for subway tunnel safety monitoring. With the application of high-speed complementary metal-oxide-semiconductor (CMOS) industrial cameras, the tunnel surface can be captured and stored in digital images. In a next step, the local dark regions with potential crack defects are segmented from the original gray-scale images by utilizing morphological image processing techniques and thresholding operations. In the feature extraction process, we present a distance histogram based shape descriptor that effectively describes the spatial shape difference between cracks and other irrelevant objects. Along with other features, the classification results successfully remove over 90% misidentified objects. Also, compared with the original gray-scale images, over 90% of the crack length is preserved in the last output binary images. The proposed approach was tested on the safety monitoring for Beijing Subway Line 1. The experimental results revealed the rules of parameter settings and also proved that the proposed approach is effective and efficient for automatic crack detection and classification.

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

PubMed

Chin, Wei-Chien-Benny; Wen, Tzai-Hung

2015-01-01

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

Experimental study of canvas characterization for paintings

NASA Astrophysics Data System (ADS)

Cornelis, Bruno; Dooms, Ann; Munteanu, Adrian; Cornelis, Jan; Schelkens, Peter

2010-02-01

The work described here fits in the context of a larger project on the objective and relevant characterization of paintings and painting canvas through the analysis of multimodal digital images. We captured, amongst others, X-ray images of different canvas types, characterized by a variety of textures and weave patterns (fine and rougher texture; single thread and multiple threads per weave), including raw canvas as well as canvas processed with different primers. In this paper, we study how to characterize the canvas by extracting global features such as average thread width, average distance between successive threads (i.e. thread density) and the spatial distribution of primers. These features are then used to construct a generic model of the canvas structure. Secondly, we investigate whether we can identify different pieces of canvas coming from the same bolt. This is an important element for dating, authentication and identification of restorations. Both the global characteristics mentioned earlier and some local properties (such as deviations from the average pattern model) are used to compare the "fingerprint" of different pieces of cloth coming from the same or different bolts.

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

Optimising measurement of health-related characteristics of the built environment: Comparing data collected by foot-based street audits, virtual street audits and routine secondary data sources.

PubMed

Pliakas, Triantafyllos; Hawkesworth, Sophie; Silverwood, Richard J; Nanchahal, Kiran; Grundy, Chris; Armstrong, Ben; Casas, Juan Pablo; Morris, Richard W; Wilkinson, Paul; Lock, Karen

2017-01-01

The role of the neighbourhood environment in influencing health behaviours continues to be an important topic in public health research and policy. Foot-based street audits, virtual street audits and secondary data sources are widespread data collection methods used to objectively measure the built environment in environment-health association studies. We compared these three methods using data collected in a nationally representative epidemiological study in 17 British towns to inform future development of research tools. There was good agreement between foot-based and virtual audit tools. Foot based audits were superior for fine detail features. Secondary data sources measured very different aspects of the local environment that could be used to derive a range of environmental measures if validated properly. Future built environment research should design studies a priori using multiple approaches and varied data sources in order to best capture features that operate on different health behaviours at varying spatial scales. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Nonlinear Dynamic Subscale Model for Partially Resolved Numerical Simulation (PRNS)/Very Large Eddy Simulation (VLES) of Internal Non-Reacting Flows

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing; Liu, nan-Suey

2010-01-01

A brief introduction of the temporal filter based partially resolved numerical simulation/very large eddy simulation approach (PRNS/VLES) and its distinct features are presented. A nonlinear dynamic subscale model and its advantages over the linear subscale eddy viscosity model are described. In addition, a guideline for conducting a PRNS/VLES simulation is provided. Results are presented for three turbulent internal flows. The first one is the turbulent pipe flow at low and high Reynolds numbers to illustrate the basic features of PRNS/VLES; the second one is the swirling turbulent flow in a LM6000 single injector to further demonstrate the differences in the calculated flow fields resulting from the nonlinear model versus the pure eddy viscosity model; the third one is a more complex turbulent flow generated in a single-element lean direct injection (LDI) combustor, the calculated result has demonstrated that the current PRNS/VLES approach is capable of capturing the dynamically important, unsteady turbulent structures while using a relatively coarse grid.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system.

PubMed

Min, Jianliang; Wang, Ping; Hu, Jianfeng

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1-2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver.

Response of the North Pacific Oscillation to global warming in the models of the Intergovernmental Panel on Climate Change Fourth Assessment Report

NASA Astrophysics Data System (ADS)

Chen, Zheng; Gan, Bolan; Wu, Lixin

2017-09-01

Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillation (NPO), which is the second most important factor determining the wintertime sea level pressure field in simulations of the pre-industrial control climate, and evaluate the NPO response to the future most reasonable global warming scenario (the A1B scenario). We reveal that while most models simulate the geographic distribution and amplitude of the NPO pattern satisfactorily, only 13 models capture both features well. However, the temporal variability of the simulated NPO could not be significantly correlated with the observations. Further analysis indicates the weakened NPO intensity for a scenario of strong global warming is attributable to the reduced lower-tropospheric baroclinicity at mid-latitudes, which is anticipated to disrupt large-scale and low-frequency atmospheric variability, resulting in the diminished transfer of energy to the NPO, together with its northward shift.

Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang; Qi, Dapeng; Liu, Yun

2014-01-01

Cracks are an important indicator reflecting the safety status of infrastructures. This paper presents an automatic crack detection and classification methodology for subway tunnel safety monitoring. With the application of high-speed complementary metal-oxide-semiconductor (CMOS) industrial cameras, the tunnel surface can be captured and stored in digital images. In a next step, the local dark regions with potential crack defects are segmented from the original gray-scale images by utilizing morphological image processing techniques and thresholding operations. In the feature extraction process, we present a distance histogram based shape descriptor that effectively describes the spatial shape difference between cracks and other irrelevant objects. Along with other features, the classification results successfully remove over 90% misidentified objects. Also, compared with the original gray-scale images, over 90% of the crack length is preserved in the last output binary images. The proposed approach was tested on the safety monitoring for Beijing Subway Line 1. The experimental results revealed the rules of parameter settings and also proved that the proposed approach is effective and efficient for automatic crack detection and classification. PMID:25325337

MTTE: an innovative strategy for the evaluation of targeted/exome enrichment efficiency

PubMed Central

Klonowska, Katarzyna; Handschuh, Luiza; Swiercz, Aleksandra; Figlerowicz, Marek; Kozlowski, Piotr

2016-01-01

Although currently available strategies for the preparation of exome-enriched libraries are well established, a final validation of the libraries in terms of exome enrichment efficiency prior to the sequencing step is of considerable importance. Here, we present a strategy for the evaluation of exome enrichment, i.e., the Multipoint Test for Targeted-enrichment Efficiency (MTTE), PCR-based approach utilizing multiplex ligation-dependent probe amplification with capillary electrophoresis separation. We used MTTE for the analysis of subsequent steps of the Illumina TruSeq Exome Enrichment procedure. The calculated values of enrichment-associated parameters (i.e., relative enrichment, relative clearance, overall clearance, and fold enrichment) and the comparison of MTTE results with the actual enrichment revealed the high reliability of our assay. Additionally, the MTTE assay enabled the determination of the sequence-associated features that may confer bias in the enrichment of different targets. Importantly, the MTTE is low cost method that can be easily adapted to the region of interest important for a particular project. Thus, the MTTE strategy is attractive for post-capture validation in a variety of targeted/exome enrichment NGS projects. PMID:27572310

MTTE: an innovative strategy for the evaluation of targeted/exome enrichment efficiency.

PubMed

Klonowska, Katarzyna; Handschuh, Luiza; Swiercz, Aleksandra; Figlerowicz, Marek; Kozlowski, Piotr

2016-10-11

Although currently available strategies for the preparation of exome-enriched libraries are well established, a final validation of the libraries in terms of exome enrichment efficiency prior to the sequencing step is of considerable importance. Here, we present a strategy for the evaluation of exome enrichment, i.e., the Multipoint Test for Targeted-enrichment Efficiency (MTTE), PCR-based approach utilizing multiplex ligation-dependent probe amplification with capillary electrophoresis separation. We used MTTE for the analysis of subsequent steps of the Illumina TruSeq Exome Enrichment procedure. The calculated values of enrichment-associated parameters (i.e., relative enrichment, relative clearance, overall clearance, and fold enrichment) and the comparison of MTTE results with the actual enrichment revealed the high reliability of our assay. Additionally, the MTTE assay enabled the determination of the sequence-associated features that may confer bias in the enrichment of different targets. Importantly, the MTTE is low cost method that can be easily adapted to the region of interest important for a particular project. Thus, the MTTE strategy is attractive for post-capture validation in a variety of targeted/exome enrichment NGS projects.

Functional morphology of the cranio-mandibular complex of the Guira cuckoo (Aves).

PubMed

Pestoni, Sofía; Degrange, Federico Javier; Tambussi, Claudia Patricia; Demmel Ferreira, María Manuela; Tirao, Germán Alfredo

2018-06-01

The cranio-mandibular complex is an important structure involved in food capture and processing. Its morphology is related to the nature of the food item. Jaw muscles enable the motion of this complex and their study is essential for functional and evolutionary analysis. The present study compares available behavioral and dietary data obtained from the literature with novel results from functional morphological analyses of the cranio-mandibular complex of the Guira cuckoo (Guira guira) to understand its relationship with the zoophagous trophic habit of this species. The bite force was estimated based on muscle dissections, measurements of the physiological cross-sectional area, and biomechanical modeling of the skull. The results were compared with the available functional morphological data for other birds. The standardized bite force of G. guira is higher than predicted for exclusively zoophagous birds, but lower than for granivorous and/or omnivorous birds. Guira guira possesses the generalized jaw muscular system of neognathous birds, but some features can be related to its trophic habit. The external adductor muscles act mainly during food item processing and multiple aspects of this muscle group are interpreted to increase bite force, that is, their high values of muscle mass, their mechanical advantage (MA), and their perpendicular orientation when the beak is closed. The m. depressor mandibulae and the m. pterygoideus dorsalis et ventralis are interpreted to prioritize speed of action (low MA values), being most important during prey capture. The supposed ecological significance of these traits is the potential to widen the range of prey size that can be processed and the possibility of rapidly capturing agile prey through changes in the leverage of the muscles involved in opening and closing of the bill. This contributes to the trophic versatility of the species and its ability to thrive in different habitats, including urban areas. © 2018 Wiley Periodicals, Inc.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California.

PubMed

Sousa, Daniel; Small, Christopher

2018-02-14

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area - despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California

PubMed Central

Small, Christopher

2018-01-01

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system. PMID:29443900

Assessing environmental features related to mental health: a reliability study of visual streetscape images.

PubMed

Wu, Yu-Tzu; Nash, Paul; Barnes, Linda E; Minett, Thais; Matthews, Fiona E; Jones, Andy; Brayne, Carol

2014-10-22

An association between depressive symptoms and features of built environment has been reported in the literature. A remaining research challenge is the development of methods to efficiently capture pertinent environmental features in relevant study settings. Visual streetscape images have been used to replace traditional physical audits and directly observe the built environment of communities. The aim of this work is to examine the inter-method reliability of the two audit methods for assessing community environments with a specific focus on physical features related to mental health. Forty-eight postcodes in urban and rural areas of Cambridgeshire, England were randomly selected from an alphabetical list of streets hosted on a UK property website. The assessment was conducted in July and August 2012 by both physical and visual image audits based on the items in Residential Environment Assessment Tool (REAT), an observational instrument targeting the micro-scale environmental features related to mental health in UK postcodes. The assessor used the images of Google Street View and virtually "walked through" the streets to conduct the property and street level assessments. Gwet's AC1 coefficients and Bland-Altman plots were used to compare the concordance of two audits. The results of conducting the REAT by visual image audits generally correspond to direct observations. More variations were found in property level items regarding physical incivilities, with broad limits of agreement which importantly lead to most of the variation in the overall REAT score. Postcodes in urban areas had lower consistency between the two methods than rural areas. Google Street View has the potential to assess environmental features related to mental health with fair reliability and provide a less resource intense method of assessing community environments than physical audits.

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

PubMed Central

Roy, Sushmita; Martinez, Diego; Platero, Harriett; Lane, Terran; Werner-Washburne, Margaret

2009-01-01

Background Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information. Results AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins. Conclusion AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains. PMID:19936254

NASA MISR Views Kruger National Park

NASA Image and Video Library

2010-10-06

This nadir camera view was captured by NASA Terra spacecraft around Kruger National Park in NE South Africa. The bright white feature is the Palabora Copper Mine, and the water body near upper right is Lake Massingir in Mozambique.

Dawn LAMO Image 89

NASA Image and Video Library

2016-05-16

This image captured by NASA Dawn spacecraft features the shadowy rim of an unnamed crater on Ceres. The crater on the left appears relatively old, as its flanks are rugged and the crater density inside it is more or less uniform.

Amygdala lesions in rhesus macaques decrease attention to threat

PubMed Central

Dal Monte, Olga; Costa, Vincent D.; Noble, Pamela L.; Murray, Elisabeth A.; Averbeck, Bruno B.

2015-01-01

Evidence from animal and human studies has suggested that the amygdala plays a role in detecting threat and in directing attention to the eyes. Nevertheless, there has been no systematic investigation of whether the amygdala specifically facilitates attention to the eyes or whether other features can also drive attention via amygdala processing. The goal of the present study was to examine the effects of amygdala lesions in rhesus monkeys on attentional capture by specific facial features, as well as gaze patterns and changes in pupil dilation during free viewing. Here we show reduced attentional capture by threat stimuli, specifically the mouth, and reduced exploration of the eyes in free viewing in monkeys with amygdala lesions. Our findings support a role for the amygdala in detecting threat signals and in directing attention to the eye region of faces when freely viewing different expressions. PMID:26658670

The Knowledge Program: an Innovative, Comprehensive Electronic Data Capture System and Warehouse

PubMed Central

Katzan, Irene; Speck, Micheal; Dopler, Chris; Urchek, John; Bielawski, Kay; Dunphy, Cheryl; Jehi, Lara; Bae, Charles; Parchman, Alandra

2011-01-01

Data contained in the electronic health record (EHR) present a tremendous opportunity to improve quality-of-care and enhance research capabilities. However, the EHR is not structured to provide data for such purposes: most clinical information is entered as free text and content varies substantially between providers. Discrete information on patients’ functional status is typically not collected. Data extraction tools are often unavailable. We have developed the Knowledge Program (KP), a comprehensive initiative to improve the collection of discrete clinical information into the EHR and the retrievability of data for use in research, quality, and patient care. A distinct feature of the KP is the systematic collection of patient-reported outcomes, which is captured discretely, allowing more refined analyses of care outcomes. The KP capitalizes on features of the Epic EHR and utilizes an external IT infrastructure distinct from Epic for enhanced functionality. Here, we describe the development and implementation of the KP. PMID:22195124

ETP-0492, Measured Residual Stresses in CYL S/N 53 Fretted Area

NASA Technical Reports Server (NTRS)

Webster, Ronald L.

1998-01-01

This test report presents the results of a residual stress survey of the inner clevis leg of lightweight cylinder SIN 053 as described by ETP-0492. The intent of this testing was to evaluate the residual stresses that occur in and around the inner clevis leg at the capture feature contact zone during a normal flight cycle. Lightweight case cylinder segment IU50717, S/N L053 from Flight STS-27 exhibited fretting around the contact zone of the inner clevis leg and the capture feature of the field joint. Post flight inspection revealed several large fitting pits on the inside of the inner clevis leg. This cylinder was assigned for both residual stress and metallurgical evaluation. This report is concerned only with the residual so= evaluations. The effects of glass bead cleaning and fi=ing were evaluated using the x-ray diffraction method.

Classification of Movement of People with Parkinsons Disease Using Wearable Inertial Movement Units and Machine Learning.

PubMed

Ireland, David; Wang, Ziwei; Lamont, Robyn; Liddle, Jacki

2016-01-01

In this work, inertial movement units were placed on people with Parkinsons disease (PwPD) who subsequently performed a standard test of walking endurance (six-minute walk test - 6MWT). Five devices were placed on each the limbs and small of the back. These devices captured the acceleration and rotational motion while the person walked as far as they can in six minutes. The wearable devices can objectively indicate the pattern and rhythmicity of limb and body movements. It is possible that this data, when subject to machine learning could provide additional objective measures that may support clinical observations related to the quality of movement. The aim of this work is two fold. First, to identify the most useful features of the captured signals; second, to identify the accuracy of using these features to predict the severity of PD as measured by standard clinical assessment.

Offline Signature Verification Using the Discrete Radon Transform and a Hidden Markov Model

NASA Astrophysics Data System (ADS)

Coetzer, J.; Herbst, B. M.; du Preez, J. A.

2004-12-01

We developed a system that automatically authenticates offline handwritten signatures using the discrete Radon transform (DRT) and a hidden Markov model (HMM). Given the robustness of our algorithm and the fact that only global features are considered, satisfactory results are obtained. Using a database of 924 signatures from 22 writers, our system achieves an equal error rate (EER) of 18% when only high-quality forgeries (skilled forgeries) are considered and an EER of 4.5% in the case of only casual forgeries. These signatures were originally captured offline. Using another database of 4800 signatures from 51 writers, our system achieves an EER of 12.2% when only skilled forgeries are considered. These signatures were originally captured online and then digitally converted into static signature images. These results compare well with the results of other algorithms that consider only global features.

Space-Weathered Anorthosite as Spectral D-Type Material on the Martian Satellites

NASA Astrophysics Data System (ADS)

Yamamoto, S.; Watanabe, S.; Matsunaga, T.

2018-02-01

Spectral D-type asteroids are characterized by dark, red-sloped, and featureless spectra at visible and near-infrared wavelengths and are thought to be composed of rocks rich in organic compounds. The Martian satellites, Phobos and Deimos, spectrally resemble D-type asteroids, suggesting that they are captured D-type asteroids from outside the Martian system. Here we show that the spectral features of lunar space-weathered anorthosite are consistent with D-type spectra, including those of Phobos and Deimos. This can also explain the distinct spectral features on Phobos, the red and blue units, as arising from different degrees of space weathering. Thus, D-type spectra of the Martian satellites can be explained by space-weathered anorthosite, indicating that D-type spectra do not necessarily support the existence of organic compounds, which would be strong evidence for the capture scenario.

The importance of service-users' perspectives: A systematic review of qualitative evidence reveals overlooked critical features of weight management programmes.

PubMed

Sutcliffe, Katy; Melendez-Torres, G J; Burchett, Helen E D; Richardson, Michelle; Rees, Rebecca; Thomas, James

2018-03-14

Extensive research effort shows that weight management programmes (WMPs) targeting both diet and exercise are broadly effective. However, the critical features of WMPs remain unclear. To develop a deeper understanding of WMPs critical features, we undertook a systematic review of qualitative evidence. We sought to understand from a service-user perspective how programmes are experienced, and may be effective, on the ground. We identified qualitative studies from existing reviews and updated the searches of one review. We included UK studies capturing the views of adult WMP users. Thematic analysis was used inductively to code and synthesize the evidence. Service users were emphatic that supportive relationships, with service providers or WMP peers, are the most critical aspect of WMPs. Supportive relationships were described as providing an extrinsic motivator or "hook" which helped to overcome barriers such as scepticism about dietary advice or a lack confidence to engage in physical activity. The evidence revealed that service-users' understandings of the critical features of WMPs differ from the focus of health promotion guidance or descriptions of evaluated programmes which largely emphasize educational or goal setting aspects of WMPs. Existing programme guidance may not therefore fully address the needs of service users. The study illustrates that the perspectives of service users can reveal unanticipated intervention mechanisms or underemphasized critical features and underscores the value of a holistic understanding about "what happens" in complex psychosocial interventions such as WMPs. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.

A parametric texture model based on deep convolutional features closely matches texture appearance for humans.

PubMed

Wallis, Thomas S A; Funke, Christina M; Ecker, Alexander S; Gatys, Leon A; Wichmann, Felix A; Bethge, Matthias

2017-10-01

Our visual environment is full of texture-"stuff" like cloth, bark, or gravel as distinct from "things" like dresses, trees, or paths-and humans are adept at perceiving subtle variations in material properties. To investigate image features important for texture perception, we psychophysically compare a recent parametric model of texture appearance (convolutional neural network [CNN] model) that uses the features encoded by a deep CNN (VGG-19) with two other models: the venerable Portilla and Simoncelli model and an extension of the CNN model in which the power spectrum is additionally matched. Observers discriminated model-generated textures from original natural textures in a spatial three-alternative oddity paradigm under two viewing conditions: when test patches were briefly presented to the near-periphery ("parafoveal") and when observers were able to make eye movements to all three patches ("inspection"). Under parafoveal viewing, observers were unable to discriminate 10 of 12 original images from CNN model images, and remarkably, the simpler Portilla and Simoncelli model performed slightly better than the CNN model (11 textures). Under foveal inspection, matching CNN features captured appearance substantially better than the Portilla and Simoncelli model (nine compared to four textures), and including the power spectrum improved appearance matching for two of the three remaining textures. None of the models we test here could produce indiscriminable images for one of the 12 textures under the inspection condition. While deep CNN (VGG-19) features can often be used to synthesize textures that humans cannot discriminate from natural textures, there is currently no uniformly best model for all textures and viewing conditions.

Neutron capture cross sections of Kr

NASA Astrophysics Data System (ADS)

Fiebiger, Stefan; Baramsai, Bayarbadrakh; Couture, Aaron; Krtička, Milan; Mosby, Shea; Reifarth, René; O'Donnell, John; Rusev, Gencho; Ullmann, John; Weigand, Mario; Wolf, Clemens

2018-01-01

Neutron capture and β- -decay are competing branches of the s-process nucleosynthesis path at 85Kr [1], which makes it an important branching point. The knowledge of its neutron capture cross section is therefore essential to constrain stellar models of nucleosynthesis. Despite its importance for different fields, no direct measurement of the cross section of 85Kr in the keV-regime has been performed. The currently reported uncertainties are still in the order of 50% [2, 3]. Neutron capture cross section measurements on a 4% enriched 85Kr gas enclosed in a stainless steel cylinder were performed at Los Alamos National Laboratory (LANL) using the Detector for Advanced Neutron Capture Experiments (DANCE). 85Kr is radioactive isotope with a half life of 10.8 years. As this was a low-enrichment sample, the main contaminants, the stable krypton isotopes 83Kr and 86Kr, were also investigated. The material was highly enriched and contained in pressurized stainless steel spheres.

Elite Capture and Corruption in two Villages in Bengkulu Province, Sumatra.

PubMed

Lucas, Anton

This paper examines leadership, elite capture and corruption in two villages in Sumatra. It compares implementation and outcomes of several conservation and development projects in the context of democratization and decentralization reforms introduced in Indonesia since 1998. In examining aspects of elite control and elite capture, this paper focuses on the activities of local elites, particularly village officials, who use their positions to monopolize planning and management of projects that were explicitly intended to incorporate participatory and accountability features. While elites' use of authority and influence to benefit personally from their roles clearly reflects elite capture, there are nonetheless members of elite groups in these case studies who use their control of projects to broad community benefit. In both villages there is considerable friction between villagers and elites as well as among members of the local elite themselves over control of local resources. Differences in the structure of these cross-cutting internal relationships and of ties between local authorities and outside government and non-government agents largely explain the differences in degree of elite capture and its outcomes in the two cases.

MODAL TRACKING of A Structural Device: A Subspace Identification Approach

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

Candy, J. V.; Franco, S. N.; Ruggiero, E. L.

Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging processing problem. To detect/classify a device subsystem from noisy data, it is necessary to identify unique signatures or particular features. An obvious feature would be resonant (modal) frequencies emitted during its normal operation. In this report, we discuss a model-based approach to incorporate these physical features into a dynamic structure that can be used for such an identification. The approach we take after pre-processing the raw vibration data and removing any extraneous disturbances is to obtain a representation ofmore » the structurally unknown device along with its subsystems that capture these salient features. One approach is to recognize that unique modal frequencies (sinusoidal lines) appear in the estimated power spectrum that are solely characteristic of the device under investigation. Therefore, the objective of this effort is based on constructing a black box model of the device that captures these physical features that can be exploited to “diagnose” whether or not the particular device subsystem (track/detect/classify) is operating normally from noisy vibrational data. Here we discuss the application of a modern system identification approach based on stochastic subspace realization techniques capable of both (1) identifying the underlying black-box structure thereby enabling the extraction of structural modes that can be used for analysis and modal tracking as well as (2) indicators of condition and possible changes from normal operation.« less

77 FR 4059 - Certain Electronic Devices for Capturing and Transmitting Images, and Components Thereof; Receipt...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-26

... Images, and Components Thereof; Receipt of Complaint; Solicitation of Comments Relating to the Public... Devices for Capturing and Transmitting Images, and Components Thereof, DN 2869; the Commission is... importation of certain electronic devices for capturing and transmitting images, and components thereof. The...

Sensitivity of a Simulated Derecho Event to Model Initial Conditions

NASA Astrophysics Data System (ADS)

Wang, Wei

2014-05-01

Since 2003, the MMM division at NCAR has been experimenting cloud-permitting scale weather forecasting using Weather Research and Forecasting (WRF) model. Over the years, we've tested different model physics, and tried different initial and boundary conditions. Not surprisingly, we found that the model's forecasts are more sensitive to the initial conditions than model physics. In 2012 real-time experiment, WRF-DART (Data Assimilation Research Testbed) at 15 km was employed to produce initial conditions for twice-a-day forecast at 3 km. On June 29, this forecast system captured one of the most destructive derecho event on record. In this presentation, we will examine forecast sensitivity to different model initial conditions, and try to understand the important features that may contribute to the success of the forecast.

FUNGIBILITY AND CONSUMER CHOICE: EVIDENCE FROM COMMODITY PRICE SHOCKS.

PubMed

Hastings, Justine S; Shapiro, Jesse M

2013-11-01

We formulate a test of the fungibility of money based on parallel shifts in the prices of different quality grades of a commodity. We embed the test in a discrete-choice model of product quality choice and estimate the model using panel microdata on gasoline purchases. We find that when gasoline prices rise consumers substitute to lower octane gasoline, to an extent that cannot be explained by income effects. Across a wide range of specifications, we consistently reject the null hypothesis that households treat "gas money" as fungible with other income. We compare the empirical fit of three psychological models of decision-making. A simple model of category budgeting fits the data well, with models of loss aversion and salience both capturing important features of the time series.

Learning Time-Varying Coverage Functions

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

Learning Time-Varying Coverage Functions.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-12-08

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data.

Algorithm research for user trajectory matching across social media networks based on paragraph2vec

NASA Astrophysics Data System (ADS)

Xu, Qian; Chen, Hongchang; Zhi, Hongxin; Wang, Yanchuan

2018-04-01

Identifying users across different social media networks (SMN) is to link accounts of the same user that belong to the same individual across SMNs. The problem is fundamental and important, and its results can benefit many applications such as cross SMN user modeling and recommendation. With the development of GPS technology and mobile communication, more and more social networks provide location services. This provides a new opportunity for cross SMN user identification. In this paper, we solve cross SMN user identification problem in an unsupervised manner by utilizing user trajectory data in SMNs. A paragraph2vec based algorithm is proposed in which location sequence feature of user trajectory is captured in temporal and spatial dimensions. Our experimental results validate the effectiveness and efficiency of our algorithm.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

PubMed Central

Siegel, Nisan; Storrie, Brian; Bruce, Marc

2016-01-01

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

Models of Protocellular Structure, Function and Evolution

NASA Technical Reports Server (NTRS)

New, Michael H.; Pohorille, Andrew; Szostak, Jack W.; Keefe, Tony; Lanyi, Janos K.; DeVincenzi, Donald L. (Technical Monitor)

2001-01-01

In the absence of any record of protocells, the most direct way to test our understanding, of the origin of cellular life is to construct laboratory models that capture important features of protocellular systems. Such efforts are currently underway in a collaborative project between NASA-Ames, Harvard Medical School and University of California. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures. The centerpiece of this project is a method for the in vitro evolution of protein enzymes toward arbitrary catalytic targets. A similar approach has already been developed for nucleic acids in which a small number of functional molecules are selected from a large, random population of candidates. The selected molecules are next vastly multiplied using the polymerase chain reaction.

Complex structures from patterned cell sheets

PubMed Central

Misra, M.; Audoly, B.; Shvartsman, S. Y.

2017-01-01

The formation of three-dimensional structures from patterned epithelial sheets plays a key role in tissue morphogenesis. An important class of morphogenetic mechanisms relies on the spatio-temporal control of apical cell contractility, which can result in the localized bending of cell sheets and in-plane cell rearrangements. We have recently proposed a modified vertex model that can be used to systematically explore the connection between the two-dimensional patterns of cell properties and the emerging three-dimensional structures. Here we review the proposed modelling framework and illustrate it through the computational analysis of the vertex model that captures the salient features of the formation of the dorsal appendages during Drosophila oogenesis. This article is part of the themed issue ‘Systems morphodynamics: understanding the development of tissue hardware’. PMID:28348251

FUNGIBILITY AND CONSUMER CHOICE: EVIDENCE FROM COMMODITY PRICE SHOCKS*

PubMed Central

Hastings, Justine S.; Shapiro, Jesse M.

2015-01-01

We formulate a test of the fungibility of money based on parallel shifts in the prices of different quality grades of a commodity. We embed the test in a discrete-choice model of product quality choice and estimate the model using panel microdata on gasoline purchases. We find that when gasoline prices rise consumers substitute to lower octane gasoline, to an extent that cannot be explained by income effects. Across a wide range of specifications, we consistently reject the null hypothesis that households treat “gas money” as fungible with other income. We compare the empirical fit of three psychological models of decision-making. A simple model of category budgeting fits the data well, with models of loss aversion and salience both capturing important features of the time series. PMID:26937053

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

Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.

Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. We characterize the QCP by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. Here, we use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. Furthermore, by comparing with the calculations basedmore » on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.« less

Validation of single-fluid and two-fluid magnetohydrodynamic models of the helicity injected torus spheromak experiment with the NIMROD code

NASA Astrophysics Data System (ADS)

Akcay, Cihan; Kim, Charlson C.; Victor, Brian S.; Jarboe, Thomas R.

2013-08-01

We present a comparison study of 3-D pressureless resistive MHD (rMHD) and 3-D presureless two-fluid MHD models of the Helicity Injected Torus with Steady Inductive helicity injection (HIT-SI). HIT-SI is a current drive experiment that uses two geometrically asymmetric helicity injectors to generate and sustain toroidal plasmas. The comparable size of the collisionless ion skin depth di to the resistive skin depth predicates the importance of the Hall term for HIT-SI. The simulations are run with NIMROD, an initial-value, 3-D extended MHD code. The modeled plasma density and temperature are assumed uniform and constant. The helicity injectors are modeled as oscillating normal magnetic and parallel electric field boundary conditions. The simulations use parameters that closely match those of the experiment. The simulation output is compared to the formation time, plasma current, and internal and surface magnetic fields. Results of the study indicate 2fl-MHD shows quantitative agreement with the experiment while rMHD only captures the qualitative features. The validity of each model is assessed based on how accurately it reproduces the global quantities as well as the temporal and spatial dependence of the measured magnetic fields. 2fl-MHD produces the current amplification Itor/Iinj and formation time τf demonstrated by HIT-SI with similar internal magnetic fields. rMHD underestimates Itor/Iinj and exhibits much a longer τf. Biorthogonal decomposition (BD), a powerful mathematical tool for reducing large data sets, is employed to quantify how well the simulations reproduce the measured surface magnetic fields without resorting to a probe-by-probe comparison. BD shows that 2fl-MHD captures the dominant surface magnetic structures and the temporal behavior of these features better than rMHD.

The Geostationary Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Key, Richard; Sander, Stanley; Eldering, Annmarie; Miller, Charles; Frankenberg, Christian; Natra, Vijay; Rider, David; Blavier, Jean-Francois; Bekker, Dmitriy; Wu, Yen-Hung

2012-01-01

The Geostationary Fourier Transform Spectrometer (GeoFTS) is an imaging spectrometer designed for an earth science mission to measure key atmospheric trace gases and process tracers related to climate change and human activity. The GeoFTS instrument is a half meter cube size instrument designed to operate in geostationary orbit as a secondary "hosted" payload on a commercial geostationary satellite mission. The advantage of GEO is the ability to continuously stare at a region of the earth, enabling frequent sampling to capture the diurnal variability of biogenic fluxes and anthropogenic emissions from city to continental scales. The science goal is to obtain a process-based understanding of the carbon cycle from simultaneous high spatial resolution measurements of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and chlorophyll fluorescence (CF) many times per day in the near infrared spectral region to capture their spatial and temporal variations on diurnal, synoptic, seasonal and interannual time scales. The GeoFTS instrument is based on a Michelson interferometer design with a number of advanced features incorporated. Two of the most important advanced features are the focal plane arrays and the optical path difference mechanism. A breadboard GeoFTS instrument has demonstrated functionality for simultaneous measurements in the visible and IR in the laboratory and subsequently in the field at the California Laboratory for Atmospheric Remote Sensing (CLARS) observatory on Mt. Wilson overlooking the Los Angeles basin. A GeoFTS engineering model instrument is being developed which will make simultaneous visible and IR measurements under space flight like environmental conditions (thermal-vacuum at 180 K). This will demonstrate critical instrument capabilities such as optical alignment stability, interferometer modulation efficiency, and high throughput FPA signal processing. This will reduce flight instrument development risk and show that the GeoFTS design is mature and flight ready.

Assessing semantic similarity of texts - Methods and algorithms

NASA Astrophysics Data System (ADS)

Rozeva, Anna; Zerkova, Silvia

2017-12-01

Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining structured representative model of the documents in a corpus by means of extracting and selecting the features, characterizing their content. Generally the model is vector-based and enables further analysis with knowledge discovery approaches. Algorithms and measures are used for assessing texts at syntactical and semantic level. An important text-mining method and similarity measure is latent semantic analysis (LSA). It provides for reducing the dimensionality of the document vector space and better capturing the text semantics. The mathematical background of LSA for deriving the meaning of the words in a given text by exploring their co-occurrence is examined. The algorithm for obtaining the vector representation of words and their corresponding latent concepts in a reduced multidimensional space as well as similarity calculation are presented.

Imaging oxygen distribution in marine sediments. The importance of bioturbation and sediment heterogeneity.

PubMed

Pischedda, L; Poggiale, J C; Cuny, P; Gilbert, F

2008-06-01

The influence of sediment oxygen heterogeneity, due to bioturbation, on diffusive oxygen flux was investigated. Laboratory experiments were carried out with 3 macrobenthic species presenting different bioturbation behaviour patterns: the polychaetes Nereis diversicolor and Nereis virens, both constructing ventilated galleries in the sediment column, and the gastropod Cyclope neritea, a burrowing species which does not build any structure. Oxygen two-dimensional distribution in sediments was quantified by means of the optical planar optode technique. Diffusive oxygen fluxes (mean and integrated) and a variability index were calculated on the captured oxygen images. All species increased sediment oxygen heterogeneity compared to the controls without animals. This was particularly noticeable with the polychaetes because of the construction of more or less complex burrows. Integrated diffusive oxygen flux increased with oxygen heterogeneity due to the production of interface available for solute exchanges between overlying water and sediments. This work shows that sediment heterogeneity is an important feature of the control of oxygen exchanges at the sediment-water interface.

DSSPcont: continuous secondary structure assignments for proteins

PubMed Central

Carter, Phil; Andersen, Claus A. F.; Rost, Burkhard

2003-01-01

The DSSP program automatically assigns the secondary structure for each residue from the three-dimensional co-ordinates of a protein structure to one of eight states. However, discrete assignments are incomplete in that they cannot capture the continuum of thermal fluctuations. Therefore, DSSPcont (http://cubic.bioc.columbia.edu/services/DSSPcont) introduces a continuous assignment of secondary structure that replaces ‘static’ by ‘dynamic’ states. Technically, the continuum results from calculating weighted averages over 10 discrete DSSP assignments with different hydrogen bond thresholds. A DSSPcont assignment for a particular residue is a percentage likelihood of eight secondary structure states, derived from a weighted average of the ten DSSP assignments. The continuous assignments have two important features: (i) they reflect the structural variations due to thermal fluctuations as detected by NMR spectroscopy; and (ii) they reproduce the structural variation between many NMR models from one single model. Therefore, functionally important variation can be extracted from a single X-ray structure using the continuous assignment procedure. PMID:12824310

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

Couture, Aaron Joseph

This report documents aspects of direct and indirect neutron capture. The importance of neutron capture rates and methods to determine them are presented. The following conclusions are drawn: direct neutron capture measurements remain a backbone of experimental study; work is being done to take increased advantage of indirect methods for neutron capture; both instrumentation and facilities are making new measurements possible; more work is needed on the nuclear theory side to understand what is needed furthest from stability.

Consumer Views: Importance of Fuel Economy

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

Singer, Mark

This presentation includes data captured by the National Renewable Energy Laboratory (NREL) to support the U.S. Department of Energy's Vehicle Technologies Office (VTO) research efforts. The data capture consumer views on the importance of fuel economy amongst other vehicle attributes and views on which alternative fuel types would be the best and worst replacements for gasoline.

Using Tikhonov Regularization for Spatial Projections from CSR Regularized Spherical Harmonic GRACE Solutions

NASA Astrophysics Data System (ADS)

Save, H.; Bettadpur, S. V.

2013-12-01

It has been demonstrated before that using Tikhonov regularization produces spherical harmonic solutions from GRACE that have very little residual stripes while capturing all the signal observed by GRACE within the noise level. This paper demonstrates a two-step process and uses Tikhonov regularization to remove the residual stripes in the CSR regularized spherical harmonic coefficients when computing the spatial projections. We discuss methods to produce mass anomaly grids that have no stripe features while satisfying the necessary condition of capturing all observed signal within the GRACE noise level.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Tracking subtle stereotypes of children with trisomy 21: from facial-feature-based to implicit stereotyping.

PubMed

Enea-Drapeau, Claire; Carlier, Michèle; Huguet, Pascal

2012-01-01

Stigmatization is one of the greatest obstacles to the successful integration of people with Trisomy 21 (T21 or Down syndrome), the most frequent genetic disorder associated with intellectual disability. Research on attitudes and stereotypes toward these people still focuses on explicit measures subjected to social-desirability biases, and neglects how variability in facial stigmata influences attitudes and stereotyping. The participants were 165 adults including 55 young adult students, 55 non-student adults, and 55 professional caregivers working with intellectually disabled persons. They were faced with implicit association tests (IAT), a well-known technique whereby response latency is used to capture the relative strength with which some groups of people--here photographed faces of typically developing children and children with T21--are automatically (without conscious awareness) associated with positive versus negative attributes in memory. Each participant also rated the same photographed faces (consciously accessible evaluations). We provide the first evidence that the positive bias typically found in explicit judgments of children with T21 is smaller for those whose facial features are highly characteristic of this disorder, compared to their counterparts with less distinctive features and to typically developing children. We also show that this bias can coexist with negative evaluations at the implicit level (with large effect sizes), even among professional caregivers. These findings support recent models of feature-based stereotyping, and more importantly show how crucial it is to go beyond explicit evaluations to estimate the true extent of stigmatization of intellectually disabled people.

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Analysis of geometric moments as features for firearm identification.

PubMed

Md Ghani, Nor Azura; Liong, Choong-Yeun; Jemain, Abdul Aziz

2010-05-20

The task of identifying firearms from forensic ballistics specimens is exacting in crime investigation since the last two decades. Every firearm, regardless of its size, make and model, has its own unique 'fingerprint'. These fingerprints transfer when a firearm is fired to the fired bullet and cartridge case. The components that are involved in producing these unique characteristics are the firing chamber, breech face, firing pin, ejector, extractor and the rifling of the barrel. These unique characteristics are the critical features in identifying firearms. It allows investigators to decide on which particular firearm that has fired the bullet. Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. Therefore, the main objective of this study is the extraction and identification of suitable features from firing pin impression of cartridge case images for firearm recognition. Some previous studies have shown that firing pin impression of cartridge case is one of the most important characteristics used for identifying an individual firearm. In this study, data are gathered using 747 cartridge case images captured from five different pistols of type 9mm Parabellum Vektor SP1, made in South Africa. All the images of the cartridge cases are then segmented into three regions, forming three different set of images, i.e. firing pin impression image, centre of firing pin impression image and ring of firing pin impression image. Then geometric moments up to the sixth order were generated from each part of the images to form a set of numerical features. These 48 features were found to be significantly different using the MANOVA test. This high dimension of features is then reduced into only 11 significant features using correlation analysis. Classification results using cross-validation under discriminant analysis show that 96.7% of the images were classified correctly. These results demonstrate the value of geometric moments technique for producing a set of numerical features, based on which the identification of firearms are made.

An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM

NASA Astrophysics Data System (ADS)

Wang, Juan

2018-03-01

The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.

Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma

NASA Astrophysics Data System (ADS)

Beig, Niha; Patel, Jay; Prasanna, Prateek; Partovi, Sasan; Varadan, Vinay; Madabhushi, Anant; Tiwari, Pallavi

2017-03-01

Glioblastoma Multiforme (GBM) is a highly aggressive brain tumor with a median survival of 14 months. Hypoxia is a hallmark trait in GBM that is known to be associated with angiogenesis, tumor growth, and resistance to conventional therapy, thereby limiting treatment options for GBM patients. There is thus an urgent clinical need for non-invasively capturing tumor hypoxia in GBM towards identifying a subset of patients who would likely benefit from anti-angiogenic therapies (bevacizumab) in the adjuvant setting. In this study, we employed radiomic descriptors to (a) capture molecular variations of tumor hypoxia on routine MRI that are otherwise not appreciable; and (b) employ the radiomic correlates of hypoxia to discriminate patients with short-term survival (STS, overall survival (OS) < 7 months), mid-term survival (MTS) (7 months16 months). A total of 97 studies (25 STS, 36 MTS, 36 LTS) with Gadolinium T1-contrast (Gd-T1c), T2w, and FLAIR protocols with their corresponding gene expression profiles were obtained from the cancer genome atlas (TCGA) database. For each MRI study, necrotic, enhancing tumor, and edematous regions were segmented by an expert. A total of 30 radiomic descriptors (i.e. Haralick, Laws energy, Gabor) were extracted from every region across all three MRI protocols. By performing unsupervised clustering of the expression profile of hypoxia associated genes, a "low", "medium", or "high" index was defined for every study. Spearman correlation was then used to identify the most significantly correlated MRI features with the hypoxia index for every study. These features were further used to categorize each study as STS, MTS, and LTS using Kaplan-Meier (KM) analysis. Our results revealed that the most significant features (p < 0.05) were identified as Laws energy and Haralick features that capture image heterogeneity on FLAIR and Gd-T1w sequences. We also found these radiomic features to be significantly associated with survival, distinguishing MTS from LTS (p=.005) and STS from LTS (p=.0008).

A Digital Approach to Learning Petrology

NASA Astrophysics Data System (ADS)

Reid, M. R.

2011-12-01

In the undergraduate igneous and metamorphic petrology course at Northern Arizona University, we are employing petrographic microscopes equipped with relatively inexpensive ( $200) digital cameras that are linked to pen-tablet computers. The camera-tablet systems can assist student learning in a variety of ways. Images provided by the tablet computers can be used for helping students filter the visually complex specimens they examine. Instructors and students can simultaneously view the same petrographic features captured by the cameras and exchange information about them by pointing to salient features using the tablet pen. These images can become part of a virtual mineral/rock/texture portfolio tailored to individual student's needs. Captured digital illustrations can be annotated with digital ink or computer graphics tools; this activity emulates essential features of more traditional line drawings (visualizing an appropriate feature and selecting a representative image of it, internalizing the feature through studying and annotating it) while minimizing the frustration that many students feel about drawing. In these ways, we aim to help a student progress more efficiently from novice to expert. A number of our petrology laboratory exercises involve use of the camera-tablet systems for collaborative learning. Observational responsibilities are distributed among individual members of teams in order to increase interdependence and accountability, and to encourage efficiency. Annotated digital images are used to share students' findings and arrive at an understanding of an entire rock suite. This interdependence increases the individual's sense of responsibility for their work, and reporting out encourages students to practice use of technical vocabulary and to defend their observations. Pre- and post-course student interest in the camera-tablet systems has been assessed. In a post-course survey, the majority of students reported that, if available, they would use camera-tablet systems to capture microscope images (77%) and to make notes on images (71%). An informal focus group recommended introducing the cameras as soon as possible and having them available for making personal mineralogy/petrology portfolios. Because the stakes are perceived as high, use of the camera-tablet systems for peer-peer learning has been progressively modified to bolster student confidence in their collaborative efforts.

Capturing and modelling high-complex alluvial topography with UAS-borne laser scanning

NASA Astrophysics Data System (ADS)

Mandlburger, Gottfried; Wieser, Martin; Pfennigbauer, Martin

2015-04-01

Due to fluvial activity alluvial forests are zones of highest complexity and relief energy. Alluvial forests are dominated by new and pristine channels in consequence of current and historic flood events. Apart from topographic features, the vegetation structure is typically very complex featuring, both, dense under story as well as high trees. Furthermore, deadwood and debris carried from upstream during periods of high discharge within the river channel are deposited in these areas. Therefore, precise modelling of the micro relief of alluvial forests using standard tools like Airborne Laser Scanning (ALS) is hardly feasible. Terrestrial Laser Scanning (TLS), in turn, is very time consuming for capturing larger areas as many scan positions are necessary for obtaining complete coverage due to view occlusions in the forest. In the recent past, the technological development of Unmanned Arial Systems (UAS) has reached a level that light-weight survey-grade laser scanners can be operated from these platforms. For capturing alluvial topography this could bridge the gap between ALS and TLS in terms of providing a very detailed description of the topography and the vegetation structure due to the achievable very high point density of >100 points per m2. In our contribution we demonstrate the feasibility to apply UAS-borne laser scanning for capturing and modelling the complex topography of the study area Neubacher Au, an alluvial forest at the pre-alpine River Pielach (Lower Austria). The area was captured with Riegl's VUX-1 compact time-of-flight laser scanner mounted on a RiCopter (X-8 array octocopter). The scanner features an effective scan rate of 500 kHz and was flown in 50-100 m above ground. At this flying height the laser footprint is 25-50 mm allowing mapping of very small surface details. Furthermore, online waveform processing of the backscattered laser energy enables the retrieval of multiple targets for single laser shots resulting in a dense point cloud of, both, the ground surface and the alluvial vegetation. From the acquired point cloud the following products could be derived: (i) a very high resolution Digital Terrain Model (10 cm raster), (ii) a high resolution model of the water surface of the River Pielach (especially useful for validation of topo-bathymetry LiDAR data) and (iii) a detailed description of the complex vegetation structure.

A multimodal biometric authentication system based on 2D and 3D palmprint features

NASA Astrophysics Data System (ADS)

Aggithaya, Vivek K.; Zhang, David; Luo, Nan

2008-03-01

This paper presents a new personal authentication system that simultaneously exploits 2D and 3D palmprint features. Here, we aim to improve the accuracy and robustness of existing palmprint authentication systems using 3D palmprint features. The proposed system uses an active stereo technique, structured light, to capture 3D image or range data of the palm and a registered intensity image simultaneously. The surface curvature based method is employed to extract features from 3D palmprint and Gabor feature based competitive coding scheme is used for 2D representation. We individually analyze these representations and attempt to combine them with score level fusion technique. Our experiments on a database of 108 subjects achieve significant improvement in performance (Equal Error Rate) with the integration of 3D features as compared to the case when 2D palmprint features alone are employed.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

Analysis of pedestrian dynamics in counter flow via an extended lattice gas model.

PubMed

Kuang, Hua; Li, Xingli; Song, Tao; Dai, Shiqiang

2008-12-01

The modeling of human behavior is an important approach to reproduce realistic phenomena for pedestrian flow. In this paper, an extended lattice gas model is proposed to simulate pedestrian counter flow under the open boundary conditions by considering the human subconscious behavior and different maximum velocities. The simulation results show that the presented model can capture some essential features of pedestrian counter flows, such as lane formation, segregation effect, and phase separation at higher densities. In particular, an interesting feature that the faster walkers overtake the slower ones and then form a narrow-sparse walkway near the central partition line is discovered. The phase diagram comparison and analysis show that the subconscious behavior plays a key role in reducing the occurrence of jam cluster. The effects of the symmetrical and asymmetrical injection rate, different partition lines, and different combinations of maximum velocities on pedestrian flow are investigated. An important conclusion is that it is needless to separate faster and slower pedestrians in the same direction by a partition line. Furthermore, the increase of the number of faster walkers does not always benefit the counter flow in all situations. It depends on the magnitude and asymmetry of injection rate. And at larger maximum velocity, the obtained critical transition point corresponding to the maximum flow rate of the fundamental diagram is in good agreement with the empirical results.

Experimental and Theoretical Understanding of Neutron Capture on Uranium Isotopes

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

Ullmann, John Leonard

2017-09-21

Neutron capture cross sections on uranium isotopes are important quantities needed to model nuclear explosion performance, nuclear reactor design, nuclear test diagnostics, and nuclear forensics. It has been difficult to calculate capture accurately, and factors of 2 or more be- tween calculation and measurements are not uncommon, although normalization to measurements of the average capture width and nuclear level density can improve the result. The calculations of capture for 233,235,237,239U are further complicated by the need to accurately include the fission channel.

Multi-channel feature dictionaries for RGB-D object recognition

NASA Astrophysics Data System (ADS)

Lan, Xiaodong; Li, Qiming; Chong, Mina; Song, Jian; Li, Jun

2018-04-01

Hierarchical matching pursuit (HMP) is a popular feature learning method for RGB-D object recognition. However, the feature representation with only one dictionary for RGB channels in HMP does not capture sufficient visual information. In this paper, we propose multi-channel feature dictionaries based feature learning method for RGB-D object recognition. The process of feature extraction in the proposed method consists of two layers. The K-SVD algorithm is used to learn dictionaries in sparse coding of these two layers. In the first-layer, we obtain features by performing max pooling on sparse codes of pixels in a cell. And the obtained features of cells in a patch are concatenated to generate patch jointly features. Then, patch jointly features in the first-layer are used to learn the dictionary and sparse codes in the second-layer. Finally, spatial pyramid pooling can be applied to the patch jointly features of any layer to generate the final object features in our method. Experimental results show that our method with first or second-layer features can obtain a comparable or better performance than some published state-of-the-art methods.

Extracting material response from simple mechanical tests on hardening-softening-hardening viscoplastic solids

NASA Astrophysics Data System (ADS)

Mohan, Nisha

Compliant foams are usually characterized by a wide range of desirable mechanical properties. These properties include viscoelasticity at different temperatures, energy absorption, recoverability under cyclic loading, impact resistance, and thermal, electrical, acoustic and radiation-resistance. Some foams contain nano-sized features and are used in small-scale devices. This implies that the characteristic dimensions of foams span multiple length scales, rendering modeling their mechanical properties difficult. Continuum mechanics-based models capture some salient experimental features like the linear elastic regime, followed by non-linear plateau stress regime. However, they lack mesostructural physical details. This makes them incapable of accurately predicting local peaks in stress and strain distributions, which significantly affect the deformation paths. Atomistic methods are capable of capturing the physical origins of deformation at smaller scales, but suffer from impractical computational intensity. Capturing deformation at the so-called meso-scale, which is capable of describing the phenomenon at a continuum level, but with some physical insights, requires developing new theoretical approaches. A fundamental question that motivates the modeling of foams is `how to extract the intrinsic material response from simple mechanical test data, such as stress vs. strain response?' A 3D model was developed to simulate the mechanical response of foam-type materials. The novelty of this model includes unique features such as the hardening-softening-hardening material response, strain rate-dependence, and plastically compressible solids with plastic non-normality. Suggestive links from atomistic simulations of foams were borrowed to formulate a physically informed hardening material input function. Motivated by a model that qualitatively captured the response of foam-type vertically aligned carbon nanotube (VACNT) pillars under uniaxial compression [2011,"Analysis of Uniaxial Compression of Vertically Aligned Carbon Nanotubes," J. Mech.Phys. Solids, 59, pp. 2227--2237, Erratum 60, 1753-1756 (2012)], the property space exploration was advanced to three types of simple mechanical tests: 1) uniaxial compression, 2) uniaxial tension, and 3) nanoindentation with a conical and a flat-punch tip. The simulations attempt to explain some of the salient features in experimental data, like 1) The initial linear elastic response. 2) One or more nonlinear instabilities, yielding, and hardening. The model-inherent relationships between the material properties and the overall stress-strain behavior were validated against the available experimental data. The material properties include the gradient in stiffness along the height, plastic and elastic compressibility, and hardening. Each of these tests was evaluated in terms of their efficiency in extracting material properties. The uniaxial simulation results proved to be a combination of structural and material influences. Out of all deformation paths, flat-punch indentation proved to be superior since it is the most sensitive in capturing the material properties.

Next-generation sequencing strategies enable routine detection of balanced chromosome rearrangements for clinical diagnostics and genetic research.

PubMed

Talkowski, Michael E; Ernst, Carl; Heilbut, Adrian; Chiang, Colby; Hanscom, Carrie; Lindgren, Amelia; Kirby, Andrew; Liu, Shangtao; Muddukrishna, Bhavana; Ohsumi, Toshiro K; Shen, Yiping; Borowsky, Mark; Daly, Mark J; Morton, Cynthia C; Gusella, James F

2011-04-08

The contribution of balanced chromosomal rearrangements to complex disorders remains unclear because they are not detected routinely by genome-wide microarrays and clinical localization is imprecise. Failure to consider these events bypasses a potentially powerful complement to single nucleotide polymorphism and copy-number association approaches to complex disorders, where much of the heritability remains unexplained. To capitalize on this genetic resource, we have applied optimized sequencing and analysis strategies to test whether these potentially high-impact variants can be mapped at reasonable cost and throughput. By using a whole-genome multiplexing strategy, rearrangement breakpoints could be delineated at a fraction of the cost of standard sequencing. For rearrangements already mapped regionally by karyotyping and fluorescence in situ hybridization, a targeted approach enabled capture and sequencing of multiple breakpoints simultaneously. Importantly, this strategy permitted capture and unique alignment of up to 97% of repeat-masked sequences in the targeted regions. Genome-wide analyses estimate that only 3.7% of bases should be routinely omitted from genomic DNA capture experiments. Illustrating the power of these approaches, the rearrangement breakpoints were rapidly defined to base pair resolution and revealed unexpected sequence complexity, such as co-occurrence of inversion and translocation as an underlying feature of karyotypically balanced alterations. These findings have implications ranging from genome annotation to de novo assemblies and could enable sequencing screens for structural variations at a cost comparable to that of microarrays in standard clinical practice. Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Protein (multi-)location prediction: utilizing interdependencies via a generative model

PubMed Central

Shatkay, Hagit

2015-01-01

Motivation: Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein’s function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. Results: We introduce a probabilistic generative model for protein localization, and develop a system based on it—which we call MDLoc—that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. Availability and implementation: MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. Contact: shatkay@udel.edu. PMID:26072505

Protein (multi-)location prediction: utilizing interdependencies via a generative model.

PubMed

Simha, Ramanuja; Briesemeister, Sebastian; Kohlbacher, Oliver; Shatkay, Hagit

2015-06-15

Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein's function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. We introduce a probabilistic generative model for protein localization, and develop a system based on it-which we call MDLoc-that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. © The Author 2015. Published by Oxford University Press.

Spectroscopic Analyses of Neutron Capture Elements in Open Clusters

NASA Astrophysics Data System (ADS)

O'Connell, Julia E.

The evolution of elements as a function or age throughout the Milky Way disk provides strong constraints for galaxy evolution models, and on star formation epochs. In an effort to provide such constraints, we conducted an investigation into r- and s-process elemental abundances for a large sample of open clusters as part of an optical follow-up to the SDSS-III/APOGEE-1 near infrared survey. To obtain data for neutron capture abundance analysis, we conducted a long-term observing campaign spanning three years (2013-2016) using the McDonald Observatory Otto Struve 2.1-meter telescope and Sandiford Cass Echelle Spectrograph (SES, R(lambda/Deltalambda) ˜60,000). The SES provides a wavelength range of ˜1400 A, making it uniquely suited to investigate a number of other important chemical abundances as well as the neutron capture elements. For this study, we derive abundances for 18 elements covering four nucleosynthetic families- light, iron-peak, neutron capture and alpha-elements- for ˜30 open clusters within 6 kpc of the Sun with ages ranging from ˜80 Myr to ˜10 Gyr. Both equivalent width (EW) measurements and spectral synthesis methods were employed to derive abundances for all elements. Initial estimates for model stellar atmospheres- effective temperature and surface gravity- were provided by the APOGEE data set, and then re-derived for our optical spectra by removing abundance trends as a function of excitation potential and reduced width log(EW/lambda). With the exception of Ba II and Zr I, abundance analyses for all neutron capture elements were performed by generating synthetic spectra from the new stellar parameters. In order to remove molecular contamination, or blending from nearby atomic features, the synthetic spectra were modeled by a best-fit Gaussian to the observed data. Nd II shows a slight enhancement in all cluster stars, while other neutron capture elements follow solar abundance trends. Ba II shows a large cluster-to-cluster abundance spread, consistent with other open cluster abundance studies. From log(Age) ˜8.5, this large spread as a function of age appears to replicate the findings from an earlier, much debated study by Orazi et al. (2009) which found a linear trend of decreasing barium abundance with increasing age.

A Learning Theory Conceptual Foundation for Using Capture Technology in Teaching

ERIC Educational Resources Information Center

Berardi, Victor; Blundell, Greg

2014-01-01

Lecture capture technologies are increasingly being used by instructors, programs, and institutions to deliver online lectures and courses. This lecture capture movement is important as it increases access to education opportunities that were not possible before, it can improve efficiency, and it can increase student engagement. However, this is…

Atomic force microscopy of orb-spider-web-silks to measure surface nanostructuring and evaluate silk fibers per strand

NASA Astrophysics Data System (ADS)

Kane, D. M.; Naidoo, N.; Staib, G. R.

2010-10-01

Atomic force microscopy (AFM) study is used to measure the surface topology and roughness of radial and capture spider silks on the micro- and nanoscale. This is done for silks of the orb weaver spider Argiope keyserlingi. Capture silk has a surface roughness that is five times less than that for radial silk. The capture silk has an equivalent flatness of λ /100 (5-6 nm deep surface features) as an optical surface. This is equivalent to a very highly polished optical surface. AFM does show the number of silk fibers that make up a silk thread but geometric distortion occurs during sample preparation. This prevented AFM from accurately measuring the silk topology on the microscale in this study.

Online phase measuring profilometry for rectilinear moving object by image correction

NASA Astrophysics Data System (ADS)

Yuan, Han; Cao, Yi-Ping; Chen, Chen; Wang, Ya-Pin

2015-11-01

In phase measuring profilometry (PMP), the object must be static for point-to-point reconstruction with the captured deformed patterns. While the object is rectilinearly moving online, the size and pixel position differences of the object in different captured deformed patterns do not meet the point-to-point requirement. We propose an online PMP based on image correction to measure the three-dimensional shape of the rectilinear moving object. In the proposed method, the deformed patterns captured by a charge-coupled diode camera are reprojected from the oblique view to an aerial view first and then translated based on the feature points of the object. This method makes the object appear stationary in the deformed patterns. Experimental results show the feasibility and efficiency of the proposed method.

Laser capture microdissection: Arcturus(XT) infrared capture and UV cutting methods.

PubMed

Gallagher, Rosa I; Blakely, Steven R; Liotta, Lance A; Espina, Virginia

2012-01-01

Laser capture microdissection (LCM) is a technique that allows the precise procurement of enriched cell populations from a heterogeneous tissue under direct microscopic visualization. LCM can be used to harvest the cells of interest directly or can be used to isolate specific cells by ablating the unwanted cells, resulting in histologically enriched cell populations. The fundamental components of laser microdissection technology are (a) visualization of the cells of interest via microscopy, (b) transfer of laser energy to a thermolabile polymer with either the formation of a polymer-cell composite (capture method) or transfer of laser energy via an ultraviolet laser to photovolatize a region of tissue (cutting method), and (c) removal of cells of interest from the heterogeneous tissue section. Laser energy supplied by LCM instruments can be infrared (810 nm) or ultraviolet (355 nm). Infrared lasers melt thermolabile polymers for cell capture, whereas ultraviolet lasers ablate cells for either removal of unwanted cells or excision of a defined area of cells. LCM technology is applicable to an array of applications including mass spectrometry, DNA genotyping and loss-of-heterozygosity analysis, RNA transcript profiling, cDNA library generation, proteomics discovery, and signal kinase pathway profiling. This chapter describes the unique features of the Arcturus(XT) laser capture microdissection instrument, which incorporates both infrared capture and ultraviolet cutting technology in one instrument, using a proteomic downstream assay as a model.

Neural representations of emotion are organized around abstract event features.

PubMed

Skerry, Amy E; Saxe, Rebecca

2015-08-03

Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural Representations of Emotion Are Organized around Abstract Event Features

PubMed Central

Skerry, Amy E.; Saxe, Rebecca

2016-01-01

Summary Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. PMID:26212878

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.

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

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.

Jovian 'Twilight Zone'

NASA Image and Video Library

2018-03-01

This image captures the swirling cloud formations around the south pole of Jupiter, looking up toward the equatorial region. NASA's Juno spacecraft took the color-enhanced image during its eleventh close flyby of the gas giant planet on Feb. 7 at 7:11 a.m. PST (10:11 a.m. EST). At the time, the spacecraft was 74,896 miles (120,533 kilometers) from the tops of Jupiter's clouds at 84.9 degrees south latitude. Citizen scientist Gerald Gerald Eichstädt processed this image using data from the JunoCam imager. This image was created by reprocessing raw JunoCam data using trajectory and pointing data from the spacecraft. This image is one in a series of images taken in an experiment to capture the best results for illuminated parts of Jupiter's polar region. To make features more visible in Jupiter's terminator -- the region where day meets night -- the Juno team adjusted JunoCam so that it would perform like a portrait photographer taking multiple photos at different exposures, hoping to capture one image with the intended light balance. For JunoCam to collect enough light to reveal features in Jupiter's dark twilight zone, the much brighter illuminated day-side of Jupiter becomes overexposed with the higher exposure. https://photojournal.jpl.nasa.gov/catalog/PIA21980

The mechanism of vapor phase hydration of calcium oxide: implications for CO2 capture.

PubMed

Kudłacz, Krzysztof; Rodriguez-Navarro, Carlos

2014-10-21

Lime-based sorbents are used for fuel- and flue-gas capture, thereby representing an economic and effective way to reduce CO2 emissions. Their use involves cyclic carbonation/calcination which results in a significant conversion reduction with increasing number of cycles. To reactivate spent CaO, vapor phase hydration is typically performed. However, little is known about the ultimate mechanism of such a hydration process. Here, we show that the vapor phase hydration of CaO formed after calcination of calcite (CaCO3) single crystals is a pseudomorphic, topotactic process, which progresses via an intermediate disordered phase prior to the final formation of oriented Ca(OH)2 nanocrystals. The strong structural control during this solid-state phase transition implies that the microstructural features of the CaO parent phase predetermine the final structural and physicochemical (reactivity and attrition) features of the product hydroxide. The higher molar volume of the product can create an impervious shell around unreacted CaO, thereby limiting the efficiency of the reactivation process. However, in the case of compact, sintered CaO structures, volume expansion cannot be accommodated in the reduced pore volume, and stress generation leads to pervasive cracking. This favors complete hydration but also detrimental attrition. Implications of these results in carbon capture and storage (CCS) are discussed.

Suitability of digital camcorders for virtual reality image data capture

NASA Astrophysics Data System (ADS)

D'Apuzzo, Nicola; Maas, Hans-Gerd

1998-12-01

Today's consumer market digital camcorders offer features which make them appear quite interesting devices for virtual reality data capture. The paper compares a digital camcorder with an analogue camcorder and a machine vision type CCD camera and discusses the suitability of these three cameras for virtual reality applications. Besides the discussion of technical features of the cameras, this includes a detailed accuracy test in order to define the range of applications. In combination with the cameras, three different framegrabbers are tested. The geometric accuracy potential of all three cameras turned out to be surprisingly large, and no problems were noticed in the radiometric performance. On the other hand, some disadvantages have to be reported: from the photogrammetrists point of view, the major disadvantage of most camcorders is the missing possibility to synchronize multiple devices, limiting the suitability for 3-D motion data capture. Moreover, the standard video format contains interlacing, which is also undesirable for all applications dealing with moving objects or moving cameras. Further disadvantages are computer interfaces with functionality, which is still suboptimal. While custom-made solutions to these problems are probably rather expensive (and will make potential users turn back to machine vision like equipment), this functionality could probably be included by the manufacturers at almost zero cost.

Design Rules and Analysis of a Capture Mechanism for Rendezvous between a Space Tether and Payload

NASA Technical Reports Server (NTRS)

Sorensen, Kirk F.; Canfield, Stephen L.; Norris, Marshall A.

2006-01-01

Momentum-exchange/electrodynamic reboost (MXER) tether systems have been proposed to serve as an "upper stage in space". A MXER tether station would boost spacecraft from low Earth orbit to a high-energy orbit quickly, like a high-thrust rocket. Then, it would slowly rebuild its orbital momentum through electrodynamic thrust, minimizing the use of propellant. One of the primary challenges in developing a momentum-exchange/electrodynamic reboost tether system as identified by the 2003 MXER Technology Assessment Group is in the development of a mechanism that will enable the processes of capture, carry and release of a payload by the rotating tether as required by the MXER tether approach. This paper will present a concept that will achieve the desired goals of the capture system. This solution is presented as a multi-DOF (degree-of-freedom) capture mechanism with nearly passive operation that features matching of the capture space and expected window of capture error, efficient use of mass and nearly passive actuation during the capture process. This paper will describe the proposed capture mechanism concept and provide an evaluation of the concept through a dynamic model and experimental tests performed on a prototype article of the mechanism in a dynamically similar environment. This paper will also develop a set of rules to guide the design of such a capture mechanism based on analytical and experimental analyses. The primary contributions of this paper will be a description of the proposed capture mechanism concept, a collection of rules to guide its design, and empirical and model information that can be used to evaluate the capability of the concept